WO2024100725A1 - Terminal, wireless communication method, and base station - Google Patents
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Definitions
- This disclosure relates to terminals, wireless communication methods, and base stations in next-generation mobile communication systems.
- LTE Long Term Evolution
- UMTS Universal Mobile Telecommunications System
- Non-Patent Document 1 LTE-Advanced (3GPP Rel. 10-14) was specified for the purpose of achieving higher capacity and greater sophistication over LTE (Third Generation Partnership Project (3GPP (registered trademark)) Release (Rel.) 8, 9).
- LTE 5th generation mobile communication system
- 5G+ 5th generation mobile communication system
- 6G 6th generation mobile communication system
- NR New Radio
- E-UTRA Evolved Universal Terrestrial Radio Access
- E-UTRAN Evolved Universal Terrestrial Radio Access Network
- AI artificial intelligence
- ML machine learning
- Beam reporting Beam reporting
- BM AI-based beam management
- Temporal DL beam prediction may be called, for example, time domain Channel State Information (CSI) prediction.
- CSI Channel State Information
- one of the objectives of this disclosure is to provide a terminal, a wireless communication method, and a base station that can achieve optimal overhead reduction/channel estimation/resource utilization.
- a terminal has a control unit that generates a beam report that does not include non-probabilistic measurement or prediction results regarding reception power or reception quality, and a transmission unit that transmits the beam report.
- FIG. 1 is a diagram illustrating an example of a framework for managing AI models.
- 2A and 2B are diagrams illustrating an example of AI-based beam prediction.
- FIG. 3 is a diagram illustrating an example of a time instance/duration relationship.
- 4A and 4B are diagrams illustrating an example of a report instance that does not include an L1-RSRP in the third embodiment.
- 5A and 5B are diagrams illustrating an example of a report instance that does not include L1-RSRP in the third embodiment.
- 6A and 6B are diagrams illustrating an example of a report instance in the fourth embodiment.
- FIG. 7 is a diagram showing an example of beam prediction according to embodiment 5-1.
- FIG. 8 is a diagram showing an example of RRC parameters related to option 5-2-1.
- FIG. 9 is a diagram showing an example of RRC parameters related to option 6-1-1.
- FIG. 10 is a diagram illustrating an example of a schematic configuration of a wireless communication system according to an embodiment.
- FIG. 11 is a diagram illustrating an example of the configuration of a base station according to an embodiment.
- FIG. 12 is a diagram illustrating an example of the configuration of a user terminal according to an embodiment.
- FIG. 13 is a diagram illustrating an example of the hardware configuration of a base station and a user terminal according to an embodiment.
- FIG. 14 is a diagram illustrating an example of a vehicle according to an embodiment.
- AI Artificial Intelligence
- ML machine learning
- CSI channel state information
- UE user equipment
- BS base stations
- CSI channel state information
- UE user equipment
- beam management e.g., improving accuracy, prediction in the time/space domain
- position measurement e.g., improving position estimation/prediction
- the AI model may output at least one piece of information such as an estimate, a prediction, a selected action, a classification, etc. based on the input information.
- the UE/BS may input channel state information, reference signal measurements, etc. to the AI model, and output highly accurate channel state information/measurements/beam selection/position, future channel state information/radio link quality, etc.
- AI may be interpreted as an object (also called a target, object, data, function, program, etc.) having (implementing) at least one of the following characteristics: - Estimation based on observed or collected information; - making choices based on observed or collected information; - Predictions based on observed or collected information.
- estimation, prediction, and inference may be interpreted as interchangeable. Also, in this disclosure, estimate, predict, and infer may be interpreted as interchangeable.
- an object may be, for example, an apparatus such as a UE or a BS, or a device. Also, in the present disclosure, an object may correspond to a program/model/entity that operates in the apparatus.
- an AI model may be interpreted as an object having (implementing) at least one of the following characteristics: - Producing estimates by feeding information, - Predicting estimates by providing information - Discover features by providing information, - Select an action by providing information.
- an AI model may refer to a data-driven algorithm that applies AI techniques to generate a set of outputs based on a set of inputs.
- AI model, model, ML model, predictive analytics, predictive analysis model, tool, autoencoder, encoder, decoder, neural network model, AI algorithm, scheme, etc. may be interchangeable.
- AI model may be derived using at least one of regression analysis (e.g., linear regression analysis, multiple regression analysis, logistic regression analysis), support vector machine, random forest, neural network, deep learning, etc.
- autoencoder may be interchangeably referred to as any autoencoder, such as a stacked autoencoder or a convolutional autoencoder.
- the encoder/decoder of this disclosure may employ models such as Residual Network (ResNet), DenseNet, and RefineNet.
- encoder encoding, encoding/encoded, modification/alteration/control by an encoder, compressing, compress/compressed, generating, generate/generated, etc. may be read as interchangeable terms.
- decoder decoding, decode/decoded, modification/alteration/control by a decoder, decompressing, decompress/decompressed, reconstructing, reconstruct/reconstructed, etc.
- decompressing decompress/decompressed, reconstructing, reconstruct/reconstructed, etc.
- a layer for an AI model
- a layer may be interpreted as a layer (input layer, intermediate layer, etc.) used in an AI model.
- a layer in the present disclosure may correspond to at least one of an input layer, intermediate layer, output layer, batch normalization layer, convolution layer, activation layer, dense layer, normalization layer, pooling layer, attention layer, dropout layer, fully connected layer, etc.
- methods for training an AI model may include supervised learning, unsupervised learning, reinforcement learning, federated learning, and the like.
- Supervised learning may refer to the process of training a model from inputs and corresponding labels.
- Unsupervised learning may refer to the process of training a model without labeled data.
- Reinforcement learning may refer to the process of training a model from inputs (i.e., states) and feedback signals (i.e., rewards) resulting from the model's outputs (i.e., actions) in the environment with which the model interacts.
- terms such as generate, calculate, derive, etc. may be interchangeable.
- terms such as implement, operate, operate, execute, etc. may be interchangeable.
- terms such as train, learn, update, retrain, etc. may be interchangeable.
- terms such as infer, after-training, live use, actual use, etc. may be interchangeable.
- terms such as signal and signal/channel may be interchangeable.
- Figure 1 shows an example of a framework for managing an AI model.
- each stage related to the AI model is shown as a block.
- This example is also expressed as life cycle management of an AI model.
- the data collection stage corresponds to the stage of collecting data for generating/updating an AI model.
- the data collection stage may include data organization (e.g., determining which data to transfer for model training/model inference), data transfer (e.g., transferring data to an entity (e.g., UE, gNB) that performs model training/model inference), etc.
- data collection may refer to a process in which data is collected by a network node, management entity, or UE for the purpose of AI model training/data analysis/inference.
- process and procedure may be interpreted as interchangeable.
- collection may also refer to obtaining a data set (e.g., usable as input/output) for training/inference of an AI model based on measurements (channel measurements, beam measurements, radio link quality measurements, position estimation, etc.).
- offline field data may be data collected from the field (real world) and used for offline training of an AI model.
- online field data may be data collected from the field (real world) and used for online training of an AI model.
- model training is performed based on the data (training data) transferred from the collection stage.
- This stage may include data preparation (e.g., performing data preprocessing, cleaning, formatting, conversion, etc.), model training/validation, model testing (e.g., checking whether the trained model meets performance thresholds), model exchange (e.g., transferring the model for distributed learning), model deployment/update (deploying/updating the model to the entities that will perform model inference), etc.
- AI model training may refer to a process for training an AI model in a data-driven manner and obtaining a trained AI model for inference.
- AI model validation may refer to a sub-process of training to evaluate the quality of an AI model using a dataset different from the dataset used to train the model. This sub-process helps select model parameters that generalize beyond the dataset used to train the model.
- AI model testing may refer to a sub-process of training to evaluate the performance of the final AI model using a dataset different from the dataset used for model training/validation. Note that testing, unlike validation, does not necessarily require subsequent model tuning.
- model inference is performed based on the data (inference data) transferred from the collection stage.
- This stage may include data preparation (e.g., performing data preprocessing, cleaning, formatting, transformation, etc.), model inference, model monitoring (e.g., monitoring the performance of model inference), model performance feedback (feeding back model performance to the entity performing the model training), and output (providing model output to the actor).
- AI model inference may refer to the process of using a trained AI model to produce a set of outputs from a set of inputs.
- a UE side model may refer to an AI model whose inference is performed entirely in the UE.
- a network side model may refer to an AI model whose inference is performed entirely in the network (e.g., gNB).
- a one-sided model may refer to a UE-side model or a network-side model.
- a two-sided model may refer to a pair of AI models where joint inference is performed.
- joint inference may include AI inference where the inference is performed jointly across the UE and the network, e.g., a first part of the inference may be performed first by the UE and the remaining part by the gNB (or vice versa).
- AI model monitoring may refer to the process of monitoring the inference performance of an AI model, and may be interchangeably read as model performance monitoring, performance monitoring, etc.
- model registration may refer to making a model executable (registering) through assigning a version identifier to the model and compiling it into the specific hardware used in the inference phase.
- Model deployment may refer to distributing (or activating at) a fully developed and tested run-time image (or an image of the execution environment) of the model to the target (e.g., UE/gNB) where inference will be performed.
- Actor stages may include action triggers (e.g., deciding whether to trigger an action on another entity), feedback (e.g., feeding back information needed for training data/inference data/performance feedback), etc.
- action triggers e.g., deciding whether to trigger an action on another entity
- feedback e.g., feeding back information needed for training data/inference data/performance feedback
- training of a model for mobility optimization may be performed in, for example, Operation, Administration and Maintenance (Management) (OAM) in a network (NW)/gNodeB (gNB).
- OAM Operation, Administration and Maintenance
- NW network
- gNodeB gNodeB
- In the former case interoperability, large capacity storage, operator manageability, and model flexibility (feature engineering, etc.) are advantageous.
- the latency of model updates and the absence of data exchange for model deployment are advantageous.
- Inference of the above model may be performed in, for example, a gNB.
- the entity performing the training/inference may be different.
- the function of the AI model may include beam management, beam prediction, autoencoder (or information compression), CSI feedback, positioning, etc.
- the OAM/gNB may perform model training and the gNB may perform model inference.
- a Location Management Function may perform model training and the LMF may perform model inference.
- the OAM/gNB/UE may perform model training and the gNB/UE may perform model inference (jointly).
- the OAM/gNB/UE may perform model training and the UE may perform model inference.
- model activation may mean activating an AI model for a particular function.
- Model deactivation may mean disabling an AI model for a particular function.
- Model switching may mean deactivating a currently active AI model for a particular function and activating a different AI model.
- Model transfer may also refer to distributing an AI model over the air interface. This may include distributing either or both of the parameters of the model structure already known at the receiving end, or a new model with the parameters. This may also include a complete model or a partial model.
- Model download may refer to model transfer from the network to the UE.
- Model upload may refer to model transfer from the UE to the network.
- AI-based beam prediction As a use case of utilizing the AI model, spatial domain downlink (DL) beam prediction or temporal DL beam prediction using a one-sided AI model in the UE or NW is being considered.
- DL spatial domain downlink
- BM Beam Management
- FIG. 2A and 2B are diagrams showing an example of AI-based beam prediction.
- FIG. 2A shows spatial domain DL beam prediction.
- the UE may measure a spatially sparse (or thick) beam, input the measurement results, etc., to an AI model, and output a predicted result of the beam quality of a spatially dense (or thin) beam.
- Figure 2B shows temporal DL beam prediction.
- the UE may measure the time series of beams, input the measurement results, etc. into an AI model, and output the predicted beam quality of the future beam.
- spatial domain DL beam prediction may be referred to as BM case 1
- temporal DL beam prediction may be referred to as BM case 2.
- temporal DL beam prediction may be referred to as, for example, time domain CSI prediction.
- the beams associated with the output (prediction result) of the AI model may be referred to as set of beams A.
- the beams associated with the input of the AI model may be referred to as set of beams B.
- set A may correspond to beams selected from the predicted beams.
- Resources for set A may be referred to as resources for beam prediction, resources for beam reporting, resources included in a CSI report, set A, resources of set A, second (or first) set, second (or first) resources, etc.
- set B may correspond to a beam whose measurement results are used as input (for the AI model/function for prediction).
- Resources for set B may be referred to as resources for beam measurements, resources for beam prediction input, set B, resources of set B, first (or second) set, resources of first (or second) set, etc.
- Candidates for input to the AI model for BM Case 1/2 include L1-RSRP (Layer 1 Reference Signal Received Power), assistance information (e.g., beam shape information, UE position/direction information, transmit beam usage information), Channel Impulse Response (CIR) information, and corresponding DL transmit/receive beam IDs.
- L1-RSRP Layer 1 Reference Signal Received Power
- assistance information e.g., beam shape information, UE position/direction information, transmit beam usage information
- CIR Channel Impulse Response
- Possible outputs of the AI model for BM Case 1 include the IDs of the top K (K is an integer) transmit/receive beams, the predicted L1-RSRP of these beams, the probability that each beam is in the top K, and the angles of these beams.
- the candidates for the output of the AI model in BM Case 2 include predicted beam failures.
- the UE generates (also called determining, calculating, estimating, measuring, etc.) CSI based on a reference signal (RS) (or a resource for the RS) and transmits (also called reporting, feedback, etc.) the generated CSI to a network (e.g., a base station).
- RS reference signal
- the CSI may be transmitted to the base station using, for example, an uplink control channel (e.g., a Physical Uplink Control Channel (PUCCH)) or an uplink shared channel (e.g., a Physical Uplink Shared Channel (PUSCH)).
- PUCCH Physical Uplink Control Channel
- PUSCH Physical Uplink Shared Channel
- CSI includes a Channel Quality Indicator (CQI), a Precoding Matrix Indicator (PMI), a CSI-RS Resource Indicator (CRI), a SS/PBCH Block Resource Indicator (SSBRI), a Layer Indicator (LI), a Rank Indicator (RI), and a Layer 1 Reference Signal Received Power (L1-RSRP).
- CQI Channel Quality Indicator
- PMI Precoding Matrix Indicator
- CRI CSI-RS Resource Indicator
- SSBRI SS/PBCH Block Resource Indicator
- LI Layer Indicator
- RI Rank Indicator
- L1-RSRP Layer 1 Reference Signal Received Power
- L1-Reference Signal Received Power L1-RSRQ
- L1-SINR Signal to Interference plus Noise Ratio
- L1-SNR Signal to Noise Ratio
- information on the channel matrix or channel coefficients
- information on the precoding matrix or precoding coefficients
- information on the beam/Transmission Configuration Indication state TCI state/spatial relation, etc.
- the RS used to generate the CSI may be, for example, at least one of a Channel State Information Reference Signal (CSI-RS), a Synchronization Signal/Physical Broadcast Channel (SS/PBCH) block, a Synchronization Signal (SS), and a DeModulation Reference Signal (DMRS).
- CSI-RS Channel State Information Reference Signal
- SS/PBCH Synchronization Signal/Physical Broadcast Channel
- SS Synchronization Signal
- DMRS DeModulation Reference Signal
- RS Non Zero Power (NZP) CSI-RS, Zero Power (ZP) CSI-RS, CSI Interference Measurement (CSI-IM), CSI-SSB, and SSB
- NZP Non Zero Power
- ZP Zero Power
- CSI-IM CSI Interference Measurement
- CSI-SSB CSI Interference Measurement
- SSB SSB
- CSI-RS may include other reference signals.
- the UE may receive configuration information regarding CSI reporting (which may be referred to as CSI report configuration, report setting, etc.) and control CSI reporting based on the configuration information.
- the report configuration information may be, for example, a Radio Resource Control (RRC) Information Element (IE) "CSI-ReportConfig.”
- RRC Radio Resource Control
- IE Radio Resource Control Information Element
- the CSI reporting configuration may include at least one of the following information: Information regarding the CSI resources used for CSI measurements (resource configuration ID, for example, "CSI-ResourceConfigId”); Information regarding one or more quantities (CSI parameters) of CSI to be reported (report quantity information, e.g., "reportQuantity”); Report type information (eg, "reportConfigType”) indicating the time domain behavior of the reporting configuration.
- resource configuration ID for example, "CSI-ResourceConfigId”
- Information regarding one or more quantities (CSI parameters) of CSI to be reported (report quantity information, e.g., "reportQuantity”
- Report type information eg, "reportConfigType" indicating the time domain behavior of the reporting configuration.
- a CSI resource may be interchangeably referred to as a time instance, a CSI-RS opportunity/CSI-IM opportunity/SSB opportunity, a CSI-RS resource (one/multiple) opportunity, a CSI opportunity, an opportunity, a CSI-RS resource/CSI-IM resource/SSB resource, a time resource, a frequency resource, an antenna port (e.g., a CSI-RS port), etc.
- the time unit of a CSI resource may be a slot, a symbol, etc.
- the information on the CSI resources may include information on CSI resources for channel measurement, information on CSI resources for interference measurement (NZP-CSI-RS resources), information on CSI-IM resources for interference measurement, etc.
- the reporting amount information may specify any one of the above CSI parameters (e.g., CRI, RI, PMI, CQI, LI, L1-RSRP, etc.) or a combination of these.
- CSI parameters e.g., CRI, RI, PMI, CQI, LI, L1-RSRP, etc.
- the report type information may indicate a periodic CSI (Periodic CSI (P-CSI)) report, an aperiodic CSI (A-CSI) report, or a semi-persistent CSI (Semi-Persistent CSI (SP-CSI)) report.
- P-CSI Period CSI
- A-CSI aperiodic CSI
- SP-CSI semi-persistent CSI
- the UE performs CSI-RS/SSB/CSI-IM measurements based on the CSI resource configuration corresponding to the CSI reporting configuration (CSI resource configuration associated with CSI-ResourceConfigId) and derives the CSI to report based on the measurement results.
- the CSI reporting configuration CSI resource configuration associated with CSI-ResourceConfigId
- the CSI resource configuration (e.g., the CSI-ResourceConfig information element) may include a csi-RS-ResourceSetList field indicating more specific CSI-RS/SSB resources, resource type information (e.g., "resourceType") indicating the time domain behavior of the resource configuration, etc.
- the resource type information may indicate a P-CSI resource, an A-CSI resource, or an SP-CSI resource.
- the timing of the P/SP-CSI resource (e.g., transmission/reception timing) may be determined by periodicity and offset information (CSI-ResourcePeriodicityAndOffset) included in the CSI resource configuration.
- the P/SP-CSI resource may be transmitted in a slot that corresponds to a position that is a multiple of the periodicity, taking the offset into account.
- the timing of the A-CSI resource may be determined based on a set offset (aperiodicTriggeringOffset).
- the offset may correspond to the time difference from a triggering DCI (e.g., a DCI including a CSI request field indicating a specific triggering state) that triggers the A-CSI resource/A-CSI report to the A-CSI resource. If not set, the value of the offset may be 0.
- the report timing of the P/SP-CSI report may be determined by information on the period and offset (CSI-ReportPeriodicityAndOffset) included in the CSI report configuration.
- the P/SP-CSI report (on PUCCH) may be transmitted in a slot corresponding to a position that is a multiple of the period, taking the offset into consideration.
- the timing of the SP-CSI report may be determined based on the slot period information (reportSlotConfig) and slot offset information (reportSlotOffsetList) included in the CSI report configuration.
- the SP-CSI report (on PUSCH) may be transmitted in a slot that is a multiple of the slot period after the slot offset based on the reception of the triggering DCI that triggers the SP-CSI report.
- the slot offset may be determined based on the slot offset information and a field of the triggering DCI (e.g., the CSI request field).
- SP-CSI measurement/reporting may be enabled/disabled a certain time after receiving the activation/deactivation MAC CE of the SP-CSI reporting setting.
- SP-CSI measurement/reporting (on PUSCH) may be performed based on a trigger state (e.g., a trigger state included in the SemiPersistentOnPUSCH-TriggerStateList information element) activated by a CSI request field included in a DCI format (e.g., DCI format 0_1/0_2) to which a Cyclic Redundancy Check (CRC) scrambled by the SP-CSI-Radio Network Temporary Identifier (RNTI)) is added.
- a trigger state e.g., a trigger state included in the SemiPersistentOnPUSCH-TriggerStateList information element
- CRC Cyclic Redundancy Check
- the timing of the A-CSI report may be determined based on slot offset information (reportSlotOffsetList) included in the CSI reporting configuration.
- the A-CSI report may be transmitted in a slot after the slot offset based on the reception of a triggering DCI that triggers the A-CSI report.
- the slot offset may be determined based on the slot offset information and a field of the triggering DCI (e.g., a CSI request field).
- the timing of the A-CSI report may be determined based on information of multiple slot offsets for the more than one A-CSI report and the time domain resource allocation field of the triggering DCI.
- a higher layer parameter related to a time constraint of a measurement e.g., timeRestrictionForChannelMeasurements related to a time constraint for a channel measurement, timeRestrictionForInterferenceMeasurements for an interference measurement, etc.
- timeRestrictionForChannelMeasurements related to a time constraint for a channel measurement timeRestrictionForInterferenceMeasurements for an interference measurement, etc.
- a channel measurement for calculating the CSI to be reported is derived based on the most recent NZP CSI-RS occasion related to the CSI reporting configuration that is not later than the CSI reference resource.
- the channel measurement in the present disclosure may be read as an interference measurement or the like.
- the channel measurement for calculating the CSI to be reported is derived based on an NZP CSI-RS occasion associated with the CSI reporting configuration that is not later than the CSI reference resource.
- the reported CSI may be derived based on one or more NZP CSI-RS occasions.
- the CSI reference resource for CSI reporting in UL slot n′ is defined in the time domain by a single DL slot n ⁇ n CSI_ref , where n corresponds to the DL slot that corresponds (overlaps) with UL slot n′.
- n CSI_ref may be determined such that the CSI reference resource is in the same valid DL slot as the corresponding CSI request; otherwise, n CSI_ref may be the minimum value equal to or greater than a certain value corresponding to a delay requirement, such that the single DL slot corresponds to a valid DL slot.
- each embodiment of the present disclosure may be applied when AI is not used (e.g., when prediction is performed using a function).
- A/B and “at least one of A and B” may be interpreted as interchangeable. Also, in this disclosure, “A/B/C” may mean “at least one of A, B, and C.”
- Radio Resource Control RRC
- RRC parameters RRC parameters
- RRC messages higher layer parameters, fields, information elements (IEs), settings, etc.
- IEs information elements
- CE Medium Access Control
- update commands activation/deactivation commands, etc.
- the higher layer signaling may be, for example, Radio Resource Control (RRC) signaling, Medium Access Control (MAC) signaling, broadcast information, positioning protocol (e.g., NR Positioning Protocol A (NRPPa)/LTE Positioning Protocol (LPP)) messages, or any combination thereof.
- RRC Radio Resource Control
- MAC Medium Access Control
- LPP LTE Positioning Protocol
- the MAC signaling may use, for example, a MAC Control Element (MAC CE), a MAC Protocol Data Unit (PDU), etc.
- the broadcast information may be, for example, a Master Information Block (MIB), a System Information Block (SIB), Remaining Minimum System Information (RMSI), Other System Information (OSI), etc.
- MIB Master Information Block
- SIB System Information Block
- RMSI Remaining Minimum System Information
- OSI System Information
- the physical layer signaling may be, for example, Downlink Control Information (DCI), Uplink Control Information (UCI), etc.
- DCI Downlink Control Information
- UCI Uplink Control Information
- index identifier
- indicator indicator
- resource ID etc.
- sequence list, set, group, cluster, subset, etc.
- TRP
- timing, time, duration, time instance, slot, subslot, symbol, subframe, etc. may be interpreted as interchangeable.
- channel measurement/estimation may be performed using at least one of, for example, a Channel State Information Reference Signal (CSI-RS), a Synchronization Signal (SS), a Synchronization Signal/Physical Broadcast Channel (SS/PBCH) block, a DeModulation Reference Signal (DMRS), a Sounding Reference Signal (SRS), etc.
- CSI-RS Channel State Information Reference Signal
- SS Synchronization Signal
- SS/PBCH Synchronization Signal/Physical Broadcast Channel
- DMRS DeModulation Reference Signal
- SRS Sounding Reference Signal
- channel state, channel status, channel, channel environment, etc. may be interpreted as interchangeable.
- UCI, CSI report, CSI feedback, feedback information, feedback bit, CSI feedback method, CSI feedback scheme, beam report, beam report scheme, etc. may be interchangeable.
- bit, bit string, bit sequence, sequence, value, information, value obtained from a bit, information obtained from a bit, etc. may be interchangeable.
- the CSI-RS resource set, the configuration parameters of the CSI-RS resource set, the NZP CSI-RS resource set, the configuration parameters of the NZP CSI-RS resource set (NZP-CSI-RS-ResourceSet), the configuration parameters of the resource set of the SSB for CSI measurement (CSI-SSB-ResourceSet), and the configuration parameters of the CSI-IM resource set (CSI-IM-ResourceSet) may be read as interchangeable.
- CSI-RS resources CSI-RS resource configuration parameters, NZP CSI-RS resources, NZP CSI-RS resource configuration parameters (NZP-CSI-RS-Resource), CSI resources, etc. may be read as interchangeable.
- a resource may refer to a reference signal resource and may be interchangeably read as a recommended/predicted/measured resource.
- a resource may refer to a resource in time/frequency/code/spatial domain, etc.
- a resource may be identified by at least one of a resource indicator, a capability index, a beam ID, etc.
- beam may be interchangeably referred to as recommended/predicted/measured beam.
- beam and resource may be interchangeably referred to.
- L1-RSRP, top-X probability (described below), top-X'/1 probability (described below), etc. may be interchangeably read as input candidates (e.g., CIR) for the AI model of BM case 1/2 described above.
- the first embodiment relates to information for (or related to) beam prediction, hereinafter also referred to as beam information.
- the UE may transmit beam information to the network.
- the beam information may include at least one of the pieces of information described below.
- the information to be included in the beam information may be notified to the UE by the network, may be specified in a standard, or may be derived from a model used for beam prediction (associated model).
- the beam information may also be derived from at least one of information notified to the UE by the network without being reported by the UE, values specified in a standard, a model used for beam prediction (associated model), etc.
- the beam information may include information indicating a resource.
- the information indicating the resource may be called a resource indicator, a channel resource indicator, etc., and may be, for example, at least one of an SSBRI, a CRI, an SRS resource indicator, etc.
- the resource indicator may be associated with a time instance/duration (e.g., may be identified by a time instance/duration) as described below.
- CRI/SSBRI may be read as a resource indicator and vice versa.
- the beam information may include information indicating the number of resource indicators.
- the information may indicate the number of resource indicators included in one beam information (which may be referred to as a report instance, etc.).
- a report instance may be interchangeably read as a beam report, a CSI report, a report, etc.
- the beam information may include information indicating a capability index for measurement/prediction.
- the capability index may indicate a panel for a corresponding resource indicator and may be interchangeably read as a panel index, a UE capability value, a UE capability value set, etc.
- a resource indicator may be interchangeably read as a resource indicator/capability index.
- the beam information may include information indicating a beam ID.
- the beam ID may be associated with a beam.
- the beam ID may be associated with a particular reference signal (e.g., CSI-RS, SSB, SRS, Positioning Reference Signal (PRS)).
- the beam ID may be associated with a time instance/duration as described below.
- the beam information may include information indicating the L1-RSRP.
- the L1-RSRP may correspond to a resource (or may be measured/predicted based on the resource).
- the L1-RSRP may be associated with a time instance/duration as described below.
- the beam information may include information indicating the top-X probability.
- the top-X probability of a resource among one or more resources may mean the probability/confidence/confidence interval that the RSRP or SINR corresponding to the resource is equal to or greater than the Xth largest RSRP or SINR among the RSRPs or SINRs corresponding to the one or more resources.
- This confidence interval may be an arbitrary percentage (e.g., 95%) confidence interval.
- the beam information may include information indicating the top-X'/1 probability.
- the top-X'/1 probability for one or more resources may mean the probability/confidence/confidence interval that at least one of the RSRPs corresponding to X' resources is the maximum among the RSRPs or SINRs corresponding to the one or more resources.
- This confidence interval may be an arbitrary percentage (e.g., 95%) confidence interval. Note that, for the same value of X', if different top-X'/1 probabilities are obtained depending on how the resources are selected, one of these values (e.g., the maximum value) may be determined as the top-X'/1 probability.
- the information indicating the L1-RSRP, the top X probability, or the top X'/1 probability may include information indicating the difference from another L1-RSRP, the top X probability, or the top X'/1 probability (difference information).
- the information indicating the L1-RSRP, the top X probability, the top X'/1 probability, or the difference information therefor may be quantized information (quantization information).
- the quantization information may correspond to information in which the L1-RSRP, the top X probability, the top X'/1 probability, or the difference therefor is represented by a specific number of bits divided by a specific quantization resolution (e.g., dB step size) for a specific expressible range (the value indicated by the bit corresponds to one of the steps (divisions)).
- the quantized information of the difference information is preferably represented with a smaller number of bits than the quantized information of non-differential information (e.g., the quantized resolution is lower or the expressible range is narrower than the quantized information of non-differential information), but it may be represented with the same or a larger number of bits.
- the information regarding X, X', the specific range, the specific quantization resolution, the specific number, etc. may be notified to the UE by the network, may be specified in a standard, may be derived from a model (associated model) used for beam prediction, or may be determined based on other information within the same reporting instance.
- the beam information may include information indicating a time instance (time instance information).
- a time instance may mean a time to be measured/predicted (in other words, a time to be measured/predicted). Note that a time instance may be interchangeably read as a timestamp.
- the time instance information may indicate at least one of a symbol index, a symbol number, a slot index (within a subframe/frame), a slot number, a system frame number, a reference signal (resource) opportunity, etc., that indicates the time instance associated with the resource indicator/beam ID.
- the time instance may be expressed as a timing Y time units (e.g., symbols, slots, milliseconds, subframes, frames, etc.) before (past) or after (future) a specific timing.
- the specific timing may be, for example, the start/end timing of a CSI reference resource, the timing at which beam information including the time instance is reported, or the RS occasion used for measurement.
- the information regarding the specific timing, Y, etc. may be notified to the UE by the network, may be specified in a standard, may be derived from a model (associated model) used for beam prediction, or may be determined based on other information within the same reporting instance.
- the beam information may include information indicating the number of time instances.
- the information may indicate the number of time instance information included in the report instance.
- the beam information may include information indicating a duration (duration information).
- duration may mean the length of time to be measured/predicted.
- the duration information may indicate the number of time units (e.g., symbols, slots, milliseconds, subframes, frames, reference signal opportunities, etc.) indicating the length of time associated with the resource indicator/beam ID.
- the duration may be a duration based on a specific timing (e.g., a specific timing). For example, it may be the start/end timing of the CSI reference resource, the timing when the beam information including the time instance is reported, the RS occasion used for the measurement, the time after the end of a specific duration (e.g., the previous duration), or may be indicated by the above time instance information.
- the beam information may include information indicating the number of durations.
- the information may indicate the number of duration information included in the report instance.
- the time instance/duration may be associated with the L1-RSRP, the top X probability or the top X'/1 probability.
- the beam information may include at least one of beam information for set A and beam information for set B.
- the UE for network-side data collection, it is preferable for the UE to report beam information for set B including beam measurement results (such as L1-RSRP) of set B. Also, for network-side data collection, it is preferable for the UE to report beam information for set A including beam measurement results (such as L1-RSRP) of set A, or information (e.g., resource indicator) indicating the top K (K ⁇ 1) beams of set A without beam measurement results.
- beam measurement results such as L1-RSRP
- the UE for network-side data collection, it is preferable for the UE to report beam information for set A including beam measurement results (such as L1-RSRP) of set A, or information (e.g., resource indicator) indicating the top K (K ⁇ 1) beams of set A without beam measurement results.
- the UE reports beam information for set A including beam measurement results (e.g., L1-RSRP) of set A, or information indicating the top K (K ⁇ 1) beams of set A (e.g., resource indicators) without beam measurement results.
- beam measurement results e.g., L1-RSRP
- K ⁇ 1 the top K beams of set A
- the UE When model inference is performed on the UE side, the UE preferably reports beam information for set A including beam prediction results (e.g., L1-RSRP) for set A or information (e.g., resource indicators) indicating the top K (K ⁇ 1) predicted beams of set A.
- the beam information for set A may also include a timestamp of the predicted time.
- the UE When model inference is performed on the network side, it is preferable for the UE to report beam information for set B including beam measurement results (such as L1-RSRP) for set B.
- the beam information for set B may also include a timestamp of the time of measurement.
- the UE can report beam information including appropriate information.
- the second embodiment relates to information reported that is associated with a time instance/duration.
- some of the reported beam information may be associated with a time instance/duration.
- the UE may report a value (e.g., L1-RSRP) at a certain time instance (e.g., a certain slot/symbol, a certain reference signal occasion).
- a value e.g., L1-RSRP
- a certain time instance e.g., a certain slot/symbol, a certain reference signal occasion.
- the UE may report a resource indicator/beam ID associated with a certain duration.
- Figure 3 shows an example of a time instance/duration relationship.
- the UE reports a recommended resource indicator to the network.
- the recommended resource indicator may be used to recommend to the base station the transmission of a signal that has a QCL relationship with the reference signal indicated by the recommended resource indicator.
- durations #0-#2 correspond to CRIs #0-#2, respectively.
- a duration may be determined from one or more time instances.
- duration #0 may correspond to the period between a specific timing (e.g., start/end timing of a CSI reference resource, a reporting slot for reporting beam information, an RS occasion used for measurement, etc.) and the first time instance (time instance #1).
- Duration #i (i ⁇ 1) may correspond to the period between the i-th time instance (e.g., time instance #1) and the i+1-th time instance (e.g., time instance #2).
- duration #i (i ⁇ 1) may correspond to the period after the i-th time instance (e.g., time instance #1) (e.g., when there is no i+1-th time instance).
- a certain duration may be determined from a set/specified duration. For example, if 5 ms is set/specified as duration #0, the UE may determine that the period of 5 ms from the specific timing corresponds to duration #0.
- the third embodiment relates to reporting beam information without L1-RSRP.
- the UE may transmit a report instance without including the associated L1-RSRP, but including resource indicators corresponding to the 1st through Zth highest L1-RSRPs corresponding to one or more resources.
- the information regarding the one or more resources, Z, etc. may be signaled to the UE by the network, may be specified in a standard, may be derived from a model used for beam prediction (associated model), or may be determined based on other information within the same reporting instance.
- the one or more resources may be resources for set A or may be resources for set B.
- the reporting instance of the third embodiment may be primarily intended for set A.
- Figures 4A and 4B are diagrams showing an example of a report instance that does not include L1-RSRP in the third embodiment.
- the report instance in this example is a CSI report (CSI report #X). Note that the order of the fields included in the report instance of the present disclosure is not limited to the order shown in the figure (the same applies to subsequent figures).
- Both Figures 4A and 4B do not include an L1-RSRP field, but include a CRI/SSBRI field, which is a resource indicator field.
- the first CRI/SSBRI field (CRI/SSBRI#1 field) may or may not correspond to the largest L1-RSRP.
- Reporting instances that do not include L1-RSRP may include a field indicating a capability index for measurement/prediction.
- a capability index for measurement/prediction For each CRI/SSBRI field in a reporting instance, an associated capability index field is reported.
- Figure 4B one capability index field is reported that is associated with all CRI/SSBRI fields in a reporting instance.
- a reporting instance that does not include L1-RSRP is expected to reduce communication overhead.
- the reporting instance is suitable for reporting beam information of set B for data collection.
- the reporting instance is suitable for reporting beam information of set A for model inference on the UE side.
- a report instance that does not include an L1-RSRP may include a field indicating the top X probability or the top X'/1 probability as described in the first embodiment.
- the UE may transmit one report instance without including an associated L1-RSRP, and including resource indicators corresponding to the 1st to Zth largest L1-RSRPs or top X probabilities corresponding to one or more resources. In this case, the UE may assume (expect) that X' and Z are the same value.
- Figures 5A and 5B are diagrams showing an example of a report instance that does not include an L1-RSRP in the third embodiment.
- the report instance in this example is similar to that in Figure 4B, except that Figure 5A includes a Top X Probability #i field corresponding to each CRI/SSBRI #i field (i is an integer), and Figure 5B includes a Top 4/1 Probability field.
- the first CRI/SSBRI field may correspond to the largest L1-RSRP or the largest top-X probability.
- the Top-X Probability#1 field may indicate the largest top-X probability reported.
- Top X Probability #1 field indicates the maximum top X probability reported
- the top X probability #1 field does not have to indicate the maximum top X probability, so there is a high degree of freedom in the placement of each field (and since the UE does not need to request differential information, it is expected that the UE load will be reduced (especially when there are a large number of fields to report)).
- X may be the same value, or different values may be allowed.
- a top 1 probability field, a top 2 probability field, ..., a top Z probability field, etc. may be included corresponding to the same CRI/SSBRI field.
- the number of top X (X is any value) probability fields corresponding to the CRI/SSBRI fields included in a report instance may be different for each CRI/SSBRI field.
- the CRI/SSBRI#i field may correspond to the i-th largest L1-RSRP, or may correspond to the i-th largest top X probability, or may indicate a CRI/SSBRI related to the top 4/1 probability indicated by the illustrated top 4/1 probability field (e.g., a CRI/SSBRI that is likely to be the largest L1-RSRP).
- the illustrated Top 4/1 probability field may be a different Top X'/1 probability field depending on the number of CRI/SSBRI fields in the reporting instance. For example, if the number of CRI/SSBRI fields in the reporting instance is 1, 2, or 3, a Top 1/1 probability field, a Top 2/1 probability field, or a Top 3/1 probability field may be included instead of the Top 4/1 probability field, respectively.
- a reporting instance may include multiple top X'/1 probability fields.
- the UE can report a reporting instance without L1-RSRP.
- the reporting instance may not include any L1-RSRP fields at all, but may instead include an L1-RSRP field corresponding to at least one resource indicator.
- the reporting instance may not include all L1-RSRP fields corresponding to all resource indicator fields in the reporting instance, but may include only some of the L1-RSRP fields.
- a fourth embodiment relates to reporting of beam information in which the number of resource indicators is reduced.
- the UE may transmit a single report instance including information indicating the L1-RSRP, top X probability, or top X'/1 probability corresponding to one or more resources (e.g., for all resources among the one or more resources).
- the one or more resources may be resources for set A or may be resources for set B.
- the reporting instance of the fourth embodiment may be primarily intended for set B.
- the number of fields (which may include a field indicating differential information) included in one report instance may be a specific number.
- the specific number may be greater than 4 or less than or equal to 4.
- the information regarding the one or more resources, the specific number, etc. may be signaled to the UE by the network, may be specified in a standard, may be derived from a model (associated model) used for beam prediction, or may be determined based on other information within the same reporting instance.
- the report instance of the fourth embodiment may include at least one of a resource indicator field and a capability index field corresponding to the maximum L1-RSRP, top X probability, or top X'/1 probability indicated by the report instance, and may not include other resource indicator fields/capability index fields. This allows the communication overhead of the report instance to be suitably reduced.
- resource indicators/capability indexes that are not reported may be identified based on the reported resource indicators/capability indexes and mapping rules.
- the first resource indicator/capability index corresponding to the reported L1-RSRP, top X probability, or top X'/1 probability field corresponds to the resource (resource indicator field/capability index field) that is reported
- the second and subsequent resource indicators/capability indexes may be determined based on the mapping rules from resources other than the first resource.
- the reporting instance of the fourth embodiment may not include at least one of the resource indicator field and the capability index field.
- the resource indicator/capability index corresponding to the reported L1-RSRP, top X probability, or top X'/1 probability field may be determined based on a mapping rule.
- FIGS. 6A and 6B are diagrams showing an example of a reporting instance in the fourth embodiment.
- the number of resources to be reported is four, and the RSRP (or differential RSRP) for all four resources is reported.
- FIG. 6A shows an example of a reporting instance.
- the CRI/SSBRI#1 field indicates the CRI/SSBRI corresponding to the maximum RSRP#1.
- the capability index field may also indicate the capability index corresponding to the CRI/SSBRI indicated by the CRI/SSBRI#1 field (or all resources (CRI/SSBRI)).
- Figure 6B is a diagram showing a specific example of CRI/SSBRI that is not reported, corresponding to Figure 6A.
- the resource indicators corresponding to the four resources are SSBRIs #1, #2, #3 and #6. If the CRI/SSBRI#1 field of the reporting instance in Figure 6A indicates SSBRI#2, then the remaining SSBRIs may correspond to the (differential) RSRP#2-#4 fields in ascending order (i.e., SSBRIs #1, #3 and #6, respectively).
- the mapping rule may be based on the resource indicator/capability index. For example, if L1-RSRP, top X probability or top X'/1 probability is measured/predicted based on one or both of the resource indicator and the capability index, the mapping rule may include: ⁇ Mapping is done in order from the smallest index to the largest. In the mapping order, CRI takes precedence over SSBRI, or SSBRI takes precedence over CRI, or no distinction is made between CRI and SSBRI; Cell IDs (e.g., physical cell IDs) are mapped from smallest to largest. Within the same cell ID, the mapping order is determined according to the CRI/SSBRI. Capability index is mapped from smallest to largest. Within the same capability index, the mapping order is determined according to CRI/SSBRI, or within the same CRI/SSBRI, the mapping order is determined according to capability index.
- ⁇ Mapping is done in order from the smallest index to the largest. In the mapping order, CRI takes precedence over SSBR
- the reporting instance of the third embodiment and the reporting instance of the fourth embodiment may be used in combination.
- the UE may report the L1-RSRP of all reference signals associated with one or more resources (without reporting some CRI/SSBRI corresponding to the L1-RSRP), and report the CRI/SSBRI that achieves the 1st to Xth largest RSRP for the one or more resources or for one or more different resources.
- Such a reporting instance is suitable, for example, for Set B beam measurement and Set A beam indication without L1-RSRP in data collection.
- the UE may be configured with one or more resources for set B.
- the UE may calculate/control the input of the beam prediction model based on measurements of the resources of set B.
- the UE may be configured with one or more resources for set A.
- the UE may perform beam prediction for the reported resources (set A) and report the prediction result using a CSI report.
- the UE may report beam information including at least one of predicted CRI/SSBRI, L1-RSRP, top X probability, top X'/1 probability, etc. based on the beam prediction performed.
- the UE may be configured with the number of RS resources (e.g., N, where N is any positive integer) for Set A/Set B per report setting.
- N the number of RS resources
- FIG. 7 is a diagram showing an example of beam prediction according to embodiment 5-1.
- the UE measures the beams/RSs included in set B. Then, the UE performs beam prediction based on the measurements of set B.
- the UE reports a CSI report including N beam qualities of set A (e.g., at least one of CRI/SSBRI, L1-RSRP, top X probability, top X'/1 probability, etc.).
- N beam qualities of set A e.g., at least one of CRI/SSBRI, L1-RSRP, top X probability, top X'/1 probability, etc.
- the UE may report beam information including at least one of predicted CRI/SSBRI, L1-RSRP, top X probability, top X'/1 probability, etc. in certain cases.
- the particular case may be, for example, at least one of the following options 5-2-1 to 5-2-3.
- the UE may report the above beam information when a specific value is set/indicated in a specific parameter.
- the specific parameters may be notified to the UE by higher layer signaling (e.g., RRC parameters/MAC CE).
- higher layer signaling e.g., RRC parameters/MAC CE.
- the RRC parameter may be included in a CSI report configuration (e.g., CSI-ReportConfig).
- the RRC parameter may be included in a report quantity parameter (e.g., reportQuantity) included in a CSI report configuration (e.g., CSI-ReportConfig).
- the specific value may be a value indicating that any information contained in the beam information described in the first embodiment is to be reported.
- FIG. 8 is a diagram showing an example of RRC parameters related to option 5-2-1.
- FIG. 8 is written using ASN.1 (Abstract Syntax Notation One) notation.
- ASN.1 Abstract Syntax Notation One
- the following drawings showing settings/RRC parameters/information elements in this disclosure are similarly written using ASN.1 notation.
- the report quantity parameter (reportQuantity) included in the CSI report configuration may include a parameter (predicted-cri-topX) indicating that the top X probability is measured/predicted based on the CSI-RS (CRI) or a parameter (predicted-ssb-Index-topX) indicating that the top X probability is measured/predicted based on the SSB (SSBRI).
- a parameter predicted-cri-topX
- SSBRI SSB
- the UE determines to report the top X probabilities based on CSI-RS (and not report L1-RSRP) using the reporting instance corresponding to this CSI reporting configuration.
- predicted-ssb-Index-topX the UE determines to report the top X probabilities based on SSB (and not report L1-RSRP) using the reporting instance corresponding to this CSI reporting configuration.
- the UE may report the above beam information when a specific AI model is activated.
- the particular AI model may be, for example, an AI model related to the predicted beam.
- the UE may report the above beam information when a specific AI model is configured/registered.
- the particular AI model may be, for example, an AI model related to the predicted beam.
- At least two of the above options 5-2-1 to 5-2-3 may be applied in combination.
- the UE may report the beam information when a specific RRC parameter (e.g., a parameter indicating that the top X probability is measured/predicted) is configured for the UE and the specific AI model is activated.
- a specific RRC parameter e.g., a parameter indicating that the top X probability is measured/predicted
- the UE may separately determine the RS (eg, CSI-RS/SSB) resources to be measured and the RS resources to be reported.
- RS eg, CSI-RS/SSB
- the UE may report at least one of the CRI/SSBRI, L1-RSRP, top X probability, top X'/1 probability, etc., of RS resources other than the RS resource being measured.
- the UE may determine the resources to be measured and the resources to be reported according to at least one of 6-1-1 to 6-1-5 below.
- the UE may make RS decisions using specific RRC parameters.
- the UE may use existing RRC parameters (defined by Rel. 16/17) to determine the RS.
- the RRC parameters may be included in parameters for setting resources for channel measurement/interference measurement, for example.
- the RRC parameters may be RRC parameters included in a CSI report configuration (e.g., CSI-ReportConfig).
- the UE may be configured with a CSI resource configuration (e.g., CSI-ResourceConfig) that includes resources for CSI (CRI/SSBRI, L1-RSRP, top-X probability, top-X'/1 probability, etc.) reported in beam prediction.
- CSI resource configuration e.g., CSI-ResourceConfig
- the UE may refer to/determine resources corresponding to existing RRC parameters (e.g., at least one of parameters for resources for channel measurement (e.g., resourceForChannelMeasurement) and parameters for resources for interference measurement (e.g., csi-IM-ResourcesForInterference)) for beam prediction calculation (e.g., input for an AI model).
- RRC parameters e.g., at least one of parameters for resources for channel measurement (e.g., resourceForChannelMeasurement) and parameters for resources for interference measurement (e.g., csi-IM-ResourcesForInterference)) for beam prediction calculation (e.g., input for an AI model).
- FIG. 9 is a diagram showing an example of RRC parameters related to option 6-1-1.
- the CSI report configuration (CSI-ReportConfig) includes a parameter (resourcesForReporting) indicating resources for reporting.
- the parameter (resourcesForReporting) indicating resources for reporting refers to the ID of the CSI resource configuration (CSI-ResourceConfigId).
- the UE determines which resources to report based on the referenced CSI-ResourceConfigId.
- the UE may make RS decisions using specific RRC parameters.
- the UE may determine the RS using new RRC parameters (defined in Rel. 18/19 and later).
- the RRC parameters may be, for example, RRC parameters included in a CSI report configuration (e.g., CSI-ReportConfig).
- CSI report configuration e.g., CSI-ReportConfig
- the RRC parameters may be configured for the UE using a CSI resource configuration that includes resources for channel measurements used for beam prediction.
- the RRC parameters may be configured for the UE using a CSI resource configuration that includes resources for interference measurements/interference beam measurements used for beam prediction.
- the RRC parameters may be configured for the UE using a CSI resource configuration that includes resources for CSI (CRI/SSBRI, L1-RSRP, top X probability, top X'/1 probability, etc.) reported in beam prediction.
- CSI resource configuration that includes resources for CSI (CRI/SSBRI, L1-RSRP, top X probability, top X'/1 probability, etc.) reported in beam prediction.
- the UE may make the RS (resource set of RS) decision using specific RRC parameters.
- CSI resource configuration parameters (e.g., CSI-ResourceConfig) may be extended.
- the UE may be configured with a resource set for the CSI (CRI/SSBRI, L1-RSRP, top X probability, top X'/1 probability, etc.) reported after beam prediction.
- CSI CRI/SSBRI, L1-RSRP, top X probability, top X'/1 probability, etc.
- a single CSI resource configuration parameter (e.g., CSI-ResourceConfig) may include both information about the resource set to be reported and information about the resource set to be measured for beam prediction.
- a single CSI resource configuration parameter (e.g., CSI-ResourceConfig) may include either information about a resource set to be reported or information about a resource set to be measured for beam prediction.
- two or more CSI resource configuration parameters (e.g., CSI-ResourceConfig) may be configured for a UE.
- the UE may make RS (RS resource) decisions using specific RRC parameters.
- the parameters for the resource set may be expanded.
- the UE may be configured with a parameter (e.g., NZP-CSI-RS-ResourceSet) for a resource set that includes the resources to be reported and the resources to be measured for beam prediction.
- a parameter e.g., NZP-CSI-RS-ResourceSet
- a list may be defined that includes at least one of the resources of the RS to be reported and the resources of the RS to be measured for beam prediction.
- the UE may determine at least one of the resources of the RS to be reported and the resources of the RS to be measured based on the list.
- the UE may be configured with a list containing the resource IDs/resource set IDs/CSI resource configurations of the resources to be reported.
- the UE may be configured with a list including resource IDs/resource set IDs/CSI resource configurations of resources to be measured for beam prediction.
- a single list may include both information about the resources of the RS to be reported and information about the resources of the RS to be measured for beam prediction.
- a single list may include either information about the resources of the RS to be reported or information about the resources of the RS to be measured for beam prediction.
- At least two of the above options 6-1-1 to 6-1-5 may be applied in combination.
- the UE may expect/assume in certain conditions that it is configured to report CRI/SSBRI, L1-RSRP, top-X probability, top-X′/1 probability, etc. for RS resources different from the RS resource it measures on.
- the particular condition may be when a particular AI model is activated.
- the particular condition may be when a particular AI model related to beam prediction is activated.
- the particular condition may be when a particular AI model associated with a particular type of beam prediction is activated.
- the particular type of beam prediction may be, for example, spatial domain beam prediction or time domain beam prediction.
- the particular condition may be when a particular RRC parameter (e.g., reportQuantity) is set/indicated to a particular value (e.g., a value indicating that any information contained in the beam information is to be reported, as described in the first embodiment).
- a particular RRC parameter e.g., reportQuantity
- the UE may expect/assume that at least one of the following for each reporting setting: RS resources for channel/interference measurements, RS resources for reporting, number of RS resources to be measured, and number of RS resources to be reported, is the same as the information associated with each model (activated AI model).
- the correspondence/mapping between the measured RS/beam and the reported RS/beam can be appropriately determined.
- AI model information may mean information including at least one of the following: - AI model input/output information, - Pre-processing/post-processing information for input/output of AI models; ⁇ Information on the parameters of the AI model, - Training information for the AI model; - Inference information for AI models, ⁇ Performance information about the AI model.
- the input/output information of the AI model may include information regarding at least one of the following: Content of input/output data (e.g. RSRP, SINR, amplitude/phase information in the channel matrix (or precoding matrix), information on the Angle of Arrival (AoA), information on the Angle of Departure (AoD), location information); - auxiliary information of the data (which may be called meta-information); - Input/output data types (e.g. immutable values, floating point numbers), - Bit width of input/output data (e.g. 64 bits for each input value), Quantization interval (quantization step size) of input/output data (e.g., 1 dBm for L1-RSRP); The range that the input/output data can take (e.g., [0, 1]).
- Content of input/output data e.g. RSRP, SINR, amplitude/phase information in the channel matrix (or precoding matrix), information on the Angle of Arrival (AoA), information on the
- the information regarding AoA may include information regarding at least one of the azimuth angle of arrival and the zenith angle of arrival (ZoA). Furthermore, the information regarding AoD may include information regarding at least one of the azimuth angle of departure and the zenith angle of departure (ZoD).
- the location information may be location information regarding the UE/NW.
- the location information may include at least one of information (e.g., latitude, longitude, altitude) obtained using a positioning system (e.g., a satellite positioning system (Global Navigation Satellite System (GNSS), Global Positioning System (GPS), etc.)), information on the BS adjacent to (or serving) the UE (e.g., a BS/cell identifier (ID), a BS-UE distance, a direction/angle of the BS (UE) as seen from the UE (BS), coordinates of the BS (UE) as seen from the UE (BS) (e.g., coordinates on the X/Y/Z axes), etc.), a specific address of the UE (e.g., an Internet Protocol (IP) address), etc.
- IP Internet Protocol
- the location information of the UE is not limited to information based on the position of the BS, and may be information based on a specific point.
- the location information may include information about its implementation (e.g., location/position/orientation of antennas, location/orientation of antenna panels, number of antennas, number of antenna panels, etc.).
- the location information may include mobility information.
- the mobility information may include information indicating at least one of the following: a mobility type, a moving speed of the UE, an acceleration of the UE, and a moving direction of the UE.
- the mobility type may correspond to at least one of fixed location UE, movable/moving UE, no mobility UE, low mobility UE, middle mobility UE, high mobility UE, cell-edge UE, not-cell-edge UE, etc.
- environmental information may be information regarding the environment in which the data is acquired/used, and may correspond to, for example, frequency information (such as a band ID), environmental type information (information indicating at least one of indoor, outdoor, Urban Macro (UMa), Urban Micro (Umi), etc.), information indicating Line Of Site (LOS)/Non-Line Of Site (NLOS), etc.
- frequency information such as a band ID
- environmental type information information indicating at least one of indoor, outdoor, Urban Macro (UMa), Urban Micro (Umi), etc.
- LOS Line Of Site
- NLOS Non-Line Of Site
- LOS may mean that the UE and BS are in an environment where they can see each other (or there is no obstruction)
- NLOS may mean that the UE and BS are not in an environment where they can see each other (or there is an obstruction).
- Information indicating LOS/NLOS may indicate a soft value (e.g., the probability of LOS/NLOS) or a hard value (e.g., either LOS or NLOS).
- meta-information may mean, for example, information regarding input/output information suitable for an AI model, information regarding data that has been acquired/can be acquired, etc.
- meta-information may include information regarding beams of RS (e.g., CSI-RS/SRS/SSB, etc.) (e.g., the pointing angle of each beam, 3 dB beam width, the shape of the pointed beam, the number of beams), layout information of gNB/UE antennas, frequency information, environmental information, meta-information ID, etc.
- RS e.g., CSI-RS/SRS/SSB, etc.
- meta-information may be used as input/output of an AI model.
- the pre-processing/post-processing information for the input/output of the AI model may include information regarding at least one of the following: Whether to apply normalization (e.g., Z-score normalization, min-max normalization), Parameters for normalization (e.g. mean/variance for Z-score normalization, min/max for min-max normalization); Whether to apply a specific numeric transformation method (e.g., one hot encoding, label encoding, etc.); Selection rule for whether or not to use as training data.
- normalization e.g., Z-score normalization, min-max normalization
- Parameters for normalization e.g. mean/variance for Z-score normalization, min/max for min-max normalization
- a specific numeric transformation method e.g., one hot encoding, label encoding, etc.
- the information of the parameters of the AI model may include information regarding at least one of the following: - Weight information in an AI model (e.g., neuron coefficients (connection coefficients)), ⁇ Structure of the AI model, -
- the type of AI model as a model component e.g., Residual Network (ResNet), DenseNet, RefineNet, Transformer model, CRBlock, Recurrent Neural Network (RNN), Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU)
- - Functions of the AI model as model components e.g., decoder, encoder.
- the weight information in the AI model may include information regarding at least one of the following: - Bit width (size) of weight information Quantization interval of weight information, - Granularity of weight information, - The range of possible weight information - Weight parameters in the AI model, - Information on the difference from the AI model before the update (if updating), - Method of weight initialization (e.g., zero initialization, random initialization (based on normal/uniform/truncated normal distribution), Xavier initialization (for sigmoid function), He initialization (for Rectified Linear Units (ReLU))).
- the structure of the AI model may also include information regarding at least one of the following: Number of layers, - Type of layer (e.g., convolutional, activation, dense, normalization, pooling, attention); - Layer information, Time series specific parameters (e.g. bidirectionality, time step), Parameters for training (e.g., type of feature (L2 regularization, dropout feature, etc.), where to put this feature (e.g., after which layer)).
- Number of layers e.g., - Type of layer (e.g., convolutional, activation, dense, normalization, pooling, attention); - Layer information, Time series specific parameters (e.g. bidirectionality, time step), Parameters for training (e.g., type of feature (L2 regularization, dropout feature, etc.), where to put this feature (e.g., after which layer)).
- - Type of layer e.g., convolutional, activation, dense, normalization, pooling, attention
- - Layer information e
- the layer information may include information regarding at least one of the following: - The number of neurons in each layer, - kernel size, strides for pooling/convolutional layers, Pooling method (MaxPooling, AveragePooling, etc.), - Information on the residual block, ⁇ Number of heads, - Normalization method (batch normalization, instance normalization, layer normalization, etc.), Activation functions (sigmoid, tanh function, ReLU, leaky ReLU information, Maxout, Softmax).
- An AI model may be included as a component of another AI model.
- an AI model may be an AI model in which processing proceeds in the order of model component #1 (ResNet), model component #2 (a transformer model), a dense layer, and a normalization layer.
- ResNet model component #1
- model component #2 a transformer model
- dense layer a dense layer
- normalization layer a normalization layer
- Training information for the AI model may include information regarding at least one of the following: Information for the optimization algorithm (e.g., type of optimization (Stochastic Gradient Descent (SGD)), AdaGrad, Adam, etc.), parameters of the optimization (learning rate, momentum information, etc.), Loss function information (e.g., information on metrics of the loss function (Mean Absolute Error (MAE)), Mean Square Error (MSE), Cross Entropy Loss, NLL Loss, Kullback-Leibler (KL) Divergence, etc.)); - parameters to be frozen for training (e.g. layers, weights), - parameters to be updated (e.g.
- Information for the optimization algorithm e.g., type of optimization (Stochastic Gradient Descent (SGD)), AdaGrad, Adam, etc.
- parameters of the optimization learning rate, momentum information, etc.
- Loss function information e.g., information on metrics of the loss function (Mean Absolute Error (MAE)
- layers, weights - parameters that should be (used as) initial parameters for training (e.g. layers, weights); How to train/update the AI model (e.g., (recommended) number of epochs, batch size, number of data used for training).
- the inference information for the AI model may include information regarding decision tree branch pruning, parameter quantization, and the function of the AI model.
- the function of the AI model may correspond to at least one of, for example, time domain beam prediction, spatial domain beam prediction, an autoencoder for CSI feedback, and an autoencoder for beam management.
- An autoencoder for CSI feedback may be used as follows: The UE inputs the CSI/channel matrix/precoding matrix into the AI model of the encoder and transmits the encoded bits as CSI feedback (CSI report); - The BS reconstructs the CSI/channel matrix/precoding matrix, which is output as input to the AI model of the decoder using the received encoded bits.
- the UE/BS may input measurement results (beam quality, e.g., RSRP) based on sparse (or thick) beams into an AI model, which may output dense (or thin) beam quality.
- beam quality e.g., RSRP
- the UE/BS may input time series (past, present, etc.) measurement results (beam quality, e.g., RSRP) into an AI model and output future beam quality.
- time series past, present, etc.
- beam quality e.g., RSRP
- the performance information regarding the AI model may include information regarding the expected value of a loss function defined for the AI model.
- the AI model information in this disclosure may include information regarding the scope of application (scope of applicability) of the AI model.
- the scope of application may be indicated by a physical cell ID, a serving cell index, etc.
- Information regarding the scope of application may be included in the above-mentioned environmental information.
- AI model information regarding a specific AI model may be predetermined in a standard, or may be notified to the UE from the network (NW).
- An AI model defined in a standard may be referred to as a reference AI model.
- AI model information regarding a reference AI model may be referred to as reference AI model information.
- the AI model information in the present disclosure may include an index for identifying the AI model (e.g., may be called an AI model index, an AI model ID, a model ID, etc.).
- the AI model information in the present disclosure may include an AI model index in addition to/instead of the input/output information of the AI model described above.
- the association between the AI model index and the AI model information (e.g., input/output information of the AI model) may be predetermined in a standard, or may be notified to the UE from the NW.
- the AI model information in this disclosure may be associated with an AI model and may be referred to as AI model relevant information, simply relevant information, etc.
- the AI model relevant information does not need to explicitly include information for identifying the AI model.
- the AI model relevant information may be information that includes only meta information, for example.
- the model ID may be interchangeably read as an ID (model set ID) corresponding to a set of AI models.
- the model ID may be interchangeably read as a meta information ID.
- the meta information (or meta information ID) may be associated with information regarding the beam (beam setting) as described above.
- the meta information (or meta information ID) may be used by the UE to select an AI model taking into account which beam the BS is using, or may be used to notify the BS of which beam to use to apply the AI model deployed by the UE.
- the meta information ID may be interchangeably read as an ID (meta information set ID) corresponding to a set of meta information.
- any information may be notified to the UE (from the NW) (in other words, any information received from the BS in the UE) using physical layer signaling (e.g., DCI), higher layer signaling (e.g., RRC signaling, MAC CE), a specific signal/channel (e.g., PDCCH, PDSCH, reference signal), or a combination thereof.
- physical layer signaling e.g., DCI
- higher layer signaling e.g., RRC signaling, MAC CE
- a specific signal/channel e.g., PDCCH, PDSCH, reference signal
- the MAC CE may be identified by including a new Logical Channel ID (LCID) in the MAC subheader that is not specified in existing standards.
- LCID Logical Channel ID
- the notification When the notification is made by a DCI, the notification may be made by a specific field of the DCI, a Radio Network Temporary Identifier (RNTI) used to scramble Cyclic Redundancy Check (CRC) bits assigned to the DCI, the format of the DCI, etc.
- RNTI Radio Network Temporary Identifier
- CRC Cyclic Redundancy Check
- notification of any information to the UE in the above-mentioned embodiments may be performed periodically, semi-persistently, or aperiodically.
- notification of any information from the UE (to the NW) may be performed using physical layer signaling (e.g., UCI), higher layer signaling (e.g., RRC signaling, MAC CE), a specific signal/channel (e.g., PUCCH, PUSCH, reference signal), or a combination thereof.
- physical layer signaling e.g., UCI
- higher layer signaling e.g., RRC signaling, MAC CE
- a specific signal/channel e.g., PUCCH, PUSCH, reference signal
- the MAC CE may be identified by including a new LCID in the MAC subheader that is not specified in existing standards.
- the notification may be transmitted using PUCCH or PUSCH.
- notification of any information from the UE may be performed periodically, semi-persistently, or aperiodically.
- At least one of the above-mentioned embodiments may be applied when a specific condition is satisfied, which may be specified in a standard or may be notified to a UE/BS using higher layer signaling/physical layer signaling.
- At least one of the above-described embodiments may be applied only to UEs that have reported or support a particular UE capability.
- the specific UE capabilities may indicate at least one of the following: Supporting specific processing/operations/control/information for at least one of the above embodiments; Supporting beam prediction; Supporting reporting for beam predictions; Supporting beam reports that do not include L1-RSRP; Support reporting of beam information (at least one of top X probability, top X′/1 probability, etc.); Number of (supported) top-X or top-X'/1 probabilities in one reporting instance; The number of (supported) capability indexes in one reporting instance.
- the above-mentioned specific UE capabilities may be capabilities that are applied across all frequencies (commonly regardless of frequency), capabilities per frequency (e.g., one or a combination of a cell, band, band combination, BWP, component carrier, etc.), capabilities per frequency range (e.g., Frequency Range 1 (FR1), FR2, FR3, FR4, FR5, FR2-1, FR2-2), capabilities per subcarrier spacing (SubCarrier Spacing (SCS)), or capabilities per Feature Set (FS) or Feature Set Per Component-carrier (FSPC).
- FR1 Frequency Range 1
- FR2 FR2, FR3, FR4, FR5, FR2-1, FR2-2
- SCS subcarrier Spacing
- FS Feature Set
- FSPC Feature Set Per Component-carrier
- the specific UE capabilities may be capabilities that are applied across all duplexing methods (commonly regardless of the duplexing method), or may be capabilities for each duplexing method (e.g., Time Division Duplex (TDD) and Frequency Division Duplex (FDD)).
- TDD Time Division Duplex
- FDD Frequency Division Duplex
- the above-mentioned embodiments may be applied when the UE configures/activates/triggers specific information related to the above-mentioned embodiments (or performs the operations of the above-mentioned embodiments) by higher layer signaling/physical layer signaling.
- the specific information may be information indicating the enablement of the use of an AI model, information indicating the enablement of CSI prediction, information indicating the enablement of reporting of specific beam information, any RRC parameters for a specific release (e.g., Rel. 18/19), etc.
- the UE may, for example, apply Rel. 15/16 operations.
- a control unit that generates a beam report that does not include non-probabilistic measurement or prediction results regarding reception power or reception quality; A terminal having a transmitting unit that transmits the beam report.
- the control unit generates the beam report including a field indicating a resource and a field indicating a top X probability of the resource, where the top X probability is a probability that the result corresponding to the resource among one or more resources is equal to or greater than the Xth largest result among the results corresponding to the one or more resources.
- Appendix 3 The terminal of claim 1 or 2, wherein the control unit generates the beam report including a field indicating a top X'/1 probability for one or more resources, where the top X'/1 probability is the probability that at least one of the results corresponding to X' resources is the maximum among the results corresponding to the one or more resources.
- Wired communication system A configuration of a wireless communication system according to an embodiment of the present disclosure will be described below.
- communication is performed using any one of the wireless communication methods according to the above embodiments of the present disclosure or a combination of these.
- FIG. 10 is a diagram showing an example of a schematic configuration of a wireless communication system according to an embodiment.
- the wireless communication system 1 (which may simply be referred to as system 1) may be a system that realizes communication using Long Term Evolution (LTE) specified by the Third Generation Partnership Project (3GPP), 5th generation mobile communication system New Radio (5G NR), or the like.
- LTE Long Term Evolution
- 3GPP Third Generation Partnership Project
- 5G NR 5th generation mobile communication system New Radio
- the wireless communication system 1 may also support dual connectivity between multiple Radio Access Technologies (RATs) (Multi-RAT Dual Connectivity (MR-DC)).
- MR-DC may include dual connectivity between LTE (Evolved Universal Terrestrial Radio Access (E-UTRA)) and NR (E-UTRA-NR Dual Connectivity (EN-DC)), dual connectivity between NR and LTE (NR-E-UTRA Dual Connectivity (NE-DC)), etc.
- RATs Radio Access Technologies
- MR-DC may include dual connectivity between LTE (Evolved Universal Terrestrial Radio Access (E-UTRA)) and NR (E-UTRA-NR Dual Connectivity (EN-DC)), dual connectivity between NR and LTE (NR-E-UTRA Dual Connectivity (NE-DC)), etc.
- E-UTRA Evolved Universal Terrestrial Radio Access
- EN-DC E-UTRA-NR Dual Connectivity
- NE-DC NR-E-UTRA Dual Connectivity
- the LTE (E-UTRA) base station (eNB) is the master node (MN), and the NR base station (gNB) is the secondary node (SN).
- the NR base station (gNB) is the MN, and the LTE (E-UTRA) base station (eNB) is the SN.
- the wireless communication system 1 may support dual connectivity between multiple base stations within the same RAT (e.g., dual connectivity in which both the MN and SN are NR base stations (gNBs) (NR-NR Dual Connectivity (NN-DC))).
- dual connectivity in which both the MN and SN are NR base stations (gNBs) (NR-NR Dual Connectivity (NN-DC))).
- gNBs NR base stations
- N-DC Dual Connectivity
- the wireless communication system 1 may include a base station 11 that forms a macrocell C1 with a relatively wide coverage, and base stations 12 (12a-12c) that are arranged within the macrocell C1 and form a small cell C2 that is narrower than the macrocell C1.
- a user terminal 20 may be located within at least one of the cells. The arrangement and number of each cell and user terminal 20 are not limited to the aspect shown in the figure. Hereinafter, when there is no need to distinguish between the base stations 11 and 12, they will be collectively referred to as base station 10.
- the user terminal 20 may be connected to at least one of the multiple base stations 10.
- the user terminal 20 may utilize at least one of carrier aggregation (CA) using multiple component carriers (CC) and dual connectivity (DC).
- CA carrier aggregation
- CC component carriers
- DC dual connectivity
- Each CC may be included in at least one of a first frequency band (Frequency Range 1 (FR1)) and a second frequency band (Frequency Range 2 (FR2)).
- Macro cell C1 may be included in FR1
- small cell C2 may be included in FR2.
- FR1 may be a frequency band below 6 GHz (sub-6 GHz)
- FR2 may be a frequency band above 24 GHz (above-24 GHz). Note that the frequency bands and definitions of FR1 and FR2 are not limited to these, and for example, FR1 may correspond to a higher frequency band than FR2.
- the user terminal 20 may communicate using at least one of Time Division Duplex (TDD) and Frequency Division Duplex (FDD) in each CC.
- TDD Time Division Duplex
- FDD Frequency Division Duplex
- the multiple base stations 10 may be connected by wire (e.g., optical fiber conforming to the Common Public Radio Interface (CPRI), X2 interface, etc.) or wirelessly (e.g., NR communication).
- wire e.g., optical fiber conforming to the Common Public Radio Interface (CPRI), X2 interface, etc.
- NR communication e.g., NR communication
- base station 11 which corresponds to the upper station
- IAB Integrated Access Backhaul
- base station 12 which corresponds to a relay station
- the base station 10 may be connected to the core network 30 directly or via another base station 10.
- the core network 30 may include at least one of, for example, an Evolved Packet Core (EPC), a 5G Core Network (5GCN), a Next Generation Core (NGC), etc.
- EPC Evolved Packet Core
- 5GCN 5G Core Network
- NGC Next Generation Core
- the core network 30 may include network functions (Network Functions (NF)) such as, for example, a User Plane Function (UPF), an Access and Mobility management Function (AMF), a Session Management Function (SMF), a Unified Data Management (UDM), an Application Function (AF), a Data Network (DN), a Location Management Function (LMF), and Operation, Administration and Maintenance (Management) (OAM).
- NF Network Functions
- UPF User Plane Function
- AMF Access and Mobility management Function
- SMF Session Management Function
- UDM Unified Data Management
- AF Application Function
- DN Data Network
- LMF Location Management Function
- OAM Operation, Administration and Maintenance
- the user terminal 20 may be a terminal that supports at least one of the communication methods such as LTE, LTE-A, and 5G.
- a wireless access method based on Orthogonal Frequency Division Multiplexing may be used.
- OFDM Orthogonal Frequency Division Multiplexing
- CP-OFDM Cyclic Prefix OFDM
- DFT-s-OFDM Discrete Fourier Transform Spread OFDM
- OFDMA Orthogonal Frequency Division Multiple Access
- SC-FDMA Single Carrier Frequency Division Multiple Access
- the radio access method may also be called a waveform.
- other radio access methods e.g., other single-carrier transmission methods, other multi-carrier transmission methods
- a downlink shared channel (Physical Downlink Shared Channel (PDSCH)) shared by each user terminal 20, a broadcast channel (Physical Broadcast Channel (PBCH)), a downlink control channel (Physical Downlink Control Channel (PDCCH)), etc. may be used as the downlink channel.
- PDSCH Physical Downlink Shared Channel
- PBCH Physical Broadcast Channel
- PDCCH Physical Downlink Control Channel
- an uplink shared channel (Physical Uplink Shared Channel (PUSCH)) shared by each user terminal 20, an uplink control channel (Physical Uplink Control Channel (PUCCH)), a random access channel (Physical Random Access Channel (PRACH)), etc. may be used as an uplink channel.
- PUSCH Physical Uplink Shared Channel
- PUCCH Physical Uplink Control Channel
- PRACH Physical Random Access Channel
- SIB System Information Block
- PDSCH User data, upper layer control information, System Information Block (SIB), etc.
- SIB System Information Block
- PUSCH User data, upper layer control information, etc.
- MIB Master Information Block
- PBCH Physical Broadcast Channel
- Lower layer control information may be transmitted by the PDCCH.
- the lower layer control information may include, for example, downlink control information (Downlink Control Information (DCI)) including scheduling information for at least one of the PDSCH and the PUSCH.
- DCI Downlink Control Information
- the DCI for scheduling the PDSCH may be called a DL assignment or DL DCI
- the DCI for scheduling the PUSCH may be called a UL grant or UL DCI.
- the PDSCH may be interpreted as DL data
- the PUSCH may be interpreted as UL data.
- a control resource set (COntrol REsource SET (CORESET)) and a search space may be used to detect the PDCCH.
- the CORESET corresponds to the resources to search for DCI.
- the search space corresponds to the search region and search method of PDCCH candidates.
- One CORESET may be associated with one or multiple search spaces. The UE may monitor the CORESET associated with a search space based on the search space configuration.
- a search space may correspond to PDCCH candidates corresponding to one or more aggregation levels.
- One or more search spaces may be referred to as a search space set. Note that the terms “search space,” “search space set,” “search space setting,” “search space set setting,” “CORESET,” “CORESET setting,” etc. in this disclosure may be read as interchangeable.
- the PUCCH may transmit uplink control information (UCI) including at least one of channel state information (CSI), delivery confirmation information (which may be called, for example, Hybrid Automatic Repeat reQuest ACKnowledgement (HARQ-ACK), ACK/NACK, etc.), and a scheduling request (SR).
- UCI uplink control information
- CSI channel state information
- HARQ-ACK Hybrid Automatic Repeat reQuest ACKnowledgement
- ACK/NACK ACK/NACK
- SR scheduling request
- the PRACH may transmit a random access preamble for establishing a connection with a cell.
- downlink, uplink, etc. may be expressed without adding "link.”
- various channels may be expressed without adding "Physical” to the beginning.
- a synchronization signal (SS), a downlink reference signal (DL-RS), etc. may be transmitted.
- a cell-specific reference signal (CRS), a channel state information reference signal (CSI-RS), a demodulation reference signal (DMRS), a positioning reference signal (PRS), a phase tracking reference signal (PTRS), etc. may be transmitted.
- the synchronization signal may be, for example, at least one of a Primary Synchronization Signal (PSS) and a Secondary Synchronization Signal (SSS).
- a signal block including an SS (PSS, SSS) and a PBCH (and a DMRS for PBCH) may be called an SS/PBCH block, an SS Block (SSB), etc.
- the SS, SSB, etc. may also be called a reference signal.
- a measurement reference signal Sounding Reference Signal (SRS)
- a demodulation reference signal DMRS
- UL-RS uplink reference signal
- DMRS may also be called a user equipment-specific reference signal (UE-specific Reference Signal).
- the base station 11 is a diagram showing an example of a configuration of a base station according to an embodiment.
- the base station 10 includes a control unit 110, a transceiver unit 120, a transceiver antenna 130, and a transmission line interface 140. Note that one or more of each of the control unit 110, the transceiver unit 120, the transceiver antenna 130, and the transmission line interface 140 may be provided.
- this example mainly shows the functional blocks of the characteristic parts of this embodiment, and the base station 10 may also be assumed to have other functional blocks necessary for wireless communication. Some of the processing of each part described below may be omitted.
- the control unit 110 controls the entire base station 10.
- the control unit 110 can be configured from a controller, a control circuit, etc., which are described based on a common understanding in the technical field to which this disclosure pertains.
- the control unit 110 may control signal generation, scheduling (e.g., resource allocation, mapping), etc.
- the control unit 110 may control transmission and reception using the transceiver unit 120, the transceiver antenna 130, and the transmission path interface 140, measurement, etc.
- the control unit 110 may generate data, control information, sequences, etc. to be transmitted as signals, and transfer them to the transceiver unit 120.
- the control unit 110 may perform call processing of communication channels (setting, release, etc.), status management of the base station 10, management of radio resources, etc.
- the transceiver unit 120 may include a baseband unit 121, a radio frequency (RF) unit 122, and a measurement unit 123.
- the baseband unit 121 may include a transmission processing unit 1211 and a reception processing unit 1212.
- the transceiver unit 120 may be composed of a transmitter/receiver, an RF circuit, a baseband circuit, a filter, a phase shifter, a measurement circuit, a transceiver circuit, etc., which are described based on a common understanding in the technical field to which the present disclosure relates.
- the transceiver unit 120 may be configured as an integrated transceiver unit, or may be composed of a transmission unit and a reception unit.
- the transmission unit may be composed of a transmission processing unit 1211 and an RF unit 122.
- the reception unit may be composed of a reception processing unit 1212, an RF unit 122, and a measurement unit 123.
- the transmitting/receiving antenna 130 can be configured as an antenna described based on common understanding in the technical field to which this disclosure pertains, such as an array antenna.
- the transceiver 120 may transmit the above-mentioned downlink channel, synchronization signal, downlink reference signal, etc.
- the transceiver 120 may receive the above-mentioned uplink channel, uplink reference signal, etc.
- the transceiver 120 may form at least one of the transmit beam and the receive beam using digital beamforming (e.g., precoding), analog beamforming (e.g., phase rotation), etc.
- digital beamforming e.g., precoding
- analog beamforming e.g., phase rotation
- the transceiver 120 may perform Packet Data Convergence Protocol (PDCP) layer processing, Radio Link Control (RLC) layer processing (e.g., RLC retransmission control), Medium Access Control (MAC) layer processing (e.g., HARQ retransmission control), etc., on data and control information obtained from the control unit 110, and generate a bit string to be transmitted.
- PDCP Packet Data Convergence Protocol
- RLC Radio Link Control
- MAC Medium Access Control
- HARQ retransmission control HARQ retransmission control
- the transceiver 120 may perform transmission processing such as channel coding (which may include error correction coding), modulation, mapping, filtering, Discrete Fourier Transform (DFT) processing (if necessary), Inverse Fast Fourier Transform (IFFT) processing, precoding, and digital-to-analog conversion on the bit string to be transmitted, and output a baseband signal.
- transmission processing such as channel coding (which may include error correction coding), modulation, mapping, filtering, Discrete Fourier Transform (DFT) processing (if necessary), Inverse Fast Fourier Transform (IFFT) processing, precoding, and digital-to-analog conversion on the bit string to be transmitted, and output a baseband signal.
- channel coding which may include error correction coding
- DFT Discrete Fourier Transform
- IFFT Inverse Fast Fourier Transform
- the transceiver unit 120 may perform modulation, filtering, amplification, etc., on the baseband signal to a radio frequency band, and transmit the radio frequency band signal via the transceiver antenna 130.
- the transceiver unit 120 may perform amplification, filtering, demodulation to a baseband signal, etc. on the radio frequency band signal received by the transceiver antenna 130.
- the transceiver 120 may apply reception processing such as analog-to-digital conversion, Fast Fourier Transform (FFT) processing, Inverse Discrete Fourier Transform (IDFT) processing (if necessary), filtering, demapping, demodulation, decoding (which may include error correction decoding), MAC layer processing, RLC layer processing, and PDCP layer processing to the acquired baseband signal, and acquire user data, etc.
- reception processing such as analog-to-digital conversion, Fast Fourier Transform (FFT) processing, Inverse Discrete Fourier Transform (IDFT) processing (if necessary), filtering, demapping, demodulation, decoding (which may include error correction decoding), MAC layer processing, RLC layer processing, and PDCP layer processing to the acquired baseband signal, and acquire user data, etc.
- FFT Fast Fourier Transform
- IDFT Inverse Discrete Fourier Transform
- the transceiver 120 may perform measurements on the received signal.
- the measurement unit 123 may perform Radio Resource Management (RRM) measurements, Channel State Information (CSI) measurements, etc. based on the received signal.
- the measurement unit 123 may measure received power (e.g., Reference Signal Received Power (RSRP)), received quality (e.g., Reference Signal Received Quality (RSRQ), Signal to Interference plus Noise Ratio (SINR), Signal to Noise Ratio (SNR)), signal strength (e.g., Received Signal Strength Indicator (RSSI)), propagation path information (e.g., CSI), etc.
- RSRP Reference Signal Received Power
- RSSI Received Signal Strength Indicator
- the measurement results may be output to the control unit 110.
- the transmission path interface 140 may transmit and receive signals (backhaul signaling) between devices included in the core network 30 (e.g., network nodes providing NF), other base stations 10, etc., and may acquire and transmit user data (user plane data), control plane data, etc. for the user terminal 20.
- devices included in the core network 30 e.g., network nodes providing NF
- other base stations 10, etc. may acquire and transmit user data (user plane data), control plane data, etc. for the user terminal 20.
- the transmitter and receiver of the base station 10 in this disclosure may be configured with at least one of the transmitter/receiver 120, the transmitter/receiver antenna 130, and the transmission path interface 140.
- the transceiver 120 may transmit to the user terminal 20 setting information (e.g., CSI report setting) for generating a beam report that does not include non-probabilistic measurement or prediction results regarding received power or reception quality.
- the transceiver 120 may receive the beam report generated in the user terminal 20 based on the setting information.
- the user terminal 12 is a diagram showing an example of the configuration of a user terminal according to an embodiment.
- the user terminal 20 includes a control unit 210, a transceiver unit 220, and a transceiver antenna 230. Note that the control unit 210, the transceiver unit 220, and the transceiver antenna 230 may each include one or more.
- this example mainly shows the functional blocks of the characteristic parts of this embodiment, and the user terminal 20 may also be assumed to have other functional blocks necessary for wireless communication. Some of the processing of each part described below may be omitted.
- the control unit 210 controls the entire user terminal 20.
- the control unit 210 can be configured from a controller, a control circuit, etc., which are described based on a common understanding in the technical field to which this disclosure pertains.
- the control unit 210 may control signal generation, mapping, etc.
- the control unit 210 may control transmission and reception using the transceiver unit 220 and the transceiver antenna 230, measurement, etc.
- the control unit 210 may generate data, control information, sequences, etc. to be transmitted as signals, and transfer them to the transceiver unit 220.
- the transceiver unit 220 may include a baseband unit 221, an RF unit 222, and a measurement unit 223.
- the baseband unit 221 may include a transmission processing unit 2211 and a reception processing unit 2212.
- the transceiver unit 220 may be composed of a transmitter/receiver, an RF circuit, a baseband circuit, a filter, a phase shifter, a measurement circuit, a transceiver circuit, etc., which are described based on a common understanding in the technical field to which the present disclosure relates.
- the transceiver unit 220 may be configured as an integrated transceiver unit, or may be composed of a transmission unit and a reception unit.
- the transmission unit may be composed of a transmission processing unit 2211 and an RF unit 222.
- the reception unit may be composed of a reception processing unit 2212, an RF unit 222, and a measurement unit 223.
- the transmitting/receiving antenna 230 can be configured as an antenna described based on common understanding in the technical field to which this disclosure pertains, such as an array antenna.
- the transceiver 220 may receive the above-mentioned downlink channel, synchronization signal, downlink reference signal, etc.
- the transceiver 220 may transmit the above-mentioned uplink channel, uplink reference signal, etc.
- the transceiver 220 may form at least one of the transmit beam and receive beam using digital beamforming (e.g., precoding), analog beamforming (e.g., phase rotation), etc.
- digital beamforming e.g., precoding
- analog beamforming e.g., phase rotation
- the transceiver 220 may perform PDCP layer processing, RLC layer processing (e.g., RLC retransmission control), MAC layer processing (e.g., HARQ retransmission control), etc. on the data and control information acquired from the controller 210, and generate a bit string to be transmitted.
- RLC layer processing e.g., RLC retransmission control
- MAC layer processing e.g., HARQ retransmission control
- the transceiver 220 may perform transmission processing such as channel coding (which may include error correction coding), modulation, mapping, filtering, DFT processing (if necessary), IFFT processing, precoding, and digital-to-analog conversion on the bit string to be transmitted, and output a baseband signal.
- transmission processing such as channel coding (which may include error correction coding), modulation, mapping, filtering, DFT processing (if necessary), IFFT processing, precoding, and digital-to-analog conversion on the bit string to be transmitted, and output a baseband signal.
- Whether or not to apply DFT processing may be based on the settings of transform precoding.
- the transceiver unit 220 transmission processing unit 2211
- the transceiver unit 220 may perform DFT processing as the above-mentioned transmission processing in order to transmit the channel using a DFT-s-OFDM waveform, and when transform precoding is not enabled, it is not necessary to perform DFT processing as the above-mentioned transmission processing.
- the transceiver unit 220 may perform modulation, filtering, amplification, etc., on the baseband signal to a radio frequency band, and transmit the radio frequency band signal via the transceiver antenna 230.
- the transceiver unit 220 may perform amplification, filtering, demodulation to a baseband signal, etc. on the radio frequency band signal received by the transceiver antenna 230.
- the transceiver 220 may apply reception processing such as analog-to-digital conversion, FFT processing, IDFT processing (if necessary), filtering, demapping, demodulation, decoding (which may include error correction decoding), MAC layer processing, RLC layer processing, and PDCP layer processing to the acquired baseband signal to acquire user data, etc.
- reception processing such as analog-to-digital conversion, FFT processing, IDFT processing (if necessary), filtering, demapping, demodulation, decoding (which may include error correction decoding), MAC layer processing, RLC layer processing, and PDCP layer processing to the acquired baseband signal to acquire user data, etc.
- the transceiver 220 may perform measurements on the received signal. For example, the measurement unit 223 may perform RRM measurements, CSI measurements, etc. based on the received signal.
- the measurement unit 223 may measure received power (e.g., RSRP), received quality (e.g., RSRQ, SINR, SNR), signal strength (e.g., RSSI), propagation path information (e.g., CSI), etc.
- the measurement results may be output to the control unit 210.
- the transmitting unit and receiving unit of the user terminal 20 in this disclosure may be configured by at least one of the transmitting/receiving unit 220 and the transmitting/receiving antenna 230.
- the control unit 210 may generate a beam report that does not include non-probabilistic measurement or prediction results regarding reception power or reception quality (e.g., measured L1-RSRP/SINR, predicted L1-RSRP/SINR).
- the transceiver unit 220 may transmit the beam report.
- the control unit 210 generates the beam report including a field indicating a resource (e.g., a resource indicator field) and a field indicating the top X probability of the resource (a top X probability field), where the top X probability may be the probability that the result corresponding to the resource among one or more resources is equal to or greater than the Xth largest result among the results corresponding to the one or more resources.
- X may be an integer.
- the control unit 210 generates the beam report including a field (Top X'/1 Probability field) indicating the top X'/1 probability for one or more resources, where the top X'/1 probability may be the probability that at least one of the results corresponding to X' resources is the maximum among the results corresponding to the one or more resources.
- X' may be an integer.
- each functional block may be realized using one device that is physically or logically coupled, or may be realized using two or more devices that are physically or logically separated and directly or indirectly connected (for example, using wires, wirelessly, etc.).
- the functional blocks may be realized by combining the one device or the multiple devices with software.
- the functions include, but are not limited to, judgement, determination, judgment, calculation, computation, processing, derivation, investigation, search, confirmation, reception, transmission, output, access, resolution, selection, election, establishment, comparison, assumption, expectation, deeming, broadcasting, notifying, communicating, forwarding, configuring, reconfiguring, allocating, mapping, and assignment.
- a functional block (component) that performs the transmission function may be called a transmitting unit, a transmitter, and the like. In either case, as mentioned above, there are no particular limitations on the method of realization.
- a base station, a user terminal, etc. in one embodiment of the present disclosure may function as a computer that performs processing of the wireless communication method of the present disclosure.
- FIG. 13 is a diagram showing an example of the hardware configuration of a base station and a user terminal according to one embodiment.
- the above-mentioned base station 10 and user terminal 20 may be physically configured as a computer device including a processor 1001, a memory 1002, a storage 1003, a communication device 1004, an input device 1005, an output device 1006, a bus 1007, etc.
- the terms apparatus, circuit, device, section, unit, etc. may be interpreted as interchangeable.
- the hardware configuration of the base station 10 and the user terminal 20 may be configured to include one or more of the devices shown in the figures, or may be configured to exclude some of the devices.
- processor 1001 may be implemented by one or more chips.
- the functions of the base station 10 and the user terminal 20 are realized, for example, by loading specific software (programs) onto hardware such as the processor 1001 and memory 1002, causing the processor 1001 to perform calculations, control communications via the communication device 1004, and control at least one of the reading and writing of data in the memory 1002 and storage 1003.
- the processor 1001 for example, runs an operating system to control the entire computer.
- the processor 1001 may be configured as a central processing unit (CPU) including an interface with peripheral devices, a control device, an arithmetic unit, registers, etc.
- CPU central processing unit
- control unit 110 210
- transmission/reception unit 120 220
- etc. may be realized by the processor 1001.
- the processor 1001 also reads out programs (program codes), software modules, data, etc. from at least one of the storage 1003 and the communication device 1004 into the memory 1002, and executes various processes according to these.
- the programs used are those that cause a computer to execute at least some of the operations described in the above embodiments.
- the control unit 110 (210) may be realized by a control program stored in the memory 1002 and running on the processor 1001, and similar implementations may be made for other functional blocks.
- Memory 1002 is a computer-readable recording medium and may be composed of at least one of, for example, Read Only Memory (ROM), Erasable Programmable ROM (EPROM), Electrically EPROM (EEPROM), Random Access Memory (RAM), and other suitable storage media. Memory 1002 may also be called a register, cache, main memory, etc. Memory 1002 can store executable programs (program codes), software modules, etc. for implementing a wireless communication method according to one embodiment of the present disclosure.
- ROM Read Only Memory
- EPROM Erasable Programmable ROM
- EEPROM Electrically EPROM
- RAM Random Access Memory
- Memory 1002 may also be called a register, cache, main memory, etc.
- Memory 1002 can store executable programs (program codes), software modules, etc. for implementing a wireless communication method according to one embodiment of the present disclosure.
- Storage 1003 is a computer-readable recording medium and may be composed of at least one of a flexible disk, a floppy disk, a magneto-optical disk (e.g., a compact disk (Compact Disc ROM (CD-ROM)), a digital versatile disk, a Blu-ray disk), a removable disk, a hard disk drive, a smart card, a flash memory device (e.g., a card, a stick, a key drive), a magnetic stripe, a database, a server, or other suitable storage medium.
- Storage 1003 may also be referred to as an auxiliary storage device.
- the communication device 1004 is hardware (transmitting/receiving device) for communicating between computers via at least one of a wired network and a wireless network, and is also called, for example, a network device, a network controller, a network card, or a communication module.
- the communication device 1004 may be configured to include a high-frequency switch, a duplexer, a filter, a frequency synthesizer, etc., to realize at least one of Frequency Division Duplex (FDD) and Time Division Duplex (TDD).
- FDD Frequency Division Duplex
- TDD Time Division Duplex
- the above-mentioned transmitting/receiving unit 120 (220), transmitting/receiving antenna 130 (230), etc. may be realized by the communication device 1004.
- the transmitting/receiving unit 120 (220) may be implemented as a transmitting unit 120a (220a) and a receiving unit 120b (220b) that are physically or logically separated.
- the input device 1005 is an input device (e.g., a keyboard, a mouse, a microphone, a switch, a button, a sensor, etc.) that accepts input from the outside.
- the output device 1006 is an output device (e.g., a display, a speaker, a Light Emitting Diode (LED) lamp, etc.) that outputs to the outside.
- the input device 1005 and the output device 1006 may be integrated into one structure (e.g., a touch panel).
- each device such as the processor 1001 and memory 1002 is connected by a bus 1007 for communicating information.
- the bus 1007 may be configured using a single bus, or may be configured using different buses between each device.
- the base station 10 and the user terminal 20 may be configured to include hardware such as a microprocessor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a programmable logic device (PLD), or a field programmable gate array (FPGA), and some or all of the functional blocks may be realized using the hardware.
- the processor 1001 may be implemented using at least one of these pieces of hardware.
- a channel, a symbol, and a signal may be read as mutually interchangeable.
- a signal may also be a message.
- a reference signal may be abbreviated as RS, and may be called a pilot, a pilot signal, or the like depending on the applied standard.
- a component carrier may also be called a cell, a frequency carrier, a carrier frequency, or the like.
- a radio frame may be composed of one or more periods (frames) in the time domain.
- Each of the one or more periods (frames) constituting a radio frame may be called a subframe.
- a subframe may be composed of one or more slots in the time domain.
- a subframe may have a fixed time length (e.g., 1 ms) that is independent of numerology.
- the numerology may be a communication parameter that is applied to at least one of the transmission and reception of a signal or channel.
- the numerology may indicate, for example, at least one of the following: SubCarrier Spacing (SCS), bandwidth, symbol length, cyclic prefix length, Transmission Time Interval (TTI), number of symbols per TTI, radio frame configuration, a specific filtering process performed by the transceiver in the frequency domain, a specific windowing process performed by the transceiver in the time domain, etc.
- SCS SubCarrier Spacing
- TTI Transmission Time Interval
- radio frame configuration a specific filtering process performed by the transceiver in the frequency domain
- a specific windowing process performed by the transceiver in the time domain etc.
- a slot may consist of one or more symbols in the time domain (such as Orthogonal Frequency Division Multiplexing (OFDM) symbols, Single Carrier Frequency Division Multiple Access (SC-FDMA) symbols, etc.).
- OFDM Orthogonal Frequency Division Multiplexing
- SC-FDMA Single Carrier Frequency Division Multiple Access
- a slot may also be a time unit based on numerology.
- a slot may include multiple minislots. Each minislot may consist of one or multiple symbols in the time domain. A minislot may also be called a subslot. A minislot may consist of fewer symbols than a slot.
- a PDSCH (or PUSCH) transmitted in a time unit larger than a minislot may be called PDSCH (PUSCH) mapping type A.
- a PDSCH (or PUSCH) transmitted using a minislot may be called PDSCH (PUSCH) mapping type B.
- a radio frame, a subframe, a slot, a minislot, and a symbol all represent time units when transmitting a signal.
- a different name may be used for a radio frame, a subframe, a slot, a minislot, and a symbol, respectively.
- the time units such as a frame, a subframe, a slot, a minislot, and a symbol in this disclosure may be read as interchangeable.
- one subframe may be called a TTI
- multiple consecutive subframes may be called a TTI
- one slot or one minislot may be called a TTI.
- at least one of the subframe and the TTI may be a subframe (1 ms) in existing LTE, a period shorter than 1 ms (e.g., 1-13 symbols), or a period longer than 1 ms.
- the unit representing the TTI may be called a slot, minislot, etc., instead of a subframe.
- TTI refers to, for example, the smallest time unit for scheduling in wireless communication.
- a base station schedules each user terminal by allocating radio resources (such as frequency bandwidth and transmission power that can be used by each user terminal) in TTI units.
- radio resources such as frequency bandwidth and transmission power that can be used by each user terminal
- the TTI may be a transmission time unit for a channel-coded data packet (transport block), a code block, a code word, etc., or may be a processing unit for scheduling, link adaptation, etc.
- the time interval e.g., the number of symbols
- the time interval in which a transport block, a code block, a code word, etc. is actually mapped may be shorter than the TTI.
- one or more TTIs may be the minimum time unit of scheduling.
- the number of slots (minislots) that constitute the minimum time unit of scheduling may be controlled.
- a TTI having a time length of 1 ms may be called a normal TTI (TTI in 3GPP Rel. 8-12), normal TTI, long TTI, normal subframe, normal subframe, long subframe, slot, etc.
- a TTI shorter than a normal TTI may be called a shortened TTI, short TTI, partial or fractional TTI, shortened subframe, short subframe, minislot, subslot, slot, etc.
- a long TTI (e.g., a normal TTI, a subframe, etc.) may be interpreted as a TTI having a time length of more than 1 ms
- a short TTI e.g., a shortened TTI, etc.
- TTI length shorter than the TTI length of a long TTI and equal to or greater than 1 ms.
- a resource block is a resource allocation unit in the time domain and frequency domain, and may include one or more consecutive subcarriers in the frequency domain.
- the number of subcarriers included in an RB may be the same regardless of numerology, and may be, for example, 12.
- the number of subcarriers included in an RB may be determined based on numerology.
- an RB may include one or more symbols in the time domain and may be one slot, one minislot, one subframe, or one TTI in length.
- One TTI, one subframe, etc. may each be composed of one or more resource blocks.
- one or more RBs may be referred to as a physical resource block (Physical RB (PRB)), a sub-carrier group (Sub-Carrier Group (SCG)), a resource element group (Resource Element Group (REG)), a PRB pair, an RB pair, etc.
- PRB Physical RB
- SCG sub-carrier Group
- REG resource element group
- PRB pair an RB pair, etc.
- a resource block may be composed of one or more resource elements (REs).
- REs resource elements
- one RE may be a radio resource area of one subcarrier and one symbol.
- a Bandwidth Part which may also be referred to as a partial bandwidth, may represent a subset of contiguous common resource blocks (RBs) for a given numerology on a given carrier, where the common RBs may be identified by an index of the RB relative to a common reference point of the carrier.
- PRBs may be defined in a BWP and numbered within the BWP.
- the BWP may include a UL BWP (BWP for UL) and a DL BWP (BWP for DL).
- BWP UL BWP
- BWP for DL DL BWP
- One or more BWPs may be configured for a UE within one carrier.
- At least one of the configured BWPs may be active, and the UE may not expect to transmit or receive a given signal/channel outside the active BWP.
- BWP bitmap
- radio frames, subframes, slots, minislots, and symbols are merely examples.
- the number of subframes included in a radio frame, the number of slots per subframe or radio frame, the number of minislots included in a slot, the number of symbols and RBs included in a slot or minislot, the number of subcarriers included in an RB, as well as the number of symbols in a TTI, the symbol length, and the cyclic prefix (CP) length can be changed in various ways.
- the information, parameters, etc. described in this disclosure may be represented using absolute values, may be represented using relative values from a predetermined value, or may be represented using other corresponding information.
- a radio resource may be indicated by a predetermined index.
- the names used for parameters and the like in this disclosure are not limiting in any respect. Furthermore, the formulas and the like using these parameters may differ from those explicitly disclosed in this disclosure.
- the various channels (PUCCH, PDCCH, etc.) and information elements may be identified by any suitable names, and therefore the various names assigned to these various channels and information elements are not limiting in any respect.
- the information, signals, etc. described in this disclosure may be represented using any of a variety of different technologies.
- the data, instructions, commands, information, signals, bits, symbols, chips, etc. that may be referred to throughout the above description may be represented by voltages, currents, electromagnetic waves, magnetic fields or magnetic particles, optical fields or photons, or any combination thereof.
- information, signals, etc. may be output from a higher layer to a lower layer and/or from a lower layer to a higher layer.
- Information, signals, etc. may be input/output via multiple network nodes.
- Input/output information, signals, etc. may be stored in a specific location (e.g., memory) or may be managed using a management table. Input/output information, signals, etc. may be overwritten, updated, or added to. Output information, signals, etc. may be deleted. Input information, signals, etc. may be transmitted to another device.
- a specific location e.g., memory
- Input/output information, signals, etc. may be overwritten, updated, or added to.
- Output information, signals, etc. may be deleted.
- Input information, signals, etc. may be transmitted to another device.
- the notification of information is not limited to the aspects/embodiments described in this disclosure, and may be performed using other methods.
- the notification of information in this disclosure may be performed by physical layer signaling (e.g., Downlink Control Information (DCI), Uplink Control Information (UCI)), higher layer signaling (e.g., Radio Resource Control (RRC) signaling, broadcast information (Master Information Block (MIB), System Information Block (SIB)), etc.), Medium Access Control (MAC) signaling), other signals, or a combination of these.
- DCI Downlink Control Information
- UCI Uplink Control Information
- RRC Radio Resource Control
- MIB Master Information Block
- SIB System Information Block
- MAC Medium Access Control
- the physical layer signaling may be called Layer 1/Layer 2 (L1/L2) control information (L1/L2 control signal), L1 control information (L1 control signal), etc.
- the RRC signaling may be called an RRC message, for example, an RRC Connection Setup message, an RRC Connection Reconfiguration message, etc.
- the MAC signaling may be notified, for example, using a MAC Control Element (CE).
- CE MAC Control Element
- notification of specified information is not limited to explicit notification, but may be implicit (e.g., by not notifying the specified information or by notifying other information).
- the determination may be based on a value represented by a single bit (0 or 1), a Boolean value represented by true or false, or a comparison of numerical values (e.g., with a predetermined value).
- Software shall be construed broadly to mean instructions, instruction sets, code, code segments, program code, programs, subprograms, software modules, applications, software applications, software packages, routines, subroutines, objects, executable files, threads of execution, procedures, functions, etc., whether referred to as software, firmware, middleware, microcode, hardware description language, or otherwise.
- Software, instructions, information, etc. may also be transmitted and received via a transmission medium.
- a transmission medium For example, if the software is transmitted from a website, server, or other remote source using at least one of wired technologies (such as coaxial cable, fiber optic cable, twisted pair, Digital Subscriber Line (DSL)), and/or wireless technologies (such as infrared, microwave, etc.), then at least one of these wired and wireless technologies is included within the definition of a transmission medium.
- wired technologies such as coaxial cable, fiber optic cable, twisted pair, Digital Subscriber Line (DSL)
- wireless technologies such as infrared, microwave, etc.
- Network may refer to the devices included in the network (e.g., base stations).
- precoding "precoder,” “weight (precoding weight),” “Quasi-Co-Location (QCL),” “Transmission Configuration Indication state (TCI state),” "spatial relation,” “spatial domain filter,” “transmit power,” “phase rotation,” “antenna port,” “antenna port group,” “layer,” “number of layers,” “rank,” “resource,” “resource set,” “resource group,” “beam,” “beam width,” “beam angle,” “antenna,” “antenna element,” and “panel” may be used interchangeably.
- Base Station may also be referred to by terms such as macrocell, small cell, femtocell, picocell, etc.
- a base station can accommodate one or more (e.g., three) cells.
- a base station accommodates multiple cells, the entire coverage area of the base station can be divided into multiple smaller areas, and each smaller area can also provide communication services by a base station subsystem (e.g., a small base station for indoor use (Remote Radio Head (RRH))).
- RRH Remote Radio Head
- the term "cell” or “sector” refers to a part or the entire coverage area of at least one of the base station and base station subsystems that provide communication services in this coverage.
- a base station transmitting information to a terminal may be interpreted as the base station instructing the terminal to control/operate based on the information.
- MS Mobile Station
- UE User Equipment
- a mobile station may also be referred to as a subscriber station, mobile unit, subscriber unit, wireless unit, remote unit, mobile device, wireless device, wireless communication device, remote device, mobile subscriber station, access terminal, mobile terminal, wireless terminal, remote terminal, handset, user agent, mobile client, client, or some other suitable terminology.
- At least one of the base station and the mobile station may be called a transmitting device, a receiving device, a wireless communication device, etc.
- at least one of the base station and the mobile station may be a device mounted on a moving object, the moving object itself, etc.
- the moving body in question refers to an object that can move, and the moving speed is arbitrary, and of course includes the case where the moving body is stationary.
- the moving body in question includes, but is not limited to, vehicles, transport vehicles, automobiles, motorcycles, bicycles, connected cars, excavators, bulldozers, wheel loaders, dump trucks, forklifts, trains, buses, handcarts, rickshaws, ships and other watercraft, airplanes, rockets, artificial satellites, drones, multicopters, quadcopters, balloons, and objects mounted on these.
- the moving body in question may also be a moving body that moves autonomously based on an operating command.
- the moving object may be a vehicle (e.g., a car, an airplane, etc.), an unmanned moving object (e.g., a drone, an autonomous vehicle, etc.), or a robot (manned or unmanned).
- a vehicle e.g., a car, an airplane, etc.
- an unmanned moving object e.g., a drone, an autonomous vehicle, etc.
- a robot manned or unmanned
- at least one of the base station and the mobile station may also include devices that do not necessarily move during communication operations.
- at least one of the base station and the mobile station may be an Internet of Things (IoT) device such as a sensor.
- IoT Internet of Things
- FIG. 14 is a diagram showing an example of a vehicle according to an embodiment.
- the vehicle 40 includes a drive unit 41, a steering unit 42, an accelerator pedal 43, a brake pedal 44, a shift lever 45, left and right front wheels 46, left and right rear wheels 47, an axle 48, an electronic control unit 49, various sensors (including a current sensor 50, an RPM sensor 51, an air pressure sensor 52, a vehicle speed sensor 53, an acceleration sensor 54, an accelerator pedal sensor 55, a brake pedal sensor 56, a shift lever sensor 57, and an object detection sensor 58), an information service unit 59, and a communication module 60.
- various sensors including a current sensor 50, an RPM sensor 51, an air pressure sensor 52, a vehicle speed sensor 53, an acceleration sensor 54, an accelerator pedal sensor 55, a brake pedal sensor 56, a shift lever sensor 57, and an object detection sensor 58
- an information service unit 59 including a communication module 60.
- the drive unit 41 is composed of at least one of an engine, a motor, and a hybrid of an engine and a motor, for example.
- the steering unit 42 includes at least a steering wheel (also called a handlebar), and is configured to steer at least one of the front wheels 46 and the rear wheels 47 based on the operation of the steering wheel operated by the user.
- the electronic control unit 49 is composed of a microprocessor 61, memory (ROM, RAM) 62, and a communication port (e.g., an Input/Output (IO) port) 63. Signals are input to the electronic control unit 49 from various sensors 50-58 provided in the vehicle.
- the electronic control unit 49 may also be called an Electronic Control Unit (ECU).
- ECU Electronic Control Unit
- Signals from the various sensors 50-58 include a current signal from a current sensor 50 that senses the motor current, a rotation speed signal of the front wheels 46/rear wheels 47 acquired by a rotation speed sensor 51, an air pressure signal of the front wheels 46/rear wheels 47 acquired by an air pressure sensor 52, a vehicle speed signal acquired by a vehicle speed sensor 53, an acceleration signal acquired by an acceleration sensor 54, a depression amount signal of the accelerator pedal 43 acquired by an accelerator pedal sensor 55, a depression amount signal of the brake pedal 44 acquired by a brake pedal sensor 56, an operation signal of the shift lever 45 acquired by a shift lever sensor 57, and a detection signal for detecting obstacles, vehicles, pedestrians, etc. acquired by an object detection sensor 58.
- the information service unit 59 is composed of various devices, such as a car navigation system, audio system, speakers, displays, televisions, and radios, for providing (outputting) various information such as driving information, traffic information, and entertainment information, and one or more ECUs that control these devices.
- the information service unit 59 uses information acquired from external devices via the communication module 60, etc., to provide various information/services (e.g., multimedia information/multimedia services) to the occupants of the vehicle 40.
- various information/services e.g., multimedia information/multimedia services
- the information service unit 59 may include input devices (e.g., a keyboard, a mouse, a microphone, a switch, a button, a sensor, a touch panel, etc.) that accept input from the outside, and may also include output devices (e.g., a display, a speaker, an LED lamp, a touch panel, etc.) that perform output to the outside.
- input devices e.g., a keyboard, a mouse, a microphone, a switch, a button, a sensor, a touch panel, etc.
- output devices e.g., a display, a speaker, an LED lamp, a touch panel, etc.
- the driving assistance system unit 64 is composed of various devices that provide functions for preventing accidents and reducing the driver's driving load, such as a millimeter wave radar, a Light Detection and Ranging (LiDAR), a camera, a positioning locator (e.g., a Global Navigation Satellite System (GNSS)), map information (e.g., a High Definition (HD) map, an Autonomous Vehicle (AV) map, etc.), a gyro system (e.g., an Inertial Measurement Unit (IMU), an Inertial Navigation System (INS), etc.), an Artificial Intelligence (AI) chip, and an AI processor, and one or more ECUs that control these devices.
- the driving assistance system unit 64 also transmits and receives various information via the communication module 60 to realize a driving assistance function or an autonomous driving function.
- the communication module 60 can communicate with the microprocessor 61 and components of the vehicle 40 via the communication port 63.
- the communication module 60 transmits and receives data (information) via the communication port 63 between the drive unit 41, steering unit 42, accelerator pedal 43, brake pedal 44, shift lever 45, left and right front wheels 46, left and right rear wheels 47, axles 48, the microprocessor 61 and memory (ROM, RAM) 62 in the electronic control unit 49, and the various sensors 50-58 that are provided on the vehicle 40.
- the communication module 60 is a communication device that can be controlled by the microprocessor 61 of the electronic control unit 49 and can communicate with an external device. For example, it transmits and receives various information to and from the external device via wireless communication.
- the communication module 60 may be located either inside or outside the electronic control unit 49.
- the external device may be, for example, the above-mentioned base station 10 or user terminal 20.
- the communication module 60 may also be, for example, at least one of the above-mentioned base station 10 and user terminal 20 (it may function as at least one of the base station 10 and user terminal 20).
- the communication module 60 may transmit at least one of the signals from the various sensors 50-58 described above input to the electronic control unit 49, information obtained based on the signals, and information based on input from the outside (user) obtained via the information service unit 59 to an external device via wireless communication.
- the electronic control unit 49, the various sensors 50-58, the information service unit 59, etc. may be referred to as input units that accept input.
- the PUSCH transmitted by the communication module 60 may include information based on the above input.
- the communication module 60 receives various information (traffic information, signal information, vehicle distance information, etc.) transmitted from an external device and displays it on an information service unit 59 provided in the vehicle.
- the information service unit 59 may also be called an output unit that outputs information (for example, outputs information to a device such as a display or speaker based on the PDSCH (or data/information decoded from the PDSCH) received by the communication module 60).
- the communication module 60 also stores various information received from external devices in memory 62 that can be used by the microprocessor 61. Based on the information stored in memory 62, the microprocessor 61 may control the drive unit 41, steering unit 42, accelerator pedal 43, brake pedal 44, shift lever 45, left and right front wheels 46, left and right rear wheels 47, axles 48, various sensors 50-58, and the like provided on the vehicle 40.
- the base station in the present disclosure may be read as a user terminal.
- each aspect/embodiment of the present disclosure may be applied to a configuration in which communication between a base station and a user terminal is replaced with communication between multiple user terminals (which may be called, for example, Device-to-Device (D2D), Vehicle-to-Everything (V2X), etc.).
- the user terminal 20 may be configured to have the functions of the base station 10 described above.
- terms such as "uplink” and "downlink” may be read as terms corresponding to terminal-to-terminal communication (for example, "sidelink").
- the uplink channel, downlink channel, etc. may be read as the sidelink channel.
- the user terminal in this disclosure may be interpreted as a base station.
- the base station 10 may be configured to have the functions of the user terminal 20 described above.
- operations that are described as being performed by a base station may in some cases be performed by its upper node.
- a network that includes one or more network nodes having base stations, it is clear that various operations performed for communication with terminals may be performed by the base station, one or more network nodes other than the base station (such as, but not limited to, a Mobility Management Entity (MME) or a Serving-Gateway (S-GW)), or a combination of these.
- MME Mobility Management Entity
- S-GW Serving-Gateway
- each aspect/embodiment described in this disclosure may be used alone, in combination, or switched between depending on the implementation.
- the processing procedures, sequences, flow charts, etc. of each aspect/embodiment described in this disclosure may be rearranged as long as there is no inconsistency.
- the methods described in this disclosure present elements of various steps using an exemplary order, and are not limited to the particular order presented.
- LTE Long Term Evolution
- LTE-A LTE-Advanced
- LTE-B LTE-Beyond
- SUPER 3G IMT-Advanced
- 4th generation mobile communication system 4th generation mobile communication system
- 5G 5th generation mobile communication system
- 6G 6th generation mobile communication system
- xG x is, for example, an integer or decimal
- Future Radio Access FX
- GSM Global System for Mobile communications
- CDMA2000 Code Division Multiple Access
- UMB Ultra Mobile Broadband
- IEEE 802.11 Wi-Fi
- IEEE 802.16 WiMAX (registered trademark)
- IEEE 802.20 Ultra-WideBand (UWB), Bluetooth (registered trademark), and other appropriate wireless communication methods, as well as next-generation systems that are expanded, modified,
- the phrase “based on” does not mean “based only on,” unless expressly stated otherwise. In other words, the phrase “based on” means both “based only on” and “based at least on.”
- any reference to elements using designations such as “first,” “second,” etc., used in this disclosure does not generally limit the quantity or order of those elements. These designations may be used in this disclosure as a convenient method of distinguishing between two or more elements. Thus, a reference to a first and second element does not imply that only two elements may be employed or that the first element must precede the second element in some way.
- determining may encompass a wide variety of actions. For example, “determining” may be considered to be judging, calculating, computing, processing, deriving, investigating, looking up, search, inquiry (e.g., looking in a table, database, or other data structure), ascertaining, etc.
- Determining may also be considered to mean “determining” receiving (e.g., receiving information), transmitting (e.g., sending information), input, output, accessing (e.g., accessing data in a memory), etc.
- “Judgment” may also be considered to mean “deciding” to resolve, select, choose, establish, compare, etc.
- judgment may also be considered to mean “deciding” to take some kind of action.
- the "maximum transmit power" referred to in this disclosure may mean the maximum value of transmit power, may mean the nominal UE maximum transmit power, or may mean the rated UE maximum transmit power.
- connection and “coupled,” or any variation thereof, refer to any direct or indirect connection or coupling between two or more elements, and may include the presence of one or more intermediate elements between two elements that are “connected” or “coupled” to each other.
- the coupling or connection between the elements may be physical, logical, or a combination thereof. For example, "connected” may be read as "accessed.”
- a and B are different may mean “A and B are different from each other.”
- the term may also mean “A and B are each different from C.”
- Terms such as “separate” and “combined” may also be interpreted in the same way as “different.”
- words meaning “good,” “bad,” “big,” “small,” “high,” “low,” “fast,” “slow,” etc. may be read as interchangeable (without being limited to positive, comparative, or superlative).
- words meaning “good,” “bad,” “big,” “small,” “high,” “low,” “fast,” “slow,” etc. may be read as interchangeable (without being limited to positive, comparative, or superlative) with “ith” added (for example, “best” may be read as “ith best”).
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Abstract
A terminal according to one aspect of the present disclosure comprises: a control unit that generates a beam report that does not include non-probability measurement or prediction results regarding received power or reception quality; and a transmission unit that transmits the beam report. According to one aspect of the present disclosure, suitable overhead reduction, channel estimation, and resource utilization can be achieved.
Description
本開示は、次世代移動通信システムにおける端末、無線通信方法及び基地局に関する。
This disclosure relates to terminals, wireless communication methods, and base stations in next-generation mobile communication systems.
Universal Mobile Telecommunications System(UMTS)ネットワークにおいて、更なる高速データレート、低遅延などを目的としてLong Term Evolution(LTE)が仕様化された(非特許文献1)。また、LTE(Third Generation Partnership Project(3GPP(登録商標)) Release(Rel.)8、9)の更なる大容量、高度化などを目的として、LTE-Advanced(3GPP Rel.10-14)が仕様化された。
Long Term Evolution (LTE) was specified for Universal Mobile Telecommunications System (UMTS) networks with the aim of achieving higher data rates and lower latency (Non-Patent Document 1). In addition, LTE-Advanced (3GPP Rel. 10-14) was specified for the purpose of achieving higher capacity and greater sophistication over LTE (Third Generation Partnership Project (3GPP (registered trademark)) Release (Rel.) 8, 9).
LTEの後継システム(例えば、5th generation mobile communication system(5G)、5G+(plus)、6th generation mobile communication system(6G)、New Radio(NR)、3GPP Rel.15以降などともいう)も検討されている。
Successor systems to LTE (e.g., 5th generation mobile communication system (5G), 5G+ (plus), 6th generation mobile communication system (6G), New Radio (NR), 3GPP Rel. 15 and later, etc.) are also under consideration.
将来の無線通信技術について、ネットワーク/デバイスの制御、管理などに、機械学習(Machine Learning(ML))のような人工知能(Artificial Intelligence(AI))技術を活用することが検討されている。
In terms of future wireless communication technologies, the use of artificial intelligence (AI) technologies such as machine learning (ML) for network/device control and management is being considered.
AIモデルの活用のユースケースとして、空間ドメイン(spatial domain)下りリンク(Downlink(DL))ビーム予測、時間的(temporal)DLビーム予測などが検討されている。このようなビーム予測方法は、AIベースドビーム予測(ビーム報告)、AIベースドビーム管理(Beam Management(BM))などと呼ばれてもよい。時間的DLビーム予測は、例えば時間ドメインチャネル状態情報(Channel State Information(CSI))予測(prediction)などと呼ばれてもよい。
Spatial domain downlink (DL) beam prediction and temporal DL beam prediction are being considered as use cases for utilizing AI models. Such beam prediction methods may be called AI-based beam prediction (beam reporting) or AI-based beam management (BM). Temporal DL beam prediction may be called, for example, time domain Channel State Information (CSI) prediction.
ところで、上述したようなAIベースドビーム予測について、端末(terminal、ユーザ端末(user terminal)、User Equipment(UE))がビーム予測に関連してどのような情報をネットワークに送信するかについては、まだ検討が十分に行われていない。既存のビームレポートでは、UE側におけるモデル推論、ネットワーク側におけるデータ収集などが行われる場合に、適切な情報が送信できないおそれがある。
However, with regard to the AI-based beam prediction described above, there has been insufficient consideration as to what information a terminal (user terminal, User Equipment (UE)) should transmit to the network in relation to beam prediction. With existing beam reports, there is a risk that appropriate information may not be transmitted when model inference is performed on the UE side or data collection is performed on the network side.
このように、ビーム予測に関連する報告について十分な検討がなされなければ、ビーム予測に基づく適切なオーバーヘッド低減/高精度なチャネル推定/高効率なリソースの利用が達成できず、通信スループット/通信品質の向上が抑制されるおそれがある。
As such, unless sufficient consideration is given to reports related to beam prediction, appropriate overhead reduction, highly accurate channel estimation, and highly efficient resource utilization based on beam prediction may not be achieved, which may hinder improvements in communication throughput and communication quality.
そこで、本開示は、好適なオーバーヘッド低減/チャネル推定/リソースの利用を実現できる端末、無線通信方法及び基地局を提供することを目的の1つとする。
Therefore, one of the objectives of this disclosure is to provide a terminal, a wireless communication method, and a base station that can achieve optimal overhead reduction/channel estimation/resource utilization.
本開示の一態様に係る端末は、受信電力又は受信品質に関する、確率でない測定又は予測の結果を含まないビームレポートを生成する制御部と、前記ビームレポートを送信する送信部と、を有する。
A terminal according to one aspect of the present disclosure has a control unit that generates a beam report that does not include non-probabilistic measurement or prediction results regarding reception power or reception quality, and a transmission unit that transmits the beam report.
本開示の一態様によれば、好適なオーバーヘッド低減/チャネル推定/リソースの利用を実現できる。
According to one aspect of the present disclosure, it is possible to achieve optimal overhead reduction, channel estimation, and resource utilization.
(無線通信への人工知能(Artificial Intelligence(AI))技術の適用)
将来の無線通信技術について、ネットワーク/デバイスの制御、管理などに、機械学習(Machine Learning(ML))のようなAI技術を活用することが検討されている。 (Application of Artificial Intelligence (AI)) Technology to Wireless Communications)
Regarding future wireless communication technologies, the use of AI technologies such as machine learning (ML) for network/device control and management is being considered.
将来の無線通信技術について、ネットワーク/デバイスの制御、管理などに、機械学習(Machine Learning(ML))のようなAI技術を活用することが検討されている。 (Application of Artificial Intelligence (AI)) Technology to Wireless Communications)
Regarding future wireless communication technologies, the use of AI technologies such as machine learning (ML) for network/device control and management is being considered.
例えば、チャネル状態情報(Channel State Information(CSI))フィードバックの向上(例えば、オーバーヘッド低減、正確度改善、予測)、ビームマネジメントの改善(例えば、正確度改善、時間/空間領域での予測)、位置測定の改善(例えば、位置推定/予測の改善)などのために、端末(terminal、ユーザ端末(user terminal)、User Equipment(UE))/基地局(Base Station(BS))がAI技術を活用することが検討されている。
For example, it is being considered that terminals (user equipment (UE))/base stations (BS)) will utilize AI technology to improve channel state information (CSI) feedback (e.g., reducing overhead, improving accuracy, prediction), improve beam management (e.g., improving accuracy, prediction in the time/space domain), and improve position measurement (e.g., improving position estimation/prediction).
AIモデルは、入力される情報に基づいて、推定値、予測値、選択される動作、分類、などの少なくとも1つの情報を出力してもよい。UE/BSは、AIモデルに対して、チャネル状態情報、参照信号測定値などを入力して、高精度なチャネル状態情報/測定値/ビーム選択/位置、将来のチャネル状態情報/無線リンク品質などを出力してもよい。
The AI model may output at least one piece of information such as an estimate, a prediction, a selected action, a classification, etc. based on the input information. The UE/BS may input channel state information, reference signal measurements, etc. to the AI model, and output highly accurate channel state information/measurements/beam selection/position, future channel state information/radio link quality, etc.
なお、本開示において、AIは、以下の少なくとも1つの特徴を有する(実施する)オブジェクト(対象、客体、データ、関数、プログラムなどとも呼ばれる)で読み替えられてもよい:
・観測又は収集される情報に基づく推定、
・観測又は収集される情報に基づく選択、
・観測又は収集される情報に基づく予測。 In this disclosure, AI may be interpreted as an object (also called a target, object, data, function, program, etc.) having (implementing) at least one of the following characteristics:
- Estimation based on observed or collected information;
- making choices based on observed or collected information;
- Predictions based on observed or collected information.
・観測又は収集される情報に基づく推定、
・観測又は収集される情報に基づく選択、
・観測又は収集される情報に基づく予測。 In this disclosure, AI may be interpreted as an object (also called a target, object, data, function, program, etc.) having (implementing) at least one of the following characteristics:
- Estimation based on observed or collected information;
- making choices based on observed or collected information;
- Predictions based on observed or collected information.
本開示において、推定(estimation)、予測(prediction)、推論(inference)は、互いに読み替えられてもよい。また、本開示において、推定する(estimate)、予測する(predict)、推論する(infer)は、互いに読み替えられてもよい。
In this disclosure, estimation, prediction, and inference may be interpreted as interchangeable. Also, in this disclosure, estimate, predict, and infer may be interpreted as interchangeable.
本開示において、オブジェクトは、例えば、UE、BSなどの装置、デバイスなどであってもよい。また、本開示において、オブジェクトは、当該装置において動作するプログラム/モデル/エンティティに該当してもよい。
In the present disclosure, an object may be, for example, an apparatus such as a UE or a BS, or a device. Also, in the present disclosure, an object may correspond to a program/model/entity that operates in the apparatus.
また、本開示において、AIモデルは、以下の少なくとも1つの特徴を有する(実施する)オブジェクトで読み替えられてもよい:
・情報を与えること(feeding)によって、推定値を生み出す、
・情報を与えることによって、推定値を予測する、
・情報を与えることによって、特徴を発見する、
・情報を与えることによって、動作を選択する。 In addition, in the present disclosure, an AI model may be interpreted as an object having (implementing) at least one of the following characteristics:
- Producing estimates by feeding information,
- Predicting estimates by providing information
- Discover features by providing information,
- Select an action by providing information.
・情報を与えること(feeding)によって、推定値を生み出す、
・情報を与えることによって、推定値を予測する、
・情報を与えることによって、特徴を発見する、
・情報を与えることによって、動作を選択する。 In addition, in the present disclosure, an AI model may be interpreted as an object having (implementing) at least one of the following characteristics:
- Producing estimates by feeding information,
- Predicting estimates by providing information
- Discover features by providing information,
- Select an action by providing information.
また、本開示において、AIモデルは、AI技術を適用し、入力のセットに基づいて出力のセットを生成するデータドリブンアルゴリズムを意味してもよい。
In addition, in this disclosure, an AI model may refer to a data-driven algorithm that applies AI techniques to generate a set of outputs based on a set of inputs.
また、本開示において、AIモデル、モデル、MLモデル、予測分析(predictive analytics)、予測分析モデル、ツール、自己符号化器(オートエンコーダ(autoencoder))、エンコーダ、デコーダ、ニューラルネットワークモデル、AIアルゴリズム、スキームなどは、互いに読み替えられてもよい。また、AIモデルは、回帰分析(例えば、線形回帰分析、重回帰分析、ロジスティック回帰分析)、サポートベクターマシン、ランダムフォレスト、ニューラルネットワーク、ディープラーニングなどの少なくとも1つを用いて導出されてもよい。
Furthermore, in this disclosure, AI model, model, ML model, predictive analytics, predictive analysis model, tool, autoencoder, encoder, decoder, neural network model, AI algorithm, scheme, etc. may be interchangeable. Furthermore, the AI model may be derived using at least one of regression analysis (e.g., linear regression analysis, multiple regression analysis, logistic regression analysis), support vector machine, random forest, neural network, deep learning, etc.
本開示において、オートエンコーダは、積層オートエンコーダ、畳み込みオートエンコーダなど任意のオートエンコーダと互いに読み替えられてもよい。本開示のエンコーダ/デコーダは、Residual Network(ResNet)、DenseNet、RefineNetなどのモデルを採用してもよい。
In this disclosure, the term "autoencoder" may be interchangeably referred to as any autoencoder, such as a stacked autoencoder or a convolutional autoencoder. The encoder/decoder of this disclosure may employ models such as Residual Network (ResNet), DenseNet, and RefineNet.
また、本開示において、エンコーダ、エンコーディング(encoding)、エンコードする/される(encode/encoded)、エンコーダによる修正/変更/制御、圧縮(compressing)、圧縮する/される(compress/compressed)、生成(generating)、生成する/される(generate/generated)などは、互いに読み替えられてもよい。
Furthermore, in this disclosure, encoder, encoding, encoding/encoded, modification/alteration/control by an encoder, compressing, compress/compressed, generating, generate/generated, etc. may be read as interchangeable terms.
また、本開示において、デコーダ、デコーディング(decoding)、デコードする/される(decode/decoded)、デコーダによる修正/変更/制御、展開(decompressing)、展開する/される(decompress/decompressed)、再構成(reconstructing)、再構成する/される(reconstruct/reconstructed)などは、互いに読み替えられてもよい。
Furthermore, in this disclosure, the terms decoder, decoding, decode/decoded, modification/alteration/control by a decoder, decompressing, decompress/decompressed, reconstructing, reconstruct/reconstructed, etc. may be interpreted as interchangeable.
本開示において、(AIモデルについての)レイヤは、AIモデルにおいて利用されるレイヤ(入力層、中間層など)と互いに読み替えられてもよい。本開示のレイヤ(層)は、入力層、中間層、出力層、バッチ正規化層、畳み込み層、活性化層、デンス(dense)層、正規化層、プーリング層、アテンション層、ドロップアウト層、全結合層などの少なくとも1つに該当してもよい。
In the present disclosure, a layer (for an AI model) may be interpreted as a layer (input layer, intermediate layer, etc.) used in an AI model. A layer in the present disclosure may correspond to at least one of an input layer, intermediate layer, output layer, batch normalization layer, convolution layer, activation layer, dense layer, normalization layer, pooling layer, attention layer, dropout layer, fully connected layer, etc.
本開示において、AIモデルの訓練方法には、教師あり学習(supervised learning)、教師なし学習(unsupervised learning)、強化学習(Reinforcement learning)、連合学習(federated learning)などが含まれてもよい。教師あり学習は、入力及び対応するラベルからモデルを訓練する処理を意味してもよい。教師なし学習は、ラベル付きデータなしでモデルを訓練する処理を意味してもよい。強化学習は、モデルが相互作用している環境において、入力(言い換えると、状態)と、モデルの出力(言い換えると、アクション)から生じるフィードバック信号(言い換えると、報酬)と、からモデルを訓練する処理を意味してもよい。
In this disclosure, methods for training an AI model may include supervised learning, unsupervised learning, reinforcement learning, federated learning, and the like. Supervised learning may refer to the process of training a model from inputs and corresponding labels. Unsupervised learning may refer to the process of training a model without labeled data. Reinforcement learning may refer to the process of training a model from inputs (i.e., states) and feedback signals (i.e., rewards) resulting from the model's outputs (i.e., actions) in the environment with which the model interacts.
本開示において、生成、算出、導出などは、互いに読み替えられてもよい。本開示において、実施、運用、動作、実行などは、互いに読み替えられてもよい。本開示において、訓練、学習、更新、再訓練などは、互いに読み替えられてもよい。本開示において、推論、訓練後(after-training)、本番の利用、実際の利用、などは互いに読み替えられてもよい。本開示において、信号は、信号/チャネルと互いに読み替えられてもよい。
In this disclosure, terms such as generate, calculate, derive, etc. may be interchangeable. In this disclosure, terms such as implement, operate, operate, execute, etc. may be interchangeable. In this disclosure, terms such as train, learn, update, retrain, etc. may be interchangeable. In this disclosure, terms such as infer, after-training, live use, actual use, etc. may be interchangeable. In this disclosure, terms such as signal and signal/channel may be interchangeable.
図1は、AIモデルの管理のフレームワークの一例を示す図である。本例では、AIモデルに関連する各ステージがブロックで示されている。本例は、AIモデルのライフサイクル管理とも表現される。
Figure 1 shows an example of a framework for managing an AI model. In this example, each stage related to the AI model is shown as a block. This example is also expressed as life cycle management of an AI model.
データ収集ステージは、AIモデルの生成/更新のためのデータを収集する段階に該当する。データ収集ステージは、データ整理(例えば、どのデータをモデル訓練/モデル推論のために転送するかの決定)、データ転送(例えば、モデル訓練/モデル推論を行うエンティティ(例えば、UE、gNB)に対して、データを転送)などを含んでもよい。
The data collection stage corresponds to the stage of collecting data for generating/updating an AI model. The data collection stage may include data organization (e.g., determining which data to transfer for model training/model inference), data transfer (e.g., transferring data to an entity (e.g., UE, gNB) that performs model training/model inference), etc.
なお、データ収集は、AIモデル訓練/データ分析/推論を目的として、ネットワークノード、管理エンティティ又はUEによってデータが収集される処理を意味してもよい。本開示において、処理、手順は互いに読み替えられてもよい。また、本開示において、収集は、測定(チャネル測定、ビーム測定、無線リンク品質測定、位置推定など)に基づいてAIモデルの訓練/推論のための(例えば、入力/出力として利用できる)データセットを取得することを意味してもよい。
In addition, data collection may refer to a process in which data is collected by a network node, management entity, or UE for the purpose of AI model training/data analysis/inference. In this disclosure, process and procedure may be interpreted as interchangeable. In this disclosure, collection may also refer to obtaining a data set (e.g., usable as input/output) for training/inference of an AI model based on measurements (channel measurements, beam measurements, radio link quality measurements, position estimation, etc.).
本開示において、オフラインフィールドデータは、フィールド(現実世界)から収集され、AIモデルのオフライン訓練のために用いられるデータであってもよい。また、本開示において、オンラインフィールドデータは、フィールド(現実世界)から収集され、AIモデルのオンライン訓練のために用いられるデータであってもよい。
In the present disclosure, offline field data may be data collected from the field (real world) and used for offline training of an AI model. Also, in the present disclosure, online field data may be data collected from the field (real world) and used for online training of an AI model.
モデル訓練ステージでは、収集ステージから転送されるデータ(訓練用データ)に基づいてモデル訓練が行われる。このステージは、データ準備(例えば、データの前処理、クリーニング、フォーマット化、変換などの実施)、モデル訓練/バリデーション(検証)、モデルテスティング(例えば、訓練されたモデルが性能の閾値を満たすかの確認)、モデル交換(例えば、分散学習のためのモデルの転送)、モデルデプロイメント/更新(モデル推論を行うエンティティに対してモデルをデプロイ/更新)などを含んでもよい。
In the model training stage, model training is performed based on the data (training data) transferred from the collection stage. This stage may include data preparation (e.g., performing data preprocessing, cleaning, formatting, conversion, etc.), model training/validation, model testing (e.g., checking whether the trained model meets performance thresholds), model exchange (e.g., transferring the model for distributed learning), model deployment/update (deploying/updating the model to the entities that will perform model inference), etc.
なお、AIモデル訓練(AI model training)は、データドリブンな方法でAIモデルを訓練し、推論のための訓練されたAIモデルを取得するための処理を意味してもよい。
In addition, AI model training may refer to a process for training an AI model in a data-driven manner and obtaining a trained AI model for inference.
また、AIモデルバリデーション(AI model validation)は、モデル訓練に使用したデータセットとは異なるデータセットを用いてAIモデルの品質を評価するための訓練のサブ処理を意味してもよい。当該サブ処理は、モデル訓練に使用したデータセットを超えて汎化するモデルパラメータの選択に役立つ。
Also, AI model validation may refer to a sub-process of training to evaluate the quality of an AI model using a dataset different from the dataset used to train the model. This sub-process helps select model parameters that generalize beyond the dataset used to train the model.
また、AIモデルテスティング(AI model testing)は、モデル訓練/バリデーションに使用したデータセットとは異なるデータセットを使用して、最終的なAIモデルの性能を評価するための訓練のサブ処理を意味してもよい。なお、テスティングは、バリデーションとは異なり、その後のモデルチューニングを前提としなくてもよい。
Also, AI model testing may refer to a sub-process of training to evaluate the performance of the final AI model using a dataset different from the dataset used for model training/validation. Note that testing, unlike validation, does not necessarily require subsequent model tuning.
モデル推論ステージでは、収集ステージから転送されるデータ(推論用データ)に基づいてモデル推論が行われる。このステージは、データ準備(例えば、データの前処理、クリーニング、フォーマット化、変換などの実施)、モデル推論、モデルモニタリング(例えば、モデル推論の性能をモニタ)、モデル性能フィードバック(モデル訓練を行うエンティティに対してモデル性能をフィードバック)、出力(アクターに対してモデルの出力を提供)などを含んでもよい。
In the model inference stage, model inference is performed based on the data (inference data) transferred from the collection stage. This stage may include data preparation (e.g., performing data preprocessing, cleaning, formatting, transformation, etc.), model inference, model monitoring (e.g., monitoring the performance of model inference), model performance feedback (feeding back model performance to the entity performing the model training), and output (providing model output to the actor).
なお、AIモデル推論(AI model inference)は、訓練されたAIモデルを用いて入力のセットから出力のセットを産み出すための処理を意味してもよい。
In addition, AI model inference may refer to the process of using a trained AI model to produce a set of outputs from a set of inputs.
また、UE側(UE side)モデルは、その推論が完全にUEにおいて実施されるAIモデルを意味してもよい。ネットワーク側(Network side)モデルは、その推論が完全にネットワーク(例えば、gNB)において実施されるAIモデルを意味してもよい。
Also, a UE side model may refer to an AI model whose inference is performed entirely in the UE. A network side model may refer to an AI model whose inference is performed entirely in the network (e.g., gNB).
また、片側(one-sided)モデルは、UE側モデル又はネットワーク側モデルを意味してもよい。両側(two-sided)モデルは、共同推論(joint inference)が行われるペアのAIモデルを意味してもよい。ここで、共同推論は、その推論がUEとネットワークにわたって共同で行われるAI推論を含んでもよく、例えば、推論の第1の部分がUEによって最初に行われ、残りの部分がgNBによって行われてもよい(又はその逆が行われてもよい)。
Also, a one-sided model may refer to a UE-side model or a network-side model. A two-sided model may refer to a pair of AI models where joint inference is performed. Here, joint inference may include AI inference where the inference is performed jointly across the UE and the network, e.g., a first part of the inference may be performed first by the UE and the remaining part by the gNB (or vice versa).
また、AIモデルモニタリング(AI model monitoring)は、AIモデルの推論性能をモニタするための処理を意味してもよく、モデル性能モニタリング、性能モニタリングなどと互いに読み替えられてもよい。
Also, AI model monitoring may refer to the process of monitoring the inference performance of an AI model, and may be interchangeably read as model performance monitoring, performance monitoring, etc.
なお、モデル登録(モデルレジストレーション(model registration))は、モデルにバージョン識別子を付与し、推論段階において利用される特定のハードウェアにコンパイルすることを介して当該モデルを実行可能にする(登録(レジスター)する)ことを意味してもよい。また、モデル配置(モデルデプロイメント(model deployment))は、完全に開発されテストされたモデルのランタイムイメージ(又は実行環境のイメージ)を、推論が実施されるターゲット(例えば、UE/gNB)に配信する(又は当該ターゲットにおいて有効化する)ことを意味してもよい。
Note that model registration may refer to making a model executable (registering) through assigning a version identifier to the model and compiling it into the specific hardware used in the inference phase. Model deployment may refer to distributing (or activating at) a fully developed and tested run-time image (or an image of the execution environment) of the model to the target (e.g., UE/gNB) where inference will be performed.
アクターステージは、アクショントリガ(例えば、他のエンティティに対してアクションをトリガするか否かの決定)、フィードバック(例えば、訓練用データ/推論用データ/性能フィードバックのために必要な情報をフィードバック)などを含んでもよい。
Actor stages may include action triggers (e.g., deciding whether to trigger an action on another entity), feedback (e.g., feeding back information needed for training data/inference data/performance feedback), etc.
なお、例えばモビリティ最適化のためのモデルの訓練は、例えば、ネットワーク(Network(NW))における保守運用管理(Operation、Administration and Maintenance(Management)(OAM))/gNodeB(gNB)において行われてもよい。前者の場合、相互運用、大容量ストレージ、オペレータの管理性、モデルの柔軟性(フィーチャーエンジニアリングなど)が有利である。後者の場合、モデル更新のレイテンシ、モデル展開のためのデータ交換などが不要な点が有利である。上記モデルの推論は、例えば、gNBにおいて行われてもよい。
Note that, for example, training of a model for mobility optimization may be performed in, for example, Operation, Administration and Maintenance (Management) (OAM) in a network (NW)/gNodeB (gNB). In the former case, interoperability, large capacity storage, operator manageability, and model flexibility (feature engineering, etc.) are advantageous. In the latter case, the latency of model updates and the absence of data exchange for model deployment are advantageous. Inference of the above model may be performed in, for example, a gNB.
ユースケース(言い換えると、AIモデルの機能)に応じて、訓練/推論を行うエンティティは異なってもよい。AIモデルの機能(function)は、ビーム管理、ビーム予測、オートエンコーダ(又は情報圧縮)、CSIフィードバック、位置測位などを含んでもよい。
Depending on the use case (i.e., the function of the AI model), the entity performing the training/inference may be different. The function of the AI model may include beam management, beam prediction, autoencoder (or information compression), CSI feedback, positioning, etc.
例えば、メジャメントレポートに基づくAI支援ビーム管理については、OAM/gNBがモデル訓練を行い、gNBがモデル推論を行ってもよい。
For example, for AI-assisted beam management based on measurement reports, the OAM/gNB may perform model training and the gNB may perform model inference.
AI支援UEアシステッドポジショニングについては、Location Management Function(LMF)がモデル訓練を行い、当該LMFがモデル推論を行ってもよい。
For AI-assisted UE-assisted positioning, a Location Management Function (LMF) may perform model training and the LMF may perform model inference.
オートエンコーダを用いるCSIフィードバック/チャネル推定については、OAM/gNB/UEがモデル訓練を行い、gNB/UEが(ジョイントで)モデル推論を行ってもよい。
For CSI feedback/channel estimation using autoencoders, the OAM/gNB/UE may perform model training and the gNB/UE may perform model inference (jointly).
ビーム測定に基づくAI支援ビーム管理又はAI支援UEベースドポジショニングについては、OAM/gNB/UEがモデル訓練を行い、UEがモデル推論を行ってもよい。
For AI-assisted beam management or AI-assisted UE-based positioning based on beam measurements, the OAM/gNB/UE may perform model training and the UE may perform model inference.
なお、モデルアクティベーションは、特定の機能のためのAIモデルを有効化することを意味してもよい。モデルディアクティベーションは、特定の機能のためのAIモデルを無効化することを意味してもよい。モデルスイッチングは、特定の機能のための現在アクティブなAIモデルをディアクティベートし、異なるAIモデルをアクティベートすることを意味してもよい。
Note that model activation may mean activating an AI model for a particular function. Model deactivation may mean disabling an AI model for a particular function. Model switching may mean deactivating a currently active AI model for a particular function and activating a different AI model.
また、モデル転送(model transfer)は、エアインターフェース上でAIモデルを配信することを意味してもよい。この配信は、受信側において既知のモデル構造のパラメータ、又はパラメータを有する新しいモデルの一方又は両方を配信することを含んでもよい。また、この配信は、完全なモデル又は部分的なモデルを含んでもよい。モデルダウンロードは、ネットワークからUEへのモデル転送を意味してもよい。モデルアップロードは、UEからネットワークへのモデル転送を意味してもよい。
Model transfer may also refer to distributing an AI model over the air interface. This may include distributing either or both of the parameters of the model structure already known at the receiving end, or a new model with the parameters. This may also include a complete model or a partial model. Model download may refer to model transfer from the network to the UE. Model upload may refer to model transfer from the UE to the network.
(AIベースドビーム予測)
AIモデルの活用のユースケースとして、UE又はNWにおける片側AIモデルを用いる空間ドメイン(spatial domain)下りリンク(Downlink(DL))ビーム予測又は時間的(temporal)DLビーム予測が検討されている。このようなビーム予測方法は、AIベースドビーム予測(ビーム報告)、AIベースドビーム管理(Beam Management(BM))などと呼ばれてもよい。 (AI-based beam prediction)
As a use case of utilizing the AI model, spatial domain downlink (DL) beam prediction or temporal DL beam prediction using a one-sided AI model in the UE or NW is being considered. Such a beam prediction method may be called AI-based beam prediction (beam reporting), AI-based beam management (Beam Management (BM)), etc.
AIモデルの活用のユースケースとして、UE又はNWにおける片側AIモデルを用いる空間ドメイン(spatial domain)下りリンク(Downlink(DL))ビーム予測又は時間的(temporal)DLビーム予測が検討されている。このようなビーム予測方法は、AIベースドビーム予測(ビーム報告)、AIベースドビーム管理(Beam Management(BM))などと呼ばれてもよい。 (AI-based beam prediction)
As a use case of utilizing the AI model, spatial domain downlink (DL) beam prediction or temporal DL beam prediction using a one-sided AI model in the UE or NW is being considered. Such a beam prediction method may be called AI-based beam prediction (beam reporting), AI-based beam management (Beam Management (BM)), etc.
図2A及び2Bは、AIベースドビーム予測の一例を示す図である。図2Aは、空間ドメインDLビーム予測を示す。UEは、空間的に疎な(又は太い)ビームを測定して、測定結果などをAIモデルに入力し、空間的に密な(又は細い)ビームのビーム品質の予測結果を出力してもよい。
2A and 2B are diagrams showing an example of AI-based beam prediction. FIG. 2A shows spatial domain DL beam prediction. The UE may measure a spatially sparse (or thick) beam, input the measurement results, etc., to an AI model, and output a predicted result of the beam quality of a spatially dense (or thin) beam.
図2Bは、時間的DLビーム予測を示す。UEは、時系列のビームを測定して、測定結果などをAIモデルに入力し、将来のビームのビーム品質の予測結果を出力してもよい。
Figure 2B shows temporal DL beam prediction. The UE may measure the time series of beams, input the measurement results, etc. into an AI model, and output the predicted beam quality of the future beam.
なお、空間ドメインDLビーム予測は、BMケース1と呼ばれてもよいし、時間的DLビーム予測は、BMケース2と呼ばれてもよい。また、時間的DLビーム予測は、例えば時間ドメインCSI予測(CSI prediction)などと呼ばれてもよい。
Note that spatial domain DL beam prediction may be referred to as BM case 1, and temporal DL beam prediction may be referred to as BM case 2. Furthermore, temporal DL beam prediction may be referred to as, for example, time domain CSI prediction.
また、AIモデルの出力(予測結果)に関連するビームは、ビームのセットAと呼ばれてもよい。AIモデルの入力に関連するビームは、ビームのセットBと呼ばれてもよい。
Furthermore, the beams associated with the output (prediction result) of the AI model may be referred to as set of beams A. The beams associated with the input of the AI model may be referred to as set of beams B.
本開示において、セットAは、予測されるビームから選択されるビームに該当してもよい。セットAのためのリソースは、ビーム予測のためのリソース、ビーム報告のためのリソース、CSIレポートに含まれるリソース、セットA、セットAのリソース、第2(又は、第1)のセット、第2(又は、第1)のリソース、などと呼ばれてもよい。
In this disclosure, set A may correspond to beams selected from the predicted beams. Resources for set A may be referred to as resources for beam prediction, resources for beam reporting, resources included in a CSI report, set A, resources of set A, second (or first) set, second (or first) resources, etc.
本開示において、セットBは、その測定結果が(予測のためのAIモデル/関数の)入力に用いられるビームに該当してもよい。セットBのためのリソースは、ビーム測定のためのリソース、ビーム予測のインプットのためのリソース、セットB、セットBのリソース、第1(又は、第2)のセット、第1(又は、第2)のセットのリソース、などと呼ばれてもよい。
In this disclosure, set B may correspond to a beam whose measurement results are used as input (for the AI model/function for prediction). Resources for set B may be referred to as resources for beam measurements, resources for beam prediction input, set B, resources of set B, first (or second) set, resources of first (or second) set, etc.
BMケース1/2のAIモデルの入力の候補は、L1-RSRP(レイヤ1における参照信号受信電力(Layer 1 Reference Signal Received Power))、アシスタンス情報(例えば、ビーム形状情報、UE位置/方向情報、送信ビーム用途情報)、チャネルインパルス応答(Channel Impulse Response(CIR))の情報、対応するDL送信/受信ビームIDなどが挙げられる。
Candidates for input to the AI model for BM Case 1/2 include L1-RSRP (Layer 1 Reference Signal Received Power), assistance information (e.g., beam shape information, UE position/direction information, transmit beam usage information), Channel Impulse Response (CIR) information, and corresponding DL transmit/receive beam IDs.
BMケース1のAIモデルの出力の候補は、上位K個(Kは整数)の送信/受信ビームのID、これらのビームの予測L1-RSRP(predicted L1-RSRP)、各ビームが上位K個に入る確率、これらのビームの角度などが挙げられる。
Possible outputs of the AI model for BM Case 1 include the IDs of the top K (K is an integer) transmit/receive beams, the predicted L1-RSRP of these beams, the probability that each beam is in the top K, and the angles of these beams.
BMケース2のAIモデルの出力の候補は、BMケース1のAIモデルの出力の候補以外に、予測されるビーム障害が挙げられる。
In addition to the candidates for the output of the AI model in BM Case 1, the candidates for the output of the AI model in BM Case 2 include predicted beam failures.
(チャネル状態情報(Channel State Information(CSI))測定/報告)
既存のNR規格(例えば、Rel.15-17 NR)におけるCSI測定/報告について説明する。UEは、参照信号(Reference Signal(RS))(又は、当該RS用のリソース)に基づいてCSIを生成(決定、計算、推定、測定等ともいう)し、生成したCSIをネットワーク(例えば、基地局)に送信(報告、フィードバック等ともいう)する。当該CSIは、例えば、上りリンク制御チャネル(例えば、Physical Uplink Control Channel(PUCCH))又は上りリンク共有チャネル(例えば、Physical Uplink Shared Channel(PUSCH))を用いて基地局に送信されてもよい。 Channel State Information (CSI) Measurement/Reporting
CSI measurement/reporting in existing NR standards (e.g., Rel. 15-17 NR) will be described. The UE generates (also called determining, calculating, estimating, measuring, etc.) CSI based on a reference signal (RS) (or a resource for the RS) and transmits (also called reporting, feedback, etc.) the generated CSI to a network (e.g., a base station). The CSI may be transmitted to the base station using, for example, an uplink control channel (e.g., a Physical Uplink Control Channel (PUCCH)) or an uplink shared channel (e.g., a Physical Uplink Shared Channel (PUSCH)).
既存のNR規格(例えば、Rel.15-17 NR)におけるCSI測定/報告について説明する。UEは、参照信号(Reference Signal(RS))(又は、当該RS用のリソース)に基づいてCSIを生成(決定、計算、推定、測定等ともいう)し、生成したCSIをネットワーク(例えば、基地局)に送信(報告、フィードバック等ともいう)する。当該CSIは、例えば、上りリンク制御チャネル(例えば、Physical Uplink Control Channel(PUCCH))又は上りリンク共有チャネル(例えば、Physical Uplink Shared Channel(PUSCH))を用いて基地局に送信されてもよい。 Channel State Information (CSI) Measurement/Reporting
CSI measurement/reporting in existing NR standards (e.g., Rel. 15-17 NR) will be described. The UE generates (also called determining, calculating, estimating, measuring, etc.) CSI based on a reference signal (RS) (or a resource for the RS) and transmits (also called reporting, feedback, etc.) the generated CSI to a network (e.g., a base station). The CSI may be transmitted to the base station using, for example, an uplink control channel (e.g., a Physical Uplink Control Channel (PUCCH)) or an uplink shared channel (e.g., a Physical Uplink Shared Channel (PUSCH)).
本開示において、CSIは、チャネル品質インディケーター(Channel Quality Indicator(CQI))、プリコーディング行列インディケーター(Precoding Matrix Indicator(PMI))、CSI-RSリソースインディケーター(CSI-RS Resource Indicator(CRI))、SS/PBCHブロックリソースインディケーター(SS/PBCH Block Resource Indicator(SSBRI))、レイヤインディケーター(Layer Indicator(LI))、ランクインディケーター(Rank Indicator(RI))、L1-RSRP(レイヤ1における参照信号受信電力(Layer 1 Reference Signal Received Power))、L1-RSRQ(Reference Signal Received Quality)、L1-SINR(Signal to Interference plus Noise Ratio)、L1-SNR(Signal to Noise Ratio)、チャネル行列(又はチャネル係数)に関する情報、プリコーディング行列(又はプリコーディング係数)に関する情報、ビーム/Transmission Configuration Indication state(TCI状態)/空間関係(spatial relation)に関する情報などの少なくとも1つを含んでもよい。
In this disclosure, CSI includes a Channel Quality Indicator (CQI), a Precoding Matrix Indicator (PMI), a CSI-RS Resource Indicator (CRI), a SS/PBCH Block Resource Indicator (SSBRI), a Layer Indicator (LI), a Rank Indicator (RI), and a Layer 1 Reference Signal Received Power (L1-RSRP). It may include at least one of the following: L1-Reference Signal Received Power (L1-RSRQ), L1-SINR (Signal to Interference plus Noise Ratio), L1-SNR (Signal to Noise Ratio), information on the channel matrix (or channel coefficients), information on the precoding matrix (or precoding coefficients), information on the beam/Transmission Configuration Indication state (TCI state)/spatial relation, etc.
CSIの生成に用いられるRSは、例えば、チャネル状態情報参照信号(Channel State Information Reference Signal(CSI-RS))、同期信号/ブロードキャストチャネル(Synchronization Signal/Physical Broadcast Channel(SS/PBCH))ブロック、同期信号(Synchronization Signal(SS))、復調用参照信号(DeModulation Reference Signal(DMRS))などの少なくとも1つであってもよい。
The RS used to generate the CSI may be, for example, at least one of a Channel State Information Reference Signal (CSI-RS), a Synchronization Signal/Physical Broadcast Channel (SS/PBCH) block, a Synchronization Signal (SS), and a DeModulation Reference Signal (DMRS).
本開示において、RS、CSI-RS、ノンゼロパワー(Non Zero Power(NZP))CSI-RS、ゼロパワー(Zero Power(ZP))CSI-RS、CSI干渉測定(CSI Interference Measurement(CSI-IM))、CSI-SSB及びSSBは、互いに読み替えられてもよい。また、CSI-RSは、その他の参照信号を含んでもよい。
In this disclosure, RS, CSI-RS, Non Zero Power (NZP) CSI-RS, Zero Power (ZP) CSI-RS, CSI Interference Measurement (CSI-IM), CSI-SSB, and SSB may be interchangeable. In addition, CSI-RS may include other reference signals.
UEは、CSI報告に関する設定情報(CSI報告設定(CSI report configuration)、報告セッティング(report setting)などと呼ばれてもよい)を受信し、当該設定情報に基づいてCSI報告を制御してもよい。当該報告設定情報は、例えば、無線リソース制御(Radio Resource Control(RRC))情報要素(Information Element(IE))の「CSI-ReportConfig」であってもよい。
The UE may receive configuration information regarding CSI reporting (which may be referred to as CSI report configuration, report setting, etc.) and control CSI reporting based on the configuration information. The report configuration information may be, for example, a Radio Resource Control (RRC) Information Element (IE) "CSI-ReportConfig."
CSI報告設定は、以下の情報の少なくとも1つを含んでもよい:
・CSI測定に用いられるCSIリソースに関する情報(リソース設定ID、例えば、「CSI-ResourceConfigId」)、
・報告すべきCSIの1つ以上の量(quantity)(CSIパラメータ)に関する情報(報告量情報、例えば、「reportQuantity」)、
・報告設定の時間ドメインのふるまいを示す報告タイプ情報(例えば、「reportConfigType」)。 The CSI reporting configuration may include at least one of the following information:
Information regarding the CSI resources used for CSI measurements (resource configuration ID, for example, "CSI-ResourceConfigId");
Information regarding one or more quantities (CSI parameters) of CSI to be reported (report quantity information, e.g., "reportQuantity");
Report type information (eg, "reportConfigType") indicating the time domain behavior of the reporting configuration.
・CSI測定に用いられるCSIリソースに関する情報(リソース設定ID、例えば、「CSI-ResourceConfigId」)、
・報告すべきCSIの1つ以上の量(quantity)(CSIパラメータ)に関する情報(報告量情報、例えば、「reportQuantity」)、
・報告設定の時間ドメインのふるまいを示す報告タイプ情報(例えば、「reportConfigType」)。 The CSI reporting configuration may include at least one of the following information:
Information regarding the CSI resources used for CSI measurements (resource configuration ID, for example, "CSI-ResourceConfigId");
Information regarding one or more quantities (CSI parameters) of CSI to be reported (report quantity information, e.g., "reportQuantity");
Report type information (eg, "reportConfigType") indicating the time domain behavior of the reporting configuration.
本開示において、CSIリソースは、時間インスタンス、CSI-RS機会/CSI-IM機会/SSB機会、CSI-RSリソースの(1つ/複数の)機会、CSI機会、機会、CSI-RSリソース/CSI-IMリソース/SSBリソース、時間リソース、周波数リソース、アンテナポート(例えば、CSI-RSポート)などと互いに読み替えられてもよい。CSIリソースの時間単位は、スロット、シンボルなどであってもよい。
In the present disclosure, a CSI resource may be interchangeably referred to as a time instance, a CSI-RS opportunity/CSI-IM opportunity/SSB opportunity, a CSI-RS resource (one/multiple) opportunity, a CSI opportunity, an opportunity, a CSI-RS resource/CSI-IM resource/SSB resource, a time resource, a frequency resource, an antenna port (e.g., a CSI-RS port), etc. The time unit of a CSI resource may be a slot, a symbol, etc.
上記CSIリソースに関する情報は、チャネル測定のためのCSIリソースに関する情報、干渉測定のためのCSIリソース(NZP-CSI-RSリソース)に関する情報、干渉測定のためのCSI-IMリソースに関する情報などを含んでもよい。
The information on the CSI resources may include information on CSI resources for channel measurement, information on CSI resources for interference measurement (NZP-CSI-RS resources), information on CSI-IM resources for interference measurement, etc.
報告量情報は、上記CSIパラメータ(例えば、CRI、RI、PMI、CQI、LI、L1-RSRPなど)のいずれか又はこれらの組み合わせを指定してもよい。
The reporting amount information may specify any one of the above CSI parameters (e.g., CRI, RI, PMI, CQI, LI, L1-RSRP, etc.) or a combination of these.
報告タイプ情報は、周期的なCSI(Periodic CSI(P-CSI))報告、非周期的なCSI(Aperiodic CSI(A-CSI))報告、又は、半永続的(半持続的、セミパーシステント(Semi-Persistent))なCSI(Semi-Persistent CSI(SP-CSI))報告を示してもよい。
The report type information may indicate a periodic CSI (Periodic CSI (P-CSI)) report, an aperiodic CSI (A-CSI) report, or a semi-persistent CSI (Semi-Persistent CSI (SP-CSI)) report.
UEは、CSI報告設定に対応するCSIリソース設定(CSI-ResourceConfigIdに関連付けられるCSIリソース設定)に基づいて、CSI-RS/SSB/CSI-IMの測定を実施し、測定結果に基づいて報告するCSIを導出する。
The UE performs CSI-RS/SSB/CSI-IM measurements based on the CSI resource configuration corresponding to the CSI reporting configuration (CSI resource configuration associated with CSI-ResourceConfigId) and derives the CSI to report based on the measurement results.
CSIリソース設定(例えば、CSI-ResourceConfig情報要素)は、より具体的なCSI-RS/SSBのリソースを示すcsi-RS-ResourceSetListフィールド、リソース設定の時間ドメインのふるまいを示すリソースタイプ情報(例えば、「resourceType」)などを含んでもよい。
The CSI resource configuration (e.g., the CSI-ResourceConfig information element) may include a csi-RS-ResourceSetList field indicating more specific CSI-RS/SSB resources, resource type information (e.g., "resourceType") indicating the time domain behavior of the resource configuration, etc.
リソースタイプ情報は、P-CSIリソース、A-CSIリソース又はSP-CSIリソースを示してもよい。
The resource type information may indicate a P-CSI resource, an A-CSI resource, or an SP-CSI resource.
<CSIリソースのタイミング>
P/SP-CSIリソースのタイミング(例えば、送信/受信タイミング)は、CSIリソース設定に含まれる周期及びオフセットの情報(CSI-ResourcePeriodicityAndOffset)によって決定されてもよい。P/SP-CSIリソースは、オフセットを考慮して周期の倍数の位置に該当するスロットにおいて、送信されてもよい。 CSI Resource Timing
The timing of the P/SP-CSI resource (e.g., transmission/reception timing) may be determined by periodicity and offset information (CSI-ResourcePeriodicityAndOffset) included in the CSI resource configuration. The P/SP-CSI resource may be transmitted in a slot that corresponds to a position that is a multiple of the periodicity, taking the offset into account.
P/SP-CSIリソースのタイミング(例えば、送信/受信タイミング)は、CSIリソース設定に含まれる周期及びオフセットの情報(CSI-ResourcePeriodicityAndOffset)によって決定されてもよい。P/SP-CSIリソースは、オフセットを考慮して周期の倍数の位置に該当するスロットにおいて、送信されてもよい。 CSI Resource Timing
The timing of the P/SP-CSI resource (e.g., transmission/reception timing) may be determined by periodicity and offset information (CSI-ResourcePeriodicityAndOffset) included in the CSI resource configuration. The P/SP-CSI resource may be transmitted in a slot that corresponds to a position that is a multiple of the periodicity, taking the offset into account.
A-CSIリソースのタイミングは、設定されるオフセット(aperiodicTriggeringOffset)に基づいて決定されてもよい。当該オフセットは、A-CSIリソース/A-CSI報告をトリガするトリガリングDCI(例えば、特定のトリガ状態を示すCSIリクエストフィールドを含むDCI)からA-CSIリソースまでの時間差に該当してもよい。なお、設定されない場合には当該オフセットの値は0であってもよい。
The timing of the A-CSI resource may be determined based on a set offset (aperiodicTriggeringOffset). The offset may correspond to the time difference from a triggering DCI (e.g., a DCI including a CSI request field indicating a specific triggering state) that triggers the A-CSI resource/A-CSI report to the A-CSI resource. If not set, the value of the offset may be 0.
<CSI報告のタイミング>
P/SP-CSI報告(on PUCCH)の報告タイミングは、CSI報告設定に含まれる周期及びオフセットの情報(CSI-ReportPeriodicityAndOffset)によって決定されてもよい。P/SP-CSI報告(on PUCCH)は、オフセットを考慮して周期の倍数の位置に該当するスロットにおいて、送信されてもよい。 <Timing of CSI reporting>
The report timing of the P/SP-CSI report (on PUCCH) may be determined by information on the period and offset (CSI-ReportPeriodicityAndOffset) included in the CSI report configuration. The P/SP-CSI report (on PUCCH) may be transmitted in a slot corresponding to a position that is a multiple of the period, taking the offset into consideration.
P/SP-CSI報告(on PUCCH)の報告タイミングは、CSI報告設定に含まれる周期及びオフセットの情報(CSI-ReportPeriodicityAndOffset)によって決定されてもよい。P/SP-CSI報告(on PUCCH)は、オフセットを考慮して周期の倍数の位置に該当するスロットにおいて、送信されてもよい。 <Timing of CSI reporting>
The report timing of the P/SP-CSI report (on PUCCH) may be determined by information on the period and offset (CSI-ReportPeriodicityAndOffset) included in the CSI report configuration. The P/SP-CSI report (on PUCCH) may be transmitted in a slot corresponding to a position that is a multiple of the period, taking the offset into consideration.
SP-CSI報告(on PUSCH)のタイミングは、CSI報告設定に含まれるスロット周期の情報(reportSlotConfig)及びスロットオフセットの情報(reportSlotOffsetList)に基づいて決定されてもよい。SP-CSI報告(on PUSCH)は、SP-CSI報告をトリガするトリガリングDCIの受信を基準として、スロットオフセット後かつスロット周期の倍数の位置に該当するスロットにおいて、送信されてもよい。なお、スロットオフセットは、上記スロットオフセットの情報と、上記トリガリングDCIのフィールド(例えば、CSIリクエストフィールド)に基づいて決定されてもよい。
The timing of the SP-CSI report (on PUSCH) may be determined based on the slot period information (reportSlotConfig) and slot offset information (reportSlotOffsetList) included in the CSI report configuration. The SP-CSI report (on PUSCH) may be transmitted in a slot that is a multiple of the slot period after the slot offset based on the reception of the triggering DCI that triggers the SP-CSI report. The slot offset may be determined based on the slot offset information and a field of the triggering DCI (e.g., the CSI request field).
なお、SP-CSI測定/報告(on PUCCH)は、SP-CSI報告設定のアクティベーション/ディアクティベーションMAC CEの受信から、一定時間後に有効/無効になってもよい。また、SP-CSI測定/報告(on PUSCH)は、SP-CSI無線ネットワーク一時識別子(SP-CSI-Radio Network Temporary Identifier(RNTI))によってスクランブルされる巡回冗長検査(Cyclic Redundancy Check(CRC))が付加されるDCIフォーマット(例えば、DCIフォーマット0_1/0_2)に含まれるCSIリクエストフィールドによってアクティベートされるトリガ状態(例えば、SemiPersistentOnPUSCH-TriggerStateList情報要素に含まれるトリガ状態)に基づいて実施されてもよい。
In addition, SP-CSI measurement/reporting (on PUCCH) may be enabled/disabled a certain time after receiving the activation/deactivation MAC CE of the SP-CSI reporting setting. In addition, SP-CSI measurement/reporting (on PUSCH) may be performed based on a trigger state (e.g., a trigger state included in the SemiPersistentOnPUSCH-TriggerStateList information element) activated by a CSI request field included in a DCI format (e.g., DCI format 0_1/0_2) to which a Cyclic Redundancy Check (CRC) scrambled by the SP-CSI-Radio Network Temporary Identifier (RNTI)) is added.
A-CSI報告のタイミングは、CSI報告設定に含まれるスロットオフセットの情報(reportSlotOffsetList)に基づいて決定されてもよい。A-CSI報告は、A-CSI報告をトリガするトリガリングDCIの受信を基準として、スロットオフセット後のスロットにおいて、送信されてもよい。なお、スロットオフセットは、上記スロットオフセットの情報と、上記トリガリングDCIのフィールド(例えば、CSIリクエストフィールド)に基づいて決定されてもよい。
The timing of the A-CSI report may be determined based on slot offset information (reportSlotOffsetList) included in the CSI reporting configuration. The A-CSI report may be transmitted in a slot after the slot offset based on the reception of a triggering DCI that triggers the A-CSI report. The slot offset may be determined based on the slot offset information and a field of the triggering DCI (e.g., a CSI request field).
なお、1つより多いA-CSI報告がトリガリングDCIによって指定される場合には、当該1つより多いA-CSI報告についての複数のスロットオフセットの情報と、上記トリガリングDCIの時間ドメインリソース割り当てフィールドと、に基づいて、A-CSI報告のタイミングが決定されてもよい。
Note that if more than one A-CSI report is specified by the triggering DCI, the timing of the A-CSI report may be determined based on information of multiple slot offsets for the more than one A-CSI report and the time domain resource allocation field of the triggering DCI.
<CSI参照リソース>
既存のNR規格では、測定の時間制約に関する上位レイヤパラメータ(例えば、チャネル測定のための時間制約に関するtimeRestrictionForChannelMeasurements、干渉測定のためのtimeRestrictionForInterferenceMeasurementsなど)が設定される(当該パラメータの値が”configured”を示すことを意味してもよい)場合、CSI参照リソースより遅くない、CSI報告設定に関連する最近の(most recent)NZP CSI-RS機会(occasion)に基づいて、報告するCSIの算出のためのチャネル測定を導出することが規定されている。なお、本開示のチャネル測定は、干渉測定と互いに読み替えられてもよい。 <CSI Reference Resources>
In the existing NR standard, when a higher layer parameter related to a time constraint of a measurement (e.g., timeRestrictionForChannelMeasurements related to a time constraint for a channel measurement, timeRestrictionForInterferenceMeasurements for an interference measurement, etc.) is set (which may mean that the value of the parameter indicates "configured"), it is specified that a channel measurement for calculating the CSI to be reported is derived based on the most recent NZP CSI-RS occasion related to the CSI reporting configuration that is not later than the CSI reference resource. Note that the channel measurement in the present disclosure may be read as an interference measurement or the like.
既存のNR規格では、測定の時間制約に関する上位レイヤパラメータ(例えば、チャネル測定のための時間制約に関するtimeRestrictionForChannelMeasurements、干渉測定のためのtimeRestrictionForInterferenceMeasurementsなど)が設定される(当該パラメータの値が”configured”を示すことを意味してもよい)場合、CSI参照リソースより遅くない、CSI報告設定に関連する最近の(most recent)NZP CSI-RS機会(occasion)に基づいて、報告するCSIの算出のためのチャネル測定を導出することが規定されている。なお、本開示のチャネル測定は、干渉測定と互いに読み替えられてもよい。 <CSI Reference Resources>
In the existing NR standard, when a higher layer parameter related to a time constraint of a measurement (e.g., timeRestrictionForChannelMeasurements related to a time constraint for a channel measurement, timeRestrictionForInterferenceMeasurements for an interference measurement, etc.) is set (which may mean that the value of the parameter indicates "configured"), it is specified that a channel measurement for calculating the CSI to be reported is derived based on the most recent NZP CSI-RS occasion related to the CSI reporting configuration that is not later than the CSI reference resource. Note that the channel measurement in the present disclosure may be read as an interference measurement or the like.
また、既存のNR規格では、上記測定の時間制約に関する上位レイヤパラメータが設定されない(当該パラメータの値が”notConfigured”を示すことを意味してもよい)場合、CSI参照リソースより遅くない、CSI報告設定に関連するNZP CSI-RS機会(occasion)に基づいて、報告するCSIの算出のためのチャネル測定を導出することが規定されている。この場合、報告されるCSIは、1つ又は複数のNZP CSI-RS機会に基づいて導出されてもよい。
Also, in the existing NR standard, when an upper layer parameter related to the time constraint of the above measurement is not configured (which may mean that the value of the parameter indicates "notConfigured"), it is specified that the channel measurement for calculating the CSI to be reported is derived based on an NZP CSI-RS occasion associated with the CSI reporting configuration that is not later than the CSI reference resource. In this case, the reported CSI may be derived based on one or more NZP CSI-RS occasions.
サービングセルについて、ULスロットn’内におけるCSI報告のためのCSI参照リソースは、時間ドメインにおいて、単一のDLスロットn-nCSI_refによって定義される。nは、ULスロットn’に対応する(重複する)DLスロットに該当する。
For a serving cell, the CSI reference resource for CSI reporting in UL slot n′ is defined in the time domain by a single DL slot n−n CSI_ref , where n corresponds to the DL slot that corresponds (overlaps) with UL slot n′.
P/SP-CSI報告の場合、nCSI_refは、上記単一のDLスロットが有効なDLスロットに対応するような、最小の値(単一のCSI-RS/SSBリソースが設定される場合は4・2μDL以上の最小の値、複数のCSI-RS/SSBリソースが設定される場合は5・2μDL以上の最小の値)である。なお、μDLはDLのためのサブキャリア間隔の設定に該当する(例えば、μDL=0、1、2、3)。
In the case of P/SP-CSI reporting, n CSI_ref is the smallest value (minimum value of 4·2 μ DL when a single CSI-RS/SSB resource is configured, minimum value of 5·2 μ DL when multiple CSI-RS/SSB resources are configured) such that the single DL slot corresponds to a valid DL slot, where μ DL corresponds to the subcarrier spacing setting for DL (e.g. μ DL =0, 1, 2, 3).
A-CSI報告について、UEがCSIリクエストと同じスロットにおいてCSIを報告するようにトリガリングDCIによって指定される場合には、nCSI_refは、CSI参照リソースが対応するCSIリクエストと同じ有効なDLスロットにあるように決定されてもよく、そうでない場合には、nCSI_refは、上記単一のDLスロットが有効なDLスロットに対応するような、遅延要求に対応する特定の値以上の最小の値であってもよい。
For A-CSI reporting, if the triggering DCI specifies that the UE should report CSI in the same slot as the CSI request, then n CSI_ref may be determined such that the CSI reference resource is in the same valid DL slot as the corresponding CSI request; otherwise, n CSI_ref may be the minimum value equal to or greater than a certain value corresponding to a delay requirement, such that the single DL slot corresponds to a valid DL slot.
ところで、上述したようなAIベースドビーム予測について、UEがビーム予測に関連してどのような情報をNWに送信するかについては、まだ検討が十分に行われていない。既存のビームレポート(L1-RSRP/SINRなどの報告)では、UE側におけるモデル推論、NW側におけるデータ収集などが行われる場合に、適切な情報が送信できないおそれがある。
However, with regard to the AI-based beam prediction described above, there has been insufficient consideration as to what information the UE should transmit to the network in relation to beam prediction. With existing beam reports (reports of L1-RSRP/SINR, etc.), there is a risk that appropriate information may not be transmitted when model inference is performed on the UE side or data collection is performed on the network side.
このように、ビーム予測に関連する報告について十分な検討がなされなければ、ビーム予測に基づく適切なオーバーヘッド低減/高精度なチャネル推定/高効率なリソースの利用が達成できず、通信スループット/通信品質の向上が抑制されるおそれがある。
As such, unless sufficient consideration is given to reports related to beam prediction, appropriate overhead reduction, highly accurate channel estimation, and highly efficient resource utilization based on beam prediction may not be achieved, which may hinder improvements in communication throughput and communication quality.
そこで、本発明者らは、好適なビーム予測に関連する報告の内容/設定を着想した。なお、本開示の各実施形態は、AIが利用されない場合に適用されてもよい(例えば、関数を用いて予測が行われる場合に適用されてもよい)。
The inventors therefore came up with the idea of report content/settings related to suitable beam prediction. Note that each embodiment of the present disclosure may be applied when AI is not used (e.g., when prediction is performed using a function).
以下、本開示に係る実施形態について、図面を参照して詳細に説明する。各実施形態に係る無線通信方法は、それぞれ単独で適用されてもよいし、組み合わせて適用されてもよい。
Below, embodiments of the present disclosure will be described in detail with reference to the drawings. The wireless communication methods according to the embodiments may be applied independently or in combination.
本開示において、「A/B」及び「A及びBの少なくとも一方」は、互いに読み替えられてもよい。また、本開示において、「A/B/C」は、「A、B及びCの少なくとも1つ」を意味してもよい。
In this disclosure, "A/B" and "at least one of A and B" may be interpreted as interchangeable. Also, in this disclosure, "A/B/C" may mean "at least one of A, B, and C."
本開示において、通知、アクティベート、ディアクティベート、指示(又は指定(indicate))、選択(select)、設定(configure)、更新(update)、決定(determine)などは、互いに読み替えられてもよい。本開示において、サポートする、制御する、制御できる、動作する、動作できるなどは、互いに読み替えられてもよい。
In this disclosure, terms such as notify, activate, deactivate, indicate (or indicate), select, configure, update, and determine may be read as interchangeable. In this disclosure, terms such as support, control, capable of control, operate, and capable of operating may be read as interchangeable.
本開示において、無線リソース制御(Radio Resource Control(RRC))、RRCパラメータ、RRCメッセージ、上位レイヤパラメータ、フィールド、情報要素(Information Element(IE))、設定などは、互いに読み替えられてもよい。本開示において、Medium Access Control制御要素(MAC Control Element(CE))、更新コマンド、アクティベーション/ディアクティベーションコマンドなどは、互いに読み替えられてもよい。
In this disclosure, Radio Resource Control (RRC), RRC parameters, RRC messages, higher layer parameters, fields, information elements (IEs), settings, etc. may be interchangeable. In this disclosure, Medium Access Control (MAC Control Element (CE)), update commands, activation/deactivation commands, etc. may be interchangeable.
本開示において、上位レイヤシグナリングは、例えば、Radio Resource Control(RRC)シグナリング、Medium Access Control(MAC)シグナリング、ブロードキャスト情報、測位用プロトコル(例えば、NR Positioning Protocol A(NRPPa)/LTE Positioning Protocol(LPP))メッセージなどのいずれか、又はこれらの組み合わせであってもよい。
In the present disclosure, the higher layer signaling may be, for example, Radio Resource Control (RRC) signaling, Medium Access Control (MAC) signaling, broadcast information, positioning protocol (e.g., NR Positioning Protocol A (NRPPa)/LTE Positioning Protocol (LPP)) messages, or any combination thereof.
本開示において、MACシグナリングは、例えば、MAC制御要素(MAC Control Element(MAC CE))、MAC Protocol Data Unit(PDU)などを用いてもよい。ブロードキャスト情報は、例えば、マスタ情報ブロック(Master Information Block(MIB))、システム情報ブロック(System Information Block(SIB))、最低限のシステム情報(Remaining Minimum System Information(RMSI))、その他のシステム情報(Other System Information(OSI))などであってもよい。
In the present disclosure, the MAC signaling may use, for example, a MAC Control Element (MAC CE), a MAC Protocol Data Unit (PDU), etc. The broadcast information may be, for example, a Master Information Block (MIB), a System Information Block (SIB), Remaining Minimum System Information (RMSI), Other System Information (OSI), etc.
本開示において、物理レイヤシグナリングは、例えば、下りリンク制御情報(Downlink Control Information(DCI))、上りリンク制御情報(Uplink Control Information(UCI))などであってもよい。
In the present disclosure, the physical layer signaling may be, for example, Downlink Control Information (DCI), Uplink Control Information (UCI), etc.
本開示において、インデックス、識別子(Identifier(ID))、インディケーター、リソースIDなどは、互いに読み替えられてもよい。本開示において、シーケンス、リスト、セット、グループ、群、クラスター、サブセットなどは、互いに読み替えられてもよい。
In this disclosure, the terms index, identifier (ID), indicator, resource ID, etc. may be interchangeable. In this disclosure, the terms sequence, list, set, group, cluster, subset, etc. may be interchangeable.
本開示において、パネル、UEパネル、パネルグループ、ビーム、ビームグループ、プリコーダ、Uplink(UL)送信エンティティ、送受信ポイント(Transmission/Reception Point(TRP))、基地局、空間関係情報(Spatial Relation Information(SRI))、空間関係、SRSリソースインディケーター(SRS Resource Indicator(SRI))、制御リソースセット(COntrol REsource SET(CORESET))、Physical Downlink Shared Channel(PDSCH)、コードワード(Codeword(CW))、トランスポートブロック(Transport Block(TB))、参照信号(Reference Signal(RS))、アンテナポート(例えば、復調用参照信号(DeModulation Reference Signal(DMRS))ポート)、アンテナポートグループ(例えば、DMRSポートグループ)、グループ(例えば、空間関係グループ、符号分割多重(Code Division Multiplexing(CDM))グループ、参照信号グループ、CORESETグループ、Physical Uplink Control Channel(PUCCH)グループ、PUCCHリソースグループ)、リソース(例えば、参照信号リソース、SRSリソース)、リソースセット(例えば、参照信号リソースセット)、CORESETプール、下りリンクのTransmission Configuration Indication state(TCI状態)(DL TCI状態)、上りリンクのTCI状態(UL TCI状態)、統一されたTCI状態(unified TCI state)、共通TCI状態(common TCI state)、擬似コロケーション(Quasi-Co-Location(QCL))、QCL想定などは、互いに読み替えられてもよい。
In this disclosure, the terms panel, UE panel, panel group, beam, beam group, precoder, Uplink (UL) transmitting entity, Transmission/Reception Point (TRP), base station, Spatial Relation Information (SRI), spatial relation, SRS Resource Indicator (SRI), Control Resource Set (CONTROLLER RESOLUTION SET (CORESET)), Physical Downlink Shared Channel (PDSCH), Codeword (CW), Transport Block (TB), Reference Signal (RS), Antenna Port (e.g., DeModulation Reference Signal (DMRS)) port), Antenna Port group (e.g., DMRS port group), group (e.g., spatial relationship group, Code Division Multiplexing (CDM) group, reference signal group, CORESET group, Physical Uplink Control Channel (PUCCH) group, PUCCH resource group), resource (e.g., reference signal resource, SRS resource), resource set (e.g., reference signal resource set), CORESET pool, downlink Transmission Configuration Indication state (TCI state) (DL TCI state), uplink TCI state (UL TCI state), unified TCI state, common TCI state, quasi-co-location (QCL), QCL assumption, etc. may be read as interchangeable.
本開示において、タイミング、時刻、時間、時間インスタンス、スロット、サブスロット、シンボル、サブフレームなどは、互いに読み替えられてもよい。
In this disclosure, timing, time, duration, time instance, slot, subslot, symbol, subframe, etc. may be interpreted as interchangeable.
本開示において、チャネル測定/推定は、例えば、チャネル状態情報参照信号(Channel State Information Reference Signal(CSI-RS))、同期信号(Synchronization Signal(SS))、同期信号/ブロードキャストチャネル(Synchronization Signal/Physical Broadcast Channel(SS/PBCH))ブロック、復調用参照信号(DeModulation Reference Signal(DMRS))、測定用参照信号(Sounding Reference Signal(SRS))などの少なくとも1つを用いて行われてもよい。
In the present disclosure, channel measurement/estimation may be performed using at least one of, for example, a Channel State Information Reference Signal (CSI-RS), a Synchronization Signal (SS), a Synchronization Signal/Physical Broadcast Channel (SS/PBCH) block, a DeModulation Reference Signal (DMRS), a Sounding Reference Signal (SRS), etc.
なお、本開示において、チャネル状態、チャネルステータス、チャネル、チャネル環境などは、互いに読み替えられてもよい。
In addition, in this disclosure, channel state, channel status, channel, channel environment, etc. may be interpreted as interchangeable.
本開示において、UCI、CSIレポート、CSIフィードバック、フィードバック情報、フィードバックビット、CSIフィードバック方法、CSIフィードバックスキーム、ビームレポート、ビーム報告スキームなどは、互いに読み替えられてもよい。また、本開示において、ビット、ビット列、ビット系列、系列、値、情報、ビットから得られる値、ビットから得られる情報などは、互いに読み替えられてもよい。
In the present disclosure, UCI, CSI report, CSI feedback, feedback information, feedback bit, CSI feedback method, CSI feedback scheme, beam report, beam report scheme, etc. may be interchangeable. Also, in the present disclosure, bit, bit string, bit sequence, sequence, value, information, value obtained from a bit, information obtained from a bit, etc. may be interchangeable.
なお、本開示において、CSI-RSリソースセット、CSI-RSリソースセットの設定パラメータ、NZP CSI-RSリソースセット、NZP CSI-RSリソースセットの設定パラメータ(NZP-CSI-RS-ResourceSet)、CSI測定用SSBのリソースセットの設定パラメータ(CSI-SSB-ResourceSet)、CSI-IMのリソースセットの設定パラメータ(CSI-IM-ResourceSet)、は互いに読み替えられてもよい。
In addition, in this disclosure, the CSI-RS resource set, the configuration parameters of the CSI-RS resource set, the NZP CSI-RS resource set, the configuration parameters of the NZP CSI-RS resource set (NZP-CSI-RS-ResourceSet), the configuration parameters of the resource set of the SSB for CSI measurement (CSI-SSB-ResourceSet), and the configuration parameters of the CSI-IM resource set (CSI-IM-ResourceSet) may be read as interchangeable.
また、本開示において、CSI-RSリソース、CSI-RSリソースの設定パラメータ、NZP CSI-RSリソース、NZP CSI-RSリソースの設定パラメータ(NZP-CSI-RS-Resource)、CSIリソースなどは、互いに読み替えられてもよい。
Furthermore, in this disclosure, CSI-RS resources, CSI-RS resource configuration parameters, NZP CSI-RS resources, NZP CSI-RS resource configuration parameters (NZP-CSI-RS-Resource), CSI resources, etc. may be read as interchangeable.
本開示において、リソースは、参照信号リソースを意味してもよく、推薦される/予測される/測定されるリソースと互いに読み替えられてもよい。リソースは、時間/周波数/符号/空間ドメインなどのリソースを意味してもよい。本開示において、リソースは、リソースインディケーター、能力インデックス、ビームIDなどの少なくとも1つによって特定されてもよい。
In the present disclosure, a resource may refer to a reference signal resource and may be interchangeably read as a recommended/predicted/measured resource. A resource may refer to a resource in time/frequency/code/spatial domain, etc. In the present disclosure, a resource may be identified by at least one of a resource indicator, a capability index, a beam ID, etc.
本開示において、ビームは、推薦される/予測される/測定されるビームと互いに読み替えられてもよい。本開示において、ビーム及びリソースは互いに読み替えられてもよい。
In this disclosure, beam may be interchangeably referred to as recommended/predicted/measured beam. In this disclosure, beam and resource may be interchangeably referred to.
本開示において、L1-RSRPは、L1-RSRP/SINR、Layer-X(LX(例えば、X=1、2、3、…)-RSRP/SINR、RSRP/SINR、予測される/測定されるL1-RSRP/SINR、予測される/測定される値(予測値/測定値)、予測される/測定される受信電力又は受信品質に関する非確率値(確率でない測定/予測結果)、などと互いに読み替えられてもよい。また、本開示において、L1-RSRP、後述のトップX確率(top-X probability)、後述のトップX’/1確率(top-X’/1 probability)などは、上述したBMケース1/2のAIモデルの入力の候補(例えば、CIR)と互いに読み替えられてもよい。
In the present disclosure, L1-RSRP may be interchangeably read as L1-RSRP/SINR, Layer-X (LX (e.g., X=1, 2, 3, ...)-RSRP/SINR, RSRP/SINR, predicted/measured L1-RSRP/SINR, predicted/measured value (predicted value/measured value), non-probability value (non-probability measurement/prediction result) regarding predicted/measured received power or received quality, etc. Also, in the present disclosure, L1-RSRP, top-X probability (described below), top-X'/1 probability (described below), etc. may be interchangeably read as input candidates (e.g., CIR) for the AI model of BM case 1/2 described above.
(無線通信方法)
<第1の実施形態>
第1の実施形態は、ビーム予測のための(又はビーム予測に関連する)情報に関する。以下、当該情報をビーム情報とも呼ぶ。 (Wireless communication method)
First Embodiment
The first embodiment relates to information for (or related to) beam prediction, hereinafter also referred to as beam information.
<第1の実施形態>
第1の実施形態は、ビーム予測のための(又はビーム予測に関連する)情報に関する。以下、当該情報をビーム情報とも呼ぶ。 (Wireless communication method)
First Embodiment
The first embodiment relates to information for (or related to) beam prediction, hereinafter also referred to as beam information.
UEは、ビーム情報をネットワークに送信してもよい。ビーム情報には、以降で述べる情報の少なくとも1つが含まれてもよい。ビーム情報にどの情報を含めるかは、ネットワークからUEに通知されてもよいし、規格において規定されてもよいし、ビーム予測に用いるモデル(関連付けられるモデル)から導出されてもよい。また、ビーム情報は、UEが報告せずにネットワークからUEに通知される情報、規格において規定された値、ビーム予測に用いるモデル(関連付けられるモデル)などの少なくとも1つから導出されてもよい。
The UE may transmit beam information to the network. The beam information may include at least one of the pieces of information described below. The information to be included in the beam information may be notified to the UE by the network, may be specified in a standard, or may be derived from a model used for beam prediction (associated model). The beam information may also be derived from at least one of information notified to the UE by the network without being reported by the UE, values specified in a standard, a model used for beam prediction (associated model), etc.
ビーム情報は、リソースを示す情報を含んでもよい。当該リソースを示す情報は、リソースインディケーター、チャネルリソースインディケーターなどと呼ばれてもよく、例えば、SSBRI、CRI、SRSリソースインディケーターなどの少なくとも1つであってもよい。上記リソースインディケーターは、後述の時間インスタンス/継続時間に関連付けられてもよい(例えば、時間インスタンス/継続時間によって特定されてもよい)。本開示において、CRI/SSBRIはリソースインディケーターと互いに読み替えられてもよい。
The beam information may include information indicating a resource. The information indicating the resource may be called a resource indicator, a channel resource indicator, etc., and may be, for example, at least one of an SSBRI, a CRI, an SRS resource indicator, etc. The resource indicator may be associated with a time instance/duration (e.g., may be identified by a time instance/duration) as described below. In the present disclosure, CRI/SSBRI may be read as a resource indicator and vice versa.
ビーム情報は、リソースインディケーターの数を示す情報を含んでもよい。当該情報は、1つのビーム情報(報告インスタンスなどと呼ばれてもよい)に含まれるリソースインディケーターの数を示してもよい。なお、本開示において、報告インスタンスは、ビームレポート、CSIレポート、レポートなどと互いに読み替えられてもよい。
The beam information may include information indicating the number of resource indicators. The information may indicate the number of resource indicators included in one beam information (which may be referred to as a report instance, etc.). In this disclosure, a report instance may be interchangeably read as a beam report, a CSI report, a report, etc.
ビーム情報は、測定/予測のための能力インデックス(capability index)を示す情報を含んでもよい。能力インデックスは、対応するリソースインディケーターのためのパネルを示してもよく、パネルインデックス、UE能力バリュー、UE能力バリューセットなどと互いに読み替えられてもよい。本開示において、リソースインディケーターは、リソースインディケーター/能力インデックスと互いに読み替えられてもよい。
The beam information may include information indicating a capability index for measurement/prediction. The capability index may indicate a panel for a corresponding resource indicator and may be interchangeably read as a panel index, a UE capability value, a UE capability value set, etc. In the present disclosure, a resource indicator may be interchangeably read as a resource indicator/capability index.
ビーム情報は、ビームIDを示す情報を含んでもよい。ビームIDは、ビームに関連付けられてもよい。ビームIDは、特定の参照信号(例えば、CSI-RS、SSB、SRS、位置決定参照信号(Positioning Reference Signal(PRS)))に関連付けられてもよい。上記ビームIDは、後述の時間インスタンス/継続時間に関連付けられてもよい。
The beam information may include information indicating a beam ID. The beam ID may be associated with a beam. The beam ID may be associated with a particular reference signal (e.g., CSI-RS, SSB, SRS, Positioning Reference Signal (PRS)). The beam ID may be associated with a time instance/duration as described below.
ビーム情報は、L1-RSRPを示す情報を含んでもよい。L1-RSRPは、リソースに対応してもよい(リソースに基づいて測定/予測されてもよい)。L1-RSRPは、後述の時間インスタンス/継続時間に関連付けられてもよい。
The beam information may include information indicating the L1-RSRP. The L1-RSRP may correspond to a resource (or may be measured/predicted based on the resource). The L1-RSRP may be associated with a time instance/duration as described below.
ビーム情報は、トップX確率(top-X probability)を示す情報を含んでもよい。1つ以上のリソースのうちのあるリソースのトップX確率は、当該あるリソースに対応するRSRP又はSINRが、上記1つ以上のリソースに対応するRSRP又はSINRのうち、X番目に大きいRSRP又はSINR以上の値である確率/信頼度/信頼区間を意味してもよい。この信頼区間は、任意のパーセント(例えば、95%)の信頼区間であってもよい。
The beam information may include information indicating the top-X probability. The top-X probability of a resource among one or more resources may mean the probability/confidence/confidence interval that the RSRP or SINR corresponding to the resource is equal to or greater than the Xth largest RSRP or SINR among the RSRPs or SINRs corresponding to the one or more resources. This confidence interval may be an arbitrary percentage (e.g., 95%) confidence interval.
ビーム情報は、トップX’/1確率(top-X’/1 probability)を示す情報を含んでもよい。1つ以上のリソースに関するトップX’/1確率は、X’個のリソースに対応するRSRPの少なくとも1つが、上記1つ以上のリソースに対応するRSRP又はSINRのなかで最大となる確率/信頼度/信頼区間を意味してもよい。この信頼区間は、任意のパーセント(例えば、95%)の信頼区間であってもよい。なお、同じX’の値について、リソースの選び方によって異なるトップX’/1確率が得られる場合、これらのうちのいずれかの値(例えば、最大値)がトップX’/1確率として決定されてもよい。
The beam information may include information indicating the top-X'/1 probability. The top-X'/1 probability for one or more resources may mean the probability/confidence/confidence interval that at least one of the RSRPs corresponding to X' resources is the maximum among the RSRPs or SINRs corresponding to the one or more resources. This confidence interval may be an arbitrary percentage (e.g., 95%) confidence interval. Note that, for the same value of X', if different top-X'/1 probabilities are obtained depending on how the resources are selected, one of these values (e.g., the maximum value) may be determined as the top-X'/1 probability.
なお、L1-RSRP、トップX確率又はトップX’/1確率を示す情報は、他のL1-RSRP、トップX確率又はトップX’/1確率からの差分を示す情報(差分情報)を含んでもよい。
In addition, the information indicating the L1-RSRP, the top X probability, or the top X'/1 probability may include information indicating the difference from another L1-RSRP, the top X probability, or the top X'/1 probability (difference information).
L1-RSRP、トップX確率、トップX’/1確率を示す情報又はこれらについての差分情報は、量子化された情報(量子化情報)であってもよい。量子化情報は、L1-RSRP、トップX確率、トップX’/1確率又はこれらについての差分を、表現可能な特定の範囲について特定の量子化分解能(例えば、dBステップサイズ)で区分した特定数のビットによって表した情報(ビットが示す値が、いずれかのステップ(区分)に対応する)に該当してもよい。
The information indicating the L1-RSRP, the top X probability, the top X'/1 probability, or the difference information therefor may be quantized information (quantization information). The quantization information may correspond to information in which the L1-RSRP, the top X probability, the top X'/1 probability, or the difference therefor is represented by a specific number of bits divided by a specific quantization resolution (e.g., dB step size) for a specific expressible range (the value indicated by the bit corresponds to one of the steps (divisions)).
なお、差分情報の量子化情報は、差分でない情報の量子化情報よりも、少ないビット数で表現されることが好ましい(例えば、差分でない情報の量子化情報より、量子化分解能が低い又は表現可能な範囲が狭い)が、同じ又は多いビット数で表現されてもよい。
Note that the quantized information of the difference information is preferably represented with a smaller number of bits than the quantized information of non-differential information (e.g., the quantized resolution is lower or the expressible range is narrower than the quantized information of non-differential information), but it may be represented with the same or a larger number of bits.
上記X、X’、特定の範囲、特定の量子化分解能、特定数などに関する情報は、ネットワークからUEに通知されてもよいし、規格において規定されてもよいし、ビーム予測に用いるモデル(関連付けられるモデル)から導出されてもよいし、同じ報告インスタンス内の他の情報に基づいて決定されてもよい。
The information regarding X, X', the specific range, the specific quantization resolution, the specific number, etc. may be notified to the UE by the network, may be specified in a standard, may be derived from a model (associated model) used for beam prediction, or may be determined based on other information within the same reporting instance.
ビーム情報は、時間インスタンス(time instance)を示す情報(時間インスタンス情報)を含んでもよい。本開示において、時間インスタンスは、測定/予測される(言い換えると、測定/予測対象の)時間を意味してもよい。なお、時間インスタンスは、タイムスタンプと互いに読み替えられてもよい。
The beam information may include information indicating a time instance (time instance information). In the present disclosure, a time instance may mean a time to be measured/predicted (in other words, a time to be measured/predicted). Note that a time instance may be interchangeably read as a timestamp.
時間インスタンス情報は、リソースインディケーター/ビームIDに関連付けられる時間インスタンスを示すシンボルインデックス、シンボル数、(サブフレーム/フレーム内の)スロットインデックス、スロット数、システムフレーム番号、参照信号(リソース)の機会、などの少なくとも1つを示してもよい。
The time instance information may indicate at least one of a symbol index, a symbol number, a slot index (within a subframe/frame), a slot number, a system frame number, a reference signal (resource) opportunity, etc., that indicates the time instance associated with the resource indicator/beam ID.
時間インスタンスは、特定のタイミングを基準としてY個の時間単位(例えば、シンボル、スロット、ミリ秒、サブフレーム、フレームなど)前(過去)又は後(未来)のタイミングとして表現されてもよい。当該特定のタイミングは、例えば、CSI参照リソースの開始/終了タイミングであってもよいし、当該時間インスタンスを含むビーム情報が報告されるタイミングであってもよいし、測定/計測に用いたRSオケーション(機会)であってもよい。
The time instance may be expressed as a timing Y time units (e.g., symbols, slots, milliseconds, subframes, frames, etc.) before (past) or after (future) a specific timing. The specific timing may be, for example, the start/end timing of a CSI reference resource, the timing at which beam information including the time instance is reported, or the RS occasion used for measurement.
上記特定のタイミング、Yなどに関する情報は、ネットワークからUEに通知されてもよいし、規格において規定されてもよいし、ビーム予測に用いるモデル(関連付けられるモデル)から導出されてもよいし、同じ報告インスタンス内の他の情報に基づいて決定されてもよい。
The information regarding the specific timing, Y, etc. may be notified to the UE by the network, may be specified in a standard, may be derived from a model (associated model) used for beam prediction, or may be determined based on other information within the same reporting instance.
ビーム情報は、時間インスタンスの数を示す情報を含んでもよい。当該情報は、報告インスタンスに含まれる時間インスタンス情報の数を示してもよい。
The beam information may include information indicating the number of time instances. The information may indicate the number of time instance information included in the report instance.
ビーム情報は、継続時間(duration)を示す情報(継続時間情報)を含んでもよい。本開示において、継続時間は、測定/予測される時間の長さを意味してもよい。継続時間情報は、リソースインディケーター/ビームIDに関連付けられる時間の長さを示す時間単位(例えば、シンボル、スロット、ミリ秒、サブフレーム、フレーム、参照信号の機会など)の数を示してもよい。継続時間は、特定のタイミングを基準とする(例えば、特定のタイミング)からの継続期間としてもよい。例えば、CSI参照リソースの開始/終了タイミングであってもよいし、当該時間インスタンスを含むビーム情報が報告されるタイミングであってもよいし、測定/計測に用いたRSオケーション(機会)であってもよいし、特定の継続時間(例えば、前の継続時間)が終了してからの時間であってもよいし、上記の時間インスタンス情報によって示されてもよい。
The beam information may include information indicating a duration (duration information). In the present disclosure, duration may mean the length of time to be measured/predicted. The duration information may indicate the number of time units (e.g., symbols, slots, milliseconds, subframes, frames, reference signal opportunities, etc.) indicating the length of time associated with the resource indicator/beam ID. The duration may be a duration based on a specific timing (e.g., a specific timing). For example, it may be the start/end timing of the CSI reference resource, the timing when the beam information including the time instance is reported, the RS occasion used for the measurement, the time after the end of a specific duration (e.g., the previous duration), or may be indicated by the above time instance information.
ビーム情報は、継続時間の数を示す情報を含んでもよい。当該情報は、報告インスタンスに含まれる継続時間情報の数を示してもよい。
The beam information may include information indicating the number of durations. The information may indicate the number of duration information included in the report instance.
時間インスタンス/継続時間は、L1-RSRP、トップX確率又はトップX’/1確率に関連付けられてもよい。
The time instance/duration may be associated with the L1-RSRP, the top X probability or the top X'/1 probability.
ビーム情報は、セットAのためのビーム情報、セットBのためのビーム情報の少なくとも一方を含んでもよい。
The beam information may include at least one of beam information for set A and beam information for set B.
例えば、NW側のデータ収集については、UEは、セットBのビーム測定結果(L1-RSRPなど)を含むセットBのためのビーム情報を報告することが好ましい。また、NW側のデータ収集については、UEは、セットAのビーム測定結果(L1-RSRPなど)、又はビーム測定結果なしでセットAの(結果が)上位K(K≧1)個のビームを示す情報(例えば、リソースインディケーター)を含むセットAのためのビーム情報を報告することが好ましい。
For example, for network-side data collection, it is preferable for the UE to report beam information for set B including beam measurement results (such as L1-RSRP) of set B. Also, for network-side data collection, it is preferable for the UE to report beam information for set A including beam measurement results (such as L1-RSRP) of set A, or information (e.g., resource indicator) indicating the top K (K≧1) beams of set A without beam measurement results.
NW側のモデルモニタリングについては、UEは、セットAのビーム測定結果(L1-RSRPなど)、又はビーム測定結果なしでセットAの上位K(K≧1)個のビームを示す情報(例えば、リソースインディケーター)を含むセットAのためのビーム情報を報告することが好ましい。
For network-side model monitoring, it is preferable that the UE reports beam information for set A including beam measurement results (e.g., L1-RSRP) of set A, or information indicating the top K (K ≥ 1) beams of set A (e.g., resource indicators) without beam measurement results.
UE側においてモデル推論が行われる場合、UEは、セットAのビーム予測結果(L1-RSRPなど)、又はセットAの予測される上位K(K≧1)個のビームを示す情報(例えば、リソースインディケーター)を含むセットAのためのビーム情報を報告することが好ましい。当該セットAのためのビーム情報には、予測される時間のタイムスタンプも含まれてもよい。
When model inference is performed on the UE side, the UE preferably reports beam information for set A including beam prediction results (e.g., L1-RSRP) for set A or information (e.g., resource indicators) indicating the top K (K≧1) predicted beams of set A. The beam information for set A may also include a timestamp of the predicted time.
NW側においてモデル推論が行われる場合、UEは、セットBのビーム測定結果(L1-RSRPなど)を含むセットBのためのビーム情報を報告することが好ましい。当該セットBのためのビーム情報には、測定される時間のタイムスタンプも含まれてもよい。
When model inference is performed on the network side, it is preferable for the UE to report beam information for set B including beam measurement results (such as L1-RSRP) for set B. The beam information for set B may also include a timestamp of the time of measurement.
以上説明した第1の実施形態によれば、UEは、適切な情報を含むビーム情報を報告できる。
According to the first embodiment described above, the UE can report beam information including appropriate information.
<第2の実施形態>
第2の実施形態は、時間インスタンス/継続時間に関連付けられて報告される情報に関する。 Second Embodiment
The second embodiment relates to information reported that is associated with a time instance/duration.
第2の実施形態は、時間インスタンス/継続時間に関連付けられて報告される情報に関する。 Second Embodiment
The second embodiment relates to information reported that is associated with a time instance/duration.
第1の実施形態で述べたように、報告されるビーム情報のうちいくつかは、時間インスタンス/継続時間に関連付けられてもよい。
As mentioned in the first embodiment, some of the reported beam information may be associated with a time instance/duration.
例えば、UEは、ある時間インスタンス(例えば、あるスロット/シンボル、ある参照信号の機会)における値(例えば、L1-RSRP)を報告してもよい。
For example, the UE may report a value (e.g., L1-RSRP) at a certain time instance (e.g., a certain slot/symbol, a certain reference signal occasion).
また、例えば、UEは、ある継続時間に関連付けられるリソースインディケーター/ビームIDを報告してもよい。
Also, for example, the UE may report a resource indicator/beam ID associated with a certain duration.
図3は、時間インスタンス/継続時間の関係の一例を示す図である。本例では、UEは、推薦されるリソースインディケーターをネットワークに報告する。なお、推薦されるリソースインディケーターは、当該推薦されるリソースインディケーターが示す参照信号とQCL関係を有する信号の送信を基地局に推薦するために用いられてもよい。本例では、継続時間#0-#2はそれぞれCRI#0-#2に対応する。
Figure 3 shows an example of a time instance/duration relationship. In this example, the UE reports a recommended resource indicator to the network. The recommended resource indicator may be used to recommend to the base station the transmission of a signal that has a QCL relationship with the reference signal indicated by the recommended resource indicator. In this example, durations #0-#2 correspond to CRIs #0-#2, respectively.
ある継続時間は、1つ以上の時間インスタンスから決定されてもよい。例えば、継続時間#0は、特定のタイミング(例えば、CSI参照リソースの開始/終了タイミング、ビーム情報を報告する報告スロット、測定/計測に用いたRSオケーション(機会)など)から最初の時間インスタンス(時間インスタンス#1)までの間の期間に該当してもよい。継続時間#i(i≧1)は、i番目の時間インスタンス(例えば、時間インスタンス#1)からi+1番目の時間インスタンス(例えば、時間インスタンス#2)までの間の期間に該当してもよい。なお、継続時間#i(i≧1)は、i番目の時間インスタンス(例えば、時間インスタンス#1)以降の期間に該当してもよい(例えば、i+1番目の時間インスタンスが無い場合)。
A duration may be determined from one or more time instances. For example, duration #0 may correspond to the period between a specific timing (e.g., start/end timing of a CSI reference resource, a reporting slot for reporting beam information, an RS occasion used for measurement, etc.) and the first time instance (time instance #1). Duration #i (i≧1) may correspond to the period between the i-th time instance (e.g., time instance #1) and the i+1-th time instance (e.g., time instance #2). Note that duration #i (i≧1) may correspond to the period after the i-th time instance (e.g., time instance #1) (e.g., when there is no i+1-th time instance).
ある継続時間は、設定/規定される継続時間から決定されてもよい。例えば、UEは、継続時間#0として5msが設定/規定される場合には、上記特定のタイミングから5msの間が継続時間#0に該当すると判断してもよい。
A certain duration may be determined from a set/specified duration. For example, if 5 ms is set/specified as duration #0, the UE may determine that the period of 5 ms from the specific timing corresponds to duration #0.
以上説明した第2の実施形態によれば、測定/予測に関連する時間インスタンス/継続時間を適切に把握(特定)できる。
According to the second embodiment described above, it is possible to properly grasp (identify) the time instance/duration related to the measurement/prediction.
<第3の実施形態>
第3の実施形態は、L1-RSRPなしのビーム情報の報告に関する。 Third Embodiment
The third embodiment relates to reporting beam information without L1-RSRP.
第3の実施形態は、L1-RSRPなしのビーム情報の報告に関する。 Third Embodiment
The third embodiment relates to reporting beam information without L1-RSRP.
UEは、1つの報告インスタンスに、関連するL1-RSRPを含めずに、かつ、1つ以上のリソースに対応する1番目からZ番目に大きいL1-RSRPに対応するリソースインディケーターを含めて、当該報告インスタンスを送信してもよい。
The UE may transmit a report instance without including the associated L1-RSRP, but including resource indicators corresponding to the 1st through Zth highest L1-RSRPs corresponding to one or more resources.
上記1つ以上のリソース、Zなどに関する情報は、ネットワークからUEに通知されてもよいし、規格において規定されてもよいし、ビーム予測に用いるモデル(関連付けられるモデル)から導出されてもよいし、同じ報告インスタンス内の他の情報に基づいて決定されてもよい。
The information regarding the one or more resources, Z, etc., may be signaled to the UE by the network, may be specified in a standard, may be derived from a model used for beam prediction (associated model), or may be determined based on other information within the same reporting instance.
上記1つ以上のリソースは、セットAのためのリソースであってもよいし、セットBのためのリソースであってもよい。第3の実施形態の報告インスタンスは、主にセットA向けであってもよい。
The one or more resources may be resources for set A or may be resources for set B. The reporting instance of the third embodiment may be primarily intended for set A.
図4A及び4Bは、第3の実施形態におけるL1-RSRPを含まない報告インスタンスの一例を示す図である。本例の報告インスタンスは、CSIレポート(CSIレポート#X)である。なお、本開示の報告インスタンスに含まれるフィールドの順番は図示される順番に限られない(以降の図面でも同様)。
Figures 4A and 4B are diagrams showing an example of a report instance that does not include L1-RSRP in the third embodiment. The report instance in this example is a CSI report (CSI report #X). Note that the order of the fields included in the report instance of the present disclosure is not limited to the order shown in the figure (the same applies to subsequent figures).
図4A及び4Bは、いずれもL1-RSRPのフィールドを含まず、リソースインディケーターのフィールドであるCRI/SSBRIフィールドを含んでいる。なお、最初のCRI/SSBRIフィールド(CRI/SSBRI#1フィールド)が、最大のL1-RSRPに対応してもよいし、対応しなくてもよい。本例では、上記Z=4までが対応可能である(CSIレポートに4つまでのCRI/SSBRIフィールドが含まれる)が、CSIレポートに含まれるリソースインディケーターのフィールドの数はこれに限られない。
Both Figures 4A and 4B do not include an L1-RSRP field, but include a CRI/SSBRI field, which is a resource indicator field. Note that the first CRI/SSBRI field (CRI/SSBRI# 1 field) may or may not correspond to the largest L1-RSRP. In this example, up to Z=4 can be supported (up to four CRI/SSBRI fields are included in the CSI report), but the number of resource indicator fields included in the CSI report is not limited to this.
L1-RSRPを含まない報告インスタンスには、測定/予測のための能力インデックス(capability index)を示すフィールドが含まれてもよい。図4Aでは、1つの報告インスタンス内のCRI/SSBRIフィールドごとに、関連付けられる能力インデックスフィールドが報告される。図4Bでは、1つの報告インスタンス内の全CRI/SSBRIフィールドに関連付けられる1つの能力インデックスフィールドが報告される。
Reporting instances that do not include L1-RSRP may include a field indicating a capability index for measurement/prediction. In Figure 4A, for each CRI/SSBRI field in a reporting instance, an associated capability index field is reported. In Figure 4B, one capability index field is reported that is associated with all CRI/SSBRI fields in a reporting instance.
図4A及び4Bに示したように、L1-RSRPを含まない報告インスタンスによって、通信オーバーヘッドの削減が期待される。例えば、当該報告インスタンスは、データ収集のためのセットBのビーム情報の報告に好適である。また、当該報告インスタンスは、UE側におけるモデル推論のためのセットAのビーム情報の報告に好適である。
As shown in Figures 4A and 4B, a reporting instance that does not include L1-RSRP is expected to reduce communication overhead. For example, the reporting instance is suitable for reporting beam information of set B for data collection. Also, the reporting instance is suitable for reporting beam information of set A for model inference on the UE side.
L1-RSRPを含まない報告インスタンスには、第1の実施形態で述べたトップX確率又はトップX’/1確率を示すフィールドが含まれてもよい。UEは、1つの報告インスタンスに、関連するL1-RSRPを含めずに、かつ、1つ以上のリソースに対応する1番目からZ番目に大きいL1-RSRP又はトップX確率に対応するリソースインディケーターを含めて、当該報告インスタンスを送信してもよい。このとき、UEは、X’とZは同じ値であると想定(期待)してもよい。
A report instance that does not include an L1-RSRP may include a field indicating the top X probability or the top X'/1 probability as described in the first embodiment. The UE may transmit one report instance without including an associated L1-RSRP, and including resource indicators corresponding to the 1st to Zth largest L1-RSRPs or top X probabilities corresponding to one or more resources. In this case, the UE may assume (expect) that X' and Z are the same value.
図5A及び5Bは、第3の実施形態におけるL1-RSRPを含まない報告インスタンスの一例を示す図である。本例の報告インスタンスは、図4Bと類似するが、図5Aは各CRI/SSBRI#iフィールド(iは整数)に対応するトップX確率#iフィールドが含まれ、図5Bはトップ4/1確率フィールドが含まれる点が異なる。
Figures 5A and 5B are diagrams showing an example of a report instance that does not include an L1-RSRP in the third embodiment. The report instance in this example is similar to that in Figure 4B, except that Figure 5A includes a Top X Probability #i field corresponding to each CRI/SSBRI #i field (i is an integer), and Figure 5B includes a Top 4/1 Probability field.
本例において、最初のCRI/SSBRIフィールド(CRI/SSBRI#1フィールド)は、最大のL1-RSRPに対応してもよいし、最大のトップX確率に対応してもよい。言い換えると、トップX確率#1フィールドは、報告される最大のトップX確率を示してもよい。
In this example, the first CRI/SSBRI field (CRI/SSBRI# 1 field) may correspond to the largest L1-RSRP or the largest top-X probability. In other words, the Top-X Probability# 1 field may indicate the largest top-X probability reported.
図5Aにおいて、トップX確率#1フィールドが、報告される最大のトップX確率を示す場合、他のトップX確率#2-#4フィールドは、最大のトップX確率からの差分トップX確率を示してもよい。例えば、トップX確率#1フィールドが0.9、差分トップX確率#2フィールドが0.1を示す場合、トップX確率#2=0.9-0.1=0.8を意味してもよい。
In FIG. 5A, if the Top X Probability # 1 field indicates the maximum top X probability reported, the other Top X Probability #2-#4 fields may indicate the differential top X probability from the maximum top X probability. For example, if the Top X Probability # 1 field indicates 0.9 and the Differential Top X Probability # 2 field indicates 0.1, this may mean that Top X Probability # 2 = 0.9 - 0.1 = 0.8.
各CRI/SSBRIフィールドに対応するトップX確率フィールドが差分トップX確率フィールドではない場合、トップX確率#1フィールドが最大のトップX確率を示さなくてもよいため、各フィールドの配置の自由度が高い(また、UEが差分情報を求める必要がないため、UE負荷の軽減が期待される(特に、報告するフィールド数が多い場合))。
If the top X probability field corresponding to each CRI/SSBRI field is not a differential top X probability field, the top X probability # 1 field does not have to indicate the maximum top X probability, so there is a high degree of freedom in the placement of each field (and since the UE does not need to request differential information, it is expected that the UE load will be reduced (especially when there are a large number of fields to report)).
なお、報告インスタンスに含まれる各トップX確率フィールドについて、Xは同じ値であってもよいし、異なる値が許容されてもよい。例えば、同じCRI/SSBRIフィールドに対応して、トップ1確率フィールド、トップ2確率フィールド、…、トップZ確率フィールドなどが含まれてもよい。また、報告インスタンスに含まれるCRI/SSBRIフィールドに対応するトップX(Xは任意の値)確率フィールドの数は、CRI/SSBRIフィールドごとに異なってもよい。
Note that for each top X probability field included in a report instance, X may be the same value, or different values may be allowed. For example, a top 1 probability field, a top 2 probability field, ..., a top Z probability field, etc. may be included corresponding to the same CRI/SSBRI field. Also, the number of top X (X is any value) probability fields corresponding to the CRI/SSBRI fields included in a report instance may be different for each CRI/SSBRI field.
図5Bにおいて、CRI/SSBRI#iフィールドは、i番目に大きいL1-RSRPに対応してもよいし、i番目に大きいトップX確率に対応してもよいし、図示されるトップ4/1確率フィールドが示すトップ4/1確率に関連するCRI/SSBRI(例えば、最大のL1-RSRPとなる確率が高いCRI/SSBRI)を示してもよい。
In FIG. 5B, the CRI/SSBRI#i field may correspond to the i-th largest L1-RSRP, or may correspond to the i-th largest top X probability, or may indicate a CRI/SSBRI related to the top 4/1 probability indicated by the illustrated top 4/1 probability field (e.g., a CRI/SSBRI that is likely to be the largest L1-RSRP).
図示されるトップ4/1確率フィールドは、報告インスタンス内のCRI/SSBRIフィールドの数に応じて別のトップX’/1確率フィールドとしてもよい。例えば、報告インスタンス内のCRI/SSBRIフィールドの数が1、2、3の場合には、トップ4/1確率フィールドの代わりにそれぞれ、トップ1/1確率フィールド、トップ2/1確率フィールド、トップ3/1確率フィールドが含まれてもよい。図示されるトップ4/1確率フィールドは、トップZ/1確率フィールドに該当してもよい(X’=Z)。
The illustrated Top 4/1 probability field may be a different Top X'/1 probability field depending on the number of CRI/SSBRI fields in the reporting instance. For example, if the number of CRI/SSBRI fields in the reporting instance is 1, 2, or 3, a Top 1/1 probability field, a Top 2/1 probability field, or a Top 3/1 probability field may be included instead of the Top 4/1 probability field, respectively. The illustrated Top 4/1 probability field may correspond to a Top Z/1 probability field (X'=Z).
なお、報告インスタンスには複数のトップX’/1確率フィールドが含まれてもよい。例えば、UEは、報告インスタンスに、トップi/1確率フィールド(i=1、…、Z)から1つ以上を含めてもよい。
Note that a reporting instance may include multiple top X'/1 probability fields. For example, the UE may include one or more of the top i/1 probability fields (i = 1, ..., Z) in a reporting instance.
図5A及び5Bに示したように、トップX確率又はトップX’/1確率フィールドを含む報告インスタンスを利用することによって、トップX確率又はトップX’/1確率を出力として提供するAIモデルを好適に利用できる。
As shown in Figures 5A and 5B, by utilizing a report instance that includes a Top X Probability or Top X'/1 Probability field, an AI model that provides the Top X Probability or Top X'/1 Probability as output can be advantageously utilized.
以上説明した第3の実施形態によれば、UEは、L1-RSRPなしの報告インスタンスを報告できる。
According to the third embodiment described above, the UE can report a reporting instance without L1-RSRP.
なお、第3の実施形態の変形例として、報告インスタンスにL1-RSRPフィールドが全く含まれない代わりに、少なくとも1つのリソースインディケーターに対応するL1-RSRPフィールドが含まれてもよい。つまり、当該報告インスタンスには、当該報告インスタンス内の全リソースインディケーターフィールドに対応する全L1-RSRPフィールドが含まれず、一部のL1-RSRPフィールドのみが含まれてもよい。
As a variation of the third embodiment, the reporting instance may not include any L1-RSRP fields at all, but may instead include an L1-RSRP field corresponding to at least one resource indicator. In other words, the reporting instance may not include all L1-RSRP fields corresponding to all resource indicator fields in the reporting instance, but may include only some of the L1-RSRP fields.
<第4の実施形態>
第4の実施形態は、リソースインディケーターの数が低減されるビーム情報の報告に関する。 Fourth Embodiment
A fourth embodiment relates to reporting of beam information in which the number of resource indicators is reduced.
第4の実施形態は、リソースインディケーターの数が低減されるビーム情報の報告に関する。 Fourth Embodiment
A fourth embodiment relates to reporting of beam information in which the number of resource indicators is reduced.
UEは、1つの報告インスタンスに、1つ以上のリソースに対応する(例えば、当該1つ以上のリソースのうち全リソースについての)L1-RSRP、トップX確率又はトップX’/1確率を示す情報を含めて、当該報告インスタンスを送信してもよい。
The UE may transmit a single report instance including information indicating the L1-RSRP, top X probability, or top X'/1 probability corresponding to one or more resources (e.g., for all resources among the one or more resources).
上記1つ以上のリソースは、セットAのためのリソースであってもよいし、セットBのためのリソースであってもよい。第4の実施形態の報告インスタンスは、主にセットB向けであってもよい。
The one or more resources may be resources for set A or may be resources for set B. The reporting instance of the fourth embodiment may be primarily intended for set B.
1つの報告要素(例えば、L1-RSRP、トップX確率又はトップX’/1確率)について、1つの報告インスタンスに含まれるフィールド(差分情報を示すフィールドを含んでもよい)の数は、特定の数であってもよい。当該特定の数は、4より大きくてもよいし、4以下であってもよい。
For one report element (e.g., L1-RSRP, Top X Probability, or Top X'/1 Probability), the number of fields (which may include a field indicating differential information) included in one report instance may be a specific number. The specific number may be greater than 4 or less than or equal to 4.
上記1つ以上のリソース、上記特定の数などに関する情報は、ネットワークからUEに通知されてもよいし、規格において規定されてもよいし、ビーム予測に用いるモデル(関連付けられるモデル)から導出されてもよいし、同じ報告インスタンス内の他の情報に基づいて決定されてもよい。
The information regarding the one or more resources, the specific number, etc. may be signaled to the UE by the network, may be specified in a standard, may be derived from a model (associated model) used for beam prediction, or may be determined based on other information within the same reporting instance.
第4の実施形態の報告インスタンスには、当該報告インスタンスによって示される最大のL1-RSRP、トップX確率又はトップX’/1確率に対応する、リソースインディケーターフィールド及び能力インデックスフィールドの少なくとも一方が含まれてもよく、他のリソースインディケーターフィールド/能力インデックスフィールドは含まれなくてもよい。これにより、報告インスタンスの通信オーバーヘッドが好適に低減できる。
The report instance of the fourth embodiment may include at least one of a resource indicator field and a capability index field corresponding to the maximum L1-RSRP, top X probability, or top X'/1 probability indicated by the report instance, and may not include other resource indicator fields/capability index fields. This allows the communication overhead of the report instance to be suitably reduced.
なお、報告されない他のリソースインディケーター/能力インデックスについては、報告されるリソースインディケーター/能力インデックスとマッピングルールに基づいて特定されてもよい。つまり、報告されるL1-RSRP、トップX確率又はトップX’/1確率フィールドに対応するリソースインディケーター/能力インデックスは、1番目が報告されるリソース(リソースインディケーターフィールド/能力インデックスフィールド)に対応し、2番目以降は、上記1番目のリソースを除くリソースからマッピングルールに基づいて判断されてもよい。
Note that other resource indicators/capability indexes that are not reported may be identified based on the reported resource indicators/capability indexes and mapping rules. In other words, the first resource indicator/capability index corresponding to the reported L1-RSRP, top X probability, or top X'/1 probability field corresponds to the resource (resource indicator field/capability index field) that is reported, and the second and subsequent resource indicators/capability indexes may be determined based on the mapping rules from resources other than the first resource.
また、第4の実施形態の報告インスタンスには、リソースインディケーターフィールド及び能力インデックスフィールドの少なくとも一方が全く含まれなくてもよい。この場合、報告されるL1-RSRP、トップX確率又はトップX’/1確率フィールドに対応するリソースインディケーター/能力インデックスは、マッピングルールに基づいて判断されてもよい。
Furthermore, the reporting instance of the fourth embodiment may not include at least one of the resource indicator field and the capability index field. In this case, the resource indicator/capability index corresponding to the reported L1-RSRP, top X probability, or top X'/1 probability field may be determined based on a mapping rule.
図6A及び6Bは、第4の実施形態における報告インスタンスの一例を示す図である。本例では、報告対象のリソース数は4であり、4つのリソース全てについてのRSRP(又は差分RSRP)が報告される。
FIGS. 6A and 6B are diagrams showing an example of a reporting instance in the fourth embodiment. In this example, the number of resources to be reported is four, and the RSRP (or differential RSRP) for all four resources is reported.
図6Aは、報告インスタンスの一例を示す。CRI/SSBRI#1フィールドは、最大のRSRP#1に対応するCRI/SSBRIを示す。また、能力インデックスフィールドは、CRI/SSBRI#1フィールドが示すCRI/SSBRI(又は全てのリソース(CRI/SSBRI))に対応する能力インデックスを示してもよい。
FIG. 6A shows an example of a reporting instance. The CRI/SSBRI# 1 field indicates the CRI/SSBRI corresponding to the maximum RSRP# 1. The capability index field may also indicate the capability index corresponding to the CRI/SSBRI indicated by the CRI/SSBRI# 1 field (or all resources (CRI/SSBRI)).
図6Bは、図6Aに対応して、報告されないCRI/SSBRIの特定の一例を示す図である。本例では、4つのリソースに対応するリソースインディケーターは、SSBRI#1、#2、#3及び#6であると想定する。図6Aの報告インスタンスのCRI/SSBRI#1フィールドがSSBRI#2を示す場合、残りのSSBRIの小さい方から順に(つまり、SSBRI#1、#3及び#6の順に)、それぞれ(差分)RSRP#2-#4フィールドに対応してもよい。
Figure 6B is a diagram showing a specific example of CRI/SSBRI that is not reported, corresponding to Figure 6A. In this example, it is assumed that the resource indicators corresponding to the four resources are SSBRIs # 1, #2, #3 and #6. If the CRI/SSBRI# 1 field of the reporting instance in Figure 6A indicates SSBRI# 2, then the remaining SSBRIs may correspond to the (differential) RSRP#2-#4 fields in ascending order (i.e., SSBRIs # 1, #3 and #6, respectively).
上記マッピングルールは、リソースインディケーター/能力インデックスに基づいてもよい。例えば、L1-RSRP、トップX確率又はトップX’/1確率がリソースインディケーター及び能力インデックスの一方又は両方に基づいて測定/予測されるとすると、上記マッピングルールは、以下を含んでもよい:
・最小のインデックスから順にマッピングされる、
・マッピング順において、CRIはSSBRIより優先される、又は、SSBRIはCRIより優先される、又は、CRIとSSBRIは区別されない、
・セルID(例えば、物理セルID)が小さい方から大きい方の順にマッピングされる。同じセルID内では、CRI/SSBRIに従ってマッピング順が決定される、
・能力インデックスが小さい方から大きい方の順にマッピングされる。同じ能力インデックス内では、CRI/SSBRIに従ってマッピング順が決定される、又は、同じCRI/SSBRI内では、能力インデックスに従ってマッピング順が決定される。 The mapping rule may be based on the resource indicator/capability index. For example, if L1-RSRP, top X probability or top X'/1 probability is measured/predicted based on one or both of the resource indicator and the capability index, the mapping rule may include:
・Mapping is done in order from the smallest index to the largest.
In the mapping order, CRI takes precedence over SSBRI, or SSBRI takes precedence over CRI, or no distinction is made between CRI and SSBRI;
Cell IDs (e.g., physical cell IDs) are mapped from smallest to largest. Within the same cell ID, the mapping order is determined according to the CRI/SSBRI.
Capability index is mapped from smallest to largest. Within the same capability index, the mapping order is determined according to CRI/SSBRI, or within the same CRI/SSBRI, the mapping order is determined according to capability index.
・最小のインデックスから順にマッピングされる、
・マッピング順において、CRIはSSBRIより優先される、又は、SSBRIはCRIより優先される、又は、CRIとSSBRIは区別されない、
・セルID(例えば、物理セルID)が小さい方から大きい方の順にマッピングされる。同じセルID内では、CRI/SSBRIに従ってマッピング順が決定される、
・能力インデックスが小さい方から大きい方の順にマッピングされる。同じ能力インデックス内では、CRI/SSBRIに従ってマッピング順が決定される、又は、同じCRI/SSBRI内では、能力インデックスに従ってマッピング順が決定される。 The mapping rule may be based on the resource indicator/capability index. For example, if L1-RSRP, top X probability or top X'/1 probability is measured/predicted based on one or both of the resource indicator and the capability index, the mapping rule may include:
・Mapping is done in order from the smallest index to the largest.
In the mapping order, CRI takes precedence over SSBRI, or SSBRI takes precedence over CRI, or no distinction is made between CRI and SSBRI;
Cell IDs (e.g., physical cell IDs) are mapped from smallest to largest. Within the same cell ID, the mapping order is determined according to the CRI/SSBRI.
Capability index is mapped from smallest to largest. Within the same capability index, the mapping order is determined according to CRI/SSBRI, or within the same CRI/SSBRI, the mapping order is determined according to capability index.
以上説明した第4の実施形態によれば、報告されるL1-RSRP、トップX確率又はトップX’/1確率よりも少ない数のリソースインディケーターフィールドのみを含む報告インスタンスを報告できる。
According to the fourth embodiment described above, it is possible to report a reporting instance that includes only a number of resource indicator fields that is less than the reported L1-RSRP, top X probability, or top X'/1 probability.
なお、第3の実施形態の報告インスタンスと第4の実施形態の報告インスタンスとが組み合わせて用いられてもよい。例えば、UEは、1つの報告インスタンスにおいて、1つ以上のリソースに関連付けられる全ての参照信号のL1-RSRPを報告しつつ(当該L1-RSRPに対応するいくつかのCRI/SSBRIは報告しない)、当該1つ以上のリソース又は異なる1つ以上のリソースについて1番目からX番目に大きいRSRPを達成するCRI/SSBRIを報告してもよい。このような報告インスタンスは、例えば、データ収集において、セットBのビーム測定及びL1-RSRPなしのセットAビーム指示のために好適である。
Note that the reporting instance of the third embodiment and the reporting instance of the fourth embodiment may be used in combination. For example, in one reporting instance, the UE may report the L1-RSRP of all reference signals associated with one or more resources (without reporting some CRI/SSBRI corresponding to the L1-RSRP), and report the CRI/SSBRI that achieves the 1st to Xth largest RSRP for the one or more resources or for one or more different resources. Such a reporting instance is suitable, for example, for Set B beam measurement and Set A beam indication without L1-RSRP in data collection.
<第5の実施形態>
第5の実施形態では、ビーム予測の報告に関して説明する。 Fifth embodiment
In the fifth embodiment, reporting of beam predictions will be described.
第5の実施形態では、ビーム予測の報告に関して説明する。 Fifth embodiment
In the fifth embodiment, reporting of beam predictions will be described.
《実施形態5-1》
UEに対し、セットBのための1つ以上のリソースが設定されてもよい。UEは、セットBのリソースの測定に基づいて、ビーム予測モデルのインプットを計算/制御してもよい。 <<Embodiment 5-1>>
The UE may be configured with one or more resources for set B. The UE may calculate/control the input of the beam prediction model based on measurements of the resources of set B.
UEに対し、セットBのための1つ以上のリソースが設定されてもよい。UEは、セットBのリソースの測定に基づいて、ビーム予測モデルのインプットを計算/制御してもよい。 <<Embodiment 5-1>>
The UE may be configured with one or more resources for set B. The UE may calculate/control the input of the beam prediction model based on measurements of the resources of set B.
UEに対し、セットAのための1つ以上のリソースが設定されてもよい。UEは、報告されるリソース(セットA)のビーム予測を行い、CSIレポートを用いて予測結果を報告してもよい。
The UE may be configured with one or more resources for set A. The UE may perform beam prediction for the reported resources (set A) and report the prediction result using a CSI report.
UEは、行ったビーム予測に基づいて、予測されるCRI/SSBRI、L1-RSRP、トップX確率、トップX’/1確率などの少なくとも1つを含むビーム情報の報告を行ってもよい。
The UE may report beam information including at least one of predicted CRI/SSBRI, L1-RSRP, top X probability, top X'/1 probability, etc. based on the beam prediction performed.
UEは、レポートセッティングごとのセットA/セットBのためのRSリソースの数(例えば、N(Nは任意の正の整数))を設定されてもよい。
The UE may be configured with the number of RS resources (e.g., N, where N is any positive integer) for Set A/Set B per report setting.
図7は、実施形態5-1に係るビーム予測の一例を示す図である。図7に示す例において、UEは、セットBに含まれるビーム/RSの測定を行う。ついで、UEは、セットBの測定に基づくビーム予測を行う。UEは、セットAのN個のビーム品質(例えば、CRI/SSBRI、L1-RSRP、トップX確率、トップX’/1確率などの少なくとも1つ)を含むCSIレポートの報告を行う。
FIG. 7 is a diagram showing an example of beam prediction according to embodiment 5-1. In the example shown in FIG. 7, the UE measures the beams/RSs included in set B. Then, the UE performs beam prediction based on the measurements of set B. The UE reports a CSI report including N beam qualities of set A (e.g., at least one of CRI/SSBRI, L1-RSRP, top X probability, top X'/1 probability, etc.).
《実施形態5-2》
UEは、特定のケースにおいて、予測されたCRI/SSBRI、L1-RSRP、トップX確率、トップX’/1確率などの少なくとも1つを含むビーム情報の報告を行ってもよい。 <<Embodiment 5-2>>
The UE may report beam information including at least one of predicted CRI/SSBRI, L1-RSRP, top X probability, top X'/1 probability, etc. in certain cases.
UEは、特定のケースにおいて、予測されたCRI/SSBRI、L1-RSRP、トップX確率、トップX’/1確率などの少なくとも1つを含むビーム情報の報告を行ってもよい。 <<Embodiment 5-2>>
The UE may report beam information including at least one of predicted CRI/SSBRI, L1-RSRP, top X probability, top X'/1 probability, etc. in certain cases.
当該特定のケースは、例えば、以下のオプション5-2-1から5-2-3の少なくとも1つであってもよい。
The particular case may be, for example, at least one of the following options 5-2-1 to 5-2-3.
[オプション5-2-1]
UEは、特定のパラメータにおいて特定の値が設定/指示された場合に、上記ビーム情報の報告を行ってもよい。 [Option 5-2-1]
The UE may report the above beam information when a specific value is set/indicated in a specific parameter.
UEは、特定のパラメータにおいて特定の値が設定/指示された場合に、上記ビーム情報の報告を行ってもよい。 [Option 5-2-1]
The UE may report the above beam information when a specific value is set/indicated in a specific parameter.
当該特定のパラメータは、上位レイヤシグナリング(例えば、RRCパラメータ/MAC CE)によってUEに対し通知されてもよい。
The specific parameters may be notified to the UE by higher layer signaling (e.g., RRC parameters/MAC CE).
例えば、当該RRCパラメータは、CSIレポート設定(例えば、CSI-ReportConfig)に含まれてもよい。また、たとえば、当該RRCパラメータは、CSIレポート設定(例えば、CSI-ReportConfig)に含まれる報告量のパラメータ(例えば、reportQuantity)に含まれてもよい。
For example, the RRC parameter may be included in a CSI report configuration (e.g., CSI-ReportConfig). Also, for example, the RRC parameter may be included in a report quantity parameter (e.g., reportQuantity) included in a CSI report configuration (e.g., CSI-ReportConfig).
上記特定の値は、第1の実施形態で述べた、ビーム情報に含まれる任意の情報を報告することを示す値であってもよい。
The specific value may be a value indicating that any information contained in the beam information described in the first embodiment is to be reported.
図8は、オプション5-2-1に係るRRCパラメータの一例を示す図である。図8は、ASN.1(Abstract Syntax Notation One)記法を用いて記載されている。以下本開示における設定/RRCパラメータ/情報要素を示す図面は、同様にASN.1記法を用いて記載される。
FIG. 8 is a diagram showing an example of RRC parameters related to option 5-2-1. FIG. 8 is written using ASN.1 (Abstract Syntax Notation One) notation. The following drawings showing settings/RRC parameters/information elements in this disclosure are similarly written using ASN.1 notation.
図8に示す例において、CSIレポート設定(CSI-ReportConfig)に含まれる報告量のパラメータ(reportQuantity)は、CSI-RS(CRI)に基づいてトップX確率を測定/予測することを示すパラメータ(predicted-cri-topX)又はSSB(SSBRI)に基づいてトップX確率を測定/予測することを示すパラメータ(predicted-ssb-Index-topX)を含んでもよい。
In the example shown in FIG. 8, the report quantity parameter (reportQuantity) included in the CSI report configuration (CSI-ReportConfig) may include a parameter (predicted-cri-topX) indicating that the top X probability is measured/predicted based on the CSI-RS (CRI) or a parameter (predicted-ssb-Index-topX) indicating that the top X probability is measured/predicted based on the SSB (SSBRI).
UEは、predicted-cri-topXが設定される場合に、このCSIレポート設定に対応する報告インスタンスを用いて、CSI-RSに基づくトップX確率の報告(かつL1-RSRPを報告しない)を行うことを判断する。UEは、predicted-ssb-Index-topXが設定される場合に、このCSIレポート設定に対応する報告インスタンスを用いて、SSBに基づくトップX確率の報告(かつL1-RSRPを報告しない)を行うことを判断する。
When predicted-cri-topX is configured, the UE determines to report the top X probabilities based on CSI-RS (and not report L1-RSRP) using the reporting instance corresponding to this CSI reporting configuration. When predicted-ssb-Index-topX is configured, the UE determines to report the top X probabilities based on SSB (and not report L1-RSRP) using the reporting instance corresponding to this CSI reporting configuration.
[オプション5-2-2]
UEは、特定のAIモデルがアクティベートされた場合に、上記ビーム情報の報告を行ってもよい。 [Option 5-2-2]
The UE may report the above beam information when a specific AI model is activated.
UEは、特定のAIモデルがアクティベートされた場合に、上記ビーム情報の報告を行ってもよい。 [Option 5-2-2]
The UE may report the above beam information when a specific AI model is activated.
当該特定のAIモデルは、例えば、予測されるビームに関連するAIモデルであってもよい。
The particular AI model may be, for example, an AI model related to the predicted beam.
[オプション5-2-3]
UEは、特定のAIモデルが設定/登録(registered)された場合に、上記ビーム情報の報告を行ってもよい。 [Option 5-2-3]
The UE may report the above beam information when a specific AI model is configured/registered.
UEは、特定のAIモデルが設定/登録(registered)された場合に、上記ビーム情報の報告を行ってもよい。 [Option 5-2-3]
The UE may report the above beam information when a specific AI model is configured/registered.
当該特定のAIモデルは、例えば、予測されるビームに関連するAIモデルであってもよい。
The particular AI model may be, for example, an AI model related to the predicted beam.
上記オプション5-2-1から5-2-3の少なくとも2つが組み合わされて適用されてもよい。
At least two of the above options 5-2-1 to 5-2-3 may be applied in combination.
例えば、UEに対し特定のRRCパラメータ(例えば、トップX確率を測定/予測することを示すパラメータ)が設定され、かつ、上記特定のAIモデルがアクティベートされた場合に、UEは上記ビーム情報の報告を行ってもよい。
For example, the UE may report the beam information when a specific RRC parameter (e.g., a parameter indicating that the top X probability is measured/predicted) is configured for the UE and the specific AI model is activated.
以上第5の実施形態によれば、ビームの測定/予測/報告のための設定/動作について適切に規定することができる。
According to the fifth embodiment described above, it is possible to appropriately specify the settings/operations for measuring/predicting/reporting beams.
<第6の実施形態>
第6の実施形態では、測定されるRS/ビームと報告されるRS/ビームとの間の対応関係/マッピングについて説明する。 Sixth embodiment
In the sixth embodiment, the correspondence/mapping between measured and reported RS/beams is described.
第6の実施形態では、測定されるRS/ビームと報告されるRS/ビームとの間の対応関係/マッピングについて説明する。 Sixth embodiment
In the sixth embodiment, the correspondence/mapping between measured and reported RS/beams is described.
《実施形態6-1》
UEは、測定対象のRS(例えば、CSI-RS/SSB)リソースと報告対象のRSリソースとを別々に決定してもよい。 <<Embodiment 6-1>>
The UE may separately determine the RS (eg, CSI-RS/SSB) resources to be measured and the RS resources to be reported.
UEは、測定対象のRS(例えば、CSI-RS/SSB)リソースと報告対象のRSリソースとを別々に決定してもよい。 <<Embodiment 6-1>>
The UE may separately determine the RS (eg, CSI-RS/SSB) resources to be measured and the RS resources to be reported.
UEは、測定するRSリソースとは異なるRSリソースのCRI/SSBRI、L1-RSRP、トップX確率、トップX’/1確率などの少なくとも1つを報告してもよい。
The UE may report at least one of the CRI/SSBRI, L1-RSRP, top X probability, top X'/1 probability, etc., of RS resources other than the RS resource being measured.
UEは、以下の6-1-1から6-1-5の少なくとも1つにしたがって、測定されるリソース及び報告されるリソースの決定を行ってもよい。
The UE may determine the resources to be measured and the resources to be reported according to at least one of 6-1-1 to 6-1-5 below.
[オプション6-1-1]
UEは、特定のRRCパラメータを用いてRSの決定を行ってもよい。 [Option 6-1-1]
The UE may make RS decisions using specific RRC parameters.
UEは、特定のRRCパラメータを用いてRSの決定を行ってもよい。 [Option 6-1-1]
The UE may make RS decisions using specific RRC parameters.
例えば、UEは、既存の(Rel.16/17までに規定される)RRCパラメータを用いてRSの決定を行ってもよい。
For example, the UE may use existing RRC parameters (defined by Rel. 16/17) to determine the RS.
当該RRCパラメータは、例えば、チャネル測定/干渉測定用のリソースを設定するためのパラメータに含まれてもよい。当該RRCパラメータは、例えば、CSIレポート設定(例えば、CSI-ReportConfig)に含まれるRRCパラメータであってもよい。
The RRC parameters may be included in parameters for setting resources for channel measurement/interference measurement, for example. The RRC parameters may be RRC parameters included in a CSI report configuration (e.g., CSI-ReportConfig).
UEは、ビーム予測において報告されるCSI(CRI/SSBRI、L1-RSRP、トップX確率、トップX’/1確率など)のリソースを含むCSIリソース設定(例えば、CSI-ResourceConfig)を設定されてもよい。
The UE may be configured with a CSI resource configuration (e.g., CSI-ResourceConfig) that includes resources for CSI (CRI/SSBRI, L1-RSRP, top-X probability, top-X'/1 probability, etc.) reported in beam prediction.
UEは、ビーム予測計算(例えば、AIモデルのインプット)のために、既存のRRCパラメータ(例えば、チャネル測定用リソースのパラメータ(例えば、resourceForChannelMeasurement)及び干渉測定用リソースのパラメータ(例えば、csi-IM-ResourcesForInterference)の少なくとも一方)に対応するリソースを参照/判断してもよい。
The UE may refer to/determine resources corresponding to existing RRC parameters (e.g., at least one of parameters for resources for channel measurement (e.g., resourceForChannelMeasurement) and parameters for resources for interference measurement (e.g., csi-IM-ResourcesForInterference)) for beam prediction calculation (e.g., input for an AI model).
図9は、オプション6-1-1に係るRRCパラメータの一例を示す図である。図9に示す例では、CSIレポート設定(CSI-ReportConfig)に、報告用のリソースを示すパラメータ(resourcesForReporting)が含まれる。報告用のリソースを示すパラメータ(resourcesForReporting)は、CSIリソース設定のID(CSI-ResourceConfigId)を参照する。
FIG. 9 is a diagram showing an example of RRC parameters related to option 6-1-1. In the example shown in FIG. 9, the CSI report configuration (CSI-ReportConfig) includes a parameter (resourcesForReporting) indicating resources for reporting. The parameter (resourcesForReporting) indicating resources for reporting refers to the ID of the CSI resource configuration (CSI-ResourceConfigId).
UEは、報告対象のリソースを、参照するCSI-ResourceConfigIdに基づいて判断する。
The UE determines which resources to report based on the referenced CSI-ResourceConfigId.
[オプション6-1-2]
UEは、特定のRRCパラメータを用いてRSの決定を行ってもよい。 [Option 6-1-2]
The UE may make RS decisions using specific RRC parameters.
UEは、特定のRRCパラメータを用いてRSの決定を行ってもよい。 [Option 6-1-2]
The UE may make RS decisions using specific RRC parameters.
例えば、UEは、新たに(Rel.18/19以降に規定される)RRCパラメータを用いてRSの決定を行ってもよい。
For example, the UE may determine the RS using new RRC parameters (defined in Rel. 18/19 and later).
当該RRCパラメータは、例えば、CSIレポート設定(例えば、CSI-ReportConfig)に含まれるRRCパラメータであってもよい。
The RRC parameters may be, for example, RRC parameters included in a CSI report configuration (e.g., CSI-ReportConfig).
当該RRCパラメータは、ビーム予測のために用いられるチャネル測定用のリソースを含むCSIリソース設定を用いてUEに対し設定されてもよい。
The RRC parameters may be configured for the UE using a CSI resource configuration that includes resources for channel measurements used for beam prediction.
当該RRCパラメータは、ビーム予測のために用いられる干渉測定/干渉ビーム測定用のリソースを含むCSIリソース設定を用いてUEに対し設定されてもよい。
The RRC parameters may be configured for the UE using a CSI resource configuration that includes resources for interference measurements/interference beam measurements used for beam prediction.
当該RRCパラメータは、ビーム予測において報告されるCSI(CRI/SSBRI、L1-RSRP、トップX確率、トップX’/1確率など)のリソースを含むCSIリソース設定を用いてUEに対し設定されてもよい。
The RRC parameters may be configured for the UE using a CSI resource configuration that includes resources for CSI (CRI/SSBRI, L1-RSRP, top X probability, top X'/1 probability, etc.) reported in beam prediction.
[オプション6-1-3]
UEは、特定のRRCパラメータを用いてRS(RSのリソースセット)の決定を行ってもよい。 [Option 6-1-3]
The UE may make the RS (resource set of RS) decision using specific RRC parameters.
UEは、特定のRRCパラメータを用いてRS(RSのリソースセット)の決定を行ってもよい。 [Option 6-1-3]
The UE may make the RS (resource set of RS) decision using specific RRC parameters.
CSIリソース設定のパラメータ(例えば、CSI-ResourceConfig)が拡張されてもよい。
CSI resource configuration parameters (e.g., CSI-ResourceConfig) may be extended.
UEは、ビーム予測後に報告されるCSI(CRI/SSBRI、L1-RSRP、トップX確率、トップX’/1確率など)についてのリソースセットを設定されてもよい。
The UE may be configured with a resource set for the CSI (CRI/SSBRI, L1-RSRP, top X probability, top X'/1 probability, etc.) reported after beam prediction.
1つのCSIリソース設定のパラメータ(例えば、CSI-ResourceConfig)に、報告されるリソースセットに関する情報と、ビーム予測のために測定されるリソースセットに関する情報と、の両方が含まれてもよい。
A single CSI resource configuration parameter (e.g., CSI-ResourceConfig) may include both information about the resource set to be reported and information about the resource set to be measured for beam prediction.
1つのCSIリソース設定のパラメータ(例えば、CSI-ResourceConfig)に、報告されるリソースセットに関する情報と、ビーム予測のために測定されるリソースセットに関する情報と、のいずれかが含まれてもよい。このとき、UEに対し、2つ以上のCSIリソース設定のパラメータ(例えば、CSI-ResourceConfig)が設定されてもよい。
A single CSI resource configuration parameter (e.g., CSI-ResourceConfig) may include either information about a resource set to be reported or information about a resource set to be measured for beam prediction. In this case, two or more CSI resource configuration parameters (e.g., CSI-ResourceConfig) may be configured for a UE.
[オプション6-1-4]
UEは、特定のRRCパラメータを用いてRS(RSのリソース)の決定を行ってもよい。 [Option 6-1-4]
The UE may make RS (RS resource) decisions using specific RRC parameters.
UEは、特定のRRCパラメータを用いてRS(RSのリソース)の決定を行ってもよい。 [Option 6-1-4]
The UE may make RS (RS resource) decisions using specific RRC parameters.
リソースセットに関するパラメータが拡張されてもよい。
The parameters for the resource set may be expanded.
例えば、UEは、報告されるリソースと、ビーム予測のために測定されるリソースと、を含むリソースセットに関するパラメータ(例えば、NZP-CSI-RS-ResourceSet)を設定されてもよい。
For example, the UE may be configured with a parameter (e.g., NZP-CSI-RS-ResourceSet) for a resource set that includes the resources to be reported and the resources to be measured for beam prediction.
[オプション6-1-5]
報告されるRSのリソースと、ビーム予測のために測定されるRSのリソースと、の少なくとも一方が含まれるリストが規定されてもよい。 [Option 6-1-5]
A list may be defined that includes at least one of the resources of the RS to be reported and the resources of the RS to be measured for beam prediction.
報告されるRSのリソースと、ビーム予測のために測定されるRSのリソースと、の少なくとも一方が含まれるリストが規定されてもよい。 [Option 6-1-5]
A list may be defined that includes at least one of the resources of the RS to be reported and the resources of the RS to be measured for beam prediction.
UEは、当該リストに基づいて、報告されるRSのリソースと測定されるRSのリソースとの少なくとも一方を判断してもよい。
The UE may determine at least one of the resources of the RS to be reported and the resources of the RS to be measured based on the list.
例えば、UEは、報告されるリソースのリソースID/リソースセットID/CSIリソース設定を含むリストを設定されてもよい。
For example, the UE may be configured with a list containing the resource IDs/resource set IDs/CSI resource configurations of the resources to be reported.
例えば、UEは、ビーム予測のために測定されるリソースのリソースID/リソースセットID/CSIリソース設定を含むリストを設定されてもよい。
For example, the UE may be configured with a list including resource IDs/resource set IDs/CSI resource configurations of resources to be measured for beam prediction.
1つのリストに、報告されるRSのリソースに関する情報と、ビーム予測のために測定されるRSのリソースに関する情報と、の両方が含まれてもよい。
A single list may include both information about the resources of the RS to be reported and information about the resources of the RS to be measured for beam prediction.
1つのリストに、報告されるRSのリソースに関する情報と、ビーム予測のために測定されるRSのリソースに関する情報と、のいずれかが含まれてもよい。
A single list may include either information about the resources of the RS to be reported or information about the resources of the RS to be measured for beam prediction.
上記オプション6-1-1から6-1-5の少なくとも2つが組み合わされて適用されてもよい。
At least two of the above options 6-1-1 to 6-1-5 may be applied in combination.
《実施形態6-2》
UEは、測定するRSリソースとは異なるRSリソースのCRI/SSBRI、L1-RSRP、トップX確率、トップX’/1確率などを報告することが設定されることを、特定の条件において期待/想定してもよい。 <<Embodiment 6-2>>
The UE may expect/assume in certain conditions that it is configured to report CRI/SSBRI, L1-RSRP, top-X probability, top-X′/1 probability, etc. for RS resources different from the RS resource it measures on.
UEは、測定するRSリソースとは異なるRSリソースのCRI/SSBRI、L1-RSRP、トップX確率、トップX’/1確率などを報告することが設定されることを、特定の条件において期待/想定してもよい。 <<Embodiment 6-2>>
The UE may expect/assume in certain conditions that it is configured to report CRI/SSBRI, L1-RSRP, top-X probability, top-X′/1 probability, etc. for RS resources different from the RS resource it measures on.
当該特定の条件は、特定のAIモデルがアクティベートされる場合であってもよい。
The particular condition may be when a particular AI model is activated.
当該特定の条件は、ビーム予測に関連する特定のAIモデルがアクティベートされる場合であってもよい。
The particular condition may be when a particular AI model related to beam prediction is activated.
当該特定の条件は、特定のタイプのビーム予測に関連する特定のAIモデルがアクティベートされる場合であってもよい。
The particular condition may be when a particular AI model associated with a particular type of beam prediction is activated.
当該特定のタイプのビーム予測は、例えば、空間ドメインビーム予測(spatial domain beam prediction)であってもよいし、時間ドメインビーム予測であってもよい。
The particular type of beam prediction may be, for example, spatial domain beam prediction or time domain beam prediction.
当該特定の条件は、特定のRRCパラメータ(例えば、reportQuantity)が特定の値(例えば、第1の実施形態で述べた、ビーム情報に含まれる任意の情報を報告することを示す値)に設定/指示される場合であってもよい。
The particular condition may be when a particular RRC parameter (e.g., reportQuantity) is set/indicated to a particular value (e.g., a value indicating that any information contained in the beam information is to be reported, as described in the first embodiment).
UEは、レポートセッティングごとの、チャネル測定/干渉測定用のRSリソース、報告用のRSリソース、測定されるRSリソースの数、報告されるRSリソースの数、の少なくとも1つが、各モデル(アクティベートされるAIモデル)に関連付けられる情報と同じであると期待/想定してもよい。
The UE may expect/assume that at least one of the following for each reporting setting: RS resources for channel/interference measurements, RS resources for reporting, number of RS resources to be measured, and number of RS resources to be reported, is the same as the information associated with each model (activated AI model).
以上第6の実施形態によれば、測定されるRS/ビームと報告されるRS/ビームとの間の対応関係/マッピングを、適切に判断できる。
According to the sixth embodiment described above, the correspondence/mapping between the measured RS/beam and the reported RS/beam can be appropriately determined.
<補足>
[AIモデル情報]
本開示において、AIモデル情報は、以下の少なくとも1つを含む情報を意味してもよい:
・AIモデルの入力/出力の情報、
・AIモデルの入力/出力のための前処理/後処理の情報、
・AIモデルのパラメータの情報、
・AIモデルのための訓練情報(トレーニング情報)、
・AIモデルのための推論情報、
・AIモデルに関する性能情報。 <Additional Information>
[AI model information]
In this disclosure, AI model information may mean information including at least one of the following:
- AI model input/output information,
- Pre-processing/post-processing information for input/output of AI models;
・Information on the parameters of the AI model,
- Training information for the AI model;
- Inference information for AI models,
・Performance information about the AI model.
[AIモデル情報]
本開示において、AIモデル情報は、以下の少なくとも1つを含む情報を意味してもよい:
・AIモデルの入力/出力の情報、
・AIモデルの入力/出力のための前処理/後処理の情報、
・AIモデルのパラメータの情報、
・AIモデルのための訓練情報(トレーニング情報)、
・AIモデルのための推論情報、
・AIモデルに関する性能情報。 <Additional Information>
[AI model information]
In this disclosure, AI model information may mean information including at least one of the following:
- AI model input/output information,
- Pre-processing/post-processing information for input/output of AI models;
・Information on the parameters of the AI model,
- Training information for the AI model;
- Inference information for AI models,
・Performance information about the AI model.
ここで、上記AIモデルの入力/出力の情報は、以下の少なくとも1つに関する情報を含んでもよい:
・入力/出力データの内容(例えば、RSRP、SINR、チャネル行列(又はプリコーディング行列)における振幅/位相情報、到来角度(Angle of Arrival(AoA))に関する情報、放射角度(Angle of Departure(AoD))に関する情報、位置情報)、
・データの補助情報(メタ情報と呼ばれてもよい)、
・入力/出力データのタイプ(例えば、不変値(immutable value)、浮動小数点数)、
・入力/出力データのビット幅(例えば、各入力値について64ビット)、
・入力/出力データの量子化間隔(量子化ステップサイズ)(例えば、L1-RSRPについて、1dBm)、
・入力/出力データが取り得る範囲(例えば、[0、1])。 Here, the input/output information of the AI model may include information regarding at least one of the following:
Content of input/output data (e.g. RSRP, SINR, amplitude/phase information in the channel matrix (or precoding matrix), information on the Angle of Arrival (AoA), information on the Angle of Departure (AoD), location information);
- auxiliary information of the data (which may be called meta-information);
- Input/output data types (e.g. immutable values, floating point numbers),
- Bit width of input/output data (e.g. 64 bits for each input value),
Quantization interval (quantization step size) of input/output data (e.g., 1 dBm for L1-RSRP);
The range that the input/output data can take (e.g., [0, 1]).
・入力/出力データの内容(例えば、RSRP、SINR、チャネル行列(又はプリコーディング行列)における振幅/位相情報、到来角度(Angle of Arrival(AoA))に関する情報、放射角度(Angle of Departure(AoD))に関する情報、位置情報)、
・データの補助情報(メタ情報と呼ばれてもよい)、
・入力/出力データのタイプ(例えば、不変値(immutable value)、浮動小数点数)、
・入力/出力データのビット幅(例えば、各入力値について64ビット)、
・入力/出力データの量子化間隔(量子化ステップサイズ)(例えば、L1-RSRPについて、1dBm)、
・入力/出力データが取り得る範囲(例えば、[0、1])。 Here, the input/output information of the AI model may include information regarding at least one of the following:
Content of input/output data (e.g. RSRP, SINR, amplitude/phase information in the channel matrix (or precoding matrix), information on the Angle of Arrival (AoA), information on the Angle of Departure (AoD), location information);
- auxiliary information of the data (which may be called meta-information);
- Input/output data types (e.g. immutable values, floating point numbers),
- Bit width of input/output data (e.g. 64 bits for each input value),
Quantization interval (quantization step size) of input/output data (e.g., 1 dBm for L1-RSRP);
The range that the input/output data can take (e.g., [0, 1]).
なお、本開示において、AoAに関する情報は、到来方位角度(azimuth angle of arrival)及び到来天頂角度(zenith angle of arrival(ZoA))の少なくとも1つに関する情報を含んでもよい。また、AoDに関する情報は、例えば、放射方位角度(azimuth angle of departure)及び放射天頂角度(zenith angle of depature(ZoD))の少なくとも1つに関する情報を含んでもよい。
In the present disclosure, the information regarding AoA may include information regarding at least one of the azimuth angle of arrival and the zenith angle of arrival (ZoA). Furthermore, the information regarding AoD may include information regarding at least one of the azimuth angle of departure and the zenith angle of departure (ZoD).
本開示において、位置情報は、UE/NWに関する位置情報であってもよい。位置情報は、測位システム(例えば、衛星測位システム(Global Navigation Satellite System(GNSS)、Global Positioning System(GPS)など))を用いて得られる情報(例えば、緯度、経度、高度)、当該UEに隣接する(又はサービング中の)BSの情報(例えば、BS/セルの識別子(Identifier(ID))、BS-UE間の距離、UE(BS)から見たBS(UE)の方向/角度、UE(BS)から見たBS(UE)の座標(例えば、X/Y/Z軸の座標)など)、UEの特定のアドレス(例えば、Internet Protocol(IP)アドレス)などの少なくとも1つを含んでもよい。UEの位置情報は、BSの位置を基準とする情報に限られず、特定のポイントを基準とする情報であってもよい。
In the present disclosure, the location information may be location information regarding the UE/NW. The location information may include at least one of information (e.g., latitude, longitude, altitude) obtained using a positioning system (e.g., a satellite positioning system (Global Navigation Satellite System (GNSS), Global Positioning System (GPS), etc.)), information on the BS adjacent to (or serving) the UE (e.g., a BS/cell identifier (ID), a BS-UE distance, a direction/angle of the BS (UE) as seen from the UE (BS), coordinates of the BS (UE) as seen from the UE (BS) (e.g., coordinates on the X/Y/Z axes), etc.), a specific address of the UE (e.g., an Internet Protocol (IP) address), etc. The location information of the UE is not limited to information based on the position of the BS, and may be information based on a specific point.
位置情報は、自身の実装に関する情報(例えば、アンテナの位置(location/position)/向き、アンテナパネルの位置/向き、アンテナの数、アンテナパネルの数など)を含んでもよい。
The location information may include information about its implementation (e.g., location/position/orientation of antennas, location/orientation of antenna panels, number of antennas, number of antenna panels, etc.).
位置情報は、モビリティ情報を含んでもよい。モビリティ情報は、モビリティタイプを示す情報、UEの移動速度、UEの加速度、UEの移動方向などの少なくとも1つを示す情報を含んでもよい。
The location information may include mobility information. The mobility information may include information indicating at least one of the following: a mobility type, a moving speed of the UE, an acceleration of the UE, and a moving direction of the UE.
ここで、モビリティタイプは、固定位置UE(fixed location UE)、移動可能/移動中UE(movable/moving UE)、モビリティ無しUE(no mobility UE)、低モビリティUE(low mobility UE)、中モビリティUE(middle mobility UE)、高モビリティUE(high mobility UE)、セル端UE(cell-edge UE)、非セル端UE(not-cell-edge UE)などの少なくとも1つに該当してもよい。
Here, the mobility type may correspond to at least one of fixed location UE, movable/moving UE, no mobility UE, low mobility UE, middle mobility UE, high mobility UE, cell-edge UE, not-cell-edge UE, etc.
本開示において、(データのための)環境情報は、データが取得される/利用される環境に関する情報であってもよく、例えば、周波数情報(バンドIDなど)、環境タイプ情報(屋内(indoor)、屋外(outdoor)、Urban Macro(UMa)、Urban Micro(Umi)などの少なくとも1つを示す情報)、Line Of Site(LOS)/Non-Line Of Site(NLOS)を示す情報などに該当してもよい。
In the present disclosure, environmental information (for data) may be information regarding the environment in which the data is acquired/used, and may correspond to, for example, frequency information (such as a band ID), environmental type information (information indicating at least one of indoor, outdoor, Urban Macro (UMa), Urban Micro (Umi), etc.), information indicating Line Of Site (LOS)/Non-Line Of Site (NLOS), etc.
ここで、LOSは、UE及びBSが互いに見通せる環境にある(又は遮蔽物がない)ことを意味してもよく、NLOSは、UE及びBSが互いに見通せる環境にない(又は遮蔽物がある)ことを意味してもよい。LOS/NLOSを示す情報は、ソフト値(例えば、LOS/NLOSの確率)を示してもよいし、ハード値(例えば、LOS/NLOSのいずれか)を示してもよい。
Here, LOS may mean that the UE and BS are in an environment where they can see each other (or there is no obstruction), and NLOS may mean that the UE and BS are not in an environment where they can see each other (or there is an obstruction). Information indicating LOS/NLOS may indicate a soft value (e.g., the probability of LOS/NLOS) or a hard value (e.g., either LOS or NLOS).
本開示において、メタ情報は、例えば、AIモデルに適した入力/出力情報に関する情報、取得した/取得できるデータに関する情報などを意味してもよい。メタ情報は、具体的には、RS(例えば、CSI-RS/SRS/SSBなど)のビームに関する情報(例えば、各ビームの指向している角度、3dBビーム幅、指向しているビームの形状、ビームの数)、gNB/UEのアンテナのレイアウト情報、周波数情報、環境情報、メタ情報IDなどを含んでもよい。なお、メタ情報は、AIモデルの入力/出力として用いられてもよい。
In the present disclosure, meta-information may mean, for example, information regarding input/output information suitable for an AI model, information regarding data that has been acquired/can be acquired, etc. Specifically, meta-information may include information regarding beams of RS (e.g., CSI-RS/SRS/SSB, etc.) (e.g., the pointing angle of each beam, 3 dB beam width, the shape of the pointed beam, the number of beams), layout information of gNB/UE antennas, frequency information, environmental information, meta-information ID, etc. In addition, meta-information may be used as input/output of an AI model.
上記AIモデルの入力/出力のための前処理/後処理の情報は、以下の少なくとも1つに関する情報を含んでもよい:
・正規化(例えば、Zスコア正規化(標準化)、最小-最大(min-max)正規化)を適用するか否か、
・正規化のためのパラメータ(例えば、Zスコア正規化については平均/分散、最小-最大正規化については最小値/最大値)、
・特定の数値変換方法(例えば、ワンホットエンコーディング(one hot encoding)、ラベルエンコーディング(label encoding)など)を適用するか否か、
・訓練データとして用いられるか否かの選択ルール。 The pre-processing/post-processing information for the input/output of the AI model may include information regarding at least one of the following:
Whether to apply normalization (e.g., Z-score normalization, min-max normalization),
Parameters for normalization (e.g. mean/variance for Z-score normalization, min/max for min-max normalization);
Whether to apply a specific numeric transformation method (e.g., one hot encoding, label encoding, etc.);
Selection rule for whether or not to use as training data.
・正規化(例えば、Zスコア正規化(標準化)、最小-最大(min-max)正規化)を適用するか否か、
・正規化のためのパラメータ(例えば、Zスコア正規化については平均/分散、最小-最大正規化については最小値/最大値)、
・特定の数値変換方法(例えば、ワンホットエンコーディング(one hot encoding)、ラベルエンコーディング(label encoding)など)を適用するか否か、
・訓練データとして用いられるか否かの選択ルール。 The pre-processing/post-processing information for the input/output of the AI model may include information regarding at least one of the following:
Whether to apply normalization (e.g., Z-score normalization, min-max normalization),
Parameters for normalization (e.g. mean/variance for Z-score normalization, min/max for min-max normalization);
Whether to apply a specific numeric transformation method (e.g., one hot encoding, label encoding, etc.);
Selection rule for whether or not to use as training data.
例えば、入力情報xに対して前処理としてZスコア正規化(xnew=(x-μ)/σ。ここで、μはxの平均、σは標準偏差)を行った正規化済み入力情報xnewをAIモデルに入力してもよく、AIモデルからの出力youtに後処理を掛けて最終的な出力yが得られてもよい。
For example, the input information x may be subjected to Z-score normalization (x new = (x - μ) / σ, where μ is the average of x and σ is the standard deviation) as pre-processing, and normalized input information x new may be input to the AI model, and the output y out from the AI model may be subjected to post-processing to obtain the final output y.
上記AIモデルのパラメータの情報は、以下の少なくとも1つに関する情報を含んでもよい:
・AIモデルにおける重み(例えば、ニューロンの係数(結合係数))情報、
・AIモデルの構造(structure)、
・モデルコンポーネントとしてのAIモデルのタイプ(例えば、Residual Network(ResNet)、DenseNet、RefineNet、トランスフォーマー(Transformer)モデル、CRBlock、回帰型ニューラルネットワーク(Recurrent Neural Network(RNN))、長・短期記憶(Long Short-Term Memory(LSTM))、ゲート付き回帰型ユニット(Gated Recurrent Unit(GRU))),
・モデルコンポーネントとしてのAIモデルの機能(例えば、デコーダ、エンコーダ)。 The information of the parameters of the AI model may include information regarding at least one of the following:
- Weight information in an AI model (e.g., neuron coefficients (connection coefficients)),
・Structure of the AI model,
- The type of AI model as a model component (e.g., Residual Network (ResNet), DenseNet, RefineNet, Transformer model, CRBlock, Recurrent Neural Network (RNN), Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU)),
- Functions of the AI model as model components (e.g., decoder, encoder).
・AIモデルにおける重み(例えば、ニューロンの係数(結合係数))情報、
・AIモデルの構造(structure)、
・モデルコンポーネントとしてのAIモデルのタイプ(例えば、Residual Network(ResNet)、DenseNet、RefineNet、トランスフォーマー(Transformer)モデル、CRBlock、回帰型ニューラルネットワーク(Recurrent Neural Network(RNN))、長・短期記憶(Long Short-Term Memory(LSTM))、ゲート付き回帰型ユニット(Gated Recurrent Unit(GRU))),
・モデルコンポーネントとしてのAIモデルの機能(例えば、デコーダ、エンコーダ)。 The information of the parameters of the AI model may include information regarding at least one of the following:
- Weight information in an AI model (e.g., neuron coefficients (connection coefficients)),
・Structure of the AI model,
- The type of AI model as a model component (e.g., Residual Network (ResNet), DenseNet, RefineNet, Transformer model, CRBlock, Recurrent Neural Network (RNN), Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU)),
- Functions of the AI model as model components (e.g., decoder, encoder).
なお、上記AIモデルにおける重み情報は、以下の少なくとも1つに関する情報を含んでもよい:
・重み情報のビット幅(サイズ)、
・重み情報の量子化間隔、
・重み情報の粒度、
・重み情報が取り得る範囲、
・AIモデルにおける重みのパラメータ、
・更新前のAIモデルからの差分の情報(更新する場合)、
・重み初期化(weight initialization)の方法(例えば、ゼロ初期化、ランダム初期化(正規分布/一様分布/切断正規分布に基づく)、Xavier初期化(シグモイド関数向け)、He初期化(整流化線形ユニット(Rectified Linear Units(ReLU))向け))。 In addition, the weight information in the AI model may include information regarding at least one of the following:
- Bit width (size) of weight information
Quantization interval of weight information,
- Granularity of weight information,
- The range of possible weight information
- Weight parameters in the AI model,
- Information on the difference from the AI model before the update (if updating),
- Method of weight initialization (e.g., zero initialization, random initialization (based on normal/uniform/truncated normal distribution), Xavier initialization (for sigmoid function), He initialization (for Rectified Linear Units (ReLU))).
・重み情報のビット幅(サイズ)、
・重み情報の量子化間隔、
・重み情報の粒度、
・重み情報が取り得る範囲、
・AIモデルにおける重みのパラメータ、
・更新前のAIモデルからの差分の情報(更新する場合)、
・重み初期化(weight initialization)の方法(例えば、ゼロ初期化、ランダム初期化(正規分布/一様分布/切断正規分布に基づく)、Xavier初期化(シグモイド関数向け)、He初期化(整流化線形ユニット(Rectified Linear Units(ReLU))向け))。 In addition, the weight information in the AI model may include information regarding at least one of the following:
- Bit width (size) of weight information
Quantization interval of weight information,
- Granularity of weight information,
- The range of possible weight information
- Weight parameters in the AI model,
- Information on the difference from the AI model before the update (if updating),
- Method of weight initialization (e.g., zero initialization, random initialization (based on normal/uniform/truncated normal distribution), Xavier initialization (for sigmoid function), He initialization (for Rectified Linear Units (ReLU))).
また、上記AIモデルの構造は、以下の少なくとも1つに関する情報を含んでもよい:
・レイヤ数、
・レイヤのタイプ(例えば、畳み込み層、活性化層、デンス(dense)層、正規化層、プーリング層、アテンション層)、
・レイヤ情報、
・時系列特有のパラメータ(例えば、双方向性、時間ステップ)、
・訓練のためのパラメータ(例えば、機能のタイプ(L2正則化、ドロップアウト機能など)、どこに(例えば、どのレイヤの後に)この機能を置くか)。 The structure of the AI model may also include information regarding at least one of the following:
Number of layers,
- Type of layer (e.g., convolutional, activation, dense, normalization, pooling, attention);
- Layer information,
Time series specific parameters (e.g. bidirectionality, time step),
Parameters for training (e.g., type of feature (L2 regularization, dropout feature, etc.), where to put this feature (e.g., after which layer)).
・レイヤ数、
・レイヤのタイプ(例えば、畳み込み層、活性化層、デンス(dense)層、正規化層、プーリング層、アテンション層)、
・レイヤ情報、
・時系列特有のパラメータ(例えば、双方向性、時間ステップ)、
・訓練のためのパラメータ(例えば、機能のタイプ(L2正則化、ドロップアウト機能など)、どこに(例えば、どのレイヤの後に)この機能を置くか)。 The structure of the AI model may also include information regarding at least one of the following:
Number of layers,
- Type of layer (e.g., convolutional, activation, dense, normalization, pooling, attention);
- Layer information,
Time series specific parameters (e.g. bidirectionality, time step),
Parameters for training (e.g., type of feature (L2 regularization, dropout feature, etc.), where to put this feature (e.g., after which layer)).
上記レイヤ情報は、以下の少なくとも1つに関する情報を含んでもよい:
・各レイヤにおけるニューロン数、
・カーネルサイズ、
・プーリング層/畳み込み層のためのストライド、
・プーリング方法(MaxPooling、AveragePoolingなど)、
・残差ブロックの情報、
・ヘッド(head)数、
・正規化方法(バッチ正規化、インスタンス正規化、レイヤ正規化など)、
・活性化関数(シグモイド、tanh関数、ReLU、リーキーReLUの情報、Maxout、Softmax)。 The layer information may include information regarding at least one of the following:
- The number of neurons in each layer,
- kernel size,
strides for pooling/convolutional layers,
Pooling method (MaxPooling, AveragePooling, etc.),
- Information on the residual block,
・Number of heads,
- Normalization method (batch normalization, instance normalization, layer normalization, etc.),
Activation functions (sigmoid, tanh function, ReLU, leaky ReLU information, Maxout, Softmax).
・各レイヤにおけるニューロン数、
・カーネルサイズ、
・プーリング層/畳み込み層のためのストライド、
・プーリング方法(MaxPooling、AveragePoolingなど)、
・残差ブロックの情報、
・ヘッド(head)数、
・正規化方法(バッチ正規化、インスタンス正規化、レイヤ正規化など)、
・活性化関数(シグモイド、tanh関数、ReLU、リーキーReLUの情報、Maxout、Softmax)。 The layer information may include information regarding at least one of the following:
- The number of neurons in each layer,
- kernel size,
strides for pooling/convolutional layers,
Pooling method (MaxPooling, AveragePooling, etc.),
- Information on the residual block,
・Number of heads,
- Normalization method (batch normalization, instance normalization, layer normalization, etc.),
Activation functions (sigmoid, tanh function, ReLU, leaky ReLU information, Maxout, Softmax).
あるAIモデルは、別のAIモデルのコンポーネントとして含まれてもよい。例えば、あるAIモデルは、モデルコンポーネント#1であるResNet、モデルコンポーネント#2であるトランスフォーマーモデル、デンス層及び正規化層の順に処理が進むAIモデルであってもよい。
An AI model may be included as a component of another AI model. For example, an AI model may be an AI model in which processing proceeds in the order of model component #1 (ResNet), model component #2 (a transformer model), a dense layer, and a normalization layer.
上記AIモデルのための訓練情報は、以下の少なくとも1つに関する情報を含んでもよい:
・最適化アルゴリズムのための情報(例えば、最適化の種類(確率的勾配降下法(Stochastic Gradient Descent(SGD)))、AdaGrad、Adamなど)、最適化のパラメータ(学習率(learning rate)、モメンタム情報など)、
・損失関数の情報(例えば、損失関数の指標(metrics)に関する情報(平均絶対誤差(Mean Absolute Error(MAE))、平均二乗誤差(Mean Square Error(MSE))、クロスエントロピーロス、NLLLoss、Kullback-Leibler(KL)ダイバージェンスなど))、
・訓練用に凍結されるべきパラメータ(例えば、レイヤ、重み)、
・更新されるべきパラメータ(例えば、レイヤ、重み)、
・訓練用の初期パラメータであるべき(初期パラメータとして用いられるべき)パラメータ(例えば、レイヤ、重み)、
・AIモデルの訓練/更新方法(例えば、(推奨)エポック数、バッチサイズ、訓練に使用するデータ数)。 Training information for the AI model may include information regarding at least one of the following:
Information for the optimization algorithm (e.g., type of optimization (Stochastic Gradient Descent (SGD)), AdaGrad, Adam, etc.), parameters of the optimization (learning rate, momentum information, etc.),
Loss function information (e.g., information on metrics of the loss function (Mean Absolute Error (MAE)), Mean Square Error (MSE), Cross Entropy Loss, NLL Loss, Kullback-Leibler (KL) Divergence, etc.));
- parameters to be frozen for training (e.g. layers, weights),
- parameters to be updated (e.g. layers, weights),
- parameters that should be (used as) initial parameters for training (e.g. layers, weights);
How to train/update the AI model (e.g., (recommended) number of epochs, batch size, number of data used for training).
・最適化アルゴリズムのための情報(例えば、最適化の種類(確率的勾配降下法(Stochastic Gradient Descent(SGD)))、AdaGrad、Adamなど)、最適化のパラメータ(学習率(learning rate)、モメンタム情報など)、
・損失関数の情報(例えば、損失関数の指標(metrics)に関する情報(平均絶対誤差(Mean Absolute Error(MAE))、平均二乗誤差(Mean Square Error(MSE))、クロスエントロピーロス、NLLLoss、Kullback-Leibler(KL)ダイバージェンスなど))、
・訓練用に凍結されるべきパラメータ(例えば、レイヤ、重み)、
・更新されるべきパラメータ(例えば、レイヤ、重み)、
・訓練用の初期パラメータであるべき(初期パラメータとして用いられるべき)パラメータ(例えば、レイヤ、重み)、
・AIモデルの訓練/更新方法(例えば、(推奨)エポック数、バッチサイズ、訓練に使用するデータ数)。 Training information for the AI model may include information regarding at least one of the following:
Information for the optimization algorithm (e.g., type of optimization (Stochastic Gradient Descent (SGD)), AdaGrad, Adam, etc.), parameters of the optimization (learning rate, momentum information, etc.),
Loss function information (e.g., information on metrics of the loss function (Mean Absolute Error (MAE)), Mean Square Error (MSE), Cross Entropy Loss, NLL Loss, Kullback-Leibler (KL) Divergence, etc.));
- parameters to be frozen for training (e.g. layers, weights),
- parameters to be updated (e.g. layers, weights),
- parameters that should be (used as) initial parameters for training (e.g. layers, weights);
How to train/update the AI model (e.g., (recommended) number of epochs, batch size, number of data used for training).
上記AIモデルのための推論情報は、決定木の枝剪定(branch pruning)、パラメータ量子化、AIモデルの機能などに関する情報を含んでもよい。ここで、AIモデルの機能は、例えば、時間ドメインビーム予測、空間ドメインビーム予測、CSIフィードバック向けのオートエンコーダ、ビーム管理向けのオートエンコーダなどの少なくとも1つに該当してもよい。
The inference information for the AI model may include information regarding decision tree branch pruning, parameter quantization, and the function of the AI model. Here, the function of the AI model may correspond to at least one of, for example, time domain beam prediction, spatial domain beam prediction, an autoencoder for CSI feedback, and an autoencoder for beam management.
CSIフィードバック向けのオートエンコーダは、以下のように用いられてもよい:
・UEは、エンコーダのAIモデルに、CSI/チャネル行列/プリコーディング行列を入力して出力される、エンコードされるビットを、CSIフィードバック(CSIレポート)として送信する、
・BSは、デコーダのAIモデルに、受信したエンコードされるビットを入力して出力される、CSI/チャネル行列/プリコーディング行列を再構成する。 An autoencoder for CSI feedback may be used as follows:
The UE inputs the CSI/channel matrix/precoding matrix into the AI model of the encoder and transmits the encoded bits as CSI feedback (CSI report);
- The BS reconstructs the CSI/channel matrix/precoding matrix, which is output as input to the AI model of the decoder using the received encoded bits.
・UEは、エンコーダのAIモデルに、CSI/チャネル行列/プリコーディング行列を入力して出力される、エンコードされるビットを、CSIフィードバック(CSIレポート)として送信する、
・BSは、デコーダのAIモデルに、受信したエンコードされるビットを入力して出力される、CSI/チャネル行列/プリコーディング行列を再構成する。 An autoencoder for CSI feedback may be used as follows:
The UE inputs the CSI/channel matrix/precoding matrix into the AI model of the encoder and transmits the encoded bits as CSI feedback (CSI report);
- The BS reconstructs the CSI/channel matrix/precoding matrix, which is output as input to the AI model of the decoder using the received encoded bits.
空間ドメインビーム予測では、UE/BSは、AIモデルに、疎な(又は太い)ビームに基づく測定結果(ビーム品質。例えば、RSRP)を入力して、密な(又は細い)ビーム品質を出力してもよい。
In spatial domain beam prediction, the UE/BS may input measurement results (beam quality, e.g., RSRP) based on sparse (or thick) beams into an AI model, which may output dense (or thin) beam quality.
時間ドメインビーム予測では、UE/BSは、AIモデルに、時系列(過去、現在などの)測定結果(ビーム品質。例えば、RSRP)を入力して、将来のビーム品質を出力してもよい。
In time domain beam prediction, the UE/BS may input time series (past, present, etc.) measurement results (beam quality, e.g., RSRP) into an AI model and output future beam quality.
上記AIモデルに関する性能情報は、AIモデルのために定義される損失関数の期待値に関する情報を含んでもよい。
The performance information regarding the AI model may include information regarding the expected value of a loss function defined for the AI model.
本開示におけるAIモデル情報は、AIモデルの適用範囲(適用可能範囲)に関する情報を含んでもよい。当該適用範囲は、物理セルID、サービングセルインデックスなどによって示されてもよい。適用範囲に関する情報は、上述の環境情報に含まれてもよい。
The AI model information in this disclosure may include information regarding the scope of application (scope of applicability) of the AI model. The scope of application may be indicated by a physical cell ID, a serving cell index, etc. Information regarding the scope of application may be included in the above-mentioned environmental information.
特定のAIモデルに関するAIモデル情報は、規格において予め定められてもよいし、ネットワーク(Network(NW))からUEに通知されてもよい。規格において規定されるAIモデルは、参照(reference)AIモデルと呼ばれてもよい。参照AIモデルに関するAIモデル情報は、参照AIモデル情報と呼ばれてもよい。
AI model information regarding a specific AI model may be predetermined in a standard, or may be notified to the UE from the network (NW). An AI model defined in a standard may be referred to as a reference AI model. AI model information regarding a reference AI model may be referred to as reference AI model information.
なお、本開示におけるAIモデル情報は、AIモデルを特定するためのインデックス(例えば、AIモデルインデックス、AIモデルID、モデルIDなどと呼ばれてもよい)を含んでもよい。本開示におけるAIモデル情報は、上述のAIモデルの入力/出力の情報などに加えて/の代わりに、AIモデルインデックスを含んでもよい。AIモデルインデックスとAIモデル情報(例えば、AIモデルの入力/出力の情報)との関連付けは、規格において予め定められてもよいし、NWからUEに通知されてもよい。
The AI model information in the present disclosure may include an index for identifying the AI model (e.g., may be called an AI model index, an AI model ID, a model ID, etc.). The AI model information in the present disclosure may include an AI model index in addition to/instead of the input/output information of the AI model described above. The association between the AI model index and the AI model information (e.g., input/output information of the AI model) may be predetermined in a standard, or may be notified to the UE from the NW.
本開示におけるAIモデル情報は、AIモデルに関連付けられてもよく、AIモデル関連情報(relevant information)、単に関連情報などと呼ばれてもよい。AIモデル関連情報には、AIモデルを特定するための情報は明示的に含まれなくてもよい。AIモデル関連情報は、例えばメタ情報のみを含んだ情報であってもよい。
The AI model information in this disclosure may be associated with an AI model and may be referred to as AI model relevant information, simply relevant information, etc. The AI model relevant information does not need to explicitly include information for identifying the AI model. The AI model relevant information may be information that includes only meta information, for example.
本開示において、モデルIDは、AIモデルのセットに対応するID(モデルセットID)と互いに読み替えられてもよい。また、本開示において、モデルIDは、メタ情報IDと互いに読み替えられてもよい。メタ情報(又はメタ情報ID)は、上述したようにビームに関する情報(ビーム設定)と関連付けられてもよい。例えば、メタ情報(又はメタ情報ID)は、どのビームをBSが使用しているかを考慮してUEがAIモデルを選択するために用いられてもよいし、UEがデプロイしたAIモデルを適用するためにBSがどのビームを使用すべきかを通知するために用いられてもよい。なお、本開示において、メタ情報IDは、メタ情報のセットに対応するID(メタ情報セットID)と互いに読み替えられてもよい。
In the present disclosure, the model ID may be interchangeably read as an ID (model set ID) corresponding to a set of AI models. Also, in the present disclosure, the model ID may be interchangeably read as a meta information ID. The meta information (or meta information ID) may be associated with information regarding the beam (beam setting) as described above. For example, the meta information (or meta information ID) may be used by the UE to select an AI model taking into account which beam the BS is using, or may be used to notify the BS of which beam to use to apply the AI model deployed by the UE. Also, in the present disclosure, the meta information ID may be interchangeably read as an ID (meta information set ID) corresponding to a set of meta information.
[UEへの情報の通知]
上述の実施形態における(NWから)UEへの任意の情報の通知(言い換えると、UEにおけるBSからの任意の情報の受信)は、物理レイヤシグナリング(例えば、DCI)、上位レイヤシグナリング(例えば、RRCシグナリング、MAC CE)、特定の信号/チャネル(例えば、PDCCH、PDSCH、参照信号)、又はこれらの組み合わせを用いて行われてもよい。 [Notification of information to UE]
In the above-described embodiment, any information may be notified to the UE (from the NW) (in other words, any information received from the BS in the UE) using physical layer signaling (e.g., DCI), higher layer signaling (e.g., RRC signaling, MAC CE), a specific signal/channel (e.g., PDCCH, PDSCH, reference signal), or a combination thereof.
上述の実施形態における(NWから)UEへの任意の情報の通知(言い換えると、UEにおけるBSからの任意の情報の受信)は、物理レイヤシグナリング(例えば、DCI)、上位レイヤシグナリング(例えば、RRCシグナリング、MAC CE)、特定の信号/チャネル(例えば、PDCCH、PDSCH、参照信号)、又はこれらの組み合わせを用いて行われてもよい。 [Notification of information to UE]
In the above-described embodiment, any information may be notified to the UE (from the NW) (in other words, any information received from the BS in the UE) using physical layer signaling (e.g., DCI), higher layer signaling (e.g., RRC signaling, MAC CE), a specific signal/channel (e.g., PDCCH, PDSCH, reference signal), or a combination thereof.
上記通知がMAC CEによって行われる場合、当該MAC CEは、既存の規格では規定されていない新たな論理チャネルID(Logical Channel ID(LCID))がMACサブヘッダに含まれることによって識別されてもよい。
When the above notification is performed by a MAC CE, the MAC CE may be identified by including a new Logical Channel ID (LCID) in the MAC subheader that is not specified in existing standards.
上記通知がDCIによって行われる場合、上記通知は、当該DCIの特定のフィールド、当該DCIに付与される巡回冗長検査(Cyclic Redundancy Check(CRC))ビットのスクランブルに用いられる無線ネットワーク一時識別子(Radio Network Temporary Identifier(RNTI))、当該DCIのフォーマットなどによって行われてもよい。
When the notification is made by a DCI, the notification may be made by a specific field of the DCI, a Radio Network Temporary Identifier (RNTI) used to scramble Cyclic Redundancy Check (CRC) bits assigned to the DCI, the format of the DCI, etc.
また、上述の実施形態におけるUEへの任意の情報の通知は、周期的、セミパーシステント又は非周期的に行われてもよい。
Furthermore, notification of any information to the UE in the above-mentioned embodiments may be performed periodically, semi-persistently, or aperiodically.
[UEからの情報の通知]
上述の実施形態におけるUEから(NWへ)の任意の情報の通知(言い換えると、UEにおけるBSへの任意の情報の送信/報告)は、物理レイヤシグナリング(例えば、UCI)、上位レイヤシグナリング(例えば、RRCシグナリング、MAC CE)、特定の信号/チャネル(例えば、PUCCH、PUSCH、参照信号)、又はこれらの組み合わせを用いて行われてもよい。 [Information notification from UE]
In the above-described embodiments, notification of any information from the UE (to the NW) (in other words, transmission/report of any information from the UE to the BS) may be performed using physical layer signaling (e.g., UCI), higher layer signaling (e.g., RRC signaling, MAC CE), a specific signal/channel (e.g., PUCCH, PUSCH, reference signal), or a combination thereof.
上述の実施形態におけるUEから(NWへ)の任意の情報の通知(言い換えると、UEにおけるBSへの任意の情報の送信/報告)は、物理レイヤシグナリング(例えば、UCI)、上位レイヤシグナリング(例えば、RRCシグナリング、MAC CE)、特定の信号/チャネル(例えば、PUCCH、PUSCH、参照信号)、又はこれらの組み合わせを用いて行われてもよい。 [Information notification from UE]
In the above-described embodiments, notification of any information from the UE (to the NW) (in other words, transmission/report of any information from the UE to the BS) may be performed using physical layer signaling (e.g., UCI), higher layer signaling (e.g., RRC signaling, MAC CE), a specific signal/channel (e.g., PUCCH, PUSCH, reference signal), or a combination thereof.
上記通知がMAC CEによって行われる場合、当該MAC CEは、既存の規格では規定されていない新たなLCIDがMACサブヘッダに含まれることによって識別されてもよい。
If the notification is made by a MAC CE, the MAC CE may be identified by including a new LCID in the MAC subheader that is not specified in existing standards.
上記通知がUCIによって行われる場合、上記通知は、PUCCH又はPUSCHを用いて送信されてもよい。
If the notification is made by UCI, the notification may be transmitted using PUCCH or PUSCH.
また、上述の実施形態におけるUEからの任意の情報の通知は、周期的、セミパーシステント又は非周期的に行われてもよい。
Furthermore, in the above-mentioned embodiments, notification of any information from the UE may be performed periodically, semi-persistently, or aperiodically.
[各実施形態の適用について]
上述の実施形態の少なくとも1つは、特定の条件を満たす場合に適用されてもよい。当該特定の条件は、規格において規定されてもよいし、上位レイヤシグナリング/物理レイヤシグナリングを用いてUE/BSに通知されてもよい。 [Application of each embodiment]
At least one of the above-mentioned embodiments may be applied when a specific condition is satisfied, which may be specified in a standard or may be notified to a UE/BS using higher layer signaling/physical layer signaling.
上述の実施形態の少なくとも1つは、特定の条件を満たす場合に適用されてもよい。当該特定の条件は、規格において規定されてもよいし、上位レイヤシグナリング/物理レイヤシグナリングを用いてUE/BSに通知されてもよい。 [Application of each embodiment]
At least one of the above-mentioned embodiments may be applied when a specific condition is satisfied, which may be specified in a standard or may be notified to a UE/BS using higher layer signaling/physical layer signaling.
上述の実施形態の少なくとも1つは、特定のUE能力(UE capability)を報告した又は当該特定のUE能力をサポートするUEに対してのみ適用されてもよい。
At least one of the above-described embodiments may be applied only to UEs that have reported or support a particular UE capability.
当該特定のUE能力は、以下の少なくとも1つを示してもよい:
・上記実施形態の少なくとも1つについての特定の処理/動作/制御/情報をサポートすること、
・ビーム予測をサポートすること、
・ビーム予測のための報告をサポートすること、
・L1-RSRPを含まないビームレポートをサポートすること、
・ビーム情報(トップX確率、トップX’/1確率などの少なくとも1つ)の報告をサポートすること、
・1つの報告インスタンスにおける(サポートする)トップX確率又はトップX’/1確率の数、
・1つの報告インスタンスにおける(サポートする)能力インデックスの数。 The specific UE capabilities may indicate at least one of the following:
Supporting specific processing/operations/control/information for at least one of the above embodiments;
Supporting beam prediction;
Supporting reporting for beam predictions;
Supporting beam reports that do not include L1-RSRP;
Support reporting of beam information (at least one of top X probability, top X′/1 probability, etc.);
Number of (supported) top-X or top-X'/1 probabilities in one reporting instance;
The number of (supported) capability indexes in one reporting instance.
・上記実施形態の少なくとも1つについての特定の処理/動作/制御/情報をサポートすること、
・ビーム予測をサポートすること、
・ビーム予測のための報告をサポートすること、
・L1-RSRPを含まないビームレポートをサポートすること、
・ビーム情報(トップX確率、トップX’/1確率などの少なくとも1つ)の報告をサポートすること、
・1つの報告インスタンスにおける(サポートする)トップX確率又はトップX’/1確率の数、
・1つの報告インスタンスにおける(サポートする)能力インデックスの数。 The specific UE capabilities may indicate at least one of the following:
Supporting specific processing/operations/control/information for at least one of the above embodiments;
Supporting beam prediction;
Supporting reporting for beam predictions;
Supporting beam reports that do not include L1-RSRP;
Support reporting of beam information (at least one of top X probability, top X′/1 probability, etc.);
Number of (supported) top-X or top-X'/1 probabilities in one reporting instance;
The number of (supported) capability indexes in one reporting instance.
また、上記特定のUE能力は、全周波数にわたって(周波数に関わらず共通に)適用される能力であってもよいし、周波数(例えば、セル、バンド、バンドコンビネーション、BWP、コンポーネントキャリアなどの1つ又はこれらの組み合わせ)ごとの能力であってもよいし、周波数レンジ(例えば、Frequency Range 1(FR1)、FR2、FR3、FR4、FR5、FR2-1、FR2-2)ごとの能力であってもよいし、サブキャリア間隔(SubCarrier Spacing(SCS))ごとの能力であってもよいし、Feature Set(FS)又はFeature Set Per Component-carrier(FSPC)ごとの能力であってもよい。
Furthermore, the above-mentioned specific UE capabilities may be capabilities that are applied across all frequencies (commonly regardless of frequency), capabilities per frequency (e.g., one or a combination of a cell, band, band combination, BWP, component carrier, etc.), capabilities per frequency range (e.g., Frequency Range 1 (FR1), FR2, FR3, FR4, FR5, FR2-1, FR2-2), capabilities per subcarrier spacing (SubCarrier Spacing (SCS)), or capabilities per Feature Set (FS) or Feature Set Per Component-carrier (FSPC).
また、上記特定のUE能力は、全複信方式にわたって(複信方式に関わらず共通に)適用される能力であってもよいし、複信方式(例えば、時分割複信(Time Division Duplex(TDD))、周波数分割複信(Frequency Division Duplex(FDD)))ごとの能力であってもよい。
The specific UE capabilities may be capabilities that are applied across all duplexing methods (commonly regardless of the duplexing method), or may be capabilities for each duplexing method (e.g., Time Division Duplex (TDD) and Frequency Division Duplex (FDD)).
また、上述の実施形態の少なくとも1つは、UEが上位レイヤシグナリング/物理レイヤシグナリングによって、上述の実施形態に関連する特定の情報(又は上述の実施形態の動作を実施すること)を設定/アクティベート/トリガされた場合に適用されてもよい。例えば、当該特定の情報は、AIモデルの利用を有効化することを示す情報、CSI予測を有効化することを示す情報、特定のビーム情報の報告を有効化することを示す情報、特定のリリース(例えば、Rel.18/19)向けの任意のRRCパラメータなどであってもよい。
Furthermore, at least one of the above-mentioned embodiments may be applied when the UE configures/activates/triggers specific information related to the above-mentioned embodiments (or performs the operations of the above-mentioned embodiments) by higher layer signaling/physical layer signaling. For example, the specific information may be information indicating the enablement of the use of an AI model, information indicating the enablement of CSI prediction, information indicating the enablement of reporting of specific beam information, any RRC parameters for a specific release (e.g., Rel. 18/19), etc.
UEは、上記特定のUE能力の少なくとも1つをサポートしない又は上記特定の情報を設定されない場合、例えばRel.15/16の動作を適用してもよい。
If the UE does not support at least one of the above specific UE capabilities or the above specific information is not configured, the UE may, for example, apply Rel. 15/16 operations.
(付記)
本開示の一実施形態に関して、以下の発明を付記する。
[付記1]
受信電力又は受信品質に関する、確率でない測定又は予測の結果を含まないビームレポートを生成する制御部と、
前記ビームレポートを送信する送信部と、を有する端末。
[付記2]
前記制御部は、リソースを示すフィールドと、前記リソースのトップX確率を示すフィールドと、を含む前記ビームレポートを生成する、ここで、前記トップX確率は、1つ以上のリソースのうちの前記リソースに対応する前記結果が、前記1つ以上のリソースに対応する前記結果のうち、X番目に大きい前記結果以上の値である確率である、付記1に記載の端末。
[付記3]
前記制御部は、1つ以上のリソースに関するトップX’/1確率を示すフィールドを含む前記ビームレポートを生成する、ここで、前記トップX’/1確率は、X’個のリソースに対応する前記結果の少なくとも1つが、前記1つ以上のリソースに対応する前記結果のなかで最大となる確率である、付記1又は付記2に記載の端末。 (Additional Note)
With respect to one embodiment of the present disclosure, the following invention is noted.
[Appendix 1]
A control unit that generates a beam report that does not include non-probabilistic measurement or prediction results regarding reception power or reception quality;
A terminal having a transmitting unit that transmits the beam report.
[Appendix 2]
The control unit generates the beam report including a field indicating a resource and a field indicating a top X probability of the resource, where the top X probability is a probability that the result corresponding to the resource among one or more resources is equal to or greater than the Xth largest result among the results corresponding to the one or more resources.
[Appendix 3]
The terminal of claim 1 or 2, wherein the control unit generates the beam report including a field indicating a top X'/1 probability for one or more resources, where the top X'/1 probability is the probability that at least one of the results corresponding to X' resources is the maximum among the results corresponding to the one or more resources.
本開示の一実施形態に関して、以下の発明を付記する。
[付記1]
受信電力又は受信品質に関する、確率でない測定又は予測の結果を含まないビームレポートを生成する制御部と、
前記ビームレポートを送信する送信部と、を有する端末。
[付記2]
前記制御部は、リソースを示すフィールドと、前記リソースのトップX確率を示すフィールドと、を含む前記ビームレポートを生成する、ここで、前記トップX確率は、1つ以上のリソースのうちの前記リソースに対応する前記結果が、前記1つ以上のリソースに対応する前記結果のうち、X番目に大きい前記結果以上の値である確率である、付記1に記載の端末。
[付記3]
前記制御部は、1つ以上のリソースに関するトップX’/1確率を示すフィールドを含む前記ビームレポートを生成する、ここで、前記トップX’/1確率は、X’個のリソースに対応する前記結果の少なくとも1つが、前記1つ以上のリソースに対応する前記結果のなかで最大となる確率である、付記1又は付記2に記載の端末。 (Additional Note)
With respect to one embodiment of the present disclosure, the following invention is noted.
[Appendix 1]
A control unit that generates a beam report that does not include non-probabilistic measurement or prediction results regarding reception power or reception quality;
A terminal having a transmitting unit that transmits the beam report.
[Appendix 2]
The control unit generates the beam report including a field indicating a resource and a field indicating a top X probability of the resource, where the top X probability is a probability that the result corresponding to the resource among one or more resources is equal to or greater than the Xth largest result among the results corresponding to the one or more resources.
[Appendix 3]
The terminal of
(無線通信システム)
以下、本開示の一実施形態に係る無線通信システムの構成について説明する。この無線通信システムでは、本開示の上記各実施形態に係る無線通信方法のいずれか又はこれらの組み合わせを用いて通信が行われる。 (Wireless communication system)
A configuration of a wireless communication system according to an embodiment of the present disclosure will be described below. In this wireless communication system, communication is performed using any one of the wireless communication methods according to the above embodiments of the present disclosure or a combination of these.
以下、本開示の一実施形態に係る無線通信システムの構成について説明する。この無線通信システムでは、本開示の上記各実施形態に係る無線通信方法のいずれか又はこれらの組み合わせを用いて通信が行われる。 (Wireless communication system)
A configuration of a wireless communication system according to an embodiment of the present disclosure will be described below. In this wireless communication system, communication is performed using any one of the wireless communication methods according to the above embodiments of the present disclosure or a combination of these.
図10は、一実施形態に係る無線通信システムの概略構成の一例を示す図である。無線通信システム1(単にシステム1と呼ばれてもよい)は、Third Generation Partnership Project(3GPP)によって仕様化されるLong Term Evolution(LTE)、5th generation mobile communication system New Radio(5G NR)などを用いて通信を実現するシステムであってもよい。
FIG. 10 is a diagram showing an example of a schematic configuration of a wireless communication system according to an embodiment. The wireless communication system 1 (which may simply be referred to as system 1) may be a system that realizes communication using Long Term Evolution (LTE) specified by the Third Generation Partnership Project (3GPP), 5th generation mobile communication system New Radio (5G NR), or the like.
また、無線通信システム1は、複数のRadio Access Technology(RAT)間のデュアルコネクティビティ(マルチRATデュアルコネクティビティ(Multi-RAT Dual Connectivity(MR-DC)))をサポートしてもよい。MR-DCは、LTE(Evolved Universal Terrestrial Radio Access(E-UTRA))とNRとのデュアルコネクティビティ(E-UTRA-NR Dual Connectivity(EN-DC))、NRとLTEとのデュアルコネクティビティ(NR-E-UTRA Dual Connectivity(NE-DC))などを含んでもよい。
The wireless communication system 1 may also support dual connectivity between multiple Radio Access Technologies (RATs) (Multi-RAT Dual Connectivity (MR-DC)). MR-DC may include dual connectivity between LTE (Evolved Universal Terrestrial Radio Access (E-UTRA)) and NR (E-UTRA-NR Dual Connectivity (EN-DC)), dual connectivity between NR and LTE (NR-E-UTRA Dual Connectivity (NE-DC)), etc.
EN-DCでは、LTE(E-UTRA)の基地局(eNB)がマスタノード(Master Node(MN))であり、NRの基地局(gNB)がセカンダリノード(Secondary Node(SN))である。NE-DCでは、NRの基地局(gNB)がMNであり、LTE(E-UTRA)の基地局(eNB)がSNである。
In EN-DC, the LTE (E-UTRA) base station (eNB) is the master node (MN), and the NR base station (gNB) is the secondary node (SN). In NE-DC, the NR base station (gNB) is the MN, and the LTE (E-UTRA) base station (eNB) is the SN.
無線通信システム1は、同一のRAT内の複数の基地局間のデュアルコネクティビティ(例えば、MN及びSNの双方がNRの基地局(gNB)であるデュアルコネクティビティ(NR-NR Dual Connectivity(NN-DC)))をサポートしてもよい。
The wireless communication system 1 may support dual connectivity between multiple base stations within the same RAT (e.g., dual connectivity in which both the MN and SN are NR base stations (gNBs) (NR-NR Dual Connectivity (NN-DC))).
無線通信システム1は、比較的カバレッジの広いマクロセルC1を形成する基地局11と、マクロセルC1内に配置され、マクロセルC1よりも狭いスモールセルC2を形成する基地局12(12a-12c)と、を備えてもよい。ユーザ端末20は、少なくとも1つのセル内に位置してもよい。各セル及びユーザ端末20の配置、数などは、図に示す態様に限定されない。以下、基地局11及び12を区別しない場合は、基地局10と総称する。
The wireless communication system 1 may include a base station 11 that forms a macrocell C1 with a relatively wide coverage, and base stations 12 (12a-12c) that are arranged within the macrocell C1 and form a small cell C2 that is narrower than the macrocell C1. A user terminal 20 may be located within at least one of the cells. The arrangement and number of each cell and user terminal 20 are not limited to the aspect shown in the figure. Hereinafter, when there is no need to distinguish between the base stations 11 and 12, they will be collectively referred to as base station 10.
ユーザ端末20は、複数の基地局10のうち、少なくとも1つに接続してもよい。ユーザ端末20は、複数のコンポーネントキャリア(Component Carrier(CC))を用いたキャリアアグリゲーション(Carrier Aggregation(CA))及びデュアルコネクティビティ(DC)の少なくとも一方を利用してもよい。
The user terminal 20 may be connected to at least one of the multiple base stations 10. The user terminal 20 may utilize at least one of carrier aggregation (CA) using multiple component carriers (CC) and dual connectivity (DC).
各CCは、第1の周波数帯(Frequency Range 1(FR1))及び第2の周波数帯(Frequency Range 2(FR2))の少なくとも1つに含まれてもよい。マクロセルC1はFR1に含まれてもよいし、スモールセルC2はFR2に含まれてもよい。例えば、FR1は、6GHz以下の周波数帯(サブ6GHz(sub-6GHz))であってもよいし、FR2は、24GHzよりも高い周波数帯(above-24GHz)であってもよい。なお、FR1及びFR2の周波数帯、定義などはこれらに限られず、例えばFR1がFR2よりも高い周波数帯に該当してもよい。
Each CC may be included in at least one of a first frequency band (Frequency Range 1 (FR1)) and a second frequency band (Frequency Range 2 (FR2)). Macro cell C1 may be included in FR1, and small cell C2 may be included in FR2. For example, FR1 may be a frequency band below 6 GHz (sub-6 GHz), and FR2 may be a frequency band above 24 GHz (above-24 GHz). Note that the frequency bands and definitions of FR1 and FR2 are not limited to these, and for example, FR1 may correspond to a higher frequency band than FR2.
また、ユーザ端末20は、各CCにおいて、時分割複信(Time Division Duplex(TDD))及び周波数分割複信(Frequency Division Duplex(FDD))の少なくとも1つを用いて通信を行ってもよい。
In addition, the user terminal 20 may communicate using at least one of Time Division Duplex (TDD) and Frequency Division Duplex (FDD) in each CC.
複数の基地局10は、有線(例えば、Common Public Radio Interface(CPRI)に準拠した光ファイバ、X2インターフェースなど)又は無線(例えば、NR通信)によって接続されてもよい。例えば、基地局11及び12間においてNR通信がバックホールとして利用される場合、上位局に該当する基地局11はIntegrated Access Backhaul(IAB)ドナー、中継局(リレー)に該当する基地局12はIABノードと呼ばれてもよい。
The multiple base stations 10 may be connected by wire (e.g., optical fiber conforming to the Common Public Radio Interface (CPRI), X2 interface, etc.) or wirelessly (e.g., NR communication). For example, when NR communication is used as a backhaul between base stations 11 and 12, base station 11, which corresponds to the upper station, may be called an Integrated Access Backhaul (IAB) donor, and base station 12, which corresponds to a relay station, may be called an IAB node.
基地局10は、他の基地局10を介して、又は直接コアネットワーク30に接続されてもよい。コアネットワーク30は、例えば、Evolved Packet Core(EPC)、5G Core Network(5GCN)、Next Generation Core(NGC)などの少なくとも1つを含んでもよい。
The base station 10 may be connected to the core network 30 directly or via another base station 10. The core network 30 may include at least one of, for example, an Evolved Packet Core (EPC), a 5G Core Network (5GCN), a Next Generation Core (NGC), etc.
コアネットワーク30は、例えば、User Plane Function(UPF)、Access and Mobility management Function(AMF)、Session Management Function(SMF)、Unified Data Management(UDM)、Application Function(AF)、Data Network(DN)、Location Management Function(LMF)、保守運用管理(Operation、Administration and Maintenance(Management)(OAM))などのネットワーク機能(Network Functions(NF))を含んでもよい。なお、1つのネットワークノードによって複数の機能が提供されてもよい。また、DNを介して外部ネットワーク(例えば、インターネット)との通信が行われてもよい。
The core network 30 may include network functions (Network Functions (NF)) such as, for example, a User Plane Function (UPF), an Access and Mobility management Function (AMF), a Session Management Function (SMF), a Unified Data Management (UDM), an Application Function (AF), a Data Network (DN), a Location Management Function (LMF), and Operation, Administration and Maintenance (Management) (OAM). Note that multiple functions may be provided by one network node. In addition, communication with an external network (e.g., the Internet) may be performed via the DN.
ユーザ端末20は、LTE、LTE-A、5Gなどの通信方式の少なくとも1つに対応した端末であってもよい。
The user terminal 20 may be a terminal that supports at least one of the communication methods such as LTE, LTE-A, and 5G.
無線通信システム1においては、直交周波数分割多重(Orthogonal Frequency Division Multiplexing(OFDM))ベースの無線アクセス方式が利用されてもよい。例えば、下りリンク(Downlink(DL))及び上りリンク(Uplink(UL))の少なくとも一方において、Cyclic Prefix OFDM(CP-OFDM)、Discrete Fourier Transform Spread OFDM(DFT-s-OFDM)、Orthogonal Frequency Division Multiple Access(OFDMA)、Single Carrier Frequency Division Multiple Access(SC-FDMA)などが利用されてもよい。
In the wireless communication system 1, a wireless access method based on Orthogonal Frequency Division Multiplexing (OFDM) may be used. For example, in at least one of the downlink (DL) and uplink (UL), Cyclic Prefix OFDM (CP-OFDM), Discrete Fourier Transform Spread OFDM (DFT-s-OFDM), Orthogonal Frequency Division Multiple Access (OFDMA), Single Carrier Frequency Division Multiple Access (SC-FDMA), etc. may be used.
無線アクセス方式は、波形(waveform)と呼ばれてもよい。なお、無線通信システム1においては、UL及びDLの無線アクセス方式には、他の無線アクセス方式(例えば、他のシングルキャリア伝送方式、他のマルチキャリア伝送方式)が用いられてもよい。
The radio access method may also be called a waveform. In the wireless communication system 1, other radio access methods (e.g., other single-carrier transmission methods, other multi-carrier transmission methods) may be used for the UL and DL radio access methods.
無線通信システム1では、下りリンクチャネルとして、各ユーザ端末20で共有される下り共有チャネル(Physical Downlink Shared Channel(PDSCH))、ブロードキャストチャネル(Physical Broadcast Channel(PBCH))、下り制御チャネル(Physical Downlink Control Channel(PDCCH))などが用いられてもよい。
In the wireless communication system 1, a downlink shared channel (Physical Downlink Shared Channel (PDSCH)) shared by each user terminal 20, a broadcast channel (Physical Broadcast Channel (PBCH)), a downlink control channel (Physical Downlink Control Channel (PDCCH)), etc. may be used as the downlink channel.
また、無線通信システム1では、上りリンクチャネルとして、各ユーザ端末20で共有される上り共有チャネル(Physical Uplink Shared Channel(PUSCH))、上り制御チャネル(Physical Uplink Control Channel(PUCCH))、ランダムアクセスチャネル(Physical Random Access Channel(PRACH))などが用いられてもよい。
In addition, in the wireless communication system 1, an uplink shared channel (Physical Uplink Shared Channel (PUSCH)) shared by each user terminal 20, an uplink control channel (Physical Uplink Control Channel (PUCCH)), a random access channel (Physical Random Access Channel (PRACH)), etc. may be used as an uplink channel.
PDSCHによって、ユーザデータ、上位レイヤ制御情報、System Information Block(SIB)などが伝送される。PUSCHによって、ユーザデータ、上位レイヤ制御情報などが伝送されてもよい。また、PBCHによって、Master Information Block(MIB)が伝送されてもよい。
User data, upper layer control information, System Information Block (SIB), etc. are transmitted via PDSCH. User data, upper layer control information, etc. may also be transmitted via PUSCH. Furthermore, Master Information Block (MIB) may also be transmitted via PBCH.
PDCCHによって、下位レイヤ制御情報が伝送されてもよい。下位レイヤ制御情報は、例えば、PDSCH及びPUSCHの少なくとも一方のスケジューリング情報を含む下り制御情報(Downlink Control Information(DCI))を含んでもよい。
Lower layer control information may be transmitted by the PDCCH. The lower layer control information may include, for example, downlink control information (Downlink Control Information (DCI)) including scheduling information for at least one of the PDSCH and the PUSCH.
なお、PDSCHをスケジューリングするDCIは、DLアサインメント、DL DCIなどと呼ばれてもよいし、PUSCHをスケジューリングするDCIは、ULグラント、UL DCIなどと呼ばれてもよい。なお、PDSCHはDLデータで読み替えられてもよいし、PUSCHはULデータで読み替えられてもよい。
Note that the DCI for scheduling the PDSCH may be called a DL assignment or DL DCI, and the DCI for scheduling the PUSCH may be called a UL grant or UL DCI. Note that the PDSCH may be interpreted as DL data, and the PUSCH may be interpreted as UL data.
PDCCHの検出には、制御リソースセット(COntrol REsource SET(CORESET))及びサーチスペース(search space)が利用されてもよい。CORESETは、DCIをサーチするリソースに対応する。サーチスペースは、PDCCH候補(PDCCH candidates)のサーチ領域及びサーチ方法に対応する。1つのCORESETは、1つ又は複数のサーチスペースに関連付けられてもよい。UEは、サーチスペース設定に基づいて、あるサーチスペースに関連するCORESETをモニタしてもよい。
A control resource set (COntrol REsource SET (CORESET)) and a search space may be used to detect the PDCCH. The CORESET corresponds to the resources to search for DCI. The search space corresponds to the search region and search method of PDCCH candidates. One CORESET may be associated with one or multiple search spaces. The UE may monitor the CORESET associated with a search space based on the search space configuration.
1つのサーチスペースは、1つ又は複数のアグリゲーションレベル(aggregation Level)に該当するPDCCH候補に対応してもよい。1つ又は複数のサーチスペースは、サーチスペースセットと呼ばれてもよい。なお、本開示の「サーチスペース」、「サーチスペースセット」、「サーチスペース設定」、「サーチスペースセット設定」、「CORESET」、「CORESET設定」などは、互いに読み替えられてもよい。
A search space may correspond to PDCCH candidates corresponding to one or more aggregation levels. One or more search spaces may be referred to as a search space set. Note that the terms "search space," "search space set," "search space setting," "search space set setting," "CORESET," "CORESET setting," etc. in this disclosure may be read as interchangeable.
PUCCHによって、チャネル状態情報(Channel State Information(CSI))、送達確認情報(例えば、Hybrid Automatic Repeat reQuest ACKnowledgement(HARQ-ACK)、ACK/NACKなどと呼ばれてもよい)及びスケジューリングリクエスト(Scheduling Request(SR))の少なくとも1つを含む上り制御情報(Uplink Control Information(UCI))が伝送されてもよい。PRACHによって、セルとの接続確立のためのランダムアクセスプリアンブルが伝送されてもよい。
The PUCCH may transmit uplink control information (UCI) including at least one of channel state information (CSI), delivery confirmation information (which may be called, for example, Hybrid Automatic Repeat reQuest ACKnowledgement (HARQ-ACK), ACK/NACK, etc.), and a scheduling request (SR). The PRACH may transmit a random access preamble for establishing a connection with a cell.
なお、本開示において下りリンク、上りリンクなどは「リンク」を付けずに表現されてもよい。また、各種チャネルの先頭に「物理(Physical)」を付けずに表現されてもよい。
Note that in this disclosure, downlink, uplink, etc. may be expressed without adding "link." Also, various channels may be expressed without adding "Physical" to the beginning.
無線通信システム1では、同期信号(Synchronization Signal(SS))、下りリンク参照信号(Downlink Reference Signal(DL-RS))などが伝送されてもよい。無線通信システム1では、DL-RSとして、セル固有参照信号(Cell-specific Reference Signal(CRS))、チャネル状態情報参照信号(Channel State Information Reference Signal(CSI-RS))、復調用参照信号(DeModulation Reference Signal(DMRS))、位置決定参照信号(Positioning Reference Signal(PRS))、位相トラッキング参照信号(Phase Tracking Reference Signal(PTRS))などが伝送されてもよい。
In the wireless communication system 1, a synchronization signal (SS), a downlink reference signal (DL-RS), etc. may be transmitted. In the wireless communication system 1, as the DL-RS, a cell-specific reference signal (CRS), a channel state information reference signal (CSI-RS), a demodulation reference signal (DMRS), a positioning reference signal (PRS), a phase tracking reference signal (PTRS), etc. may be transmitted.
同期信号は、例えば、プライマリ同期信号(Primary Synchronization Signal(PSS))及びセカンダリ同期信号(Secondary Synchronization Signal(SSS))の少なくとも1つであってもよい。SS(PSS、SSS)及びPBCH(及びPBCH用のDMRS)を含む信号ブロックは、SS/PBCHブロック、SS Block(SSB)などと呼ばれてもよい。なお、SS、SSBなども、参照信号と呼ばれてもよい。
The synchronization signal may be, for example, at least one of a Primary Synchronization Signal (PSS) and a Secondary Synchronization Signal (SSS). A signal block including an SS (PSS, SSS) and a PBCH (and a DMRS for PBCH) may be called an SS/PBCH block, an SS Block (SSB), etc. In addition, the SS, SSB, etc. may also be called a reference signal.
また、無線通信システム1では、上りリンク参照信号(Uplink Reference Signal(UL-RS))として、測定用参照信号(Sounding Reference Signal(SRS))、復調用参照信号(DMRS)などが伝送されてもよい。なお、DMRSはユーザ端末固有参照信号(UE-specific Reference Signal)と呼ばれてもよい。
In addition, in the wireless communication system 1, a measurement reference signal (Sounding Reference Signal (SRS)), a demodulation reference signal (DMRS), etc. may be transmitted as an uplink reference signal (UL-RS). Note that the DMRS may also be called a user equipment-specific reference signal (UE-specific Reference Signal).
(基地局)
図11は、一実施形態に係る基地局の構成の一例を示す図である。基地局10は、制御部110、送受信部120、送受信アンテナ130及び伝送路インターフェース(transmission line interface)140を備えている。なお、制御部110、送受信部120及び送受信アンテナ130及び伝送路インターフェース140は、それぞれ1つ以上が備えられてもよい。 (base station)
11 is a diagram showing an example of a configuration of a base station according to an embodiment. Thebase station 10 includes a control unit 110, a transceiver unit 120, a transceiver antenna 130, and a transmission line interface 140. Note that one or more of each of the control unit 110, the transceiver unit 120, the transceiver antenna 130, and the transmission line interface 140 may be provided.
図11は、一実施形態に係る基地局の構成の一例を示す図である。基地局10は、制御部110、送受信部120、送受信アンテナ130及び伝送路インターフェース(transmission line interface)140を備えている。なお、制御部110、送受信部120及び送受信アンテナ130及び伝送路インターフェース140は、それぞれ1つ以上が備えられてもよい。 (base station)
11 is a diagram showing an example of a configuration of a base station according to an embodiment. The
なお、本例では、本実施の形態における特徴部分の機能ブロックを主に示しており、基地局10は、無線通信に必要な他の機能ブロックも有すると想定されてもよい。以下で説明する各部の処理の一部は、省略されてもよい。
Note that this example mainly shows the functional blocks of the characteristic parts of this embodiment, and the base station 10 may also be assumed to have other functional blocks necessary for wireless communication. Some of the processing of each part described below may be omitted.
制御部110は、基地局10全体の制御を実施する。制御部110は、本開示に係る技術分野での共通認識に基づいて説明されるコントローラ、制御回路などから構成することができる。
The control unit 110 controls the entire base station 10. The control unit 110 can be configured from a controller, a control circuit, etc., which are described based on a common understanding in the technical field to which this disclosure pertains.
制御部110は、信号の生成、スケジューリング(例えば、リソース割り当て、マッピング)などを制御してもよい。制御部110は、送受信部120、送受信アンテナ130及び伝送路インターフェース140を用いた送受信、測定などを制御してもよい。制御部110は、信号として送信するデータ、制御情報、系列(sequence)などを生成し、送受信部120に転送してもよい。制御部110は、通信チャネルの呼処理(設定、解放など)、基地局10の状態管理、無線リソースの管理などを行ってもよい。
The control unit 110 may control signal generation, scheduling (e.g., resource allocation, mapping), etc. The control unit 110 may control transmission and reception using the transceiver unit 120, the transceiver antenna 130, and the transmission path interface 140, measurement, etc. The control unit 110 may generate data, control information, sequences, etc. to be transmitted as signals, and transfer them to the transceiver unit 120. The control unit 110 may perform call processing of communication channels (setting, release, etc.), status management of the base station 10, management of radio resources, etc.
送受信部120は、ベースバンド(baseband)部121、Radio Frequency(RF)部122、測定部123を含んでもよい。ベースバンド部121は、送信処理部1211及び受信処理部1212を含んでもよい。送受信部120は、本開示に係る技術分野での共通認識に基づいて説明されるトランスミッター/レシーバー、RF回路、ベースバンド回路、フィルタ、位相シフタ(phase shifter)、測定回路、送受信回路などから構成することができる。
The transceiver unit 120 may include a baseband unit 121, a radio frequency (RF) unit 122, and a measurement unit 123. The baseband unit 121 may include a transmission processing unit 1211 and a reception processing unit 1212. The transceiver unit 120 may be composed of a transmitter/receiver, an RF circuit, a baseband circuit, a filter, a phase shifter, a measurement circuit, a transceiver circuit, etc., which are described based on a common understanding in the technical field to which the present disclosure relates.
送受信部120は、一体の送受信部として構成されてもよいし、送信部及び受信部から構成されてもよい。当該送信部は、送信処理部1211、RF部122から構成されてもよい。当該受信部は、受信処理部1212、RF部122、測定部123から構成されてもよい。
The transceiver unit 120 may be configured as an integrated transceiver unit, or may be composed of a transmission unit and a reception unit. The transmission unit may be composed of a transmission processing unit 1211 and an RF unit 122. The reception unit may be composed of a reception processing unit 1212, an RF unit 122, and a measurement unit 123.
送受信アンテナ130は、本開示に係る技術分野での共通認識に基づいて説明されるアンテナ、例えばアレイアンテナなどから構成することができる。
The transmitting/receiving antenna 130 can be configured as an antenna described based on common understanding in the technical field to which this disclosure pertains, such as an array antenna.
送受信部120は、上述の下りリンクチャネル、同期信号、下りリンク参照信号などを送信してもよい。送受信部120は、上述の上りリンクチャネル、上りリンク参照信号などを受信してもよい。
The transceiver 120 may transmit the above-mentioned downlink channel, synchronization signal, downlink reference signal, etc. The transceiver 120 may receive the above-mentioned uplink channel, uplink reference signal, etc.
送受信部120は、デジタルビームフォーミング(例えば、プリコーディング)、アナログビームフォーミング(例えば、位相回転)などを用いて、送信ビーム及び受信ビームの少なくとも一方を形成してもよい。
The transceiver 120 may form at least one of the transmit beam and the receive beam using digital beamforming (e.g., precoding), analog beamforming (e.g., phase rotation), etc.
送受信部120(送信処理部1211)は、例えば制御部110から取得したデータ、制御情報などに対して、Packet Data Convergence Protocol(PDCP)レイヤの処理、Radio Link Control(RLC)レイヤの処理(例えば、RLC再送制御)、Medium Access Control(MAC)レイヤの処理(例えば、HARQ再送制御)などを行い、送信するビット列を生成してもよい。
The transceiver 120 (transmission processing unit 1211) may perform Packet Data Convergence Protocol (PDCP) layer processing, Radio Link Control (RLC) layer processing (e.g., RLC retransmission control), Medium Access Control (MAC) layer processing (e.g., HARQ retransmission control), etc., on data and control information obtained from the control unit 110, and generate a bit string to be transmitted.
送受信部120(送信処理部1211)は、送信するビット列に対して、チャネル符号化(誤り訂正符号化を含んでもよい)、変調、マッピング、フィルタ処理、離散フーリエ変換(Discrete Fourier Transform(DFT))処理(必要に応じて)、逆高速フーリエ変換(Inverse Fast Fourier Transform(IFFT))処理、プリコーディング、デジタル-アナログ変換などの送信処理を行い、ベースバンド信号を出力してもよい。
The transceiver 120 (transmission processor 1211) may perform transmission processing such as channel coding (which may include error correction coding), modulation, mapping, filtering, Discrete Fourier Transform (DFT) processing (if necessary), Inverse Fast Fourier Transform (IFFT) processing, precoding, and digital-to-analog conversion on the bit string to be transmitted, and output a baseband signal.
送受信部120(RF部122)は、ベースバンド信号に対して、無線周波数帯への変調、フィルタ処理、増幅などを行い、無線周波数帯の信号を、送受信アンテナ130を介して送信してもよい。
The transceiver unit 120 (RF unit 122) may perform modulation, filtering, amplification, etc., on the baseband signal to a radio frequency band, and transmit the radio frequency band signal via the transceiver antenna 130.
一方、送受信部120(RF部122)は、送受信アンテナ130によって受信された無線周波数帯の信号に対して、増幅、フィルタ処理、ベースバンド信号への復調などを行ってもよい。
On the other hand, the transceiver unit 120 (RF unit 122) may perform amplification, filtering, demodulation to a baseband signal, etc. on the radio frequency band signal received by the transceiver antenna 130.
送受信部120(受信処理部1212)は、取得されたベースバンド信号に対して、アナログ-デジタル変換、高速フーリエ変換(Fast Fourier Transform(FFT))処理、逆離散フーリエ変換(Inverse Discrete Fourier Transform(IDFT))処理(必要に応じて)、フィルタ処理、デマッピング、復調、復号(誤り訂正復号を含んでもよい)、MACレイヤ処理、RLCレイヤの処理及びPDCPレイヤの処理などの受信処理を適用し、ユーザデータなどを取得してもよい。
The transceiver 120 (reception processing unit 1212) may apply reception processing such as analog-to-digital conversion, Fast Fourier Transform (FFT) processing, Inverse Discrete Fourier Transform (IDFT) processing (if necessary), filtering, demapping, demodulation, decoding (which may include error correction decoding), MAC layer processing, RLC layer processing, and PDCP layer processing to the acquired baseband signal, and acquire user data, etc.
送受信部120(測定部123)は、受信した信号に関する測定を実施してもよい。例えば、測定部123は、受信した信号に基づいて、Radio Resource Management(RRM)測定、Channel State Information(CSI)測定などを行ってもよい。測定部123は、受信電力(例えば、Reference Signal Received Power(RSRP))、受信品質(例えば、Reference Signal Received Quality(RSRQ)、Signal to Interference plus Noise Ratio(SINR)、Signal to Noise Ratio(SNR))、信号強度(例えば、Received Signal Strength Indicator(RSSI))、伝搬路情報(例えば、CSI)などについて測定してもよい。測定結果は、制御部110に出力されてもよい。
The transceiver 120 (measurement unit 123) may perform measurements on the received signal. For example, the measurement unit 123 may perform Radio Resource Management (RRM) measurements, Channel State Information (CSI) measurements, etc. based on the received signal. The measurement unit 123 may measure received power (e.g., Reference Signal Received Power (RSRP)), received quality (e.g., Reference Signal Received Quality (RSRQ), Signal to Interference plus Noise Ratio (SINR), Signal to Noise Ratio (SNR)), signal strength (e.g., Received Signal Strength Indicator (RSSI)), propagation path information (e.g., CSI), etc. The measurement results may be output to the control unit 110.
伝送路インターフェース140は、コアネットワーク30に含まれる装置(例えば、NFを提供するネットワークノード)、他の基地局10などとの間で信号を送受信(バックホールシグナリング)し、ユーザ端末20のためのユーザデータ(ユーザプレーンデータ)、制御プレーンデータなどを取得、伝送などしてもよい。
The transmission path interface 140 may transmit and receive signals (backhaul signaling) between devices included in the core network 30 (e.g., network nodes providing NF), other base stations 10, etc., and may acquire and transmit user data (user plane data), control plane data, etc. for the user terminal 20.
なお、本開示における基地局10の送信部及び受信部は、送受信部120、送受信アンテナ130及び伝送路インターフェース140の少なくとも1つによって構成されてもよい。
Note that the transmitter and receiver of the base station 10 in this disclosure may be configured with at least one of the transmitter/receiver 120, the transmitter/receiver antenna 130, and the transmission path interface 140.
なお、送受信部120は、受信電力又は受信品質に関する、確率でない測定又は予測の結果を含まないビームレポートを生成させるための設定情報(例えば、CSIレポート設定)を、ユーザ端末20に送信してもよい。送受信部120は、前記設定情報に基づいて前記ユーザ端末20において生成される前記ビームレポートを受信してもよい。
The transceiver 120 may transmit to the user terminal 20 setting information (e.g., CSI report setting) for generating a beam report that does not include non-probabilistic measurement or prediction results regarding received power or reception quality. The transceiver 120 may receive the beam report generated in the user terminal 20 based on the setting information.
(ユーザ端末)
図12は、一実施形態に係るユーザ端末の構成の一例を示す図である。ユーザ端末20は、制御部210、送受信部220及び送受信アンテナ230を備えている。なお、制御部210、送受信部220及び送受信アンテナ230は、それぞれ1つ以上が備えられてもよい。 (User terminal)
12 is a diagram showing an example of the configuration of a user terminal according to an embodiment. Theuser terminal 20 includes a control unit 210, a transceiver unit 220, and a transceiver antenna 230. Note that the control unit 210, the transceiver unit 220, and the transceiver antenna 230 may each include one or more.
図12は、一実施形態に係るユーザ端末の構成の一例を示す図である。ユーザ端末20は、制御部210、送受信部220及び送受信アンテナ230を備えている。なお、制御部210、送受信部220及び送受信アンテナ230は、それぞれ1つ以上が備えられてもよい。 (User terminal)
12 is a diagram showing an example of the configuration of a user terminal according to an embodiment. The
なお、本例では、本実施の形態における特徴部分の機能ブロックを主に示しており、ユーザ端末20は、無線通信に必要な他の機能ブロックも有すると想定されてもよい。以下で説明する各部の処理の一部は、省略されてもよい。
Note that this example mainly shows the functional blocks of the characteristic parts of this embodiment, and the user terminal 20 may also be assumed to have other functional blocks necessary for wireless communication. Some of the processing of each part described below may be omitted.
制御部210は、ユーザ端末20全体の制御を実施する。制御部210は、本開示に係る技術分野での共通認識に基づいて説明されるコントローラ、制御回路などから構成することができる。
The control unit 210 controls the entire user terminal 20. The control unit 210 can be configured from a controller, a control circuit, etc., which are described based on a common understanding in the technical field to which this disclosure pertains.
制御部210は、信号の生成、マッピングなどを制御してもよい。制御部210は、送受信部220及び送受信アンテナ230を用いた送受信、測定などを制御してもよい。制御部210は、信号として送信するデータ、制御情報、系列などを生成し、送受信部220に転送してもよい。
The control unit 210 may control signal generation, mapping, etc. The control unit 210 may control transmission and reception using the transceiver unit 220 and the transceiver antenna 230, measurement, etc. The control unit 210 may generate data, control information, sequences, etc. to be transmitted as signals, and transfer them to the transceiver unit 220.
送受信部220は、ベースバンド部221、RF部222、測定部223を含んでもよい。ベースバンド部221は、送信処理部2211、受信処理部2212を含んでもよい。送受信部220は、本開示に係る技術分野での共通認識に基づいて説明されるトランスミッター/レシーバー、RF回路、ベースバンド回路、フィルタ、位相シフタ、測定回路、送受信回路などから構成することができる。
The transceiver unit 220 may include a baseband unit 221, an RF unit 222, and a measurement unit 223. The baseband unit 221 may include a transmission processing unit 2211 and a reception processing unit 2212. The transceiver unit 220 may be composed of a transmitter/receiver, an RF circuit, a baseband circuit, a filter, a phase shifter, a measurement circuit, a transceiver circuit, etc., which are described based on a common understanding in the technical field to which the present disclosure relates.
送受信部220は、一体の送受信部として構成されてもよいし、送信部及び受信部から構成されてもよい。当該送信部は、送信処理部2211、RF部222から構成されてもよい。当該受信部は、受信処理部2212、RF部222、測定部223から構成されてもよい。
The transceiver unit 220 may be configured as an integrated transceiver unit, or may be composed of a transmission unit and a reception unit. The transmission unit may be composed of a transmission processing unit 2211 and an RF unit 222. The reception unit may be composed of a reception processing unit 2212, an RF unit 222, and a measurement unit 223.
送受信アンテナ230は、本開示に係る技術分野での共通認識に基づいて説明されるアンテナ、例えばアレイアンテナなどから構成することができる。
The transmitting/receiving antenna 230 can be configured as an antenna described based on common understanding in the technical field to which this disclosure pertains, such as an array antenna.
送受信部220は、上述の下りリンクチャネル、同期信号、下りリンク参照信号などを受信してもよい。送受信部220は、上述の上りリンクチャネル、上りリンク参照信号などを送信してもよい。
The transceiver 220 may receive the above-mentioned downlink channel, synchronization signal, downlink reference signal, etc. The transceiver 220 may transmit the above-mentioned uplink channel, uplink reference signal, etc.
送受信部220は、デジタルビームフォーミング(例えば、プリコーディング)、アナログビームフォーミング(例えば、位相回転)などを用いて、送信ビーム及び受信ビームの少なくとも一方を形成してもよい。
The transceiver 220 may form at least one of the transmit beam and receive beam using digital beamforming (e.g., precoding), analog beamforming (e.g., phase rotation), etc.
送受信部220(送信処理部2211)は、例えば制御部210から取得したデータ、制御情報などに対して、PDCPレイヤの処理、RLCレイヤの処理(例えば、RLC再送制御)、MACレイヤの処理(例えば、HARQ再送制御)などを行い、送信するビット列を生成してもよい。
The transceiver 220 (transmission processor 2211) may perform PDCP layer processing, RLC layer processing (e.g., RLC retransmission control), MAC layer processing (e.g., HARQ retransmission control), etc. on the data and control information acquired from the controller 210, and generate a bit string to be transmitted.
送受信部220(送信処理部2211)は、送信するビット列に対して、チャネル符号化(誤り訂正符号化を含んでもよい)、変調、マッピング、フィルタ処理、DFT処理(必要に応じて)、IFFT処理、プリコーディング、デジタル-アナログ変換などの送信処理を行い、ベースバンド信号を出力してもよい。
The transceiver 220 (transmission processor 2211) may perform transmission processing such as channel coding (which may include error correction coding), modulation, mapping, filtering, DFT processing (if necessary), IFFT processing, precoding, and digital-to-analog conversion on the bit string to be transmitted, and output a baseband signal.
なお、DFT処理を適用するか否かは、トランスフォームプリコーディングの設定に基づいてもよい。送受信部220(送信処理部2211)は、あるチャネル(例えば、PUSCH)について、トランスフォームプリコーディングが有効(enabled)である場合、当該チャネルをDFT-s-OFDM波形を用いて送信するために上記送信処理としてDFT処理を行ってもよいし、そうでない場合、上記送信処理としてDFT処理を行わなくてもよい。
Whether or not to apply DFT processing may be based on the settings of transform precoding. When transform precoding is enabled for a certain channel (e.g., PUSCH), the transceiver unit 220 (transmission processing unit 2211) may perform DFT processing as the above-mentioned transmission processing in order to transmit the channel using a DFT-s-OFDM waveform, and when transform precoding is not enabled, it is not necessary to perform DFT processing as the above-mentioned transmission processing.
送受信部220(RF部222)は、ベースバンド信号に対して、無線周波数帯への変調、フィルタ処理、増幅などを行い、無線周波数帯の信号を、送受信アンテナ230を介して送信してもよい。
The transceiver unit 220 (RF unit 222) may perform modulation, filtering, amplification, etc., on the baseband signal to a radio frequency band, and transmit the radio frequency band signal via the transceiver antenna 230.
一方、送受信部220(RF部222)は、送受信アンテナ230によって受信された無線周波数帯の信号に対して、増幅、フィルタ処理、ベースバンド信号への復調などを行ってもよい。
On the other hand, the transceiver unit 220 (RF unit 222) may perform amplification, filtering, demodulation to a baseband signal, etc. on the radio frequency band signal received by the transceiver antenna 230.
送受信部220(受信処理部2212)は、取得されたベースバンド信号に対して、アナログ-デジタル変換、FFT処理、IDFT処理(必要に応じて)、フィルタ処理、デマッピング、復調、復号(誤り訂正復号を含んでもよい)、MACレイヤ処理、RLCレイヤの処理及びPDCPレイヤの処理などの受信処理を適用し、ユーザデータなどを取得してもよい。
The transceiver 220 (reception processor 2212) may apply reception processing such as analog-to-digital conversion, FFT processing, IDFT processing (if necessary), filtering, demapping, demodulation, decoding (which may include error correction decoding), MAC layer processing, RLC layer processing, and PDCP layer processing to the acquired baseband signal to acquire user data, etc.
送受信部220(測定部223)は、受信した信号に関する測定を実施してもよい。例えば、測定部223は、受信した信号に基づいて、RRM測定、CSI測定などを行ってもよい。測定部223は、受信電力(例えば、RSRP)、受信品質(例えば、RSRQ、SINR、SNR)、信号強度(例えば、RSSI)、伝搬路情報(例えば、CSI)などについて測定してもよい。測定結果は、制御部210に出力されてもよい。
The transceiver 220 (measurement unit 223) may perform measurements on the received signal. For example, the measurement unit 223 may perform RRM measurements, CSI measurements, etc. based on the received signal. The measurement unit 223 may measure received power (e.g., RSRP), received quality (e.g., RSRQ, SINR, SNR), signal strength (e.g., RSSI), propagation path information (e.g., CSI), etc. The measurement results may be output to the control unit 210.
なお、本開示におけるユーザ端末20の送信部及び受信部は、送受信部220及び送受信アンテナ230の少なくとも1つによって構成されてもよい。
In addition, the transmitting unit and receiving unit of the user terminal 20 in this disclosure may be configured by at least one of the transmitting/receiving unit 220 and the transmitting/receiving antenna 230.
なお、制御部210は、受信電力又は受信品質に関する、確率でない測定又は予測の結果(例えば、測定L1-RSRP/SINR、予測L1-RSRP/SINR)を含まないビームレポートを生成してもよい。送受信部220は、前記ビームレポートを送信してもよい。
The control unit 210 may generate a beam report that does not include non-probabilistic measurement or prediction results regarding reception power or reception quality (e.g., measured L1-RSRP/SINR, predicted L1-RSRP/SINR). The transceiver unit 220 may transmit the beam report.
制御部210は、リソースを示すフィールド(例えば、リソースインディケーターフィールド)と、前記リソースのトップX確率を示すフィールド(トップX確率フィールド)と、を含む前記ビームレポートを生成する、ここで、前記トップX確率は、1つ以上のリソースのうちの前記リソースに対応する前記結果が、前記1つ以上のリソースに対応する前記結果のうち、X番目に大きい前記結果以上の値である確率であってもよい。なお、Xは整数であってもよい。
The control unit 210 generates the beam report including a field indicating a resource (e.g., a resource indicator field) and a field indicating the top X probability of the resource (a top X probability field), where the top X probability may be the probability that the result corresponding to the resource among one or more resources is equal to or greater than the Xth largest result among the results corresponding to the one or more resources. X may be an integer.
制御部210は、1つ以上のリソースに関するトップX’/1確率を示すフィールド(トップX’/1確率フィールド)を含む前記ビームレポートを生成する、ここで、前記トップX’/1確率は、X’個のリソースに対応する前記結果の少なくとも1つが、前記1つ以上のリソースに対応する前記結果のなかで最大となる確率であってもよい。なお、X’は整数であってもよい。
The control unit 210 generates the beam report including a field (Top X'/1 Probability field) indicating the top X'/1 probability for one or more resources, where the top X'/1 probability may be the probability that at least one of the results corresponding to X' resources is the maximum among the results corresponding to the one or more resources. X' may be an integer.
(ハードウェア構成)
なお、上記実施形態の説明に用いたブロック図は、機能単位のブロックを示している。これらの機能ブロック(構成部)は、ハードウェア及びソフトウェアの少なくとも一方の任意の組み合わせによって実現される。また、各機能ブロックの実現方法は特に限定されない。すなわち、各機能ブロックは、物理的又は論理的に結合した1つの装置を用いて実現されてもよいし、物理的又は論理的に分離した2つ以上の装置を直接的又は間接的に(例えば、有線、無線などを用いて)接続し、これら複数の装置を用いて実現されてもよい。機能ブロックは、上記1つの装置又は上記複数の装置にソフトウェアを組み合わせて実現されてもよい。 (Hardware configuration)
The block diagrams used in the description of the above embodiments show functional blocks. These functional blocks (components) are realized by any combination of at least one of hardware and software. The method of realizing each functional block is not particularly limited. That is, each functional block may be realized using one device that is physically or logically coupled, or may be realized using two or more devices that are physically or logically separated and directly or indirectly connected (for example, using wires, wirelessly, etc.). The functional blocks may be realized by combining the one device or the multiple devices with software.
なお、上記実施形態の説明に用いたブロック図は、機能単位のブロックを示している。これらの機能ブロック(構成部)は、ハードウェア及びソフトウェアの少なくとも一方の任意の組み合わせによって実現される。また、各機能ブロックの実現方法は特に限定されない。すなわち、各機能ブロックは、物理的又は論理的に結合した1つの装置を用いて実現されてもよいし、物理的又は論理的に分離した2つ以上の装置を直接的又は間接的に(例えば、有線、無線などを用いて)接続し、これら複数の装置を用いて実現されてもよい。機能ブロックは、上記1つの装置又は上記複数の装置にソフトウェアを組み合わせて実現されてもよい。 (Hardware configuration)
The block diagrams used in the description of the above embodiments show functional blocks. These functional blocks (components) are realized by any combination of at least one of hardware and software. The method of realizing each functional block is not particularly limited. That is, each functional block may be realized using one device that is physically or logically coupled, or may be realized using two or more devices that are physically or logically separated and directly or indirectly connected (for example, using wires, wirelessly, etc.). The functional blocks may be realized by combining the one device or the multiple devices with software.
ここで、機能には、判断、決定、判定、計算、算出、処理、導出、調査、探索、確認、受信、送信、出力、アクセス、解決、選択、選定、確立、比較、想定、期待、みなし、報知(broadcasting)、通知(notifying)、通信(communicating)、転送(forwarding)、構成(configuring)、再構成(reconfiguring)、割り当て(allocating、mapping)、割り振り(assigning)などがあるが、これらに限られない。例えば、送信を機能させる機能ブロック(構成部)は、送信部(transmitting unit)、送信機(transmitter)などと呼称されてもよい。いずれも、上述したとおり、実現方法は特に限定されない。
Here, the functions include, but are not limited to, judgement, determination, judgment, calculation, computation, processing, derivation, investigation, search, confirmation, reception, transmission, output, access, resolution, selection, election, establishment, comparison, assumption, expectation, deeming, broadcasting, notifying, communicating, forwarding, configuring, reconfiguring, allocating, mapping, and assignment. For example, a functional block (component) that performs the transmission function may be called a transmitting unit, a transmitter, and the like. In either case, as mentioned above, there are no particular limitations on the method of realization.
例えば、本開示の一実施形態における基地局、ユーザ端末などは、本開示の無線通信方法の処理を行うコンピュータとして機能してもよい。図13は、一実施形態に係る基地局及びユーザ端末のハードウェア構成の一例を示す図である。上述の基地局10及びユーザ端末20は、物理的には、プロセッサ1001、メモリ1002、ストレージ1003、通信装置1004、入力装置1005、出力装置1006、バス1007などを含むコンピュータ装置として構成されてもよい。
For example, a base station, a user terminal, etc. in one embodiment of the present disclosure may function as a computer that performs processing of the wireless communication method of the present disclosure. FIG. 13 is a diagram showing an example of the hardware configuration of a base station and a user terminal according to one embodiment. The above-mentioned base station 10 and user terminal 20 may be physically configured as a computer device including a processor 1001, a memory 1002, a storage 1003, a communication device 1004, an input device 1005, an output device 1006, a bus 1007, etc.
なお、本開示において、装置、回路、デバイス、部(section)、ユニットなどの文言は、互いに読み替えることができる。基地局10及びユーザ端末20のハードウェア構成は、図に示した各装置を1つ又は複数含むように構成されてもよいし、一部の装置を含まずに構成されてもよい。
In addition, in this disclosure, the terms apparatus, circuit, device, section, unit, etc. may be interpreted as interchangeable. The hardware configuration of the base station 10 and the user terminal 20 may be configured to include one or more of the devices shown in the figures, or may be configured to exclude some of the devices.
例えば、プロセッサ1001は1つだけ図示されているが、複数のプロセッサがあってもよい。また、処理は、1のプロセッサによって実行されてもよいし、処理が同時に、逐次に、又はその他の手法を用いて、2以上のプロセッサによって実行されてもよい。なお、プロセッサ1001は、1以上のチップによって実装されてもよい。
For example, although only one processor 1001 is shown, there may be multiple processors. Furthermore, processing may be performed by one processor, or processing may be performed by two or more processors simultaneously, sequentially, or using other techniques. Furthermore, the processor 1001 may be implemented by one or more chips.
基地局10及びユーザ端末20における各機能は、例えば、プロセッサ1001、メモリ1002などのハードウェア上に所定のソフトウェア(プログラム)を読み込ませることによって、プロセッサ1001が演算を行い、通信装置1004を介する通信を制御したり、メモリ1002及びストレージ1003におけるデータの読み出し及び書き込みの少なくとも一方を制御したりすることによって実現される。
The functions of the base station 10 and the user terminal 20 are realized, for example, by loading specific software (programs) onto hardware such as the processor 1001 and memory 1002, causing the processor 1001 to perform calculations, control communications via the communication device 1004, and control at least one of the reading and writing of data in the memory 1002 and storage 1003.
プロセッサ1001は、例えば、オペレーティングシステムを動作させてコンピュータ全体を制御する。プロセッサ1001は、周辺装置とのインターフェース、制御装置、演算装置、レジスタなどを含む中央処理装置(Central Processing Unit(CPU))によって構成されてもよい。例えば、上述の制御部110(210)、送受信部120(220)などの少なくとも一部は、プロセッサ1001によって実現されてもよい。
The processor 1001, for example, runs an operating system to control the entire computer. The processor 1001 may be configured as a central processing unit (CPU) including an interface with peripheral devices, a control device, an arithmetic unit, registers, etc. For example, at least a portion of the above-mentioned control unit 110 (210), transmission/reception unit 120 (220), etc. may be realized by the processor 1001.
また、プロセッサ1001は、プログラム(プログラムコード)、ソフトウェアモジュール、データなどを、ストレージ1003及び通信装置1004の少なくとも一方からメモリ1002に読み出し、これらに従って各種の処理を実行する。プログラムとしては、上述の実施形態において説明した動作の少なくとも一部をコンピュータに実行させるプログラムが用いられる。例えば、制御部110(210)は、メモリ1002に格納され、プロセッサ1001において動作する制御プログラムによって実現されてもよく、他の機能ブロックについても同様に実現されてもよい。
The processor 1001 also reads out programs (program codes), software modules, data, etc. from at least one of the storage 1003 and the communication device 1004 into the memory 1002, and executes various processes according to these. The programs used are those that cause a computer to execute at least some of the operations described in the above embodiments. For example, the control unit 110 (210) may be realized by a control program stored in the memory 1002 and running on the processor 1001, and similar implementations may be made for other functional blocks.
メモリ1002は、コンピュータ読み取り可能な記録媒体であり、例えば、Read Only Memory(ROM)、Erasable Programmable ROM(EPROM)、Electrically EPROM(EEPROM)、Random Access Memory(RAM)、その他の適切な記憶媒体の少なくとも1つによって構成されてもよい。メモリ1002は、レジスタ、キャッシュ、メインメモリ(主記憶装置)などと呼ばれてもよい。メモリ1002は、本開示の一実施形態に係る無線通信方法を実施するために実行可能なプログラム(プログラムコード)、ソフトウェアモジュールなどを保存することができる。
Memory 1002 is a computer-readable recording medium and may be composed of at least one of, for example, Read Only Memory (ROM), Erasable Programmable ROM (EPROM), Electrically EPROM (EEPROM), Random Access Memory (RAM), and other suitable storage media. Memory 1002 may also be called a register, cache, main memory, etc. Memory 1002 can store executable programs (program codes), software modules, etc. for implementing a wireless communication method according to one embodiment of the present disclosure.
ストレージ1003は、コンピュータ読み取り可能な記録媒体であり、例えば、フレキシブルディスク、フロッピー(登録商標)ディスク、光磁気ディスク(例えば、コンパクトディスク(Compact Disc ROM(CD-ROM)など)、デジタル多用途ディスク、Blu-ray(登録商標)ディスク)、リムーバブルディスク、ハードディスクドライブ、スマートカード、フラッシュメモリデバイス(例えば、カード、スティック、キードライブ)、磁気ストライプ、データベース、サーバ、その他の適切な記憶媒体の少なくとも1つによって構成されてもよい。ストレージ1003は、補助記憶装置と呼ばれてもよい。
Storage 1003 is a computer-readable recording medium and may be composed of at least one of a flexible disk, a floppy disk, a magneto-optical disk (e.g., a compact disk (Compact Disc ROM (CD-ROM)), a digital versatile disk, a Blu-ray disk), a removable disk, a hard disk drive, a smart card, a flash memory device (e.g., a card, a stick, a key drive), a magnetic stripe, a database, a server, or other suitable storage medium. Storage 1003 may also be referred to as an auxiliary storage device.
通信装置1004は、有線ネットワーク及び無線ネットワークの少なくとも一方を介してコンピュータ間の通信を行うためのハードウェア(送受信デバイス)であり、例えばネットワークデバイス、ネットワークコントローラ、ネットワークカード、通信モジュールなどともいう。通信装置1004は、例えば周波数分割複信(Frequency Division Duplex(FDD))及び時分割複信(Time Division Duplex(TDD))の少なくとも一方を実現するために、高周波スイッチ、デュプレクサ、フィルタ、周波数シンセサイザなどを含んで構成されてもよい。例えば、上述の送受信部120(220)、送受信アンテナ130(230)などは、通信装置1004によって実現されてもよい。送受信部120(220)は、送信部120a(220a)と受信部120b(220b)とで、物理的に又は論理的に分離された実装がなされてもよい。
The communication device 1004 is hardware (transmitting/receiving device) for communicating between computers via at least one of a wired network and a wireless network, and is also called, for example, a network device, a network controller, a network card, or a communication module. The communication device 1004 may be configured to include a high-frequency switch, a duplexer, a filter, a frequency synthesizer, etc., to realize at least one of Frequency Division Duplex (FDD) and Time Division Duplex (TDD). For example, the above-mentioned transmitting/receiving unit 120 (220), transmitting/receiving antenna 130 (230), etc. may be realized by the communication device 1004. The transmitting/receiving unit 120 (220) may be implemented as a transmitting unit 120a (220a) and a receiving unit 120b (220b) that are physically or logically separated.
入力装置1005は、外部からの入力を受け付ける入力デバイス(例えば、キーボード、マウス、マイクロフォン、スイッチ、ボタン、センサなど)である。出力装置1006は、外部への出力を実施する出力デバイス(例えば、ディスプレイ、スピーカー、Light Emitting Diode(LED)ランプなど)である。なお、入力装置1005及び出力装置1006は、一体となった構成(例えば、タッチパネル)であってもよい。
The input device 1005 is an input device (e.g., a keyboard, a mouse, a microphone, a switch, a button, a sensor, etc.) that accepts input from the outside. The output device 1006 is an output device (e.g., a display, a speaker, a Light Emitting Diode (LED) lamp, etc.) that outputs to the outside. The input device 1005 and the output device 1006 may be integrated into one structure (e.g., a touch panel).
また、プロセッサ1001、メモリ1002などの各装置は、情報を通信するためのバス1007によって接続される。バス1007は、単一のバスを用いて構成されてもよいし、装置間ごとに異なるバスを用いて構成されてもよい。
Furthermore, each device such as the processor 1001 and memory 1002 is connected by a bus 1007 for communicating information. The bus 1007 may be configured using a single bus, or may be configured using different buses between each device.
また、基地局10及びユーザ端末20は、マイクロプロセッサ、デジタル信号プロセッサ(Digital Signal Processor(DSP))、Application Specific Integrated Circuit(ASIC)、Programmable Logic Device(PLD)、Field Programmable Gate Array(FPGA)などのハードウェアを含んで構成されてもよく、当該ハードウェアを用いて各機能ブロックの一部又は全てが実現されてもよい。例えば、プロセッサ1001は、これらのハードウェアの少なくとも1つを用いて実装されてもよい。
Furthermore, the base station 10 and the user terminal 20 may be configured to include hardware such as a microprocessor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a programmable logic device (PLD), or a field programmable gate array (FPGA), and some or all of the functional blocks may be realized using the hardware. For example, the processor 1001 may be implemented using at least one of these pieces of hardware.
(変形例)
なお、本開示において説明した用語及び本開示の理解に必要な用語については、同一の又は類似する意味を有する用語と置き換えてもよい。例えば、チャネル、シンボル及び信号(シグナル又はシグナリング)は、互いに読み替えられてもよい。また、信号はメッセージであってもよい。参照信号(reference signal)は、RSと略称することもでき、適用される標準によってパイロット(Pilot)、パイロット信号などと呼ばれてもよい。また、コンポーネントキャリア(Component Carrier(CC))は、セル、周波数キャリア、キャリア周波数などと呼ばれてもよい。 (Modification)
In addition, the terms described in this disclosure and the terms necessary for understanding this disclosure may be replaced with terms having the same or similar meanings. For example, a channel, a symbol, and a signal (signal or signaling) may be read as mutually interchangeable. A signal may also be a message. A reference signal may be abbreviated as RS, and may be called a pilot, a pilot signal, or the like depending on the applied standard. A component carrier (CC) may also be called a cell, a frequency carrier, a carrier frequency, or the like.
なお、本開示において説明した用語及び本開示の理解に必要な用語については、同一の又は類似する意味を有する用語と置き換えてもよい。例えば、チャネル、シンボル及び信号(シグナル又はシグナリング)は、互いに読み替えられてもよい。また、信号はメッセージであってもよい。参照信号(reference signal)は、RSと略称することもでき、適用される標準によってパイロット(Pilot)、パイロット信号などと呼ばれてもよい。また、コンポーネントキャリア(Component Carrier(CC))は、セル、周波数キャリア、キャリア周波数などと呼ばれてもよい。 (Modification)
In addition, the terms described in this disclosure and the terms necessary for understanding this disclosure may be replaced with terms having the same or similar meanings. For example, a channel, a symbol, and a signal (signal or signaling) may be read as mutually interchangeable. A signal may also be a message. A reference signal may be abbreviated as RS, and may be called a pilot, a pilot signal, or the like depending on the applied standard. A component carrier (CC) may also be called a cell, a frequency carrier, a carrier frequency, or the like.
無線フレームは、時間領域において1つ又は複数の期間(フレーム)によって構成されてもよい。無線フレームを構成する当該1つ又は複数の各期間(フレーム)は、サブフレームと呼ばれてもよい。さらに、サブフレームは、時間領域において1つ又は複数のスロットによって構成されてもよい。サブフレームは、ニューメロロジー(numerology)に依存しない固定の時間長(例えば、1ms)であってもよい。
A radio frame may be composed of one or more periods (frames) in the time domain. Each of the one or more periods (frames) constituting a radio frame may be called a subframe. Furthermore, a subframe may be composed of one or more slots in the time domain. A subframe may have a fixed time length (e.g., 1 ms) that is independent of numerology.
ここで、ニューメロロジーは、ある信号又はチャネルの送信及び受信の少なくとも一方に適用される通信パラメータであってもよい。ニューメロロジーは、例えば、サブキャリア間隔(SubCarrier Spacing(SCS))、帯域幅、シンボル長、サイクリックプレフィックス長、送信時間間隔(Transmission Time Interval(TTI))、TTIあたりのシンボル数、無線フレーム構成、送受信機が周波数領域において行う特定のフィルタリング処理、送受信機が時間領域において行う特定のウィンドウイング処理などの少なくとも1つを示してもよい。
Here, the numerology may be a communication parameter that is applied to at least one of the transmission and reception of a signal or channel. The numerology may indicate, for example, at least one of the following: SubCarrier Spacing (SCS), bandwidth, symbol length, cyclic prefix length, Transmission Time Interval (TTI), number of symbols per TTI, radio frame configuration, a specific filtering process performed by the transceiver in the frequency domain, a specific windowing process performed by the transceiver in the time domain, etc.
スロットは、時間領域において1つ又は複数のシンボル(Orthogonal Frequency Division Multiplexing(OFDM)シンボル、Single Carrier Frequency Division Multiple Access(SC-FDMA)シンボルなど)によって構成されてもよい。また、スロットは、ニューメロロジーに基づく時間単位であってもよい。
A slot may consist of one or more symbols in the time domain (such as Orthogonal Frequency Division Multiplexing (OFDM) symbols, Single Carrier Frequency Division Multiple Access (SC-FDMA) symbols, etc.). A slot may also be a time unit based on numerology.
スロットは、複数のミニスロットを含んでもよい。各ミニスロットは、時間領域において1つ又は複数のシンボルによって構成されてもよい。また、ミニスロットは、サブスロットと呼ばれてもよい。ミニスロットは、スロットよりも少ない数のシンボルによって構成されてもよい。ミニスロットより大きい時間単位で送信されるPDSCH(又はPUSCH)は、PDSCH(PUSCH)マッピングタイプAと呼ばれてもよい。ミニスロットを用いて送信されるPDSCH(又はPUSCH)は、PDSCH(PUSCH)マッピングタイプBと呼ばれてもよい。
A slot may include multiple minislots. Each minislot may consist of one or multiple symbols in the time domain. A minislot may also be called a subslot. A minislot may consist of fewer symbols than a slot. A PDSCH (or PUSCH) transmitted in a time unit larger than a minislot may be called PDSCH (PUSCH) mapping type A. A PDSCH (or PUSCH) transmitted using a minislot may be called PDSCH (PUSCH) mapping type B.
無線フレーム、サブフレーム、スロット、ミニスロット及びシンボルは、いずれも信号を伝送する際の時間単位を表す。無線フレーム、サブフレーム、スロット、ミニスロット及びシンボルは、それぞれに対応する別の呼称が用いられてもよい。なお、本開示におけるフレーム、サブフレーム、スロット、ミニスロット、シンボルなどの時間単位は、互いに読み替えられてもよい。
A radio frame, a subframe, a slot, a minislot, and a symbol all represent time units when transmitting a signal. A different name may be used for a radio frame, a subframe, a slot, a minislot, and a symbol, respectively. Note that the time units such as a frame, a subframe, a slot, a minislot, and a symbol in this disclosure may be read as interchangeable.
例えば、1サブフレームはTTIと呼ばれてもよいし、複数の連続したサブフレームがTTIと呼ばれてよいし、1スロット又は1ミニスロットがTTIと呼ばれてもよい。つまり、サブフレーム及びTTIの少なくとも一方は、既存のLTEにおけるサブフレーム(1ms)であってもよいし、1msより短い期間(例えば、1-13シンボル)であってもよいし、1msより長い期間であってもよい。なお、TTIを表す単位は、サブフレームではなくスロット、ミニスロットなどと呼ばれてもよい。
For example, one subframe may be called a TTI, multiple consecutive subframes may be called a TTI, or one slot or one minislot may be called a TTI. In other words, at least one of the subframe and the TTI may be a subframe (1 ms) in existing LTE, a period shorter than 1 ms (e.g., 1-13 symbols), or a period longer than 1 ms. Note that the unit representing the TTI may be called a slot, minislot, etc., instead of a subframe.
ここで、TTIは、例えば、無線通信におけるスケジューリングの最小時間単位のことをいう。例えば、LTEシステムでは、基地局が各ユーザ端末に対して、無線リソース(各ユーザ端末において使用することが可能な周波数帯域幅、送信電力など)を、TTI単位で割り当てるスケジューリングを行う。なお、TTIの定義はこれに限られない。
Here, TTI refers to, for example, the smallest time unit for scheduling in wireless communication. For example, in an LTE system, a base station schedules each user terminal by allocating radio resources (such as frequency bandwidth and transmission power that can be used by each user terminal) in TTI units. Note that the definition of TTI is not limited to this.
TTIは、チャネル符号化されたデータパケット(トランスポートブロック)、コードブロック、コードワードなどの送信時間単位であってもよいし、スケジューリング、リンクアダプテーションなどの処理単位となってもよい。なお、TTIが与えられたとき、実際にトランスポートブロック、コードブロック、コードワードなどがマッピングされる時間区間(例えば、シンボル数)は、当該TTIよりも短くてもよい。
The TTI may be a transmission time unit for a channel-coded data packet (transport block), a code block, a code word, etc., or may be a processing unit for scheduling, link adaptation, etc. When a TTI is given, the time interval (e.g., the number of symbols) in which a transport block, a code block, a code word, etc. is actually mapped may be shorter than the TTI.
なお、1スロット又は1ミニスロットがTTIと呼ばれる場合、1以上のTTI(すなわち、1以上のスロット又は1以上のミニスロット)が、スケジューリングの最小時間単位となってもよい。また、当該スケジューリングの最小時間単位を構成するスロット数(ミニスロット数)は制御されてもよい。
Note that when one slot or one minislot is called a TTI, one or more TTIs (i.e., one or more slots or one or more minislots) may be the minimum time unit of scheduling. In addition, the number of slots (minislots) that constitute the minimum time unit of scheduling may be controlled.
1msの時間長を有するTTIは、通常TTI(3GPP Rel.8-12におけるTTI)、ノーマルTTI、ロングTTI、通常サブフレーム、ノーマルサブフレーム、ロングサブフレーム、スロットなどと呼ばれてもよい。通常TTIより短いTTIは、短縮TTI、ショートTTI、部分TTI(partial又はfractional TTI)、短縮サブフレーム、ショートサブフレーム、ミニスロット、サブスロット、スロットなどと呼ばれてもよい。
A TTI having a time length of 1 ms may be called a normal TTI (TTI in 3GPP Rel. 8-12), normal TTI, long TTI, normal subframe, normal subframe, long subframe, slot, etc. A TTI shorter than a normal TTI may be called a shortened TTI, short TTI, partial or fractional TTI, shortened subframe, short subframe, minislot, subslot, slot, etc.
なお、ロングTTI(例えば、通常TTI、サブフレームなど)は、1msを超える時間長を有するTTIで読み替えてもよいし、ショートTTI(例えば、短縮TTIなど)は、ロングTTIのTTI長未満かつ1ms以上のTTI長を有するTTIで読み替えてもよい。
Note that a long TTI (e.g., a normal TTI, a subframe, etc.) may be interpreted as a TTI having a time length of more than 1 ms, and a short TTI (e.g., a shortened TTI, etc.) may be interpreted as a TTI having a TTI length shorter than the TTI length of a long TTI and equal to or greater than 1 ms.
リソースブロック(Resource Block(RB))は、時間領域及び周波数領域のリソース割当単位であり、周波数領域において、1つ又は複数個の連続した副搬送波(サブキャリア(subcarrier))を含んでもよい。RBに含まれるサブキャリアの数は、ニューメロロジーに関わらず同じであってもよく、例えば12であってもよい。RBに含まれるサブキャリアの数は、ニューメロロジーに基づいて決定されてもよい。
A resource block (RB) is a resource allocation unit in the time domain and frequency domain, and may include one or more consecutive subcarriers in the frequency domain. The number of subcarriers included in an RB may be the same regardless of numerology, and may be, for example, 12. The number of subcarriers included in an RB may be determined based on numerology.
また、RBは、時間領域において、1つ又は複数個のシンボルを含んでもよく、1スロット、1ミニスロット、1サブフレーム又は1TTIの長さであってもよい。1TTI、1サブフレームなどは、それぞれ1つ又は複数のリソースブロックによって構成されてもよい。
Furthermore, an RB may include one or more symbols in the time domain and may be one slot, one minislot, one subframe, or one TTI in length. One TTI, one subframe, etc. may each be composed of one or more resource blocks.
なお、1つ又は複数のRBは、物理リソースブロック(Physical RB(PRB))、サブキャリアグループ(Sub-Carrier Group(SCG))、リソースエレメントグループ(Resource Element Group(REG))、PRBペア、RBペアなどと呼ばれてもよい。
In addition, one or more RBs may be referred to as a physical resource block (Physical RB (PRB)), a sub-carrier group (Sub-Carrier Group (SCG)), a resource element group (Resource Element Group (REG)), a PRB pair, an RB pair, etc.
また、リソースブロックは、1つ又は複数のリソースエレメント(Resource Element(RE))によって構成されてもよい。例えば、1REは、1サブキャリア及び1シンボルの無線リソース領域であってもよい。
Furthermore, a resource block may be composed of one or more resource elements (REs). For example, one RE may be a radio resource area of one subcarrier and one symbol.
帯域幅部分(Bandwidth Part(BWP))(部分帯域幅などと呼ばれてもよい)は、あるキャリアにおいて、あるニューメロロジー用の連続する共通RB(common resource blocks)のサブセットのことを表してもよい。ここで、共通RBは、当該キャリアの共通参照ポイントを基準としたRBのインデックスによって特定されてもよい。PRBは、あるBWPで定義され、当該BWP内で番号付けされてもよい。
A Bandwidth Part (BWP), which may also be referred to as a partial bandwidth, may represent a subset of contiguous common resource blocks (RBs) for a given numerology on a given carrier, where the common RBs may be identified by an index of the RB relative to a common reference point of the carrier. PRBs may be defined in a BWP and numbered within the BWP.
BWPには、UL BWP(UL用のBWP)と、DL BWP(DL用のBWP)とが含まれてもよい。UEに対して、1キャリア内に1つ又は複数のBWPが設定されてもよい。
The BWP may include a UL BWP (BWP for UL) and a DL BWP (BWP for DL). One or more BWPs may be configured for a UE within one carrier.
設定されたBWPの少なくとも1つがアクティブであってもよく、UEは、アクティブなBWPの外で所定の信号/チャネルを送受信することを想定しなくてもよい。なお、本開示における「セル」、「キャリア」などは、「BWP」で読み替えられてもよい。
At least one of the configured BWPs may be active, and the UE may not expect to transmit or receive a given signal/channel outside the active BWP. Note that "cell," "carrier," etc. in this disclosure may be read as "BWP."
なお、上述した無線フレーム、サブフレーム、スロット、ミニスロット及びシンボルなどの構造は例示に過ぎない。例えば、無線フレームに含まれるサブフレームの数、サブフレーム又は無線フレームあたりのスロットの数、スロット内に含まれるミニスロットの数、スロット又はミニスロットに含まれるシンボル及びRBの数、RBに含まれるサブキャリアの数、並びにTTI内のシンボル数、シンボル長、サイクリックプレフィックス(Cyclic Prefix(CP))長などの構成は、様々に変更することができる。
Note that the above-mentioned structures of radio frames, subframes, slots, minislots, and symbols are merely examples. For example, the number of subframes included in a radio frame, the number of slots per subframe or radio frame, the number of minislots included in a slot, the number of symbols and RBs included in a slot or minislot, the number of subcarriers included in an RB, as well as the number of symbols in a TTI, the symbol length, and the cyclic prefix (CP) length can be changed in various ways.
また、本開示において説明した情報、パラメータなどは、絶対値を用いて表されてもよいし、所定の値からの相対値を用いて表されてもよいし、対応する別の情報を用いて表されてもよい。例えば、無線リソースは、所定のインデックスによって指示されてもよい。
In addition, the information, parameters, etc. described in this disclosure may be represented using absolute values, may be represented using relative values from a predetermined value, or may be represented using other corresponding information. For example, a radio resource may be indicated by a predetermined index.
本開示においてパラメータなどに使用する名称は、いかなる点においても限定的な名称ではない。さらに、これらのパラメータを使用する数式などは、本開示において明示的に開示したものと異なってもよい。様々なチャネル(PUCCH、PDCCHなど)及び情報要素は、あらゆる好適な名称によって識別できるので、これらの様々なチャネル及び情報要素に割り当てている様々な名称は、いかなる点においても限定的な名称ではない。
The names used for parameters and the like in this disclosure are not limiting in any respect. Furthermore, the formulas and the like using these parameters may differ from those explicitly disclosed in this disclosure. The various channels (PUCCH, PDCCH, etc.) and information elements may be identified by any suitable names, and therefore the various names assigned to these various channels and information elements are not limiting in any respect.
本開示において説明した情報、信号などは、様々な異なる技術のいずれかを使用して表されてもよい。例えば、上記の説明全体に渡って言及され得るデータ、命令、コマンド、情報、信号、ビット、シンボル、チップなどは、電圧、電流、電磁波、磁界若しくは磁性粒子、光場若しくは光子、又はこれらの任意の組み合わせによって表されてもよい。
The information, signals, etc. described in this disclosure may be represented using any of a variety of different technologies. For example, the data, instructions, commands, information, signals, bits, symbols, chips, etc. that may be referred to throughout the above description may be represented by voltages, currents, electromagnetic waves, magnetic fields or magnetic particles, optical fields or photons, or any combination thereof.
また、情報、信号などは、上位レイヤから下位レイヤ及び下位レイヤから上位レイヤの少なくとも一方へ出力され得る。情報、信号などは、複数のネットワークノードを介して入出力されてもよい。
In addition, information, signals, etc. may be output from a higher layer to a lower layer and/or from a lower layer to a higher layer. Information, signals, etc. may be input/output via multiple network nodes.
入出力された情報、信号などは、特定の場所(例えば、メモリ)に保存されてもよいし、管理テーブルを用いて管理してもよい。入出力される情報、信号などは、上書き、更新又は追記をされ得る。出力された情報、信号などは、削除されてもよい。入力された情報、信号などは、他の装置へ送信されてもよい。
Input/output information, signals, etc. may be stored in a specific location (e.g., memory) or may be managed using a management table. Input/output information, signals, etc. may be overwritten, updated, or added to. Output information, signals, etc. may be deleted. Input information, signals, etc. may be transmitted to another device.
情報の通知は、本開示において説明した態様/実施形態に限られず、他の方法を用いて行われてもよい。例えば、本開示における情報の通知は、物理レイヤシグナリング(例えば、下り制御情報(Downlink Control Information(DCI))、上り制御情報(Uplink Control Information(UCI)))、上位レイヤシグナリング(例えば、Radio Resource Control(RRC)シグナリング、ブロードキャスト情報(マスタ情報ブロック(Master Information Block(MIB))、システム情報ブロック(System Information Block(SIB))など)、Medium Access Control(MAC)シグナリング)、その他の信号又はこれらの組み合わせによって実施されてもよい。
The notification of information is not limited to the aspects/embodiments described in this disclosure, and may be performed using other methods. For example, the notification of information in this disclosure may be performed by physical layer signaling (e.g., Downlink Control Information (DCI), Uplink Control Information (UCI)), higher layer signaling (e.g., Radio Resource Control (RRC) signaling, broadcast information (Master Information Block (MIB), System Information Block (SIB)), etc.), Medium Access Control (MAC) signaling), other signals, or a combination of these.
なお、物理レイヤシグナリングは、Layer 1/Layer 2(L1/L2)制御情報(L1/L2制御信号)、L1制御情報(L1制御信号)などと呼ばれてもよい。また、RRCシグナリングは、RRCメッセージと呼ばれてもよく、例えば、RRC接続セットアップ(RRC Connection Setup)メッセージ、RRC接続再構成(RRC Connection Reconfiguration)メッセージなどであってもよい。また、MACシグナリングは、例えば、MAC制御要素(MAC Control Element(CE))を用いて通知されてもよい。
The physical layer signaling may be called Layer 1/Layer 2 (L1/L2) control information (L1/L2 control signal), L1 control information (L1 control signal), etc. The RRC signaling may be called an RRC message, for example, an RRC Connection Setup message, an RRC Connection Reconfiguration message, etc. The MAC signaling may be notified, for example, using a MAC Control Element (CE).
また、所定の情報の通知(例えば、「Xであること」の通知)は、明示的な通知に限られず、暗示的に(例えば、当該所定の情報の通知を行わないことによって又は別の情報の通知によって)行われてもよい。
Furthermore, notification of specified information (e.g., notification that "X is the case") is not limited to explicit notification, but may be implicit (e.g., by not notifying the specified information or by notifying other information).
判定は、1ビットで表される値(0か1か)によって行われてもよいし、真(true)又は偽(false)で表される真偽値(boolean)によって行われてもよいし、数値の比較(例えば、所定の値との比較)によって行われてもよい。
The determination may be based on a value represented by a single bit (0 or 1), a Boolean value represented by true or false, or a comparison of numerical values (e.g., with a predetermined value).
ソフトウェアは、ソフトウェア、ファームウェア、ミドルウェア、マイクロコード、ハードウェア記述言語と呼ばれるか、他の名称で呼ばれるかを問わず、命令、命令セット、コード、コードセグメント、プログラムコード、プログラム、サブプログラム、ソフトウェアモジュール、アプリケーション、ソフトウェアアプリケーション、ソフトウェアパッケージ、ルーチン、サブルーチン、オブジェクト、実行可能ファイル、実行スレッド、手順、機能などを意味するよう広く解釈されるべきである。
Software shall be construed broadly to mean instructions, instruction sets, code, code segments, program code, programs, subprograms, software modules, applications, software applications, software packages, routines, subroutines, objects, executable files, threads of execution, procedures, functions, etc., whether referred to as software, firmware, middleware, microcode, hardware description language, or otherwise.
また、ソフトウェア、命令、情報などは、伝送媒体を介して送受信されてもよい。例えば、ソフトウェアが、有線技術(同軸ケーブル、光ファイバケーブル、ツイストペア、デジタル加入者回線(Digital Subscriber Line(DSL))など)及び無線技術(赤外線、マイクロ波など)の少なくとも一方を使用してウェブサイト、サーバ、又は他のリモートソースから送信される場合、これらの有線技術及び無線技術の少なくとも一方は、伝送媒体の定義内に含まれる。
Software, instructions, information, etc. may also be transmitted and received via a transmission medium. For example, if the software is transmitted from a website, server, or other remote source using at least one of wired technologies (such as coaxial cable, fiber optic cable, twisted pair, Digital Subscriber Line (DSL)), and/or wireless technologies (such as infrared, microwave, etc.), then at least one of these wired and wireless technologies is included within the definition of a transmission medium.
本開示において使用する「システム」及び「ネットワーク」という用語は、互換的に使用され得る。「ネットワーク」は、ネットワークに含まれる装置(例えば、基地局)のことを意味してもよい。
As used in this disclosure, the terms "system" and "network" may be used interchangeably. "Network" may refer to the devices included in the network (e.g., base stations).
本開示において、「プリコーディング」、「プリコーダ」、「ウェイト(プリコーディングウェイト)」、「擬似コロケーション(Quasi-Co-Location(QCL))」、「Transmission Configuration Indication state(TCI状態)」、「空間関係(spatial relation)」、「空間ドメインフィルタ(spatial domain filter)」、「送信電力」、「位相回転」、「アンテナポート」、「アンテナポートグル-プ」、「レイヤ」、「レイヤ数」、「ランク」、「リソース」、「リソースセット」、「リソースグループ」、「ビーム」、「ビーム幅」、「ビーム角度」、「アンテナ」、「アンテナ素子」、「パネル」などの用語は、互換的に使用され得る。
In this disclosure, terms such as "precoding," "precoder," "weight (precoding weight)," "Quasi-Co-Location (QCL)," "Transmission Configuration Indication state (TCI state)," "spatial relation," "spatial domain filter," "transmit power," "phase rotation," "antenna port," "antenna port group," "layer," "number of layers," "rank," "resource," "resource set," "resource group," "beam," "beam width," "beam angle," "antenna," "antenna element," and "panel" may be used interchangeably.
本開示においては、「基地局(Base Station(BS))」、「無線基地局」、「固定局(fixed station)」、「NodeB」、「eNB(eNodeB)」、「gNB(gNodeB)」、「アクセスポイント(access point)」、「送信ポイント(Transmission Point(TP))」、「受信ポイント(Reception Point(RP))」、「送受信ポイント(Transmission/Reception Point(TRP))」、「パネル」、「セル」、「セクタ」、「セルグループ」、「キャリア」、「コンポーネントキャリア」などの用語は、互換的に使用され得る。基地局は、マクロセル、スモールセル、フェムトセル、ピコセルなどの用語で呼ばれる場合もある。
In this disclosure, terms such as "Base Station (BS)", "Radio base station", "Fixed station", "NodeB", "eNB (eNodeB)", "gNB (gNodeB)", "Access point", "Transmission Point (TP)", "Reception Point (RP)", "Transmission/Reception Point (TRP)", "Panel", "Cell", "Sector", "Cell group", "Carrier", "Component carrier", etc. may be used interchangeably. Base stations may also be referred to by terms such as macrocell, small cell, femtocell, picocell, etc.
基地局は、1つ又は複数(例えば、3つ)のセルを収容することができる。基地局が複数のセルを収容する場合、基地局のカバレッジエリア全体は複数のより小さいエリアに区分でき、各々のより小さいエリアは、基地局サブシステム(例えば、屋内用の小型基地局(Remote Radio Head(RRH)))によって通信サービスを提供することもできる。「セル」又は「セクタ」という用語は、このカバレッジにおいて通信サービスを行う基地局及び基地局サブシステムの少なくとも一方のカバレッジエリアの一部又は全体を指す。
A base station can accommodate one or more (e.g., three) cells. When a base station accommodates multiple cells, the entire coverage area of the base station can be divided into multiple smaller areas, and each smaller area can also provide communication services by a base station subsystem (e.g., a small base station for indoor use (Remote Radio Head (RRH))). The term "cell" or "sector" refers to a part or the entire coverage area of at least one of the base station and base station subsystems that provide communication services in this coverage.
本開示において、基地局が端末に情報を送信することは、当該基地局が当該端末に対して、当該情報に基づく制御/動作を指示することと、互いに読み替えられてもよい。
In this disclosure, a base station transmitting information to a terminal may be interpreted as the base station instructing the terminal to control/operate based on the information.
本開示においては、「移動局(Mobile Station(MS))」、「ユーザ端末(user terminal)」、「ユーザ装置(User Equipment(UE))」、「端末」などの用語は、互換的に使用され得る。
In this disclosure, terms such as "Mobile Station (MS)", "user terminal", "User Equipment (UE)", and "terminal" may be used interchangeably.
移動局は、加入者局、モバイルユニット、加入者ユニット、ワイヤレスユニット、リモートユニット、モバイルデバイス、ワイヤレスデバイス、ワイヤレス通信デバイス、リモートデバイス、モバイル加入者局、アクセス端末、モバイル端末、ワイヤレス端末、リモート端末、ハンドセット、ユーザエージェント、モバイルクライアント、クライアント又はいくつかの他の適切な用語で呼ばれる場合もある。
A mobile station may also be referred to as a subscriber station, mobile unit, subscriber unit, wireless unit, remote unit, mobile device, wireless device, wireless communication device, remote device, mobile subscriber station, access terminal, mobile terminal, wireless terminal, remote terminal, handset, user agent, mobile client, client, or some other suitable terminology.
基地局及び移動局の少なくとも一方は、送信装置、受信装置、無線通信装置などと呼ばれてもよい。なお、基地局及び移動局の少なくとも一方は、移動体(moving object)に搭載されたデバイス、移動体自体などであってもよい。
At least one of the base station and the mobile station may be called a transmitting device, a receiving device, a wireless communication device, etc. In addition, at least one of the base station and the mobile station may be a device mounted on a moving object, the moving object itself, etc.
当該移動体は、移動可能な物体をいい、移動速度は任意であり、移動体が停止している場合も当然含む。当該移動体は、例えば、車両、輸送車両、自動車、自動二輪車、自転車、コネクテッドカー、ショベルカー、ブルドーザー、ホイールローダー、ダンプトラック、フォークリフト、列車、バス、リヤカー、人力車、船舶(ship and other watercraft)、飛行機、ロケット、人工衛星、ドローン、マルチコプター、クアッドコプター、気球及びこれらに搭載される物を含み、またこれらに限られない。また、当該移動体は、運行指令に基づいて自律走行する移動体であってもよい。
The moving body in question refers to an object that can move, and the moving speed is arbitrary, and of course includes the case where the moving body is stationary. The moving body in question includes, but is not limited to, vehicles, transport vehicles, automobiles, motorcycles, bicycles, connected cars, excavators, bulldozers, wheel loaders, dump trucks, forklifts, trains, buses, handcarts, rickshaws, ships and other watercraft, airplanes, rockets, artificial satellites, drones, multicopters, quadcopters, balloons, and objects mounted on these. The moving body in question may also be a moving body that moves autonomously based on an operating command.
当該移動体は、乗り物(例えば、車、飛行機など)であってもよいし、無人で動く移動体(例えば、ドローン、自動運転車など)であってもよいし、ロボット(有人型又は無人型)であってもよい。なお、基地局及び移動局の少なくとも一方は、必ずしも通信動作時に移動しない装置も含む。例えば、基地局及び移動局の少なくとも一方は、センサなどのInternet of Things(IoT)機器であってもよい。
The moving object may be a vehicle (e.g., a car, an airplane, etc.), an unmanned moving object (e.g., a drone, an autonomous vehicle, etc.), or a robot (manned or unmanned). Note that at least one of the base station and the mobile station may also include devices that do not necessarily move during communication operations. For example, at least one of the base station and the mobile station may be an Internet of Things (IoT) device such as a sensor.
図14は、一実施形態に係る車両の一例を示す図である。車両40は、駆動部41、操舵部42、アクセルペダル43、ブレーキペダル44、シフトレバー45、左右の前輪46、左右の後輪47、車軸48、電子制御部49、各種センサ(電流センサ50、回転数センサ51、空気圧センサ52、車速センサ53、加速度センサ54、アクセルペダルセンサ55、ブレーキペダルセンサ56、シフトレバーセンサ57、及び物体検知センサ58を含む)、情報サービス部59と通信モジュール60を備える。
FIG. 14 is a diagram showing an example of a vehicle according to an embodiment. The vehicle 40 includes a drive unit 41, a steering unit 42, an accelerator pedal 43, a brake pedal 44, a shift lever 45, left and right front wheels 46, left and right rear wheels 47, an axle 48, an electronic control unit 49, various sensors (including a current sensor 50, an RPM sensor 51, an air pressure sensor 52, a vehicle speed sensor 53, an acceleration sensor 54, an accelerator pedal sensor 55, a brake pedal sensor 56, a shift lever sensor 57, and an object detection sensor 58), an information service unit 59, and a communication module 60.
駆動部41は、例えば、エンジン、モータ、エンジンとモータのハイブリッドの少なくとも1つで構成される。操舵部42は、少なくともステアリングホイール(ハンドルとも呼ぶ)を含み、ユーザによって操作されるステアリングホイールの操作に基づいて前輪46及び後輪47の少なくとも一方を操舵するように構成される。
The drive unit 41 is composed of at least one of an engine, a motor, and a hybrid of an engine and a motor, for example. The steering unit 42 includes at least a steering wheel (also called a handlebar), and is configured to steer at least one of the front wheels 46 and the rear wheels 47 based on the operation of the steering wheel operated by the user.
電子制御部49は、マイクロプロセッサ61、メモリ(ROM、RAM)62、通信ポート(例えば、入出力(Input/Output(IO))ポート)63で構成される。電子制御部49には、車両に備えられた各種センサ50-58からの信号が入力される。電子制御部49は、Electronic Control Unit(ECU)と呼ばれてもよい。
The electronic control unit 49 is composed of a microprocessor 61, memory (ROM, RAM) 62, and a communication port (e.g., an Input/Output (IO) port) 63. Signals are input to the electronic control unit 49 from various sensors 50-58 provided in the vehicle. The electronic control unit 49 may also be called an Electronic Control Unit (ECU).
各種センサ50-58からの信号としては、モータの電流をセンシングする電流センサ50からの電流信号、回転数センサ51によって取得された前輪46/後輪47の回転数信号、空気圧センサ52によって取得された前輪46/後輪47の空気圧信号、車速センサ53によって取得された車速信号、加速度センサ54によって取得された加速度信号、アクセルペダルセンサ55によって取得されたアクセルペダル43の踏み込み量信号、ブレーキペダルセンサ56によって取得されたブレーキペダル44の踏み込み量信号、シフトレバーセンサ57によって取得されたシフトレバー45の操作信号、物体検知センサ58によって取得された障害物、車両、歩行者などを検出するための検出信号などがある。
Signals from the various sensors 50-58 include a current signal from a current sensor 50 that senses the motor current, a rotation speed signal of the front wheels 46/rear wheels 47 acquired by a rotation speed sensor 51, an air pressure signal of the front wheels 46/rear wheels 47 acquired by an air pressure sensor 52, a vehicle speed signal acquired by a vehicle speed sensor 53, an acceleration signal acquired by an acceleration sensor 54, a depression amount signal of the accelerator pedal 43 acquired by an accelerator pedal sensor 55, a depression amount signal of the brake pedal 44 acquired by a brake pedal sensor 56, an operation signal of the shift lever 45 acquired by a shift lever sensor 57, and a detection signal for detecting obstacles, vehicles, pedestrians, etc. acquired by an object detection sensor 58.
情報サービス部59は、カーナビゲーションシステム、オーディオシステム、スピーカー、ディスプレイ、テレビ、ラジオ、といった、運転情報、交通情報、エンターテイメント情報などの各種情報を提供(出力)するための各種機器と、これらの機器を制御する1つ以上のECUとから構成される。情報サービス部59は、外部装置から通信モジュール60などを介して取得した情報を利用して、車両40の乗員に各種情報/サービス(例えば、マルチメディア情報/マルチメディアサービス)を提供する。
The information service unit 59 is composed of various devices, such as a car navigation system, audio system, speakers, displays, televisions, and radios, for providing (outputting) various information such as driving information, traffic information, and entertainment information, and one or more ECUs that control these devices. The information service unit 59 uses information acquired from external devices via the communication module 60, etc., to provide various information/services (e.g., multimedia information/multimedia services) to the occupants of the vehicle 40.
情報サービス部59は、外部からの入力を受け付ける入力デバイス(例えば、キーボード、マウス、マイクロフォン、スイッチ、ボタン、センサ、タッチパネルなど)を含んでもよいし、外部への出力を実施する出力デバイス(例えば、ディスプレイ、スピーカー、LEDランプ、タッチパネルなど)を含んでもよい。
The information service unit 59 may include input devices (e.g., a keyboard, a mouse, a microphone, a switch, a button, a sensor, a touch panel, etc.) that accept input from the outside, and may also include output devices (e.g., a display, a speaker, an LED lamp, a touch panel, etc.) that perform output to the outside.
運転支援システム部64は、ミリ波レーダ、Light Detection and Ranging(LiDAR)、カメラ、測位ロケータ(例えば、Global Navigation Satellite System(GNSS)など)、地図情報(例えば、高精細(High Definition(HD))マップ、自動運転車(Autonomous Vehicle(AV))マップなど)、ジャイロシステム(例えば、慣性計測装置(Inertial Measurement Unit(IMU))、慣性航法装置(Inertial Navigation System(INS))など)、人工知能(Artificial Intelligence(AI))チップ、AIプロセッサといった、事故を未然に防止したりドライバの運転負荷を軽減したりするための機能を提供するための各種機器と、これらの機器を制御する1つ以上のECUとから構成される。また、運転支援システム部64は、通信モジュール60を介して各種情報を送受信し、運転支援機能又は自動運転機能を実現する。
The driving assistance system unit 64 is composed of various devices that provide functions for preventing accidents and reducing the driver's driving load, such as a millimeter wave radar, a Light Detection and Ranging (LiDAR), a camera, a positioning locator (e.g., a Global Navigation Satellite System (GNSS)), map information (e.g., a High Definition (HD) map, an Autonomous Vehicle (AV) map, etc.), a gyro system (e.g., an Inertial Measurement Unit (IMU), an Inertial Navigation System (INS), etc.), an Artificial Intelligence (AI) chip, and an AI processor, and one or more ECUs that control these devices. The driving assistance system unit 64 also transmits and receives various information via the communication module 60 to realize a driving assistance function or an autonomous driving function.
通信モジュール60は、通信ポート63を介して、マイクロプロセッサ61及び車両40の構成要素と通信することができる。例えば、通信モジュール60は通信ポート63を介して、車両40に備えられた駆動部41、操舵部42、アクセルペダル43、ブレーキペダル44、シフトレバー45、左右の前輪46、左右の後輪47、車軸48、電子制御部49内のマイクロプロセッサ61及びメモリ(ROM、RAM)62、各種センサ50-58との間でデータ(情報)を送受信する。
The communication module 60 can communicate with the microprocessor 61 and components of the vehicle 40 via the communication port 63. For example, the communication module 60 transmits and receives data (information) via the communication port 63 between the drive unit 41, steering unit 42, accelerator pedal 43, brake pedal 44, shift lever 45, left and right front wheels 46, left and right rear wheels 47, axles 48, the microprocessor 61 and memory (ROM, RAM) 62 in the electronic control unit 49, and the various sensors 50-58 that are provided on the vehicle 40.
通信モジュール60は、電子制御部49のマイクロプロセッサ61によって制御可能であり、外部装置と通信を行うことが可能な通信デバイスである。例えば、外部装置との間で無線通信を介して各種情報の送受信を行う。通信モジュール60は、電子制御部49の内部と外部のどちらにあってもよい。外部装置は、例えば、上述の基地局10、ユーザ端末20などであってもよい。また、通信モジュール60は、例えば、上述の基地局10及びユーザ端末20の少なくとも1つであってもよい(基地局10及びユーザ端末20の少なくとも1つとして機能してもよい)。
The communication module 60 is a communication device that can be controlled by the microprocessor 61 of the electronic control unit 49 and can communicate with an external device. For example, it transmits and receives various information to and from the external device via wireless communication. The communication module 60 may be located either inside or outside the electronic control unit 49. The external device may be, for example, the above-mentioned base station 10 or user terminal 20. The communication module 60 may also be, for example, at least one of the above-mentioned base station 10 and user terminal 20 (it may function as at least one of the base station 10 and user terminal 20).
通信モジュール60は、電子制御部49に入力された上述の各種センサ50-58からの信号、当該信号に基づいて得られる情報、及び情報サービス部59を介して得られる外部(ユーザ)からの入力に基づく情報、の少なくとも1つを、無線通信を介して外部装置へ送信してもよい。電子制御部49、各種センサ50-58、情報サービス部59などは、入力を受け付ける入力部と呼ばれてもよい。例えば、通信モジュール60によって送信されるPUSCHは、上記入力に基づく情報を含んでもよい。
The communication module 60 may transmit at least one of the signals from the various sensors 50-58 described above input to the electronic control unit 49, information obtained based on the signals, and information based on input from the outside (user) obtained via the information service unit 59 to an external device via wireless communication. The electronic control unit 49, the various sensors 50-58, the information service unit 59, etc. may be referred to as input units that accept input. For example, the PUSCH transmitted by the communication module 60 may include information based on the above input.
通信モジュール60は、外部装置から送信されてきた種々の情報(交通情報、信号情報、車間情報など)を受信し、車両に備えられた情報サービス部59へ表示する。情報サービス部59は、情報を出力する(例えば、通信モジュール60によって受信されるPDSCH(又は当該PDSCHから復号されるデータ/情報)に基づいてディスプレイ、スピーカーなどの機器に情報を出力する)出力部と呼ばれてもよい。
The communication module 60 receives various information (traffic information, signal information, vehicle distance information, etc.) transmitted from an external device and displays it on an information service unit 59 provided in the vehicle. The information service unit 59 may also be called an output unit that outputs information (for example, outputs information to a device such as a display or speaker based on the PDSCH (or data/information decoded from the PDSCH) received by the communication module 60).
また、通信モジュール60は、外部装置から受信した種々の情報をマイクロプロセッサ61によって利用可能なメモリ62へ記憶する。メモリ62に記憶された情報に基づいて、マイクロプロセッサ61が車両40に備えられた駆動部41、操舵部42、アクセルペダル43、ブレーキペダル44、シフトレバー45、左右の前輪46、左右の後輪47、車軸48、各種センサ50-58などの制御を行ってもよい。
The communication module 60 also stores various information received from external devices in memory 62 that can be used by the microprocessor 61. Based on the information stored in memory 62, the microprocessor 61 may control the drive unit 41, steering unit 42, accelerator pedal 43, brake pedal 44, shift lever 45, left and right front wheels 46, left and right rear wheels 47, axles 48, various sensors 50-58, and the like provided on the vehicle 40.
また、本開示における基地局は、ユーザ端末で読み替えてもよい。例えば、基地局及びユーザ端末間の通信を、複数のユーザ端末間の通信(例えば、Device-to-Device(D2D)、Vehicle-to-Everything(V2X)などと呼ばれてもよい)に置き換えた構成について、本開示の各態様/実施形態を適用してもよい。この場合、上述の基地局10が有する機能をユーザ端末20が有する構成としてもよい。また、「上りリンク(uplink)」、「下りリンク(downlink)」などの文言は、端末間通信に対応する文言(例えば、「サイドリンク(sidelink)」)で読み替えられてもよい。例えば、上りリンクチャネル、下りリンクチャネルなどは、サイドリンクチャネルで読み替えられてもよい。
Furthermore, the base station in the present disclosure may be read as a user terminal. For example, each aspect/embodiment of the present disclosure may be applied to a configuration in which communication between a base station and a user terminal is replaced with communication between multiple user terminals (which may be called, for example, Device-to-Device (D2D), Vehicle-to-Everything (V2X), etc.). In this case, the user terminal 20 may be configured to have the functions of the base station 10 described above. Furthermore, terms such as "uplink" and "downlink" may be read as terms corresponding to terminal-to-terminal communication (for example, "sidelink"). For example, the uplink channel, downlink channel, etc. may be read as the sidelink channel.
同様に、本開示におけるユーザ端末は、基地局で読み替えてもよい。この場合、上述のユーザ端末20が有する機能を基地局10が有する構成としてもよい。
Similarly, the user terminal in this disclosure may be interpreted as a base station. In this case, the base station 10 may be configured to have the functions of the user terminal 20 described above.
本開示において、基地局によって行われるとした動作は、場合によってはその上位ノード(upper node)によって行われることもある。基地局を有する1つ又は複数のネットワークノード(network nodes)を含むネットワークにおいて、端末との通信のために行われる様々な動作は、基地局、基地局以外の1つ以上のネットワークノード(例えば、Mobility Management Entity(MME)、Serving-Gateway(S-GW)などが考えられるが、これらに限られない)又はこれらの組み合わせによって行われ得ることは明らかである。
In this disclosure, operations that are described as being performed by a base station may in some cases be performed by its upper node. In a network that includes one or more network nodes having base stations, it is clear that various operations performed for communication with terminals may be performed by the base station, one or more network nodes other than the base station (such as, but not limited to, a Mobility Management Entity (MME) or a Serving-Gateway (S-GW)), or a combination of these.
本開示において説明した各態様/実施形態は単独で用いてもよいし、組み合わせて用いてもよいし、実行に伴って切り替えて用いてもよい。また、本開示において説明した各態様/実施形態の処理手順、シーケンス、フローチャートなどは、矛盾の無い限り、順序を入れ替えてもよい。例えば、本開示において説明した方法については、例示的な順序を用いて様々なステップの要素を提示しており、提示した特定の順序に限定されない。
Each aspect/embodiment described in this disclosure may be used alone, in combination, or switched between depending on the implementation. In addition, the processing procedures, sequences, flow charts, etc. of each aspect/embodiment described in this disclosure may be rearranged as long as there is no inconsistency. For example, the methods described in this disclosure present elements of various steps using an exemplary order, and are not limited to the particular order presented.
本開示において説明した各態様/実施形態は、Long Term Evolution(LTE)、LTE-Advanced(LTE-A)、LTE-Beyond(LTE-B)、SUPER 3G、IMT-Advanced、4th generation mobile communication system(4G)、5th generation mobile communication system(5G)、6th generation mobile communication system(6G)、xth generation mobile communication system(xG(xは、例えば整数、小数))、Future Radio Access(FRA)、New-Radio Access Technology(RAT)、New Radio(NR)、New radio access(NX)、Future generation radio access(FX)、Global System for Mobile communications(GSM(登録商標))、CDMA2000、Ultra Mobile Broadband(UMB)、IEEE 802.11(Wi-Fi(登録商標))、IEEE 802.16(WiMAX(登録商標))、IEEE 802.20、Ultra-WideBand(UWB)、Bluetooth(登録商標)、その他の適切な無線通信方法を利用するシステム、これらに基づいて拡張、修正、作成又は規定された次世代システムなどに適用されてもよい。また、複数のシステムが組み合わされて(例えば、LTE又はLTE-Aと、5Gとの組み合わせなど)適用されてもよい。
Each aspect/embodiment described in this disclosure includes Long Term Evolution (LTE), LTE-Advanced (LTE-A), LTE-Beyond (LTE-B), SUPER 3G, IMT-Advanced, 4th generation mobile communication system (4G), 5th generation mobile communication system (5G), 6th generation mobile communication system (6G), xth generation mobile communication system (xG (x is, for example, an integer or decimal)), Future Radio Access (FRA), New-Radio The present invention may be applied to systems that use Access Technology (RAT), New Radio (NR), New radio access (NX), Future generation radio access (FX), Global System for Mobile communications (GSM (registered trademark)), CDMA2000, Ultra Mobile Broadband (UMB), IEEE 802.11 (Wi-Fi (registered trademark)), IEEE 802.16 (WiMAX (registered trademark)), IEEE 802.20, Ultra-WideBand (UWB), Bluetooth (registered trademark), and other appropriate wireless communication methods, as well as next-generation systems that are expanded, modified, created, or defined based on these. In addition, multiple systems may be combined (for example, a combination of LTE or LTE-A and 5G, etc.).
本開示において使用する「に基づいて」という記載は、別段に明記されていない限り、「のみに基づいて」を意味しない。言い換えれば、「に基づいて」という記載は、「のみに基づいて」と「に少なくとも基づいて」の両方を意味する。
As used in this disclosure, the phrase "based on" does not mean "based only on," unless expressly stated otherwise. In other words, the phrase "based on" means both "based only on" and "based at least on."
本開示において使用する「第1の」、「第2の」などの呼称を使用した要素へのいかなる参照も、それらの要素の量又は順序を全般的に限定しない。これらの呼称は、2つ以上の要素間を区別する便利な方法として本開示において使用され得る。したがって、第1及び第2の要素の参照は、2つの要素のみが採用され得ること又は何らかの形で第1の要素が第2の要素に先行しなければならないことを意味しない。
Any reference to elements using designations such as "first," "second," etc., used in this disclosure does not generally limit the quantity or order of those elements. These designations may be used in this disclosure as a convenient method of distinguishing between two or more elements. Thus, a reference to a first and second element does not imply that only two elements may be employed or that the first element must precede the second element in some way.
本開示において使用する「判断(決定)(determining)」という用語は、多種多様な動作を包含する場合がある。例えば、「判断(決定)」は、判定(judging)、計算(calculating)、算出(computing)、処理(processing)、導出(deriving)、調査(investigating)、探索(looking up、search、inquiry)(例えば、テーブル、データベース又は別のデータ構造での探索)、確認(ascertaining)などを「判断(決定)」することであるとみなされてもよい。
The term "determining" as used in this disclosure may encompass a wide variety of actions. For example, "determining" may be considered to be judging, calculating, computing, processing, deriving, investigating, looking up, search, inquiry (e.g., looking in a table, database, or other data structure), ascertaining, etc.
また、「判断(決定)」は、受信(receiving)(例えば、情報を受信すること)、送信(transmitting)(例えば、情報を送信すること)、入力(input)、出力(output)、アクセス(accessing)(例えば、メモリ中のデータにアクセスすること)などを「判断(決定)」することであるとみなされてもよい。
"Determining" may also be considered to mean "determining" receiving (e.g., receiving information), transmitting (e.g., sending information), input, output, accessing (e.g., accessing data in a memory), etc.
また、「判断(決定)」は、解決(resolving)、選択(selecting)、選定(choosing)、確立(establishing)、比較(comparing)などを「判断(決定)」することであるとみなされてもよい。つまり、「判断(決定)」は、何らかの動作を「判断(決定)」することであるとみなされてもよい。
"Judgment" may also be considered to mean "deciding" to resolve, select, choose, establish, compare, etc. In other words, "judgment" may also be considered to mean "deciding" to take some kind of action.
また、「判断(決定)」は、「想定する(assuming)」、「期待する(expecting)」、「みなす(considering)」などで読み替えられてもよい。
In addition, "judgment (decision)" may be interpreted as "assuming," "expecting," "considering," etc.
本開示に記載の「最大送信電力」は送信電力の最大値を意味してもよいし、公称最大送信電力(the nominal UE maximum transmit power)を意味してもよいし、定格最大送信電力(the rated UE maximum transmit power)を意味してもよい。
The "maximum transmit power" referred to in this disclosure may mean the maximum value of transmit power, may mean the nominal UE maximum transmit power, or may mean the rated UE maximum transmit power.
本開示において使用する「接続された(connected)」、「結合された(coupled)」という用語、又はこれらのあらゆる変形は、2又はそれ以上の要素間の直接的又は間接的なあらゆる接続又は結合を意味し、互いに「接続」又は「結合」された2つの要素間に1又はそれ以上の中間要素が存在することを含むことができる。要素間の結合又は接続は、物理的であっても、論理的であっても、あるいはこれらの組み合わせであってもよい。例えば、「接続」は「アクセス」で読み替えられてもよい。
As used in this disclosure, the terms "connected" and "coupled," or any variation thereof, refer to any direct or indirect connection or coupling between two or more elements, and may include the presence of one or more intermediate elements between two elements that are "connected" or "coupled" to each other. The coupling or connection between the elements may be physical, logical, or a combination thereof. For example, "connected" may be read as "accessed."
本開示において、2つの要素が接続される場合、1つ以上の電線、ケーブル、プリント電気接続などを用いて、並びにいくつかの非限定的かつ非包括的な例として、無線周波数領域、マイクロ波領域、光(可視及び不可視の両方)領域の波長を有する電磁エネルギーなどを用いて、互いに「接続」又は「結合」されると考えることができる。
In this disclosure, when two elements are connected, they may be considered to be "connected" or "coupled" to one another using one or more wires, cables, printed electrical connections, and the like, as well as using electromagnetic energy having wavelengths in the radio frequency range, microwave range, light (both visible and invisible) range, and the like, as some non-limiting and non-exhaustive examples.
本開示において、「AとBが異なる」という用語は、「AとBが互いに異なる」ことを意味してもよい。なお、当該用語は、「AとBがそれぞれCと異なる」ことを意味してもよい。「離れる」、「結合される」などの用語も、「異なる」と同様に解釈されてもよい。
In this disclosure, the term "A and B are different" may mean "A and B are different from each other." The term may also mean "A and B are each different from C." Terms such as "separate" and "combined" may also be interpreted in the same way as "different."
本開示において、「含む(include)」、「含んでいる(including)」及びこれらの変形が使用されている場合、これらの用語は、用語「備える(comprising)」と同様に、包括的であることが意図される。さらに、本開示において使用されている用語「又は(or)」は、排他的論理和ではないことが意図される。
When the terms "include," "including," and variations thereof are used in this disclosure, these terms are intended to be inclusive, similar to the term "comprising." Additionally, the term "or," as used in this disclosure, is not intended to be an exclusive or.
本開示において、例えば、英語でのa, an及びtheのように、翻訳によって冠詞が追加された場合、本開示は、これらの冠詞の後に続く名詞が複数形であることを含んでもよい。
In this disclosure, where articles have been added through translation, such as a, an, and the in English, this disclosure may include that the nouns following these articles are plural.
本開示において、「以下」、「未満」、「以上」、「より多い」、「と等しい」などは、互いに読み替えられてもよい。また、本開示において、「良い」、「悪い」、「大きい」、「小さい」、「高い」、「低い」、「早い」、「遅い」などを意味する文言は、互いに読み替えられてもよい(原級、比較級、最上級を限らず)。また、本開示において、「良い」、「悪い」、「大きい」、「小さい」、「高い」、「低い」、「早い」、「遅い」などを意味する文言は、「i番目に」を付けた表現として互いに読み替えられてもよい(原級、比較級、最上級を限らず)(例えば、「最高」は「i番目に最高」と互いに読み替えられてもよい)。
In this disclosure, terms such as "less than or equal to," "less than," "greater than," "more than," "equal to," etc. may be read as interchangeable. In addition, in this disclosure, words meaning "good," "bad," "big," "small," "high," "low," "fast," "slow," etc. may be read as interchangeable (without being limited to positive, comparative, or superlative). In addition, in this disclosure, words meaning "good," "bad," "big," "small," "high," "low," "fast," "slow," etc. may be read as interchangeable (without being limited to positive, comparative, or superlative) with "ith" added (for example, "best" may be read as "ith best").
本開示において、「の(of)」、「のための(for)」、「に関する(regarding)」、「に関係する(related to)」、「に関連付けられる(associated with)」などは、互いに読み替えられてもよい。
In this disclosure, the terms "of," "for," "regarding," "related to," "associated with," etc. may be read interchangeably.
以上、本開示に係る発明について詳細に説明したが、当業者にとっては、本開示に係る発明が本開示中に説明した実施形態に限定されないということは明らかである。本開示に係る発明は、請求の範囲の記載に基づいて定まる発明の趣旨及び範囲を逸脱することなく修正及び変更態様として実施することができる。したがって、本開示の記載は、例示説明を目的とし、本開示に係る発明に対して何ら制限的な意味をもたらさない。
The invention disclosed herein has been described in detail above, but it is clear to those skilled in the art that the invention disclosed herein is not limited to the embodiments described herein. The invention disclosed herein can be implemented in modified and altered forms without departing from the spirit and scope of the invention as defined by the claims. Therefore, the description of the disclosure is intended as an illustrative example and does not impose any limiting meaning on the invention disclosed herein.
Claims (5)
- 受信電力又は受信品質に関する、確率でない測定又は予測の結果を含まないビームレポートを生成する制御部と、
前記ビームレポートを送信する送信部と、を有する端末。 A control unit that generates a beam report that does not include non-probabilistic measurement or prediction results regarding reception power or reception quality;
A terminal having a transmitting unit that transmits the beam report. - 前記制御部は、リソースを示すフィールドと、前記リソースのトップX確率を示すフィールドと、を含む前記ビームレポートを生成する、ここで、前記トップX確率は、1つ以上のリソースのうちの前記リソースに対応する前記結果が、前記1つ以上のリソースに対応する前記結果のうち、X番目に大きい前記結果以上の値である確率である、請求項1に記載の端末。 The terminal according to claim 1, wherein the control unit generates the beam report including a field indicating a resource and a field indicating a top X probability of the resource, where the top X probability is a probability that the result corresponding to the resource among one or more resources is equal to or greater than the Xth largest result among the results corresponding to the one or more resources.
- 前記制御部は、1つ以上のリソースに関するトップX’/1確率を示すフィールドを含む前記ビームレポートを生成する、ここで、前記トップX’/1確率は、X’個のリソースに対応する前記結果の少なくとも1つが、前記1つ以上のリソースに対応する前記結果のなかで最大となる確率である、請求項1に記載の端末。 The terminal of claim 1, wherein the control unit generates the beam report including a field indicating a top X'/1 probability for one or more resources, where the top X'/1 probability is the probability that at least one of the results corresponding to X' resources is the maximum among the results corresponding to the one or more resources.
- 受信電力又は受信品質に関する、確率でない測定又は予測の結果を含まないビームレポートを生成するステップと、
前記ビームレポートを送信するステップと、を有する端末の無線通信方法。 generating a beam report that does not include non-probabilistic measurements or predictions regarding received power or quality;
A wireless communication method for a terminal comprising the step of transmitting the beam report. - 受信電力又は受信品質に関する、確率でない測定又は予測の結果を含まないビームレポートを生成させるための設定情報を、端末に送信する送信部と、
前記ビームレポートを受信する受信部と、を有する基地局。 A transmission unit that transmits setting information to a terminal for generating a beam report that does not include a result of a non-probability measurement or prediction regarding a reception power or reception quality;
A base station having a receiving unit that receives the beam report.
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WO2021100100A1 (en) * | 2019-11-18 | 2021-05-27 | 株式会社Nttドコモ | Terminal and wireless communication method |
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