WO2024100725A1 - Terminal, wireless communication method, and base station - Google Patents

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

Terminal, wireless communication method and base station

This disclosure relates to terminals, wireless communication methods, and base stations in next-generation mobile communication systems.

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).

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.

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.

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.

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.

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.

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.

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.

According to one aspect of the present disclosure, it is possible to achieve optimal overhead reduction, channel estimation, and resource utilization.

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.

(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.

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).

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.).

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.

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.

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.

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.

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.

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).

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.

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).

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).

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.

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.

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.

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.

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.

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.

For AI-assisted UE-assisted positioning, a Location Management Function (LMF) may perform model training and the LMF may perform model inference.

For CSI feedback/channel estimation using autoencoders, the OAM/gNB/UE may perform model training and the gNB/UE may perform model inference (jointly).

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.

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.

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. Such a beam prediction method may be called AI-based beam prediction (beam reporting), AI-based beam management (Beam Management (BM)), etc.

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.

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.

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.

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.

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.

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.

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.

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.

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)).

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.

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).

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.

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."

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.

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.

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.

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.

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 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.

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.

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.

<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.

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).

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.

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).

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 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.

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.

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′.

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).

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.

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.

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.

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).

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.

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."

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.

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.

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.

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.

In the present disclosure, the physical layer signaling may be, for example, Downlink Control Information (DCI), Uplink Control Information (UCI), etc.

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.

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.

In this disclosure, timing, time, duration, time instance, slot, subslot, symbol, subframe, etc. may be interpreted as interchangeable.

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.

In addition, in this disclosure, channel state, channel status, channel, channel environment, etc. may be interpreted as interchangeable.

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.

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.

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.

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.

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.

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.

(Wireless communication method)
First Embodiment
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. In the present disclosure, 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.). In this disclosure, 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. In the present disclosure, 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.

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).

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)).

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.

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). 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.

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). 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.

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.

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.

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.

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.

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.

According to the first embodiment described above, the UE can report beam information including appropriate information.

Second Embodiment
The second embodiment relates to information reported that is associated with a time instance/duration.

As mentioned in the first embodiment, some of the reported beam information may be associated with a time instance/duration.

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).

Also, for example, 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. 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.

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).

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.

According to the second embodiment described above, it is possible to properly grasp (identify) the time instance/duration related to the measurement/prediction.

Third Embodiment
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. 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.

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.

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.

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.

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.

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.

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)).

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.

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).

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).

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.

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.

According to the third embodiment described above, the UE can report a reporting instance without L1-RSRP.

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.

Fourth Embodiment
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.

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.

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.

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.

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.

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.

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. 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).

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.

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.

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.

Fifth embodiment
In the fifth embodiment, reporting of beam predictions will be described.

<<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.

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.

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.).

<<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.

The particular case may be, for example, at least one of the following options 5-2-1 to 5-2-3.

[Option 5-2-1]
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).

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).

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. The following drawings showing settings/RRC parameters/information elements in this disclosure are similarly written using ASN.1 notation.

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).

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.

[Option 5-2-2]
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.

[Option 5-2-3]
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.

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.

According to the fifth embodiment described above, it is possible to appropriately specify the settings/operations for measuring/predicting/reporting beams.

Sixth embodiment
In the sixth embodiment, the correspondence/mapping between measured and reported RS/beams is described.

<<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.

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.

[Option 6-1-1]
The UE may make RS decisions using specific RRC parameters.

For example, 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.

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).

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).

The UE determines which resources to report based on the referenced CSI-ResourceConfigId.

[Option 6-1-2]
The UE may make RS decisions using specific RRC parameters.

For example, 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).

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.

[Option 6-1-3]
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.

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. In this case, two or more CSI resource configuration parameters (e.g., CSI-ResourceConfig) may be configured for a UE.

[Option 6-1-4]
The UE may make RS (RS resource) decisions using specific RRC parameters.

The parameters for the resource set may be expanded.

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.

[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.

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.

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.

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.

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.

<<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.

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).

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).

According to the sixth embodiment described above, the correspondence/mapping between the measured RS/beam and the reported RS/beam can be appropriately determined.

<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.

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]).

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).

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.

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.

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.

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.

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).

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.

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.

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.

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).

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))).

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)).

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. 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.

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).

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.

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.

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.

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.

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.

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.

[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.

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.

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.

Furthermore, notification of any information to the UE in the above-mentioned embodiments may be performed periodically, semi-persistently, or aperiodically.

[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.

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.

If the notification is made by UCI, the notification may be transmitted using PUCCH or PUSCH.

Furthermore, in the above-mentioned embodiments, notification of any information from the UE may be performed periodically, semi-persistently, or aperiodically.

[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.

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.

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).

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)).

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.

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.

(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.

(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.

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.

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.

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.

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))).

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).

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.

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.

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.

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.

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.

The user terminal 20 may be a terminal that supports at least one of the communication methods such as LTE, LTE-A, and 5G.

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.

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.

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.

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.

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.

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.

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.

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). The PRACH may transmit a random access preamble for establishing a connection with a cell.

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.

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.

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.

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).

(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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

(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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

(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.

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.

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.

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.

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.

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. 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.

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.

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.

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). 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.

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).

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.

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.

(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.

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.

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.

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.

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. 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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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."

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.

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.

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. 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.

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.

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.

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.

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).

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).

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. 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.

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).

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.

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.

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.

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.

In this disclosure, terms such as "Mobile Station (MS)", "user terminal", "User Equipment (UE)", and "terminal" may be used interchangeably.

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. 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.

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). 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.

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.

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).

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.

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.

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. 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.

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. For example, 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.

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.

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.

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.

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.

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.).

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."

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.

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.

"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. In other words, "judgment" may also be considered to mean "deciding" to take some kind of action.

In addition, "judgment (decision)" may be interpreted as "assuming," "expecting," "considering," etc.

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.

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."

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.

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."

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.

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.

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").

In this disclosure, the terms "of," "for," "regarding," "related to," "associated with," etc. may be read interchangeably.

　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)

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.
2. 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.
3. 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.
4. 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.
5. 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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