WO2025041803A1 - 端末及び無線通信方法 - Google Patents

端末及び無線通信方法 Download PDF

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Publication number
WO2025041803A1
WO2025041803A1 PCT/JP2024/029704 JP2024029704W WO2025041803A1 WO 2025041803 A1 WO2025041803 A1 WO 2025041803A1 JP 2024029704 W JP2024029704 W JP 2024029704W WO 2025041803 A1 WO2025041803 A1 WO 2025041803A1
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Prior art keywords
unit
report
model
jitter
remaining
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English (en)
French (fr)
Japanese (ja)
Inventor
天楊 閔
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NTT Docomo Inc
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NTT Docomo Inc
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B17/00—Monitoring; Testing
    • H04B17/20—Monitoring; Testing of receivers
    • H04B17/24—Monitoring; Testing of receivers with feedback of measurements to the transmitter
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H04W24/10—Scheduling measurement reports ; Arrangements for measurement reports
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W52/00—Power management, e.g. Transmission Power Control [TPC] or power classes
    • H04W52/02—Power saving arrangements

Definitions

  • This disclosure relates to a terminal and a wireless communication method.
  • the 3rd Generation Partnership Project (3GPP: registered trademark) is defining specifications for the 5th generation mobile communication system (5G, also known as New Radio (NR) or Next Generation (NG)) and is also developing specifications for the next generation, known as Beyond 5G, 5G Evolution or 6G.
  • 5G also known as New Radio (NR) or Next Generation (NG)
  • NG Next Generation
  • 3GPP Release 18 proposes a functional architecture for artificial intelligence/machine learning models (AI/ML Model) (Non-Patent Document 1).
  • the terminal (User Equipment, UE) can report information that contributes to mitigating overheating of the UE (overheatingAssistance) to the network (specifically, the gNB) using UE Assistance Information (Non-Patent Document 2).
  • the UE can report the secondary cell group that it wishes to deactivate (scg-DeactivationPreference) to the gNB. This can ultimately reduce the power consumption of the UE and suppress battery consumption.
  • overheatingAssistance or scg-DeactivationPreference can reduce battery consumption in the UE, but both are indirect methods and have limited effect on reducing battery consumption.
  • the following disclosure has been made in light of this situation, and aims to provide a terminal and wireless communication method that can more directly reduce battery consumption.
  • One aspect of the present disclosure is a terminal (UE200) that includes a control unit (control unit 240) that uses a learning model to predict an allowable transmission delay for uplink data waiting to be transmitted, and a transmission unit (report unit 230) that transmits a report of the predicted transmission delay to the network.
  • control unit 240 that uses a learning model to predict an allowable transmission delay for uplink data waiting to be transmitted
  • transmission unit 230 that transmits a report of the predicted transmission delay to the network.
  • One aspect of the present disclosure is a terminal that includes a control unit (control unit 240) that uses a learning model to predict jitter that occurs in uplink data, and a transmission unit that transmits a report of the predicted jitter to the network.
  • control unit 240 that uses a learning model to predict jitter that occurs in uplink data
  • transmission unit that transmits a report of the predicted jitter to the network.
  • One aspect of the present disclosure is a terminal (UE200) that includes a control unit (control unit 240) that determines the remaining charge of an installed battery, and a transmission unit (report unit 230) that transmits a report of the determined remaining charge of the battery to a network.
  • control unit 240 that determines the remaining charge of an installed battery
  • transmission unit 230 that transmits a report of the determined remaining charge of the battery to a network.
  • FIG. 1 is a schematic diagram showing the overall configuration of a wireless communication system 10.
  • FIG. 2 is a functional block diagram of gNB100.
  • FIG. 3 is a functional block diagram of UE 200.
  • Figure 4 shows an example of the functional architecture of an AI/ML model.
  • FIG. 5 is a diagram showing an example of a communication sequence regarding the BSR and DSR according to the first operation example.
  • FIG. 6 is a diagram showing an example of a communication sequence regarding a UL jitter report according to the second operation example.
  • FIG. 7 is a diagram showing an example of a communication sequence regarding DL jitter reporting according to the second operation example.
  • FIG. 8 is a diagram showing an example of a communication sequence regarding a battery remaining amount report according to the third operation example.
  • FIG. 9 is a diagram showing an example of the hardware configuration of gNB100 and UE200.
  • FIG. 10 is a diagram showing an example of the configuration of a vehicle 2001.
  • FIG. 1 is an overall schematic configuration diagram of a wireless communication system 10 according to this embodiment.
  • the wireless communication system 10 is a wireless communication system conforming to 5G New Radio (NR) and includes a Next Generation-Radio Access Network 20 (hereinafter, NG-RAN 20) and a terminal 200 (User Equipment 200, hereinafter, UE 200).
  • NR 5G New Radio
  • NG-RAN 20 Next Generation-Radio Access Network 20
  • UE 200 User Equipment 200
  • the wireless communication system 10 may be a wireless communication system conforming to a method called Beyond 5G, 5G Evolution, or 6G, or may include a wireless communication system conforming to a method called Long Term Evolution (LTE) or 4G.
  • the wireless communication system 10 may support functions related to the Industrial Internet of Things (IIoT) and URLLC (Ultra-Reliable and Low Latency Communications).
  • IIoT Industrial Internet of Things
  • URLLC Ultra-Reliable and Low Latency Communications
  • NG-RAN 20 includes a radio base station 100 (hereinafter, gNB 100).
  • gNB 100 radio base station 100
  • the gNB100 may also adopt a fronthaul (FH) interface defined by the Open Radio Access Network Alliance (O-RAN).
  • the gNB100 may include an O-RAN Distributed Unit (O-DU) and an O-RAN Radio Unit (O-RU).
  • the gNB100 may function as a type of NG-RAN node.
  • NG-RAN20 actually includes multiple NG-RAN Nodes, specifically gNBs (or ng-eNBs), and is connected to a 5G-compliant core network (5GC, not shown).
  • 5GC 5G-compliant core network
  • CUPS Control and User Plane Separation
  • NG-RAN20 may be connected to NF50 via 5GC or directly from NG-RAN20.
  • NF50 may be interpreted as a logical node that provides a network function.
  • NF50 may include an Access and Mobility Management Function (AMF) that is included in the 5G system architecture and provides access and mobility management functions for UE200, a Session Management Function (SMF) that provides session management functions, a User Plane Function (UPF) that relays and terminates the user plane of PDU (Protocol Data Unit) sessions in 5GC, and a Location Management Function (LMF) that handles communication control related to location information services defined in 5GC.
  • AMF Access and Mobility Management Function
  • SMF Session Management Function
  • UPF User Plane Function
  • LMF Location Management Function
  • UDM/UDR Unified Data Management/User Data Repository
  • NG-RAN20 and 5GC may simply be referred to as a "network”.
  • NG-RAN20 may also be connected to a server managed by a 3GPP service provider or a server managed by a party other than the provider (3GPP or non-3GPP server).
  • the gNB100 is a radio base station conforming to NR, and performs wireless communication conforming to NR with the UE200.
  • the gNB100 may be composed of a CU (Central Unit) and a DU (Distributed Unit), and the DU may be separated from the CU and installed in a different geographical location.
  • One or more DUs may be connected to the CU.
  • gNB100 gNB-CU
  • gNB-CU may be connected to each other via an Xn interface
  • the CU and DU may be connected to each other via an F1 interface.
  • the gNB100 and UE200 are capable of supporting Massive MIMO, which generates more directional beams by controlling the radio signals transmitted from multiple antenna elements, Carrier Aggregation (CA), which bundles together multiple component carriers (CCs), and Dual Connectivity (DC), which enables simultaneous communication between the UE and multiple NG-RAN nodes.
  • Massive MIMO which generates more directional beams by controlling the radio signals transmitted from multiple antenna elements
  • CA Carrier Aggregation
  • CCs component carriers
  • DC Dual Connectivity
  • AI/machine learning may be applied in the NG-RAN 20.
  • a learning model (herein referred to as an AI/ML model) may be used to optimize the mobility or handover (which may be read as transition, cell transition, cell selection, etc.) of the UE 200.
  • AI/ML Model may also be expressed as another term meaning AI or ML, such as artificial intelligence (AI) model or machine learning (ML) model.
  • AI artificial intelligence
  • ML machine learning
  • the mobility of UE200 may refer, in a broad sense, to the ease of movement and maneuverability of UE200, but in this embodiment, it may also refer to the minimization of call drops, radio link (including beam) failures, unnecessary handovers, ping-pong states, and the like.
  • such an AI/ML model may be used to predict various states related to the UE 200.
  • the AI/ML model may be used to predict the UE 200's buffer, uplink (UL) data delay time, UL jitter, remaining battery charge, and the like.
  • the AI/ML model may also be used to predict DL jitter in the gNB 100, etc.
  • the AI/ML model may be provided in the NF 50 or in the gNB 100.
  • the model may be provided in UE 200.
  • the UE 200 may support the transmission of reports indicating the internal status of the UE 200 regarding the UL. Specifically, the UE 200 may support a Buffer Status Report (BSR) and a Delay Status Report (DSR).
  • BSR Buffer Status Report
  • DSR Delay Status Report
  • the BSR reports the status of the UL transmission buffers (which may be interpreted as Radio Link Control Layer (RLC) buffers) in UE200 to the network (gNB).
  • the buffer size field of the BSR may indicate the amount of data waiting to be transmitted across all logical channels in the logical channel group (LCG).
  • a BSR may be triggered for the following reasons:
  • the BSR may be inserted since it is better to derive useful scheduling information from the available payload instead of padding, if possible.
  • DSR reports to the network (gNB) the tolerable (waiting) delay time until transmission for UL data remaining in the transmission buffer.
  • UE200 can report the tolerable delay time (which may be called the remaining time) for UL data remaining in the transmission buffer for each LCG.
  • UE200 may also report the size of the transmission buffer to the gNB. Based on the remaining time transmitted from UE200, the gNB can prioritize scheduling for LCGs that indicate a smaller remaining time.
  • the gNB 100 and the UE 200 can also report jitter occurring in transmission data (transmission traffic). Specifically, the gNB 100 can report jitter occurring in DL data to the UE 200. Furthermore, the UE 200 can report jitter occurring in UL data to the gNB 100. Note that jitter may mean fluctuations in the timing of data transmission or reception in the time direction.
  • UE200 may transmit information (overheatingAssistance) that contributes to mitigating overheating of UE200 to gNB100 by UE Assistance Information (see 3GPP TS38.331). This makes it possible to mitigate overheating, reduce power consumption, and suppress battery consumption.
  • overheatingAssistance information that contributes to mitigating overheating of UE200 to gNB100 by UE Assistance Information (see 3GPP TS38.331). This makes it possible to mitigate overheating, reduce power consumption, and suppress battery consumption.
  • a functional block configuration of the wireless communication system 10 will be described. Specifically, the functional block configurations of the gNB 100 and the UE 200 will be described.
  • Fig. 2 is a functional block configuration diagram of the gNB 100.
  • Fig. 3 is a functional block configuration diagram of the UE 200.
  • the gNB 100 includes a wireless communication unit 110, a scheduling unit 120, an AI/ML model unit 130 and a control unit 140.
  • the scheduling unit 120 performs DL scheduling and UL scheduling. Specifically, the scheduling unit 120 can perform dynamic or semi-static allocation of radio resources (time, frequency, and space) in DL and UL, and determination of transmission parameters including data rate, etc.
  • the scheduling unit 120 can transmit a report of jitter occurring in downlink (DL) data to the NF 50 (network device) or the UE 200.
  • the scheduling unit 120 may constitute a transmitting unit that transmits a report of jitter to the terminal.
  • the scheduling unit 120 can transmit a report including the amount of jitter in DL predicted by the control unit 140 using the AI/ML model unit 130 to the NF 50 (network device) or the UE 200.
  • the report of the amount of jitter may be indicated by absolute time or by a specific range. There may be one or more jitter ranges.
  • the AI/ML model unit 130 executes processing using a learning model (AI/ML Model). Specifically, the AI/ML model unit 130 executes processing using an AI/ML Model that is applied to optimization of the mobility and/or handover of the UE 200, etc.
  • AI/ML Model a learning model that is applied to optimization of the mobility and/or handover of the UE 200, etc.
  • the AI/ML model unit 130 can determine the validity period of a learned (trained) AI/ML model.
  • the AI/ML model unit 130 can also evaluate the performance of the AI/ML model and determine whether the performance of the AI/ML model has deteriorated below a specified level.
  • the AI/ML model unit 130 may re-learn (retrain) the AI/ML model when the validity period of the AI/ML model expires or when the performance of the AI/ML model falls below a specified level.
  • the AI/ML model itself may be mounted on the gNB100 or on another network node (network device) such as the NF50.
  • the AI/ML model unit 130 can also predict jitter that will occur in DL data. Specifically, the AI/ML model unit 130 learns the transitions in the amount of jitter that occurred in past DL data transmissions, and can predict the amount of jitter that may occur in future DL data transmissions based on the learning results.
  • the target time (range) for jitter prediction may be fixed or variable. Alternatively, jitter in multiple ranges (e.g., 10 minutes, 30 minutes, etc.) may be predicted.
  • the control unit 140 controls each functional block constituting the gNB 100.
  • the control unit 140 can control scheduling by the scheduling unit 120 based on at least one of the BSR and DSR transmitted from the UE 200.
  • control unit 140 may instruct the scheduling unit 120 to perform preferential scheduling for LCGs that have a large amount of remaining data or a small remaining time, based on the amount of remaining data indicated by the BSR or the remaining time indicated by the DSR.
  • the control unit 140 can also predict jitter that may occur in DL data using the AI/ML model unit 130 (learning model). Specifically, the control unit 140 instructs the AI/ML model unit 130 to predict the amount of jitter that may occur in future DL data transmissions.
  • the control unit 140 can instruct the scheduling unit 120 to schedule DL data based on the predicted jitter amount provided by the AI/ML model unit 130.
  • the channels include a control channel and a data channel.
  • the control channels include PDCCH (Physical Downlink Control Channel), PUCCH (Physical Uplink Control Channel), PRACH (Physical Random Access Channel), and PBCH (Physical Broadcast Channel), etc.
  • Data channels include PDSCH (Physical Downlink Shared Channel) and PUSCH (Physical Uplink Shared Channel).
  • PDSCH Physical Downlink Shared Channel
  • PUSCH Physical Uplink Shared Channel
  • Reference signals include Demodulation reference signal (DMRS), Sounding Reference Signal (SRS), Phase Tracking Reference Signal (PTRS), and Channel State Information-Reference Signal (CSI-RS), and signals include channels and reference signals.
  • Data may refer to data transmitted and received via a data channel. Meanwhile, control data may be transmitted and received by messages of the Radio Resource Control layer (RRC layer).
  • RRC layer Radio Resource Control layer
  • PDUs Protocol Data Units
  • SDUs Service Data Units
  • MAC Medium Access Control layer
  • RLC Radio Link Control layer
  • PDCP Packet Data Convergence Protocol layer
  • the UE 200 includes a wireless communication unit 210 , an AI/ML model unit 220 , a reporting unit 230 and a control unit 240 .
  • the wireless communication unit 210 transmits an uplink signal (UL signal) that complies with NR.
  • the wireless communication unit 210 also receives an uplink signal (DL signal) that complies with NR.
  • the AI/ML model unit 220 executes processing using a learning model (AI/ML Model).
  • the AI/ML model unit 220 may have similar functions to the AI/ML model unit 130 of the gNB100.
  • the AI/ML model unit may be provided in either the gNB100 or the UE200, or may be provided in both.
  • the AI/ML model unit 220 can predict the future remaining time based on the DSR.
  • the AI/ML model unit 220 may also predict the future amount of buffered data based on the BSR.
  • the AI/ML model unit 220 can learn the transitions of past remaining time and predict the future remaining time of UL data based on the learning results, etc.
  • the amount of data remaining in the buffer can also be predicted in a similar manner.
  • the AI/ML model unit 220 can also predict jitter that will occur in UL data. Specifically, the AI/ML model unit 220 learns the transitions in the amount of jitter that occurred in past UL data transmissions, and can predict the amount of jitter that may occur in future UL data transmissions based on the learning results.
  • the target time (range) for jitter prediction may be fixed or variable. Alternatively, jitter in multiple ranges (e.g., 10 minutes, 30 minutes, etc.) may be predicted.
  • the AI/ML model unit 220 can predict the remaining charge of the battery installed in the UE 200. Specifically, the AI/ML model unit 220 can learn the past battery consumption state and predict the future remaining charge of the battery based on the learning results, etc.
  • the reporting unit 230 executes various reports to the network.
  • the reporting unit 230 can transmit to the network a report of the remaining time (transmission delay) predicted by the control unit 240 using the AI/ML model unit 220.
  • the reporting unit 230 may constitute a transmitting unit that transmits a report of the transmission delay.
  • the reporting unit 230 may transmit a remaining time report (DSR) based on an instruction from the network (e.g., an instruction by RRC).
  • DSR remaining time report
  • the reporting unit 230 may transmit a report on the remaining time when the amount of UL data remaining in the transmission buffer of the UE 200 exceeds a threshold value, or when the remaining time is smaller than a threshold value. At this time, the amount of data remaining in the buffer may also be reported in the same manner.
  • the reporting unit 230 may start a timer for reporting based on instructions from the network, and when the timer expires, send a report of the remaining time.
  • the reporting unit 230 can also transmit to the network a report of the jitter of the UL data predicted by the control unit 240 using the AI/ML model unit 220.
  • the reporting unit 230 may constitute a transmitting unit that transmits the jitter report.
  • the reporting unit 230 may transmit the jitter report based on an instruction from the network (e.g., an instruction by RRC).
  • the reporting unit 230 may send a report on the jitter of the UL data if a value indicating the characteristics of the jitter of the UL data exceeds a threshold value.
  • the reporting unit 230 may start a reporting timer based on instructions from the network, and send a jitter report when the timer expires.
  • the reporting unit 230 can also transmit a report of the remaining battery capacity determined by the control unit 240 to the network.
  • the reporting unit 230 may constitute a transmitting unit that transmits the report of the remaining battery capacity.
  • the reporting unit 230 may transmit the report of the remaining battery capacity based on an instruction from the network (e.g., an instruction by RRC).
  • the reporting unit 230 may start a timer based on instructions from the network, and when the timer expires, send a report of the remaining battery charge.
  • the control unit 240 controls each functional block that constitutes the UE 200.
  • the control unit 240 can predict the future state of the UE 200 using the AI/ML model unit 220 (learning model).
  • control unit 240 can predict the remaining time allowed for UL data waiting to be transmitted using the AI/ML model unit 220. As described above, the control unit 240 can use the AI/ML model unit 220 to predict at least one of the future state of the transmission buffer (which may simply be expressed as the buffer) of UL data and the future remaining time based on the past state of the UL data in the transmission buffer and the past remaining time.
  • the control unit 240 can use the AI/ML model unit 220 to predict at least one of the future state of the transmission buffer (which may simply be expressed as the buffer) of UL data and the future remaining time based on the past state of the UL data in the transmission buffer and the past remaining time.
  • the control unit 240 can also predict jitter that will occur in the UL data using the AI/ML model unit 220. As described above, the control unit 240 can use the AI/ML model unit 220 to learn the transitions in the amount of jitter that occurred in past transmissions of UL data, and predict the amount of jitter that may occur in future transmissions of UL data based on the learning results, etc.
  • the control unit 240 can also determine the remaining charge of the battery installed in the UE 200. For example, the control unit 240 can determine the remaining charge of the battery according to stages divided into representative percentages (e.g., 100%, 80%, 60%, 40%, 20%, 5%).
  • the control unit 240 can also predict the future remaining battery charge using the AI/ML model unit 220. As described above, the control unit 240 can use the AI/ML model unit 220 to learn the past battery consumption state and predict the future remaining battery charge based on the learning results, etc.
  • Example of AI/ML Model Configuration Figure 4 shows an example of the functional architecture of the AI/ML model. As shown in Figure 4, the architecture may include the following functions.
  • Model Training Train, validate, and test ML models. As part of the model testing procedure, model performance metrics may be generated.
  • the model training function may also be responsible for data preparation (data pre-processing and cleaning, formatting, conversion, etc.).
  • Model inference Provides inference output (such as a prediction or decision).
  • the model inference function may provide control of model inference to the model management/performance monitoring function.
  • ⁇ Model management/performance monitoring Manage ML models and monitor model performance.
  • the network may be able to configure the UE as to whether or not to trigger (send) a DSR.
  • the threshold for triggering a DSR may be set, for example, per LCG. However, as mentioned above, it may also be set per LC or QFI.
  • the UE when it transmits a DSR for each LCG, it may also report (BSR) the status of the transmission buffer together with the remaining time.
  • BSR the status of the transmission buffer together with the remaining time.
  • DSR may be reported by a MAC-CE (control element) just like BSR.
  • the MAC-CE may be an extension of the MAC-CE for BSR, or a new MAC-CE may be defined for DSR.
  • Operation example 1 (3.3.1) Issues As described above, gNB100 performs scheduling in accordance with the BSR and DSR reported from UE200.
  • UL data arrives in the UE (remains in the transmission buffer), and the UE transmits the BSR and DSR to the gNB.
  • the gNB performs scheduling for the UE based on the received BSR and DSR.
  • new UL data may continue to arrive (occur) at the UE even while the UE is transmitting the BSR and DSR to the gNB. For this reason, there is a concern that the BSR and DSR may not be reported to the gNB for the new UL data that arrives after the UE has transmitted the BSR and DSR.
  • the gNB may not be able to simultaneously implement scheduling that corresponds to those remaining times.
  • gNBs could recognize the future contents of BSR and DSR, more efficient and planned scheduling could be achieved.
  • the UE may be equipped with a function that uses an AI/ML model to predict the future state of the transmission buffer (amount of remaining UL data) and the delay state of data in the transmission buffer based on the past state of the transmission buffer (buffer status) and the delay state of data in the transmission buffer (remaining time).
  • the UE may be equipped with an AI model inference and/or AI model training function (see Figure 4) for the prediction function.
  • the prediction may be realized by a higher layer or a lower layer. Specifically, the prediction may be realized by any one or more of the application (AP), RRC, PDCP, RLC, MAC, and PHY layers.
  • the predicted buffer status (BSR) and delay status (DSR) may be exchanged between layers.
  • the BSR and/or DSR may be reported to the gNB per LCG, LC or QoS/QFI (QoS Flow Identifier).
  • the gNB may enable the UE to turn on/off the prediction and reporting of buffer status (BSR) and delay status (DSR) using the AI/ML model, for example, via an RRC message.
  • BSR buffer status
  • DSR delay status
  • the gNB may activate or deactivate the function using the MAC-CE.
  • the UE can report the buffer status (BSR) and delay status (DSR) predicted by the AI/ML model, allowing the gNB to recognize the future contents of the BSR and DSR, enabling more efficient and planned UL scheduling.
  • BSR buffer status
  • DSR delay status
  • Operation Example Fig. 6 shows an example of a communication sequence regarding a UL jitter report according to Operation Example 2.
  • the UE may predict future UL jitter using an AI/ML model and report the predicted jitter amount (range) to the network.
  • the UE may be equipped with a function that predicts future UL jitter using an AI/ML model based on past UL jitter values (UL jitter).
  • the UE may also be equipped with an AI model inference and/or AI model training function (see Figure 4) for the prediction function.
  • UL jitter may be predicted for each QoS/QFI (QoS Flow Identifier) and reported to the gNB.
  • QoS/QFI QoS Flow Identifier
  • the gNB may enable the UE to turn on/off the prediction and reporting of UL jitter using the AI/ML model, for example, via an RRC message.
  • the gNB may activate or deactivate the function using the MAC-CE.
  • the report of the UL jitter predicted by the AI/ML model may be triggered when the jitter value (jitter amount), or the average, median, jitter range or jitter variance of the jitter value exceeds a threshold.
  • the UE may report the UL jitter based on a reporting periodicity pre-configured by the gNB. Alternatively, the UE may report the UL jitter in response to an explicit instruction from the gNB.
  • the UE may report the UL jitter predicted by the AI/ML Model with a timestamp (which may be relative or absolute time information) that allows the future time of the predicted target to be determined. For example, jitter range in 10 minutes, jitter range in 30 minutes, jitter range in 60 minutes, jitter range in 120 minutes, etc.
  • a timestamp which may be relative or absolute time information
  • the gNB may set a timer (prohibit timer) for the UE. Specifically, when the UE reports UL jitter predicted by the AI/ML model, the prohibit timer may be started, and the next report may be prohibited until the prohibit timer expires.
  • Figure 7 shows an example of a communication sequence for DL jitter reporting in operation example 2.
  • the SMF may predict future DL jitter using an AI/ML model and report the predicted jitter amount (range) to the gNB.
  • the gNB may be equipped with a function to predict future DL jitter using an AI/ML model based on past DL jitter values (DL jitter).
  • the gNB may also be equipped with an AI model inference and/or AI model training function (see Figure 4) for the prediction function.
  • a network node such as the UPF or SMF may be equipped with the function to predict DL jitter.
  • the DL jitter value predicted by the AI/ML model may be reported to the gNB, for example, from the SMF via the AMF.
  • DL jitter may be predicted for each QoS/QFI (QoS Flow Identifier) and reported from the SMF via the AMF to the gNB (similarly, it may be reported from the SMF to the gNB below).
  • QoS/QFI QoS Flow Identifier
  • the DL jitter report predicted by the AI/ML model may be triggered when the jitter value (jitter amount), or the average, median, jitter range or jitter variance of the jitter value exceeds a threshold.
  • the UL jitter may be reported based on a pre-configured reporting periodicity.
  • the SMF may report the DL jitter in response to an explicit instruction from the gNB.
  • the SMF may attach a timestamp (which may be relative or absolute time information) to the report of DL jitter predicted by the AI/ML model, which allows the future time of the prediction to be determined. For example, jitter range in 10 minutes, jitter range in 30 minutes, jitter range in 60 minutes, jitter range in 120 minutes, etc.
  • a timestamp which may be relative or absolute time information
  • the UE can report UL jitter predicted by the AI/ML model, allowing the gNB to recognize future UL jitter and achieve more efficient and planned UL scheduling.
  • network devices such as the gNB, UPF, or SMF can predict DL jitter by the AI/ML model and report it to other network devices or UEs as necessary, achieving more efficient and planned DL scheduling.
  • the UE can mitigate overheating and reduce power consumption by notifying the gNB of the maximum number of CCs, maximum bandwidth, and maximum number of MIMO layers that it wants to set.
  • 3GPP TS38.331 (Release-17) allows the secondary cell group that you want to deactivate (scg-DeactivationPreference) to be reported to the gNB. This can also reduce power consumption.
  • the gNB can recognize the current or future remaining battery charge of the UE, it can systematically set the maximum number of CCs, maximum bandwidth, and maximum number of MIMO layers for the UE. The gNB can also decide to activate or deactivate the SCG for the UE. However, the gNB cannot recognize the current or future remaining battery charge of the UE.
  • Operation Example Fig. 8 shows an example of a communication sequence related to a battery remaining amount report according to Operation Example 3. As shown in Fig. 8, the UE can report the current battery remaining amount to the network, predict the future battery remaining amount using an AI/ML model, and report the predicted battery remaining amount to the network.
  • the UE may obtain the current battery remaining capacity and report the obtained battery remaining capacity to the gNB.
  • the battery remaining capacity may be indicated, for example, by a percentage (100%, 80%, 60%, 40%, 20%, 5%, etc.).
  • the UE may also be equipped with a function for predicting future remaining battery charge using an AI/ML model.
  • the UE may also be equipped with an AI model inference and/or AI model training function (see Figure 4) for the prediction function.
  • the UE may report the current battery remaining capacity and/or future battery remaining capacity via an RRC message (e.g., UE Assistance Information).
  • RRC message e.g., UE Assistance Information
  • the gNB may enable the UE to turn on/off the prediction and reporting of remaining battery capacity using an AI/ML model, for example, via an RRC message.
  • the gNB may activate or deactivate the function using the MAC-CE.
  • the UE may trigger a BSR and/or DSR to report the remaining battery capacity when the remaining battery capacity predicted by the AI/ML model falls below a threshold.
  • the UE may report the remaining battery capacity based on a reporting periodicity pre-set by the gNB. Alternatively, the UE may report the remaining battery capacity in response to an explicit instruction from the gNB.
  • the UE may attach a timestamp (which may be relative information or absolute time information) that can determine the future time that is the subject of the prediction to the report of remaining battery capacity predicted by the AI/ML model. For example, “remaining battery in 60 minutes,” “remaining in 120 minutes,” “remaining battery in 180 minutes,” “remaining in 240 minutes,” etc. may be used.
  • a timestamp which may be relative information or absolute time information
  • the gNB may set a prohibit timer for the UE. Specifically, when the UE reports the remaining battery capacity predicted by the AI/ML model, the prohibit timer may be started, and the next report may be prohibited until the prohibit timer expires.
  • the UE's current and future remaining battery power can be reported to the gNB, so the gNB can recognize the UE's current and future remaining battery power and can systematically determine the maximum number of CCs, maximum bandwidth, maximum number of MIMO layers, etc., taking into account the remaining battery power.
  • the gNB can also determine whether to activate or deactivate the SCG for the UE based on the remaining battery power.
  • future BSR, DSR, UL/DL jitter, and remaining battery capacity were predicted using an AI/ML model, but the term prediction may be replaced with terms such as determination, calculation, computation, and arithmetic.
  • configure, activate, update, indicate, enable, specify, and select may be read as interchangeable.
  • link, associate, correspond, and map may be read as interchangeable, and allocate, assign, monitor, and map may also be read as interchangeable.
  • 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 connected directly or indirectly (e.g., using wires, wirelessly, etc.).
  • the functional blocks may be realized by combining the one device or the multiple devices with software.
  • 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, regard, broadcasting, notifying, communicating, forwarding, configuring, reconfiguring, allocating, mapping, and assignment.
  • a functional block (component) that performs the transmission function is called a transmitting unit or transmitter.
  • FIG. 9 is a diagram showing an example of the hardware configuration of the device.
  • the device may be 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, and a bus 1007.
  • apparatus can be interpreted as a circuit, device, unit, etc.
  • the hardware configuration of the apparatus may be configured to include one or more of the devices shown in the figure, or may be configured to exclude some of the devices.
  • Each functional block of the device (see Figures 2 and 3) is realized by any hardware element of the computer device, or a combination of the hardware elements.
  • each function of the device is realized by loading a specific software (program) onto hardware such as the processor 1001 and memory 1002, causing the processor 1001 to perform calculations, control communications by the communications device 1004, and control at least one of reading and writing data in the memory 1002 and storage 1003.
  • a specific software program
  • 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) that includes an interface with peripheral devices, a control unit, an arithmetic unit, registers, etc.
  • CPU central processing unit
  • 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-mentioned embodiments.
  • the various processes described above may be executed by one processor 1001, or may be executed simultaneously or sequentially by two or more processors 1001.
  • the processor 1001 may be implemented by one or more chips.
  • the programs may be transmitted from a network via a telecommunications line.
  • Memory 1002 is a computer-readable recording medium and may be composed of, for example, at least one of Read Only Memory (ROM), Erasable Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), Random Access Memory (RAM), etc.
  • Memory 1002 may also be called a register, cache, main memory, etc.
  • Memory 1002 can store a program (program code), software module, etc. capable of executing a method according to one embodiment of the present disclosure.
  • Storage 1003 is a computer-readable recording medium, and may be, for example, at least one of an optical disk such as a Compact Disc ROM (CD-ROM), a hard disk drive, a flexible disk, a magneto-optical disk (e.g., a compact disk, a digital versatile disk, a Blu-ray (registered trademark) disk), a smart card, a flash memory (e.g., a card, a stick, a key drive), a floppy (registered trademark) disk, a magnetic strip, etc.
  • Storage 1003 may also be referred to as an auxiliary storage device.
  • the above-mentioned recording medium may be, for example, a database, a server, or other suitable medium including at least one of memory 1002 and storage 1003.
  • 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, a communication module, etc.
  • the communication device 1004 may be configured to include a high-frequency switch, a duplexer, a filter, a frequency synthesizer, etc., to realize, for example, at least one of Frequency Division Duplex (FDD) and Time Division Duplex (TDD).
  • FDD Frequency Division Duplex
  • TDD Time Division Duplex
  • 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, an LED lamp, etc.) that performs output to the outside. Note that the input device 1005 and the output device 1006 may be integrated into one structure (e.g., a touch panel).
  • each device such as the processor 1001 and the memory 1002 is connected by a bus 1007 for communicating information.
  • the bus 1007 may be configured using a single bus, or may be configured using different buses between each device.
  • the device 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 by the hardware.
  • DSP digital signal processor
  • ASIC application specific integrated circuit
  • PLD programmable logic device
  • FPGA field programmable gate array
  • the processor 1001 may be implemented using at least one of these pieces of hardware.
  • the notification of information is not limited to the aspects/embodiments described in the present disclosure and may be performed using other methods.
  • the notification of information may be performed by physical layer signaling (e.g., Downlink Control Information (DCI), Uplink Control Information (UCI)), higher layer signaling (e.g., RRC signaling, Medium Access Control (MAC) signaling, broadcast information (Master Information Block (MIB), System Information Block (SIB)), other signals, or a combination of these.
  • RRC signaling may be referred to as an RRC message, and may be, for example, an RRC Connection Setup message, an RRC Connection Reconfiguration message, etc.
  • LTE Long Term Evolution
  • LTE-A LTE-Advanced
  • SUPER 3G IMT-Advanced
  • 4th generation mobile communication system 4th generation mobile communication system
  • 5G 5th generation mobile communication system
  • 6G 6th generation mobile communication system
  • xth generation mobile communication system The present invention may be applied to at least one of systems using LTE, LTE-A, LTE-G, LTE-H, LTE-H-G ...
  • certain operations that are described as being performed by a base station may in some cases also be performed by its upper node.
  • a network consisting of one or more network nodes having a base station
  • various operations performed for communication with a terminal may be performed by at least one of the base station and other network nodes other than the base station (such as, but not limited to, an MME or S-GW).
  • the above example shows a case where there is one other network node other than the base station, it may also be a combination of multiple other network nodes (such as an MME and an S-GW).
  • Information, signals can be output from a higher layer (or a lower layer) to a lower layer (or a higher layer). They may be input and output via multiple network nodes.
  • the input and output information may be stored in a specific location (e.g., memory) or may be managed using a management table.
  • the input and output information may be overwritten, updated, or appended.
  • the output information may be deleted.
  • the input information may be sent to another device.
  • the determination may be based on a value represented by one bit (0 or 1), a Boolean (true or false) value, or a numerical comparison (e.g., with a predetermined value).
  • notification of specific information is not limited to being done explicitly, but may be done implicitly (e.g., not notifying the specific information).
  • 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 be transmitted and received over a transmission medium.
  • a transmission medium For example, if 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/or wireless technologies is included within the definition of a transmission medium.
  • wired technologies such as coaxial cable, fiber optic cable, twisted pair, Digital Subscriber Line (DSL)
  • wireless technologies such as infrared, microwave, etc.
  • the information, signals, etc. described in this disclosure may be represented using any of a variety of different technologies.
  • the data, instructions, commands, information, signals, bits, symbols, chips, etc. that may be referred to throughout the above description may be represented by voltages, currents, electromagnetic waves, magnetic fields or magnetic particles, optical fields or photons, or any combination thereof.
  • At least one of the channel and the symbol may be a signal (signaling).
  • the signal may be a message.
  • a component carrier (CC) may be called a carrier frequency, a cell, a frequency carrier, etc.
  • system and “network” are used interchangeably.
  • a radio resource may be indicated by an index.
  • the names used for the above-mentioned parameters are not limiting in any respect. Furthermore, the formulas etc. using these parameters may differ from those explicitly disclosed in this disclosure.
  • the various channels (e.g., 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.
  • Base station BS
  • wireless base station fixed station
  • NodeB NodeB
  • eNodeB eNodeB
  • gNodeB gNodeB
  • a base station can accommodate one or more (e.g., three) cells (also called sectors). If a base station accommodates multiple cells, the overall 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 indoor base station (Remote Radio Head: RRH)).
  • a base station subsystem e.g., a small indoor base station (Remote Radio Head: RRH)
  • cell refers to part or all of the coverage area of a base station and/or a base station subsystem that provides communication services within that coverage.
  • a base station transmitting information to a terminal may be interpreted as the base station instructing the terminal to control or operate based on the information.
  • MS Mobile Station
  • UE User Equipment
  • a mobile station may also be referred to by those skilled in the art 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 communication device, etc.
  • At least one of the base station and the mobile station may be a device mounted on a moving object, the moving object itself, etc.
  • the moving object is a movable object, and the moving speed is arbitrary. It also includes the case where the moving object is stopped.
  • the moving object includes, but is not limited to, for example, a vehicle, a transport vehicle, an automobile, a motorcycle, a bicycle, a connected car, an excavator, a bulldozer, a wheel loader, a dump truck, a forklift, a train, a bus, a handcar, a rickshaw, a ship and other watercraft, an airplane, a rocket, an artificial satellite, a drone (registered trademark), a multicopter, a quadcopter, a balloon, and objects mounted thereon.
  • the moving object may also be a moving object that runs autonomously based on an operation command.
  • At least one of the base station and the mobile station may be a device that does not necessarily move during communication operations.
  • at least one of the base station and the mobile station may be an IoT (Internet of Things) device such as a sensor.
  • IoT Internet of Things
  • the base station in the present disclosure may be interpreted as a mobile station (user terminal, the same applies below).
  • each aspect/embodiment of the present disclosure may be applied to a configuration in which communication between a base station and a mobile station is replaced with communication between multiple mobile stations (which may be called, for example, Device-to-Device (D2D), Vehicle-to-Everything (V2X), etc.).
  • the mobile station may be configured to have the functions of a base station.
  • terms such as "uplink” and "downlink” may be interpreted as terms corresponding to communication between terminals (for example, "side”).
  • the uplink channel, downlink channel, etc. may be interpreted as a side channel (or side link).
  • the mobile station in this disclosure may be interpreted as a base station.
  • the base station may be configured to have the functions of the mobile station.
  • a radio frame may be composed of one or more frames in the time domain. Each of the one or more frames in the time domain may be called a subframe. A subframe may further 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.
  • Numerology may be a communication parameter that applies to at least one of the transmission and reception of a signal or channel. 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 structure, a particular filtering operation performed by the transceiver in the frequency domain, a particular windowing operation performed by the transceiver in the time domain, etc.
  • SCS Subcarrier Spacing
  • TTI Transmission Time Interval
  • radio frame structure a particular filtering operation performed by the transceiver in the frequency domain, a particular windowing operation performed by the transceiver in the time domain, etc.
  • a slot may consist of one or more symbols in the time domain (e.g., Orthogonal Frequency Division Multiplexing (OFDM) symbols, Single Carrier Frequency Division Multiple Access (SC-FDMA) symbols, etc.).
  • OFDM Orthogonal Frequency Division Multiplexing
  • SC-FDMA Single Carrier Frequency Division Multiple Access
  • a slot may be a numerology-based unit of time.
  • 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 (or PUSCH) mapping type A.
  • a PDSCH (or PUSCH) transmitted using a minislot may be called PDSCH (or PUSCH) mapping type B.
  • Radio frame, subframe, slot, minislot, and symbol all represent time units for transmitting signals. Radio frame, subframe, slot, minislot, and symbol may each be referred to by a different name that corresponds to the radio frame, subframe, slot, minislot, and symbol.
  • one subframe may be called a transmission time interval (TTI)
  • TTI transmission time interval
  • multiple consecutive subframes may be called a TTI
  • one slot or one minislot may be called a TTI.
  • at least one of the subframe and the TTI may be a subframe (1 ms) in existing LTE, a period shorter than 1 ms (e.g., 1-13 symbols), or a period longer than 1 ms.
  • the unit expressing the TTI may be called a slot, minislot, etc., instead of a subframe.
  • TTI refers to, for example, the smallest time unit for scheduling in wireless communication.
  • a base station schedules each user terminal by allocating radio resources (such as frequency bandwidth and transmission power that can be used by each user terminal) in TTI units.
  • radio resources such as frequency bandwidth and transmission power that can be used by each user terminal
  • the TTI may be a transmission time unit for a channel-encoded data packet (transport block), a code block, a code word, etc., or may be a processing unit for scheduling, link adaptation, etc.
  • the time interval e.g., the number of symbols
  • the time interval in which a transport block, a code block, a code word, etc. is actually mapped may be shorter than the TTI.
  • one or more TTIs may be the minimum time unit of scheduling.
  • the number of slots (minislots) that constitute the minimum time unit of scheduling may be controlled.
  • a long TTI (e.g., a normal TTI, a subframe, etc.) may be interpreted as a TTI having a time length of more than 1 ms
  • a short TTI e.g., a shortened TTI, etc.
  • the time domain of an RB may include one or more symbols and may be one slot, one minislot, one subframe, or one TTI in length.
  • One TTI, one subframe, etc. may each be composed of one or more resource blocks.
  • one or more RBs may also be referred to as a physical resource block (PRB), a sub-carrier group (SCG), a resource element group (REG), a PRB pair, an RB pair, etc.
  • PRB physical resource block
  • SCG sub-carrier group
  • REG resource element group
  • PRB pair an RB pair, etc.
  • a resource block may be composed of one or more resource elements (RE).
  • RE resource elements
  • one RE may be a radio resource area of one subcarrier and one symbol.
  • a Bandwidth Part which may also be referred to as a partial bandwidth, may represent a subset of contiguous common resource blocks (RBs) for a given numerology on a given carrier, where the common RBs may be identified by an index of the RB relative to a common reference point of the carrier.
  • PRBs may be defined in a BWP and numbered within that BWP.
  • the BWP may include a BWP for UL (UL BWP) and a BWP for DL (DL BWP).
  • UL BWP UL BWP
  • DL BWP DL BWP
  • One or more BWPs may be configured for a UE within one carrier.
  • At least one of the configured BWPs may be active, and the UE may not expect to transmit or receive a given signal/channel outside the active BWP.
  • BWP bitmap
  • radio frames, subframes, slots, minislots, and symbols are merely examples.
  • the number of subframes included in a radio frame, the number of slots per subframe or radio frame, the number of minislots included in a slot, the number of symbols and RBs included in a slot or minislot, the number of subcarriers included in an RB, as well as the number of symbols in a TTI, the symbol length, and the cyclic prefix (CP) length can be changed in various ways.
  • connection refers 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 elements may be physical, logical, or a combination thereof.
  • “connected” may be read as "access.”
  • two elements may be considered to be “connected” or “coupled” to each other using at least one of one or more wires, cables, and printed electrical connections, as well as electromagnetic energy having wavelengths in the radio frequency range, microwave range, and optical (both visible and invisible) range, as some non-limiting and non-exhaustive examples.
  • the reference signal may also be abbreviated as Reference Signal (RS) or referred to as a pilot depending on the applicable standard.
  • RS Reference Signal
  • 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 an element using a designation 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 way of distinguishing between two or more elements. Thus, a reference to a first and a second element does not imply that only two elements may be employed therein or that the first element must precede the second element in some way.
  • determining may encompass a wide variety of actions.
  • Determining and “determining” may include, for example, judging, calculating, computing, processing, deriving, investigating, looking up, search, inquiry (e.g., searching in a table, database, or other data structure), ascertaining something as “judging” or “determining”, and the like.
  • Determining and “determining” may also include receiving (e.g., receiving information), transmitting (e.g., sending information), input, output, accessing (e.g., accessing data in memory), and the like as “judging” or “determining”.
  • judgment and “decision” can include considering resolving, selecting, choosing, establishing, comparing, etc., to have been “judged” or “decided.” In other words, “judgment” and “decision” can include considering some action to have been “judged” or “decided.” Additionally, “judgment (decision)” can be interpreted as “assuming,” “expecting,” “considering,” etc.
  • 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.”
  • FIG. 10 shows an example of the configuration of a vehicle 2001.
  • the vehicle 2001 includes a drive unit 2002, a steering unit 2003, an accelerator pedal 2004, a brake pedal 2005, a shift lever 2006, left and right front wheels 2007, left and right rear wheels 2008, an axle 2009, an electronic control unit 2010, various sensors 2021-2029, an information service unit 2012, and a communication module 2013.
  • the drive unit 2002 is composed of, for example, an engine, a motor, or a hybrid of an engine and a motor.
  • the steering unit 2003 includes at least a steering wheel (also called a handle) and is configured to steer at least one of the front wheels and the rear wheels based on the operation of the steering wheel operated by the user.
  • a steering wheel also called a handle
  • the electronic control unit 2010 is composed of a microprocessor 2031, a memory (ROM, RAM) 2032, and a communication port (IO port) 2033. Signals are input to the electronic control unit 2010 from various sensors 2021 to 2027 provided in the vehicle.
  • the electronic control unit 2010 may also be called an ECU (Electronic Control Unit).
  • Signals from the various sensors 2021 to 2028 include a current signal from a current sensor 2021 that senses the current of the motor, a rotation speed signal of the front and rear wheels acquired by a rotation speed sensor 2022, an air pressure signal of the front and rear wheels acquired by an air pressure sensor 2023, a vehicle speed signal acquired by a vehicle speed sensor 2024, an acceleration signal acquired by an acceleration sensor 2025, an accelerator pedal depression amount signal acquired by an accelerator pedal sensor 2029, a brake pedal depression amount signal acquired by a brake pedal sensor 2026, a shift lever operation signal acquired by a shift lever sensor 2027, and a detection signal for detecting obstacles, vehicles, pedestrians, etc. acquired by an object detection sensor 2028.
  • the information service unit 2012 is composed of various devices, such as a car navigation system, an audio system, speakers, a television, and a radio, for providing (outputting) various information such as driving information, traffic information, and entertainment information, and one or more ECUs for controlling these devices.
  • the information service unit 2012 uses information acquired from external devices via the communication module 2013, etc., to provide various multimedia information and multimedia services to the occupants of the vehicle 1.
  • the information service unit 2012 may include input devices (e.g., a keyboard, a mouse, a microphone, a switch, a button, a sensor, a touch panel, etc.) that accept input from the outside, and may also include output devices (e.g., a display, a speaker, an LED lamp, a touch panel, etc.) that perform output to the outside.
  • input devices e.g., a keyboard, a mouse, a microphone, a switch, a button, a sensor, a touch panel, etc.
  • output devices e.g., a display, a speaker, an LED lamp, a touch panel, etc.
  • the driving assistance system unit 2030 is composed of various devices that provide functions for preventing accidents and reducing the driving burden on the driver, such as a millimeter wave radar, LiDAR (Light Detection and Ranging), a camera, a positioning locator (e.g., GNSS, etc.), map information (e.g., high definition (HD) map, autonomous vehicle (AV) map, etc.), a gyro system (e.g., IMU (Inertial Measurement Unit), INS (Inertial Navigation System), etc.), AI (Artificial Intelligence) chip, and an AI processor, as well as one or more ECUs that control these devices.
  • the driving assistance system unit 2030 also transmits and receives various information via the communication module 2013 to realize driving assistance functions or autonomous driving functions.
  • the communication module 2013 can communicate with the microprocessor 2031 and components of the vehicle 1 via the communication port.
  • the communication module 2013 transmits and receives data via the communication port 2033 between the drive unit 2002, steering unit 2003, accelerator pedal 2004, brake pedal 2005, shift lever 2006, left and right front wheels 2007, left and right rear wheels 2008, axle 2009, microprocessor 2031 and memory (ROM, RAM) 2032 in electronic control unit 2010, and sensors 2021 to 2028, which are provided on the vehicle 2001.
  • the communication module 2013 is a communication device that can be controlled by the microprocessor 2031 of the electronic control unit 2010 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 2013 may be located either inside or outside the electronic control unit 2010.
  • the external device may be, for example, a base station, a mobile station, etc.
  • the communications module 2013 may transmit at least one of the signals from the various sensors 2021-2028 described above input to the electronic control unit 2010, information obtained based on the signals, and information based on input from the outside (user) obtained via the information service unit 2012 to an external device via wireless communication.
  • the electronic control unit 2010, the various sensors 2021-2028, the information service unit 2012, etc. may be referred to as input units that accept input.
  • the PUSCH transmitted by the communications module 2013 may include information based on the above input.
  • the communication module 2013 receives various information (traffic information, signal information, vehicle distance information, etc.) transmitted from an external device, and displays it on the information service unit 2012 provided in the vehicle.
  • the information service unit 2012 may 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 2013).
  • the communication module 2013 also stores various information received from an external device in a memory 2032 that can be used by the microprocessor 2031.
  • the microprocessor 2031 may control the drive unit 2002, steering unit 2003, accelerator pedal 2004, brake pedal 2005, shift lever 2006, left and right front wheels 2007, left and right rear wheels 2008, axles 2009, sensors 2021 to 2028, etc. provided in the vehicle 2001.
  • a first feature is a terminal including a control unit that predicts an allowable transmission delay for uplink data waiting to be transmitted using a learning model, and a transmission unit that transmits a report of the predicted transmission delay to a network.
  • the second feature is the first feature, in which the control unit predicts at least one of the future state of the uplink data in the buffer and the future transmission delay based on the past state of the uplink data in the buffer and the past transmission delay.
  • the third feature is the first or second feature, in which the transmission unit transmits the report based on an instruction from the network.
  • the fourth feature is the second or third feature, in which the transmitter transmits the report when the uplink data remaining in the buffer exceeds a threshold or when the transmission delay is smaller than a threshold.
  • the fifth feature is that in the first to fourth features, the transmission unit starts a timer based on an instruction from the network, and transmits the report when the timer expires.
  • the sixth feature is a terminal that includes a control unit that uses a learning model to predict jitter that will occur in uplink data, and a transmission unit that transmits a report of the predicted jitter to the network.
  • the seventh feature is the sixth feature, in which the control unit predicts the jitter based on identification information of the service quality flow.
  • the eighth feature is the sixth or seventh feature, in which the transmitter transmits the report when the value indicating the jitter characteristic exceeds a threshold value.
  • the ninth feature is that in the sixth to eighth features, the transmission unit starts a timer based on an instruction from the network, and transmits the report when the timer expires.
  • the tenth feature is a terminal that includes a control unit that determines the remaining charge of an installed battery, and a transmission unit that transmits a report of the determined remaining charge of the battery to a network.
  • the eleventh feature is the tenth feature, in which the control unit predicts the remaining charge of the battery in the future using a learning model.
  • the twelfth feature is the tenth or eleventh feature, in which the transmission unit transmits the report based on an instruction from the network.
  • the thirteenth feature is any one of the tenth to twelfth features, in which the transmitter transmits the report when the remaining charge of the battery falls below a threshold.
  • the fourteenth feature is any one of the tenth to thirteenth features, in which the transmission unit starts a timer based on an instruction from the network, and transmits the report when the timer expires.
  • Wireless Communication Systems 20 NG-RAN 50 NF 100 gNB 110 wireless communication unit 120 scheduling unit 130 AI/ML model unit 140 control unit 200 UE 210 wireless communication unit 220 AI/ML model unit 230 reporting unit 240 control unit 1001 processor 1002 memory 1003 storage 1004 communication device 1005 input device 1006 output device 1007 bus 2001 vehicle 2002 drive unit 2003 steering unit 2004 accelerator pedal 2005 brake pedal 2006 shift lever 2007 left and right front wheels 2008 left and right rear wheels 2009 axle 2010 electronic control unit 2012 information service unit 2013 communication module 2021 current sensor 2022 rotation speed sensor 2023 air pressure sensor 2024 vehicle speed sensor 2025 acceleration sensor 2026 brake pedal sensor 2027 shift lever sensor 2028 Object detection sensor 2029 Accelerator pedal sensor 2030 Driving assistance system section 2031 Microprocessor 2032 Memory (ROM, RAM) 2033 communication port

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  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Physics & Mathematics (AREA)
  • Electromagnetism (AREA)
  • Mobile Radio Communication Systems (AREA)
PCT/JP2024/029704 2023-08-24 2024-08-21 端末及び無線通信方法 Pending WO2025041803A1 (ja)

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Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2009204590A (ja) * 2008-02-29 2009-09-10 Hitachi Ltd ポータブルナビゲーション機器
WO2013047001A1 (ja) * 2011-09-30 2013-04-04 京セラ株式会社 移動通信方法、ユーザ端末、及びプロセッサ
US20210123982A1 (en) * 2019-10-29 2021-04-29 Samsung Electronics Co., Ltd. Apparatus and method for predicting a remaining battery life in a device
US20220005358A1 (en) * 2018-10-04 2022-01-06 Postmates Inc. Hailing self driving personal mobility devices

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2009204590A (ja) * 2008-02-29 2009-09-10 Hitachi Ltd ポータブルナビゲーション機器
WO2013047001A1 (ja) * 2011-09-30 2013-04-04 京セラ株式会社 移動通信方法、ユーザ端末、及びプロセッサ
US20220005358A1 (en) * 2018-10-04 2022-01-06 Postmates Inc. Hailing self driving personal mobility devices
US20210123982A1 (en) * 2019-10-29 2021-04-29 Samsung Electronics Co., Ltd. Apparatus and method for predicting a remaining battery life in a device

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