Terminal and wireless communication method

Abstract

A terminal according to the present invention determines the remaining power of a mounted battery and transmits a report about the determined remaining power of the battery to a network.

Description

Terminal and wireless communication method

[0001] The present disclosure relates to a terminal and a wireless communication method.

[0002] The 3rd Generation Partnership Project (3GPP: registered trademark) is developing 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.

[0003] For example, 3GPP Release 18 proposes a functional architecture for an artificial intelligence / machine learning model (AI / ML Model) (Non-Patent Document 1).

[0004] In addition, 3GPP Release 17 allows a terminal (User Equipment, UE) to report information that contributes to mitigating UE overheating (overheatingAssistance) to the network (specifically, gNB) using UE Assistance Information (see Non-Patent Document 2). Furthermore, the UE can report the secondary cell group (scg-DeactivationPreference) that it wishes to deactivate to the gNB. This ultimately reduces the UE's power consumption and can suppress battery consumption.

[0005] "Discussion on AI / ML Architecture General", R2-2305969, 3GPP TSG-RAN WG2 Meeting #122, 3GPP, May 20233GPP TS 38.331 V17.5.0, 3rd Generation Partnership Project; Technical Specification Group Radio Access Network; NR; Radio Resource Control (RRC) protocol specification (Release 17), 3GPP, June 2023

[0006] As described above, overheatingAssistance or scg-DeactivationPreference can reduce battery consumption of the UE, but both are indirect methods and have limited effect in reducing battery consumption.

[0007] The following disclosure has been made in light of the above circumstances, and aims to provide a terminal and a wireless communication method that can more directly reduce battery consumption.

[0008] 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 a network.

[0009] One aspect of the present disclosure is a terminal comprising a control unit (control unit 240) that predicts jitter that occurs in uplink data using a learning model, and a transmission unit that transmits a report of the predicted jitter to a network.

[0010] One aspect of the present disclosure is a terminal (UE200) that includes a control unit (control unit 240) that determines the remaining capacity of an installed battery, and a transmission unit (report unit 230) that transmits a report of the determined remaining capacity of the battery to a network.

[0011] FIG. 1 is a diagram showing an overall schematic configuration of a wireless communication system 10. FIG. 2 is a functional block configuration diagram of a gNB 100. FIG. 3 is a functional block configuration diagram of a UE 200. FIG. 4 is a diagram showing an example of the functional architecture of an AI / ML model. FIG. 5 is a diagram showing an example of a communication sequence related to BSR and DSR according to an operation example 1. FIG. 6 is a diagram showing an example of a communication sequence related to a UL jitter report according to an operation example 2. FIG. 7 is a diagram showing an example of a communication sequence related to a DL jitter report according to an operation example 2. FIG. 8 is a diagram showing an example of a communication sequence related to a remaining battery level report according to an operation example 3. FIG. 9 is a diagram showing an example of the hardware configuration of a gNB 100 and a UE 200. FIG. 10 is a diagram showing an example of the configuration of a vehicle 2001.

[0012] Hereinafter, embodiments will be described with reference to the drawings. Note that the same or similar reference numerals are used to designate the same functions or configurations, and descriptions thereof will be omitted as appropriate.

[0013] (1) Overall Schematic Configuration of Wireless Communication System Fig. 1 is a diagram showing the overall schematic configuration 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).

[0014] 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 Ultra-Reliable and Low Latency Communications (URLLC).

[0015] The NG-RAN 20 includes a radio base station 100 (hereinafter, gNB 100). Note that the specific configuration of the radio communication system 10, including the number of gNBs (or eNBs, etc.) and UEs, is not limited to the example shown in FIG. 1 .

[0016] The gNB 100 may also employ a fronthaul (FH) interface defined by the Open Radio Access Network Alliance (O-RAN). The gNB 100 may include an O-RAN Distributed Unit (O-DU) and an O-RAN Radio Unit (O-RU). The gNB 100 can function as a type of NG-RAN node.

[0017] The NG-RAN 20 actually includes multiple NG-RAN nodes, specifically, gNBs (or ng-eNBs), and is connected to a 5G-compliant core network (5GC, not shown). In the 5GC, the concept of CUPS (Control and User Plane Separation) may be introduced, in which the functions of the user plane and the control plane are clearly separated.

[0018] The NG-RAN 20 may be connected to the NF 50 via the 5G LTE network or directly from the NG-RAN 20. The NF 50 may be interpreted as a logical node providing a network function. The NF 50 may include, as part of the 5G system architecture, an Access and Mobility Management Function (AMF) that provides access and mobility management functions for the UE 200, 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 the 5G LTE network, and a Location Management Function (LMF) that controls communications related to location-based services specified in the 5G LTE network. Furthermore, a Unified Data Management / User Data Repository (UDM / UDR) may be connected to the AMF and / or SMF. The NG-RAN 20 and the 5G LTE network may also be referred to simply as a "network."

[0019] In addition, the NG-RAN 20 may be connected to a server managed by a 3GPP service provider or a server (3GPP or non-3GPP server) managed by a party other than the provider.

[0020] The gNB100 is a radio base station conforming to NR and performs radio communication with the UE200 conforming to NR. The gNB100 may be configured with 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. The gNB100 (gNB-CU) may be connected to each other via an Xn interface, and the CU and DU may be connected to each other via an F1 interface.

[0021] The gNB100 and UE200 are capable of supporting Massive MIMO, which generates more directional beams by controlling radio signals transmitted from multiple antenna elements; Carrier Aggregation (CA), which aggregates and uses multiple component carriers (CCs); and Dual Connectivity (DC), which enables simultaneous communication between the UE and multiple NG-RAN nodes.

[0022] Furthermore, in the wireless communication system 10, artificial intelligence (AI) / machine learning (ML) may be applied to the NG-RAN 20. Specifically, a learning model (herein referred to as an AI / ML model) may be used to optimize the mobility or handover (which may also be read as transition, cell transition, cell selection, etc.) of the UE 200.

[0023] The AI / ML model may also be expressed as another term meaning AI or ML, such as an artificial intelligence (AI) model or a machine learning (ML) model.

[0024] In a broad sense, the mobility of UE200 may mean the ease of movement and maneuverability of UE200, but in this embodiment, it may also mean minimizing call drops, radio link (including beam) failures, unnecessary handovers, ping-pong states, etc.

[0025] In the wireless communication system 10, such an AI / ML model may be used to predict various states related to the UE 200. In particular, in this embodiment, the AI / ML model may be used to predict the buffer of the UE 200, the delay time of uplink (UL) data, UL jitter, remaining battery capacity, etc. Furthermore, the AI / ML model may be used to predict DL jitter in the gNB 100, etc.

[0026] The AI / ML model may be provided in the NF 50 or the gNB 100. The AI / ML model may also be provided in the UE 200.

[0027] Furthermore, in the wireless communication system 10, the UE 200 may support transmission of a report indicating an internal UL status of the UE 200. Specifically, the UE 200 may support a Buffer Status Report (BSR) and a Delay Status Report (DSR).

[0028] The BSR reports to the network (gNB) the status of the buffers (which may be interpreted as Radio Link Control Layer (RLC) buffers) for UL transmissions in the UE 200. The buffer size field of the BSR may indicate the amount of data waiting to be transmitted across all logical channels in a logical channel group (LCG).

[0029] A BSR may be triggered for the following reasons:

[0030] When data arrives in the buffer that has a higher priority than the data currently in the transmit buffer, i.e., data in an LCG that has a higher priority than the data currently being transmitted, this can affect scheduling decisions.

[0031] - When the timer expires.

[0032] Padding alternative: If the amount of padding required to match the scheduled transport block (TB) size is larger than the BSR, then the BSR may be inserted, since it is better to derive useful scheduling information from the available payload rather than padding, if possible.

[0033] The DSR reports to the network (gNB) the delay time (waiting time) that can be tolerated (that can be waited) until transmission of UL data remaining in the transmission buffer. Specifically, the UE 200 can report the tolerable delay time (which may be called the remaining time) of the UL data remaining in the transmission buffer for each LCG. The UE 200 may also report the size of the transmission buffer to the gNB. Based on the remaining time transmitted from the UE 200, the gNB can prioritize scheduling for LCGs that indicate a shorter remaining time.

[0034] Furthermore, in the wireless communication system 10, 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 refer to fluctuations in the transmission or reception timing of data in the time direction.

[0035] Note that the type of UE 200 is not particularly limited, but in this embodiment, a handheld terminal such as a smartphone equipped with a battery such as a lithium ion battery may be assumed. UE 200 may transmit information (overheatingAssistance) that contributes to mitigating overheating of UE 200 to gNB 100 using UE Assistance Information (see 3GPP TS38.331). This can mitigate overheating, reduce power consumption, and suppress battery consumption.

[0036] (2) Functional Block Configuration of Wireless Communication System Next, the functional block configuration of the wireless communication system 10 will be described. Specifically, the functional block configuration 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.

[0037] (2.1) gNB100 As shown in FIG. 2, the gNB100 includes a radio communication unit 110, a scheduling unit 120, an AI / ML model unit 130, and a control unit 140.

[0038] The wireless communication unit 110 transmits downlink signals (DL signals) conforming to NR, and also receives uplink signals (UL signals) conforming to NR.

[0039] The scheduler 120 performs DL scheduling and UL scheduling. Specifically, the scheduler 120 can dynamically or semi-statically allocate radio resources (time, frequency, and space) in DL and UL, determine transmission parameters including data rates, etc.

[0040] In this embodiment, 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. In this embodiment, the scheduling unit 120 may constitute a transmitting unit that transmits the jitter report to the terminal.

[0041] Specifically, 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.

[0042] 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 mobility and / or handover of the UE 200, etc.

[0043] For example, the AI / ML model unit 130 can determine the validity period of a trained AI / ML model. The AI / ML model unit 130 may 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.

[0044] The AI / ML model unit 130 may retrain the AI / ML model when the validity period of the AI / ML model expires or when the performance of the AI / ML model drops below a specified level. Note that the AI / ML model itself may be installed in the gNB 100 or in another network node (network device) such as the NF 50.

[0045] The AI / ML model unit 130 can also predict jitter that will occur in DL data. Specifically, the AI / ML model unit 130 learns 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 may be predicted in multiple ranges (e.g., 10 minutes, 30 minutes, etc.).

[0046] The control unit 140 controls each functional block constituting the gNB 100. In particular, in this embodiment, the control unit 140 can control scheduling by the scheduling unit 120 based on at least one of a BSR and a DSR transmitted from the UE 200.

[0047] Specifically, the control unit 140 may instruct the scheduling unit 120 to prioritize 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.

[0048] Furthermore, the control unit 140 can 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.

[0049] 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.

[0050] In this embodiment, the channels include a control channel and a data channel, such as a physical downlink control channel (PDCCH), a physical uplink control channel (PUCCH), a physical random access channel (PRACH), and a physical broadcast channel (PBCH).

[0051] The data channels include a physical downlink shared channel (PDSCH) and a physical uplink shared channel (PUSCH).

[0052] The reference signal includes a Demodulation Reference Signal (DMRS), a Sounding Reference Signal (SRS), a Phase Tracking Reference Signal (PTRS), and a Channel State Information-Reference Signal (CSI-RS), and the signal includes a channel and a reference signal. Furthermore, data may refer to data transmitted and received via a data channel. Meanwhile, control data may be transmitted and received by a message of a Radio Resource Control (RRC) layer.

[0053] In addition, in this embodiment, assembly / disassembly of Protocol Data Units (PDUs) and Service Data Units (SDUs) at multiple layers (such as Medium Access Control layer (MAC), Radio Link Control layer (RLC), and Packet Data Convergence Protocol layer (PDCP)) may be performed.

[0054] (2.2) UE 200 As shown in FIG. 3, the UE 200 includes a radio communication unit 210, an AI / ML model unit 220, a reporting unit 230, and a control unit 240.

[0055] The wireless communication unit 210 transmits an uplink signal (UL signal) conforming to NR. The wireless communication unit 210 also receives an uplink signal (DL signal) conforming to NR.

[0056] The AI / ML model unit 220 executes processing using a learning model (AI / ML Model). The AI / ML model unit 220 may have the same functions as the AI / ML model unit 130 of the gNB 100. The AI / ML model unit may be provided in either the gNB 100 or the UE 200, or may be provided in both.

[0057] In particular, in this embodiment, the AI / ML model unit 220 can predict the future remaining time based on the DSR. Note that the AI / ML model unit 220 may also predict the future amount of buffered data based on the BSR.

[0058] Specifically, the AI / ML model unit 220 learns the transition of the past remaining time, and can predict the future remaining time of UL data based on the learning results, etc. The amount of data remaining in the buffer may also be predicted in a similar manner.

[0059] The AI / ML model unit 220 can also predict jitter that may occur in UL data. Specifically, the AI / ML model unit 220 learns 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 may be predicted within multiple ranges (e.g., 10 minutes, 30 minutes, etc.).

[0060] Furthermore, the AI / ML model unit 220 can predict the remaining capacity of the battery installed in the UE 200. Specifically, the AI / ML model unit 220 can learn the past consumption state of the battery and predict the remaining capacity of the battery in the future based on the learning results, etc.

[0061] The reporting unit 230 executes various reports to the network. In particular, in this embodiment, 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. In this embodiment, the reporting unit 230 may constitute a transmitting unit that transmits the 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).

[0062] Specifically, the reporting unit 230 may transmit a report of the remaining time when the amount of UL data remaining in the transmission buffer of the UE 200 exceeds a threshold or when the remaining time is smaller than a threshold. At this time, the amount of data remaining in the buffer may also be reported in the same manner.

[0063] The reporting unit 230 may start a timer for reporting based on an instruction from the network, and when the timer expires, transmit a report of the remaining time.

[0064] Furthermore, the reporting unit 230 can 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. In this embodiment, 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).

[0065] Specifically, the reporting unit 230 may send a report of the jitter of the UL data if the value characteristic of the jitter of the UL data exceeds a threshold value.

[0066] The reporting unit 230 may start a timer for reporting based on an instruction from the network, and transmit a jitter report when the timer expires.

[0067] Furthermore, the reporting unit 230 can transmit a report of the remaining battery capacity determined by the control unit 240 to the network. In this embodiment, 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).

[0068] Specifically, the reporting unit 230 may send a report of the remaining battery power when the remaining battery power falls below a threshold.

[0069] The reporting unit 230 may start a timer based on an instruction from the network, and transmit a report of the remaining battery capacity when the timer expires.

[0070] The control unit 240 controls each functional block constituting the UE 200. In particular, in this embodiment, the control unit 240 can predict the future state of the UE 200 using the AI / ML model unit 220 (learning model).

[0071] Specifically, the 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 may use the AI / ML model unit 220 to predict at least one of the future state of the transmission buffer (which may be simply referred to as the buffer) and the future remaining time, based on the past state of the UL data in the transmission buffer and the past remaining time.

[0072] Furthermore, the control unit 240 can predict jitter that will occur in UL data using the AI / ML model unit 220. As described above, the control unit 240 may use the AI / ML model unit 220 to learn transitions in the amount of jitter that occurred in past UL data transmissions, and may predict the amount of jitter that may occur in future UL data transmissions based on the learning results, etc.

[0073] The control unit 240 may predict jitter based on the Quality of Service Flow (QoS Flow) Identification Information (QFI). Alternatively, the LCG or the logical channel (LC) may be used as the criterion. Note that this criterion may be applied not only to predicting jitter but also to predicting the remaining time and the like.

[0074] The control unit 240 may also determine the remaining capacity of a battery installed in the UE 200. For example, the control unit 240 may determine the remaining capacity of the battery according to stages divided by representative percentages (e.g., 100%, 80%, 60%, 40%, 20%, 5%).

[0075] The control unit 240 can also predict the remaining battery charge in the future using the AI / ML model unit 220. As described above, the control unit 240 may use the AI / ML model unit 220 to learn the past battery consumption state and predict the remaining battery charge in the future based on the learning results, etc.

[0076] (3) Operation of the Wireless Communication System Next, a description will be given of the operation of the wireless communication system 10. Specifically, a description will be given of an example of operation in which the future state of the UE 200 is predicted using an AI / ML model, and more efficient scheduling and power consumption reduction can be achieved.

[0077] (3.1) Example of AI / ML Model Configuration Figure 4 shows an example of the functional architecture of an AI / ML model. As shown in Figure 4, the architecture may include the following functions:

[0078] Data collection: Providing input data for model training and model inference functions.

[0079] Model training: Train, validate, and test ML models. As part of the model testing procedure, model performance metrics may be generated.

[0080] The model training function may also be responsible for data preparation (data pre-processing and cleaning, formatting, transformation, etc.).

[0081] Model inference: Provides inference output (such as a prediction or decision). The model inference function may provide control of the model inference to the model management / performance monitoring function.

[0082] Model management / performance monitoring: Manage ML models and monitor model performance.

[0083] (3.2) Premise As described above, the introduction of DSR (Delay Status Report) is being considered for the Work Item (WI) of augmented reality (XR), and the wireless communication system 10 may support DSR.

[0084] The network may be able to configure the UE whether to trigger (send) a DSR. The threshold for triggering a DSR may be configured, for example, per LCG. However, as mentioned above, it may also be per LC or QFI.

[0085] In addition, when transmitting a DSR for each LCG, the UE may also report (BSR) the status of the transmission buffer together with the remaining time.

[0086] Similar to BSR, DSR may be reported by a MAC-CE (Control Element), which may be an extension of the MAC-CE for BSR, or a new MAC-CE may be defined for DSR.

[0087] Below, we will explain an example of operation that takes into account the application of such an AI / ML model and the assumptions based on the WI of XR.

[0088] (3.3) Operation Example 1 (3.3.1) Issues As described above, gNB100 performs scheduling in accordance with the BSR and DSR reported from UE200.

[0089] In the above-described method of reporting BSR and DSR, UL data arrives in the UE (remains in the transmission buffer), and the UE transmits BSR and DSR to the gNB. The gNB performs scheduling for the UE based on the received BSR and DSR.

[0090] However, new UL data may continue to arrive (or be generated) at the UE while the UE is transmitting the BSR and DSR to the gNB, which raises the concern that the UE may not be able to report the BSR and DSR to the gNB for the new UL data that arrives after the UE has transmitted the BSR and DSR.

[0091] Furthermore, if there are many UEs with strict remaining times indicated by DSR, the gNB may not be able to simultaneously implement scheduling that corresponds to those remaining times.

[0092] If gNBs can recognize the contents of future BSRs and DSRs, they can achieve more efficient and planned scheduling.

[0093] (3.3.2) Operation Example Fig. 5 shows an example of a communication sequence regarding BSR and DSR according to Operation Example 1. As shown in Fig. 5, the UE may predict future buffer status and delay status (remaining time) using an AI / ML model and report BSR and DSR to the network.

[0094] Specifically, the UE may be equipped with a function for predicting the future state of the transmission buffer (amount of UL data remaining) and the delay state of data in the transmission buffer using an AI / ML model 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 also be equipped with an AI model inference and / or AI model training function (see FIG. 4) for the prediction function.

[0095] The prediction may be performed by a higher layer or a lower layer. Specifically, the prediction may be performed by 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 communicated between layers.

[0096] When prediction is made using an AI / ML model, the BSR and / or DSR may be reported to the gNB for each LCG, LC, or QoS / QFI (QoS Flow Identifier).

[0097] In the case of prediction by an AI / ML model, the BSR and / or DSR may be reported to the gNB by an existing MAC-CE for the BSR, or may be reported to the gNB by a new MAC-CE, or may be reported by an RRC message.

[0098] The gNB may enable the UE to turn on / off the prediction and reporting of the buffer status (BSR) and delay status (DSR) using the AI / ML model, for example, by an RRC message. Alternatively, the gNB may activate or deactivate the function using the MAC-CE.

[0099] The UE may trigger a BSR and / or a DSR when the amount of UL data remaining in the transmission buffer exceeds a threshold or when the remaining time is less than a threshold, based on predictions made using an AI / ML model. The UE may report a BSR and / or a DSR based on a reporting periodicity preset by the gNB. Alternatively, the UE may report a BSR and / or a DSR in response to an explicit instruction from the gNB.

[0100] The UE may attach a timestamp (which may be relative information or absolute time information) that can determine the future time that is the target of the prediction to the report of the buffer status (BSR) and delay status (DSR) predicted by the AI / ML model.

[0101] In addition, to avoid excessive reporting of the buffer status (BSR) and delay status (DSR) predicted by the AI / ML model, the gNB may set a timer (prohibit timer) for the UE. Specifically, when the UE reports the buffer status (BSR) and delay status (DSR) predicted by the AI / ML model, the prohibit timer is started, and the next report may be prohibited until the prohibit timer expires.

[0102] According to this operation example, the UE can report the buffer status (BSR) and delay status (DSR) predicted by the AI / ML model, so that the gNB can recognize the future contents of the BSR and DSR, thereby realizing more efficient and planned UL scheduling.

[0103] (3.4) Operation Example 2 (3.4.1) Issues 3GPP proposes that a UE report a single value indicating the jitter amount (range) of UL traffic (see, for example, 3GPP R2-2308352). UL traffic jitter may fluctuate from moment to moment depending on, for example, the congestion level of UL data transmitted from the UE. In other words, jitter may fluctuate over time, but it is difficult to report a jitter range that reflects such fluctuations. Note that this issue also applies to DL.

[0104] In other words, it is difficult for the UE to report future UL jitter to the gNB. Also, DL jitter cannot be notified to the gNB from the SMF via the AMF.

[0105] (3.4.2) Operation Example Fig. 6 shows an example of a communication sequence related to UL jitter reporting according to Operation Example 2. As shown in Fig. 6, the UE may predict future UL jitter using an AI / ML model and report the predicted jitter amount (range) to the network.

[0106] Specifically, the UE may be equipped with a function for predicting future UL jitter using an AI / ML model based on past UL jitter values ​​(UL jitter), and may also be equipped with an AI model inference and / or AI model training function (see FIG. 4) for the prediction function.

[0107] When predicting using an AI / ML model, UL jitter may be predicted for each QoS / QFI (QoS Flow Identifier) ​​and reported to the gNB.

[0108] The gNB may enable the UE to turn on / off the prediction and reporting of UL jitter using the AI / ML model, for example, by an RRC message. Alternatively, the gNB may activate or deactivate the function using the MAC-CE.

[0109] A report of the UL jitter predicted by the AI / ML model may be triggered when the jitter value (jitter amount), or the average value, median value, jitter range, or jitter variance of the jitter value exceeds a threshold. The UE may report the UL jitter based on a reporting periodicity preset by the gNB. Alternatively, the UE may report the UL jitter in response to an explicit instruction from the gNB.

[0110] The UE may attach a timestamp (which may be relative information or absolute time information) that can determine the future time targeted for prediction to the UL jitter report predicted by the AI / ML model. For example, the jitter range may be 10 minutes, 30 minutes, 60 minutes, or 120 minutes.

[0111] In addition, to avoid excessive reporting of the UL jitter predicted by the AI / ML model, the gNB may set a timer (prohibit timer) for the UE. Specifically, when the UE reports the UL jitter predicted by the AI / ML model, the prohibit timer is started, and the next report may be prohibited until the prohibit timer expires.

[0112] Fig. 7 shows an example of a communication sequence related to DL jitter reporting according to operation example 2. As shown in Fig. 7, the SMF may predict future DL jitter using an AI / ML model and report the predicted jitter amount (range) to the gNB.

[0113] The gNB, like the UE, may be equipped with a function for predicting 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 FIG. 4) for the prediction function.

[0114] Note that a network node (network device) such as a UPF or SMF, instead of a gNB, may be equipped with a function to predict DL jitter. In this case, the DL jitter value predicted by the AI / ML model may be reported to the gNB, for example, from the SMF via the AMF. Also, DL jitter may be predicted for each QoS / QFI (QoS Flow Identifier) ​​and reported from the SMF to the gNB via the AMF (similarly, it may be reported from the SMF to the gNB).

[0115] A DL jitter report predicted by the AI / ML model may be triggered when the jitter value (jitter amount), or the mean, median, range, or variance of the jitter value exceeds a threshold. UL jitter may be reported based on a pre-configured reporting periodicity. Alternatively, the SMF may report DL jitter in response to an explicit instruction from the gNB.

[0116] The SMF may attach a timestamp (which may be relative or absolute) that indicates the future time of the predicted DL jitter to the report of DL jitter predicted by the AI / ML model. For example, the timestamp may be a jitter range of 10 minutes, a jitter range of 30 minutes, a jitter range of 60 minutes, or a jitter range of 120 minutes.

[0117] According to this operation example, the UE can report the UL jitter predicted by the AI / ML model, so that the gNB can recognize future UL jitter and realize more efficient and planned UL scheduling. Also, a network device such as the gNB, UPF, or SMF can predict DL jitter by the AI / ML model and report it to other network devices or the UE as needed, so that more efficient and planned DL scheduling can be realized.

[0118] (3.5) Operation Example 3 (3.5.1) Issues In 3GPP TS38.331 (Release-17), information that contributes to mitigating UE overheating (overheatingAssistance) can be reported to the network (specifically, gNB) using UE Assistance Information.

[0119] Specifically, the UE can mitigate UE 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 be configured.

[0120] In addition, 3GPP TS38.331 (Release-17) allows the gNB to report the secondary cell group it wants to deactivate (scg-DeactivationPreference), which can also reduce power consumption.

[0121] If the gNB could know the current or future remaining battery capacity of the UE, it could systematically set the maximum number of CCs, maximum bandwidth, and maximum number of MIMO layers for the UE. The gNB could also determine whether to activate or deactivate the SCG for the UE. However, the gNB cannot know the current or future remaining battery capacity of the UE.

[0122] (3.5.2) Operation Example Fig. 8 shows an example of a communication sequence related to a remaining battery level report according to Operation Example 3. As shown in Fig. 8, the UE can report the current remaining battery level to the network, or predict the future remaining battery level using an AI / ML model and report the predicted remaining battery level to the network.

[0123] The UE may obtain a current remaining battery capacity and report the obtained remaining battery capacity to the gNB. The remaining battery capacity may be expressed, for example, as a percentage (100%, 80%, 60%, 40%, 20%, 5%, etc.).

[0124] The UE may also be equipped with a function for predicting future remaining battery capacity using an AI / ML model, and may also be equipped with an AI model inference and / or AI model training function (see FIG. 4 ) for the prediction function.

[0125] The UE may report the current remaining battery capacity and / or the future remaining battery capacity via an RRC message (e.g., UE Assistance Information).

[0126] The gNB may enable the UE to turn on / off the prediction and reporting of the remaining battery capacity using the AI / ML model, for example, by an RRC message. Alternatively, the gNB may activate or deactivate the function using the MAC-CE.

[0127] 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 preset by the gNB. Alternatively, the UE may report the remaining battery capacity in response to an explicit instruction from the gNB.

[0128] The UE may attach a timestamp (which may be relative information or absolute time information) that can determine the future time targeted for prediction to the report of the remaining battery capacity predicted by the AI / ML model. For example, the time may be "remaining battery in 60 minutes," "remaining in 120 minutes," "remaining battery in 180 minutes," or "remaining in 240 minutes."

[0129] In addition, in order to avoid excessive reporting of the remaining battery capacity predicted by the AI / ML model, the gNB may set a timer (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 activated, and the next report may be prohibited until the prohibit timer expires.

[0130] According to this operation example, the current and future remaining battery power of the UE can be reported to the gNB, so that the gNB can recognize the current and future remaining battery power of the UE and can systematically determine the maximum number of CCs, maximum bandwidth, maximum number of MIMO layers, etc., taking the remaining battery power into consideration. The gNB can also determine activation or deactivation of an SCG for the UE based on the remaining battery power.

[0131] This makes it possible to achieve effective power consumption reduction taking into account the remaining battery capacity of the UE.

[0132] (4) Other Embodiments The contents of the present proposal have been explained above using examples, but it will be obvious to those skilled in the art that the present proposal is not limited to these descriptions and that various modifications and improvements are possible.

[0133] For example, in the above-described embodiment, 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, operation, and computation.

[0134] In the above description, configure, activate, update, indicate, enable, specify, and select may be interchangeable. Similarly, link, associate, correspond, and map may be interchangeable, and allocate, assign, monitor, and map may be interchangeable.

[0135] Furthermore, specific, dedicated, UE-specific, and UE-dedicated may be interchangeable. Similarly, common, shared, group-common, UE-common, and UE-shared may be interchangeable.

[0136] In the present 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," "panel," etc. may be used interchangeably.

[0137] Furthermore, the block diagrams (FIGS. 2 and 3) used in the description of the above-described embodiments show functional blocks. These functional blocks (components) are realized by any combination of hardware and / or software. Furthermore, the method for realizing each functional block is not particularly limited. That is, each functional block may be realized using a single device that is physically or logically coupled, or may be realized using two or more physically or logically separated devices that are directly or indirectly connected (e.g., wired, wireless, etc.) and these multiple devices. The functional block may also be realized by combining software with the single device or multiple devices.

[0138] Functions include, but are not limited to, judgment, determination, judgment, calculation, computation, processing, derivation, investigation, search, confirmation, reception, transmission, output, access, resolution, selection, selection, establishment, comparison, assumption, expectation, consideration, broadcasting, notifying, communicating, forwarding, configuring, reconfiguring, allocating, mapping, and assignment. For example, a functional block (component) that performs transmission is called a transmitting unit or transmitter. As mentioned above, there are no particular limitations on how each is implemented.

[0139] Furthermore, the above-described gNB100 and UE200 (the devices) may function as a computer that performs processing of the wireless communication method of the present disclosure. Figure 9 is a diagram showing an example of the hardware configuration of the devices. As shown in Figure 9, the devices 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, a bus 1007, etc.

[0140] In the following description, the term "apparatus" can be interpreted as a circuit, a device, a unit, etc. The hardware configuration of the apparatus may be configured to include one or more of the apparatuses shown in the drawings, or may be configured to exclude some of the apparatuses.

[0141] Each functional block of the device (see FIGS. 2 and 3) is realized by any hardware element of the computer device or a combination of the hardware elements.

[0142] In addition, each function of the device is realized by loading specified software (programs) onto hardware such as processor 1001 and memory 1002, causing processor 1001 to perform calculations, control communication via communication device 1004, and control at least one of reading and writing data in memory 1002 and storage 1003.

[0143] The processor 1001 controls the entire computer by running, for example, an operating system, and may be configured as a central processing unit (CPU) including an interface with peripheral devices, a control unit, an arithmetic unit, and registers.

[0144] The processor 1001 also reads 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 in accordance with these. The programs used are those that cause a computer to execute at least some of the operations described in the above-described embodiments. Furthermore, the various processes described above may be executed by a single 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.

[0145] The memory 1002 is a computer-readable recording medium and may be configured by at least one of, for example, a read-only memory (ROM), an erasable programmable ROM (EPROM), an electrically erasable programmable ROM (EEPROM), a random access memory (RAM), etc. The memory 1002 may also be called a register, a cache, a main memory (primary storage device), etc. The memory 1002 may store a program (program code), a software module, etc., capable of executing a method according to an embodiment of the present disclosure.

[0146] 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 disc), a smart card, a flash memory (e.g., a card, a stick, a key drive), a floppy 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.

[0147] The communication device 1004 is hardware (transmission / reception 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.

[0148] 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).

[0149] The input device 1005 is an input device (e.g., a keyboard, a mouse, a microphone, a switch, a button, a sensor, etc.) that receives input from the outside. The output device 1006 is an output device (e.g., a display, a speaker, an LED lamp, etc.) that outputs to the outside. Note that the input device 1005 and the output device 1006 may be integrated into one device (e.g., a touch panel).

[0150] Furthermore, each device such as the processor 1001 and the memory 1002 is connected to 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.

[0151] Furthermore, 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. For example, the processor 1001 may be implemented using at least one of these pieces of hardware.

[0152] Furthermore, the notification of information is not limited to the aspects / embodiments described in the present disclosure, and may be performed using other methods. For example, 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 thereof. Furthermore, the 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, or the like.

[0153] Each aspect / embodiment described in the present disclosure may be applied to at least one of a system using Long Term Evolution (LTE), LTE-Advanced (LTE-A), SUPER 3G, IMT-Advanced, a 4th generation mobile communication system (4G), a 5th generation mobile communication system (5G), a 6th generation mobile communication system (6G), an xth generation mobile communication system (xG) (where x is, for example, an integer or a decimal), Future Radio Access (FRA), New Radio (NR), W-CDMA (registered trademark), 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), or other suitable system, and a next-generation system extended based on these. Furthermore, a combination of multiple systems (e.g., a combination of at least one of LTE and LTE-A with 5G) may also be applied.

[0154] The order of the procedures, sequences, flowcharts, etc. of each aspect / embodiment described in this disclosure may be changed unless it is consistent. For example, the methods described in this disclosure present elements of various steps using an example order, and are not limited to the particular order presented.

[0155] In the present disclosure, a specific operation described as being performed by a base station may also be performed by its upper node in some cases. In a network consisting of one or more network nodes having a base station, it is clear that various operations performed for communication with a terminal may be performed by at least one of the base station and another network node other than the base station (e.g., MME or S-GW, etc., but are not limited to these). Although the above example illustrates a case where there is one other network node other than the base station, a combination of multiple other network nodes (e.g., MME and S-GW) may also be used.

[0156] Information, signals (information, etc.) may be output from a higher layer (or a lower layer) to a lower layer (or a higher layer), or may be input and output via multiple network nodes.

[0157] The input and output information may be stored in a specific location (for example, a memory) or may be managed using a management table. The input and output information may be overwritten, updated, or added to. The output information may be deleted. The input information may be transmitted to another device.

[0158] The determination may be made based on a value represented by one bit (0 or 1), a Boolean value (true or false), or a numerical comparison (e.g., comparison with a predetermined value).

[0159] The aspects / embodiments described in this disclosure may be used alone, in combination, or switched depending on the implementation. Notification of predetermined information (e.g., notification that "X is true") is not limited to explicit notification, but may be implicit (e.g., not notifying the predetermined information).

[0160] 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.

[0161] Software, instructions, information, etc. may also be transmitted or received over a transmission medium. For example, if software is transmitted from a website, server, or other remote source using wired technologies (such as coaxial cable, fiber optic cable, twisted pair, Digital Subscriber Line (DSL)), and / or wireless technologies (such as infrared, microwave), then these wired and / or wireless technologies are included within the definition of transmission media.

[0162] The information, signals, etc. described in this disclosure may be represented using any of a variety of different technologies. For example, 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.

[0163] Note that terms described in this disclosure and terms necessary for understanding this disclosure may be replaced with terms having the same or similar meanings. For example, at least one of a channel and a symbol may be a signal (signaling). Furthermore, a signal may be a message. Furthermore, a component carrier (CC) may be called a carrier frequency, a cell, a frequency carrier, etc.

[0164] As used in this disclosure, the terms "system" and "network" are used interchangeably.

[0165] Furthermore, the information, parameters, etc. described in the present disclosure may be expressed using absolute values, may be expressed using relative values ​​from a predetermined value, or may be expressed using other corresponding information. For example, a radio resource may be indicated by an index.

[0166] The names used for the above-described parameters are not intended to be limiting in any way. Furthermore, the mathematical expressions 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 intended to be limiting in any way.

[0167] In this disclosure, terms such as "base station (BS)," "radio base station," "fixed station," "NodeB," "eNodeB (eNB)," "gNodeB (gNB)," "access point," "transmission point," "reception point," "transmission / reception point," "cell," "sector," "cell group," "carrier," and "component carrier" may be used interchangeably. Base stations may also be referred to by terms such as macrocell, small cell, femtocell, and picocell.

[0168] A base station can accommodate one or more (e.g., three) cells (also called sectors). When 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 be provided with communication services by a base station subsystem (e.g., a small indoor base station (Remote Radio Head: RRH)).

[0169] The terms "cell" or "sector" refer to part or all of the coverage area of ​​a base station and / or base station subsystem that provides communication services within that coverage area.

[0170] In the present disclosure, the 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.

[0171] In this disclosure, the terms "Mobile Station (MS)," "user terminal," "User Equipment (UE)," "terminal," etc. may be used interchangeably.

[0172] 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.

[0173] At least one of the base station and the mobile station may be referred to as 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 mobile object, the mobile object itself, etc. The mobile object refers to a movable object, and may move at any speed. Naturally, this also includes cases where the mobile object is stationary. Examples of the mobile object include, but are not limited to, vehicles, transport vehicles, automobiles, motorcycles, bicycles, connected cars, excavators, bulldozers, wheel loaders, dump trucks, forklifts, trains, buses, handcars, rickshaws, ships and other watercraft, airplanes, rockets, satellites, drones (registered trademark), multicopters, quadcopters, balloons, and objects mounted thereon. The mobile object may also be a mobile object that moves autonomously based on an operational command. It may be a vehicle (e.g., a car, an airplane, etc.), an unmanned mobile object (e.g., a drone, an autonomous vehicle, etc.), or a robot (manned or unmanned). At least one of the base station and the mobile station may be a device that does not necessarily move during communication operations. For example, at least one of the base station and the mobile station may be an IoT (Internet of Things) device such as a sensor.

[0174] Furthermore, a base station in the present disclosure may be read as a mobile station (user terminal, the same applies hereinafter). For example, the aspects / embodiments 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) or Vehicle-to-Everything (V2X)). In this case, the mobile station may be configured to have the functions of a base station. Furthermore, terms such as "uplink" and "downlink" may be read as terms corresponding to terminal-to-terminal communication (for example, "side"). For example, terms such as an uplink channel and a downlink channel may be read as a side channel (or sidelink).

[0175] Similarly, a mobile station in the present disclosure may be interpreted as a base station, in which case the base station may have the functions of a mobile station.

[0176] 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.

[0177] Numerology may be communication parameters that apply to the transmission and / or reception of a signal or channel, such as subcarrier spacing (SCS), bandwidth, symbol length, cyclic prefix length, transmission time interval (TTI), number of symbols per TTI, radio frame structure, specific filtering operations performed by the transceiver in the frequency domain, and specific windowing operations performed by the transceiver in the time domain.

[0178] A slot may consist of one or more symbols in the time domain (such as an Orthogonal Frequency Division Multiplexing (OFDM) symbol, a Single Carrier Frequency Division Multiple Access (SC-FDMA) symbol, etc.) A slot may be a numerology-based time unit.

[0179] A slot may include multiple minislots. Each minislot may consist of one or more 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.

[0180] The radio frame, subframe, slot, minislot, and symbol all represent time units for transmitting signals, and may be referred to by other names corresponding to the radio frame, subframe, slot, minislot, and symbol.

[0181] For example, one subframe may be referred to as a transmission time interval (TTI), multiple consecutive subframes may be referred to as a TTI, or one slot or one minislot may be referred to as a TTI. That is, 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.

[0182] 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 to allocate 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.

[0183] 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. When a TTI is given, the time interval (e.g., the number of symbols) to which a transport block, a code block, a code word, etc. is actually mapped may be shorter than the TTI.

[0184] In addition, 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 for scheduling, and the number of slots (minislots) constituting the minimum time unit for scheduling may be controlled.

[0185] A TTI having a time length of 1 ms may be referred to as a regular TTI (TTI in LTE Rel. 8-12), normal TTI, long TTI, regular subframe, normal subframe, long subframe, slot, etc. A TTI shorter than a regular TTI may be referred to as a shortened TTI, short TTI, partial or fractional TTI, shortened subframe, short subframe, minislot, subslot, slot, etc.

[0186] In addition, 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.

[0187] 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.

[0188] The number of subcarriers included in an RB may be the same regardless of the numerology, and may be, for example, 12. The number of subcarriers included in an RB may also be determined based on the numerology.

[0189] The time domain of an RB may include one or more symbols and may have a length of one slot, one minislot, one subframe, or one TTI, each of which may consist of one or more resource blocks.

[0190] Note that one or more RBs may also be called a physical resource block (PRB), a sub-carrier group (SCG), a resource element group (REG), a PRB pair, an RB pair, etc.

[0191] Furthermore, a resource block may be composed of one or more resource elements (REs). For example, one RE may be a radio resource region of one subcarrier and one symbol.

[0192] A Bandwidth Part (BWP) (which may also be referred to as a fractional 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 their index relative to a common reference point of the carrier. PRBs may be defined in a given BWP and numbered within that BWP.

[0193] The BWP may include a BWP for UL (UL BWP) and a BWP for DL ​​(DL BWP). One or more BWPs may be configured for a UE within one carrier.

[0194] 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 the terms "cell," "carrier," etc. in this disclosure may be read as "BWP."

[0195] The above-described structures of the radio frame, subframe, slot, minislot, and symbol 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, the number of symbols in a TTI, the symbol length, the cyclic prefix (CP) length, and other configurations may be changed in various ways.

[0196] The terms "connected," "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 elements may be physical, logical, or a combination thereof. For example, "connected" may be read as "access." As used in this disclosure, two elements may be considered to be "connected" or "coupled" to each other using one or more wires, cables, and / or 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.

[0197] The reference signal may also be abbreviated as Reference Signal (RS) and may be called a pilot depending on the applicable standard.

[0198] 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."

[0199] The "means" in the configuration of each of the above devices may be replaced with "part," "circuit," "device," etc.

[0200] As used in this disclosure, any reference to an element using a designation such as "first," "second," etc. 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 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.

[0201] 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." Furthermore, when the term "or" is used in this disclosure, it is not intended to be an exclusive or.

[0202] In this disclosure, where articles are added by translation, such as a, an, and the in English, the disclosure may include that the nouns following these articles are in the plural form.

[0203] As used in this disclosure, the terms "determining" and "determining" may encompass a wide variety of actions. "Determining" and "determining" may include, for example, judging, calculating, computing, processing, deriving, investigating, looking up, searching, inquiring (e.g., searching in a table, database, or other data structure), ascertaining, 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. Furthermore, "judgment" and "decision" can include regarding resolving, selecting, choosing, establishing, comparing, etc. as having been "judged" or "decided." In other words, "judgment" and "decision" can include regarding some action as having been "judged" or "decided." Furthermore, "judgment (decision)" can be interpreted as "assuming," "expecting," "considering," etc.

[0204] In the present 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 "coupled" may also be interpreted in the same way as "different."

[0205] 10 shows an example of the configuration of a vehicle 2001. As shown in Fig. 10, 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 to 2029, an information service unit 2012, and a communication module 2013.

[0206] The drive unit 2002 is composed of, for example, an engine, a motor, or a hybrid of an engine and a motor.

[0207] 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.

[0208] 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).

[0209] The 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 obtained by a rotation speed sensor 2022, an air pressure signal of the front and rear wheels obtained by an air pressure sensor 2023, a vehicle speed signal obtained by a vehicle speed sensor 2024, an acceleration signal obtained by an acceleration sensor 2025, an accelerator pedal depression amount signal obtained by an accelerator pedal sensor 2029, a brake pedal depression amount signal obtained by a brake pedal sensor 2026, a shift lever operation signal obtained by a shift lever sensor 2027, and a detection signal for detecting obstacles, vehicles, pedestrians, etc. obtained by an object detection sensor 2028.

[0210] 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 types of 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 types of multimedia information and multimedia services to the occupants of the vehicle 1.

[0211] The information service unit 2012 may include input devices (e.g., keyboards, mice, microphones, switches, buttons, sensors, touch panels, etc.) that accept input from the outside, and may also include output devices (e.g., displays, speakers, LED lamps, touch panels, etc.) that output to the outside.

[0212] The driving assistance system unit 2030 is composed of various devices that provide functions for preventing accidents and reducing the driver's driving burden, such as millimeter-wave radar, LiDAR (Light Detection and Ranging), cameras, positioning locators (e.g., GNSS, etc.), map information (e.g., high-definition (HD) maps, autonomous vehicle (AV) maps, etc.), gyro systems (e.g., IMU (Inertial Measurement Unit), INS (Inertial Navigation System), etc.), AI (Artificial Intelligence) chips, and AI processors, 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.

[0213] The communication module 2013 can communicate with the microprocessor 2031 and components of the vehicle 1 via the communication port. For example, the communication module 2013 transmits and receives data via the communication port 2033 to and from a driving 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, a microprocessor 2031 and memory (ROM, RAM) 2032 in the electronic control unit 2010, and sensors 2021 to 2028, which are provided in the vehicle 2001.

[0214] 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, or the like.

[0215] The communication module 2013 may transmit at least one of signals from the above-mentioned various sensors 2021 to 2028 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 to 2028, the information service unit 2012, etc. may be referred to as input units that accept input. For example, the PUSCH transmitted by the communication module 2013 may include information based on the above-mentioned input.

[0216] The communication module 2013 receives various information (traffic information, traffic signal information, vehicle-to-vehicle information, etc.) transmitted from external devices and displays it on an information service unit 2012 provided in the vehicle. The information service unit 2012 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 2013). The communication module 2013 also stores the various information received from external devices in a memory 2032 that can be used by the microprocessor 2031. Based on the information stored in the memory 2032, 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, and the like provided in the vehicle 2001.

[0217] (Additional Note) The above disclosure may be expressed as follows: 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.

[0218] A second feature is that, in the first feature, the control unit predicts at least one of a future state of the uplink data in the buffer and the future transmission delay based on a past state of the uplink data in the buffer and the past transmission delay.

[0219] A third feature based on the first or second feature is that the transmitter transmits the report based on an instruction from the network.

[0220] A fourth feature is, in the second or third feature, 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.

[0221] A fifth feature is any one of the first to fourth features, wherein the transmission unit starts a timer based on an instruction from the network, and transmits the report when the timer expires.

[0222] A sixth feature is a terminal including a control unit that predicts jitter that occurs in uplink data using a learning model, and a transmission unit that transmits a report of the predicted jitter to a network.

[0223] According to a seventh feature based on the sixth feature, the control unit predicts the jitter based on identification information of a quality of service flow.

[0224] According to an eighth feature based on the sixth or seventh feature, the transmitter transmits the report when a value indicating the jitter characteristic exceeds a threshold.

[0225] A ninth feature is the sixth to eighth features, wherein the transmission unit starts a timer based on an instruction from the network, and transmits the report when the timer expires.

[0226] A tenth feature is a terminal including a control unit that determines a remaining capacity of a battery installed therein, and a transmission unit that transmits a report of the determined remaining capacity of the battery to a network.

[0227] An eleventh feature is the tenth feature, wherein the control unit predicts a future remaining amount of the battery using a learning model.

[0228] A twelfth feature based on the tenth or eleventh feature is that the transmitter transmits the report based on an instruction from the network.

[0229] A thirteenth feature, in any one of the tenth to twelfth features, is that the transmitter transmits the report when the remaining charge of the battery falls below a threshold.

[0230] A fourteenth feature according to any one of the tenth to thirteenth features is that the transmission unit starts a timer based on an instruction from the network, and transmits the report when the timer expires.

[0231] 10 Wireless communication system 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 RPM 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

Claims

1. A terminal comprising: a control unit that determines the remaining charge of a battery installed therein; and a transmission unit that transmits a report of the determined remaining charge of the battery to a network.

2. The terminal according to claim 1, wherein the control unit predicts a future remaining capacity of the battery using a learning model, and the transmission unit transmits a report of the predicted remaining capacity of the battery.

3. The terminal according to claim 1, wherein the transmitting unit transmits the report based on an instruction from the network.

4. The terminal according to claim 1, wherein the transmitting unit transmits the report when the remaining charge of the battery falls below a threshold.

5. The terminal according to claim 1, wherein the transmitting unit starts a timer based on an instruction from the network, and transmits the report when the timer expires.

6. A wireless communication method in a terminal, comprising: determining a remaining charge of a battery installed in the terminal; and transmitting a report of the determined remaining charge of the battery to a network.

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