Communication node, wireless communication system, and wireless communication method

Abstract

This communication node comprises: a control unit that executes an operation corresponding to a model that can be used as a model relating to artificial intelligence or machine learning; and a transmission unit that transmits, to another communication node, a message including information indicating a data rate predicted by the model. The data rate is a data rate desirable as a rate of receipt of data from the other communication node, and the message includes information relating to a time of the data rate predicted by the model.

Description

Communication Node, Wireless Communication System, and Wireless Communication Method

[0001] The present disclosure relates to a communication node, a wireless communication system, and a wireless communication method that support AI / ML technology.

[0002] The 3rd Generation Partnership Project (3GPP: registered trademark) is standardizing the 5th generation mobile communication system (also called 5G, New Radio (NR), or Next Generation (NG)). Furthermore, 3GPP is also proceeding with the standardization of the next generation, called Beyond 5G, 5G Evolution, or 6G.

[0003] Furthermore, 3GPP is considering a framework for the Radio Access Network (RAN) realized by AI (Artificial Intelligence) (AI / ML (Artificial Intelligence Machine Learning) technology) (for example, Non-Patent Document 1).

[0004] “New WID on Artificial Intelligence (AI) / Machine Learning (ML) for NR Air Interface”, RP-234039, 3GPP TSG RAN Meeting #102, 3GPP, December 2023

[0005] By the way, in the existing specifications, a communication node such as a base station can notify a desired data rate as the rate of data transmitted from other communication nodes (for example, bit rate or data rate) in order to suppress congestion of the communication node.

[0006] Under such circumstances, as a result of intensive studies, the inventors have found a need to introduce a mechanism for appropriately notifying a desired data rate when assuming AI / ML technology.

[0007] Therefore, this disclosure is made to solve the aforementioned problems and aims to provide a communication node, wireless communication system, and wireless communication method that can appropriately notify a desirable data rate when AI / ML technology is assumed.

[0008] The aspect of the disclosure is a communication node comprising: a control unit that performs operations corresponding to a model available as a model relating to artificial intelligence or machine learning; and a transmission unit that transmits a message to another communication node containing information indicating a data rate predicted by the model, wherein the data rate is a desirable data rate for the rate of data to be received from the other communication node, and the message contains information regarding the time of the data rate predicted by the model.

[0009] The disclosed aspect is a wireless communication system comprising a first communication node and a second communication node, wherein the first communication node comprises a control unit that performs operations corresponding to a model available as a model for artificial intelligence or machine learning, and a transmission unit that transmits a message to the second communication node containing information indicating a data rate predicted by the model, the data rate being a desirable data rate for data received from the second communication node, and the message containing information regarding the time of the data rate predicted by the model.

[0010] The aspect of the disclosure is a wireless communication method comprising: step A performing an operation corresponding to a model available as a model relating to artificial intelligence or machine learning; and step B sending a message to another communication node containing information indicating a data rate predicted by the model, wherein the data rate is a desired data rate for the rate of data to be received from the other communication node, and the message contains information regarding the time of the data rate predicted by the model.

[0011] Figure 1 is an overall schematic diagram of the wireless communication system 10. Figure 2 is a diagram showing the frequency range used in the cellular network. Figure 3 is a diagram showing an example configuration of wireless frames, subframes, and slots used in the cellular network. Figure 4 is a functional block diagram of the UE200. Figure 5 is a functional block diagram of the network device 50. Figure 6 is a diagram for explaining the AI / ML model. Figure 7 is a diagram for explaining operation example 1. Figure 8 is a diagram for explaining operation example 1. Figure 9 is a diagram for explaining operation example 1. Figure 10 is a diagram for explaining operation example 2. Figure 11 is a diagram for explaining operation example 2. Figure 12 is a diagram for explaining operation example 3. Figure 13 is a diagram showing an example of the hardware configuration of the network device 50 and UE200. Figure 14 is a diagram showing an example configuration of the vehicle 2001.

[0012] The embodiments will be described below with reference to the drawings. Note that identical or similar reference numerals are used to denote the same functions and components, and their descriptions will be omitted as appropriate.

[0013] [Embodiment] (1) Overall schematic diagram 1 of the wireless communication system is an overall schematic diagram of the wireless communication system 10 according to the embodiment. The wireless communication system 10 has terminals 200 (hereinafter referred to as UE (User Equipment) 200), a first network 10A and a second network 10B.

[0014] The first network 10A includes a radio access network 20A and a core network 30A. The radio access network 20A includes a base station 100A that performs wireless communication with the UE200. However, the first network 10A may not have the radio access network 20A but may have the base station 100A. The first network 10A may not have the core network 30A. The base station 100A may consist of a DU (Distributed Unit) and a CU (Central Unit). The DU may perform processing at the MAC layer or lower. The CU may perform processing at the PDCP layer or higher.

[0015] The first network 10A may be a network conforming to new technology (6G). 6G may be referred to as Beyond 5G or 5G Evolution. The first network 10A may be a network conforming to existing technology (5G). 5G may be referred to as 5G New Radio (NR).

[0016] The second network 10B includes a radio access network 20B and a core network 30B. The radio access network 20B includes a base station 100B that performs wireless communication with the UE 200. However, the second network 10B may not have the radio access network 20B but may have the base station 100B. The second network 10B may not have the core network 30B. The base station 100B may be composed of a DU and a CU.

[0017] The second network 10B may be a network that conforms to existing technology (5G). 5G may also be called 5G New Radio (NR). The second network 10B may be a network that conforms to new technology (6G). 6G may also be called Beyond 5G or 5G Evolution.

[0018] Here, the first network 10A and the second network 10B may have the same wireless access method or may have different wireless access methods. For example, the wireless access method may be a cellular network wireless access method referred to as 5G, Beyond 5G, 5G Evolution, or 6G.

[0019] Firstly, the cellular network may support multiple frequency ranges (FRs) as shown in Figure 2. For example, as shown in Figure 2, the cellular network may support FR1 and FR2. The frequency bands for each FR are as follows:

[0020] FR1: 410 MHz to 7.125 GHz FR2-1: 24.25 GHz to 52.6 GHz FR2-2: Over 52.6 GHz to 71 GHz In FR1, 15, 30, or 60 kHz Sub-Carrier Spacing (SCS) may be used, and a bandwidth (BW) of 5 to 100 MHz may be used. FR2 is a higher frequency than FR1, and 60 kHz or 120 kHz (240 kHz may be included) SCS may be used, and a bandwidth (BW) of 50 to 400 MHz may be used.

[0021] Furthermore, cellular networks may support higher frequency bands than those used by FR2. Specifically, cellular networks may support frequency bands exceeding 52.6 GHz up to 71 GHz or 114.25 GHz.

[0022] Secondly, the cellular network may correspond to the wireless frames, subframes, and slots shown in Figure 3.

[0023] As shown in Figure 3, one slot consists of 14 symbols, and the larger (wider) the SCS, the shorter the symbol duration (and slot duration). In addition to 15kHz, 30kHz, 60kHz, 120kHz, and 240kHz, 480kHz, 960kHz, etc., may also be used for the SCS.

[0024] Furthermore, the number of symbols constituting one slot does not necessarily have to be 14 (for example, 28 symbols, 56 symbols). In addition, the number of slots per subframe may differ depending on the SCS.

[0025] The time direction (t) shown in Figure 3 may also be called the time domain, symbol period, or symbol time. The frequency direction may also be called the frequency domain, resource block, subcarrier, or bandwidth part (BWP).

[0026] (2) Functional block configuration of the wireless communication system The functional block configuration of the wireless communication system 10 will be described below.

[0027] First, we will describe the functional block configuration of UE200.

[0028] Figure 4 is a functional block diagram of the UE200. As shown in Figure 4, the UE200 comprises a wireless signal transmission / reception unit 210, an amplifier unit 220, a modulation / demodulation unit 230, a control signal / reference signal processing unit 240, an encoding / decoding unit 250, a data transmission / reception unit 260, and a control unit 270.

[0029] The wireless signal transceiver unit 210 transmits and receives wireless signals in accordance with 5G or 6G. The wireless signal transceiver unit 210 supports Massive MIMO, CA using multiple CCs bundled together, and DC which communicates simultaneously between the UE and each of the two NG-RAN Nodes.

[0030] The amplifier section 220 consists of components such as a PA (Power Amplifier) ​​and an LNA (Low Noise Amplifier). The amplifier section 220 amplifies the signal output from the modulation / demodulation section 230 to a predetermined power level. The amplifier section 220 also amplifies the RF signal output from the wireless signal transmission / reception section 210.

[0031] The modulation / demodulation unit 230 performs data modulation / demodulation, transmit power setting, and resource block allocation for each predetermined communication destination (gNB100 or other gNB). The modulation / demodulation unit 230 may apply Cyclic Prefix-Orthogonal Frequency Division Multiplexing (CP-OFDM) / Discrete Fourier Transform - Spread (DFT-S-OFDM). Furthermore, DFT-S-OFDM may be used not only for the uplink (UL) but also for the downlink (DL).

[0032] The control signal / reference signal processing unit 240 performs processing related to various control signals transmitted and received by the UE200, and processing related to various reference signals transmitted and received by the UE200.

[0033] Specifically, the control signal / reference signal processing unit 240 receives various control signals transmitted from the gNB100 via a predetermined control channel, such as control signals for the radio resource control layer (RRC). The control signal / reference signal processing unit 240 also transmits various control signals to the gNB100 via a predetermined control channel.

[0034] The control signal / reference signal processing unit 240 performs processing using reference signals (RS) such as the Demodulation Reference Signal (DM-RS) and the Phase Tracking Reference Signal (PT-RS).

[0035] DM-RS is a terminal-specific reference signal (pilot signal) between the base station and the terminal used to estimate the fading channel used for data demodulation. PT-RS is a terminal-specific reference signal intended to estimate phase noise, which is a problem in the high-frequency band.

[0036] In addition to DM-RS and PT-RS, the reference signals may also include Channel State Information-Reference Signal (CSI-RS), Sounding Reference Signal (SRS), and Positioning Reference Signal (PRS) for location information.

[0037] Furthermore, channels include control channels and data channels. Control channels include PDCCH (Physical Downlink Control Channel), PUCCH (Physical Uplink Control Channel), RACH (Random Access Channel), Downlink Control Information (DCI) including Random Access Radio Network Temporary Identifier (RA-RNTI), and Physical Broadcast Channel (PBCH), among others.

[0038] Furthermore, data channels include PDSCH (Physical Downlink Shared Channel) and PUSCH (Physical Uplink Shared Channel), among others. "Data" refers to data transmitted through a data channel. A data channel may also be interpreted as a shared channel.

[0039] Here, the control signal / reference signal processing unit 240 may receive downlink control information (DCI). The DCI includes fields that store existing fields such as DCI Formats, Carrier indicator (CI), BWP indicator, FDRA (Frequency Domain Resource Assignment), TDRA (Time Domain Resource Assignment), MCS (Modulation and Coding Scheme), HPN (HARQ Process Number), NDI (New Data Indicator), and RV (Redundancy Version).

[0040] The value stored in the DCI Format field is an information element that specifies the DCI format. The value stored in the CI field is an information element that specifies the CC to which the DCI applies. The value stored in the BWP indicator field is an information element that specifies the BWP to which the DCI applies. The BWP that can be specified by the BWP indicator is set by an information element (BandwidthPart-Config) included in the RRC message. The value stored in the FDRA field is an information element that specifies the frequency domain resource to which the DCI applies. The frequency domain resource is identified by the value stored in the FDRA field and an information element (RA Type) included in the RRC message. The value stored in the TDRA field is an information element that specifies the time domain resource to which the DCI applies. The time domain resource is identified by the value stored in the TDRA field and an information element (pdsch-TimeDomainAllocationList, push-TimeDomainAllocationList) included in the RRC message. The time domain resource may also be identified by the value stored in the TDRA field and the default table. The value stored in the MCS field is an information element that specifies the MCS to which the DCI applies. The MCS is identified by the value stored in MCS and the MCS table. The MCS table may be specified by the RRC message or identified by RNTI scrambling. The value stored in the HPN field is an information element that specifies the HARQ Process to which DCI is applied. The value stored in NDI is an information element that determines whether the data to which DCI is applied is initial transmission data. The value stored in the RV field is an information element that specifies the redundancy of the data to which DCI is applied.

[0041] The encoding / decoding unit 250 performs data splitting / concatenation and channel coding / decoding for each predetermined communication destination (gNB100 or other gNB).

[0042] Specifically, the encoding / decoding unit 250 divides the data output from the data transmission / reception unit 260 into a predetermined size and performs channel coding on the divided data. Also, the encoding / decoding unit 250 decodes the data output from the modulation / demodulation unit 230 and concatenates the decoded data.

[0043] The data transmission / reception unit 260 performs the transmission and reception of Protocol Data Unit (PDU) and Service Data Unit (SDU). Specifically, the data transmission / reception unit 260 performs operations such as the assembly / disassembly of PDU / SDU in a plurality of layers (such as the Medium Access Control layer (MAC), the Radio Link Control layer (RLC), and the Packet Data Convergence Protocol layer (PDCP)). Also, the data transmission / reception unit 260 performs error correction and retransmission control of data based on Hybrid Automatic Repeat Request (HARQ).

[0044] The control unit 270 controls each functional block constituting the UE 200. In an embodiment, the control unit 270 may constitute a control unit that executes operations corresponding to a model (hereinafter, AI / ML model) that can be used as an artificial intelligence or machine learning model. For example, the control unit 270 may predict a desired data rate as the rate of data received from another communication node (for example, the base station 100A or the base station 100B) using the AI / ML model. The predicted data rate may be referred to as the AI / ML predicted recommended Bit Rate or the AI / ML predicted desired data rate.

[0045] Although not particularly limited, the control unit 270 predicts the congestion status of the UE 200 by inputting, to the AI / ML model, the number of channels or bearers established by the UE 200, the number of services used by the UE 200, the type of services used by the UE 200, etc., and may predict the data rate based on the predicted congestion status of the network device 50.

[0046] In an embodiment, the wireless signal transceiver 210 may constitute a transmitter that transmits a message including information indicating a data rate predicted by an AI / ML model. The wireless signal transceiver 210 may constitute a receiver that receives an inquiry about a data rate predicted by an AI / ML model.

[0047] Second, the functional block configuration of the network device 50 will be described. For example, the network device 50 is provided in the first network 10A or the second network 10B. That is, the network device 50 may be the base station 100A, may be a CU constituting a part of the base station 100A, or may be a DU constituting a part of the base station 100A. The network device 50 may be the base station 100B, may be a CU constituting a part of the base station 100B, or may be a DU constituting a part of the base station 100B. The network device 50 may be a device provided in the core network 30A (e.g., UPF; User Plane Function), or may be a device provided in the core network 30B (e.g., UPF).

[0048] As shown in FIG. 5, the network device 50 includes a receiver 51, a transmitter 52, and a controller 53.

[0049] The receiver 51 receives various signals from the UE 200. The receiver 51 may receive a control signal (PUCCH) or may receive a data signal (PUSCH). The receiver 51 may receive information from other network devices.

[0050] The transmitter 52 transmits various signals to the UE 200. The transmitter 52 may transmit a control signal (PDCCH) or may transmit a data signal (PDSCH). The transmitter 52 may transmit information to other network devices.

[0051] The control unit 53 controls each block that constitutes the network device 50. The control unit 53 may be configured to assume that the UE200 performs operations corresponding to a model available as an artificial intelligence or machine learning model (AI / ML model). For example, the control unit 53 may use an AI / ML model to predict a desired data rate as the rate of data to be received from other communication nodes (e.g., the UE200 or CN). The predicted data rate may be referred to as the AI / ML predicted bit rate or the AI / ML predicted data rate.

[0052] While not particularly limited, the control unit 53 may predict the congestion status of the network device 50 by inputting the number of UE200s under the network device 50, the number of channels or bearers established by the UE200s under the network device 50, the number of services used by the UE200s under the network device 50, and the types of services used by the UE200s under the network device 50 into an AI / ML model, and then predict the data rate based on the predicted congestion status of the network device 50.

[0053] In this embodiment, the transmitting unit 52 may be configured to transmit a message containing information indicating the data rate predicted by the AI / ML model. The receiving unit 51 may be configured to receive an inquiry about the data rate predicted by the AI / ML model.

[0054] (3) AI / ML Model The AI / ML model will be described below. The AI / ML model may be used for various functions (AI / ML functionality). AI / ML functionality may include one or more functionalities selected from AIML for beam management, AIML for CSI prediction, AIML for CSI compression, AIML for positioning, and AIML for mobility.

[0055] As shown in Figure 6, the AI / ML model may include functions such as data collection, model training, model interface, model management / performance monitoring, and model storage.

[0056] Data collection collects input data for models used to measure (predict) predictive information. Data collection outputs input data (Training Data) to Model training. Data collection outputs input data (Monitoring Data) to Model Management / Performance monitoring. Data collection outputs input data (Interface Data) to Model Interface.

[0057] Model training involves training, validating, and testing models used to measure (predict) predictive information based on training data. Model training may also perform preprocessing such as cleaning, formatting, and transforming the training data. Model training then outputs the trained or updated model to model storage.

[0058] The Model Interface uses a model retrieved from Model Storage to output predictive information (Output) corresponding to the input data (Interface Data). The Model Interface may also output the predictive information (Output) as feedback to Model Management / Performance Monitoring.

[0059] Model Management / Performance monitoring outputs information used to identify the model used in the Model Interface (Model Interface Control) to the Model Interface. Identification may also be referred to as Activate, Deactivate, select, switch, fallback, etc. Based on the input data (Monitoring Data) and prediction information (Output), Model Management / Performance monitoring outputs information used for retraining or updating the model (Model training control) to Model training.

[0060] Model storage stores the models output from Model training. Model storage outputs the stored models to the Model Interface. The output of the models may also be referred to as Model deliver / transfer.

[0061] (4) Problem: In the existing specifications, communication nodes such as base stations can notify other communication nodes of a desired data rate (e.g., bit rate or data rate) in order to suppress congestion at other communication nodes.

[0062] The technical challenges addressed in this disclosure are not limited to those mentioned above, and other technical challenges not mentioned here will be clearly understood by a person with ordinary skill in the art to which this disclosure pertains, based on the description herein.

[0063] Against this backdrop, the inventors, after diligent consideration, found a need to introduce a mechanism to appropriately notify the desired data rate when AI / ML technology is assumed.

[0064] (5) Example of Operation In order to solve the above-mentioned problems, the following operation may be performed. Specifically, the communication node sends a message to other communication nodes that contains information indicating the data rate predicted by the AI / ML model. The data rate is the desired data rate for the data to be received from other communication nodes. The message contains information about the time of the data rate predicted by the AI / ML model (hereinafter referred to as time info).

[0065] In this case, where the data rate for time B is predicted at time A, the following options are possible for the time info.

[0066] In option A, time info may include the time stamp of time A, which is the time when the data rate forecast was performed.

[0067] In option B, time info may include the time stamp of time B, which is the time for which the data rate is to be predicted.

[0068] In option C, time info may include information indicating the difference between time B and time A (e.g., 1000 msec).

[0069] Option D may be a combination of two or more options selected from Options A through C.

[0070] The following are examples of possible operations.

[0071] (5.1) Operation Example 1 Operation Example 1 describes the data (UL data) received from the UE when the gNB performs an operation corresponding to the AI / ML model. In Operation Example 1, the gNB is an example of a communication node (or first communication node), and the UE is an example of another communication node (or second communication node). The following options are possible for Operation Example 1.

[0072] In Option 1-1, as shown in Figure 7, in step S10, the gNB transmits the AI / ML predicted recommended bit rate to the UE. The AI / ML predicted recommended bit rate includes information indicating the data rate predicted by the AI / ML model (AI / ML predicted bit rate) and the time info described above.

[0073] In Option 1-1, the AI / ML predicted bit rate may be the data rate per logical channel, per radio bearer, or per quality of service flow. Therefore, the AI / ML predicted recommended bit rate may include information that identifies the subject of the AI / ML predicted bit rate (logical channel ID, radio bearer ID, or QoS flow ID).

[0074] In option 1-2, as shown in Figure 8, in step S20, the UE sends an AI / ML predicted recommended bit rate query to the gNB. In step S21, the gNB sends the AI / ML predicted recommended bit rate to the UE. That is, in response to the AI / ML predicted bit rate query, the gNB sends the AI / ML predicted recommended bit rate to the UE.

[0075] In Option 1-2, the AI / ML predicted bit rate may be the data rate per logical channel, per radio bearer, or per quality of service flow. Therefore, the AI / ML predicted recommended bit rate may include information that identifies the subject of the AI / ML predicted bit rate (logical channel ID, radio bearer ID, or QoS flow ID). The AI / ML predicted recommended bit rate query may be a query for the AI / ML predicted bit rate per logical channel, per radio bearer, or per quality of service flow.

[0076] In option 1-2, the UE may refrain from sending the next AI / ML predicted recommended bit rate query until the timer triggered by the transmission of the AI / ML predicted recommended bit rate query expires. The timer may be referred to as the bitRateQueryProhibitTimer. In other words, the gNB may not expect to receive the next AI / ML predicted recommended bit rate query until the bitRateQueryProhibitTimer expires, and may expect to receive the next AI / ML predicted recommended bit rate query after the bitRateQueryProhibitTimer has expired.

[0077] In Operation Example 1, the AI / ML predicted recommended bit rate may be MAC CE. As shown in Figure 9, MAC CE includes information indicating the data rate predicted by the AI / ML model (AI / ML predicted bit rate) and the time info described above.

[0078] Here, the AI / ML predicted bit rate may be the data rate per logical channel, per radio bearer, or per quality of service flow. Therefore, the MAC CE may include information that identifies the subject of the AI / ML predicted bit rate (logical channel ID, radio bearer ID, or QoS flow ID).

[0079] Here, the AI / ML predicted recommended bit rate may have a configuration similar to the Recommended bit rate MAC CE of the existing specification (e.g., 3GPP TS38.321 §6.1.3.20 “Recommended bit rate MAC CE”). In such cases, the time info may be represented by the reserve bit of the existing specification. The AI / ML predicted bit rate may be replaced by the Bit Rate of the existing specification. The logical channel ID, radio bearer ID, or QoS flow ID may be replaced by the LCID of the existing specification.

[0080] In Operation Example 1, the AI / ML predicted recommended bit rate may be included in the RRC message.

[0081] (5.2) Operation Example 2 Operation Example 2 describes the case in which gNB is composed of DU and CU. Specifically, it describes the data (DL data) received from CU in the case in which DU performs operations corresponding to an AI / ML model. In Operation Example 2, DU is an example of a communication node (or first communication node), and CU is an example of another communication node (or second communication node).

[0082] As shown in Figure 10, in step S30, the DU transmits the AI / ML predicted desired bit rate to the CU. The AI / ML predicted desired bit rate includes information indicating the data rate predicted by the AI / ML model (AI / ML predicted data rate) and the time info mentioned above.

[0083] In Operation Example 2, the AI / ML predicted data rate may be the data rate per logical channel, per radio bearer, or per quality of service flow. Therefore, the AI / ML predicted desired bit rate may include information that identifies the target of the AI / ML predicted bit rate (logical channel ID, radio bearer ID, or QoS flow ID).

[0084] In Operation Example 2, the AI / ML predicted desired bit rate may be the DL DATA DELIVERY STATUS. As shown in Figure 11, the DL DATA DELIVERY STATUS includes information indicating the data rate predicted by the AI / ML model (AI / ML predicted data rate) and the time info mentioned above. Furthermore, the DL DATA DELIVERY STATUS may include an indication that the DL DATA DELIVERY STATUS includes the AI / ML predicted data rate (AI / ML predicted data rate indication).

[0085] (5.3) Operation Example 3 Operation Example 3 describes the data (DL data) received from the CN (e.g., UPF) when the gNB performs an operation corresponding to the AI / ML model. In Operation Example 3, the gNB is an example of a communication node (or first communication node), and the CN (e.g., UPF) is an example of another communication node (or second communication node).

[0086] As shown in Figure 12, in step S40, the gNB transmits the AI / ML predicted desired bit rate to the CN. The AI / ML predicted desired bit rate includes information indicating the data rate predicted by the AI / ML model (AI / ML predicted data rate) and the time info mentioned above.

[0087] In Operation Example 3, the AI / ML predicted data rate may be the data rate per logical channel, per radio bearer, or per quality of service flow. Therefore, the AI / ML predicted desired bit rate may include information that identifies the target of the AI / ML predicted bit rate (logical channel ID, radio bearer ID, or QoS flow ID).

[0088] (5.4) Operation Example 4 Operation Example 4 describes the data (DL data) received from a gNB or CN (e.g., UPF) when the UE performs an operation corresponding to the AI / ML model. In Operation Example 3, the UE is an example of a communication node (or first communication node), and the gNB or CN (e.g., UPF) is an example of another communication node (or second communication node).

[0089] In Operation Example 4, in the case described in Operation Example 3, simply replace gNB with UE and CN with either gNB or CN.

[0090] In other words, the UE transmits the AI / ML predicted desired bit rate to the gNB or CN. The AI / ML predicted desired bit rate includes information indicating the data rate predicted by the AI / ML model (AI / ML predicted data rate) and the time info mentioned above.

[0091] In Operation Example 4, the AI / ML predicted data rate may be the data rate per logical channel, per radio bearer, or per quality of service flow. Therefore, the AI / ML predicted desired bit rate may include information that identifies the target of the AI / ML predicted bit rate (logical channel ID, radio bearer ID, or QoS flow ID).

[0092] (5.5) Operation Example 5 Operation Example 5 describes the data (UL data) received from the UE or gNB when the CN (e.g., UPF) performs an operation corresponding to the AI / ML model. In Operation Example 5, the CN (e.g., UPF) is an example of a communication node (or first communication node), and the UE or gNB is an example of another communication node (or second communication node).

[0093] In Operation Example 5, in the case described in Operation Example 1, simply replace gNB with CN and UE with either UE or gNB.

[0094] In other words, the CN transmits the AI / ML predicted recommended bit rate to the UE or gNB. The AI / ML predicted recommended bit rate includes information indicating the data rate predicted by the AI / ML model (AI / ML predicted bit rate) and the time info mentioned above.

[0095] In Operation Example 5, the AI / ML predicted bit rate may be the data rate per logical channel, per radio bearer, or per quality of service flow. Therefore, the AI / ML predicted recommended bit rate may include information that identifies the target of the AI / ML predicted bit rate (logical channel ID, radio bearer ID, or QoS flow ID).

[0096] (5.6) In the other example of operation 2 described above, the CU may send an AI / ML predicted bit rate query to the DU, and the DU may send the AI / ML predicted bit rate in response to the query. In such a case, the DU may, as in the example of operation 1, refrain from sending the next AI / ML predicted bit rate query until the timer that is activated in response to the sending of the AI / ML predicted bit rate query expires.

[0097] In the above-described example 3, the CN may send an AI / ML predicted bit rate query to the gNB, and the gNB may send the AI / ML predicted bit rate in response to the query. In such a case, the gNB may, as in example 1, refrain from sending the next AI / ML predicted bit rate query until the timer that is activated in response to the sending of the AI / ML predicted bit rate query expires.

[0098] In the above-described example 4, the gNB or CN may send an AI / ML predicted bit rate query to the UE, and the UE may send the AI / ML predicted bit rate in response to the query. In such a case, the UE may, as in example 1, refrain from sending the next AI / ML predicted bit rate query until the timer that is activated in response to the sending of the AI / ML predicted bit rate query expires.

[0099] In the above-described example 5, the UE or gNB may send an AI / ML predicted bit rate query to the CN, and the UE or gNB may send the AI / ML predicted bit rate in response to the query. In such a case, the UE or gNB may, as in example 1, refrain from sending the next AI / ML predicted bit rate query until the timer that is activated in response to the transmission of the AI / ML predicted bit rate query expires.

[0100] The above-described operation example 4 may be combined with operation example 3. That is, the AI / ML predicted bit rate may be sent from the UE to the gNB, and then from the gNB to the CN.

[0101] The above-described example 5 may be combined with example 1. That is, the AI / ML predicted bit rate may be sent from CN to gNB, and then from gNB to UE.

[0102] (6) Operation and Effects In the embodiment, a communication node sends a message to other communication nodes that includes information indicating the data rate predicted by the AI / ML model, and the message includes information about the time of the predicted data rate (hereinafter referred to as time info). With such a configuration, the desired data rate can be appropriately notified when AI / ML technology is assumed.

[0103] In this embodiment, the communication node may not anticipate receiving the next AI / ML predicted bit rate query until the timer triggered by the AI / ML predicted bit rate query expires, and may only anticipate receiving the next AI / ML predicted bit rate query after the timer has expired. With such a configuration, the frequency of AI / ML predicted bit rate queries can be suppressed, and traffic between the communication node and other communication nodes can be reduced.

[0104] (7) Other Embodiments Although the contents of the present invention have been described above in accordance with the embodiments, it will be obvious to those skilled in the art that the present invention is not limited to these descriptions and that various modifications and improvements are possible.

[0105] Although not specifically mentioned in the disclosure above, the choice of which of Operation Examples 1 to 5 to use (which mode to use) may be set by a higher-layer parameter. The choice of which of each option in Operation Examples 1 to 5 to use may be set by a higher-layer parameter. Which mode to support may be reported by UE200 as UE capability(ies). Which mode to use may be predefined in the wireless communication system 10. Which mode to use may be set by a higher-layer parameter and reported by UE200 as UE capability(ies).

[0106] Although not specifically mentioned in the disclosure above, the following UE capability(ies) may be defined. UE capability(ies) may be defined for each A-IoT device, for each FR (e.g., FR1, FR2, FR2-1, FR2-2, FR3), for each SCS, for each band, for each BC (Bandwidth Combination), or for each FC (Frequency Combination). UE capability(ies) may be included in the signals reported from UE200 to gNB100, or in the signals set from gNB100 to UE200.

[0107] The block diagrams (Figures 4 and 5) used in the description of the embodiments above show functional units. These functional blocks (components) are realized by any combination of at least one of hardware and software. Furthermore, the method of realizing each functional block is not particularly limited. That is, each functional block may be realized using one device that is physically or logically coupled, or it may be realized using two or more physically or logically separated devices that are directly or indirectly connected (for example, using wired or wireless connections). A functional block may also be realized by combining the above one device or the above multiple devices with software.

[0108] Functions include, but are not limited to, judgment, decision, determination, calculation, calculation, processing, derivation, investigation, exploration, confirmation, reception, transmission, output, access, resolution, selection, selection, establishment, comparison, assumption, expectation, assumption, broadcasting, notifying, communicating, forwarding, configuring, reconfiguring, allocating (mapping), and assigning. For example, a functional block (configuration part) that enables transmission is called a transmitting unit or transmitter. In any case, as mentioned above, the method of implementation is not particularly limited.

[0109] Furthermore, the network device 50 and UE200 (the device) described above may function as a computer that processes the wireless communication method of this disclosure. Figure 13 shows an example of the hardware configuration of the device. As shown in Figure 13, the device may be configured as a computer device including a processor 1001, memory 1002, storage 1003, communication device 1004, input device 1005, output device 1006, and bus 1007.

[0110] In the following explanation, the term "device" can be replaced with "circuit," "device," "unit," etc. The hardware configuration of the device may include one or more of the devices shown in the diagram, or it may be configured to omit some of the devices.

[0111] Each functional block of the device (see Figures 4 and 5) is implemented by any hardware element of the computer device, or a combination of such hardware elements.

[0112] Furthermore, each function in the device is realized by loading predetermined software (programs) onto hardware such as the processor 1001 and memory 1002, which allows the processor 1001 to perform calculations, control communication by the communication device 1004, and control at least one of the reading and writing of data in the memory 1002 and storage 1003.

[0113] The processor 1001 controls the entire computer, for example, by running an operating system. The processor 1001 may consist of a central processing unit (CPU) that includes interfaces with peripheral devices, control units, arithmetic units, registers, and so on.

[0114] Furthermore, the processor 1001 reads programs (program code), 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 accordingly. The program used is one that causes the computer to execute at least a part of the operations described in the above embodiment. Moreover, the above-mentioned various processes may be executed by one processor 1001, or by two or more processors 1001 simultaneously or sequentially. The processor 1001 may be implemented by one or more chips. The program may also be transmitted from a network via a telecommunications line.

[0115] Memory 1002 is a computer-readable recording medium and may consist of at least one of the following: 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., that can execute a method according to one embodiment of this disclosure.

[0116] Storage 1003 is a computer-readable recording medium and may consist of at least one of the following: an optical disc such as a Compact Disc ROM (CD-ROM), a hard disk drive, a flexible disk, a magneto-optical disk (e.g., Compact Disc, Digital Multipurpose Disc, Blu-ray® Disc), a smart card, flash memory (e.g., a card, stick, key drive), a floppy® disk, a magnetic strip, etc. Storage 1003 may also be called an auxiliary storage device. The recording medium described above may also be, for example, a database, server, or other suitable medium including at least one of memory 1002 and storage 1003.

[0117] The communication device 1004 is hardware (transceiver / receiver device) for communicating between computers via at least one of a wired network and a wireless network, and is also referred to as a network device, network controller, network card, communication module, etc.

[0118] The communication device 1004 may be configured to include, for example, a high-frequency switch, a duplexer, a filter, a frequency synthesizer, etc., in order to implement at least one of frequency division duplex (FDD) and time division duplex (TDD).

[0119] The input device 1005 is an input device that accepts input from an external source (e.g., a keyboard, mouse, microphone, switch, button, sensor, etc.). The output device 1006 is an output device that outputs to an external source (e.g., a display, speaker, LED lamp, etc.). The input device 1005 and the output device 1006 may be configured as an integrated unit (e.g., a touch panel).

[0120] Furthermore, 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 different buses may be configured for each device.

[0121] Furthermore, the device may include hardware such as a microprocessor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a programmable logic device (PLD), and a field programmable gate array (FPGA), and some or all of the functional blocks may be implemented by such hardware. For example, processor 1001 may be implemented using at least one of these hardware components.

[0122] Furthermore, notification of information is not limited to the embodiments / models described herein and may be carried out by other means. For example, notification of information may be carried out by physical layer signaling (e.g., Downlink Control Information (DCI), Uplink Control Information (UCI)), upper layer signaling (e.g., RRC signaling, Medium Access Control (MAC) signaling, broadcast information (Master Information Block (MIB), System Information Block (SIB))), other signals, or combinations thereof. RRC signaling may also be called RRC messages, and may be, for example, RRC Connection Setup messages, RRC Connection Reconfiguration messages, etc.

[0123] Each aspect / embodiment described herein may be applied to at least one of the following: Long Term Evolution (LTE), LTE-Advanced (LTE-A), SUPER 3G, IMT-Advanced, 4th generation mobile communication system (4G), 5th generation mobile communication system (5G), Future Radio Access (FRA), New Radio (NR), W-CDMA®, GSM®, CDMA2000, Ultra Mobile Broadband (UMB), IEEE 802.11 (Wi-Fi®), IEEE 802.16 (WiMAX®), IEEE 802.20, Ultra-WideBand (UWB), Bluetooth®, and other appropriate systems, as well as next-generation systems extended based thereon. Furthermore, multiple systems may be applied in combination (for example, a combination of at least one of LTE and LTE-A with 5G).

[0124] The processing procedures, sequences, flowcharts, etc., of each aspect / embodiment described in this disclosure may be reordered, provided they do not contradict each other. For example, the methods described in this disclosure present various step elements using exemplary order and are not limited to the specific order presented.

[0125] The specific operations described in this disclosure as being performed by a base station may, in some cases, be performed by its upper node. 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 can be performed by the base station and at least one other network node (for example, an MME or S-GW, but not limited to these). Although the above example illustrates the case where there is one other network node besides the base station, it may also be a combination of multiple other network nodes (for example, an MME and an S-GW).

[0126] Information and signals (such as data) can be output from a higher layer (or lower layer) to a lower layer (or higher layer). Input and output may occur via multiple network nodes.

[0127] The input and output information may be stored in a specific location (e.g., memory) or managed using a management table. The input and output information may be overwritten, updated, or appended to. Output information may be deleted. Input information may be transmitted to other devices.

[0128] The determination may be made by a value represented by one bit (0 or 1), by a boolean value (true or false), or by a numerical comparison (for example, a comparison with a predetermined value).

[0129] Each aspect / embodiment described in this disclosure may be used individually, in combination, or switched between as needed during implementation. Furthermore, notification of specific information (e.g., notification that "X is") is not limited to explicit notification, but may also be implicit (e.g., by not providing such notification).

[0130] Software should be broadly interpreted to mean instructions, instruction sets, code, code segments, program code, programs, subprograms, software modules, applications, software applications, software packages, routines, subroutines, objects, executable files, execution threads, procedures, functions, and so on, whether they are called software, firmware, middleware, microcode, hardware description languages, or by any other name.

[0131] Furthermore, software, instructions, information, etc., may be transmitted and received via a transmission medium. For example, if software is transmitted from a website, server, or other remote source using at least one of wired technology (such as coaxial cable, fiber optic cable, twisted pair, or Digital Subscriber Line (DSL)) and wireless technology (such as infrared or microwave), then at least one of these wired and wireless technologies is included in the definition of a transmission medium.

[0132] The information, signals, etc. described in this disclosure may be represented using any of the various different technologies. For example, the data, instructions, commands, information, signals, bits, symbols, chips, etc. that may be referred to throughout the above description may be represented by voltage, current, electromagnetic waves, magnetic fields or magnetic particles, optical fields or photons, or any combination thereof.

[0133] In addition, terms used 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 the channel and symbol may be a signal (signaling). Also, a signal may be a message. Furthermore, a component carrier (CC) may be called a carrier frequency, cell, frequency carrier, etc.

[0134] The terms “system” and “network” as used in this disclosure are interchangeable.

[0135] Furthermore, the information, parameters, etc., described in this disclosure may be expressed using absolute values, relative values ​​from a given value, or other corresponding information. For example, wireless resources may be indicated by an index.

[0136] The names used for the parameters described above are not restrictive in any way. Furthermore, the formulas and other expressions using these parameters may differ from those expressly disclosed in this disclosure. Since various channels (e.g., PUCCH, PDCCH, etc.) and information elements can be identified by any suitable name, the various names assigned to these various channels and information elements are not restrictive in any way.

[0137] In this disclosure, terms such as "Base Station (BS)," "wireless 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.

[0138] A base station can house one or more (e.g., three) cells (also called sectors). When a base station houses multiple cells, the entire coverage area of ​​the base station can be divided into multiple smaller areas, each of which can also be provided with communication services by a base station subsystem (e.g., a small indoor base station (Remote Radio Head: RRH)).

[0139] The terms "cell" or "sector" refer to a portion or all of the coverage area of ​​at least one of the base stations and base station subsystems that provide communication services in this coverage.

[0140] In this disclosure, terms such as "Mobile Station (MS)," "user terminal," "User Equipment (UE)," and "terminal" may be used interchangeably.

[0141] 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 several other appropriate terms.

[0142] 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 mobile body, the mobile body itself, etc. The mobile body may be a vehicle (e.g., a car, an airplane, etc.), an unmanned mobile body (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 operation. For example, at least one of the base station and the mobile station may be an Internet of Things (IoT) device such as a sensor.

[0143] Furthermore, the term "base station" in this disclosure may be interpreted as "mobile station" (user terminal, hereinafter the same). For example, the various aspects / embodiments of this 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.). In this case, the mobile station may have the functions that a base station has. Also, terms such as "uplink" and "downlink" may be interpreted as terms corresponding to terminal-to-terminal communication (for example, "side"). For example, uplink channel, downlink channel, etc. may be interpreted as side channel.

[0144] Similarly, the term "mobile station" in this disclosure may be interpreted as "base station." In this case, the base station may be configured to have the functions that a mobile station has.

[0145] A wireless frame may consist of one or more frames in the time domain. Each of these frames in the time domain may be called a subframe.

[0146] A subframe may further consist 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.

[0147] Numerology may be communication parameters applied to at least one of the transmission and reception of a signal or channel. Numerology may include, for example, at least one of the following: subcarrier spacing (SCS), bandwidth, symbol length, cyclic prefix length, transmission time interval (TTI), number of symbols per TTI, radio frame configuration, specific filtering processes performed by the transceiver in the frequency domain, and specific windowing processes performed by the transceiver in the time domain.

[0148] A slot may consist of one or more symbols in the time domain (such as Orthogonal Frequency Division Multiplexing (OFDM) symbols or Single Carrier Frequency Division Multiple Access (SC-FDMA) symbols). A slot may also be a time unit based on neurology.

[0149] A slot may include multiple mini-slots. Each mini-slot may consist of one or more symbols in the time domain. Mini-slots may also be called sub-slots. Mini-slots may consist of fewer symbols than a slot. A PDSCH (or PUSCH) transmitted in a time unit larger than a mini-slot may be called a PDSCH (or PUSCH) mapping type A. A PDSCH (or PUSCH) transmitted using a mini-slot may be called a PDSCH (or PUSCH) mapping type B.

[0150] Wireless frames, subframes, slots, minislots, and symbols all represent units of time when transmitting a signal. Different names may be used for each of these terms.

[0151] For example, one subframe may be called a transmission time interval (TTI), multiple consecutive subframes may be called a TTI, or one slot or one minislot may be called a TTI. In other words, at least one of a subframe and a 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.

[0152] Here, TTI refers to, for example, the smallest unit of time for scheduling in wireless communication. For example, in an LTE system, the base station schedules each user terminal to allocate wireless resources (such as the frequency bandwidth and transmission power available to each user terminal) in TTI units. However, the definition of TTI is not limited to this.

[0153] TTI may be a transmission time unit for channel-encoded data packets (transport blocks), code blocks, code words, etc., or it may be a processing unit for scheduling, link adaptation, etc. Note that when a TTI is given, the actual time interval (e.g., number of symbols) in which the transport block, code block, code word, etc. are mapped may be shorter than the given TTI.

[0154] Furthermore, if one slot or one mini-slot is referred to as TTI, then one or more TTIs (i.e., one or more slots or one or more mini-slots) may constitute the minimum time unit of scheduling. In addition, the number of slots (number of mini-slots) that constitute the minimum time unit of scheduling may be controlled.

[0155] A TTI with a time length of 1ms may also be called a normal TTI, long TTI, normal subframe, long subframe, slot, etc. A TTI shorter than a normal TTI may also be called a shortened TTI, short TTI, partial or fractional TTI, shortened subframe, short subframe, mini slot, sub slot, slot, etc.

[0156] Furthermore, long TTIs (e.g., normal TTIs, subframes, etc.) may be interpreted as TTIs with a time length exceeding 1 ms, and short TTIs (e.g., shortened TTIs, etc.) may be interpreted as TTIs with a TTI length less than that of a long TTI but 1 ms or more.

[0157] A resource block (RB) is a resource allocation unit in the time domain and frequency domain, and in the frequency domain, it may contain one or more consecutive subcarriers. The number of subcarriers in an RB may be the same regardless of the neurology, for example, 12. The number of subcarriers in an RB may be determined based on the neurology.

[0158] Furthermore, the time domain of RB may contain one or more symbols and may be the length of one slot, one minislot, one subframe, or one TTI. One TTI, one subframe, etc., may each consist of one or more resource blocks.

[0159] One or more RBs may also be called Physical RBs (PRBs), Sub-Carrier Groups (SCGs), Resource Element Groups (REGs), PRB pairs, RB pairs, etc.

[0160] Furthermore, a resource block may consist of one or more resource elements (REs). For example, one RE may be a radio resource area comprising one subcarrier and one symbol.

[0161] A Bandwidth Part (BWP), also known as a partial bandwidth, may represent a subset of consecutive common resource blocks (RBs) for a given neurology in a given carrier. Here, the common RBs may be identified by an index of the RBs relative to the carrier's common reference point. PRBs may be defined and numbered within a given BWP.

[0162] A BWP may include BWPs for UL (UL BWP) and BWPs for DL ​​(DL BWP). One or more BWPs may be configured within a single carrier for a UE.

[0163] At least one of the configured BWPs may be active, and the UE does not need to assume that it will send or receive a given signal / channel outside of the active BWP. In this disclosure, terms such as "cell" and "carrier" may be read as "BWP".

[0164] The structures described above, such as wireless frames, subframes, slots, minislots, and symbols, are merely illustrative. For example, the number of subframes included in a wireless frame, the number of slots per subframe or wireless 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, and the number of symbols, symbol length, and cyclic prefix (CP) length within a TTI can be varied in various ways.

[0165] The terms “connected,” “coupled,” or any variation thereof, mean 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” with each other. The coupling or connection between elements may be physical, logical, or a combination thereof. For example, “connection” may be reinterpreted as “access.” As used in this disclosure, two elements may be considered to be “connected” or “coupled” with each other using at least one of one or more wires, cables, and printed electrical connections, and, in some non-limiting and non-exclusive examples, electromagnetic energy having wavelengths in the radio frequency domain, microwave domain, and optical (both visible and invisible) domain.

[0166] The reference signal can also be abbreviated as Reference Signal (RS), and may be called a pilot depending on the applicable standard.

[0167] In this disclosure, the phrase "based on" does not mean "based solely on" unless otherwise specified. In other words, the phrase "based on" means both "based solely on" and "based at least on."

[0168] In the configuration of each of the above devices, "means" may be replaced with "part," "circuit," "device," etc.

[0169] Any reference to elements using the designations “first,” “second,” etc., as 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 to distinguish between two or more elements. Accordingly, references to the first and second elements do not imply that only two elements may be employed therein, or that the first element must precede the second element in any way.

[0170] Where the terms “include,” “including,” and variations thereof are used in this disclosure, these terms are intended to be inclusive, as is the term “comprising.” Furthermore, the term “or” as used in this disclosure is not intended to mean exclusive OR.

[0171] In this disclosure, if articles are added through translation, such as a, an, and the in English, this disclosure may include the fact that the noun following these articles is plural.

[0172] As used in this disclosure, the terms “determining” and “determining” may encompass a wide variety of actions. “Determining” may include, for example, judging, calculating, computing, processing, deriving, investigating, looking up, searching, or inquiring (e.g., searching in a table, database, or other data structure), or ascertaining. “Determining” may also include receiving (e.g., receiving information), transmitting (e.g., sending information), inputting, outputting, or accessing (e.g., accessing data in memory). Furthermore, "judgment" and "decision" can include considering something as having been "judged" or "decided" after resolving, selecting, choosing, establishing, comparing, etc. In other words, "judgment" and "decision" can include considering something as having been "judged" or "decided" after some action. Also, "judgment (decision)" can be reinterpreted as "assuming," "expecting," or "considering."

[0173] In this disclosure, the term "A and B are different" may mean "A and B are different from each other." The term may also mean "A and B are each different from C." Terms such as "separate" and "combine" may be interpreted similarly to "different."

[0174] Figure 14 shows an example of the configuration of vehicle 2001. As shown in Figure 14, 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.

[0175] The drive unit 2002 is composed of, for example, an engine, a motor, or a hybrid of an engine and a motor.

[0176] 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, which is operated by the user.

[0177] The electronic control unit 2010 consists of a microprocessor 2031, memory (ROM, RAM) 2032, and communication ports (IO ports) 2033. Signals from various sensors 2021 to 2027 installed in the vehicle are input to the electronic control unit 2010. The electronic control unit 2010 may also be called an ECU (Electronic Control Unit).

[0178] Signals from various sensors 2021 to 2028 include current signals from the current sensor 2021 that senses motor current, front and rear wheel rotation speed signals obtained by the rotation speed sensor 2022, front and rear wheel air pressure signals obtained by the air pressure sensor 2023, vehicle speed signals obtained by the vehicle speed sensor 2024, acceleration signals obtained by the acceleration sensor 2025, accelerator pedal depression signals obtained by the accelerator pedal sensor 2029, brake pedal depression signals obtained by the brake pedal sensor 2026, shift lever operation signals obtained by the shift lever sensor 2027, and detection signals obtained by the object detection sensor 2028 for detecting obstacles, vehicles, pedestrians, etc.

[0179] The Information Services Unit 2012 consists of various devices for providing various types of information, such as driving information, traffic information, and entertainment information, including a car navigation system, audio system, speakers, television, and radio, and one or more ECUs that control these devices. The Information Services Unit 2012 uses information acquired from external devices via a communication module 2013, etc., to provide various multimedia information and multimedia services to the occupants of Vehicle 1.

[0180] The driver assistance system unit 2030 consists of various devices that provide functions to prevent accidents or reduce the driver's workload, such as millimeter-wave radar, LiDAR (Light Detection and Ranging), cameras, positioning locators (e.g., GNSS), map information (e.g., high-definition (HD) maps, autonomous vehicle (AV) maps), gyro systems (e.g., IMU (Inertial Measurement Unit), INS (Inertial Navigation System)), AI (Artificial Intelligence) chips, and AI processors, as well as one or more ECUs that control these devices. The driver assistance system unit 2030 also sends and receives various information via the communication module 2013 to realize driver assistance functions or autonomous driving functions.

[0181] The communication module 2013 can communicate with the microprocessor 2031 and components of the vehicle 1 via its communication port. For example, the communication module 2013 sends 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, the microprocessor 2031 and memory (ROM, RAM) 2032 in the electronic control unit 2010, and sensors 2021 to 2028 provided in the vehicle 2001.

[0182] 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 external devices. For example, it can send and receive various types of information to and from external devices 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 or a mobile station.

[0183] The communication module 2013 transmits current signals from current sensors input to the electronic control unit 2010 to an external device via wireless communication. The communication module 2013 also transmits, via wireless communication, other signals input to the electronic control unit 2010, including front and rear wheel rotation speed signals obtained by the rotation speed sensor 2022, front and rear wheel air pressure signals obtained by the air pressure sensor 2023, vehicle speed signals obtained by the vehicle speed sensor 2024, acceleration signals obtained by the acceleration sensor 2025, accelerator pedal depression signals obtained by the accelerator pedal sensor 2029, brake pedal depression signals obtained by the brake pedal sensor 2026, shift lever operation signals obtained by the shift lever sensor 2027, and detection signals obtained by the object detection sensor 2028 for detecting obstacles, vehicles, pedestrians, etc.

[0184] The communication module 2013 receives various information (traffic information, signal information, distance information, etc.) transmitted from external devices and displays it on the information service unit 2012 installed in the vehicle. The communication module 2013 also stores the various information received from external devices in memory 2032, which is available to the microprocessor 2031. Based on the information stored in 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, etc., installed in the vehicle 2001.

[0185] Although the present disclosure has been described in detail above, it will be clear to those skilled in the art that the present disclosure is not limited to the embodiments described herein. The present disclosure can be implemented in modified and altered forms without departing from the intent and scope of the present disclosure as defined by the claims. Therefore, the descriptions in the present disclosure are illustrative and not intended to be restrictive in any way.

[0186] (Note) The disclosure described above may also be expressed as follows:

[0187] The first feature is a communication node comprising: a control unit that performs operations corresponding to a model available as a model for artificial intelligence or machine learning; and a transmission unit that sends a message to another communication node containing information indicating the data rate predicted by the model, wherein the data rate is a desirable data rate for the data received from the other communication node, and the message contains information regarding the time of the data rate predicted by the model.

[0188] The second feature is that, in the first feature, the device includes a receiving unit that receives a data rate query from the other communication node, and the transmitting unit is a communication node that transmits the message in response to the data rate query.

[0189] The third feature is that, in the second feature, the receiving unit is a communication node that does not anticipate receiving the next data rate query following the first data rate query until the timer activated in response to the data rate query has expired, and anticipates receiving the next data rate query after the timer has expired.

[0190] The fourth feature is a communication node in which, in at least one of the first to third features, the data rate is the data rate per logical channel, per wireless bearer, or per quality of service flow.

[0191] A fifth feature is a wireless communication system comprising a first communication node and a second communication node, wherein the first communication node comprises a control unit that performs operations corresponding to a model available as a model for artificial intelligence or machine learning, and a transmission unit that transmits a message to the second communication node containing information indicating a data rate predicted by the model, the data rate being a desirable data rate for data received from the second communication node, and the message containing information regarding the time of the data rate predicted by the model.

[0192] A sixth feature is a wireless communication method comprising: step A, performing an operation corresponding to a model available as a model for artificial intelligence or machine learning; and step B, sending a message to another communication node containing information indicating a data rate predicted by the model, wherein the data rate is a desired data rate for the rate of data to be received from the other communication node, and the message contains information regarding the time of the data rate predicted by the model.

[0193] 10 Wireless Communication System 10A First Network 10B Second Network 20A, 20B Wireless Access Network 30A, 30B Core Network 50 Network Device 51 Receiving Unit 52 Transmitting Unit 53 Control Unit 100A, 100B Base Station 200 UE 210 Wireless Signal Transmitting / Receiving Unit 220 Amplifier Unit 230 Modulation / Demodulation Unit 240 Control Signal / Reference Signal Processing Unit 250 Encoding / Decoding Unit 260 Data Transmitting / Receiving Unit 270 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 Front wheels (left and right) 2008 Rear wheels (left and right) 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 unit 2031 Microprocessor 2032 Memory (ROM, RAM) 2033 Communication port

Claims

1. A communication node comprising: a control unit that performs operations corresponding to a model available as a model for artificial intelligence or machine learning; and a transmission unit that transmits a message to another communication node containing information indicating the data rate predicted by the model, wherein the data rate is a desirable data rate for the rate of data received from the other communication node, and the message contains information regarding the time of the data rate predicted by the model.

2. The communication node according to claim 1, comprising a receiving unit that receives a data rate query from the other communication node, and the transmitting unit that transmits the message in response to the data rate query.

3. The communication node according to claim 2, wherein the receiving unit does not anticipate receiving the next data rate inquiry following the previous data rate inquiry until a timer activated in response to the data rate inquiry has expired, and anticipates receiving the next data rate inquiry after the timer has expired.

4. The communication node according to claim 1, wherein the data rate is the data rate for each logical channel, each wireless bearer, or each quality of service flow.

5. A wireless communication system comprising a first communication node and a second communication node, wherein the first communication node comprises a control unit that performs operations corresponding to a model available as a model for artificial intelligence or machine learning, and a transmission unit that transmits a message to the second communication node containing information indicating a data rate predicted by the model, wherein the data rate is a desirable data rate for the rate of data received from the second communication node, and the message contains information regarding the time of the data rate predicted by the model.

6. A wireless communication method comprising: step A performing an operation corresponding to a model available as a model for artificial intelligence or machine learning; and step B sending a message to another communication node containing information indicating a data rate predicted by the model, wherein the data rate is a desired data rate for the rate of data to be received from the other communication node, and the message contains information regarding the time of the data rate predicted by the model.

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