Terminal

Abstract

A terminal is provided with: a control unit that calculates a predicted value of cell quality using a learning model, and compares the predicted value with a threshold value; and a transmission unit that transmits a measurement report relating to the cell quality on the basis of the comparison by the control unit, and the control unit compares either the predicted value or the threshold value with an offset value added thereto.

Description

Technical Field

[0001] This disclosure relates to a terminal that uses a learning model to perform mobility-related actions. Background Technology

[0002] The 3rd Generation Partnership Project (3GPP, a registered trademark) standardized the 5th generation mobile communication system (also known as 5G, New Radio (NR), or Next Generation (NG)) and also standardized the next-generation mobile communication system known as Beyond 5G, 5G Evolution, or 6G.

[0003] Release 18 discusses the introduction of Artificial Intelligence (AI) / Machine Learning (ML). AI / ML models (hereinafter also referred to as learning models) are downloaded from base stations (hereinafter also referred to as gNodeB, gNB) and applied to terminals (hereinafter also referred to as User Equipment, UE).

[0004] By applying the learning model to the UE, it is expected to improve performance in various areas such as Channel State Information (CSI) feedback, beam management (BM), positioning, mobility, network slicing, and Quality of Experience (QoE). Regarding mobility, a learning model for Radio Resource Management (RRM) is being researched (Non-Patent Document 1).

[0005] Existing technical documents

[0006] Non-patent literature

[0007] Non-patent literature 1: "Moderator's summary for REL-19 RAN2 topic AI / ML for AirInterface SI (Mobility)", RP-232622, 3GPP TSG RAN Meeting #101, 3GPP, September 11-15, 2023 Summary of the Invention

[0008] By applying the learning model used in RRM, the UE can calculate predicted cell quality values ​​instead of actually measuring cell quality. These predicted cell quality values ​​can be, for example, values ​​predicted as the cell quality after t seconds. Based on these predicted cell quality values, the UE can perform tasks such as sending measurement reports and executing autonomous handover (HO) operations.

[0009] The predicted cell quality value may vary for each UE depending on the algorithm or implementation method of the learning model applied. Furthermore, since the parameters used to calculate the predicted value are diverse, it is not easy to define a benchmark for calculating the predicted value. Therefore, even under the same conditions, mobility-related actions (e.g., sending measurement reports or executing autonomous HO) may differ for each UE. That is, even under the same conditions, there may be a mixture of UEs performing mobility actions and UEs not performing mobility actions.

[0010] Therefore, this disclosure was made in view of the following situation, and its purpose is to provide a terminal that can uniformly perform mobility-related actions regardless of the algorithm or implementation method of the learning model applied.

[0011] One disclosed embodiment is a terminal comprising: a control unit (control unit 270) that uses a learning model to calculate a predicted value of cell quality and compares the predicted value with a threshold; and a transmission unit (wireless signal transceiver unit 210) that, based on the comparison by the control unit, transmits a measurement report related to the cell quality, wherein the control unit compares the predicted value and the threshold by adding an offset value to either one.

[0012] One disclosed embodiment is a terminal comprising: a receiving unit (wireless signal transceiver 210) that receives a threshold for performing autonomous handover; and a control unit (control unit 270) that uses a learning model to calculate a predicted value of cell quality and compares the predicted value with the threshold, wherein the control unit adds an offset value to either the predicted value or the threshold for comparison. Attached Figure Description

[0013] Figure 1 It is a general structural diagram of the wireless communication system.

[0014] Figure 2 This is a diagram showing the frequency ranges used in wireless communication systems.

[0015] Figure 3 This is a diagram illustrating an example of the structure of wireless frames, subframes, time slots, and symbols used in a wireless communication system.

[0016] Figure 4 This is a functional block diagram of the terminal.

[0017] Figure 5 This is a functional block diagram of a base station.

[0018] Figure 6 This is a graph showing the timing of sending measurement reports using a learning model.

[0019] Figure 7 This is a diagram showing the timing of autonomous HO using a learning model.

[0020] Figure 8 This is a diagram showing an example of the content of a measurement report sent using a learning model.

[0021] Figure 9 This is a diagram illustrating an example of the hardware structure of a base station and a terminal.

[0022] Figure 10 This is a diagram showing an example of the structure of a vehicle. Detailed Implementation

[0023] The embodiments are described below based on the accompanying drawings. Furthermore, the same or similar reference numerals are used to denote the same function or structure, and their descriptions are omitted where appropriate.

[0024] (1) Structure of wireless communication system

[0025] Figure 1 The wireless communication system 10 shown is a wireless communication system that follows a method known as 5G. On the other hand, the wireless communication system 10 can also be a wireless communication system that follows a method known as Beyond 5G, 5G Evolution, or 6G.

[0026] The wireless communication system 10 can support massive multiple-input multiple-output (MIMO) that generates more directional beams by controlling wireless signals transmitted from multiple antenna elements, carrier aggregation (CA) that uses multiple component carriers (CC), and dual connectivity (DC) that communicates simultaneously with two base stations.

[0027] like Figure 1As shown, the wireless communication system 10 includes a Next Generation-RadioAccess Network (NG-RAN) 20, a base station (hereinafter also referred to as gNodeB or gNB) 100 connected to the NG-RAN 20, and a terminal (hereinafter also referred to as User Equipment or UE) 200 that communicates wirelessly with the gNB 100. The NG-RAN 20 is connected to a core network (CN) not shown. The NG-RAN 20 and CN can also be simply referred to as a "network". Additionally, the gNB 100 can be understood as being included within the network. Furthermore, the specific structure of the wireless communication system 10, such as the number of gNBs 100 and UEs 200, is not limited to [specific details needed]. Figure 1 The example shown.

[0028] In addition, the wireless communication system 10 can support multiple frequency ranges (FRs). That is, such as Figure 2 As shown, the following FRs can be supported.

[0029] FR1: 410MHz~7.125GHz

[0030] FR2-1: 24.25GHz~52.6GHz

[0031] FR2-2: Over 52.6GHz to 71GHz

[0032] In FR1, a subcarrier spacing (SCS) of 15, 30, or 60 kHz and a bandwidth (BW) of 5–100 MHz can be used. In FR2-1, an SCS of 60 or 120 kHz (or including 240 kHz) and a BW of 50–400 MHz can be used.

[0033] In FR2-2, to avoid increasing phase noise, Cyclic Prefix-Orthogonal Frequency Division Multiplexing (CP-OFDM) or Discrete Fourier Transform-Spread-Orthogonal Frequency Division Multiplexing (DFT-S-OFDM) with a larger SCS can be applied.

[0034] In addition, such as Figure 3As shown, one time slot in the wireless communication system 10 consists of 14 symbols. While maintaining this structure, a larger (wider) SCS results in a shorter symbol period (and time slot period). Furthermore, the SCS is not limited to... Figure 3 The frequency shown can be, for example, 480kHz, 960kHz, etc.

[0035] Furthermore, the number of symbols constituting one time slot does not necessarily have to be 14 symbols; for example, it could be 28 or 56 symbols. Also, the number of time slots in each subframe can vary depending on the SCS.

[0036] (2) Functional block structure of wireless communication system

[0037] (2.1) Functional block structure of the terminal

[0038] like Figure 4 As shown, the UE 200 includes a wireless signal transceiver unit 210, an amplifier unit 220, a modem unit 230, and a control signal transceiver unit 200. The reference signal processing unit 240, the encoding / decoding unit 250, the data transceiver unit 260, and the control unit 270 are included.

[0039] The wireless transceiver unit 210 transmits and receives wireless signals with the gNB 100. The wireless transceiver unit 210 can also be configured as a transmitter sending wireless signals to the gNB 100 and a receiver receiving wireless signals from the gNB 100. Transmission can also be replaced by reporting, notification, etc. Furthermore, reception can be replaced by setting, indicating, etc. In addition, setting can be implemented through Radio Resource Control (RRC), and indicating can be implemented through the Media Access Control (MAC) control element (MAC CE) or Downlink Control Information (DCI).

[0040] The wireless transceiver unit 210 of the embodiment sends a measurement report related to cell quality to the gNB 100 based on the comparison by the control unit 270 described later. Cells that are the targets of cell quality measurement include, for example, serving cells (PCell, PSCell, SpCell), neighboring cells, and secondary cells (SCell). Furthermore, the wireless transceiver unit 210 of the embodiment may also send a measurement report related to cell quality to the gNB 100 based on settings or instructions from the gNB 100.

[0041] The wireless transceiver unit 210 of the embodiment can transmit the measurement report along with information relating to the time or period of the transmission timing for sending the measurement report. Furthermore, the information relating to the time of transmission timing for sending the measurement report can also be referred to as a timestamp, and the information relating to the period of transmission timing for sending the measurement report can also be referred to as a time window.

[0042] The wireless transceiver unit 210 of the embodiment can transmit the measurement report along with information relating to the timing or period of the execution of autonomous handover (HO). Furthermore, the information relating to the timing of the execution of autonomous HO can also be referred to as a timestamp, and the information relating to the period of the execution of autonomous HO can also be referred to as a time window.

[0043] The wireless signal transceiver unit 210 of the embodiment can transmit at least one of the following together: the measurement report and the location information of the UE 200 predicted by the control unit 270 using the learning model, the reduction timing of cell quality degradation, and the event conditions for performing HO.

[0044] The wireless transceiver unit 210 of the embodiment receives a threshold for performing autonomous HO from the gNB 100. Autonomous HO can be, for example, Conditional Handover (CHO), Conditional PSCellAddition / Change (CPAC), or Lower Layer Triggered Mobility (LTM) controlled in lower layers (L1 / L2). The threshold for performing autonomous HO can also be understood as part of the HO execution conditions.

[0045] The amplification unit 220 includes a power amplifier (PA) and a low-noise amplifier (LNA). The amplification unit 220 amplifies the wireless signal output from the wireless signal transceiver unit 210. Additionally, the amplification unit 220 amplifies the wireless signal output from the modem 230.

[0046] The modem 230 performs data modulation / demodulation, transmit power setting, and resource block allocation for each predetermined communication target (gNB 100 or other gNB). CP-OFDM / DFT-S-OFDM can also be applied in the modem 230. Furthermore, DFT-S-OFDM can be used not only for the uplink (UL) but also for the downlink (DL).

[0047] control signals The reference signal processing unit 240 performs processing of control signals, such as Radio Resource Control (RRC) signaling, that are transmitted and received with the gNB 100.

[0048] control signals The reference signal processing unit 240 performs processing on reference signals transmitted and received with gNB 100, such as demodulation reference signal (DMRS), phase tracking reference signal (PTRS), channel state information-reference signal (CSI-RS), sounding reference signal (SRS), and positioning reference signal (PRS).

[0049] In addition, the channels include control channels and data channels. Control channels include the Physical Uplink Control Channel (PUCCH), Physical Downlink Control Channel (PDCCH), Physical Random Access Channel (PRACH), and Physical Broadcast Channel (PBCH). Data channels include the Physical Uplink Shared Channel (PUSCH) and Physical Downlink Shared Channel (PDSCH).

[0050] The encoding / decoding unit 250 performs segmentation / linking and encoding / decoding of the data contained in the wireless signal for each predetermined communication target (gNB 100 or other gNB).

[0051] Specifically, the encoder / decoder 250 decodes the data output from the modem 230 and concatenates the decoded data. Additionally, the encoder / decoder 250 divides the data output from the data transceiver 260 into predetermined sizes and encodes the divided data.

[0052] The data transceiver unit 260 performs tasks such as assembling and decomposing Protocol Data Units (PDUs) and Service Data Units (SDUs) that constitute data between layers. These layers include the Media Access Control (MAC) layer, the Radio Link Control (RLC) layer, and the Packet Data Convergence Protocol (PDCP) layer. Furthermore, the data transceiver unit 260 performs error correction and retransmission control based on Hybrid Automatic Repeat Request (HARQ).

[0053] The control unit 270 controls the UE 200. For example, the control unit 270 controls the transmission and reception of wireless signals based on the wireless signal transceiver unit 210, amplification based on the amplification unit 220, data modulation / demodulation based on the modulation / demodulation unit 230, and control signals. The signal processing of the reference signal processing unit 240, the encoding / decoding based on the encoding / decoding unit 250, and the assembly / decomposition of data units based on the data transceiver unit 260.

[0054] In this implementation, the control unit 270 uses a learning model to calculate a predicted value for cell quality. Furthermore, the control unit 270 compares the calculated predicted value with a threshold, and if the predicted value is lower (or higher) than the threshold, decides to send a measurement report related to the cell quality. That is, the wireless transceiver unit 210 sends a measurement report related to cell quality based on the comparison made by the control unit 270.

[0055] In this embodiment, the control unit 270 uses a learning model to calculate a predicted value for cell quality. Furthermore, the control unit 270 compares the calculated predicted value with a threshold, and performs autonomous HO (Housing and Optimization) if the predicted value is lower than (or higher than) the threshold. The control unit 270 can also use the learning model to predict the execution timing for autonomous HO. In this case, the control unit 270 can perform autonomous HO at that execution timing.

[0056] Furthermore, the control unit 270 in the implementation can also calculate the measured value of cell quality without using a learning model and compare it with a threshold.

[0057] The control unit 270 in this implementation can use a learning model to predict both the transmission timing of sending the measurement report and the execution timing of performing autonomous HO (Hospital Response). In this case, the control unit 270 can predict the other based on either the transmission timing or the execution timing. Furthermore, the control unit 270 can also predict the transmission timing or the execution timing based on the movement speed of the UE 200. For example, if the UE 200 moves quickly, the transmission timing or the execution timing can be advanced; if the UE 200 moves slowly, the transmission timing or the execution timing can be delayed.

[0058] The control unit 270 in this implementation can use a learning model to predict various parameters; that is, the control unit 270 can use the learning model to calculate predicted values ​​for various parameters. For example, the control unit 270 can use the learning model to predict the location information of the UE 200, predict the timing of cell quality degradation, and predict the event conditions for performing autonomous HO (Hospital Response) operations.

[0059] The predicted value of cell quality (hereinafter also referred to as the predicted value) can be, for example, a value predicted as the cell quality after t seconds. Cell quality values ​​include, for example, Reference Signal Received Power (RSRP), Reference Signal Received Quality (RSRQ), and Signal to Interference plus Noise Power Ratio (SINR). Furthermore, cell quality values ​​can be measured in L3 or in lower layers (L1 / L2, hereinafter also referred to as L1). Therefore, the predicted values ​​of cell quality are, for example, the predicted values ​​of L1 / L3 RSRP, L1 / L3 RSRQ, and L1 / L3 SINR.

[0060] The threshold can be a threshold used to determine the quality of a cell and send a measurement report. In this case, the threshold can be understood as part of the event conditions used to send the measurement report. Alternatively, the threshold can also be a threshold used to perform the aforementioned autonomous HO (Hospital Response) mechanism.

[0061] Furthermore, the control unit 270 in this embodiment can also add an offset value to either the predicted value or the threshold during the comparison between the predicted value and the threshold. That is, the control unit 270 can compare the predicted value plus the offset value with the threshold, or it can compare the predicted value with the threshold plus the offset value. Therefore, the control unit 270 can also decide to send a measurement report related to the cell quality mentioned above when the predicted value plus the offset value is lower than (or higher than) the threshold, or when the predicted value is lower than (or higher than) the threshold plus the offset value.

[0062] The offset value can be positive or negative. It can be fixed or variable. The offset value can be a predetermined value or calculated by the control unit 270 using a learning model. Furthermore, the control unit 270 can also use the learning model to change the offset value. In addition, the offset value in this embodiment is sometimes labeled AIML_offset for convenience, but it is not limited to a value calculated using a learning model; it can also be a predetermined value.

[0063] There can be one predicted value, one threshold, and one offset value. That is, as explained in the action examples column, you can compare one predicted value (+offset value) with one threshold (+offset value), or you can compare multiple predicted values ​​(+offset values) with multiple thresholds (+offset values).

[0064] (2.2) Functional block structure of base station

[0065] like Figure 5As shown, the gNB 100 includes a wireless signal transceiver unit 110 and a control unit 120.

[0066] The wireless transceiver unit 110 transmits and receives wireless signals with the UE 200. The wireless transceiver unit 110 may also be configured as a transmitting unit that sends wireless signals to the UE 200 and a receiving unit that receives wireless signals from the UE 200. Transmission may be replaced by setting, indicating, etc. Furthermore, reception may be replaced by reporting, notifying, etc. In addition, setting may be implemented through Radio Resource Control (RRC), and indicating may be implemented through the Media Access Control (MAC) control element (MAC CE) or Downlink Control Information (DCI).

[0067] The wireless transceiver unit 110 of the embodiment sends setting information related to cell quality measurement (e.g., a threshold for sending measurement reports) to the UE 200 (see reference). Figure 6 Additionally, the wireless transceiver unit 110 sends configuration information for performing autonomous HO (e.g., a threshold for performing autonomous HO) to the UE 200 (see reference). Figure 7 ).

[0068] The control unit 120 controls the gNB 100. For example, the control unit 120 controls the transmission and reception of wireless signals performed by the wireless signal transceiver unit 110. In addition, the control unit 120 performs scheduling for the UE 200.

[0069] The control unit 120 in the embodiment can also use the learning model to make various predictions in the same way as the control unit 270 of the UE 200. The various predictions made by the control unit 120 can also be the same as the predictions made by the control unit 270, and detailed descriptions are omitted.

[0070] (2.3) Architecture of the learning model

[0071] A learning model can include the following features as its architecture.

[0072] • Data collection: “Data collection” refers to collecting input data to provide for “model training” as described later.

[0073] Model training: "Model training" involves training, validating, and testing the learned model based on the input data, and then saving the trained (validated / tested) model to the "model storage device" described later. Furthermore, "model training" can also generate model performance metrics as part of the testing process. Additionally, "model training" can also perform data preparation (data preprocessing and cleaning, formatting, conversion, etc.).

[0074] • Model storage device: The “model storage device” stores the learning model.

[0075] • Model Estimation: "Model Estimation" uses the learned model stored in the "Model Storage Device" to perform predictions (output predicted values) corresponding to the input data. "Model Estimation" can also provide predicted values ​​for feedback to "Model Management / Performance Monitoring" described later.

[0076] • Model Management / Performance Monitoring: "Model Management / Performance Monitoring" manages and monitors the performance of the learning model. "Model Management / Performance Monitoring" can also provide information for training the learning model based on predicted values ​​to "Model Training".

[0077] (3) Operation of wireless communication system

[0078] (3.1) Topic

[0079] (3.1.1) Topic 1

[0080] The predicted cell quality value may vary for each UE depending on the algorithm or implementation method of the learning model applied. Furthermore, since the parameters used to calculate the predicted value are diverse, it is not easy to define a benchmark for calculating the predicted value. Therefore, even under the same conditions, mobility-related actions (e.g., sending measurement reports or executing autonomous HO) may differ for each UE. That is, even under the same conditions, there may be a mixture of UEs performing mobility actions and UEs not performing mobility actions.

[0081] (3.1.2) Topic 2

[0082] Regarding the timing of measurement report transmission and the timing of autonomous HO execution, we also considered using learning models for prediction. However, we believe there is room for improvement in predictions that utilize learning models, such as predicting these timings not only individually but also in combination.

[0083] (3.2) Example of an action

[0084] (3.2.1) Action Example 1

[0085] Reference Figure 6Example 1 of the action will be explained below. UE 200 may send (trigger) a measurement report when the following event conditions are met. Furthermore, the measurement report is based on predicted values ​​calculated using a learning model, and therefore may also be referred to as AIML measurement reporting or AIML reporting. The predicted cell quality values ​​shown below are, for example, L1 / L3 RSRP, L1 / L3 RSRQ, and L1 / L3 SINR. The AIML_offset shown below corresponds to the "offset value" mentioned above. AIML_offset can be, for example, +XdB or -XdB.

[0086] • The predicted cell quality value of the service cell plus AIML_offset is higher than the predetermined threshold.

[0087] • When the predicted cell quality value of the service cell plus AIML_offset is lower than the predetermined threshold.

[0088] • The predicted cell quality of neighboring cells plus AIML_offset is higher than a predetermined threshold.

[0089] • When the predicted cell quality of neighboring cells plus AIML_offset is lower than a predetermined threshold.

[0090] • If the predicted cell quality plus AIML_offset of a neighboring cell is greater than or equal to the predicted or measured cell quality of SpCell, then...

[0091] • The case where the predicted cell quality value of SpCell plus AIML_offset is lower than a predetermined threshold (threshold 1), and the predicted cell quality value of neighboring cells plus AIML_offset is higher than a predetermined threshold (threshold 2).

[0092] • If the predicted cell quality plus AIML_offset of a neighboring cell is greater than or equal to the predicted or measured cell quality of SCell, then...

[0093] • Case where the predicted value of neighboring cells in an Inter-RAT (Rest-Agent Attempt) plus the AIML_offset exceeds a predetermined threshold.

[0094] • The case where the predicted cell quality value of PCell plus AIML_offset is lower than a predetermined threshold (threshold 1), and the predicted cell quality value of inter-RAT neighboring cells plus AIML_offset is higher than a predetermined threshold (threshold 2).

[0095] Additionally, UE 200 can also attach a timestamp or time window that meets the event conditions when sending measurement reports. Furthermore, in addition to adding AIML_offset, AIML_hysteresis can also be added to the aforementioned event conditions. AIML_hysteresis can be understood as a hysteresis value that changes less than the aforementioned offset value. Furthermore, AIML_hysteresis can also be calculated by UE 200 using a learning model, just like the aforementioned offset value. Moreover, it is also possible to compare the predicted value with a predetermined threshold by adding AIML_offset. Similarly, UE 200 can also use a learning model to predict the predetermined threshold, just like with the predicted value.

[0096] In addition, AIML_offset can also be used via Figure 6 The AIML measurement configuration is shown. For example, it can also be set in the measObject. Additionally, the AIML_offset can be set for each UE 200. The AIML_offset can be associated with UE capabilities, or it can utilize UE capability reports. Furthermore, the possibility of AIML_offset changing over time can be considered. That is, the UE 200 can also use a learning model to predict the temporal changes in AIML_offset and adjust the AIML_offset accordingly. Additionally, the gNB 100 can also use a learning model to predict the temporal changes in AIML_offset and set the AIML_offset change pattern for the UE 200 based on this prediction.

[0097] (3.2.2) Action Example 2

[0098] Reference Figure 7 Example 2 of the action will be explained. Furthermore, in Figure 7 In this configuration, gNB 100 of the cell forming the migration source is designated as gNB 100A, and gNB 100 of the cell forming the migration destination is designated as gNB 100B. UE 200 can execute autonomous HOs (e.g., CHO, CPAC, LTM) under the following HO execution conditions. Furthermore, autonomous HOs can be... Figure 7The RACH-based HO shown can also be a RACH-less HO. The predicted cell quality values ​​shown below are, for example, L1 / L3 RSRP, L1 / L3 RSRQ, and L1 / L3 SINR. The AIML_offset shown below corresponds to the "offset values" mentioned above. AIML_offset can be, for example, +XdB or -XdB.

[0099] • The predicted cell quality of neighboring cells plus AIML_offset is higher than a predetermined threshold.

[0100] • If the predicted cell quality plus AIML_offset of a neighboring cell is greater than or equal to the predicted or measured cell quality of SpCell, then...

[0101] • The case where the predicted cell quality value of SpCell plus AIML_offset is lower than a predetermined threshold (threshold 1), and the predicted cell quality value of neighboring cells plus AIML_offset is higher than a predetermined threshold (threshold 2).

[0102] • Case where the predicted value of neighboring cells in an Inter-RAT (Rest-Agent Attempt) plus the AIML_offset exceeds a predetermined threshold.

[0103] • The case where the predicted cell quality value of PCell plus AIML_offset is lower than a predetermined threshold (threshold 1), and the predicted cell quality value of inter-RAT neighboring cells plus AIML_offset is higher than a predetermined threshold (threshold 2).

[0104] Furthermore, in the HO conditions described above, not only AIML_offset but also AIML_hysteresis can be added. AIML_hysteresis can be understood as a hysteresis value with a smaller change compared to the aforementioned offset value. Additionally, AIML_hysteresis can be calculated by the UE 200 using a learning model, just like the aforementioned offset value. Moreover, it is also possible to compare the predicted value with a predetermined threshold by adding AIML_offset. Furthermore, similar to the predicted value, the UE 200 can also use a learning model to predict the predetermined threshold.

[0105] Additionally, UE 200 can also use a learning model to predict the execution timing of autonomous HO (House of Action). The execution timing is, for example, a specific moment (e.g., 10:50:12) or a period (e.g., a time interval such as 10:50:12 to 10:51:12). UE 200 can also execute autonomous HO at the predicted execution timing. Furthermore, gNB 100 can also use a learning model to predict the execution timing and configure UE 200 to execute autonomous HO at the predicted execution timing via RRC, MAC CE, DCI, etc.

[0106] Furthermore, AIML_offset can also be set via the AIML measurement configuration, just like in Action Example 1. For example, it can also be set in the measObject. Alternatively, it can be set via... Figure 7 The AIML_offset is set using either CHO / CPAC / LTM preparation or RRCReconfiguration. Alternatively, the AIML_offset can be set differently for each UE 200. Furthermore, the possibility of AIML_offset changing over time can be considered. That is, the UE 200 can also use a learning model to predict the temporal changes in AIML_offset and adjust the AIML_offset accordingly. Additionally, the gNB 100 can also use a learning model to predict the temporal changes in AIML_offset and set the AIML_offset variation pattern for the UE 200 based on this prediction.

[0107] (3.2.3) Action Example 3

[0108] Reference Figures 6 to 8 Action Example 3 will be explained. Action Example 3 provides more detailed specifications regarding the timing of sending the measurement report and the content of the measurement report as described in Action Example 1, and the timing of executing the autonomous HO as described in Action Example 2.

[0109] (Content of the measurement report)

[0110] • A timestamp or time window that satisfies the event conditions described in Action Example 1

[0111] ·like Figure 8 The predicted UE 200 location information (which can also be 3D location), the predicted timing (time interval) of the cell quality degradation (deterioration) of the serving cell, the predicted neighboring cell with the best cell quality, the predicted execution timing (time interval) of the HO, and the predicted event that meets the conditions or at least one of the event conditions are shown.

[0112] (Timing of measurement report sending, timing of HO execution)

[0113] • Immediately after the predicted value of cell quality (AIML inference value of RRM) meets the predetermined event conditions.

[0114] • A learning model can also be used to predict the execution timing of the HO (e.g., a specific time like 10:50:12, or a time interval like 10:50:12 to 10:51:12). Furthermore, x seconds before the predicted HO execution timing can be considered as the measurement report transmission timing. In other words, the measurement report transmission timing can also be predicted based on the predicted HO execution timing. Moreover, the prediction using the learning model can be performed by either UE 200 or gNB 100. When UE 200 uses the learning model for prediction, the aforementioned x seconds can be included in the measurement report content and reported to gNB 100. When gNB 100 uses the learning model for prediction, it can also be done through the AIML measurement config (see...). Figure 6 Set the above x seconds for UE 200.

[0115] Similarly, the timing of measurement report transmission can be predicted, and the execution timing of the HO can be considered as x seconds after the predicted transmission timing. In other words, the execution timing of the HO can also be predicted based on the predicted transmission timing of the measurement report.

[0116] • The x seconds mentioned above can also be changed according to the moving speed of UE 200. For example, x can be decreased when UE 200 is moving at high speed and increased when UE 200 is moving at low speed.

[0117] (4) Functions and effects

[0118] According to the above implementation method, regardless of the algorithm or implementation method of the learning model used, it is possible to uniformly execute mobility-related actions.

[0119] (5) Other implementation methods

[0120] The present invention has been described above according to the embodiments, but the present invention is not limited to these descriptions and various modifications and improvements can be made, which will be obvious to those skilled in the art.

[0121] The above disclosure envisions the use of a general learning model, but it is not limited to this. Different learning models can also be used depending on the content to be predicted.

[0122] The above examples of actions can be combined and used in combination as long as they do not contradict each other.

[0123] Furthermore, the block diagrams used in the description of the above embodiments illustrate blocks based on function. These functional blocks (structural units) are implemented through any combination of at least one of hardware and software. Additionally, there are no particular limitations on the implementation method of each functional block. That is, each functional block can be implemented using a single device that is physically or logically combined, or by directly or indirectly (e.g., using wired, wireless, etc.) connecting two or more physically or logically separate devices. Functional blocks can also be implemented by combining software within one or more of the aforementioned devices.

[0124] The functions include judgment, decision, determination, calculation, calculation, processing, derivation, investigation, search, confirmation, receiving, sending, output, access, resolution, selection, selection, establishment, comparison, assumption, expectation, consideration, broadcasting, notifying, communicating, forwarding, configuring, reconfiguring, allocating, mapping, and assigning, but are not limited to these. For example, the functional block (structural part) that performs the sending function is called the transmitting unit or transmitter. In short, as mentioned above, there are no particular limitations on the implementation method.

[0125] For example, in one embodiment of this disclosure, the base station 100, terminal 200, etc., can also function as a computer for processing the wireless communication method of this disclosure. Figure 9 This is a diagram illustrating an example of the hardware structure of a base station 100 and a terminal 200 according to an embodiment of this disclosure. The base station 100 and the terminal 200 described above may also be configured as a computer device that physically includes a processor 1001, a memory 1002, a storage device 1003, a communication device 1004, an input device 1005, an output device 1006, a bus 1007, etc.

[0126] Furthermore, in the following description, the term "device" can be replaced with "circuit," "device," "unit," etc. The hardware structure of base station 100 and terminal 200 can be configured to include one or more of the devices shown in the figures, or it can be configured to not include any of them.

[0127] The functions of the base station 100 and the terminal 200 are implemented by reading predetermined software (programs) into hardware such as the processor 1001 and the memory 1002, so that the processor 1001 performs calculations and controls the communication of the communication device 1004 or controls at least one of reading out and writing data in the memory 1002 and the storage device 1003.

[0128] The processor 1001 controls the computer as a whole, for example, by instructing the operating system to operate. The processor 1001 may also be a central processing unit (CPU) that includes interfaces with peripheral devices, control devices, arithmetic devices, registers, etc.

[0129] Furthermore, the processor 1001 reads programs (program code), software modules, data, etc., from at least one direction of memory 1002 in the storage device 1003 and the communication device 1004, and performs various processes accordingly. The program is used to cause the computer to perform at least a portion of the actions described in the above embodiments. Although it has been described that the various processes described above are performed by one processor 1001, the various processes described above can also be performed simultaneously or sequentially by two or more processors 1001. The processor 1001 can also be implemented using one or more chips. In addition, the program can also be transmitted from a network via a telecommunications line.

[0130] The memory 1002 is a computer-readable recording medium, and may be composed of at least one of the following: read-only memory (ROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), and random access memory (RAM). The memory 1002 may be referred to as a register, cache, main memory (main storage device), etc. The memory 1002 can store programs (program code), software modules, etc., that are executable for implementing the wireless communication method according to one embodiment of this disclosure.

[0131] Storage device 1003 is a computer-readable recording medium, and may be composed of at least one of the following: optical discs such as CD-ROM (Compact Disc ROM), hard disks, floppy disks, magneto-optical discs (e.g., compact discs, digital multipurpose discs, Blu-ray discs), smart cards, flash memory (e.g., cards, sticks, key drives), floppy disks, magnetic stripes, etc. Storage device 1003 may also be referred to as an auxiliary storage device. The aforementioned storage medium may be, for example, a database, server, or other suitable media that includes at least one of memory 1002 and storage device 1003.

[0132] The communication device 1004 is hardware (transceiver) used for communication between computers via at least one of a wired network and a wireless network. It is also referred to as a network device, network controller, network interface card (NIC), communication module, etc. The communication device 1004 may, for example, be configured to include a high-frequency switch, duplexer, filter, frequency synthesizer, etc., to implement at least one of Frequency Division Duplex (FDD) and Time Division Duplex (TDD).

[0133] Input device 1005 is an input device that accepts input from external sources (e.g., keyboard, mouse, microphone, switch, button, sensor, etc.). Output device 1006 is an output device that performs output to external sources (e.g., display, speaker, LED, etc.). Furthermore, input device 1005 and output device 1006 can also be integrated (e.g., a touch panel).

[0134] Furthermore, the processor 1001, memory 1002, and other devices are connected via a bus 1007 for communicating information. The bus 1007 can be configured using a single bus or different buses can be used between each device.

[0135] Furthermore, the base station 100 and the terminal 200 can 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), and a field-programmable gate array (FPGA), which can be used to implement some or all of the functional blocks. For example, the processor 1001 can also be implemented using at least one of these hardware components.

[0136] The notification of information is not limited to the forms / implementations described in this disclosure, and other methods may also be used. For example, the notification of information may be implemented through physical layer signaling (e.g., Downlink Control Information (DCI), Uplink Control Information (UCI)), higher layer signaling (e.g., Radio Resource Control (RRC) signaling, Medium Access Control (MAC) signaling), broadcast information (Master Information Block (MIB), System Information Block (SIB)), other signals, or combinations thereof. Additionally, RRC signaling may also be referred to as an RRC message, for example, an RRC Connection Setup message, an RRC Connection Reconfiguration message, etc.

[0137] The various forms / implementations described in this disclosure can also be applied to systems utilizing LTE (Long Term Evolution), LTE-A (LTE-Advanced), SUPER 3G, IMT-Advanced, 4th generation mobile communication system (4G), 5th generation mobile communication system (5G), 6th generation mobile communication system (6G), xth generation mobile communication system (xG) (x is, for example, an integer or a decimal), Future Radio Access (FRA), New Radio (NR), New Radio Access (NX), Future Generation Radio Access (FX), 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 The system may include at least one of 802.20, Ultra-Wideband (UWB), Bluetooth (registered trademark), other suitable systems, and next-generation systems based on these systems that have been extended, modified, generated, or specified. Additionally, multiple systems may be combined (e.g., a combination of at least one of LTE and LTE-A with 5G, etc.) for application.

[0138] The processing procedures, timing, and flow of the various forms / implementations described in this disclosure may be changed in order, provided there is no contradiction. For example, the elements of various steps are indicated using an illustrative order in the methods described in this disclosure, but are not limited to the specific order indicated.

[0139] In this disclosure, certain actions performed by the base station are sometimes also performed by its upper node, depending on the circumstances. In a network consisting of one or more network nodes having a base station, it is obvious that various actions performed to communicate with a terminal can be performed by at least one of the base station and other network nodes besides the base station (e.g., considering an MME or S-GW, but not limited to these). The above illustration depicts a case where there is only one other network node besides the base station, but it can also be a combination of multiple other network nodes (e.g., an MME and an S-GW).

[0140] It can output information and signals (information, etc.) from a higher (or lower) level to a lower (or higher) level. It can also be input or output through multiple network nodes.

[0141] Input or output information can be stored in a specific location (e.g., memory) or managed using a management table. Input or output information can be overwritten, updated, or appended. Output information can also be deleted. Input information can also be sent to other devices.

[0142] The determination can be made by the value represented by 1 bit (0 or 1), by a Boolean value (Boolean: true or false), or by comparing numerical values ​​(e.g., comparing with a predetermined value).

[0143] The various forms / implementations described in this disclosure can be used individually or in combination, and can be switched depending on the execution. Furthermore, the notification of predetermined information (e.g., a "It is X" notification) is not limited to being explicit, but can also be implicit (e.g., not notifying the predetermined information).

[0144] Software, whether called software, firmware, middleware, microcode, hardware description language, or by other names, should be broadly interpreted as referring to commands, command sets, code, code segments, program code, programs, subroutines, software modules, applications, software applications, software packages, routines, subroutines, objects, executable files, execution threads, procedures, functions, etc.

[0145] In addition, software, commands, information, etc., can be sent and received via a transmission medium. For example, when software is sent from a webpage, server, or other remote source using at least one of wired technologies (coaxial cable, fiber optic cable, twisted pair, Digital Subscriber Line (DSL) etc.) and wireless technologies (infrared, microwave, etc.), at least one of these wired and wireless technologies is included within the definition of a transmission medium.

[0146] The information, signals, etc., described in this disclosure can also be represented using any of a variety of different technologies. For example, the data, commands, instructions, information, signals, bits, symbols, chips, etc., that may be involved in the above description can be represented by voltage, current, electromagnetic waves, magnetic fields or magnetic particles, light fields or photons, or any combination of these.

[0147] Furthermore, the terms used in this disclosure and those necessary for understanding this disclosure may be replaced with terms that have the same or similar meanings. For example, at least one of the channel and symbol may also be a signal (signaling). Additionally, a signal may also be a message. Furthermore, a component carrier (CC) may also be referred to as carrier frequency, cell, frequency carrier, etc.

[0148] The terms “system” and “network” as used in this disclosure are used interchangeably.

[0149] Furthermore, the information, parameters, etc., described in this disclosure can be represented using absolute values, relative values ​​to predetermined values, or other corresponding information. For example, wireless resources can be indicated using indexes.

[0150] The names used for the above parameters are non-limiting in any respect. Furthermore, the formulas, etc., using these parameters sometimes differ from those explicitly disclosed in this disclosure. Various channels (e.g., PUCCH, PDCCH, etc.) and information elements can be identified by all appropriate names, therefore the various names assigned to these channels and information elements are non-limiting in any respect.

[0151] In this disclosure, the terms "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" are used interchangeably. Sometimes, terms such as macro cell, small cell, femtocell, and picocell are also used to refer to base stations.

[0152] 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, each of which can also provide communication services through a base station subsystem (e.g., a small indoor base station (Remote Radio Head: RRH)). The terms "cell" or "sector" refer to a portion or the entire coverage area of ​​at least one of the base station and base station subsystem providing communication services within that coverage area.

[0153] In this disclosure, the base station sending information to the terminal can also be replaced by the base station instructing the terminal on information-based control / actions.

[0154] In this disclosure, the terms "terminal", "user terminal", "mobile station (MS)" and "user equipment (UE)" are used interchangeably.

[0155] For mobile stations, those skilled in the art sometimes also use the following terms: 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, handheld device, user agent, mobile client, client, or some other appropriate terms.

[0156] At least one of the base station and mobile station can also be referred to as a transmitting device, receiving device, communication device, etc. Furthermore, at least one of the base station and mobile station can also be a device mounted on a mobile body, the mobile body itself, etc. The mobile body refers to a movable object with an arbitrary speed of movement. It also includes situations where the mobile body is stationary. Examples of mobile bodies include, but are not limited to, vehicles, transport vehicles, automobiles, motorcycles, bicycles, connected cars, excavators, bulldozers, wheel loaders, dump trucks, forklifts, trains, buses, rear cars, rickshaws, ships (ships and other watercraft), airplanes, rockets, artificial satellites, Drone (registered trademark), multi-rotor helicopters, quadcopter helicopters, balloons, and objects mounted on them. Additionally, the mobile body can also be a mobile body that moves autonomously based on operating commands. It can be a means of transportation (e.g., car, airplane), a mobile body that moves unmanned (e.g., drone, autonomous vehicle), or a robot (humanized or unmanned). Furthermore, at least one of the base station and mobile station also includes devices that do not necessarily move during communication operations. For example, at least one of the base station and the mobile station can be an IoT (Internet of Things) device such as a sensor.

[0157] Furthermore, the base station in this disclosure can also be replaced by a terminal. For example, various forms / implementations of this disclosure can be applied to a structure that replaces the communication between the base station and the terminal with communication between multiple terminals (e.g., also referred to as D2D (Device-to-Device), V2X (Vehicle-to-Everything), etc.). In this case, the terminal 200 can also be configured to have the functions of the base station 100 described above. In addition, terms such as "uplink" and "downlink" can be replaced with terms corresponding to communication between terminals (e.g., "side"). For example, uplink channel, downlink channel, etc., can also be replaced with side channel.

[0158] Similarly, the terminal in this disclosure can also be replaced by a base station. In this case, the base station 100 can also be configured to have the functions of the terminal 200 described above.

[0159] Figure 10 An example of the structure of vehicle 2001 is shown. For example... Figure 10As shown, the vehicle 2001 includes a drive unit 2002, a steering unit 2003, an accelerator pedal 2004, a brake pedal 2005, a gear 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.

[0160] The drive unit 2002 may consist of, for example, an engine, a motor, or a hybrid power system of an engine and a motor.

[0161] The steering unit 2003 includes at least a steering wheel (also called a steering wheel) 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.

[0162] The electronic control unit 2010 consists of a microprocessor 2031, a memory (ROM, RAM) 2032, and a communication port (I / O port) 2033. Signals from various sensors 2021 to 2027 of the vehicle are input to the electronic control unit 2010. The electronic control unit 2010 can also be referred to as an Electronic Control Unit (ECU).

[0163] The signals from various sensors 2021 to 2029 include current signals from current sensor 2021 that senses the current of the motor, speed signals of the front and rear wheels obtained by speed sensor 2022, air pressure signals of the front and rear wheels obtained by air pressure sensor 2023, vehicle speed signals obtained by vehicle speed sensor 2024, acceleration signals obtained by acceleration sensor 2025, accelerator pedal input signals obtained by accelerator pedal sensor 2029, brake pedal input signals obtained by brake pedal sensor 2026, gear lever operation signals obtained by gear lever sensor 2027, and detection signals obtained by object detection sensor 2028 for detecting obstacles, vehicles, pedestrians, etc.

[0164] The Information Service Unit 2012 consists of various devices such as a car navigation system, audio system, speakers, television, and radio, which provide (output) various information such as driving information, traffic information, and entertainment information, and one or more ECUs that control these devices. The Information Service Unit 2012 uses information obtained from external devices via communication modules 2013, etc., to provide various multimedia information and multimedia services to the occupants of the vehicle 2001.

[0165] The Information Services Department 2012 may include input devices that accept input from external sources (e.g., keyboard, mouse, microphone, switch, button, sensor, touch panel, etc.) and output devices that implement output to external sources (e.g., monitor, speaker, LED light, touch panel, etc.).

[0166] The Driver Assistance System 2030 comprises various devices used to prevent accidents or reduce driver workload, such as millimeter-wave radar, LiDAR (Light Detection and Ranging), cameras, positioning devices (e.g., GNSS), map information (e.g., high-definition (HD) maps, autonomous vehicle (AV) maps), gyroscope 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. Furthermore, the Driver Assistance System 2030 transmits and receives various information via the communication module 2013 to achieve driver assistance or autonomous driving functions.

[0167] The communication module 2013 can communicate with the microprocessor 2031 and the components of the vehicle 2001 via the communication port. For example, the communication module 2013 can send and receive data with the drive unit 2002, steering unit 2003, accelerator pedal 2004, brake pedal 2005, gear shift lever 2006, left and right front wheels 2007, left and right rear wheels 2008, axle 2009, microprocessor 2031 in the electronic control unit 2010, memory (ROM, RAM) 2032, and sensors 2021 to 2029 in the vehicle 2001 via the communication port 2033.

[0168] The communication module 2013, controlled by the microprocessor 2031 of the electronic control unit 2010, is a communication device capable of communicating with external devices. For example, it can transmit and receive various types of information with external devices via wireless communication. The communication module 2013 can be located inside or outside the electronic control unit 2010. External devices can be, for example, base stations, mobile stations, etc.

[0169] The communication module 2013 can wirelessly transmit to an external device at least one of the signals input to the electronic control unit 2010 from the various sensors 2021-2029, information obtained based on those signals, and information obtained via the information service unit 2012 based on input from an external source (user). The electronic control unit 2010, the various sensors 2021-2029, and the information service unit 2012 can also be referred to as input units that receive input. For example, the PUSCH transmitted by the communication module 2013 can contain information based on the aforementioned input.

[0170] The communication module 2013 receives various information (traffic information, signal information, inter-vehicle information, etc.) sent from external devices and displays it on the information service unit 2012 provided by the vehicle. The information service unit 2012 can also be referred to as an output unit that outputs information (for example, outputs information to devices such as displays and speakers based on the PDSCH received by the communication module 2013 (or the data / information decoded from the PDSCH).

[0171] In addition, the communication module 2013 stores various information received from external devices in a memory 2032 available to the microprocessor 2031. The microprocessor 2031 can also control the drive unit 2002, steering unit 2003, accelerator pedal 2004, brake pedal 2005, gear shift lever 2006, left and right front wheels 2007, left and right rear wheels 2008, axles 2009, sensors 2021 to 2029, etc., of the vehicle 2001 based on the information stored in the memory 2032.

[0172] As used in this disclosure, terms such as "determining" and "determining" sometimes encompass a variety of actions. For example, "determining" or "determining" may include actions such as judging, calculating, computing, processing, deriving, investigating, searching (e.g., searching in a table, database, or other data structure), and ascertaining, which are considered as actions of "determining" or "determining." Furthermore, "determining" or "determining" may include actions such as receiving (e.g., receiving information), transmitting (e.g., sending information), inputting, outputting, and accessing (e.g., accessing data in memory), which are considered as actions of "determining" or "determining." Additionally, "determining" or "determining" may include actions such as resolving, selecting, choosing, establishing, and comparing, which are considered as actions of "determining" or "determining." That is, "judgment" and "decision" can include matters that are considered as having been "judged" or "decided". In addition, "judgment (decision)" can also be replaced by "assuming", "expecting", "considering", etc.

[0173] The terms “connected,” “coupled,” or any variations thereof are intended to indicate any direct or indirect connection or combination between two or more elements, including cases where there is one or more intermediate elements between the two elements that are “connected” or “coupled.” The combination or connection between elements can be physical, logical, or a combination of these. For example, “access” can be used instead of “connected.” In the context of this disclosure, it can be understood that two elements are “connected” or “coupled” to each other using at least one of one or more wires, cables, and printed electrical connections, and, as some non-limiting and non-inclusive examples, using electromagnetic energy with wavelengths in the wireless frequency domain, microwave region, and light (including both visible and invisible regions) to “connect” or “couple” to each other.

[0174] The reference signal can also be abbreviated as RS, or, depending on the standard applied, as a pilot.

[0175] As used in this disclosure, the word "based on" does not mean "based on only" unless otherwise expressly stated. In other words, the word "based on" means both "based on only" and "based on at least".

[0176] Any reference to elements using the designations "first," "second," etc., as used in this disclosure does not necessarily limit the number or order of these elements. These designations may be used in this disclosure as a convenient method of distinguishing between two or more elements. Therefore, references to the first and second elements do not imply that only two elements can be taken, or that the first element must precede the second element in any form.

[0177] Alternatively, the "unit" in the structure of the above devices can be replaced with "section", "circuit", "equipment", etc.

[0178] When the terms "include," "including," and their variations are used in this disclosure, these terms, like the term "comprising," imply inclusion. Furthermore, the term "or" as used in this disclosure does not refer to XOR.

[0179] A radio frame can consist of one or more frames in the time domain. Each frame in the time domain can be called a subframe. A subframe can also consist of one or more time slots in the time domain. A subframe can be a fixed duration (e.g., 1 ms) independent of the parameter set (numerology).

[0180] A parameter set can be communication parameters applied to at least one of the transmission and reception of a signal or channel. For example, a parameter set can represent at least one of the following: Subcarrier Spacing (SCS), bandwidth, symbol length, cyclic prefix length, Transmission Time Interval (TTI), number of symbols per TTI, radio frame structure, specific filtering processing performed by the transceiver in the frequency domain, and specific windowing processing performed by the transceiver in the time domain.

[0181] In the time domain, a time slot can be composed of one or more symbols (OFDM (Orthogonal Frequency Division Multiplexing) symbols, SC-FDMA (Single Carrier Frequency Division Multiple Access) symbols, etc.). A time slot can be a time unit based on a set of parameters.

[0182] A time slot can contain multiple mini-time slots. Each mini-time slot can consist of one or more symbols in the time domain. Additionally, a mini-time slot can also be called a sub-time slot. A mini-time slot can consist of fewer symbols than a time slot. PDSCH (or PUSCH) transmitted in time units larger than mini-time slots can be called PDSCH (or PUSCH) mapping type (type) A. PDSCH (or PUSCH) transmitted using mini-time slots can be called PDSCH (or PUSCH) mapping type (type) B.

[0183] Radio frames, subframes, time slots, mini-time slots, and symbols all represent time units for transmitting signals. Radio frames, subframes, time slots, mini-time slots, and symbols can each be referred to by other corresponding names.

[0184] For example, a single subframe can be called a Transmission Time Interval (TTI), multiple consecutive subframes can also be called a TTI, and a single time slot or a single mini-time slot can also be called a TTI. In other words, at least one of a subframe or TTI can be a subframe (1ms) in existing LTE, a period shorter than 1ms (e.g., symbols 1-13), or a period longer than 1ms. Furthermore, the unit representing TTI can also be called a time slot, mini-time slot, etc., instead of a subframe.

[0185] Here, TTI refers, for example, to the smallest unit of time for scheduling in wireless communication. For instance, in an LTE system, the base station schedules the allocation of radio resources (bandwidth, transmit power, etc., available to each terminal) to each terminal in units of TTI. However, the definition of TTI is not limited to this.

[0186] The Time Interval (TTI) can be a unit of time for transmitting channel-coded data packets (transmission blocks), code blocks, codewords, etc., or it can be a processing unit such as scheduling or link adaptation. Furthermore, when a TTI is given, the actual time interval (e.g., the number of symbols) that the transmission block, code block, codeword, etc., are mapped to can be shorter than that TTI.

[0187] Furthermore, when one time slot or one mini time slot is referred to as a TTI, more than one TTI (i.e., more than one time slot or more than one mini time slot) can become the minimum time unit for scheduling. In addition, the number of time slots (mini time slots) constituting the minimum time unit for scheduling can also be controlled.

[0188] A TTI with a duration of 1ms can also be called a normal TTI (TTI in LTE Rel.8-12), a long TTI, a normal subframe, a long subframe, or a time slot. A TTI shorter than a normal TTI can also be called a shortened TTI, a short TTI, a partial or fractional TTI, a shortened subframe, a short subframe, a mini time slot, a sub-time slot, or a time slot.

[0189] Furthermore, for long TTIs (e.g., normal TTIs, subframes, etc.), they can be replaced with TTIs with a duration of more than 1ms. For short TTIs (e.g., shortened TTIs, etc.), they can be replaced with TTIs with a duration of less than long TTIs but more than 1ms.

[0190] A resource block (RB) is a unit of resource allocation in both the time and frequency domains. In the frequency domain, it can contain one or more consecutive subcarriers. The number of subcarriers contained in an RB can be the same regardless of the parameter set, for example, it can be 12. The number of subcarriers contained in an RB can also be determined based on the parameter set.

[0191] In addition, the time domain of an RB can contain one or more symbols, which can be a time slot, a mini time slot, a subframe, or a TTI in length. A TTI, a subframe, etc., can each be composed of one or more resource blocks.

[0192] In addition, one or more RBs can also be called Physical Resource Block (PRB), Sub-Carrier Group (SCG), Resource Element Group (REG), PRB pair, RB pair, etc.

[0193] In addition, a resource block can consist of one or more resource elements (REs). For example, one RE can be a radio resource area consisting of one subcarrier and one symbol.

[0194] The Bandwidth Part (BWP) (also known as partial bandwidth, etc.) can represent a subset of contiguous common resource blocks (RBs) used for a certain parameter set in a given carrier. Here, common RBs can be determined by indexing RBs based on a common reference point of that carrier. PRBs can be defined and numbered within a BWP.

[0195] A BWP can include a UL BWP and a DL BWP. One or more BWPs can be set for a UE within a single carrier.

[0196] At least one of the configured BWPs can be active, and the UE may not intend to transmit or receive predetermined signals / channels outside of the active BWP. Furthermore, the terms "cell," "carrier," etc., used in this disclosure can be replaced with "BWP."

[0197] The structures of radio frames, subframes, time slots, mini-time slots, and symbols described above are merely illustrative. For example, the number of subframes contained in a radio frame, the number of time slots in each subframe or radio frame, the number of mini-time slots contained within a time slot, the number of symbols and RBs contained in a time slot or mini-time slot, the number of subcarriers contained in an RB, the number of symbols in a TTI, the symbol length, the cyclic prefix (CP) length, and other structures can be varied in many ways.

[0198] The term "maximum transmit power" as used in this disclosure may refer to the maximum value of the transmit power, the nominal maximum transmit power, or the rated maximum transmit power.

[0199] In this disclosure, for example, in cases where articles are added through translation, such as in English (e.g., a, an, and the), this disclosure may also include cases where the noun following these articles is in a plural form.

[0200] In this disclosure, the phrase "A and B are different" can mean "A and B are not the same." Furthermore, this phrase can also mean "A and B are each different from C." Terms such as "separate" and "combined" can also be interpreted in the same way as "different."

[0201] The present disclosure has been described in detail above, but 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 as modifications and variations without departing from the spirit and scope of the present disclosure as defined by the claims. Therefore, the present disclosure is for illustrative purposes only and is not intended to be limiting.

[0202] (Postscript)

[0203] The aforementioned disclosure can also be expressed as follows.

[0204] The first feature is a terminal comprising: a control unit that uses a learning model to calculate a predicted value of cell quality and compares the predicted value with a threshold; and a transmission unit that, based on the comparison by the control unit, transmits a measurement report related to the cell quality, wherein the control unit compares the predicted value and the threshold by adding an offset value to either one.

[0205] The second feature is that, in the first feature, the transmitting unit transmits the measurement report together with information related to the time or period of the transmission timing of the measurement report.

[0206] The third feature is that, in the first or second feature, the control unit uses the learning model to change the offset value.

[0207] The fourth feature is a terminal comprising: a receiving unit that receives a threshold for performing autonomous handover; and a control unit that uses a learning model to calculate a predicted value of cell quality and compares the predicted value with the threshold, wherein the control unit adds an offset value to either the predicted value or the threshold for comparison.

[0208] The fifth feature is that, in the fourth feature, the control unit uses the learning model to predict the execution timing for performing the switch, and performs the switch at the execution timing.

[0209] The sixth feature is that, in the fourth or fifth feature, the control unit uses the learning model to change the offset value.

[0210] Label Explanation

[0211] 10: Wireless Communication System

[0212] 20: NG-RAN

[0213] 100: Base station

[0214] 110: Wireless Signal Transceiver Unit

[0215] 120: Control Department

[0216] 200: Terminal

[0217] 210: Wireless Signal Transceiver Unit

[0218] 220: Enlarged section

[0219] 230: Modulation and Demodulation Section

[0220] 240: Control Signal & Reference Signal Processing Unit

[0221] 250: Encoding / Decoding Section

[0222] 260: Data Transceiver Department

[0223] 270: Control Department

[0224] 1001: Processor

[0225] 1002: Memory

[0226] 1003: Storage device

[0227] 1004: Communication device

[0228] 1005: Input device

[0229] 1006: Output device

[0230] 1007: Bus

[0231] 2001: Vehicles

[0232] 2002: Drive Unit

[0233] 2003: Steering Unit

[0234] 2004: Accelerator Pedal

[0235] 2005: Brake Pedal

[0236] 2006: Gear Shift

[0237] 2007: Left and right front wheels

[0238] 2008: Left and right rear wheels

[0239] 2009: Axle

[0240] 2010: Electronic Control Department

[0241] 2012: Information Services Department

[0242] 2013: Communication Module

[0243] 2021: Current Sensor

[0244] 2022: Speed ​​Sensor

[0245] 2023: Barometric Pressure Sensor

[0246] 2024: Vehicle Speed ​​Sensor

[0247] 2025: Accelerometer

[0248] 2026: Brake Pedal Sensor

[0249] 2027: Gearshift Sensor

[0250] 2028: Object Detection Sensor

[0251] 2029: Accelerator Pedal Sensor

[0252] 2030: Driver Assistance Systems Department

[0253] 2031: Microprocessors

[0254] 2032: Memory (ROM, RAM)

[0255] 2033: Communication port (IO port)

Claims

1. A terminal, comprising: The control unit uses a learning model to calculate predicted values ​​for cell quality and compares these predicted values ​​with thresholds; and The transmitting unit, based on the comparison made by the control unit, transmits a measurement report related to the cell quality. The control unit compares the predicted value and any one of the threshold values ​​by adding an offset value.

2. The terminal according to claim 1, wherein, The transmitting unit sends the measurement report along with information related to the time or period during which the measurement report is transmitted.

3. The terminal according to claim 1, wherein, The control unit uses the learning model to change the offset value.

4. A terminal, comprising: The receiving unit receives a threshold for performing autonomous handover; and The control unit uses a learning model to calculate predicted values ​​for cell quality and compares these predicted values ​​with the threshold. The control unit compares the predicted value and any one of the threshold values ​​by adding an offset value.

5. The terminal according to claim 4, wherein, The control unit uses the learning model to predict the execution timing for the switch, and performs the switch at the specified execution timing.

6. The terminal according to claim 4, wherein, The control unit uses the learning model to change the offset value.

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