Terminal, communication method, and computer-readable recording medium

Abstract

To enhance reporting of radio qualities in a terminal.SOLUTION: For a predetermined cell or beam in a learning phase, for a learned model acquired by machine learning in which a result of first measurement of wireless quality at a first timing is used as input and a result of second measurement of wireless quality at one or more second timings after a predetermined period from the first timing is used as teacher data, A terminal apparatus having a function of estimating radio quality at each of one or more timings after a predetermined timing by inputting a result of measurement of radio quality at a predetermined timing of a predetermined cell or beam in an inference phase transmits, to a base station apparatus being connected, a report including a value indicating an estimated value of radio quality output from a learned model for the predetermined cell or beam and information indicating which timing after the predetermined timing the estimated value corresponds to.SELECTED DRAWING: Figure 5

Description

[Technical Field]

[0001] The present invention relates to techniques for reporting radio quality in cellular communication systems. [Background technology]

[0002] In a wireless communication system compliant with the 3rd Generation Partnership Project (3GPP (registered trademark)) cellular communication standard, a terminal device measures the wireless quality of surrounding cells (beams) and continues to connect to a base station device that provides a cell with good wireless quality. To achieve this, the terminal device reports the measurement results of the wireless quality of surrounding cells (beams) to the base station device to which it is currently connected, and the base station device transmits to the terminal device an instruction to switch the cell (beam) to which the terminal device should connect as necessary. This allows the terminal device to be provided with a continuously good-quality communication service. Summary of the Invention [Problem to be solved by the invention]

[0003] In recent years, there has been an increasing demand for improved communication quality and throughput in cellular communication systems. To meet such demands, it is important to improve the measurement of wireless quality in terminal devices and the reporting of the results to base station devices. [Means for solving the problem]

[0004] The present invention provides a technique for enhancing reporting of wireless quality in terminal devices.

[0005] A terminal device according to one embodiment of the present invention has an estimation means for inputting the result of a first measurement of wireless quality at a first timing for a specified cell or beam into a trained model obtained by machine learning in a learning phase, using as input the result of a first measurement of wireless quality at one or more second timings a specified period after the first timing, as training data, in an inference phase, thereby estimating wireless quality at each of one or more timings a specified period after the specified timing; and a transmission means for transmitting to a connected base station device a report including a value indicating an estimated value of wireless quality output from the trained model for the specified cell or beam and information indicating which timing after the specified timing the estimated value corresponds to.

[0006] A base station device according to one embodiment of the present invention has a connection means for connecting to a terminal device capable of estimating wireless quality at each of one or more timings after a predetermined period from a predetermined timing by inputting the result of a first measurement of wireless quality at a first timing for a predetermined cell or beam into a trained model obtained by machine learning in a learning phase, using as input the result of a first measurement of wireless quality at a first timing and the result of a second measurement of wireless quality at one or more second timings after the first timing as training data, in an inference phase; and a receiving means for receiving from the terminal device a report including a value indicating an estimated value of wireless quality output from the trained model for the predetermined cell or beam and information indicating which timing after the predetermined timing the estimated value corresponds to. [Effects of the Invention]

[0007] According to the present invention, it is possible to improve the reporting of wireless quality in a terminal device. [Brief explanation of the drawings]

[0008] [Figure 1] FIG. 1 is a diagram illustrating an example of the configuration of a wireless communication system. [Figure 2] FIG. 2 is a diagram illustrating an example of the hardware configuration of a base station device and a terminal device. [Figure 3] FIG. 2 is a diagram illustrating an example of a functional configuration of a terminal device. [Figure 4] FIG. 2 is a diagram illustrating an example of a functional configuration of a base station device. [Figure 5] FIG. 1 is a diagram illustrating an example of a flow of processing executed in a wireless communication system. DETAILED DESCRIPTION OF THE INVENTION

[0009] Hereinafter, the embodiments will be described in detail with reference to the accompanying drawings. Note that the following embodiments do not limit the scope of the invention as claimed, and not all combinations of features described in the embodiments are necessarily essential to the invention. Two or more of the features described in the embodiments may be combined in any desired manner. Furthermore, the same reference numerals are used to designate identical or similar components, and redundant descriptions will be omitted.

[0010] (System Configuration) FIG. 1 shows an example of the configuration of a communication system according to this embodiment. This communication system is a wireless communication system that complies with, for example, the Long Term Evolution (LTE) or fifth generation (5G) cellular communication standards of the Third Generation Partnership Project (3GPP (registered trademark)) or their successor standards. This wireless communication system includes a base station device 101 and a terminal device 111. The terminal device 111 establishes a connection with the base station device 101 and performs wireless communication in a cell 121 provided by the base station device 101. The terminal device 111 is assumed to be, for example, portable by a user and to be mobile. If the terminal device 111 moves beyond the range of the cell 121 while performing communication in the cell 121, it is assumed that the terminal device 111 will perform a handover to another cell (cell 122 or cell 123). For such a handover, conventionally, the terminal device 111 measures the wireless quality of other cells adjacent to the cell to which it is currently connected and reports the measured wireless quality to the base station device 101. The term "cell" used in this embodiment may be read as "beam" unless otherwise specified.

[0011] In recent years, the application of artificial intelligence (AI) / machine learning (ML) to cellular communication systems has been discussed. For example, the use of AI / ML can estimate the wireless quality of neighboring cells based on the wireless quality of a currently connected cell. For example, a trained model can be acquired by machine learning using, as input, a first measurement result of the wireless quality of a first cell or beam whose wireless quality is to be measured in a learning phase and a second measurement result of the wireless quality of a second cell or beam different from the first cell or beam as training data. In this case, by inputting the measurement result of the wireless quality of the first cell or beam to this trained model in an inference phase, it becomes possible to estimate the wireless quality of the second cell or beam.

[0012] Furthermore, in the learning phase, a trained model can be acquired by machine learning using as input the result of a first measurement of wireless quality at a first timing for a specific cell or beam, and as training data the result of a second measurement of wireless quality at one or more (in one example, multiple) second timings a specific period after the first timing. Then, in this inference phase, by inputting the result of the measurement of wireless quality at a specific timing for the specific cell or beam to the trained model, it becomes possible to estimate wireless quality at each of multiple timings a specific period after (in the future) the specific timing.

[0013] Furthermore, in the learning phase, a trained model can be acquired by machine learning using as input a result of a first measurement of wireless quality at a first timing for a first cell or beam, and as training data a result of a second measurement of wireless quality for a second cell at one or more (in one example, multiple) second timings a predetermined period after the first timing. Then, in this inference phase, by inputting the result of the measurement of wireless quality at a predetermined timing for the first cell or beam to the trained model, it becomes possible to estimate the wireless quality for the second cell or beam at each of multiple timings a predetermined period after (in the future) the predetermined timing.

[0014] Furthermore, the measurement result used as input may be a single value at one timing, or a series (time series) of measurement results at multiple timings. If measurement results at multiple timings are used as input in the learning phase, measurement results obtained at multiple timings with the same time intervals as the multiple timings in the learning phase will also be used as input in the inference phase.

[0015] In this way, by utilizing AI / ML, it is possible to measure the wireless quality of some cells to obtain estimates of the wireless quality of other cells, and also to obtain estimates of the wireless quality of the currently connected cell or other adjacent cells at a future time.

[0016] Conventionally, the base station device 101 notifies the terminal device 111 of configuration information specifying target cells for measuring and reporting radio quality, and the terminal device 111 measures and reports radio quality based on the configuration information. The configuration information includes, for example, a measObject related to information on reference signals and carrier frequencies for specifying measurement targets, and a reportConfig which is a configuration related to reporting. This configuration information is notified from the base station device 101 to the terminal device 111 via a radio resource control (RRC) message such as an RRC Reconfiguration message. The configuration information usually includes information in which identification information (measID) of the configuration information, a measObjectID specifying the measurement configuration (measObject), and a reportConfigID specifying the report configuration (reportConfig) are associated with each other. That is, a separate measObjectID is assigned to each of one or more measurement configurations (measObject), and a reportConfigID is assigned to each of one or more report configurations (reportConfig), and the measurement configuration and the report configuration are associated with each other by associating and specifying one measObjectID with one reportConfigID. Then, a measID is assigned to the combination that associates the measurement configuration and the report configuration. Conventionally, one measID is always associated with one measObjectID and one reportConfigID. In other words, the measObjectID and the reportConfigID are essential information elements and are not permitted to be omitted. The terminal device 111 measures the wireless quality based on the measurement configuration identified by the measObjectID, and reports the measurement results using the report configuration specified by the reportConfigID associated with the measObjectID.In addition, the terminal device 111 includes a measID in the measurement result report message (Measurement Report) to specify which setting the measurement result is based on, and in this way the base station device 101 can identify which setting information the measurement result information received from the terminal device 111 is based on.

[0017] On the other hand, when AI / ML is used, it is assumed that an estimated value of wireless quality for a cell that is not measured will be obtained, as described above. That is, in the terminal device 111, an estimated value of wireless quality for a cell for which no measObject is set will be generated. Meanwhile, since no measObject is set for that cell, no measObjectID is assigned, and as a result, no corresponding measID exists. For this reason, in the conventional framework, the terminal device 111 cannot report the estimated value of wireless quality to the base station device 101.

[0018] In view of the above circumstances, this embodiment provides a technique that enables the terminal device 111 to transmit an estimated value of wireless quality to the base station device 101.

[0019] As an example, in this embodiment, as in the conventional case, the base station device 101 transmits to the terminal device 111 configuration information related to measurements and reports for a cell whose wireless quality is to be measured. That is, configuration information in which a measObjectID, a reportConfigID, and a measID are associated with each other for a cell whose wireless quality is to be measured is notified from the base station device 101 to the terminal device 111. On the other hand, for a cell whose wireless quality is to be estimated by inputting measurement results of other cells into a trained model, configuration information in which a reportConfigID is associated with a measID and no measObjectID is notified from the base station device 101 to the terminal device 111. That is, the measObjectID, which was previously a required information item, is made optional, and it is possible to omit this information item for cells whose wireless quality is not to be measured. This makes it possible to report an estimated value for a cell for which no measurement is performed and for which no measObject is set. Note that which cell the configuration information, which is associated with the measID and reportConfigID but not associated with the measObjectID, is associated with can be identified, for example, by a trained model for obtaining an estimated value of wireless quality. That is, when a target cell for wireless quality estimation using a trained model is uniquely determined, an estimated value of wireless quality for that cell is reported from the terminal device 111 to the base station device 101 based on the configuration information, which is not associated with the measObjectID.

[0020] On the other hand, when estimates of radio quality for multiple cells are reported, a separate reporting configuration may be prepared for each cell. In this case, information for identifying a cell for which radio quality is estimated may be associated with a measID and a reportConfigID and notified to the terminal device 111. For example, configuration information for a cell for which radio quality is measured may be notified to the terminal device 111 by associating an item measObjectID with a measID and a reportConfigID, and by associating an item named predictObjectID with a measID and a reportConfigID, respectively. The item predictObjectID may include, for example, a cell identifier (such as a physical cell identifier). Note that this item name is merely an example shown for illustrative purposes, and other item names may be used. Furthermore, for example, when estimates of radio quality for different cells are obtained in multiple trained models, information identifying the trained models may be used as information for identifying a cell for which radio quality is estimated. That is, when multiple trained models are each associated with one cell, identifying one trained model can identify which cell an estimate is obtained for by that trained model.

[0021] For a first cell in which a measObject is set and a measObjectID associated with a measID is specified, the terminal device 111 measures radio quality by observing a reference signal (for example, a synchronization signal (SS) / physical broadcast channel (PBCH) block (SSB) or a channel state information-reference signal (CSI-RS)) specified in the measObject. Then, the terminal device 111 sets the (cell-level) radio quality in cellResults (resultSSB-Cell, resultCSI-RS-Cell) of MeasResults. Note that, when reporting beam-level radio quality, the terminal device 111 sets the radio quality in rsIndexResults (resultSSB-Indexes, resultCSI-RS-Indexes) of MeasResults. Then, the terminal device 111 reports the value set in MeasResults to the base station device 101 using the report configuration indicated by reportConfig associated with the measID.

[0022] On the other hand, the terminal device 111 does not measure the radio quality of a second cell for which a measObject is not set and for which a measObjectID associated with a measID is not specified. The terminal device 111 inputs the radio qualities of other cells to a trained model that can output an estimated value of the radio quality for that cell. Then, the terminal device 111 acquires the estimated value of the radio quality for that second cell as an output from the trained model. The terminal device 111 then sets the (cell-level) radio quality in cellResults(resultSSB-Cell, resultCSI-RS-Cell) of MeasResults. Note that, when reporting beam-level radio quality, the terminal device 111 sets the radio quality in rsIndexResults(resultSSB-Indexes, resultCSI-RS-Indexes) of MeasResults. Then, the terminal device 111 reports the value set in MeasResults to the base station device 101 using the reporting configuration indicated by reportConfig associated with the measID. In addition, the value of measID is stored in MeasResults to indicate which setting the report is based on.

[0023] In this way, the base station device 101 generates first information associating measID, measObjectID, and reportConfigID for a first cell for which wireless quality measurement is to be performed, and generates second information associating measID with reportConfigID but not measObjectID for a second cell for which an estimated wireless quality value is to be obtained based on wireless quality measurement values ​​for other cells, and notifies the terminal device 111 of configuration information including the first information and second information. Based on this configuration information, the terminal device 111 measures wireless quality based on the configuration of measObject for the first cell for which the first information has been notified, and estimates wireless quality using AI / ML without measuring wireless quality for the second cell for which the second information has been notified. Then, the terminal device 111 reports the wireless quality measurement values ​​of the first cell to the base station device 101 based on reportConfig associated with the first information, using MeasResults including the measID associated with the first information. Furthermore, the terminal device 111 reports the estimated value of the wireless quality of the second cell to the base station device 101 based on the reportConfig associated with the second information, using MeasResults including the measID associated with the second information. This makes it possible to report the estimated value of the wireless quality for a cell for which no measurement target is configured, with minimal changes from the conventional measurement and reporting configuration.

[0024] Furthermore, when AI / ML is used, it is assumed that an estimated value of future wireless quality for a specific cell will be obtained, as described above. It is also assumed that multiple estimated values ​​of wireless quality for a specific cell at multiple future timings will be obtained. Meanwhile, conventionally, while it has been possible to report a wireless quality measurement value at a current timing for one cell, there has been no provision for reporting an estimated value of wireless quality at a future time point. Therefore, in the conventional framework, the terminal device 111 cannot report one or more estimated values ​​of wireless quality at that future time point to the base station device 101.

[0025] In this embodiment, in view of such circumstances, it is possible to report an estimated value of radio quality at a future time point. For example, in MeasResults, the item MeasQuantityResults that defines the contents of ResultsSSB-Cell (ResultsSSB-Indexes) or ResultsCSI-RS-Cell (ResultsCSI-RS-Indexes), which indicate measurement values, may be extended to include information indicating the timing at which the reported value corresponds. Note that this is just one example, and the timing at which the reported value corresponds may be indicated in an item other than MeasQuantityResults. Note that when multiple estimated values ​​are reported, multiple ResultsSSB-Cell (ResultsSSB-Indexes) or ResultsCSI-RS-Cell (ResultsCSI-RS-Indexes) may be listed in MeasResults to indicate each estimated value. Then, each of the multiple listed information elements may be used to report one estimated value, and timestamp information indicating the timing at which the estimated value corresponds may be stored in the information element. In one example, ResultsSSB-Cell (ResultsSSB-Indexes) or ResultsCSI-RS-Cell (ResultsCSI-RS-Indexes) that does not include timestamp information may be used in MeasResults to report the actually measured wireless quality instead of an estimated value. That is, when the base station device 101 receives information that does not include a timestamp, it may determine that the value indicated by the information is the actually measured wireless quality, and when the base station device 101 receives information that includes a timestamp, it may determine that the value indicated by the information is an estimated value of the wireless quality.

[0026] Note that, for example, when wireless quality is estimated at multiple timings, the timestamp may be indicated in units corresponding to the time intervals between the multiple timings. For example, when wireless quality is estimated based on SSBs, the multiple timings may be set at SSB periods. In this case, the timestamp may be indicated by the number of SSB periods. For example, the timing at which the SSB wireless quality is measured may be set as "0," the timestamp for the estimated value of wireless quality corresponding to the next SSB may be set as "1," and the timestamp for the estimated value of wireless quality corresponding to the SSB after that may be set as "2." Furthermore, the timestamp may be specified in units of time slots. Furthermore, for example, a combination of information indicating the earliest timing among the estimated values ​​of wireless quality and the time increment width of subsequent timings may be notified. For example, information specifying multiple timings collectively may be notified, such as the first timing being 20 milliseconds (ms) after a predetermined timing at which wireless quality is measured, followed by five estimates transmitted at 10 ms intervals.

[0027] The base station device 101 may notify the terminal device 111 in advance of information indicating the number of estimated values ​​to be reported among the estimated values ​​corresponding to different timings as configuration information. That is, configuration information specifying the number of pieces of information on radio quality to be transmitted together with information indicating future timings may be specified in, for example, ReportConfig.

[0028] In this way, it is possible to transmit to the base station device 101 an estimated value of wireless quality estimated by the terminal device 111 using AI / ML for each of one or more future timings. This enables the base station device 101 to perform, for example, early execution control of handover using the value of future wireless quality. Note that, in the above example, an example has been described in which the terminal device 111 acquires an estimated value of wireless quality for each of one or more future timings for the connected cell using AI / ML, but this is not limiting. For example, an estimated value of wireless quality for one or more future timings of another cell, such as a neighboring cell, may be acquired based on a measurement value of wireless quality in the connected cell, or an estimated value of wireless quality for one or more future timings of another cell may be acquired based on a measurement value of wireless quality in the other cell. Furthermore, an estimated value of wireless quality for one or more future timings of the connected cell may be acquired based on a measurement value of wireless quality in the other cell.

[0029] The terminal device 111 can notify the base station device 101 of information indicating whether or not it is possible to estimate radio quality using AI / ML, using information indicating its own capabilities (UE Capability). When the terminal device 111 is capable of estimating radio quality using AI / ML, the base station device 101 can notify the base station device 101 of the above-mentioned configuration information. That is, when the terminal device 111 is not capable of estimating radio quality using AI / ML, the base station device 101 transmits to the terminal device 111 configuration information that includes first information in which a measObjectID, a reportConfigID, and a measID are associated with each other, and does not include second information in which the reportConfigID and the measID are associated with each other but the measObjectID is not associated with each other. On the other hand, when the terminal device 111 is capable of estimating radio quality using AI / ML, the base station device 101 transmits to the terminal device 111 configuration information that includes first information on a cell that is a target for radio quality measurement and second information on a cell that is a target for radio quality estimation. This enables the base station device 101 to individually transmit appropriate configuration information in an environment where terminal devices capable of estimating wireless quality using AI / ML and terminal devices not capable of such estimation coexist.

[0030] The terminal device 111 may generate a trained model by performing machine learning, or may acquire a separately generated trained model from the base station device 101. When machine learning is performed in the terminal device 111, a trained model cannot be acquired until training data has been acquired a sufficient number of times, but a trained model suitable for the terminal device 111 can be acquired. On the other hand, when a trained model is provided from the base station device 101, a large amount of training data can be obtained from communications by a large number of terminal devices that have previously connected to the cell 121, thereby enabling learning to be completed quickly. The base station device 101 can also perform machine learning using, for example, a report of measurement results from a terminal device that is not capable of estimating wireless quality using AI / ML. The base station device 101 may also notify the terminal device 111 of information to be input into the provided trained model and information indicating the output of the trained model at that time. In accordance with the notification, the terminal device 111 may, for example, collect information to be input into the trained model provided from the base station device 101 (the wireless quality of the currently connected cell 121 or other cells) and input it into the trained model. Then, in accordance with the notification, the terminal device 111 may identify what kind of information is output from the trained model (for example, whether it is the wireless quality of another cell or the future wireless quality of the currently connected cell 121), and transmit a measurement result report in a format suitable for that output to the base station device 101. Furthermore, the terminal device 111 may perform machine learning in accordance with the notification.

[0031] Note that performance evaluation of the trained model may be performed periodically, for example. For example, the base station device 101 may notify the terminal device 111, which is capable of estimating wireless quality, of configuration information including both the first information and the second information for the cell for which wireless quality is to be estimated. The terminal device 111 then measures the wireless quality of the cell and estimates the wireless quality, and reports both to the base station device 101. The base station device 101 may then calculate the difference (error) between the actual measured value and the estimated value of the wireless quality, and if the error is equal to or greater than a predetermined value, may evaluate the trained model as unsuitable for the real environment and decide to perform re-learning (additional learning). Furthermore, if the difference between the estimated value and the actual measured value of the wireless quality for the maximum value or a predetermined number of cells from the highest value is equal to or greater than a predetermined value, the trained model may be evaluated as unsuitable for the real environment and re-learning may be performed. The base station device 101 then instructs, for example, a connected terminal device to measure and report the wireless quality of the cell to which the terminal device belongs and its neighboring cells, and performs re-learning of the trained model using the reported wireless quality. The base station device 101 may terminate re-learning when the error between the output of the trained model and the actually measured wireless quality becomes equal to or less than a predetermined level as a result of the re-learning. The base station device 101 may receive reports of wireless quality measurement results from terminal devices that do not estimate wireless quality, and periodically re-learn the trained model based on the measurement results. The base station device 101 notifies the terminal device 111 of the trained model after re-learning, and the terminal device 111 estimates wireless quality using the updated trained model after the notification. If the terminal device 111 has generated a trained model, it may notify the base station device 101 of the intention to perform this re-learning. Furthermore, the terminal device 111 may notify the base station device 101 that re-learning is necessary, and may perform re-learning upon receiving a predetermined instruction from the base station device 101. This allows the trained model to be maintained in an appropriate state, and makes it possible to execute handover processing based on predictions at appropriate times.

[0032] (Device configuration) FIG. 2 shows an example of the hardware configuration of the base station device 101 and the terminal device 111 according to this embodiment. In one example, the base station device 101 and the terminal device 111 are configured to include a processor 201, a ROM 202, a RAM 203, a storage device 204, and a communication circuit 205. The processor 201 is a computer configured to include one or more processing circuits, such as a general-purpose CPU (Central Processing Unit) or an ASIC (Application Specific Integrated Circuit), and executes the overall processing of the device and each of the above-mentioned processes by reading and executing programs stored in the ROM 202 or the storage device 204. The ROM 202 is a read-only memory that stores information such as programs and various parameters related to the processing executed by the base station device 101 and the terminal device 111. The RAM 203 functions as a workspace when the processor 201 executes a program and is a random access memory that stores temporary information. The storage device 204 is configured, for example, by a removable external storage device. The communication circuit 205 is configured, for example, by a circuit for wireless communication of 5G or its successor standards. Although FIG. 2 illustrates one communication circuit 205, the base station device 101 and the terminal device 111 may have multiple communication circuits. For example, the base station device 101 and the terminal device 111 may have wireless communication circuits for 5G and its successor standard, and a common antenna for these circuits. The base station device 101 and the terminal device 111 may have separate antennas suitable for each standard. The base station device 101 may also have a wired communication circuit used when communicating with other base station devices or nodes in the core network. The terminal device 111 may also have a communication circuit compliant with a wireless communication standard other than the cellular communication standard, such as a wireless local area network (LAN) or Bluetooth (registered trademark). The base station device 101 and the terminal device 111 may have separate communication circuits 205 for each of multiple available frequency bands, or may have a common communication circuit 205 for at least some of these frequency bands.

[0033] FIG. 3 shows an example of the functional configuration of the terminal device 111. The terminal device 111 includes, for example, a capability information notification unit 301, a setting information receiving unit 302, a quality measurement unit 303, a quality estimation unit 304, and a reporting unit 305. The terminal device 111 may also include, as an option, a learning unit 306. Note that FIG. 3 only shows functions particularly related to this embodiment, and does not illustrate various other functions that the terminal device 111 may have. For example, the terminal device 111 naturally has other functions that terminal devices conforming to LTE, 5G, or subsequent standards generally have. The functional blocks in FIG. 3 are shown schematically, and the respective functional blocks may be realized as an integrated unit or may be further subdivided. The functions in FIG. 3 may be realized, for example, by the processor 201 executing a program stored in the ROM 202 or the storage device 204, or by a processor within the communication circuit 205 executing predetermined software. The details of the processes executed by each functional unit have been described above, so only the general functions of the terminal device 111 will be outlined here.

[0034] The capability information notifying unit 301 notifies the base station device 101 of capability information possessed by the terminal device 111 as UE Capability. The capability information notifying unit 301 notifies the base station device 101, for example, of information indicating whether the terminal device 111 has the capability to estimate the wireless quality of some cells from the measurement values ​​of the wireless quality of other cells using AI / ML. Furthermore, the capability information notifying unit 301 notifies the base station device 101, for example, of information indicating whether the terminal device 111 has the capability to estimate the future wireless quality of a specific cell from the measurement values ​​of the wireless quality of the specific cell using AI / ML. The setting information receiving unit 302 receives setting information related to communication from the base station device 101. As described above, the setting information includes first information in which a measObjectID, a reportConfigID, and a measID for a cell for which wireless quality measurement is to be performed are associated with each other. In addition, when the terminal device 111 has the capability to acquire an estimated value of the wireless quality of a second cell by inputting a measured value of the wireless quality of a first cell into a trained model, the configuration information may include second information in which the reportConfigID is associated with the measID but the measObjectID is not associated. Also, when the terminal device 111 has the capability to specify the wireless quality of a specific cell at a future timing by inputting a measured value of the wireless quality of the specific cell into a trained model, the configuration information may include information for instructing notification of information associating the estimated value with the timing, and information indicating the number of estimated values ​​of the wireless quality to be notified among the estimated values ​​of the wireless quality corresponding to each different timing.

[0035] The quality measurement unit 303 measures the wireless quality of the connected first cell, etc., in accordance with the configuration information (measObject) identified by the measObjectID specified in the first information or the predetermined information among the configuration information received by the configuration information reception unit 302. The quality estimation unit 304 inputs the wireless quality of the first cell measured by the quality measurement unit 303 into the trained model, thereby obtaining an estimate of the wireless quality of the second cell or the wireless quality of the first cell at a future timing.

[0036] The reporting unit 305 reports the measurement values ​​and the estimated values ​​of the wireless quality to the base station device 101 based on the configuration information. The reporting unit 305 reports information on the measurement values ​​of the wireless quality, including the measID associated with the first information, to the base station device 101, using a reportConfig specified by a reportConfigID associated with the first information. Furthermore, the reporting unit 305 reports information on the estimated values ​​of the wireless quality, including the measID associated with the second information, to the base station device 101, using a reportConfig specified by a reportConfigID associated with the second information. Furthermore, the reporting unit 305 reports information indicating the estimated values ​​of the wireless quality at future timing, together with information that can identify the timing, to the base station device 101. Note that when the number of estimated values ​​of future wireless quality to be reported is specified by the base station device 101, the reporting unit 305 can generate MeasResults that lists the same number of cellResults or rsIndexResults indicating the wireless quality for the same cell, and report the generated MeasResults to the base station device 101. At this time, information indicating the timing can be stored in each of cellResults or rsIndexResults.

[0037] When a trained model needs to be generated in the terminal device 111, the learning unit 306 generates the trained model by machine learning. In addition, the learning unit 306 may execute re-learning of the trained model in response to an instruction from the base station device 101, for example.

[0038] FIG. 4 shows an example of the functional configuration of the base station device 101. The base station device 101 includes a capability information receiving unit 401, a setting information notifying unit 402, and a report receiving unit 403. The base station device 101 may also include a learning unit 404 as an option. Note that FIG. 4 only shows functions particularly related to this embodiment, and does not illustrate various other functions that the base station device 101 may have. For example, the base station device 101 naturally has other functions that are generally included in base station devices that comply with LTE, 5G, or subsequent standards. The functional blocks in FIG. 4 are shown schematically, and the respective functional blocks may be integrated or further subdivided. Each function in FIG. 4 may be implemented, for example, by the processor 201 executing a program stored in the ROM 202 or the storage device 204, or by a processor within the communication circuit 205 executing predetermined software. Since the details of the processing performed by each functional unit are as described above, only the general functions of the base station device 101 will be outlined here.

[0039] The capability information receiving unit 401 receives capability information (UE Capability) from the terminal device 111, the capability information including information indicating whether or not the terminal device 111 has the capability to estimate radio quality using AI / ML. The configuration information notifying unit 402 can transmit information instructing whether or not to estimate radio quality using AI / ML, to the terminal device 111 that has the capability to estimate radio quality using AI / ML. Furthermore, the configuration information notifying unit 402 can notify the terminal device 111 that has the capability to estimate the radio quality of some cells based on measurement values ​​of the radio quality of other cells using AI / ML of configuration information including the first information and second information. Furthermore, the configuration information notifying unit 402 can notify the terminal device 111 that has the capability to acquire an estimate of radio quality of a specific cell at a future timing based on measurement values ​​of the radio quality of the specific cell using AI / ML of configuration information indicating the number of estimates to be reported for the specific cell. The configuration information may associate the measObjectID, reportConfigID, and measID for that particular cell, and may further include information indicating that estimates of future timing should be reported, and the number of estimates to be reported.

[0040] The report receiving unit 403 receives from the terminal device 111 a report of the measured and estimated values ​​of wireless quality based on the setting information notified to the terminal device 111 by the setting information notifying unit 402. The base station device 101 can initiate handover processing of the terminal device 111 based on the measured and estimated values.

[0041] The learning unit 404 performs machine learning to generate a trained model for estimating wireless quality. Note that it is sufficient if either the learning unit 306 of the terminal device 111 or the learning unit 404 of the base station device 101 performs machine learning; it is not necessary for both to perform machine learning. Also, machine learning may be performed in a network node different from either the base station device 101 or the terminal device 111. Note that the base station device 101 may transmit an instruction to the terminal device 111 to report the difference between the actual measurement value and the estimated value of wireless quality to the base station device 101. Then, if the difference exceeds a predetermined value, either the learning unit 306 of the terminal device 111 or the learning unit 404 of the base station device 101 performs re-learning of the trained model. Also, instead of the difference value between the estimated value and the actual measurement value, information indicating that re-learning is required may be notified from the terminal device 111 to the base station device 101. When machine learning is performed in a network node different from both the base station device 101 and the terminal device 111, the base station device 101 may notify the network node that re-learning should be performed.

[0042] (Processing flow) An example of the processing flow according to this embodiment is shown in Fig. 5. Note that, since the details of the processing executed in the wireless communication system are as described above, only an overview of the processing flow will be given here, and the details will not be repeated.

[0043] First, the terminal device 111 notifies the base station device 101 of its own capability information (S501). Here, the capability information including information indicating that the terminal device 111 is capable of estimating wireless quality using AI / ML is notified from the terminal device 111 to the base station device 101. When the base station device 101 determines from the capability information that the terminal device 111 is capable of estimating wireless quality using AI / ML, the base station device 101 notifies the terminal device 111 of setting information for estimating and reporting wireless quality, for example, by using an RRC Reconfiguration message. Thereafter, the terminal device 111 measures a reference signal transmitted from the base station device 101 (S503, S504) and inputs the measurement value into a trained model, thereby estimating an estimate of the wireless quality of another cell or an estimate of the future wireless quality of that cell (S505). Then, the terminal device 111 notifies the base station device 101 of the value of the measurement result of the wireless quality in S504 and the value of the estimation result of the wireless quality in S505 (S506).

[0044] As described above, according to the present embodiment, it is possible for the terminal device 111 to notify the base station device 101 of estimated values ​​of wireless quality for cells not designated as measurement targets, without significantly changing the format of reporting measurement results in the past. This makes it possible to timely set an appropriate cell or beam to which the terminal device 111 is connected. Furthermore, it is possible for the terminal device 111 to notify the base station device 101 of estimated values ​​of wireless quality for one cell at multiple timings. This allows the base station device 101 to obtain a predicted value of future wireless quality, which improves the reporting of wireless quality compared to the conventional case where only one actually measured wireless quality is reported for each cell. As a result, it becomes possible to perform more advanced communication control of the terminal device 111. This makes it possible to contribute to Goal 9 of the Sustainable Development Goals (SDGs) led by the United Nations, which is to "build resilient infrastructure, promote sustainable industrialization and foster innovation."

[0045] The invention is not limited to the above-described embodiment, and various modifications and variations are possible within the scope of the gist of the invention.

Claims

1. A terminal device, an estimation means for estimating wireless quality at each of one or more timings after a predetermined period from a predetermined timing by inputting, into a trained model acquired by machine learning in a learning phase, a result of a first measurement of wireless quality at a first timing for a predetermined cell or beam and a result of a second measurement of wireless quality at one or more second timings after the first timing as training data; and a transmitting means for transmitting to a connected base station device a report including a value indicating an estimated value of wireless quality output from the trained model for the specified cell or beam and information indicating which timing after the specified timing the estimated value corresponds to; A terminal device comprising:

2. The terminal device according to claim 1, characterized in that the transmitting means transmits to the base station device as the report MeasResults including one or more information elements each including the estimated value corresponding to one or more timings after the predetermined period from the predetermined timing and information indicating which timing after the predetermined timing the estimated value corresponds to.

3. The terminal device according to claim 1, characterized in that the one or more timings correspond to a period at which a synchronization signal (SS) / physical broadcast channel (PBCH) block (SSB) is transmitted in the specified cell or beam.

4. 2. The terminal device according to claim 1, further comprising: receiving means for receiving information indicating the number of said estimates to be included in said report from said base station device.

5. A base station device, a connection means for connecting to a terminal device capable of estimating wireless quality at each of one or more timings after a predetermined period from a predetermined timing by inputting, in an inference phase, the measurement result of wireless quality at a predetermined timing for the predetermined cell or beam to a trained model acquired by machine learning using, as input, a result of a first measurement of wireless quality at a first timing for the predetermined cell or beam and, as training data, results of second measurement of wireless quality at one or more second timings after the first timing; a receiving means for receiving from the terminal device a report including a value indicating an estimated value of wireless quality output from the trained model for the specified cell or beam and information indicating which timing after the specified timing the estimated value corresponds to; A base station device comprising:

6. The base station device according to claim 5, characterized in that the receiving means receives from the terminal device, as the report, MeasResults including one or more information elements each including the estimated value corresponding to one or more timings after the predetermined period from the predetermined timing and information indicating to which timing of the one or more timings after the predetermined period from the predetermined timing the estimated value corresponds.

7. The base station device according to claim 5, characterized in that the one or more timings correspond to a period at which a synchronization signal (SS) / physical broadcast channel (PBCH) block (SSB) is transmitted in the specified cell or beam.

8. The base station device according to claim 5, further comprising a notification means for notifying the terminal device of information indicating the number of estimated values ​​of wireless quality corresponding to different timings output from the trained model to be included in the report.

9. A communication method executed by a terminal device having a function of estimating wireless quality at each of one or more timings after a predetermined period from a predetermined timing by inputting, into a trained model acquired by machine learning in a learning phase, a result of a first measurement of wireless quality at a first timing for a predetermined cell or beam and using, as training data, results of second measurement of wireless quality at one or more second timings after the first timing, the result of measuring wireless quality at a predetermined timing for the predetermined cell or beam in an inference phase, the method comprising: transmitting to the currently connected base station device a report including a value indicating an estimated value of wireless quality output from the trained model for the specified cell or beam and information indicating which timing after the specified timing the estimated value corresponds to; A communication method comprising:

10. A communication method performed by a base station device, comprising: a terminal device is connected to a trained model acquired by machine learning in a learning phase, in which a result of a first measurement of wireless quality at a first timing for a predetermined cell or beam is input and a result of a second measurement of wireless quality at one or more second timings after a predetermined period from the first timing is used as training data, by inputting a result of the measurement of wireless quality at a predetermined timing for the predetermined cell or beam in an inference phase; the terminal device is capable of estimating wireless quality at each of one or more timings after the predetermined period from the predetermined timing; receiving, from the terminal device, a report including a value indicating an estimated value of wireless quality output from the trained model for the specified cell or beam and information indicating which timing after the specified timing the estimated value corresponds to; A communication method comprising:

11. A program for causing a computer provided in a terminal device having a function of estimating wireless quality at each of one or more timings after a predetermined period from a predetermined timing by inputting the result of a first measurement of wireless quality at a first timing for a predetermined cell or beam in a learning phase and the result of a second measurement of wireless quality at one or more second timings after the predetermined period from the first timing as training data to execute the communication method described in claim 9.

12. A program for causing a computer provided in a base station device to execute the communication method according to claim 10.

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