Terminal, base station, and communication method

Abstract

This terminal is provided with: a control circuit that, in data collection of an artificial intelligence model for predicting channel state information, determines control information pertaining to conditions or statuses specific to the implementation of a communication device or a communication counterpart in the measurement of the channel state information; and a transmission circuit that transmits the control information to the communication counterpart.

Description

Terminal, base station and communication method

[0001] The present disclosure relates to a terminal, a base station, and a communication method.

[0002] In recent years, the expansion and diversification of wireless services has led to the expectation of rapid development of the Internet of Things (IoT). Mobile communications are now being used in a wide range of applications, from smartphones and other information terminals to automobiles, homes, home appliances, and industrial equipment. To support this diversification, significant improvements in the performance and functionality of mobile communication systems are required, addressing various requirements, such as increased system capacity, an increased number of connected devices, and low latency. Fifth-generation mobile communication systems (5G) boast high-capacity and ultra-high-speed data transfer (eMBB: enhanced Mobile Broadband), massive machine-type communication (mMTC: massive Machine-Type Communication), and ultra-reliable and low-latency communication (URLLC), providing flexible wireless communications to meet diverse needs.

[0003] The 3rd Generation Partnership Project (3GPP), an international standardization organization, is working on the specification of New Radio (NR) as one of the 5G wireless interfaces.

[0004] RP-221348, “Revised SID: Study on Artificial Intelligence (AI) / Machine Learning (ML) for NR Air Interface,” Qualcomm (Moderator), June 2022.3GPP TS 37.320 V17.5.0, “Radio measurement collection for Minimization of Drive Tests (MDT),” September 2023.

[0005] However, there is room for improvement in the efficiency of wireless communications.

[0006] Non-limiting embodiments of the present disclosure contribute to providing a terminal, a base station, and a communication method that can improve the efficiency of wireless communication.

[0007] A terminal according to one embodiment of the present disclosure includes a control circuit that determines, in data collection for an artificial intelligence model for reporting channel state information, information regarding measurement status in multiple measurement occasions for measuring the channel state information or information regarding the time of the multiple measurement occasions, and a transmission circuit that transmits the measured channel state information and the information regarding the measurement status or the information regarding the time in groups including the multiple measurement occasions.

[0008] These comprehensive or specific aspects may be realized as a system, an apparatus, a method, an integrated circuit, a computer program, or a recording medium, or may be realized as any combination of a system, an apparatus, a method, an integrated circuit, a computer program, and a recording medium.

[0009] According to an embodiment of the present disclosure, it is possible to improve the efficiency of wireless communication.

[0010] Further advantages and benefits of one embodiment of the present disclosure will become apparent from the specification and drawings. Such advantages and / or benefits may be provided by some embodiments and features described in the specification and drawings, respectively, but not necessarily all of them may be provided to obtain one or more identical features.

[0011] 1. Diagram showing an example of Channel State Information (CSI) compression in the spatial and frequency domains using Machine Learning (ML) / Artificial Intelligence (AI) technology. 2. Diagram showing an example of CSI prediction using AI / ML technology. 3. Block diagram showing an example of data collection on the network side. 4. Diagram showing an example of not measuring CSI during CSI measurement occasions. 5. Block diagram showing an example of the configuration of a part of a base station. 6. Block diagram showing an example of the configuration of a part of a terminal. 7. Diagram showing an example of a CSI report. 8. Diagram showing an example of a data series of a CSI report. 9. Diagram showing an example of a CSI report. 10. Diagram showing an example of a data series of a CSI report. 11. Diagram showing an example of a CSI report. 12. Diagram showing an example of a data series of a CSI report. 13. Diagram showing an example of an operation of a terminal and a base station. 14. Block diagram showing an example of the configuration of a base station. 15. Block diagram showing an example of the configuration of a terminal. 16. Diagram of an exemplary architecture of a 3GPP NR system. 17. Diagram of an exemplary functional division in 5G O-RAN.

[0012] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the drawings.

[0013] The basic functions of eMBB or URLLC were specified in Release 15. From Release 16 onwards, URLLC has been extended to include the Industrial IoT, V2X (Vehicle-to-Everything), and non-terrestrial networks (NTN) including satellites. The extended specifications of 3GPP have been called "5G-Advanced" since Release 18 (also called Rel. 18).

[0014] Furthermore, advances in artificial intelligence (AI) technologies such as machine learning (ML) have been remarkable, and their application to mobile communications is also being considered. 3GPP is also studying and standardizing the application of AI / ML to various applications, and has begun studying the application of AI / ML to wireless interfaces since Release 18 (see, for example, Non-Patent Document 1). Representative use cases of AI / ML under consideration include channel state information (CSI) feedback, beam control, and position estimation.

[0015] In NR, for example, an access scheme based on Orthogonal Frequency Division Multiplexing (OFDM) is adopted for downlink communication. Furthermore, Multiple-Input Multiple Output (MIMO) is adopted to improve communication quality or increase data rates. To effectively utilize the performance of MIMO, closed-loop control is introduced, in which channel estimation is performed on the terminal (e.g., also called user equipment (UE)) side, and CSI is fed back to the base station (e.g., also called gNB). The base station applies transmit precoding and other techniques based on the fed-back CSI to perform downlink communication.

[0016] CSI feedback is expected to achieve high performance with less control information.

[0017] Furthermore, for example, when a wireless channel fluctuates over time due to the movement of a terminal, the wireless channel may fluctuate between the time when the terminal estimates the channel and the time when the base station actually performs downlink communication. In this case, a difference may occur between the channel used in the calculation of transmit precoding in the base station (e.g., the channel estimated and fed back by the terminal) and the channel used when the base station actually performs transmission. This difference in channel may be a factor that degrades the performance of downlink communication to which precoding is applied.

[0018] In Release 18, the application of AI / ML technologies to the radio interface is being considered, for example, for CSI feedback (CSI reporting), methods for compressing the amount of CSI information in the spatial and frequency domains using AI / ML technologies (hereinafter referred to as CSI compression), and for CSI prediction in the time domain using AI / ML technologies on the terminal side.

[0019] For example, ML allows for automatic feature extraction by training an AI / ML model (e.g., an artificial intelligence model) such as a neural network using a huge amount of training data. CSI compression can utilize an algorithm called an autoencoder, which is primarily used for dimensional compression and reconstruction of image data. For example, as shown in Figure 1, a CSI matrix represented by two-dimensional spatial and frequency domains is considered an image. The encoding unit (encoder) used for compression by the autoencoder is used for CSI compression processing on the terminal side, and the decoding unit (decoder) used for reconstruction is used for CSI reconstruction processing on the base station or network (e.g., also referred to as "base station / network").

[0020] In addition, in CSI prediction, as shown in Figure 2, multiple temporal CSI samples (historic CSI) measured by the terminal are input to an AI / ML model (CSI prediction model), and future CSI (predicted CSI) is output from the AI / ML model. Then, by feeding back the predicted CSI from the terminal to the base station, it is expected that performance degradation of downlink communication due to the difference between the channel used by the base station to calculate transmit precoding (the channel estimated and fed back by the terminal) and the channel used by the base station for actual transmission can be suppressed.

[0021] For the training and operation (e.g., performance monitoring) of AI / ML models for CSI compression and CSI prediction using AI / ML technologies, it is expected that, for example, data collection procedures or mechanisms will be considered.

[0022] In CSI compression, which applies encoding or decoding utilizing AI / ML technologies on both the terminal side and the base station / network side, a method is being considered in which data is collected on the network side, the network side learns both AI / ML models, and the terminal-side AI / ML model (encoding unit or compression unit) is transferred to the terminal side. Also, in CSI prediction utilizing AI / ML technologies on the terminal side, there may be cases in which data is collected on the network (e.g., base station) side, the network side learns an AI / ML model, and the AI / ML model (or a dataset used to train the AI / ML model) is transferred to the terminal side.

[0023] When data collection is performed on the network side, the network notifies the terminal of a reference signal configuration for CSI measurement, such as CSI-RS, to configure CSI measurement for the terminal. The terminal reports measured CSI (e.g., training data or ground-truth CSI) to the network, for example, as shown in FIG. 3. Here, reporting of ground-truth CSI from the terminal may be performed for each CSI measurement sample, as shown in FIG. 3, or may be performed for each group including multiple samples. In reporting for each sample, there is a one-to-one correspondence between CSI measurements and CSI reports, and one CSI report includes ground-truth CSI generated by one CSI measurement. In reporting for each group, one CSI report includes ground-truth CSI generated by multiple CSI measurements.

[0024] Here, at least in data collection for training, measurement time may be long (e.g., several minutes or hours) to collect a sufficient data set. Furthermore, the ground-truth CSI for training an AI / ML model may be a channel matrix, eigenvector, or a codebook with a relatively large amount of information in order to report channel information with sufficient accuracy. In this case, the amount of information (overhead) of the ground-truth CSI may be large. On the other hand, it is expected that the latency requirements for CSI reporting for training an AI / ML model will be significantly relaxed compared to existing CSI reporting. Therefore, in data collection for training an AI / ML model, instead of CSI reporting per sample, group-based reporting is effective, in which a terminal logs and stores CSI measurements and collectively reports the recorded and stored CSI measurements (e.g., also referred to as a "measurement log").

[0025] However, a UE may not necessarily measure the CSI and record and store the CSI measurement value on a configured CSI measurement occasion (also referred to as a "CSI measurement occasion" or a "CSI-RS measurement occasion"). For example, as shown in FIG. 4, when the UE is in an inactive state in Discontinuous Reception (DRX), when a random access operation is performed, or when a radio link failure occurs, the UE may not measure the CSI on a configured CSI measurement occasion (for example, when the UE does not perform CSI measurement or when the CSI measurement fails).

[0026] When CSI measurement and CSI reporting for data collection are configured in a terminal, there is room for study on terminal operation when an event occurs in which the terminal does not measure the CSI during the CSI measurement occasion configured as described above.In addition, there is room for study on a CSI reporting framework when an event occurs in which the terminal does not measure the CSI in group-based CSI reporting as described above.

[0027] For example, when CSI measurement and CSI reporting for data collection are configured in a terminal, an example of terminal operation and CSI reporting method when an event occurs in which the terminal does not measure CSI during a configured CSI measurement occasion will be described.

[0028] The first method is a method in which the terminal reports ground-truth CSI only when CSI measurement is successful, and the measurement log of the CSI report is composed of a single CSI measurement value. This method is equivalent to the sample-by-sample CSI reporting described above. In sample-by-sample CSI reporting, CSI measurements and CSI reports correspond one-to-one, and one CSI report contains ground-truth CSI generated by one CSI measurement. The network can identify which measurement occasions the terminal did not measure CSI in based on CSI transmission occasions for which there is no report from the terminal. However, this method may result in more frequent reporting than group-based reporting. Furthermore, this method cannot apply information compression using temporal statistical information, so the overhead of each CSI report is large, and an increase in overall overhead is expected. Furthermore, although the network can identify which CSI measurement occasions the terminal did not measure CSI in, it cannot identify the reason why the terminal did not measure CSI (e.g., the CSI measurement status at the terminal).

[0029] A second method is one in which a terminal reports ground-truth CSI only when CSI measurement is successful, and the measurement log for the CSI report is composed of multiple CSI measurements. This method is equivalent to the group-based CSI reporting described above, and one CSI report includes ground-truth CSI generated by multiple CSI measurements. This method can reduce the frequency of CSI reporting compared to sample-by-sample reporting, and can also apply information compression using temporal statistical information, which is expected to reduce the overhead of CSI reporting. However, with this method, for example, if the terminal simply reports ground-truth CSI when CSI measurement is successful, it is difficult for the network to identify which CSI measurement occasions the terminal did not measure CSI in, and it is also unable to identify the reason why the terminal did not measure CSI. This may affect the accuracy of data collection in the network.

[0030] In one non-limiting embodiment of the present disclosure, when CSI measurement and CSI reporting for data collection are configured in a terminal in order to perform data collection on the network side, a terminal operation and a CSI reporting method will be described when an event occurs in which the terminal does not measure CSI in the configured CSI measurement occasion.

[0031] For example, in a non-limiting embodiment of the present disclosure, a measurement log of a CSI report is based on reporting in groups each consisting of a plurality of CSI measurements, and in addition to ground-truth CSI when a terminal has successfully measured CSI, information about the time of CSI measurement or the situation at the time of CSI measurement is recorded and saved in the measurement log of the CSI report, and reported to the network. This is expected to improve the accuracy of data collection on the network side.

[0032] Non-limiting embodiments of the present disclosure will be described below.

[0033] In the following, CSI compression and CSI prediction are described as examples of targets of the AI / ML model. However, the targets of the AI / ML model are not limited to CSI compression and CSI prediction, and the model can also be applied to other use cases (e.g., spatial or temporal beam prediction, positioning, etc.) in which data collection is performed on the network side and CSI measurements (e.g., ground-truth CSI) are reported from terminals.

[0034] [Overview of Communication System] A communication system according to an aspect of the present disclosure includes, for example, at least one base station and at least one terminal.

[0035] FIG. 5 is a block diagram showing a configuration example of a portion of a base station 100 according to an embodiment of the present disclosure, and FIG. 6 is a block diagram showing a configuration example of a portion of a terminal 200 according to an embodiment of the present disclosure.

[0036] In the base station 100 shown in Fig. 5, a communication unit (e.g., corresponding to a receiving circuit) receives, in data collection by an artificial intelligence model (e.g., an AI / ML model) for reporting channel state information (e.g., CSI), information on measurement status in multiple measurement occasions for measuring the channel state information or information on the time of the multiple measurement occasions, and the channel state information, in units of groups including multiple measurement occasions. A control unit (e.g., corresponding to a control circuit) controls the data collection based on the channel state information and the information on the measurement status or the information on the time.

[0037] In the terminal 200 shown in Fig. 6, a control unit (e.g., corresponding to a control circuit) determines information about measurement situations in multiple measurement occasions for measuring channel state information or information about the times of the multiple measurement occasions in data collection by an artificial intelligence model (e.g., an AI / ML model) for reporting channel state information (e.g., CSI). A communication unit (e.g., corresponding to a transmission circuit) transmits the measured channel state information and the information about the measurement situations or information about the times in units of groups including multiple measurement occasions.

[0038] (Embodiment 1) A network (for example, base station 100) notifies terminal 200 of a reference signal configuration for CSI measurement, such as CSI-RS, and configures CSI measurement for terminal 200.

[0039] Terminal 200 reports measured CSI (e.g., training data or ground-truth CSI) to the network. Here, reporting of ground-truth CSI from terminal 200 is performed in groups including multiple samples. In group-based CSI reporting, one CSI report includes ground-truth CSI generated by multiple CSI measurements. Furthermore, in group-based CSI reporting, multiple CSI reference resources may be configured for one CSI report. For example, a CSI reference resource may be configured for each of multiple CSI measurements and ground-truth CSI generation corresponding to one CSI report.

[0040] In this embodiment, the Minimalization of Drive Tests (MDT) framework (see, for example, Non-Patent Document 2) is used for CSI reporting. MDT is a specification for radio measurement collection, and a terminal can include a timestamp in each MDT measurement value. For example, in existing NR, the basic unit of the MDT timestamp that can be recorded in a log is seconds.

[0041] In the present embodiment, for example, as shown in Fig. 7 , terminal 200 records and stores in a log not only ground-truth CSI when CSI measurement is successful but also timestamps of times (CSI measurement times) corresponding to CSI measurement occasions when CSI measurement is successful, and reports the recorded and stored information collectively to the network. That is, terminal 200 determines information (e.g., timestamps) related to measurement times corresponding to CSI measurement occasions when CSI measurement is successful among a plurality of CSI measurement occasions, but does not determine information related to measurement times corresponding to CSI measurement occasions when CSI measurement is not successful (e.g., CSI measurement occasions when CSI measurement is unsuccessful or CSI measurement occasions when CSI measurement is not performed).

[0042] In the example of Fig. 7, terminal 200 transmits to the network a CSI report including timestamps #1, #3, #N-1, and #N of CSI measurement occasions where CSI measurement was successful among multiple CSI measurement occasions, and CSI measurement values ​​(e.g., ground-truth CSI) for these CSI measurement occasions. As shown in Fig. 7, timestamps of CSI measurement occasions where CSI measurement was not successful are not included in the measurement log reported to the network.

[0043] The base unit of the recorded CSI measurement occasion timestamp may be the same unit as in existing NR specifications (e.g., seconds), or a finer granularity (e.g., smaller than a second) may be introduced to match the granularity of the CSI measurement occasion for data collection, or other units may be used.

[0044] The time stamp information may be, for example, information in the format YY-MM-DD HH:MM:SS or information in another format.

[0045] FIG. 8 is a diagram showing an example of a data sequence of a CSI report according to this embodiment.

[0046] As shown in FIG. 8, the CSI report includes a CSI measurement value (e.g., ground-truth CSI) in a CSI measurement occasion where the CSI measurement was successful, and a timestamp corresponding to the CSI measurement occasion.

[0047] As described above, in the present embodiment, terminal 200 determines information regarding the times of multiple CSI measurement occasions in data collection of an AI / ML model for CSI reporting, and transmits a group-based CSI report including CSI measurements and information regarding the times of the CSI measurement occasions to the network. This allows the network to identify, among multiple CSI measurement occasions, CSI measurement occasions on which terminal 200 does not measure CSI, based on timestamp information included in the CSI report (e.g., information regarding the CSI measurement occasions on which terminal 200 measured CSI). This allows the network to improve the accuracy of data collection on the network side by identifying whether or not CSI measurements were performed on each CSI measurement occasion that is the target of CSI reporting, even if an event occurs in which terminal 200 does not measure CSI in group-based CSI reporting. Therefore, according to the present embodiment, it is possible to improve the efficiency of wireless communication.

[0048] (Variation of First Embodiment) Note that the information related to the CSI measurement time is not limited to a timestamp. For example, the information related to the CSI measurement time may be a frame number, a slot number, or a symbol number instead of a timestamp. Furthermore, when the maximum number of ground-truth CSI reports that can be included in one CSI report is known in the network, the information related to the CSI measurement time may be the number of the ground-truth CSI report included in one CSI report or the number of the corresponding CSI measurement occasion.

[0049] These modifications can reduce the overhead involved in reporting information about CSI measurement times compared to timestamps.

[0050] Second Embodiment A network (for example, base station 100) notifies terminal 200 of a reference signal configuration for CSI measurement, such as CSI-RS, and configures terminal 200 for CSI measurement.

[0051] Terminal 200 reports measured CSI (e.g., training data or ground-truth CSI) to the network. Here, reporting of ground-truth CSI from terminal 200 is performed in groups including multiple samples. In group-based CSI reporting, one CSI report includes ground-truth CSI generated by multiple CSI measurements. Furthermore, in group-based CSI reporting, multiple CSI reference resources may be configured for one CSI report. For example, a CSI reference resource may be configured for each of multiple CSI measurements and ground-truth CSI generation corresponding to one CSI report.

[0052] In the first embodiment, since the CSI report includes information related to the CSI measurement time, if the overhead of the information related to the CSI measurement time is large, the overhead of the CSI report may increase.

[0053] In this embodiment, for example, as shown in FIG. 9 , terminal 200 records and stores in a log not only ground-truth CSI when CSI measurement is successful, but also information on whether CSI measurement was successful or not (e.g., whether CSI measurement was successful or unsuccessful) for each of multiple CSI measurement occasions that are targets of CSI reporting (e.g., within a group), and reports the recorded and stored information together to the network.

[0054] For example, the information on whether the CSI measurement was successful or not may be one bit of information (0 or 1) for each CSI measurement occasion. For example, if the CSI measurement was successful, it may be set to "0," and if the CSI measurement was unsuccessful, it may be set to "1," or vice versa.

[0055] Furthermore, the CSI report may include, in addition to information regarding whether or not the CSI measurement was successful in each CSI measurement occasion, ground-truth CSI corresponding to the CSI measurement occasion in which the CSI measurement was successful.

[0056] FIG. 10 is a diagram showing an example of a data sequence of a CSI report according to this embodiment.

[0057] As shown in FIG. 10, the CSI report includes information indicating whether or not CSI measurement was successful (success: "0", failure: "1") at each CSI measurement occasion (e.g., CSI measurement occasions #1 to #N), and CSI measurement values ​​(e.g., ground-truth CSI) for the CSI measurement occasions where CSI measurement was successful.

[0058] As described above, in the present embodiment, in data collection of an AI / ML model for CSI reporting, terminal 200 determines information on measurement statuses (e.g., whether CSI measurement was successful) in multiple CSI measurement occasions, and transmits a group-based CSI report including the CSI measurement values ​​and information on the CSI measurement status to the network. This allows the network to identify, from among multiple CSI measurement occasions, CSI measurement occasions on which terminal 200 does not measure CSI, based on information on whether CSI measurement was successful in each CSI measurement occasion. This allows the network to improve the accuracy of data collection on the network side by identifying whether CSI measurement was performed in each CSI measurement occasion that is a target of CSI reporting, even if an event occurs in which terminal 200 does not measure CSI in group-based CSI reporting.

[0059] Furthermore, according to this embodiment, by using information regarding whether or not CSI measurement was successful for each CSI measurement occasion, the overhead of CSI reporting can be reduced compared to when information regarding the CSI measurement time is reported.

[0060] Therefore, according to this embodiment, it is possible to improve the efficiency of wireless communication.

[0061] Note that the CSI reporting in this embodiment is not limited to the example shown in Fig. 10. For example, the CSI reporting may report CSI measurement values ​​(Ground-truth CSI) in CSI measurement occasions where CSI measurement is successful, and may report information indicating that CSI measurement has failed in CSI measurement occasions where CSI measurement has failed. That is, the CSI reporting may not include information indicating whether CSI measurement has been successful in CSI measurement occasions where CSI measurement has been successful.

[0062] (Embodiment 3) A network (for example, base station 100) notifies terminal 200 of a reference signal configuration for CSI measurement, such as CSI-RS, and configures CSI measurement for terminal 200.

[0063] Terminal 200 reports measured CSI (e.g., training data or ground-truth CSI) to the network. Here, reporting of ground-truth CSI from terminal 200 is performed in groups including multiple samples. In group-based CSI reporting, one CSI report includes ground-truth CSI generated by multiple CSI measurements. Furthermore, in group-based CSI reporting, multiple CSI reference resources may be configured for one CSI report. For example, a CSI reference resource may be configured for each of multiple CSI measurements and ground-truth CSI generation corresponding to one CSI report.

[0064] In the first embodiment, since the CSI report includes information about the CSI measurement time, if the overhead of the information about the CSI measurement time is large, the overhead of the CSI report may increase. Also, in the second embodiment, the network cannot identify the reason why the CSI is not measured in the terminal 200.

[0065] In this embodiment, for example, as shown in FIG. 11 , terminal 200 records and stores in a log not only ground-truth CSI when CSI measurement is successful, but also information on the CSI measurement status at each of multiple CSI measurement occasions that are the subject of CSI reporting (e.g., within a group), and reports the recorded and stored information together to the network.

[0066] For example, the information regarding the measurement status in the CSI measurement occasion may include information corresponding to a status of "successful CSI measurement," a status of "failed CSI measurement due to channel quality dependency," and a status of "measurement not performed due to other transmission / reception operations in the terminal, not due to channel quality dependency." For example, if terminal 200 fails to measure CSI due to a radio link failure, it may report the status of "failed CSI measurement due to channel quality dependency." Furthermore, for example, if terminal 200 is in an inactive state in DRX or if it does not measure CSI because a random access operation has been performed, it may report the status of "not performed measurement due to other transmission / reception operations in the terminal, not due to channel quality dependency."

[0067] For example, information regarding the measurement status in a CSI measurement occasion may be 2-bit information for each CSI measurement occasion. As an example, a "CSI measurement successful" status may be represented by "00", a "CSI measurement failed due to channel quality dependency" status may be represented by "01", and a "measurement not performed due to other transmission / reception operations in the terminal, not due to channel quality dependency" status may be represented by "10". Note that the association between the measurement status in a CSI measurement occasion and the 2-bit information is not limited to this, and other associations may be used.

[0068] Furthermore, for a CSI measurement occasion in which CSI measurement was successful, the CSI report may include corresponding ground-truth CSI in addition to information about the measurement status in the CSI measurement occasion.

[0069] FIG. 12 is a diagram showing an example of a data sequence of a CSI report according to this embodiment.

[0070] As shown in Figure 12, the CSI report includes information (2-bit information) indicating the measurement status at each CSI measurement occasion (e.g., CSI measurement occasions #1 to #N), and CSI measurement values ​​(e.g., ground-truth CSI) at CSI measurement occasions where CSI measurement was successful (e.g., information indicating the measurement status: 00).

[0071] As described above, in the present embodiment, in data collection of an AI / ML model for CSI reporting, terminal 200 determines information on measurement statuses in multiple CSI measurement occasions, and transmits a group-based CSI report to the network, including information on the CSI measurement values ​​and the CSI measurement status (a situation in which CSI measurement is successful, a situation in which CSI measurement is not performed). This allows the network to identify, based on the information on the measurement status in each CSI measurement occasion, CSI measurement occasions among multiple CSI measurement occasions in which terminal 200 does not measure CSI, and the reason why terminal 200 does not measure CSI (for example, whether the reason depends on channel quality). This allows the network to improve the accuracy of data collection on the network side by identifying whether CSI measurement is performed in each CSI measurement occasion that is the target of CSI reporting, and the reason why CSI measurement is not performed, based on the information on the measurement status in each CSI measurement occasion.

[0072] Furthermore, according to this embodiment, by using information on the measurement status at each CSI measurement occasion, it is possible to reduce the overhead of CSI reporting compared to the case where information on the CSI measurement time is reported.

[0073] Therefore, according to this embodiment, it is possible to improve the efficiency of wireless communication.

[0074] Note that the CSI reporting in this embodiment is not limited to the example shown in Fig. 12. For example, the CSI reporting may report CSI measurement values ​​(ground-truth CSI) in CSI measurement occasions where CSI measurement is successful, and may report information indicating the measurement status in CSI measurement occasions where CSI measurement is unsuccessful. That is, the CSI reporting may not include information indicating the measurement status in CSI measurement occasions where CSI measurement is successful.

[0075] (Embodiment 4) A network (for example, base station 100) notifies terminal 200 of a reference signal configuration for CSI measurement, such as CSI-RS, and configures CSI measurement for terminal 200.

[0076] Terminal 200 reports measured CSI (e.g., training data or ground-truth CSI) to the network. Here, reporting of ground-truth CSI from terminal 200 is performed in groups including multiple samples. In group-based CSI reporting, one CSI report includes ground-truth CSI generated by multiple CSI measurements. Furthermore, in group-based CSI reporting, multiple CSI reference resources may be configured for one CSI report. For example, a CSI reference resource may be configured for each of multiple CSI measurements and ground-truth CSI generation corresponding to one CSI report.

[0077] In this embodiment, for example, as shown in FIG. 13 , terminal 200 records and stores in a log not only ground-truth CSI when CSI measurement is successful, but also information on the CSI measurement status for each of multiple CSI measurement occasions that are CSI reporting targets (e.g., within a group), and reports the recorded and stored information together to the network.

[0078] For example, information regarding the measurement status in a CSI measurement occasion may include information corresponding to a status in which "CSI measurement is successful," "CSI measurement is not performed due to DRX inactive state," "CSI measurement is not performed due to execution of a random access operation," and "CSI measurement failed due to radio link failure."

[0079] For example, the information on the measurement status in the CSI measurement occasion may be N bits of information for each CSI measurement occasion. In the case of N bits of information, the information on the measurement status in the CSI measurement occasion may be used to N Individual statuses (including, for example, the status "CSI measurement successful") can be reported.

[0080] Furthermore, for a CSI measurement occasion in which CSI measurement was successful, the CSI report may include corresponding ground-truth CSI in addition to information about the measurement status in the CSI measurement occasion.

[0081] FIG. 14 is a diagram showing an example of a data sequence of a CSI report according to this embodiment.

[0082] As shown in Figure 14, the CSI report includes information (N-bit information; N=2 in Figure 14) indicating the measurement status at each CSI measurement occasion (e.g., CSI measurement occasions #1 to #N), and CSI measurement values ​​(e.g., ground-truth CSI) for CSI measurement occasions where CSI measurement was successful (e.g., information indicating the measurement status: 00).

[0083] As described above, in the present embodiment, in data collection of an AI / ML model for CSI reporting, terminal 200 determines information on measurement statuses in multiple CSI measurement occasions, and transmits a group-based CSI report to the network, including information on the CSI measurement values ​​and the CSI measurement status (a situation in which CSI measurement is successful, a situation in which CSI measurement is not performed). As a result, according to (1), the network can identify, among multiple CSI measurement occasions, CSI measurement occasions in which terminal 200 does not measure CSI, and the cause of terminal 200 not measuring CSI (for example, DRX inactive state, execution of a random access operation, or a radio link failure), based on information on the measurement status in each CSI measurement occasion. As a result, in the present embodiment, the network can identify a more detailed cause of terminal 200 not measuring CSI than in the third embodiment. Therefore, even if an event occurs in which terminal 200 does not measure CSI in group-based CSI reporting, the network can improve the accuracy of data collection on the network side by identifying whether CSI measurement is performed in each CSI measurement occasion that is the target of CSI reporting, and the cause of not measuring CSI.

[0084] Furthermore, according to this embodiment, by using information on the measurement status at each CSI measurement occasion, it is possible to reduce the overhead of CSI reporting compared to the case where information on the CSI measurement time is reported.

[0085] Therefore, according to this embodiment, it is possible to improve the efficiency of wireless communication.

[0086] Note that the CSI reporting in this embodiment is not limited to the example shown in Fig. 14. For example, the CSI reporting may report CSI measurement values ​​(Ground-truth CSI) in CSI measurement occasions where CSI measurement is successful, and may report information indicating the measurement status in CSI measurement occasions where CSI measurement is unsuccessful. That is, the CSI reporting may not include information indicating the measurement status in CSI measurement occasions where CSI measurement is successful.

[0087] Furthermore, the information regarding the CSI measurement situation is not limited to the above-mentioned examples, and may be defined for other situations instead of or in addition to the above-mentioned examples.

[0088] (Other Embodiments) Assuming that the latency requirements for data collection for training at least an AI / ML model are significantly relaxed compared to existing CSI reporting, statistical properties such as the occurrence probability, occurrence frequency, or occurrence count of a data sequence included in a CSI report can be obtained, and the data sequence can be compressed based on the statistical properties or a probability model to reduce the overhead of the CSI report. For example, Huffman coding, run-length coding, dictionary-based coding, or the like may be applied to compress the data sequence.

[0089] For example, in data collection on the network side, in group-based CSI reporting in which CSI measurements recorded and stored in a log are collectively reported, the CSI measurements recorded and stored in the log may be compressed using one of the following methods (options).

[0090] <Option 1> In Option 1, the data series of the log containing the CSI measurement values ​​and the information about the measurement situation described above is processed bit by bit, and the entire data series included in the CSI report for data collection is compressed.

[0091] For example, a bit-by-bit run-length code is applied, data is compared bit by bit, and when the same data is repeated, the data is replaced with the value of the data and the number of repeated occurrences, thereby compressing the data.

[0092] <Option 2> In Option 2, the log data series including the CSI measurement values ​​and the above-mentioned information on the measurement situation is processed in units of CSI measurement values ​​(or CSI measurement values ​​and information on the measurement situation), and the entire data series included in the CSI report for data collection is compressed.

[0093] For example, data compression may be performed by treating the CSI measurement value (or information on the CSI measurement value and the measurement situation) as one symbol and applying a Huffman code to encode each symbol using statistical properties such as the occurrence probability of each symbol.

[0094] Furthermore, for example, dictionary compression such as LZ77 may be applied, which compresses symbol repetition by treating the CSI measurement value (or information related to the CSI measurement value and the measurement situation) as one symbol.

[0095] Furthermore, bit-by-bit data compression using Option 1 may be further applied to the compressed data sequence.

[0096] <Option 3> In Option 3, first, the entire data sequence included in the CSI report for data collection is divided into multiple subsequences. Here, each subsequence may include multiple CSI measurement values ​​and the above-mentioned information about the measurement situation. Next, bit-wise data compression similar to Option 1 is applied to each subsequence. Next, Huffman coding or dictionary compression similar to Option 2 is applied to each subsequence after bit-wise data compression as one symbol.

[0097] At least one of the setting of the data compression method to be adopted and the setting of the data compression section (the data sequence length to which data compression is applied) may be terminal implementation-dependent or may be standardized in a standard specification. If it is terminal implementation-dependent, terminal 200 may report information regarding the type of data compression applied to the group-based CSI report to the network. This information may be defined as additional condition or assistance information of terminal 200 for data collection.

[0098] The method for compressing the data sequence included in the CSI report has been described above.

[0099] [Example of Operation of Base Station 100 and Terminal 200] FIG. 15 is a flowchart showing an example of operation of base station 100 (referred to as base station / network) and terminal 200 according to this embodiment.

[0100] In FIG. 15, the base station / network transmits configuration related to CSI measurement and reporting to terminal 200 (S101).

[0101] Terminal 200 measures CSI based on the configuration related to CSI measurement and reporting (S102). Terminal 200 transmits a CSI report to the base station / network based on the CSI measurement result (S103). When reporting CSI, terminal 200 reports, for example, information related to the CSI measurement time or information related to the measurement status at the CSI-RS transmission opportunity to the base station / network.

[0102] The base station / network collects data for an AI / ML model for outputting predicted CSI, for example, based on a CSI report from terminal 200 (e.g., CSI measurement results, and information on CSI measurement times or information on measurement conditions at CSI-RS transmission opportunities) (S104), and uses the collected data to train and update the AI / ML model (S105).Then, the base station / network transmits (or transfers or distributes) the AI / ML model or a data set of the AI / ML model to terminal 200 (S106).

[0103] [Configuration of Base Station] Fig. 16 is a block diagram showing an example configuration of base station 100. In Fig. 16, base station 100 has a control unit 101, a signal generation unit 102, a transmission unit 103, a reception unit 104, an extraction unit 105, a demodulation unit 106, and a decoding unit 107.

[0104] At least one of the control unit 101, the signal generation unit 102, the extraction unit 105, the demodulation unit 106, and the decoding unit 107 shown in Fig. 16 may be included in the control unit shown in Fig. 5. Also, at least one of the transmission unit 103 and the reception unit 104 shown in Fig. 16 may be included in the communication unit shown in Fig. 5.

[0105] Control section 101 determines, for example, control information related to CSI measurement and reporting of terminal 200, and outputs the determined control information to signal generation section 102. The control information related to CSI measurement and reporting may include, for example, a reference signal configuration for CSI measurement such as CSI-RS, and a CSI report configuration for terminal 200 to report CSI.

[0106] Furthermore, the control unit 101 may output, for example, CSI measurement data (e.g., measurement values ​​based on a CSI report or an SRS) or auxiliary information input from the decoding unit 107 to a function for processing AI / ML (e.g., a data collection function or an AI / ML model learning function). Note that the function for processing AI / ML may be included in the base station 100 or may be included in a node different from the base station 100.

[0107] Furthermore, the control unit 101 determines, for example, information for the terminal 200 to receive a downlink signal, and outputs the determined information to the signal generation unit 102. The information for the terminal 200 to receive a downlink signal may include, for example, information on resource allocation of a downlink data channel (e.g., PDSCH: Physical Downlink Shared Channel) or a downlink control channel (e.g., PDCCH: Physical Downlink Control Channel), and information on a coding and modulation scheme (e.g., MCS: Modulation and Coding Scheme).

[0108] Furthermore, the control unit 101 determines, for example, information used by the terminal 200 to transmit an uplink signal, and outputs the determined information to the signal generation unit 102, the extraction unit 105, the demodulation unit 106, and the decoding unit 107. The information used by the terminal 200 to transmit an uplink signal may include, for example, information on resource allocation of an uplink data channel (e.g., a Physical Uplink Shared Channel (PUSCH)) or an uplink control channel (e.g., a Physical Uplink Control Channel (PUCCH)), and information on a coding / modulation scheme (e.g., MCS). Furthermore, the information used to transmit an uplink signal may include, for example, information on CSI reporting.

[0109] The signal generation unit 102 generates a data signal or a control signal bit sequence using, for example, information input from the control unit 101, and applies encoding as necessary. The signal generation unit 102 also modulates the encoded bit sequence to generate a modulated signal (for example, a symbol sequence), and maps the modulated signal to the radio resource specified by the control unit 101. The signal generation unit 102 outputs the mapped signal to the transmission unit 103.

[0110] The transmitting unit 103 performs, for example, OFDM or other transmission waveform generation processing on the signal input from the signal generating unit 102. Furthermore, in the case of OFDM transmission using a cyclic prefix (CP), for example, the transmitting unit 103 performs an inverse fast Fourier transform (IFFT) processing on the signal and adds a CP to the signal after the IFFT. Furthermore, the transmitting unit 103 performs, for example, RF processing such as D / A conversion or up-conversion on the signal and transmits the radio signal to the terminal 200 via an antenna.

[0111] The receiving unit 104 performs RF processing such as downconvert or A / D conversion on an uplink signal received from the terminal 200 via an antenna. In addition, in the case of OFDM transmission, the receiving unit 104 performs Fast Fourier Transform (FFT) processing on the received signal, and outputs the resulting frequency domain signal to the extracting unit 105.

[0112] The extraction unit 105 extracts, for example, based on information input from the control unit 101, a radio resource portion from which an uplink signal (for example, a PUSCH or a PUCCH) is transmitted, from the received signal input from the receiving unit 104, and outputs the extracted radio resource portion to the demodulation unit 106.

[0113] The demodulation unit 106 demodulates the uplink signal (for example, PUSCH or PUCCH) input from the extraction unit 105, for example, based on information input from the control unit 101. The demodulation unit 106 outputs the demodulation result to the decoding unit 107, for example.

[0114] The decoding unit 107 performs error correction decoding on the uplink signal (for example, PUSCH or PUCCH) based on, for example, the information input from the control unit 101 and the demodulation result input from the demodulation unit 106, and obtains a decoded received bit sequence. For example, if the decoded received bit sequence includes a CSI report from the terminal 200, the decoding unit 107 outputs the information to the control unit 101.

[0115] 17 is a block diagram showing an example configuration of a terminal 200 according to an embodiment of the present disclosure. For example, in FIG. 17, the terminal 200 includes a receiving unit 201, an extracting unit 202, a demodulating unit 203, a decoding unit 204, a control unit 205, a signal generating unit 206, and a transmitting unit 207.

[0116] At least one of the extraction unit 202, demodulation unit 203, decoding unit 204, control unit 205, and signal generation unit 206 shown in Fig. 17 may be included in the control unit shown in Fig. 6. Furthermore, at least one of the reception unit 201 and transmission unit 207 shown in Fig. 17 may be included in the communication unit shown in Fig. 6.

[0117] The receiving unit 201 receives, for example, a downlink signal (e.g., a downlink data signal or a downlink control signal) from the base station 100 via an antenna, and performs RF processing such as downconvert or A / D conversion on the radio received signal to obtain a received signal (baseband signal). Furthermore, when receiving an OFDM signal, the receiving unit 201 performs FFT processing on the received signal to convert it into the frequency domain. The receiving unit 201 outputs the received signal to the extracting unit 202.

[0118] Extraction section 202 extracts a radio resource portion that may include a downlink control signal from the received signal input from receiving section 201, based on, for example, information about the radio resource of the downlink control signal input from control section 205, and outputs the extracted radio resource portion to demodulation section 203. Furthermore, extraction section 202 extracts a radio resource portion that includes a downlink data signal, based on information about the radio resource of the data signal input from control section 205, and outputs the extracted radio resource portion to demodulation section 203. Furthermore, extraction section 202 extracts, for example, a radio resource portion that includes a CSI-RS, and outputs the extracted radio resource portion to control section 205.

[0119] The demodulation unit 203 demodulates the signal (for example, PDCCH or PDSCH) input from the extraction unit 202 based on information input from the control unit 205 , for example, and outputs the demodulation result to the decoding unit 204 .

[0120] The decoding unit 204 performs error correction decoding of the PDCCH or PDSCH using, for example, information input from the control unit 205 and the demodulation result input from the demodulation unit 203, and obtains, for example, a control signal or a downlink data signal. The decoding unit 204 outputs the control signal to the control unit 205.

[0121] The control unit 205 identifies information related to downlink transmission based on, for example, information obtained from the control signal input from the decoding unit 204, and outputs the information to the extraction unit 202, the demodulation unit 203, and the decoding unit 204. The control unit 205 also identifies information related to uplink transmission based on, for example, information obtained from the control signal input from the decoding unit 204, and outputs the information to the signal generation unit 206. The control unit 205 also generates information related to CSI reporting using the CSI measurement result based on the CSI-RS input from the extraction unit 202 by the method described above, and outputs the information to the signal generation unit 206.

[0122] Furthermore, the control unit 205 may output the CSI measurement results and information (e.g., an AI / ML model or a dataset of the AI / ML model) from the network (e.g., base station 100) to a function for processing AI / ML. Note that the function for processing AI / ML may be included in the terminal 200 or may be included in an external device (e.g., a server) connected to the terminal 200.

[0123] The signal generation unit 206 generates an uplink data signal or an uplink control signal based on the CSI report or information related to uplink transmission input from the control unit 205, encodes and modulates the bit string of the generated signal, and maps it to radio resources. The signal generation unit 206 outputs the uplink signal onto which the signal has been mapped to the transmission unit 207, for example.

[0124] The transmitter 207 generates a transmission signal waveform, such as OFDM, for the signal input from the signal generator 206. Furthermore, in the case of OFDM transmission or DFT-s-OFDM transmission using a CP, for example, the transmitter 207 performs IFFT processing on the signal and adds a CP to the signal after IFFT. Alternatively, when the transmitter 207 generates a single-carrier waveform such as a DFT-s-OFDM waveform, a DFT unit (not shown) may be added before the signal generator 206. Furthermore, the transmitter 207 performs RF processing, such as D / A conversion and up-conversion, on the transmission signal, and transmits the radio signal to the base station 100 via an antenna.

[0125] The above describes the embodiments according to non-limiting examples of the present disclosure.

[0126] Note that the CSI report in an embodiment of the present disclosure may be reported from terminal 200 via any uplink signal (e.g., Radio Resource Control (RRC), Medium Access Control Control Element (MAC-CE), Uplink Control Information (UCI)). The timing of the CSI report may be any timing during the CSI measurement period for data collection, or may be timing after the completion of the CSI measurement period for data collection.

[0127] Furthermore, data collection on the network side by the terminal 200 reporting ground-truth CSI is not limited to the use case of CSI feedback, but is common to use cases in which AI / ML is applied to the air interface. The CSI prediction described in one embodiment of the present disclosure is an example, and can be applied to other use cases, such as CSI compression, a combination of CSI compression and prediction, beam prediction in the space or time domain, and positioning.

[0128] Furthermore, application of an embodiment of the present disclosure is not limited to reporting ground-truth CSI for network-side data collection to apply AI / ML to the air interface. For example, an embodiment of the present disclosure may also be applied to periodic or semi-persistent L1 or MAC reporting over a long period of time.

[0129] (Supplementary Note) Information indicating whether the terminal 200 supports the functions, operations, or processes described in each of the above-described embodiments and each supplementary note may be transmitted (or notified) from the terminal 200 to the base station 100, for example, as capability information or capability parameters of the terminal 200.

[0130] The capability information may include an information element (IE) that individually indicates whether or not the terminal 200 supports at least one of the functions, operations, or processes described in the above-described embodiments, modifications, and supplements. Alternatively, the capability information may include an information element that indicates whether or not the terminal 200 supports a combination of any two or more of the functions, operations, or processes described in the above-described embodiments, modifications, and supplements.

[0131] For example, the base station 100 may determine (or decide or assume) the functions, operations, or processes that the terminal 200 that transmitted the capability information supports (or does not support) based on the capability information received from the terminal 200. The base station 100 may perform operations, processes, or control according to the determination result based on the capability information. For example, the base station 100 may control processing related to an AI / ML model based on the capability information received from the terminal 200.

[0132] Note that the fact that terminal 200 does not support some of the functions, operations, or processes described in the above-described embodiments, modifications, and supplementary notes may be interpreted as meaning that such some of the functions, operations, or processes are restricted in terminal 200. For example, information or a request regarding such restrictions may be notified to base station 100.

[0133] Information regarding the capabilities or limitations of terminal 200 may, for example, be defined in a standard, or may be implicitly notified to base station 100 in association with information known at base station 100 or information transmitted to base station 100.

[0134] The above has described the embodiments, modifications, and supplementary notes according to a non-limiting example of the present disclosure.

[0135] (Control Signal) In the present disclosure, a downlink control signal (or downlink control information) related to an embodiment of the present disclosure may be, for example, a signal (or information) transmitted in a Physical Downlink Control Channel (PDCCH) of a physical layer, or a signal (or information) transmitted in a Medium Access Control Control Element (MAC CE) or Radio Resource Control (RRC) of a higher layer. Furthermore, the signal (or information) is not limited to being notified by a downlink control signal, but may be predefined in a specification (or standard) or preconfigured in a base station and a terminal.

[0136] In the present disclosure, an uplink control signal (or uplink control information) related to an embodiment of the present disclosure may be, for example, a signal (or information) transmitted in a PUCCH of a physical layer, or a signal (or information) transmitted in a MAC CE or RRC of a higher layer. Furthermore, the signal (or information) is not limited to being notified by an uplink control signal, but may be predefined in a specification (or standard) or preconfigured in a base station and a terminal. Furthermore, the uplink control signal may be replaced with, for example, uplink control information (UCI), 1st stage sidelink control information (SCI), or 2nd stage SCI.

[0137] (Base Station) In an embodiment of the present disclosure, the base station may be a Transmission Reception Point (TRP), a cluster head, an access point, a Remote Radio Head (RRH), an eNodeB (eNB), a gNodeB (gNB), a Base Station (BS), a Base Transceiver Station (BTS), a parent device, a gateway, or the like. In sidelink communication, a terminal may play the role of a base station. Instead of a base station, a relay device that relays communication between an upper node and a terminal may be used. Alternatively, a roadside unit may be used.

[0138] (Uplink / Downlink / Sidelink) An embodiment of the present disclosure may be applied to, for example, any of the uplink, downlink, and sidelink. For example, an embodiment of the present disclosure may be applied to a Physical Uplink Shared Channel (PUSCH), a Physical Uplink Control Channel (PUCCH), or a Physical Random Access Channel (PRACH) in the uplink, a Physical Downlink Shared Channel (PDSCH), a PDCCH, or a Physical Broadcast Channel (PBCH) in the downlink, or a Physical Sidelink Shared Channel (PSSCH), a Physical Sidelink Control Channel (PSCCH), or a Physical Sidelink Broadcast Channel (PSBCH) in the sidelink.

[0139] The PDCCH, PDSCH, PUSCH, and PUCCH are examples of a downlink control channel, a downlink data channel, an uplink data channel, and an uplink control channel, respectively. The PSCCH and PSSCH are examples of a sidelink control channel and a sidelink data channel. The PBCH and PSBCH are examples of a broadcast channel, and the PRACH is an example of a random access channel.

[0140] (Data Channel / Control Channel) An embodiment of the present disclosure may be applied to, for example, either a data channel or a control channel. For example, the channel in an embodiment of the present disclosure may be replaced with any of the data channels PDSCH, PUSCH, and PSSCH, or the control channels PDCCH, PUCCH, PBCH, PSCCH, and PSBCH.

[0141] (Reference Signal) In one embodiment of the present disclosure, a reference signal is, for example, a signal known by both a base station and a mobile station, and may also be called a Reference Signal (RS) or a pilot signal. The reference signal may be any of a Demodulation Reference Signal (DMRS), a Channel State Information - Reference Signal (CSI-RS), a Tracking Reference Signal (TRS), a Phase Tracking Reference Signal (PTRS), a Cell-specific Reference Signal (CRS), or a Sounding Reference Signal (SRS).

[0142] (Time Interval) In one embodiment of the present disclosure, the unit of time resource is not limited to one or a combination of slots and symbols, but may be, for example, a time resource unit such as a frame, a superframe, a subframe, a slot, a time slot, a subslot, a minislot, a symbol, an Orthogonal Frequency Division Multiplexing (OFDM) symbol, a Single Carrier-Frequency Division Multiplexing Access (SC-FDMA) symbol, or another time resource unit. Furthermore, the number of symbols included in one slot is not limited to the number of symbols exemplified in the above-mentioned embodiment, and may be another number of symbols.

[0143] (Frequency Band) An embodiment of the present disclosure may be applied to either a licensed band or an unlicensed band.

[0144] (Communication) An embodiment of the present disclosure may be applied to communication between a base station and a terminal (Uu link communication), communication between terminals (Sidelink communication), or Vehicle to Everything (V2X) communication. For example, the channel in an embodiment of the present disclosure may be replaced with any of PSCCH, PSSCH, Physical Sidelink Feedback Channel (PSFCH), PSBCH, PDCCH, PUCCH, PDSCH, PUSCH, or PBCH.

[0145] An embodiment of the present disclosure may be applied to a terrestrial network, a non-terrestrial network (NTN) using a satellite or a high altitude pseudo satellite (HAPS), or a terrestrial network in which transmission delay is large compared to the symbol length or slot length, such as a network with a large cell size or an ultra-wideband transmission network.

[0146] (SBFD) In ​​one embodiment of the present disclosure, operations on uplink, downlink, and sidelink symbols may be applied to symbols (e.g., SBFD symbols) on which SBFD (Subband Non-Overlapping Full Duplex, Subband Full Duplex) operations or controls are performed. In SBFD symbols, a frequency domain (or frequency resource, frequency band) is divided into multiple frequency domains (e.g., subbands, RB sets, subbands, or sub-BWPs (Bandwidth Parts)). A terminal transmits and receives in different directions (e.g., downlink or uplink) in units of subbands, which are the divided domains. In SBFD symbols, a terminal may transmit and receive in one direction, either uplink or downlink, but not in the other direction. On the other hand, a base station may be capable of transmitting and receiving on both the uplink and downlink simultaneously. SBFD symbols may have a smaller frequency domain available for downlink use than symbols that transmit and receive only downlink use. Also, SBFD symbols may have a smaller frequency domain available for uplink use than symbols that transmit and receive only uplink use.

[0147] In addition, in the SBFD symbol, a terminal may transmit and receive uplink and downlink simultaneously. In this case, the frequency domain in which the terminal transmits and the frequency domain in which the terminal receives may not be adjacent, but may be separated by a frequency interval (also called a frequency gap).

[0148] In addition, different transmission and reception directions in subband units, which are divided areas, may include transmission and reception of side links.

[0149] (XDD: Cross Division Duplex) In one embodiment of the present disclosure, the operation for uplink, downlink, and sidelink symbols may be applied to symbols (e.g., full duplex symbols) where full duplex operation or control is performed. In a full duplex symbol, both the terminal and the base station can simultaneously transmit and receive on the uplink and downlink. In a full duplex symbol, the terminal and the base station may simultaneously transmit and receive in an available frequency region (or frequency resource, frequency band), or may simultaneously transmit and receive in a partial frequency region (i.e., transmission or reception may be performed in other frequency regions). In this case, the frequency region in which the base station or terminal transmits and receives may not be adjacent, but may have a frequency interval (also called a frequency gap). Furthermore, for the purpose of, for example, reducing interference, either the terminal or the base station may simultaneously transmit and receive (i.e., the other may transmit or receive).

[0150] In addition, full duplex operation may be applied to an operation in which a terminal can simultaneously transmit and receive sidelinks, or to an operation in which a terminal can simultaneously transmit and receive sidelinks and uplinks or downlinks.

[0151] (Antenna Port) In one embodiment of the present disclosure, an antenna port refers to a logical antenna (antenna group) consisting of one or more physical antennas. For example, an antenna port does not necessarily refer to a single physical antenna, but may refer to an array antenna consisting of multiple antennas. For example, the number of physical antennas that an antenna port is composed of is not specified, and the antenna port may be specified as the smallest unit by which a terminal station can transmit a reference signal. Furthermore, an antenna port may also be specified as the smallest unit by which a weighting of a precoding vector is multiplied.

[0152] <5G NR System Architecture and Protocol Stack> The 5G NR system architecture generally assumes an NG-RAN (Next Generation - Radio Access Network) including gNBs. The gNBs provide UE-side termination of the NG radio access user plane (SDAP / PDCP / RLC / MAC / PHY) and control plane (RRC) protocols. The gNBs are connected to each other via an Xn interface. The gNBs are also connected to a Next Generation Core (NGC) via a Next Generation (NG) interface, more specifically to an Access and Mobility Management Function (AMF) (e.g., a specific core entity that performs AMF) via an NG-C interface, and to a User Plane Function (UPF) (e.g., a specific core entity that performs UPF) via an NG-U interface. The NG-RAN architecture is shown in Figure 18 (see, for example, 3GPP TS 38.300 v15.6.0, section 4).

[0153] <RRC connection setup and reconfiguration procedure> This shows the NAS part of the interaction between the UE, gNB, and AMF (5GC entity) when the UE transitions from RRC_IDLE to RRC_CONNECTED (see TS 38.300 v15.6.0).

[0154] RRC is a higher layer signaling protocol used to configure the UE and gNB. The AMF prepares UE context data (including, for example, PDU session context, security keys, UE radio capabilities, UE security capabilities, etc.) and sends it to the gNB along with an INITIAL CONTEXT SETUP REQUEST. The gNB then activates AS security together with the UE. This is done by the gNB sending a SecurityModeCommand message to the UE, and the UE responding with a SecurityModeComplete message to the gNB. The gNB then sends an RRCReconfiguration message to the UE, and upon receiving an RRCReconfigurationComplete from the UE, the gNB performs reconfiguration to set up Signaling Radio Bearer 2 (SRB2) and Data Radio Bearer (DRB). For signaling-only connections, the steps related to RRCReconfiguration are omitted because SRB2 and DRB are not set up. Finally, the gNB notifies the AMF that the setup procedure is complete with an INITIAL CONTEXT SETUP RESPONSE.

[0155] Therefore, the present disclosure provides a 5th Generation Core (5GC) entity (e.g., AMF, SMF, etc.) that includes: a control circuit that, upon operation, establishes a Next Generation (NG) connection with a gNodeB; and a transmitter that, upon operation, transmits an initial context setup message to the gNodeB via the NG connection so that a signaling radio bearer between the gNodeB and a user equipment (UE) is set up. Specifically, the gNodeB transmits Radio Resource Control (RRC) signaling, including a resource allocation configuration information element (IE), to the UE via the signaling radio bearer. The UE then transmits in uplink or receives in downlink based on the resource allocation configuration.

[0156] <QoS Control> The 5G Quality of Service (QoS) model is based on QoS flows and supports both QoS flows that require a guaranteed flow bit rate (Guaranteed Bit Rate QoS flows (GBR)) and QoS flows that do not require a guaranteed flow bit rate (non-GBR QoS flows). Thus, at the NAS level, a QoS flow is the finest granularity of QoS classification in a PDU session. A QoS flow is identified within a PDU session by a QoS Flow ID (QFI) carried in an encapsulation header over the NG-U interface.

[0157] For each UE, 5GC establishes one or more PDU sessions. For each UE, the NG-RAN establishes, for example, at least one Data Radio Bearer (DRB) for each PDU session. Additional DRBs for the QoS flows of that PDU session can be configured later (when this is up to the NG-RAN). The NG-RAN maps packets belonging to different PDU sessions to different DRBs. NAS-level packet filters in the UE and 5GC associate UL and DL packets with QoS flows, while AS-level mapping rules in the UE and NG-RAN associate UL and DL QoS flows with DRBs.

[0158] (Open-RAN) The base station described in each embodiment (for example, a 5G NR base station called a gNB) may be configured with three functional modules: a Centralized Unit (CU), a Distributed Unit (DU), and a Radio Unit (RU).

[0159] A CU may be referred to as a centralized node, aggregation node, central station, aggregation station, or centralized unit. A DU may be referred to as an O-RAN Distributed Unit (O-DU), distributed node, distributed station, or distributed unit. An RU may be referred to as an O-RAN Radio Unit (O-RU), radio equipment, radio node, radio station, antenna unit, or radio unit.

[0160] There are several split options for the functional split configuration (or functional split point) between CU, DU, and RU. The term "functional split point" is sometimes referred to as "split," "option," or "split option."

[0161] Examples of "division options" include the following division options 1 to 8. The functions of the base station described in each embodiment may be divided into a CU, a DU, and an RU by any of the following division options 1 to 8. For example, the CU, DU, and RU may be functionally divided, or the functions may be divided only between the CU and DU or only between the DU and RU. (1) Segmentation option 1: Between RRC (radio resource control) and PDCP (2) Segmentation option 2: Between PDCP and RLC (High-RLC) (3) Segmentation option 3: Between High-RLC and Low-RLC (4) Segmentation option 4: Between RLC (Low-RLC) and MAC (High-MAC) (5) Segmentation option 5: Between High-MAC and Low-MAC (6) Segmentation option 6: Between MAC (Low-MAC) and PHY (High-PHY) (7) Segmentation option 7: Between High-PHY and Low-PHY (8) Segmentation option 8: Between PHY (Low-PHY) and RF

[0162] The functional split point between the CU and O-DU may be split option 2. The section between the CU and O-DU is called midhaul, and the F1 interface is specified by 3GPP. The section between the O-DU and O-RU is called fronthaul, and the functional split point may be split option 7-2x, which is adopted as the O-RAN fronthaul specification.

[0163] Figure 19 shows an example of functional division of the gNB base station functions into CU, O-DU, and O-RU using Split Option 2 and Split Option 7-2x.

[0164] The CU may have, for example, a radio resource control (RRC) function, a service data adaptation protocol (SDAP) function, and a packet data convergence protocol (PDCP) function.

[0165] The O-DU may include, for example, a radio link control (RLC) function, a MAC function, and a higher physical layer (HIGH-PHY) function. The HIGH-PHY function may include an encoding function, a scrambling function, a modulation function, a layer mapping function, a precoding function, and a resource element (RE) mapping function for downlink (DL) transmission. The HIGH-PHY function may also include a decoding function, a descrambling function, a demodulation function, a layer demapping function, and a resource element (RE) demapping function for uplink (UL) reception.

[0166] The O-RU may have, for example, a LOW-PHY function and an RF function. The LOW-PHY function may also have, for downlink transmission, a beamforming function, an IFFT (Inverse First Fourier Transform) + CP (Cyclic Prefix) assignment function, and a D / A (Digital to Analog) conversion function. The LOW-PHY function may also have, for uplink reception, an A / D (Analog to Digital) conversion function, a CP removal + FFT (First Fourier Transform) function, and a beamforming function.

[0167] In addition, if the O-DU does not have a precoding function, the O-RU may have a precoding function.

[0168] The O-RU may have functionality related to LBT (listen before talk).

[0169] The evolving Common Public Radio Interface (eCPRI) is specified as the communication method between the O-DU and O-RU in Split Option 7-2x. In Split Option 7-2x, eCPRI transmits and receives sampling sequences of the in-phase (I) and quadrature (Q) components of OFDM signals in the frequency domain, as well as information used for beamforming in antennas and time synchronization signals.

[0170] Information transmitted by the signals described in each embodiment (PDCCH, PUCCH, PDSCH, PUSCH, MAC CE, RRC, etc.) may be transmitted between the O-DU and the O-RU via the eCPRI User Plane (U-Plane) or Control Plane (C-Plane).

[0171] When the functions described in each embodiment are performed in the O-RU by functional division, the O-DU may control the O-RU by transmitting information for controlling the functions via a control signal (e.g., eCPRI) between the O-DU and the O-RU.

[0172] When the functions described in each embodiment are performed in the O-DU by functional division, the O-RU may receive the results of the functions performed in the O-DU via a control signal (e.g., eCPRI) and control the O-RU based on the received results.

[0173] The CU, O-DU, and O-RU may be deployed in physically different devices with their respective functions connected by optical fiber or the like, or some or all of their functions may be deployed in the same physical device.

[0174] The CU and O-DU may be logical entities implemented as software running on a server in the cloud or the like as a virtualized RAN (virtual Radio Access Network: vRAN). Also, some or all of the functions of the CU and O-DU may be provided as a virtualized network function (Network Functions Virtualization: NFV) service.

[0175] The transceiver does not have to be a radio transceiver, but may be, for example, a network transceiver, an optical transceiver, etc. The radio resources allocated by the O-DU may be resources for wireless communication between the O-RU and the UE.

[0176] The present disclosure can be realized in software, hardware, or software in conjunction with hardware.

[0177] Each functional block used in the description of the above embodiments may be partially or entirely realized as an LSI, which is an integrated circuit, and each process described in the above embodiments may be partially or entirely controlled by a single LSI or a combination of LSIs. The LSI may be composed of individual chips, or may be composed of a single chip that includes some or all of the functional blocks. The LSI may have data input and output. Depending on the degree of integration, the LSI may also be called an IC, system LSI, super LSI, or ultra LSI.

[0178] The integrated circuit method is not limited to LSI, and may be realized by a dedicated circuit, a general-purpose processor, or a dedicated processor. Also, a field programmable gate array (FPGA) that can be programmed after LSI manufacturing, or a reconfigurable processor that can reconfigure the connections and settings of circuit cells within the LSI, may be used. The present disclosure may be realized as digital processing or analog processing.

[0179] Furthermore, if an integrated circuit technology that can replace LSI emerges due to advances in semiconductor technology or other derivative technologies, it is natural that such technology may be used to integrate functional blocks. The application of biotechnology, etc. is also a possibility.

[0180] The present disclosure may be implemented in any type of apparatus, device, or system (collectively referred to as a communications apparatus) that has a communications function. The communications apparatus may include a radio transceiver and processing / control circuitry. The radio transceiver may include a receiver and a transmitter, or both functions. The radio transceiver (transmitter and receiver) may include a radio frequency (RF) module and one or more antennas. The RF module may include an amplifier, an RF modulator / demodulator, or the like. Non-limiting examples of communication devices include telephones (e.g., cell phones, smartphones), tablets, personal computers (PCs) (e.g., laptops, desktops, notebooks), cameras (e.g., digital still / video cameras), digital players (e.g., digital audio / video players), wearable devices (e.g., wearable cameras, smartwatches, tracking devices), game consoles, digital book readers, telehealth / telemedicine devices, communication-enabled vehicles or mobile transportation (e.g., cars, airplanes, ships), and combinations of the above devices.

[0181] The communication devices are not limited to portable or mobile devices, but also include any kind of non-portable or fixed equipment, devices, and systems, such as smart home devices (such as home appliances, lighting equipment, smart meters or measuring devices, control panels, etc.), vending machines, and any other "things" that may exist on an IoT (Internet of Things) network.

[0182] Communications include data communications via cellular systems, wireless LAN systems, communication satellite systems, and the like, as well as data communications via combinations of these.

[0183] A communications apparatus also includes devices such as controllers and sensors connected or coupled to a communications device that performs the communications functions described in this disclosure, such as controllers and sensors that generate control and data signals used by the communications device to perform the communications functions of the communications apparatus.

[0184] The communication apparatus also includes infrastructure facilities, such as base stations, access points, and any other apparatus, device, or system that communicates with or controls the various apparatuses listed above, but are not limited to these.

[0185] A terminal according to one embodiment of the present disclosure includes a control circuit that determines, in data collection for an artificial intelligence model for reporting channel state information, information regarding measurement status in multiple measurement occasions for measuring the channel state information or information regarding the time of the multiple measurement occasions, and a transmission circuit that transmits the measured channel state information and the information regarding the measurement status or the information regarding the time in groups including the multiple measurement occasions.

[0186] In one embodiment of the present disclosure, the control circuit determines information regarding the time corresponding to a measurement occasion in which the channel state information is successfully measured among the plurality of measurement occasions, and does not determine information regarding the time corresponding to a measurement occasion in which the channel state information is not successfully measured.

[0187] In one embodiment of the present disclosure, the information about the measurement status includes information about whether the channel state information was successfully measured in each of the plurality of measurement occasions.

[0188] In one embodiment of the present disclosure, the information about the measurement status includes information about the measurement status of the channel state information in each of the plurality of measurement occasions.

[0189] In one embodiment of the present disclosure, the measurement situations include a situation in which the channel state information is successfully measured, a situation in which the channel state information is not measured depending on the channel quality, and a situation in which the channel state information is not measured regardless of the channel quality.

[0190] In one embodiment of the present disclosure, the measurement situations include a situation in which the channel state information is successfully measured, a situation in which the channel state information is not measured due to an inactive state of Discontinuous Reception (DRX), a situation in which the channel state information is not measured due to the execution of a random access operation, and a situation in which the channel state information measurement fails due to a radio link failure.

[0191] A base station according to one embodiment of the present disclosure includes, in data collection for an artificial intelligence model for reporting channel state information, a receiving circuit that receives information on measurement status in multiple measurement occasions for measuring the channel state information or information on the time of the multiple measurement occasions, and the channel state information in groups including the multiple measurement occasions, and a control circuit that controls the data collection based on the channel state information and the information on the measurement status or the information on the time.

[0192] In a communication method according to one embodiment of the present disclosure, a terminal, in collecting data for an artificial intelligence model for reporting channel state information, determines information regarding measurement status in multiple measurement occasions for measuring the channel state information, or information regarding the time of the multiple measurement occasions, and transmits the measured channel state information and the information regarding the measurement status or the information regarding the time in groups including the multiple measurement occasions.

[0193] In a communication method according to one embodiment of the present disclosure, a base station, in collecting data for an artificial intelligence model for reporting channel state information, receives information on the measurement status in multiple measurement occasions for measuring the channel state information or information on the time of the multiple measurement occasions, and the channel state information in groups including the multiple measurement occasions, and controls the data collection based on the channel state information and the information on the measurement status or the information on the time.

[0194] The disclosures of the specification, drawings and abstract contained in Japanese Patent Application No. 2024-022164, filed February 16, 2024, are incorporated herein by reference in their entirety.

[0195] One embodiment of the present disclosure is useful in wireless communication systems.

[0196] 100 Base station 101, 205 Control unit 102, 206 Signal generation unit 103, 207 Transmission unit 104, 201 Reception unit 105, 202 Extraction unit 106, 203 Demodulation unit 107, 204 Decoding unit 200 Terminal

Claims

1. A terminal comprising: a control circuit for determining information regarding the measurement status of multiple measurement occasions for measuring the channel state information or information regarding the time of the multiple measurement occasions in data collection for an artificial intelligence model for reporting channel state information; and a transmission circuit for transmitting the measured channel state information and the information regarding the measurement status or the information regarding the time in groups including the multiple measurement occasions.

2. The terminal according to claim 1, wherein the control circuit determines information about the time corresponding to a measurement occasion in which the channel state information was successfully measured among the plurality of measurement occasions, and does not determine information about the time corresponding to a measurement occasion in which the channel state information was not successfully measured.

3. The terminal according to claim 1, wherein the information on the measurement status includes information on whether the channel state information was successfully measured in each of the plurality of measurement occasions.

4. The terminal according to claim 1, wherein the information on the measurement status includes information on the measurement status of the channel state information in each of the plurality of measurement occasions.

5. The terminal according to claim 4, wherein the measurement situations include a situation in which the channel state information is successfully measured, a situation in which the channel state information measurement fails depending on the channel quality, and a situation in which the channel state information measurement is not performed regardless of the channel quality.

6. The terminal according to claim 4, wherein the measurement situations include a situation in which the channel state information is successfully measured, a situation in which the channel state information is not measured due to an inactive state of Discontinuous Reception (DRX), a situation in which the channel state information is not measured due to execution of a random access operation, and a situation in which the channel state information measurement fails due to a radio link failure.

7. A base station comprising: a receiving circuit for receiving, in data collection for an artificial intelligence model for reporting channel state information, information on the measurement status in multiple measurement occasions for measuring the channel state information or information on the time of the multiple measurement occasions, and the channel state information in groups including the multiple measurement occasions; and a control circuit for controlling the data collection based on the channel state information and the information on the measurement status or the information on the time.

8. A communication method in which a terminal, in collecting data for an artificial intelligence model for reporting channel state information, determines information regarding the measurement status in multiple measurement occasions for measuring the channel state information or information regarding the time of the multiple measurement occasions, and transmits the measured channel state information and the information regarding the measurement status or the information regarding the time in groups including the multiple measurement occasions.

9. A communications method in which a base station, in collecting data for an artificial intelligence model to report channel state information, receives information on the measurement status in multiple measurement occasions for measuring the channel state information or information on the time of the multiple measurement occasions, and the channel state information in groups including the multiple measurement occasions, and controls the data collection based on the channel state information and the information on the measurement status or the information on the time.

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