Terminal, base station, and communication method

Abstract

The terminal of the present invention is provided with: a control circuit that, in data collection for an artificial intelligence model for prediction of channel state information, determines control information related to a condition or situation specific to an implementation of a communication device or a communication object in measurement of channel state information; and a transmission circuit that transmits the control information to the communication object.

Description

Technical Field

[0001] This disclosure relates to terminals, base stations, and communication methods. Background Technology

[0002] In recent years, against the backdrop of the expansion and diversification of wireless services, the rapid development of the Internet of Things (IoT) is anticipated. The application of mobile communication is expanding beyond information terminals such as smartphones to all areas, including vehicles, homes, home appliances, and industrial equipment. To support this service diversification, in addition to increasing system capacity, significant improvements in the performance and functionality of mobile communication systems are required to meet various necessary conditions such as the increase in the number of connected devices and low latency. Fifth-generation mobile communication systems (5G) feature high capacity and ultra-high speed (eMBB), massive machine-type communication (mMTC), and ultra-reliable and low-latency communication (URLLC), providing flexible wireless communication to meet diverse needs.

[0003] The 3rd Generation Partnership Project (3GPP), an international standards organization, is developing specifications for New Radio (NR), one of the wireless interfaces for 5G.

[0004] Existing technical documents

[0005] Non-patent literature

[0006] Non-patent literature 1: RP-221348, “Revised SID: Study on Artificial Intelligence (AI) / Machine Learning (ML) for NR Air Interface,” Qualcomm (Moderator), June 2022.

[0007] Non-patent literature 2: 3GPP TS 37.320 V17.5.0, “Radio measurement collection for Minimization of Drive Tests (MDT),” September 2023. Summary of the Invention

[0008] However, there is still room for research into methods to improve the efficiency of wireless communication.

[0009] The non-limiting embodiments disclosed herein help to provide terminals, base stations, and communication methods that can improve the efficiency of wireless communication.

[0010] A terminal according to one embodiment of this disclosure includes: a control circuit that, during data acquisition for an artificial intelligence model used for reporting channel state information, determines information related to the measurement status of a plurality of measurement opportunities for measuring the channel state information or information related to the time of the plurality of measurement opportunities; and a transmission circuit that transmits the measured channel state information, the information related to the measurement status, or the information related to the time, in units of groups including the plurality of measurement opportunities.

[0011] Furthermore, these broad or specific methods can be implemented by systems, apparatuses, methods, integrated circuits, computer programs, or recording media, or by any combination of systems, apparatuses, methods, integrated circuits, computer programs, and recording media.

[0012] According to one embodiment of this disclosure, the efficiency of wireless communication can be improved.

[0013] Further advantages and effects of one embodiment of this disclosure will be illustrated by the specification and drawings. These advantages and / or effects are provided by the various embodiments and the features described in the specification and drawings, but not necessarily all of them need to be provided in order to obtain one or more of the same features. Attached Figure Description

[0014] Figure 1 This is a diagram illustrating an example of channel state information (CSI) compression in both the spatial and frequency domains using artificial intelligence (AI) / machine learning (ML) techniques.

[0015] Figure 2 This is a diagram illustrating an example of CSI prediction using AI / ML technology.

[0016] Figure 3 This is a block diagram illustrating an example of data collection on the network side.

[0017] Figure 4This is a diagram illustrating an example where CSI was not measured during a CSI measurement opportunity.

[0018] Figure 5 This is a block diagram illustrating a structural example of a portion of a base station.

[0019] Figure 6 This is a block diagram illustrating a structural example of a portion of a terminal.

[0020] Figure 7 This is a diagram showing an example of a CSI report.

[0021] Figure 8 This is a diagram showing an example of a data sequence from a CSI report.

[0022] Figure 9 This is a diagram showing an example of a CSI report.

[0023] Figure 10 This is a diagram showing an example of a data sequence from a CSI report.

[0024] Figure 11 This is a diagram showing an example of a CSI report.

[0025] Figure 12 This is a diagram showing an example of a data sequence from a CSI report.

[0026] Figure 13 This is a diagram showing an example of a CSI report.

[0027] Figure 14 This is a diagram showing an example of a data sequence from a CSI report.

[0028] Figure 15 This is a diagram illustrating an example of the operation of a terminal and a base station.

[0029] Figure 16 This is a block diagram illustrating an example of the structure of a base station.

[0030] Figure 17 This is a block diagram showing an example of the terminal's structure.

[0031] Figure 18 This is a diagram of an exemplary architecture for a 3GPP NR system.

[0032] Figure 19 This is a diagram of an exemplary functional segmentation in 5G O-RAN. Detailed Implementation

[0033] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the accompanying drawings.

[0034] The basic functionality of eMBB or URLLC was standardized in Release 15. In Release 16 and later, extensions were made for Industrial IoT (IoT) for URLLC, V2X (Vehicle-to-Everything), or for Non-Terrestrial Networks (NTN) including satellites. The 3GPP extended specifications have been called "5G-Advanced" since Release 18 (e.g., also known as Rel.18).

[0035] Furthermore, the development of artificial intelligence (AI) technologies such as machine learning (ML) has been significant, and their application in mobile communications has been continuously studied. Within 3GPP, research and standardization are underway for applying AI / ML to various purposes. Research on AI / ML applications related to radio interfaces began with version 18 (see, for example, non-patent literature 1). Representative use cases for AI / ML include channel state information (CSI) feedback, beam control, and location estimation.

[0036] In NR, for example, downlink communication employs an access method based on Orthogonal Frequency Division Multiplexing (OFDM). Furthermore, to improve communication quality or data rate, Multiple-Input Multiple-Output (MIMO) is used. To effectively utilize MIMO performance, closed-loop control is implemented, channel estimation is performed at the terminal (e.g., also known as user equipment (UE)), and CSI is fed back to the base station (e.g., also known as gNB). Based on the fed-back CSI, the base station applies transmission precoding, etc., and performs downlink communication.

[0037] For CSI feedback, the expectation is that it can achieve higher performance with less control information.

[0038] Furthermore, for example, when the wireless channel changes over time due to terminal movement, the wireless channel may change between the time the terminal estimates the channel and the time the base station actually performs downlink communication. In this case, there may be a difference between the channel calculated by the base station for transmitting precoding (e.g., the channel estimated and fed back by the terminal) and the channel when the base station actually transmits. This difference in channel may become a factor that degrades the performance of downlink communication using precoding.

[0039] In the application of AI / ML technology for wireless interfaces in version 18, for example, for CSI feedback (CSI reporting), methods for compressing CSI information in the spatial and frequency domains using AI / ML technology (hereinafter also referred to as CSI compression) and time-domain CSI prediction using AI / ML technology on the terminal side are being studied.

[0040] For example, in machine learning (ML), features can be automatically extracted by training AI / ML models (e.g., artificial intelligence models) using massive amounts of training data, such as neural networks. In CSI compression, for example, algorithms called autoencoders, primarily used for dimensionality reduction and reconstruction of image data, can be utilized. For example, ... Figure 1 As shown, the CSI matrix, represented by two-dimensional domains in spatial and frequency domains, is regarded as an image. The encoding unit (encoder) used for compression in 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") side.

[0041] Furthermore, in CSI prediction, such as Figure 2 As shown, multiple CSI samples (historic CSI) measured by the terminal over time are used as input to the AI / ML model (CSI prediction model), and future CSI (predicted CSI) are used as the output of the AI / ML model. Therefore, by feeding back the CSI predicted by the terminal to the base station, it is hoped that the performance degradation of downlink communication caused by the difference between the channel used by the base station when calculating transmission precoding (the channel estimated and fed back by the terminal) and the channel when the base station actually transmits is suppressed.

[0042] For the training and application of AI / ML models for CSI compression and CSI prediction using AI / ML technologies (e.g., performance monitoring), it is desirable to study the steps or mechanisms of data collection.

[0043] In CSI compression employing AI / ML technology for encoding or decoding on both the terminal side and the base station / network side, the following method is being researched: data acquisition is performed on the network side, the network side trains the AI / ML models for both sides, and the AI / ML model (encoding or compression unit) on the terminal side is transmitted to the terminal side. Alternatively, in CSI prediction utilizing terminal-side AI / ML technology, there may be situations where data acquisition is performed on the network side (e.g., base station), the network side trains the AI / ML model, and the AI / ML model (or the dataset used for training the AI / ML model) is transmitted to the terminal side.

[0044] When data acquisition is performed on the network side, the network may, for example, notify the terminal of the configuration of reference signals used for CSI measurements, such as CSI-RS, to set up the terminal's CSI measurements. For example, ... Figure 3 As shown, the terminal reports the measured CSI (e.g., training data CSI or ground-truth CSI) to the network. Here, as... Figure 3 As shown, the report of true CSI from the terminal can be generated for each sample of the CSI measurement, or it can be generated for a group of multiple samples. In the report per sample, there is a one-to-one correspondence between the CSI measurement and the CSI report, with one CSI report containing the true CSI generated by one CSI measurement. In the report generated by a group, one CSI report contains the true CSI generated by multiple CSI measurements.

[0045] Here, at least in data acquisition for training, measurement time may be lengthy (e.g., minutes or hours) in order to collect a sufficient dataset. Furthermore, to report channel information with sufficient accuracy, the ground truth CSI used to train AI / ML models may be a channel matrix, eigenvectors, or a codebook with relatively large information content. In this case, the information content (overhead) of the ground truth CSI may increase. On the other hand, the latency requirements for CSI reporting for AI / ML model training are expected to be significantly relaxed compared to existing CSI reporting. Therefore, in data acquisition for AI / ML model training, group-based reporting (e.g., also known as "measurement logs"), where the terminal records (logs) and stores (stores) CSI measurements, and then aggregates and reports the recorded and stored CSI measurements, is more efficient than reporting CSI per sample in data acquisition for AI / ML model training.

[0046] However, the terminal may not be able to measure, record, and save CSI measurement values ​​during the designated CSI measurement occasion (also known as "CSI measurement opportunity" or "CSI-RS measurement opportunity"). For example, such as... Figure 4As shown, when the terminal is in an inactive state of Discontinuous Reception (DRX), performing a random access operation, or experiencing a radio link failure, the terminal may not measure CSI during the set CSI measurement opportunities (e.g., no CSI measurement or CSI measurement failure).

[0047] Regarding the terminal operation when CSI measurement and CSI reporting are configured for data acquisition, further research is needed on how to handle situations where the terminal fails to measure CSI during the configured CSI measurement opportunities. Additionally, the CSI reporting mechanism for group-based CSI reporting in response to such events also warrants further investigation.

[0048] For example, the following describes an example of terminal operation and CSI reporting methods when the terminal fails to measure CSI during a set CSI measurement opportunity, provided that the terminal is configured for CSI measurement and CSI reporting for data acquisition.

[0049] As a first method, one approach is to report true CSI only when the terminal successfully performs a CSI measurement, and the measurement log of the CSI report consists of a single CSI measurement value. This method is equivalent to the per-sample CSI reporting described above, where there is a one-to-one correspondence between CSI measurements and CSI reports, with each CSI report containing the true CSI generated by a single CSI measurement. The network can determine in which measurement opportunity the terminal did not measure CSI based on the opportunity where no CSI report was sent from the terminal. However, compared to reporting on a group basis, this method may have a higher reporting frequency. Furthermore, since this method cannot apply information compression utilizing time-based statistics, the overhead of each CSI report increases, and the total overhead is expected to increase. Additionally, while the network can determine in which CSI measurement opportunity the terminal did not measure CSI, it cannot determine the reason why the terminal did not measure CSI (e.g., the CSI measurement status within the terminal).

[0050] As a second approach, one method is to report the true CSI only when the terminal successfully performs a CSI measurement, and the measurement log of the CSI report consists of multiple CSI measurements. This method is equivalent to the group-based CSI reporting described above, where a single CSI report contains the true CSI generated from multiple CSI measurements. Compared to reporting per sample, this method can reduce the frequency of CSI reporting and can apply information compression using time-based statistics, thus potentially reducing the overhead of CSI reporting. However, in this method, for example, if only the true CSI when a CSI measurement is successfully performed is reported, the network may have difficulty determining in which CSI measurement opportunity the terminal failed to measure CSI, and the reason why the terminal did not measure CSI cannot be determined. This could affect the accuracy of network data acquisition.

[0051] In one non-limiting embodiment of this disclosure, a terminal operation and CSI reporting method are described when a terminal is configured for CSI measurement and CSI reporting for data acquisition in order to perform data acquisition on the network side, and an event occurs in which the terminal fails to measure CSI during a configured CSI measurement opportunity.

[0052] For example, in a non-limiting embodiment of this disclosure, based on a CSI report measurement log consisting of multiple CSI measurement values ​​grouped together, the CSI report measurement log, in addition to the true CSI value when the terminal successfully performed the CSI measurement, also records and saves information related to the CSI measurement time or the status of the CSI measurement, and reports this information to the network. This is expected to improve the data acquisition accuracy on the network side.

[0053] The following describes non-limiting embodiments of this disclosure.

[0054] It should be noted that CSI compression and CSI prediction are described below as an example of the objects of AI / ML models. However, the objects of AI / ML models are not limited to CSI compression and CSI prediction. They can also be applied to other use cases where data is collected on the network side and the terminal reports the CSI measurement results (e.g., true CSI).

[0055] [Overview of Communication Systems]

[0056] One aspect of the communication system disclosed herein includes, for example, at least one base station and at least one terminal.

[0057] Figure 5 This is a block diagram illustrating a structural example of a base station 100 according to an embodiment of the present disclosure. Figure 6 This is a block diagram illustrating a structural example of a portion of a terminal 200 according to an embodiment of the present disclosure.

[0058] exist Figure 5 In the base station 100 shown, the communication unit (e.g., corresponding to the receiving circuit) receives channel state information, as well as information related to the measurement status of the multiple measurement opportunities or time-related information of the multiple measurement opportunities, in groups of data acquisition for an artificial intelligence model (e.g., an AI / ML model) used to report channel state information (e.g., CSI). The control unit (e.g., corresponding to the control circuit) controls the data acquisition based on the channel state information and the information related to the measurement status or time-related information.

[0059] exist Figure 6 In the terminal 200 shown, the control unit (e.g., corresponding to the control circuit) determines, during data acquisition for an artificial intelligence model (e.g., an AI / ML model) used to report channel state information (e.g., CSI), information related to the measurement status of multiple measurement opportunities or information related to the time of multiple measurement opportunities. The communication unit (e.g., corresponding to the transmission circuit) transmits the measured channel state information, as well as the information related to the measurement status or the time-related information, in groups including multiple measurement opportunities.

[0060] (Implementation Method 1)

[0061] The network (e.g., base station 100) may notify terminal 200 of the configuration of a reference signal for CSI measurement, such as CSI-RS, to set up CSI measurement for terminal 200.

[0062] Terminal 200 reports the measured CSIs (e.g., training data or ground truth CSIs) to the network. Here, the reporting of ground truth CSIs from terminal 200 is done in groups comprising multiple samples (i.e., on a group-by-group basis). In a group-by-group CSI report, one CSI report contains ground truth CSIs generated from multiple CSI measurements. Furthermore, when reporting CSIs on a group-by-group basis, multiple CSI reference resources can be set for one CSI report. For example, for the multiple CSI measurements and ground truth CSIs corresponding to one CSI report, CSI reference resources can be set separately for each of them.

[0063] In this embodiment, the CSI report utilizes the Minimization of Drive Tests (MDT) mechanism (e.g., see Non-Patent Document 2). MDT is a specification for wireless measurement acquisition, allowing the terminal to include timestamps in each MDT measurement. For example, in existing NR systems, the basic unit for MDT timestamps that can be recorded in the log is the second.

[0064] In this embodiment, for example, such as Figure 7 As shown, in addition to the true CSI value when a CSI measurement is successfully performed, terminal 200 also records and saves the timestamp corresponding to the time (CSI measurement time) of the successful CSI measurement opportunity in its log, and summarizes and reports the recorded and saved information to the network. That is, terminal 200 determines the information related to the measurement time (e.g., timestamp) corresponding to the CSI measurement opportunity that was successfully performed among multiple CSI measurement opportunities, but does not determine the information related to the measurement time corresponding to the CSI measurement opportunity that was not successfully performed (e.g., CSI measurement opportunity that failed or CSI measurement was not performed).

[0065] exist Figure 7 In the example, terminal 200 sends the following CSI report to the network, which includes timestamps #1, #3, #N-1, and #N of the CSI measurement opportunities where CSI measurements were successfully performed, and the CSI measurement values ​​(e.g., true CSI) for these CSI measurement opportunities. Figure 7 As shown, the timestamps of CSI measurement opportunities that were not successfully performed are not included in the measurement logs reported to the network.

[0066] The basic unit of the timestamp for the recorded CSI measurement opportunity can be the same as the existing NR specification (e.g., seconds), or a finer granularity can be introduced to be consistent with the granularity of CSI measurement opportunities for data acquisition (e.g., time shorter than seconds), or other units.

[0067] The timestamp information can be in the format YY-MM-DD HH:MM:SS, or other formats.

[0068] Figure 8 This is a diagram illustrating an example of the data sequence of the CSI report in this embodiment.

[0069] like Figure 8 As shown, the CSI report includes the CSI measurement value (e.g., true CSI) of a CSI measurement opportunity that was successfully performed, along with the timestamp corresponding to that CSI measurement opportunity.

[0070] Thus, in this embodiment, during data acquisition for the AI / ML model used in CSI reporting, terminal 200 determines time-related information for multiple CSI measurement opportunities and sends a group-based CSI report containing CSI measurement values ​​and time-related information for the CSI measurement opportunities to the network. Consequently, the network can determine the CSI measurement opportunities where terminal 200 did not measure CSI, based on the timestamp information included in the CSI report (e.g., information related to CSI measurement opportunities where terminal 200 measured CSI). Therefore, even if an event occurs in the group-based CSI report where terminal 200 did not measure CSI, the network can still determine whether CSI measurement was performed in each CSI measurement opportunity of the CSI report object, thereby improving the data acquisition accuracy on the network side. Therefore, according to this embodiment, the efficiency of wireless communication can be improved.

[0071] (A variation of Implementation Method 1)

[0072] It should be noted that information related to CSI measurement time is not limited to timestamps. For example, instead of timestamps, information related to CSI measurement time can also be frame numbers, slot numbers, or symbol numbers. Additionally, where the maximum number of true CSI reports that can be included in a single CSI report is known to the network, the information related to CSI measurement time can be a number, which is the number of the true CSI report or the corresponding CSI measurement opportunity included in a single CSI report.

[0073] According to the above variation, compared with the case of using timestamps, the overhead of reporting information related to CSI measurement time can be reduced.

[0074] (Implementation Method 2)

[0075] The network (e.g., base station 100) may notify terminal 200 of the configuration of a reference signal for CSI measurement, such as CSI-RS, to set up CSI measurement for terminal 200.

[0076] Terminal 200 reports the measured CSIs (e.g., training data or ground truth CSIs) to the network. Here, the reporting of ground truth CSIs from terminal 200 is done in groups comprising multiple samples (i.e., on a group-by-group basis). In a group-by-group CSI report, one CSI report contains ground truth CSIs generated from multiple CSI measurements. Furthermore, when reporting CSIs on a group-by-group basis, multiple CSI reference resources can be set for one CSI report. For example, for the multiple CSI measurements and ground truth CSIs corresponding to one CSI report, CSI reference resources can be set separately for each of them.

[0077] In Implementation 1, since the CSI report contains information related to the CSI measurement time, the overhead of the CSI report may increase if the overhead of the information related to the CSI measurement time is large.

[0078] In this embodiment, for example, such as Figure 9 As shown, in addition to the true CSI value when a CSI measurement is successfully performed, terminal 200 also records and saves information related to whether a CSI measurement was successfully performed (e.g., whether the CSI measurement was successful or failed) among the multiple CSI measurement opportunities (e.g., multiple CSI measurement opportunities within a group) of the CSI reporting object, and summarizes and reports the recorded and saved information to the network.

[0079] For example, information related to whether a CSI measurement was successful could be a 1-bit message (0 or 1) corresponding to each CSI measurement opportunity. For example, it could be set to "0" if a CSI measurement was successful and "1" if a CSI measurement failed, or vice versa.

[0080] In addition to information related to whether CSI measurements were successfully performed on each CSI measurement opportunity, the CSI report may also include the true CSI for the CSI measurement opportunities that were successfully performed.

[0081] Figure 10 This is a diagram illustrating an example of the data sequence of the CSI report in this embodiment.

[0082] like Figure 10 As shown, the CSI report includes information indicating whether a CSI measurement was successfully performed in each CSI measurement opportunity (e.g., CSI measurement opportunities #1 to #N) (success: "0", failure: "1"), as well as the CSI measurement value (e.g., true CSI) for the CSI measurement opportunities that were successfully performed.

[0083] Thus, in this embodiment, during data acquisition for the AI / ML model used in CSI reporting, terminal 200 determines information related to the measurement status (e.g., whether CSI measurement was successfully performed) of multiple CSI measurement opportunities and sends a group-based CSI report containing CSI measurement values ​​and information related to the CSI measurement status to the network. Therefore, the network can determine the CSI measurement opportunities where terminal 200 did not measure CSI based on information related to whether CSI measurement was successfully performed in each CSI measurement opportunity. Thus, even if an event occurs in the group-based CSI report where terminal 200 did not measure CSI, the network can still determine whether CSI measurement was performed in each CSI measurement opportunity of the CSI report object, thereby improving the data acquisition accuracy on the network side.

[0084] Furthermore, according to this embodiment, by using information related to whether CSI measurement was successfully performed in each CSI measurement opportunity, the overhead of CSI reporting can be reduced compared to reporting information related to CSI measurement time.

[0085] Therefore, according to this embodiment, the efficiency of wireless communication can be improved.

[0086] It should be noted that the CSI report in this embodiment is not limited to... Figure 10 The example shown illustrates this. For instance, a CSI report can report the CSI measurement value (true CSI) for successful CSI measurement opportunities and report information indicating the failure of a CSI measurement for failed CSI measurement opportunities. That is, the CSI report may not include information indicating whether a CSI measurement was successfully performed in a CSI measurement opportunity that was initially successful.

[0087] (Implementation Method 3)

[0088] The network (e.g., base station 100) may notify terminal 200 of the configuration of a reference signal for CSI measurement, such as CSI-RS, to set up CSI measurement for terminal 200.

[0089] Terminal 200 reports the measured CSIs (e.g., training data or ground truth CSIs) to the network. Here, the reporting of ground truth CSIs from terminal 200 is done in groups comprising multiple samples (i.e., on a group-by-group basis). In a group-by-group CSI report, one CSI report contains ground truth CSIs generated from multiple CSI measurements. Furthermore, when reporting CSIs on a group-by-group basis, multiple CSI reference resources can be set for one CSI report. For example, for the multiple CSI measurements and ground truth CSIs corresponding to one CSI report, CSI reference resources can be set separately for each of them.

[0090] In Implementation 1, since the CSI report contains information related to the CSI measurement time, the overhead of the CSI report may increase if the overhead of the information related to the CSI measurement time is high. Furthermore, in Implementation 2, the network cannot determine why the terminal 200 did not perform a CSI measurement.

[0091] In this embodiment, for example, such as Figure 11 As shown, in addition to the true CSI value when a CSI measurement is successfully performed, terminal 200 also records and saves information related to the CSI measurement status of each of the multiple CSI measurement opportunities (e.g., multiple CSI measurement opportunities within a group) of the CSI reporting object in the log, and summarizes and reports the recorded and saved information to the network.

[0092] For example, information related to the measurement status during a CSI measurement opportunity may include information corresponding to the following conditions: "CSI measurement successfully performed"; "CSI measurement failed due to channel quality"; and "No measurement was performed due to other transceiver operations in the terminal, not due to channel quality." For example, if a CSI measurement fails due to a radio link failure, terminal 200 may report a "CSI measurement failed due to channel quality" condition. Additionally, for example, if terminal 200 is in a DRX inactive state or fails to perform a CSI measurement due to a random access operation, terminal 200 may report a "No measurement was performed due to other transceiver operations in the terminal, not due to channel quality" condition.

[0093] For example, the information related to the measurement status in a CSI measurement opportunity can be 2 bits of information corresponding to each CSI measurement opportunity. As an example, a "successful CSI measurement" status can be represented by "00", a "CSI measurement failed due to channel quality" status can be represented by "01", and a "no measurement was not performed due to other transmit / receive operations in the terminal, not channel quality" status can be represented by "10". It should be noted that the correspondence between the measurement status in a CSI measurement opportunity and the 2 bits of information is not limited to this; other correspondences can also be used.

[0094] In addition, for CSI measurement opportunities that are successfully performed, the CSI report may include the corresponding true CSI value, in addition to information related to the measurement status of the CSI measurement opportunity.

[0095] Figure 12 This is a diagram illustrating an example of the data sequence of the CSI report in this embodiment.

[0096] like Figure 12As shown, the CSI report contains information (2 bits) indicating the measurement status of each CSI measurement opportunity (e.g., CSI measurement opportunities #1 to #N), and the CSI measurement value (e.g., true CSI) for CSI measurement opportunities that were successfully performed (e.g., the information indicating the measurement status is "00").

[0097] Thus, in this embodiment, during data acquisition for the AI / ML model used in CSI reporting, terminal 200 determines information related to the measurement status of multiple CSI measurement opportunities and sends a group-based CSI report containing CSI measurement values ​​and information related to the CSI measurement status (successful CSI measurement and non-CSI measurement) to the network. Therefore, the network can determine, based on the information related to the measurement status of each CSI measurement opportunity, the CSI measurement opportunities in which terminal 200 did not measure CSI and the reasons for the non-measurement (e.g., whether it depends on channel quality). Thus, even if an event occurs in the group-based CSI report where terminal 200 did not measure CSI, the network can determine whether CSI measurement was performed in each CSI measurement opportunity of the CSI report object and the reasons for non-measurement, thereby improving the data acquisition accuracy on the network side.

[0098] Furthermore, according to this embodiment, by using information related to the measurement status in each CSI measurement opportunity, the overhead of CSI reporting can be reduced compared to reporting information related to CSI measurement time.

[0099] Therefore, according to this embodiment, the efficiency of wireless communication can be improved.

[0100] It should be noted that the CSI report in this embodiment is not limited to... Figure 12 The example shown illustrates this. For instance, a CSI report can report the CSI measurement value (true CSI) for successful CSI measurement opportunities and information indicating the measurement status for failed CSI measurement opportunities. That is, the CSI report may not include information indicating the measurement status of successful CSI measurement opportunities.

[0101] (Implementation Method 4)

[0102] The network (e.g., base station 100) may notify terminal 200 of the configuration of a reference signal for CSI measurement, such as CSI-RS, to set up CSI measurement for terminal 200.

[0103] Terminal 200 reports the measured CSIs (e.g., training data or ground truth CSIs) to the network. Here, the reporting of ground truth CSIs from terminal 200 is done in groups comprising multiple samples (i.e., on a group-by-group basis). In a group-by-group CSI report, one CSI report contains ground truth CSIs generated from multiple CSI measurements. Furthermore, when reporting CSIs on a group-by-group basis, multiple CSI reference resources can be set for one CSI report. For example, for the multiple CSI measurements and ground truth CSIs corresponding to one CSI report, CSI reference resources can be set separately for each of them.

[0104] In this embodiment, for example, such as Figure 13 As shown, in addition to the true CSI value when a CSI measurement is successfully performed, terminal 200 also records and saves information related to the CSI measurement status of each of the multiple CSI measurement opportunities (e.g., multiple CSI measurement opportunities within a group) of the CSI reporting object in the log, and summarizes and reports the recorded and saved information to the network.

[0105] For example, information related to the measurement status in a CSI measurement opportunity may include information corresponding to the following conditions: "CSI measurement successfully performed"; "CSI measurement not performed due to DRX inactivity"; "CSI measurement not performed due to random access operation"; and "CSI measurement failed due to radio link failure".

[0106] For example, information related to the measurement status of a CSI measurement opportunity could be N bits of information corresponding to each CSI measurement opportunity. Using N bits of information, it is possible to report information related to the measurement status of a CSI measurement opportunity. N This includes situations such as "CSI measurement successfully performed".

[0107] In addition, for CSI measurement opportunities that are successfully performed, the CSI report may include the corresponding true CSI value, in addition to information related to the measurement status of the CSI measurement opportunity.

[0108] Figure 14 This is a diagram illustrating an example of the data sequence of the CSI report in this embodiment.

[0109] like Figure 14 As shown, the CSI report contains information (N bits of information) indicating the measurement status of each CSI measurement opportunity (e.g., CSI measurement opportunities #1 to #N). Figure 14The CSI measurement (e.g., true CSI) is the CSI measurement opportunity (e.g., the information indicating the measurement status is "00") that was successfully performed (N=2).

[0110] Thus, in this embodiment, during data acquisition for the AI / ML model used in CSI reporting, terminal 200 determines information related to the measurement status of multiple CSI measurement opportunities and sends a group-based CSI report containing CSI measurement values ​​and information related to the CSI measurement status (successful CSI measurement, no CSI measurement) to the network. Therefore, the network can determine, based on the information related to the measurement status of each CSI measurement opportunity, the CSI measurement opportunities in which terminal 200 did not measure CSI and the reasons for the terminal 200's failure to measure CSI (e.g., DRX inactivity, random access operation, or radio link failure). Therefore, in this embodiment, compared to embodiment 3, the network can determine more detailed reasons why terminal 200 did not measure CSI. Thus, even if an event occurs in a group-based CSI report where terminal 200 did not measure CSI, the network can determine whether CSI measurement was performed in each CSI measurement opportunity of the CSI report object and the reasons for not measuring CSI, thereby improving the accuracy of data acquisition on the network side.

[0111] Furthermore, according to this embodiment, by using information related to the measurement status in each CSI measurement opportunity, the overhead of CSI reporting can be reduced compared to reporting information related to CSI measurement time.

[0112] Therefore, according to this embodiment, the efficiency of wireless communication can be improved.

[0113] It should be noted that the CSI report in this embodiment is not limited to... Figure 14 The example shown illustrates this. For instance, a CSI report can report the CSI measurement value (true CSI) for successful CSI measurement opportunities and information indicating the measurement status for failed CSI measurement opportunities. That is, the CSI report may not include information indicating the measurement status of successful CSI measurement opportunities.

[0114] In addition, information related to CSI measurement conditions is not limited to the examples above, and other conditions may be defined in place of the examples above or based on the examples above.

[0115] (Other implementation methods)

[0116] At least for data acquisition used in AI / ML model training, if we assume that the latency requirements are significantly relaxed compared to existing CSI reports, we can obtain statistical properties such as the probability, frequency, or number of occurrences of the data sequences included in the CSI report. Furthermore, we can compress the data sequences based on these statistical properties or probabilistic models, thereby reducing the overhead of CSI reports. For example, Huffman coding, run-length encoding, or dictionary encoding can be applied to data sequence compression.

[0117] For example, in network-side data acquisition, for group-based CSI reports that summarize and report CSI measurements recorded and stored in logs, the CSI measurements recorded and stored in logs can be compressed using any of the following methods (Option).

[0118] <Option 1>

[0119] In Option 1, the data sequence of the log containing CSI measurements and the aforementioned information related to the measurement status is processed in bits, and the entire data sequence contained in the CSI report for data acquisition is compressed.

[0120] For example, run-length code, which uses bits as the unit, can be used to compare data with the preceding and following data bit by bit, and replace the identical data with the value of the data and the number of consecutive occurrences, thereby compressing the data.

[0121] <Option 2>

[0122] In Option 2, the data sequence of logs containing CSI measurements and the aforementioned measurement status information is processed in units of CSI measurements (or CSI measurements and information related to the measurement status), and the entire data sequence contained in the CSI report for data acquisition is compressed.

[0123] For example, CSI measurements (or CSI measurements and information related to the measurement status) can be treated as a symbol, and Huffman codes, which encode each symbol based on statistical properties such as the probability of occurrence of each symbol, can be used for data compression.

[0124] Alternatively, for example, CSI measurements (or CSI measurements and information related to the measurement status) can be treated as a single symbol, and dictionary compression, such as LZ77, can be used to compress recurring symbols.

[0125] Additionally, option 1, bit-based data compression, can be further applied to the compressed data sequence.

[0126] <Option 3>

[0127] In Option 3, firstly, the entire data sequence contained in the CSI report for data acquisition is divided into multiple partial sequences. Here, each partial sequence may contain multiple CSI measurements and the aforementioned measurement-related information. Next, each partial sequence is compressed in bits, as in Option 1. Then, each bit-compressed partial sequence is treated as a single symbol and compressed using Huffman coding or dictionary-based compression, as in Option 2.

[0128] The choice of data compression method and the setting of the data compression interval (the length of the data sequence to which data compression is applied) may depend on the terminal implementation or may be standardized in a standard specification. In the case of the terminal implementation, terminal 200 may report to the network information related to the type of data compression applied to group-based CSI reports. This information may be defined as additional condition or assistance information for the terminal 200 used for data acquisition.

[0129] The above explains the compression method for the data sequences included in the CSI report.

[0130] [Operational Example of Base Station 100 and Terminal 200]

[0131] Figure 15 This is a flowchart illustrating an operational example of the base station 100 (referred to as base station / network) and terminal 200 in this embodiment.

[0132] exist Figure 15 In this process, the base station / network sends the settings related to CSI measurement and reporting to the terminal 200 (S101).

[0133] Terminal 200 measures CSI based on settings related to CSI measurement and reporting (S102). Based on the CSI measurement result, terminal 200 sends a CSI report to the base station / network (S103). When making a CSI report, terminal 200 reports information related to the CSI measurement time or information related to the measurement status during the CSI-RS transmission opportunity to the base station / network.

[0134] The base station / network, for example, based on a CSI report from terminal 200 (e.g., CSI measurement results, and information related to the CSI measurement time or measurement status during CSI-RS transmission opportunities), collects data for an AI / ML model to output predicted CSI (S104), and uses the collected data to train and update the AI / ML model (S105). Then, the base station / network sends (or transmits, distributes) the AI / ML model or the dataset of the AI / ML model to terminal 200 (S106).

[0135] [Base station structure]

[0136] Figure 16 This is a block diagram illustrating a structural example of base station 100. Figure 16 In this base station 100, there are a control unit 101, a signal generation unit 102, a transmission unit 103, a receiving unit 104, an extraction unit 105, a demodulation unit 106, and a decoding unit 107.

[0137] It should be noted that, Figure 16 At least one of the control unit 101, signal generation unit 102, extraction unit 105, demodulation unit 106, and decoding unit 107 shown may be included. Figure 5 In the control unit shown. Additionally... Figure 16 At least one of the transmitting unit 103 and the receiving unit 104 shown may be included Figure 5 shown in the Communications Department.

[0138] The control unit 101 determines, for example, the control information related to CSI measurement and reporting of the terminal 200, and outputs the determined control information to the signal generation unit 102. The control information related to CSI measurement and reporting may include, for example, the configuration of a reference signal for CSI measurement such as CSI-RS, and the CSI report configuration for the terminal 200 to report CSI.

[0139] Additionally, the control unit 101 can, for example, output CSI measurement data (e.g., measurements based on CSI reports or SRS) or auxiliary information input from the decoding unit 107 to functions that process AI / ML (e.g., data acquisition functions or AI / ML model training functions). It should be noted that the AI / ML processing function can be contained within the base station 100 or in a node different from the base station 100.

[0140] Additionally, the control unit 101 may, for example, determine information for the terminal 200 to receive downlink signals and output the determined information to the signal generation unit 102. The information for the terminal 200 to receive downlink signals may include, for example, information related to resource allocation of the downlink data channel (e.g., PDSCH: Physical Downlink Shared Channel) or the downlink control channel (e.g., PDCCH: Physical Downlink Control Channel), and information related to the coding / modulation scheme (e.g., MCS: Modulation and Coding Scheme).

[0141] Additionally, the control unit 101 determines, for example, information for the terminal 200 to transmit uplink signals, 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 for the terminal 200 to transmit uplink signals may include, for example, information related to resource allocation of the uplink data channel (e.g., PUSCH: Physical Uplink Shared Channel) or the uplink control channel (e.g., PUCCH: Physical Uplink Control Channel), and information related to the coding / modulation method (e.g., MCS). Furthermore, the information for transmitting uplink signals may include, for example, information related to CSI reporting.

[0142] The signal generation unit 102 uses information input from the control unit 101 to generate a data signal or control signal bit string, and applies encoding as needed. Furthermore, the signal generation unit 102 modulates the encoded bit string to generate a modulated signal (e.g., a symbol string), and maps it to a radio resource indicated by the control unit 101. The signal generation unit 102 outputs the mapped signal to the transmission unit 103.

[0143] The transmitting unit 103 performs OFDM transmission waveform generation processing on the signal input from the signal generation unit 102, for example. Additionally, in the case of OFDM transmission using a cyclic prefix (CP), the transmitting unit 103 performs an Inverse Fast Fourier Transform (IFFT) on the signal and appends a CP to the IFFT-derived signal. Furthermore, the transmitting unit 103 performs RF (Radio Frequency) processing on the signal, such as D / A conversion or up-conversion, and transmits the wireless signal to the terminal 200 via an antenna.

[0144] The receiving unit 104 performs RF processing, such as down-conversion or A / D conversion, on the uplink signal received from the terminal 200 via the antenna. Alternatively, 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 extraction unit 105.

[0145] Extraction unit 105 extracts, for example, the radio resource portion that transmits uplink signals (e.g., PUSCH or PUCCH) from the received signal input by receiving unit 104 based on information input from control unit 101, and outputs the extracted radio resource portion to demodulation unit 106.

[0146] The demodulation unit 106 demodulates the uplink signal (e.g., PUSCH or PUCCH) input from the extraction unit 105 based on information input from the control unit 101. The demodulation unit 106 outputs the demodulation result to the decoding unit 107, for example.

[0147] The decoding unit 107 performs error correction decoding on the uplink signal (e.g., PUSCH or PUCCH) based on information input from the control unit 101 and demodulation results input from the demodulation unit 106, to obtain the decoded received bit sequence. If, for example, the decoded received bit sequence contains a CSI report from the terminal 200, the decoding unit 107 outputs this information to the control unit 101.

[0148] [Terminal Structure]

[0149] Figure 17 This is a block diagram illustrating a structural example of a terminal 200 according to an embodiment of the present disclosure. For example, in Figure 17 In the terminal 200, there are a receiving unit 201, an extraction unit 202, a demodulation unit 203, a decoding unit 204, a control unit 205, a signal generation unit 206, and a transmitting unit 207.

[0150] It should be noted that, Figure 17 At least one of the extraction unit 202, demodulation unit 203, decoding unit 204, control unit 205, and signal generation unit 206 shown may be included Figure 6 In the control unit shown. Additionally... Figure 17 At least one of the receiving unit 201 and the transmitting unit 207 shown may be included Figure 6 shown in the Communications Department.

[0151] The receiving unit 201 receives downlink signals (e.g., downlink data signals or downlink control signals) from the base station 100 via an antenna, and performs RF processing such as down-conversion or A / D conversion on the received wireless signal to obtain a received signal (baseband signal). Alternatively, when receiving OFDM signals, the receiving unit 201 performs FFT processing on the received signal to convert it to the frequency domain. The receiving unit 201 then outputs the received signal to the extraction unit 202.

[0152] The extraction unit 202, for example, extracts radio resource portions that may contain downlink control signals from the received signal input by the receiving unit 201 based on radio resource information related to downlink control signals input from the control unit 205, and outputs this information to the demodulation unit 203. Additionally, the extraction unit 202 extracts radio resource portions containing downlink data signals based on radio resource information related to data signals input from the control unit 205, and outputs this information to the demodulation unit 203. Furthermore, the extraction unit 202, for example, extracts radio resource portions containing CSI-RS and outputs this information to the control unit 205.

[0153] The demodulation unit 203 demodulates the signal (e.g., PDCCH or PDSCH) input from the extraction unit 202 based on information input from the control unit 205, and outputs the demodulation result to the decoding unit 204.

[0154] The decoding unit 204 uses, for example, information input from the control unit 205 and demodulation results input from the demodulation unit 203 to perform error correction decoding on the PDCCH or PDSCH, to obtain, for example, control signals or downlink data signals. The decoding unit 204 outputs the control signal to the control unit 205.

[0155] Control unit 205, for example, determines information related to downlink transmission based on information obtained from control signals input from decoding unit 204, and outputs it to extraction unit 202, demodulation unit 203, and decoding unit 204. Additionally, control unit 205, for example, determines information related to uplink transmission based on information obtained from control signals input from decoding unit 204, and outputs it to signal generation unit 206. Furthermore, control unit 205, using the CSI measurement results obtained based on CSI-RS input from extraction unit 202, generates information related to CSI reporting using the above method, and outputs it to signal generation unit 206.

[0156] Additionally, the control unit 205 can output CSI measurement results and information from the network (e.g., base station 100) (e.g., AI / ML model or AI / ML model dataset) to the AI / ML processing function. It should be noted that the AI / ML processing function can be contained within the terminal 200 or in an external device (e.g., a server) connected to the terminal 200.

[0157] The signal generation unit 206 generates an uplink data signal or an uplink control signal based on the CSI report or uplink transmission-related information 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, for example, outputs the mapped uplink signal to the transmission unit 207.

[0158] The transmitting unit 207 generates a transmit signal waveform, such as OFDM, from the signal input from the signal generation unit 206. Additionally, in cases of OFDM transmission using CP or DFT-s-OFDM transmission, the transmitting unit 207 performs IFFT processing on the signal and adds CP to the IFFT-derived signal. Alternatively, when generating a single-carrier waveform such as a DFT-s-OFDM waveform, the transmitting unit 207 may add a DFT unit (not shown) before the signal generation unit 206. Furthermore, the transmitting unit 207 performs RF processing on the transmit signal, such as D / A conversion and up-conversion, and transmits the wireless signal to the base station 100 via an antenna.

[0159] The above describes various embodiments of a non-limiting example of this disclosure.

[0160] It should be noted that, in one embodiment of this disclosure, the CSI report can be reported from the terminal 200 via any uplink signal (e.g., Radio Resource Control (RRC), Medium Access Control (MAC-CE), or Uplink Control Information (UCI)). The timing of the CSI report can be any time within the CSI measurement period for data acquisition, or it can be at the end of the CSI measurement period for data acquisition.

[0161] Furthermore, network-side data acquisition via terminal 200 reporting true CSI is common to use cases that apply AI / ML to wireless interfaces and is not limited to CSI feedback use cases. The CSI prediction described in one embodiment of this disclosure is one example, and it can also be applied to other use cases such as CSI compression, a combination of CSI compression and prediction, beam prediction in the spatial or temporal domain, and positioning.

[0162] Furthermore, the application of one embodiment of this disclosure is not limited to truth CSI reports for network-side data acquisition used to apply AI / ML to wireless interfaces. For example, one embodiment of this disclosure can also be applied to long-term continuous periodic or semi-persistent L1 or MAC reports.

[0163] (Replenish)

[0164] Information indicating whether terminal 200 supports the functions, operations, or processes shown in the above embodiments and supplements can also be sent (or notified) by terminal 200 to base station 100 as capability information or capability parameters of terminal 200.

[0165] The capability information may also include an information element indicating whether the terminal 200 supports at least one of the functions, operations, and processes described in the above embodiments, variations, and supplements. Alternatively, the capability information may include an information element indicating whether the terminal 200 supports two or more combinations of the functions, operations, and processes described in the above embodiments, variations, and supplements.

[0166] Base station 100 can, for example, determine (or decide or envision) the functions, operations, or processes supported (or not supported) by the source terminal 200, based on capability information received from terminal 200. Base station 100 can implement operations, processes, or controls corresponding to the determination results based on the capability information. For example, base station 100 can control processing related to AI / ML models based on the capability information received from terminal 200.

[0167] It should be noted that terminal 200 does not support some of the functions, operations, or processes shown in the above embodiments, modifications, and supplements. Alternatively, in terminal 200, such functions, operations, or processes may be limited. For example, information or requests related to such limitations may also be notified to base station 100.

[0168] Information related to the capabilities or limitations of terminal 200 may be defined in a standard, or may be implicitly communicated to base station 100 in association with information known to base station 100 or information sent to base station 100.

[0169] The above describes various implementations, modifications, and additions of a non-limiting embodiment of this disclosure.

[0170] (Control signal)

[0171] In this disclosure, the downlink control signal (or downlink control information) associated with an embodiment of this disclosure may be, for example, a signal (or information) transmitted in the Physical Downlink Control Channel (PDCCH) of the physical layer, or a signal (or information) transmitted in a higher-layer Medium Access Control Element (MAC CE) or Radio Resource Control (RRC). Furthermore, the signal (or information) is not limited to being notified by a downlink control signal; it may also be predefined in a specification (or standard) or pre-set in the base station and terminal.

[0172] In this disclosure, the uplink control signal (or uplink control information) associated with an embodiment of this disclosure may be, for example, a signal (or information) transmitted in the physical layer PUCCH, or a signal (or information) transmitted in the higher layer MAC CE or RRC. Furthermore, the signal (or information) is not limited to being notified by the uplink control signal; it may also be predefined in a specification (or standard), or pre-set in the base station and terminal. Additionally, the uplink control signal may be replaced, for example, with uplink control information (UCI), first-stage sidelink control information (SCI), or second-stage SCI.

[0173] (Base station)

[0174] In one embodiment of this disclosure, the base station can be a Transmission Reception Point (TRP), cluster head, access point, Remote Radio Head (RRH), eNodeB (eNB), gNodeB (gNB), Base Station (BS), Base Transceiver Station (BTS), host, gateway, etc. Alternatively, in sidelink communication, the functions of the base station can also be performed by the terminal. Instead of a base station, it can also be a relay device for communication between a high-level relay node and the terminal. Additionally, it can be a roadside device.

[0175] (Uplink / Downlink / Sidelink)

[0176] An embodiment of this disclosure can be applied, for example, to any link in the uplink, downlink, or sidelink. For example, an embodiment of this disclosure can be applied to the Physical Uplink Shared Channel (PUSCH), Physical Uplink Control Channel (PUCCH), Physical Random Access Channel (PRACH) of the uplink, the Physical Downlink Shared Channel (PDSCH), PDCCH, Physical Broadcast Channel (PBCH) of the downlink, or the Physical Sidelink Shared Channel (PSSCH), Physical Sidelink Control Channel (PSCCH), and Physical Sidelink Broadcast Channel (PSBCH) of the sidelink.

[0177] It should be noted that PDCCH, PDSCH, PUSCH, and PUCCH are examples of downlink control channel, downlink data channel, uplink data channel, and uplink control channel, respectively. Additionally, PSCCH and PSSCH are examples of sidelink control channel and sidelink data channel, respectively. Furthermore, PBCH and PSBCH are examples of broadcast channels, and PRACH is an example of a random access channel.

[0178] (Data channel / Control channel)

[0179] An embodiment of this disclosure can be applied, for example, to any channel in the data channel and the control channel. For example, the channel in an embodiment of this disclosure can also be replaced with one of the data channel's PDSCH, PUSCH, PSSCH, and the control channel's PDCCH, PUCCH, PBCH, PSCCH, PSBCH.

[0180] (Reference signal)

[0181] In one embodiment of this disclosure, the reference signal is, for example, a signal known to both the base station and the mobile station, and is sometimes referred to as "RS (Reference Signal)" or "pilot signal". The reference signal can also be one of the following: Demodulation Reference Signal (DMRS), Channel State Information-Reference Signal (CSI-RS), Tracking Reference Signal (TRS), Phase Tracking Reference Signal (PTRS), Cell-specific Reference Signal (CRS), or Sounding Reference Signal (SRS).

[0182] (Time interval)

[0183] In one embodiment of this disclosure, the unit of time resource is not limited to one or a combination of time slots and symbols. For example, it can be a time resource unit such as a frame, superframe, subframe, time slot, time slot, sub-time slot, micro-time slot, or symbol, Orthogonal Frequency Division Multiplexing (OFDM) symbol, Single Carrier-Frequency Division Multiplexing Access (SC-FDMA) symbol, or other time resource units. Furthermore, the number of symbols contained in one time slot is not limited to the number of symbols exemplified in the above embodiments, and can also be other numbers of symbols.

[0184] (frequency band)

[0185] One embodiment of this disclosure can be applied to any band domain, whether it is an authorized band domain or an unauthorized band domain.

[0186] (communication)

[0187] One embodiment of this disclosure can be applied to any communication in base station-terminal communication (Uu link communication), terminal-to-terminal communication (sidelink communication), and vehicle-to-everything (V2X) wireless communication technology. For example, the channel in one embodiment of this disclosure can be replaced with one of PSCCH, PSSCH, Physical Sidelink Feedback Channel (PSFCH), PSBCH, PDCCH, PUCCH, PDSCH, PUSCH, and PBCH.

[0188] Furthermore, one embodiment of this disclosure can be applied to any network, including terrestrial networks and non-terrestrial networks (NTNs) that use satellites or High Altitude Pseudo Satellites (HAPS). Additionally, one embodiment of this disclosure can also be applied to terrestrial networks with transmission delays greater than the symbol length or time slot length, such as networks with large cell sizes and ultra-wideband transmission networks.

[0189] (SBFD)

[0190] In one embodiment of this disclosure, operations on symbols for uplink, downlink, and sidelink can also be applied to symbols (e.g., SBFD symbols) used for SBFD (Subband Non-overlapping Full-Duplex) operations or control. In an SBFD symbol, the frequency domain (or frequency resources, frequency band) is divided into multiple frequency domains (e.g., also called subbands, RB sets, sub-bands, sub-BWPs (BandWidth Parts)). The terminal transmits and receives in different directions (e.g., downlink or uplink) based on the divided areas, i.e., subbands. In an SBFD symbol, the terminal can transmit and receive in one direction of the uplink and downlink, but not in the other direction. Alternatively, the base station can also be configured to transmit and receive simultaneously in both the uplink and downlink. It is possible that, compared to symbols that only transmit and receive in the downlink, the SBFD symbol has less frequency domain available for the downlink. Additionally, it is possible that, compared to symbols that only transmit and receive in the uplink, the SBFD symbol has less frequency domain available for the uplink.

[0191] Alternatively, in SBFD symbols, the terminal can simultaneously transmit and receive uplink and downlink signals. In this case, the frequency domain for transmission and reception can be non-adjacent, leaving a frequency gap (also known as a frequency interval).

[0192] In addition, as different transmission and reception directions per sub-band (i.e., segmented area) unit, it may also include transmission and reception of side links.

[0193] (XDD: Cross-segment duplex)

[0194] In one embodiment of this disclosure, the operations for uplink, downlink, and sidelink symbols can also be applied to symbols for full-duplex operation or control (e.g., full-duplex symbols). In a full-duplex symbol, both the terminal and the base station can simultaneously transmit and receive uplink and downlink signals. A full-duplex symbol can employ simultaneous transmission and reception by the terminal and base station in the available frequency domain (or frequency resources, frequency band), or it can employ simultaneous transmission and reception in a portion of the frequency domain (i.e., transmission or reception can be performed in a frequency domain other than the available frequency domain). In this case, the frequency domains for transmission and reception by the base station or terminal may not be adjacent, but rather have a frequency gap (also called a frequency interval). Additionally, for example, for the purpose of reducing interference, operations where one of the terminal and the base station can simultaneously transmit and receive can be employed (i.e., the other party can either transmit or receive).

[0195] Furthermore, full-duplex operation can also be applied to terminals that can simultaneously perform sidelink transmission and reception. Additionally, full-duplex operation can also be applied to terminals that can simultaneously perform sidelink and uplink or downlink transmission and reception.

[0196] (Antenna port)

[0197] In one embodiment of this disclosure, an antenna port refers to a logical antenna (antenna group) composed of one or more physical antennas. For example, an antenna port may not necessarily refer to a single physical antenna; sometimes it refers to an array antenna composed of multiple antennas. For instance, instead of specifying how many physical antennas constitute an antenna port, it may be defined as the smallest unit that the terminal station can transmit a reference signal. Additionally, an antenna port is sometimes also defined as the smallest unit multiplied by a precoding vector.

[0198] <5G NR System Architecture and Protocol Stack>

[0199] The overall 5G NR system architecture is envisioned to include the gNB's NG-RAN (Next Generation Radio Access Network). The gNB provides UE-side termination for the NG radio access user plane (SDAP (Service Data Adaptation Protocol) / PDCP (Packet Data Convergence Protocol) / RLC (Radio Link Control) / MAC / PHY (Physical Layer)) and control plane (RRC) protocols. gNBs are interconnected via the Xn interface. Additionally, the gNB connects to the NGC (Next Generation Core) via the Next Generation (NG) interface, and more specifically, to the AMF (Access and Mobility Management Function) (e.g., a specific core entity implementing the AMF) via the NG-C interface, and to the UPF (User Plane Function) (e.g., a specific core entity implementing the UPF) via the NG-U interface. Figure 18 This refers to the NG-RAN architecture (e.g., refer to 3GPP TS 38.300 v15.6.0, section 4).

[0200] <The process of setting up and reconfiguring RRC connections>

[0201] The following illustrates the interaction between the UE, gNB, and AMF (5GC entity) when the UE transitions from RRC_IDLE (RRC idle) to RRC_CONNECTED (RRC connected) in the NAS section (refer to TS 38.300 v15.6.0).

[0202] RRC is a higher-level signaling (protocol) used for UE and gNB configuration. The AMF prepares UE context data (which may include, for example, PDU session context, security key, UE radio capabilities, and UE security capabilities) and sends it to the gNB along with an initial context setting request. Next, the gNB and UE activate AS security together. This is done by the gNB sending a Security Mode Command message to the UE, which responds with a Security Mode Complete message. Then, the gNB sends an RRC Reconfiguration message to the UE, and receives an RRC Reconfiguration Complete message from the UE for this message. This allows for the reconfiguration of the Signaling Radio Bearer 2 (SRB2) and Data Radio Bearer (DRB). For signaling-only connections, since SRB2 and DRB are not configured, the steps related to RRC reconfiguration can be omitted. Finally, the gNB notifies the AMF that the configuration process is complete using the Initial Context Setup Reply.

[0203] Therefore, this disclosure provides an entity (e.g., AMF, SMF, etc.) of a fifth-generation core network (5GC), comprising: a control circuit that, during operation, establishes a Next Generation (NG) connection with a gNodeB; and a transmission unit that, during operation, sends an initial context setting message to the gNodeB via the NG connection to set the signaling radio bearer between the gNodeB and the User Equipment (UE). Specifically, the gNodeB sends Radio Resource Control (RRC) signaling containing a Resource Allocation Setting Information Element (IE) to the UE via the signaling radio bearer. The UE then performs uplink transmission or downlink reception based on the resource allocation settings.

[0204] <QoS Control>

[0205] 5G's QoS (Quality of Service) model is based on QoS flows, supporting both QoS flows that require guaranteed bit rate (GBR) and QoS flows that do not require guaranteed bit rate (non-GBR QoS flows). Therefore, at the NAS level, QoS flows represent the finest granular QoS classification within a PDU session. QoS flows are determined within a PDU session based on the QoS Flow ID (QFI) transmitted via the encapsulation header through the NG-U interface.

[0206] For each UE, the 5GC establishes one or more PDU sessions. For each UE, in conjunction with the PDU session, for example, the NG-RAN establishes at least one Data Radio Bearer (DRB). Additionally, for the QoS flows of this PDU session, additional DRBs can be configured later (when to configure depends on the NG-RAN). The NG-RAN maps packets belonging to various PDU sessions to various DRBs. NAS-level packet filters in the UE and 5GC are used to associate UL packets and DL packets with QoS flows, while AS-level mapping rules in the UE and NG-RAN associate UL QoS flows and DL QoS flows with DRBs.

[0207] (Open-RAN)

[0208] The base station described in the various embodiments (e.g., a 5G NR base station referred to as gNB) can be composed of three functional modules: a centralized unit (CU), a distributed unit (DU), and a radio unit (RU).

[0209] A CU can be referred to as a centralized node, aggregation node, centralized station, aggregation station, or centralized unit. A DU can be referred to as an O-DU (O-RAN Distributed Unit), distributed node, distributed station, or distributed unit. A RU can be referred to as an O-RU (O-RAN Radio Unit), radio device, radio node, radio station, antenna unit, or radio unit.

[0210] The functional split configuration (or functional split point) between CU, DU, and RU specifies multiple split options. The term "functional split point" is sometimes also referred to as "split", "option", or "split option".

[0211] An example of the “segmentation options” is the following segmentation options 1 to 8. The functions of the base station described in the various embodiments can be segmented into CU, DU, RU by one of the following segmentation options 1 to 8. For example, functional segmentation can be performed between CU, DU, and RU, or only between CU and DU or between DU and RU.

[0212] (1) Split Option 1: Between RRC (Radio Resource Control) and PDCP

[0213] (2) Segmentation Option 2: Between PDCP and RLC (High-RLC)

[0214] (3) Segmentation Option 3: Between High-RLC and Low-RLC

[0215] (4) Segmentation Option 4: Between RLC (Low-RLC) and MAC (High-MAC)

[0216] (5) Splitting option 5: Between High-MAC and Low-MAC

[0217] (6) Segmentation Option 6: Between MAC (Low-MAC) and PHY (High-PHY)

[0218] (7) Splitting option 7: Between High-PHY and Low-PHY

[0219] (8) Splitting option 8: Between PHY (Low-PHY) and RF

[0220] The functional split point between the CU and O-DU can be Split Option 2. The connection between the CU and O-DU is called midhaul, and 3GPP specifies the F1 interface. Alternatively, the connection between the O-DU and O-RU is called fronthaul, and its functional split point can be Split Option 7-2x, which is adopted as the O-RAN fronthaul specification.

[0221] An example of splitting the gNB base station function into CU, O-DU, and O-RU using Split Option 2 and Split Option 7-2x is shown below. Figure 19 .

[0222] For example, a CU can have RRC (Radio Resource Control) functionality, SDAP (Service Data Adaptation Protocol) functionality, and PDCP (Packet Data Convergence Protocol) functionality.

[0223] For example, an O-DU can possess RLC (Radio Link Control) functionality, MAC functionality, and high-PHY functionality. Additionally, the high-PHY function can include encoding, scrambling, modulation, layer mapping, precoding, and RE (Resource Element) mapping functions for downlink (DL) transmission. Furthermore, the high-PHY function can include decoding, descrambling, demodulation, layer demapping, and RE (Resource Element) demapping functions for uplink (UL) reception.

[0224] For example, an O-RU can possess low-level physical layer (Low-PHY) functionality and RF functionality. Additionally, the Low-PHY functionality can include beamforming, IFFT (Inverse Fast Fourier Transform) + CP (Cyclic Prefix) addition, and D / A (Digital to Analog) conversion for downlink transmission. Furthermore, the Low-PHY functionality can include A / D (Analog to Digital) conversion, CP removal + FFT (Fast Fourier Transform), and beamforming for uplink reception.

[0225] In addition, when the O-DU does not have precoding capabilities, the O-RU can have precoding capabilities.

[0226] O-RU can have LBT (listen before talk) related functions.

[0227] As the communication method between O-DU and O-RU in Split Option 7-2x, eCPRI (Evolved Common Public Radio Interface) is specified. In Split Option 7-2x, eCPRI, in addition to transmitting and receiving sampled sequences of in-phase (I) and quadrature (Q) components of OFDM signals in the frequency domain, also transmits and receives information for beamforming in the antenna and timing synchronization signals.

[0228] Information transmitted using the signals (PDCCH, PUCCH, PDSCH, PUSCH, MAC CE, RRC, etc.) described in the various embodiments can be transmitted between O-DU and O-RU via the eCPRI user plane (U-Plane) or control plane (C-Plane).

[0229] When the functions described in the various embodiments are executed in the O-RU through function partitioning, the O-DU can use control signals (e.g., eCPRI) between the O-DU and the O-RU to send information for controlling the function, thereby controlling the O-RU.

[0230] When the functions described in the various embodiments are executed in the O-DU through function partitioning, the O-RU can receive the result of the function being executed in the O-DU through a control signal (e.g., eCPRI) and control the O-RU based on the received result.

[0231] The functions of CU, O-DU, and O-RU can be configured (deployed) in physically different devices connected by optical fibers, or some or all of their functions can be configured in physically identical devices.

[0232] CU and O-DU can be logical entities implemented as virtualized RAN (vRAN), or software running on cloud servers, etc. Furthermore, some or all of the functions of CU and O-DU can be provided as services of Network Functions Virtualization (NFV).

[0233] A transceiver is not necessarily a wireless transceiver; it can be a network transceiver, an optical transceiver, etc. The radio resources allocated by the O-DU can be resources used for wireless communication between the O-RU and the UE.

[0234] This disclosure can be implemented by software, hardware, or software in collaboration with hardware.

[0235] The functional blocks used in the above embodiments are implemented partially or wholly as LSIs (Large Scale Integration) of integrated circuits. The processes described in the above embodiments can also be controlled partially or wholly by a single LSI or a combination of LSIs. An LSI can be composed of individual chips, or it can be composed of a single chip containing part or all of the functional blocks. An LSI may also include data input and output. Depending on the degree of integration, an LSI may also be called an "IC (Integrated Circuit)," a "System LSI," a "Super LSI," or an "Ultra LSI."

[0236] The method of integrating the LSI is not limited to LSI; it can also be implemented using dedicated circuits, general-purpose processors, or special-purpose processors. Alternatively, it can utilize FPGAs (Field Programmable Gate Arrays) that are programmable after LSI fabrication, or reconfigurable processors that allow reconfiguration of the connections or configurations of the circuit blocks within the LSI. This disclosure can also be implemented for digital or analog processing.

[0237] Furthermore, if advancements in semiconductor technology or the development of other derivative technologies lead to integrated circuit technologies that can replace LSIs, these technologies could also be used to integrate functional blocks. There are also possibilities for applications such as biotechnology.

[0238] This disclosure can be implemented in all kinds of devices, apparatuses, and systems with communication capabilities (collectively referred to as "communication devices"). A communication device may also include a wireless transceiver and processing / control circuitry. The wireless transceiver may also include a receiving unit and a transmitting unit, or perform the functions of these units. The wireless transceiver (transmitting unit, receiving unit) may also include an RF (Radio Frequency) module and one or more antennas. The RF module may also include an amplifier, an RF modulator / demodulator, or similar devices. Non-limiting examples of communication devices include: telephones (mobile phones, smartphones, etc.), tablet computers, personal computers (PCs) (laptops, desktops, laptops, etc.), cameras (digital cameras, digital camcorders, etc.), digital players (digital audio / video players, etc.), wearable devices (wearable cameras, smartwatches, tracking devices, etc.), game consoles, e-book readers, remote health / telemedicine (remote healthcare / medical prescription) devices, vehicles or transportation vehicles with communication capabilities (cars, airplanes, ships, etc.), and combinations of the various devices described above.

[0239] Communication devices are not limited to portable or movable devices, but also include all kinds of devices, equipment, and systems that cannot be carried or fixed. Examples include: smart home devices (home appliances, lighting equipment, smart meters or meters, control panels, etc.), vending machines, and all other "things" that can exist on the IoT (Internet of Things) network.

[0240] In addition to data communication via cellular systems, wireless LAN (Local Area Network) systems, and communication satellite systems, communication also includes data communication via a combination of these systems.

[0241] In addition, the communication device also includes devices such as controllers or sensors that are connected or linked to a communication device performing the communication functions described in this disclosure. For example, it includes a controller or sensor that generates control signals or data signals used by the communication device to perform the communication functions of the communication device.

[0242] In addition, the communication device includes infrastructure equipment that communicates with or controls the various devices described above (not limited to these), such as base stations, access points, and all other devices, equipment, and systems.

[0243] A terminal according to one embodiment of this disclosure includes: a control circuit that, during data acquisition for an artificial intelligence model used for reporting channel state information, determines information related to the measurement status of a plurality of measurement opportunities for measuring the channel state information or information related to the time of the plurality of measurement opportunities; and a transmission circuit that transmits the measured channel state information, the information related to the measurement status, or the information related to the time, in units of groups including the plurality of measurement opportunities.

[0244] In one embodiment of this disclosure, the control circuit determines the time-related information corresponding to a measurement opportunity in which the channel state information measurement is successfully performed out of the plurality of measurement opportunities, but does not determine the time-related information corresponding to a measurement opportunity in which the channel state information measurement is not successfully performed.

[0245] In one embodiment of this disclosure, the information related to the measurement status includes information related to whether the channel state information was successfully measured in each of the plurality of measurement opportunities.

[0246] In one embodiment of this disclosure, the information related to the measurement status includes information related to the measurement status of the channel state information of each of the plurality of measurement opportunities.

[0247] In one embodiment of this disclosure, the measurement status includes: a status in which the channel state information is successfully measured; a status in which the channel state information measurement fails depending on channel quality; and a status in which the channel state information is not measured regardless of channel quality.

[0248] In one embodiment of this disclosure, the measurement status includes: a status in which the channel state information is successfully measured; a status in which the channel state information is not measured due to discontinuous reception, i.e., DRX inactivity; a status in which the channel state information is not measured due to random access operation; and a status in which the measurement of the channel state information fails due to a radio link failure.

[0249] A base station according to an embodiment of this disclosure includes: a receiving circuit that, in data acquisition for an artificial intelligence model for reporting channel state information, receives, in units of a group including multiple measurement opportunities for measuring the channel state information, information related to the measurement status of the multiple measurement opportunities or information related to the time of the multiple measurement opportunities; and a control circuit that controls the data acquisition based on the channel state information and the information related to the measurement status or the information related to the time.

[0250] In a communication method according to an embodiment of this disclosure, a terminal performs the following steps: during data acquisition for an artificial intelligence model used for reporting channel state information, determining information related to the measurement status of a plurality of measurement opportunities for measuring the channel state information or information related to the time of the plurality of measurement opportunities; and transmitting the measured channel state information, the information related to the measurement status, or the information related to the time, in units of a group including the plurality of measurement opportunities.

[0251] In a communication method according to an embodiment of this disclosure, a base station performs the following steps: in data acquisition for an artificial intelligence model used for reporting channel state information, receiving, in units of a group including multiple measurement opportunities for measuring the channel state information, the channel state information, and information related to the measurement status of the multiple measurement opportunities or information related to the time of the multiple measurement opportunities; and controlling the data acquisition based on the channel state information, and the information related to the measurement status or the time-related information.

[0252] The entire contents of the specification, drawings and abstract of the specification contained in Japanese Patent Application No. 2024-022164, filed on February 16, 2024, are incorporated herein by reference.

[0253] Industrial applicability

[0254] One embodiment of this disclosure is useful for wireless communication systems.

[0255] Explanation of reference numerals in the attached figures

[0256] 100 base stations

[0257] 101, 205 Control Department

[0258] Signal generation units 102 and 206

[0259] 103, 207 Sending Department

[0260] Receiving Departments 104 and 201

[0261] Extraction sections 105 and 202

[0262] Demodulation Departments 106 and 203

[0263] Decoding sections 107 and 204

[0264] 200 terminals

Claims

1. A terminal, characterized in that, have: The control circuit, during data acquisition for an artificial intelligence model used to report channel state information, determines information related to the measurement status of multiple measurement opportunities for measuring the channel state information or information related to the time of the multiple measurement opportunities. as well as The transmitting circuit transmits the measured channel state information, as well as the measurement status-related information or the time-related information, in units of groups including the plurality of measurement opportunities.

2. The terminal as described in claim 1, wherein, The control circuit determines the time-related information corresponding to the measurement opportunity that successfully performs the measurement of the channel state information among the plurality of measurement opportunities, but does not determine the time-related information corresponding to the measurement opportunity that fails to perform the measurement of the channel state information.

3. The terminal as described in claim 1, wherein, The information related to the measurement status includes information related to whether the channel state information was successfully measured in each of the plurality of measurement opportunities.

4. The terminal as described in claim 1, wherein, The information related to the measurement status includes information related to the measurement status of the channel state information in each of the plurality of measurement opportunities.

5. The terminal as described in claim 4, wherein, The measurement status includes: a status in which the channel state information is successfully measured; a status in which the channel state information measurement fails due to channel quality; and a status in which the channel state information is not measured due to indifference to channel quality.

6. The terminal as described in claim 4, wherein, The measurement status includes: a status in which the channel state information is successfully measured; a status in which the channel state information is not measured due to discontinuous reception, i.e., DRX inactivity; a status in which the channel state information is not measured due to random access operation; and a status in which the channel state information measurement fails due to radio link failure.

7. A base station, characterized in that, have: The receiving circuit, in the data acquisition of the artificial intelligence model for reporting channel state information, receives the channel state information, as well as information related to the measurement status of the multiple measurement opportunities or information related to the time of the multiple measurement opportunities, in units of a group including multiple measurement opportunities for measuring the channel state information. as well as The control circuit controls the data acquisition based on the channel state information and the information related to the measurement status or the information related to time.

8. A communication method, characterized in that, The terminal performs the following steps: In the data acquisition of the artificial intelligence model used for reporting channel state information, information related to the measurement status in multiple measurement opportunities for measuring the channel state information or information related to the time of the multiple measurement opportunities is determined. as well as The measured channel state information, as well as the measurement status-related information or the time-related information, are transmitted in groups that include the multiple measurement opportunities.

9. A communication method, characterized in that, The base station performs the following steps: In the data acquisition of the artificial intelligence model used for reporting channel state information, the channel state information, as well as information related to the measurement status in the multiple measurement opportunities or information related to the time of the multiple measurement opportunities, are received in units of multiple measurement opportunities that include multiple measurement opportunities for measuring the channel state information. as well as The data acquisition is controlled based on the channel state information, as well as the information related to the measurement status or the information related to time.

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