WO2025161853A1 - Model monitoring method, apparatus and system - Google Patents

Abstract

Embodiments of the present application provide a model monitoring method, apparatus and system. The method comprises: receiving a reference signal; and sending first information and second information, the first information comprising true CSI, the true CSI being obtained on the basis of the reference signal, the second information comprising a first CSI report, and the first CSI report being obtained on the basis of the true CSI, wherein the first CSI report is a complete report, or the first CSI report is an omitted report. By means of the method, a network device uses a complete CSI report for model monitoring, so that the influence of CSI omission can be eliminated, and the performance of a model itself is monitored. Alternatively, the first CSI report is an omitted report, and the network device uses the omitted CSI report for model monitoring, so that the robustness of the model to CSI omission can be monitored.

Description

Model monitoring method, device and system

This application claims priority to the Chinese patent application with application number 202410129894.8 filed with the State Intellectual Property Office of China on January 29, 2024, and priority to the Chinese patent application with the invention name “Model Monitoring Method, Device and System”, all contents of which are incorporated by reference into this application.

Technical Field

The present application relates to the field of communication technology, and in particular to a model monitoring method, device, and system.

Background Art

In New Radio (NR) communication systems, base stations need to obtain downlink channel state information (CSI) to determine the resource, modulation and coding scheme (MCS), and precoding configurations for downlink data channels used by user equipment (UE) for scheduling. In Time Division Duplex (TDD) systems, due to the reciprocity of uplink and downlink channels, base stations can obtain uplink CSI by measuring uplink reference signals, thereby inferring more accurate downlink CSI. For example, the uplink CSI can be used as downlink CSI. In the frequency division duplex (FDD) system, uplink and downlink reciprocity cannot be guaranteed. The downlink CSI is obtained by the UE measuring the downlink reference signal, such as the channel state information reference signal (CSI-RS) or the synchronization signal block (SSB). Therefore, the UE needs to generate a CSI report as predefined in the protocol or configured by the base station, and feed the CSI back to the base station so that it can obtain the downlink CSI.

When monitoring an artificial intelligence (AI)-based CSI feedback model, if CSI omission occurs (for example, when uplink resources available for transmitting a CSI report are insufficient to transmit a complete CSI report, the UE omits lower-priority bits from the CSI report), poor CSI feedback performance may be due to two factors: poor CSI feedback model performance or CSI omission. Existing technologies do not clearly define how to monitor the CSI feedback model in this situation or determine the cause of the poor CSI feedback performance.

Summary of the Invention

The present application discloses a model monitoring method, device, and system, which can monitor model performance according to actual needs, such as eliminating the impact of CSI omission and monitoring the performance of the model itself; or, can monitor the robustness of the model to CSI omission.

In a first aspect, embodiments of the present application provide a model monitoring method, performed by a user equipment (UE) or a circuit for a UE. The method includes: the UE receiving a reference signal. Furthermore, the UE sending first information and second information. The first information includes true CSI. The true CSI is obtained based on the reference signal. The second information includes a first CSI report, which is obtained based on the true CSI. The first CSI report is a complete report.

In an embodiment of the present application, a user equipment sends first information and second information to a network device. The first information includes true CSI, and the second information includes a first CSI report. The first CSI report is a complete report. This allows the network device to monitor model performance based on the true CSI and the first CSI report. This approach helps the network device use the complete CSI report for model monitoring, eliminating the impact of omitted CSI and allowing the performance of the model to be monitored.

The true CSI can be understood as the CSI obtained by the user equipment (UE) by measuring the downlink reference signal. This CSI is uncompressed. This CSI can be the channel response matrix measured by the UE, or a precoding matrix processed by the channel response matrix. The true CSI can also be called input CSI, model input, measured CSI, original CSI, or ground-truth CSI, etc., which is not limited in this solution.

The true CSI is obtained based on the reference signal. For example, the true CSI can be obtained by measuring the reference signal, or by performing eigendecomposition or singular value decomposition on the measured CSI.

The first CSI report may be referred to as CSI feedback, CSI latent space, quantized CSI, or compressed CSI (CSI compression). The first CSI report may be used for model monitoring.

The complete report may be understood as a CSI report without omission, and the complete report may include information such as compressed CSI or quantized CSI.

In one possible implementation, the user equipment and the network equipment perform model monitoring using complete CSI reporting based on protocol definition.

In another possible implementation, the user equipment further receives first indication information, where the first indication information indicates that a complete CSI report is used for model monitoring, or the first indication information indicates that the user equipment sends a complete CSI report.

In a possible implementation, the user equipment further sends third information, where the third information includes a second CSI report, where the second CSI report is an omitted report, and where the second CSI report is obtained based on the reference signal.

The omitted report can be understood as a CSI report that discards or omits part of its content. The omitted report may include part of the compressed CSI or quantized CSI, that is, a report obtained by omitting the compressed CSI or quantized CSI information in the complete report. For example, when the uplink resources used to transmit the CSI report are insufficient to transmit the complete CSI report, the user equipment may omit some bits or content of the CSI report with lower priority.

The second CSI report is also used for model monitoring. The second CSI report may be obtained by measuring the reference signal. For example, the second CSI report and the first CSI report are obtained by measuring the reference signal at the same time, that is, the omitted CSI report is obtained by omitting the first CSI report (the complete CSI report); or the second CSI report and the first CSI report are obtained by measuring the reference signal at different times.

In this example, the user equipment sends not only a complete CSI report (first CSI report) but also an omitted CSI report (second CSI report) to the network device. Both the first and second CSI reports are used for model monitoring. Based on the first and second CSI reports, the network device can obtain first and second model monitoring performance. Based on this example, both the performance of the model itself and its robustness to CSI omission can be monitored simultaneously.

In a possible implementation, the user equipment further sends fourth information, where the fourth information includes a third CSI report, where the third CSI report is an omitted report and is used for CSI feedback.

The third CSI report is used for CSI feedback. For example, when performing model inference, an AI model is used for CSI feedback so that the network device can obtain precoding for downlink transmission.

In a possible implementation manner, the first information and the second information are reported through high-layer signaling.

The high-level signaling can be, for example, Medium Access Control (MAC) layer signaling or Radio Resource Control (RRC) signaling.

In a possible implementation, the user equipment further receives fifth information, where the fifth information is used to indicate a first resource, and the first resource is used to transmit a complete CSI report.

During the model monitoring process, or when the network device configures the user equipment to feedback a CSI report for model monitoring, the network device needs to allocate sufficient uplink resources to the user equipment for transmitting the complete CSI report, so that the user equipment can complete the transmission of the complete CSI report based on the resources.

In one possible implementation, the user equipment does not expect CSI omission to occur in the CSI report for model monitoring, or the user equipment does not expect to omit the CSI report for model monitoring, or the user equipment does not expect that resources used to transmit the CSI report for model monitoring are less than resources required for the CSI report for model monitoring.

In this way, the network device needs to configure sufficient resources for the user equipment to transmit a complete CSI report.

In one possible implementation, when the CSI report for model monitoring is omitted, or the resources used to transmit the CSI report for model monitoring are less than the resources required for the CSI report for model monitoring, the user equipment sends sixth information to the network device, where the sixth information includes at least one of the size of the CSI report for model monitoring, the size of the omitted part of the CSI report for model monitoring, the resources required for the CSI report for model monitoring, and the resources required for the omitted part of the CSI report for model monitoring.

In this way, the network device can allocate additional resources for the transmission of the CSI report to transmit the complete CSI report.

In one possible implementation, the priority of the CSI report used for model monitoring is higher than that of other CSI reports, or the priority of the report content is not distinguished within the CSI report used for model monitoring, or the priority of the CSI report used for monitoring is the same as the priority of the report used to feedback the true value CSI, and is higher than that of other CSI reports.

Among them, when the priority of the CSI report used for model monitoring is higher than other CSI reports, when two or more CSI reports of the above user equipment conflict in the time domain, in some cases the user equipment will not send the CSI report with a lower priority.

In a second aspect, embodiments of the present application provide a model monitoring method, performed by a user equipment (UE) or a circuit for a UE. The method includes: the UE receiving a reference signal. Furthermore, the UE sending first information and second information. The first information includes true CSI. The true CSI is obtained based on the reference signal. The second information includes a first CSI report, which is obtained based on the true CSI. The first CSI report is an omitted report.

In this embodiment of the present application, a user equipment sends first information and second information to a network device. The first information includes true CSI, and the second information includes a first CSI report. The first CSI report is an omitted report. This allows the network device to monitor model performance based on the true CSI and the first CSI report. This approach allows the network device to use the omitted CSI report for model monitoring, enabling monitoring of the model's robustness to CSI omissions.

The first CSI report is an omitted report. This omitted report can be understood as a CSI report that discards or omits some of its content. This omitted report may include some compressed CSI or quantized CSI content, i.e., a report obtained by omitting the compressed CSI or quantized CSI information in a complete report. For example, when the uplink resources used to transmit the CSI report are insufficient to transmit the complete CSI report, the user equipment may omit some lower-priority bits or content in the CSI report.

In one possible implementation, the user equipment and the network equipment perform model monitoring based on the protocol definition using omitted CSI reporting.

In another possible implementation, the network device sends second indication information to the user equipment, where the second indication information instructs to use the omitted CSI report for model monitoring; or, the second indication information instructs to send the omitted CSI report.

In one possible implementation, the user equipment reports a CSI report for model monitoring (i.e., the first CSI report described above, or the second CSI report described below) using high-layer signaling. The high-layer signaling may be, for example, medium access control (MAC) layer signaling or radio resource control (RRC) signaling.

In one possible implementation, the priority of the CSI report used for model monitoring is higher than that of other CSI reports, or the priority of the report content is not distinguished within the CSI report used for model monitoring, or the priority of the CSI report used for monitoring is the same as the priority of the report used to feedback the true value CSI, and is higher than that of other CSI reports.

In a possible implementation, the user equipment further sends third information to the network device, where the third information includes a second CSI report, where the second CSI report is a complete report and is obtained based on the reference signal.

In a possible implementation, the user equipment sends fourth information to the network device, where the fourth information includes a third CSI report, where the third CSI report is an omitted report and is used for CSI feedback.

Based on the third CSI report, the network device obtains precoding for downlink transmission.

In a third aspect, embodiments of the present application provide a model monitoring method, performed by a network device or a circuit for a network device. The method includes: the network device sending a reference signal. The network device then receives first information and second information, wherein the first information includes true CSI, which is obtained based on the reference signal; and the second information includes a first CSI report, which is obtained based on the true CSI; wherein the first CSI report is a complete report. The network device also obtains a first model monitoring performance based on the first information and the second information.

In a possible implementation, the network device further sends first indication information, where the first indication information indicates use of a complete CSI report for model monitoring; or, the first indication information indicates the user equipment to send a complete CSI report.

In one possible implementation, the network device further receives third information, the third information including a second CSI report, the second CSI report being an omitted report and obtained based on the reference signal, and further obtains a second model monitoring performance based on the third information and the true CSI.

In a possible implementation, the network device further receives fourth information, where the fourth information includes a third CSI report, where the third CSI report is an omitted report, and where the third CSI report is used for CSI feedback.

In a possible implementation manner, the first information and the second information are reported through high-layer signaling.

In a possible implementation, the network device further sends fifth information, where the fifth information is used to indicate a first resource, where the first resource is used to transmit a complete CSI report.

In one possible implementation, the user equipment does not expect CSI omission to occur in the CSI report for model monitoring, or the user equipment does not expect to omit the CSI report for model monitoring, or the user equipment does not expect that resources used to transmit the CSI report for model monitoring are less than resources required for the CSI report for model monitoring.

In one possible implementation, when the CSI report for model monitoring is omitted, or the resources used to transmit the CSI report for model monitoring are less than the resources required for the CSI report for model monitoring, the user equipment sends sixth information to the network device, where the sixth information includes at least one of the size of the CSI report for model monitoring, the size of the omitted part of the CSI report for model monitoring, the resources required for the CSI report for model monitoring, and the resources required for the omitted part of the CSI report for model monitoring.

In this way, the network device can allocate additional resources for the transmission of the CSI report to transmit the complete CSI report.

In one possible implementation, the priority of the CSI report used for model monitoring is higher than that of other CSI reports, or the priority of the report content is not distinguished within the CSI report used for model monitoring, or the priority of the CSI report used for monitoring is the same as the priority of the report used to feedback the true value CSI, and is higher than that of other CSI reports.

In a fourth aspect, embodiments of the present application provide a model monitoring method, performed by a network device or a circuit for a network device. The method includes: the network device sending a reference signal. The network device then receives first information and second information, wherein the first information includes true CSI, which is obtained based on the reference signal; and the second information includes a first CSI report, which is obtained based on the true CSI; wherein the first CSI report is an omitted report. The network device also obtains a first model monitoring performance based on the first information and the second information.

In a possible implementation, the network device further sends second indication information, where the second indication information instructs the user equipment to use the omitted CSI report for model monitoring; or the second indication information instructs the user equipment to send the omitted CSI report.

In one possible implementation, the network device further receives third information, the third information including a second CSI report, the second CSI report being a complete report and obtained based on the reference signal, and further obtains a second model monitoring performance based on the third information and the true CSI.

In a possible implementation, the network device further receives fourth information, where the fourth information includes a third CSI report, where the third CSI report is an omitted report, and where the third CSI report is used for CSI feedback.

In a possible implementation manner, the first information and the second information are reported through high-layer signaling.

In one possible implementation, the priority of the CSI report used for model monitoring is higher than that of other CSI reports, or the priority of the report content is not distinguished within the CSI report used for model monitoring, or the priority of the CSI report used for monitoring is the same as the priority of the report used to feedback the true value CSI, and is higher than that of other CSI reports.

In a fifth aspect, an embodiment of the present application provides a model monitoring method, performed by a user device or a circuit for a user device. The method includes: the user device receives a reference signal. The user device also sends first information, the first information including a first CSI report, the first CSI report being obtained based on the reference signal; the first CSI report being a complete report. The user device also receives second information indicating first recovered CSI, the first recovered CSI being obtained based on the first CSI report. The user device also obtains a first model monitoring performance based on true CSI and the first recovered CSI, the true CSI being obtained based on the reference signal.

In an embodiment of the present application, a user device sends first information to a network device, where the first information includes a first CSI report. The first CSI report is a complete report. The network device recovers CSI based on the first CSI report and sends the recovered CSI to the user device. The user device then monitors model performance based on the true CSI and the recovered CSI. This approach allows the user device to monitor the model using the complete CSI report, eliminating the impact of omitted CSI and enabling the monitoring of the model's performance.

In a possible implementation, the user equipment further receives first indication information, where the first indication information indicates use of a complete CSI report for model monitoring; or, the first indication information indicates that the user equipment sends a complete CSI report.

In one possible implementation, the user equipment further transmits third information, where the third information includes a second CSI report, where the second CSI report is an omitted report and is obtained based on the reference signal. The user equipment further receives fourth information indicating second restored CSI, where the second restored CSI is obtained based on the second CSI report. The user equipment further obtains a second model monitoring performance based on the true CSI and the second restored CSI.

In a possible implementation manner, the first information is reported through high-layer signaling.

In a possible implementation, the user equipment further receives sixth information, where the sixth information is used to indicate a first resource, and the first resource is used to transmit a complete CSI report.

In one possible implementation, the user equipment does not expect CSI omission to occur in the CSI report for model monitoring, or the user equipment does not expect to omit the CSI report for model monitoring, or the user equipment does not expect that resources used to transmit the CSI report for model monitoring are less than resources required for the CSI report for model monitoring.

In one possible implementation, when the CSI report for model monitoring is omitted, or the resources used to transmit the CSI report for model monitoring are less than the resources required for the CSI report for model monitoring, the user equipment sends sixth information to the network device, where the sixth information includes at least one of the size of the CSI report for model monitoring, the size of the omitted part of the CSI report for model monitoring, the resources required for the CSI report for model monitoring, and the resources required for the omitted part of the CSI report for model monitoring.

In this way, the network device can allocate additional resources for the transmission of the CSI report to transmit the complete CSI report.

In one possible implementation, the priority of the CSI report used for model monitoring is higher than that of other CSI reports, or the priority of the report content is not distinguished within the CSI report used for model monitoring, or the priority of the CSI report used for monitoring is the same as the priority of the report used to feedback the true value CSI, and is higher than that of other CSI reports.

In a sixth aspect, an embodiment of the present application provides a model monitoring method, performed by a user device or a circuit for a user device. The method includes: the user device receives a reference signal. The user device also transmits first information, the first information including a first CSI report, the first CSI report being obtained based on the reference signal; the first CSI report being an omitted report. The user device also receives second information indicating first recovered CSI, the first recovered CSI being obtained based on the first CSI report. The user device also obtains a first model monitoring performance based on true CSI and the first recovered CSI, the true CSI being obtained based on the reference signal.

In an embodiment of the present application, a user device transmits first information to a network device, the first information including a first CSI report. The first CSI report is an omitted report. The network device obtains recovered CSI based on the first CSI report and transmits the recovered CSI to the user device. The user device can monitor model performance based on the true CSI and the recovered CSI. This approach allows the user device to monitor the model using the omitted CSI report, thereby monitoring the model's robustness to CSI omissions.

In a possible implementation, the user equipment further receives second indication information, where the second indication information instructs the user equipment to use the omitted CSI report for model monitoring; or the second indication information instructs the user equipment to send the omitted CSI report.

In one possible implementation, the user equipment further transmits third information, where the third information includes a second CSI report, where the second CSI report is a complete report and is obtained based on the reference signal. The user equipment further receives fourth information indicating second recovered CSI, where the second recovered CSI is obtained based on the second CSI report. The user equipment further obtains a second model monitoring performance based on the true CSI and the second recovered CSI.

In a possible implementation, the user equipment further sends fifth information, where the fifth information includes a third CSI report, where the third CSI report is an omitted report and is used for CSI feedback.

In a possible implementation manner, the first information is reported through high-layer signaling.

In one possible implementation, the priority of the CSI report used for model monitoring is higher than that of other CSI reports, or the priority of the report content is not distinguished within the CSI report used for model monitoring, or the priority of the CSI report used for monitoring is the same as the priority of the report used to feedback the true value CSI, and is higher than that of other CSI reports.

In a seventh aspect, embodiments of the present application provide a model monitoring method, performed by a network device or a circuit for a network device. The method includes: the network device transmitting a reference signal. The network device also receives first information, the first information including a first CSI report, the first CSI report being obtained based on the reference signal; the first CSI report being a complete report. The network device also transmits second information indicating first recovered CSI, the first recovered CSI being obtained based on the first CSI report.

In a possible implementation, the network device further sends first indication information, where the first indication information indicates use of a complete CSI report for model monitoring; or, the first indication information indicates the user equipment to send a complete CSI report.

In one possible implementation, the network device further receives third information, where the third information includes a second CSI report, where the second CSI report is an omitted report and is obtained based on the reference signal. The network device further sends fourth information, where the fourth information is used to indicate second recovered CSI, where the second recovered CSI is obtained based on the second CSI report.

In a possible implementation manner, the first information is reported through high-layer signaling.

In a possible implementation, the network device further sends sixth information, where the sixth information is used to indicate a first resource, where the first resource is used to transmit a complete CSI report.

In one possible implementation, the user equipment does not expect CSI omission to occur in the CSI report for model monitoring, or the user equipment does not expect to omit the CSI report for model monitoring, or the user equipment does not expect that resources used to transmit the CSI report for model monitoring are less than resources required for the CSI report for model monitoring.

In one possible implementation, when the CSI report for model monitoring is omitted, or the resources used to transmit the CSI report for model monitoring are less than the resources required for the CSI report for model monitoring, the user equipment sends sixth information to the network device, where the sixth information includes at least one of the size of the CSI report for model monitoring, the size of the omitted part of the CSI report for model monitoring, the resources required for the CSI report for model monitoring, and the resources required for the omitted part of the CSI report for model monitoring.

In this way, the network device can allocate additional resources for the transmission of the CSI report to transmit the complete CSI report.

In one possible implementation, the priority of the CSI report used for model monitoring is higher than that of other CSI reports, or the priority of the report content is not distinguished within the CSI report used for model monitoring, or the priority of the CSI report used for monitoring is the same as the priority of the report used to feedback the true value CSI, and is higher than that of other CSI reports.

In an eighth aspect, embodiments of the present application provide a model monitoring method, performed by a network device or a circuit for a network device. The method includes: the network device transmitting a reference signal. The network device also receives first information, the first information including a first CSI report, the first CSI report being obtained based on the reference signal; the first CSI report being an omitted report. The network device also transmits second information indicating first recovered CSI, the first recovered CSI being obtained based on the first CSI report.

In a possible implementation, the network device further sends second indication information, where the second indication information instructs the user equipment to use the omitted CSI report for model monitoring; or the second indication information instructs the user equipment to send the omitted CSI report.

In one possible implementation, the network device further receives third information, where the third information includes a second CSI report, where the second CSI report is a complete report and is obtained based on the reference signal. The network device further sends fourth information, where the fourth information is used to indicate second recovered CSI, where the second recovered CSI is obtained based on the second CSI report.

In a possible implementation, the network device further receives fifth information, where the fifth information includes a third CSI report, where the third CSI report is an omitted report and is used for CSI feedback.

In a possible implementation manner, the first information is reported through high-layer signaling.

In a possible implementation, the priority of the first CSI report is higher than that of the third CSI report, or the priority of report contents in the first CSI report is not distinguished.

In a ninth aspect, an embodiment of the present application provides a model monitoring method, performed by a user equipment or a circuit for a user equipment. The method includes: the user equipment receiving a reference signal. The user equipment further obtains true CSI based on the reference signal. The user equipment further obtains first recovered CSI based on a first CSI report; the first CSI report is obtained based on the true CSI, and the first CSI report is a complete CSI report. The user equipment further obtains a first model monitoring performance based on the true CSI and the first recovered CSI.

In this embodiment of the present application, a user equipment (UE) obtains true CSI based on a reference signal and obtains a first CSI report based on the true CSI. This first CSI report is a complete report. The UE also obtains recovered CSI based on the first CSI report. Thus, the UE can monitor model performance based on the true CSI and the recovered CSI. This approach allows the UE to monitor model performance using the complete CSI report, eliminating the impact of omitted CSI and enabling the monitoring of model performance.

In a possible implementation, the user equipment further receives first indication information, where the first indication information indicates use of a complete CSI report for model monitoring; or, the first indication information indicates that the user equipment sends a complete CSI report.

In one possible implementation, the user equipment also obtains a second model monitoring performance based on the true CSI and the second recovered CSI, where the second recovered CSI is obtained based on a second CSI report, which is an omitted report and is obtained based on the reference signal.

In a possible implementation, the user equipment further sends first information, where the first information includes a third CSI report, where the third CSI report is an omitted report and is used for CSI feedback.

In a possible implementation, the user equipment further receives sixth information, where the sixth information is used to indicate a first resource, and the first resource is used to transmit a complete CSI report.

In a tenth aspect, an embodiment of the present application provides a model monitoring method, performed by a user equipment or a circuit for a user equipment. The method includes: the user equipment receiving a reference signal. The user equipment further obtains true CSI based on the reference signal. The user equipment further obtains first recovered CSI based on a first CSI report; the first CSI report is obtained based on the true CSI, and the first CSI report is an omitted report. The user equipment further obtains a first model monitoring performance based on the true CSI and the first recovered CSI.

In this embodiment of the present application, a user equipment (UE) obtains true CSI based on a reference signal and obtains a first CSI report based on the true CSI. This first CSI report is an omitted report. The UE also obtains recovered CSI based on the first CSI report. Thus, the UE can monitor model performance based on the true CSI and the recovered CSI. This approach allows the UE to monitor the model using the omitted CSI report, thereby monitoring the robustness of the model to CSI omission.

In a possible implementation, the user equipment further receives second indication information, where the second indication information instructs the user equipment to use the omitted CSI report for model monitoring; or the second indication information instructs the user equipment to send the omitted CSI report.

In one possible implementation, the user equipment also obtains a second model monitoring performance based on the true CSI and the second recovered CSI, where the second recovered CSI is obtained based on a second CSI report, the second CSI report is a complete report, and the second CSI report is obtained based on the reference signal.

In a possible implementation, the user equipment further sends first information, where the first information includes a third CSI report, where the third CSI report is an omitted report and is used for CSI feedback.

In an eleventh aspect, embodiments of the present application provide a model monitoring method, performed by a network device or a circuit for a network device. The method includes: the network device transmitting a reference signal. The network device also receives a first model monitoring performance, where the first model monitoring performance is obtained based on true CSI and first recovered CSI, where the first recovered CSI is obtained based on a first CSI report, where the first CSI report is obtained based on the true CSI, and where the true CSI is obtained based on the reference signal; wherein the first CSI report is a complete CSI report.

In a possible implementation, the network device further sends first indication information, where the first indication information instructs the user equipment to use a complete CSI report for model monitoring; or, the first indication information instructs the user equipment to send a complete CSI report.

In a possible implementation, the network device further receives first information, where the first information includes a third CSI report, where the third CSI report is an omitted report, and where the third CSI report is used for CSI feedback.

In a twelfth aspect, an embodiment of the present application provides a model monitoring method, performed by a network device or a circuit for a network device. The method includes: the network device sending a reference signal. The network device also receives a first model monitoring performance, where the first model monitoring performance is obtained based on true CSI and first recovered CSI, where the first recovered CSI is obtained based on a first CSI report, where the first CSI report is obtained based on the true CSI, and where the true CSI is obtained based on the reference signal; wherein the first CSI report is an omitted report.

In a possible implementation, the network device further sends second indication information, where the second indication information instructs the user equipment to use the omitted CSI report for model monitoring; or the second indication information instructs the user equipment to send the omitted CSI report.

In a possible implementation, the network device further receives first information, where the first information includes a third CSI report, where the third CSI report is an omitted report, and where the third CSI report is used for CSI feedback.

In a thirteenth aspect, an embodiment of the present application provides a model monitoring method, performed by a user device or a circuit for a user device. The method includes: the user device receiving a reference signal. The user device obtaining predicted CSI based on the reference signal. The user device obtaining true CSI corresponding to the predicted CSI based on the reference signal. The user device further obtains model monitoring performance based on a first CSI report and the true CSI corresponding to the predicted CSI. The first CSI report is an omitted report and is obtained based on the predicted CSI.

In an embodiment of the present application, a user equipment obtains predicted CSI and true CSI based on the reference signal, and then the user equipment obtains a model-monitored performance based on a first CSI report and the true CSI corresponding to the predicted CSI. The first CSI report is an omitted report, obtained based on the predicted CSI. In this way, the user equipment can monitor the actual performance corresponding to the omitted CSI report it reports, rather than directly using the predicted CSI for model monitoring. This allows the monitored performance to take into account the impact of the omitted CSI.

The predicted CSI is the CSI at a future time predicted based on current and/or past CSI. In one possible implementation, the user equipment measures the downlink reference signal to obtain true CSI1, and then performs CSI prediction based on the true CSI1 to obtain the predicted CSI. Alternatively, the user equipment measures the downlink reference signal at times t1 and t2, respectively, to obtain true CSI1 and true CSI2. The user equipment obtains the predicted CSI based on the true CSI1 and true CSI2. Of course, the user equipment can also perform prediction based on at least three true CSI values.

The first CSI report is used to indicate the CSI feedback corresponding to the predicted CSI, and the CSI feedback is the CSI represented by the CSI report corresponding to the predicted CSI after being omitted. For example, the CSI feedback CSI3" is a precoding matrix, and the first CSI report includes CSI3" or a compressed representation of CSI3". For another example, CSI3" is a channel response, and the first CSI report includes the precoding matrix corresponding to CSI3" or a compressed representation of the precoding matrix, etc.

In a possible implementation, the user equipment sends the first CSI report to the network equipment, so that the network equipment determines downlink precoding according to the predicted CSI.

In the fourteenth aspect, the present application provides a model monitoring device, comprising a processor and a memory; wherein the memory is used to store program code, and the processor is used to call the program code to execute the method provided in any aspect from the first aspect to the thirteenth aspect and any possible implementation method thereof.

In the fifteenth aspect, the present application provides a model monitoring device, including a transceiver module and a processing module, which are respectively used to execute the method provided corresponding to any aspect of the first to thirteenth aspects and any possible implementation methods thereof.

In the sixteenth aspect, the present application provides a model monitoring system, which includes a model monitoring device for the method described in the first aspect/second aspect, and a model monitoring device for the method described in the third aspect/fourth aspect; or, the system includes a model monitoring device for the method described in the fifth aspect/sixth aspect, and a model monitoring device for the method described in the seventh aspect/eighth aspect; or, the system includes a model monitoring device for the method described in the ninth aspect/tenth aspect, and a model monitoring device for the method described in the eleventh aspect/twelfth aspect.

In the seventeenth aspect, the present application provides a computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program, and the computer program is executed by a processor to implement the method provided in any aspect from the first aspect to the thirteenth aspect and any possible implementation method thereof.

In the eighteenth aspect, the present application provides a computer program product, characterized in that when the computer program product is run on a computer, the computer is enabled to execute the method provided in any aspect from the first aspect to the thirteenth aspect and any possible implementation manner thereof.

In the nineteenth aspect, the present application also provides a chip or chip system for implementing the method provided in any aspect from the first aspect to the thirteenth aspect and any possible implementation manner thereof.

It is understandable that the above-mentioned methods, devices, computer-readable storage media, computer program products, or chips or chip systems are all used to perform the above-mentioned methods. Therefore, the beneficial effects that can be achieved can refer to the beneficial effects of the corresponding methods and will not be repeated here.

BRIEF DESCRIPTION OF THE DRAWINGS

The following is an introduction to the drawings used in the embodiments of this application.

FIG1 is a simplified schematic diagram of a wireless communication system provided by an embodiment of the present application;

FIG2a is a schematic diagram of a communication system provided by an embodiment of the present application;

FIG2b is a schematic diagram of another communication system provided in an embodiment of the present application;

FIG3a is a schematic diagram of a possible application framework in a communication system provided in an embodiment of the present application;

FIG3 b is a schematic diagram of another possible application framework in the communication system provided in an embodiment of the present application;

FIG4 is a schematic diagram of an encoder and a decoder provided in an embodiment of the present application;

FIG5 is a schematic diagram of an AI application framework provided in an embodiment of the present application;

FIG6 is a flow chart of a model monitoring method provided in an embodiment of the present application;

FIG7 is a flow chart of another model monitoring method provided in an embodiment of the present application;

FIG8 is a flow chart of another model monitoring method provided in an embodiment of the present application;

FIG9 is a flow chart of a model monitoring method provided in an embodiment of the present application;

FIG10 is a flow chart of another model monitoring method provided in an embodiment of the present application;

FIG11 is a flow chart of another model monitoring method provided in an embodiment of the present application;

FIG12 is another communication schematic diagram provided in an embodiment of the present application;

FIG13 is a schematic structural diagram of a model monitoring device provided in an embodiment of the present application;

FIG14 is a schematic structural diagram of another model monitoring device provided in an embodiment of the present application;

FIG15 is a schematic structural diagram of another model monitoring device provided in an embodiment of the present application.

DETAILED DESCRIPTION

In order to make the objectives, technical solutions and advantages of the present disclosure more clear, the present disclosure will be further described in detail below with reference to the accompanying drawings.

The present disclosure relates to at least one (item) as follows, indicating one (item) or more (items). More than one (item) refers to two (items) or more than two (items). "And/or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and/or B can represent: A exists alone, A and B exist at the same time, and B exists alone. The character "/" generally indicates that the previous and next associated objects are in an "or" relationship. In addition, it should be understood that although the terms first, second, etc. may be used to describe each object in the present disclosure, these objects should not be limited to these terms. These terms are only used to distinguish each object from each other.

The terms "including" and "having" and any variations thereof mentioned in the following description of the present disclosure are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally includes other steps or units that are not listed, or optionally includes other steps or units that are inherent to these processes, methods, products or devices. It should be noted that in the present disclosure, words such as "exemplary" or "for example" are used to indicate examples, illustrations or explanations. Any method or design described in the present disclosure as "exemplary" or "for example" should not be interpreted as being more preferred or more advantageous than other methods or designs. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a concrete way.

It should be noted that in this application, "send" can be understood as "output" and "receive" can be understood as "input". "Send information to A", where "to A" only indicates the direction of information transmission, A is the destination, and does not limit "sending information to A" to direct transmission on the air interface. "Sending information to A" includes sending information directly to A, and also includes sending information indirectly to A through a transmitter, so "sending information to A" can also be understood as "outputting information to A". Similarly, "receiving information from A" indicates that the source of the information is A, including receiving information directly from A, and also including receiving information indirectly from A through a receiver, so "receiving information from A" can also be understood as "inputting information from A".

It is understood that, in this application, "indication" can include direct indication, indirect indication, explicit indication, and implicit indication. When describing a certain indication information as indicating A, it can be understood that the indication information carries A, directly indicates A, or indirectly indicates A. In this application, the information indicated by the indication information is referred to as the information to be indicated. In the specific implementation process, there are many ways to indicate the information to be indicated. For example, but not limited to, the information to be indicated can be directly indicated, such as the information to be indicated itself or an index of the information to be indicated, or it can be indirectly indicated by indicating other information, where there is an association between the other information and the information to be indicated. It is also possible to indicate only a part of the information to be indicated, while the rest of the information to be indicated is known or agreed in advance. For example, it is also possible to indicate specific information by using a pre-agreed (e.g., protocol-specified) order of arrangement of various information, thereby reducing the indication overhead to a certain extent. The information to be indicated can be sent as a whole or divided into multiple sub-information and sent separately, and the sending period and/or sending time of these sub-information can be the same or different. The specific sending method is not limited in this application. The sending period and/or sending timing of these sub-information may be predefined, for example, predefined according to a protocol, or may be configured by the transmitting end device by sending configuration information to the receiving end device.

The technology provided by the present disclosure can be applied to various communication systems, for example, the communication system can be a fifth-generation (5G) or new radio (NR) system, a long-term evolution (LTE) system, an LTE frequency division duplex (FDD) system, an LTE time division duplex (TDD) system, a wireless local area network (WLAN) system, a satellite communication system, a future communication system such as a sixth-generation (6G) mobile communication system, or a fusion system of multiple systems. The technical solutions provided by the present application can also be applied to device-to-device (D2D) communication, vehicle-to-everything (V2X) communication, machine-to-machine (M2M) communication, machine type communication (MTC), and Internet of Things (IoT) communication systems or other communication systems.

A device in a communication system can send a signal to another device or receive a signal from another device. The signal may include information, signaling, or data, etc. The device can also be replaced by an entity, a network entity, a network element, a communication device, a communication module, a node, a communication node, etc. The present disclosure uses the device as an example for description. For example, the communication system may include at least one terminal device and at least one access network device. The access network device can send a downlink signal to the terminal device, and/or the terminal device can send an uplink signal to the access network device. In addition, it can be understood that if the communication system includes multiple terminal devices, the multiple terminal devices can also send signals to each other, that is, the signal sending device and the signal receiving device can both be terminal devices.

The model monitoring method provided in the embodiment of the present application can be applied to wireless communication systems such as 5G, 6G, and satellite communications. Referring to Figure 1, Figure 1 is a simplified schematic diagram of the wireless communication system provided in the embodiment of the present application. As shown in Figure 1, the wireless communication system includes a wireless access network 100. The wireless access network 100 can be a next-generation (e.g., 6G or higher) wireless access network, or a traditional (e.g., 5G, 4G, 3G, or 2G) wireless access network. One or more communication devices (120a-120j, collectively referred to as 120) can be connected to each other or to one or more network devices (110a, 110b, collectively referred to as 110) in the wireless access network 100. Optionally, Figure 1 is only a schematic diagram, and the wireless communication system may also include other devices, such as core network devices, wireless relay devices, and/or wireless backhaul devices, which are not shown in Figure 1.

Optionally, in actual applications, the wireless communication system may include multiple network devices (also called access network devices) or multiple communication devices at the same time. A network device may serve one or more communication devices at the same time. A communication device may also access one or more network devices at the same time. The embodiments of the present application do not limit the number of communication devices and network devices included in the wireless communication system.

Among them, the network device can be an entity on the network side for transmitting or receiving signals. The network device can be an access device for the communication device to access the wireless communication system in a wireless manner, such as the network device can be a base station. The base station can broadly cover the various names below, or be replaced with the following names, such as: Node B (NodeB), evolved NodeB (eNB), next generation NodeB (gNB), access network equipment in open radio access network (O-RAN), relay station, access point, transmission point (TRP), transmitting point (TP), master station (MeNB), secondary eNodeB (SeNB), multi-standard radio (Multi-standard radio) The term "network device" may also refer to a base station (BS), a home base station (FBS), a network controller, an access node, a wireless node, an access point (AP), a transmission node, a transceiver node, a baseband unit (BBU), a remote radio unit (RRU), an active antenna unit (AAU), a remote radio head (RRH), a central unit (CU), a distributed unit (DU), a radio unit (RU), a centralized unit control plane (CU-CP) node, a centralized unit user plane (CU-UP) node, a positioning node, and the like. A base station may be a macro base station, a micro base station, a relay node, a donor node, or the like, or a combination thereof. A network device may also refer to a communication module, a modem, or a chip used to be provided in the aforementioned device or apparatus. The network device may also be a mobile switching center and a device that performs base station functions in device-to-device (D2D), vehicle-to-everything (V2X), and machine-to-machine (M2M) communications, a network-side device in a 6G network, or a device that performs base station functions in future communication systems. The network device may support networks with the same or different access technologies. The embodiments of this application do not limit the specific technology and specific device form adopted by the network device.

Network devices can be fixed or mobile. For example, base stations 110a and 110b are stationary and are responsible for wireless transmission and reception in one or more cells from communication device 120. The helicopter or drone 120i shown in Figure 1 can be configured to act as a mobile base station, and one or more cells can move according to the location of the mobile base station 120i. In other examples, the helicopter or drone (120i) can be configured to act as a communication device communicating with base station 110b.

In the present disclosure, the communication device used to implement the above-mentioned access network functions can be an access network device, a network device that has some of the access network functions, or a device that can support the implementation of the access network functions, such as a chip system, a hardware circuit, a software module, or a hardware circuit and a software module. The device can be installed in the access network device or used in conjunction with the access network device. The method of the present disclosure is described using the example of the communication device used to implement the access network device functions being an access network device.

A communication device may be an entity on the user side for receiving or transmitting signals, such as a mobile phone. A communication device may be used to connect people, objects, and machines. A communication device may communicate with one or more core networks through a network device. Communication devices include handheld devices with wireless connection capabilities, other processing devices connected to a wireless modem, or vehicle-mounted devices. A communication device may be a portable, pocket-sized, handheld, computer-built-in, or vehicle-mounted mobile device. The communication device 120 may be widely used in various scenarios, such as cellular communication, device-to-device D2D, vehicle-to-everything V2X, peer-to-peer (P2P), machine-to-machine (M2M), machine-type communication (MTC), Internet of Things (IoT), virtual reality (VR), augmented reality (AR), industrial control, autonomous driving, telemedicine, smart grid, smart furniture, smart office, smart wearables, smart transportation, smart city, drones, robots, remote sensing, passive sensing, positioning, navigation and tracking, autonomous delivery and mobility, etc. Some examples of communication devices 120 include: 3GPP standard user equipment (UE), fixed devices, mobile devices, handheld devices, wearable devices, cellular phones, smart phones, Session Initialization Protocol (SIP) phones, laptops, personal computers, smart books, vehicles, satellites, Global Positioning System (GPS) devices, target tracking devices, drones, helicopters, aircraft, ships, remote control devices, smart home devices, industrial devices, personal communication service (PCS) phones, wireless local loop (WLL) stations, personal digital assistants (PDAs), and so on. The communication device 120 may be a wireless device in the above scenarios or a device used to be set in a wireless device, such as a communication module, modem, or chip in the above devices. The communication device may also be called a terminal, terminal device, user equipment (UE), mobile station (MS), mobile terminal (MT), etc. The communication device may also be called a terminal, terminal device, user equipment (UE), mobile station (MS), mobile terminal (MT), etc. The communication device may also be called a communication device in a future wireless communication system. The communication device can be used in a dedicated network device or a general-purpose device. The embodiments of the present application do not limit the specific technology and specific device form used by the communication device.

Alternatively, a communication device can function as a base station. For example, a UE can function as a dispatching entity, providing sidelink signals between UEs in V2X, D2D, or P2P scenarios. As shown in Figure 1 , a cell phone 120a and a car 120b communicate with each other using sidelink signals. Cell phone 120a and smart home device 120e communicate without relaying the communication signals through base station 110b.

In the present disclosure, a communication device for realizing the functions of a communication device may be a terminal device, or a terminal device having some of the functions of the above communication devices, or a device capable of supporting the functions of the above communication devices, such as a chip system, which may be installed in the terminal device or used in combination with the terminal device. In the present disclosure, a chip system may be composed of a chip, or may include a chip and other discrete devices. In the technical solution provided in the present disclosure, the communication device is described as a terminal device or UE as an example.

Optionally, a wireless communication system is typically composed of cells, with base stations managing the cells and providing communication services to multiple mobile stations (MSs) within the cells. A base station includes a baseband unit (BBU) and a remote radio unit (RRU). The BBU and RRU can be placed in different locations, for example, with the RRU being remotely located in a high-traffic area and the BBU being located in a central equipment room. Alternatively, the BBU and RRU can be placed in the same equipment room. Alternatively, the BBU and RRU can be separate components within the same rack. Optionally, a cell can correspond to a carrier or component carrier.

It can be understood that the present disclosure can be applied between a network device and a communication device, between a network device and a network device, or between a communication device and a communication device, that is, between a primary device and a secondary device. The primary device can be a network device or a communication device. When the primary device is a network device, the secondary device can be another network device or a communication device. When the primary device is a communication device, the secondary device can be another communication device.

The following describes the solution using the example of a primary device being a network device, such as an access network device, and a secondary device being a communication device, such as a terminal device. The downlink direction corresponds to the primary device sending data to the secondary device, and the uplink direction corresponds to the secondary device sending data to the primary device.

Protocol layer structure between access network equipment and terminal equipment

Communication between access network equipment and terminal equipment follows a specific protocol layer structure. This protocol layer structure may include a control plane protocol layer structure and a user plane protocol layer structure. For example, the control plane protocol layer structure may include the functions of protocol layers such as the radio resource control (RRC) layer, the packet data convergence protocol (PDCP) layer, the radio link control (RLC) layer, the medium access control (MAC) layer, and the physical layer. For example, the user plane protocol layer structure may include the functions of protocol layers such as the PDCP layer, the RLC layer, the MAC layer, and the physical layer. In one possible implementation, the service data adaptation protocol (SDAP) layer may also be included above the PDCP layer.

Optionally, the protocol layer structure between the access network device and the terminal may also include an artificial intelligence (AI) layer for transmitting data related to AI functions.

Taking data transmission between access network equipment and terminal devices as an example, data transmission needs to pass through the user plane protocol layer, such as the SDAP layer, PDCP layer, RLC layer, MAC layer, and physical layer. Among them, the SDAP layer, PDCP layer, RLC layer, MAC layer, and physical layer can also be collectively referred to as the access layer. According to the direction of data transmission, it is divided into sending or receiving, and each of the above layers is further divided into sending and receiving parts. Taking downlink data transmission as an example, after the PDCP layer obtains data from the upper layer, it transmits the data to the RLC layer and MAC layer. The MAC layer then generates a transport block, which is then wirelessly transmitted through the physical layer. Data is encapsulated accordingly in each layer. For example, data received by a layer from the layer above it is considered a service data unit (SDU) of that layer. After being encapsulated by that layer, it becomes a protocol data unit (PDU) and is then passed to the next layer.

For example, a terminal device may also have an application layer and a non-access layer. The application layer can be used to provide services to applications installed in the terminal device. For example, downlink data received by the terminal device can be sequentially transmitted from the physical layer to the application layer, and then provided by the application layer to the application. For another example, the application layer can obtain data generated by the application and sequentially transmit the data to the physical layer for transmission to other communication devices. The non-access layer can be used to forward user data, such as forwarding uplink data received from the application layer to the SDAP layer, or forwarding downlink data received from the SDAP layer to the application layer.

Structure of access network equipment

Access network equipment may include a centralized unit (CU) and a distributed unit (DU). Multiple DUs may be centrally controlled by one CU. As an example, the interface between the CU and the DU may be referred to as the F1 interface. The control plane (CP) interface may be F1-C, and the user plane (UP) interface may be F1-U. The CU and the DU may be divided according to the protocol layers of the wireless network: for example, the functions of the PDCP layer and above are set in the CU, and the functions of the protocol layers below the PDCP layer (such as the RLC layer and the MAC layer) are set in the DU; for another example, the functions of the protocol layers above the PDCP layer are set in the CU, and the functions of the protocol layers below the PDCP layer are set in the DU.

It is understandable that the above division of the processing functions of CU and DU according to the protocol layer is only an example, and can also be divided in other ways, for example, the CU or DU can be divided into functions with more protocol layers, and for example, the CU or DU can also be divided into partial processing functions with the protocol layer. In one design, some functions of the RLC layer and the functions of the protocol layers above the RLC layer are set in the CU, and the remaining functions of the RLC layer and the functions of the protocol layers below the RLC layer are set in the DU. In another design, the functions of the CU or DU can also be divided according to the service type or other system requirements, for example, by delay, the functions whose processing time needs to meet the delay requirements are set in the DU, and the functions that do not need to meet the delay requirements are set in the CU. In another design, the CU can also have one or more functions of the core network. For example, the CU can be set on the network side to facilitate centralized management. In another design, the RU of the DU is set remotely. Among them, the RU has a radio frequency function.

Optionally, the DU and RU can be divided at the physical layer (PHY). For example, the DU can implement high-level functions in the PHY layer, and the RU can implement low-level functions in the PHY layer. Specifically, when used for transmission, the functions of the PHY layer may include adding cyclic redundancy check (CRC) codes, channel coding, rate matching, scrambling, modulation, layer mapping, precoding, resource mapping, physical antenna mapping, and/or RF transmission functions. Specifically, when used for reception, the functions of the PHY layer may include CRC, channel decoding, rate matching, descrambling, demodulation, layer demapping, channel detection, resource demapping, physical antenna demapping, and/or RF reception functions. Specifically, the high-level functions in the PHY layer may include a portion of the functions of the PHY layer, such as a portion of the functions that is closer to the MAC layer, and the low-level functions in the PHY layer may include another portion of the functions of the PHY layer, such as a portion of the functions that is closer to the RF functions. For example, the high-level functions in the PHY layer may include adding CRC codes, channel coding, rate matching, scrambling, modulation, and layer mapping, and the low-level functions in the PHY layer may include precoding, resource mapping, physical antenna mapping, and RF transmission functions; or, the high-level functions in the PHY layer may include adding CRC codes, channel coding, rate matching, scrambling, modulation, layer mapping, and precoding, and the low-level functions in the PHY layer may include resource mapping, physical antenna mapping, and RF transmission functions.

For example, the functions of the CU can be implemented by one entity, or by different entities. For example, the functions of the CU can be further divided, that is, the control plane and the user plane are separated and implemented by different entities, namely the control plane CU entity (i.e., CU-CP entity) and the user plane CU entity (i.e., CU-UP entity). The CU-CP entity and the CU-UP entity can be coupled with the DU to jointly complete the functions of the access network device.

In the above architecture, signaling generated by the CU can be sent to the terminal device via the DU, and vice versa. For example, RRC or PDCP layer signaling is ultimately processed into physical layer signaling and sent to the terminal device, or converted from received physical layer signaling. In this architecture, the RRC or PDCP layer signaling can be considered to be sent via the DU, or via the DU and RU.

Optionally, any of the above-mentioned DU, CU, CU-CP, CU-UP, and RU can be a software module, a hardware structure, or a software module + hardware structure, without limitation. The existence forms of different entities can be different and are not limited. For example, DU, CU, CU-CP, and CU-UP are software modules, and RU is a hardware structure. These modules and their execution methods are also within the scope of protection of this disclosure.

Access network equipment may support one or more types of fronthaul interfaces, with different fronthaul interfaces corresponding to DUs and RUs with different functions. If the fronthaul interface between the DU and RU is a common public radio interface (CPRI), the DU is configured to implement one or more baseband functions, and the RU is configured to implement one or more radio frequency functions. If the fronthaul interface between the DU and RU is another type of interface, compared to CPRI, some downlink and/or uplink baseband functions, such as precoding, digital beamforming (BF), or inverse fast Fourier transform (IFFT)/cyclic prefix (CP) for downlink, are moved from the DU to the RU for implementation. For uplink, digital beamforming (BF), or one or more fast Fourier transform (FFT)/cyclic prefix (CP) are moved from the DU to the RU for implementation. In one possible implementation, the interface can be an enhanced common public radio interface (eCPRI). In the eCPRI architecture, the division between the DU and RU is different, corresponding to different types (Categories) of eCPRI, such as eCPRI Category A, B, C, D, E, and F.

Taking eCPRI Cat A as an example, for downlink transmission, based on layer mapping, the DU is configured to implement layer mapping and one or more functions before it (i.e., one or more of coding, rate matching, scrambling, modulation, and layer mapping), while other functions after layer mapping (for example, one or more of resource element (RE) mapping, digital beamforming (BF), or inverse fast Fourier transform (IFFT)/adding a cyclic prefix (CP)) are moved to the RU for implementation. For uplink transmission, the DU is configured to perform demapping and one or more of the preceding functions (i.e., decoding, rate matching, descrambling, demodulation, inverse discrete Fourier transform (IDFT), channel equalization, and demapping), with demapping being the key division. Other functions after demapping (e.g., one or more of digital BF or fast Fourier transform (FFT)/CP removal) are implemented in the RU. For a functional description of the DU and RU corresponding to various types of eCPRI, please refer to the eCPRI protocol and will not be elaborated on here.

In one possible design, the processing unit used to implement baseband functions in the BBU is called a baseband high (BBH) unit, and the processing unit used to implement baseband functions in the RRU/AAU/RRH is called a baseband low (BBL) unit.

In different systems, CU (or CU-CP and CU-UP), DU or RU may have different names, but those skilled in the art will understand their meanings. For example, in an open radio access network (open RAN, ORAN) system, CU may also be called O-CU (open CU), DU may also be called O-DU, CU-CP may also be called O-CU-CP, CU-UP may also be called O-CU-UP, and RU may also be called O-RU. Any of the CU (or CU-CP, CU-UP), DU and RU in this application may be implemented by a software module, a hardware module, or a combination of a software module and a hardware module.

In the embodiments of the present application, the device for implementing the functions of the network device can be a network device; it can also be a device that can support the network device to implement the functions, such as a chip system, a hardware circuit, a software module, or a hardware circuit and a software module. The device can be installed in the network device or used in conjunction with the network device. In the embodiments of the present application, only the device for implementing the functions of the network device is used as an example to illustrate, and does not constitute a limitation on the solutions of the embodiments of the present application.

The network device and/or terminal device can be deployed on land, including indoors or outdoors, handheld or vehicle-mounted; it can also be deployed on the water surface; it can also be deployed on aircraft, balloons and satellites in the air. The embodiments of this application do not limit the scenarios in which the network device and the terminal device are located. In addition, the terminal device and the network device can be hardware devices, or they can be software functions running on dedicated hardware, software functions running on general-purpose hardware, such as virtualization functions instantiated on a platform (e.g., a cloud platform), or entities including dedicated or general-purpose hardware devices and software functions. This application does not limit the specific forms of the terminal device and the network device.

It should be understood that the number and type of each device in the communication system shown in Figure 1 are for illustration only and the present disclosure is not limited thereto. In actual applications, the communication system may further include more terminal devices, more access network devices, and other network elements, such as core network devices and/or network elements for implementing artificial intelligence functions. The network element for implementing artificial intelligence functions may be a RAN intelligent controller (RIC). Figure 2a is a schematic diagram of a communication system applicable to an embodiment of the present application. As shown in Figure 2a, communication system 200 may include at least one network device, such as network device 210 shown in Figure 2a; communication system 200 may also include at least one terminal device, such as terminal device 220 and terminal device 230 shown in Figure 2a. Network device 210 and terminal devices (such as terminal device 220 and terminal device 230) may communicate via wireless links. Communication between the communication devices in the communication system, such as network device 210 and terminal device 220, may utilize multi-antenna technology.

Figure 2b is a schematic diagram of another communication system applicable to an embodiment of the present application. Compared to the communication system 200 shown in Figure 2a, the communication system 300 shown in Figure 2b also includes an AI network element 240. AI network element 240 is used to perform AI-related operations, such as constructing a training dataset or training an AI model.

In one possible implementation, the network device 210 may send data related to the training of the AI model to the AI network element 240, which constructs a training data set and trains the AI model. For example, the data related to the training of the AI model may include data reported by the terminal device. The AI network element 240 may send the results of the operations related to the AI model to the network device 210, and forward them to the terminal device through the network device 210. For example, the results of the operations related to the AI model may include at least one of the following: an AI model that has completed training, an evaluation result or a test result of the model, etc. Exemplarily, a portion of the trained AI model may be deployed on the network device 210, and another portion may be deployed on the terminal device. Alternatively, the trained AI model may be deployed on the network device 210. Alternatively, the trained AI model may be deployed on the terminal device.

It should be understood that Figure 2b illustrates only the example of a direct connection between AI network element 240 and network device 210. In other scenarios, AI network element 240 may also be connected to a terminal device. Alternatively, AI network element 240 may be connected to both network device 210 and a terminal device simultaneously. Alternatively, AI network element 240 may be connected to network device 210 via a third-party network element (also referred to as a third-party device or third-party entity). This embodiment of the present application does not limit the connection relationship between the AI network element and other network elements.

The AI network element 240 may also be provided as a module in a network device and/or a terminal device, for example, in the network device 210 or the terminal device shown in FIG. 2 a .

It should be noted that Figures 2a and 2b are simplified schematic diagrams for ease of understanding. For example, the communication system may also include other devices, such as wireless relay devices and/or wireless backhaul devices, which are not shown in Figures 2a and 2b. In actual applications, the communication system may include multiple network devices and multiple terminal devices. The embodiments of the present application do not limit the number of network devices and terminal devices included in the communication system.

In order to support AI technology in wireless networks, AI nodes may also be introduced into the network.

Optionally, the AI node can be deployed in one or more of the following locations in the communication system: access network equipment, terminal equipment, or core network equipment. Alternatively, the AI node can be deployed independently, for example, in a location other than any of the aforementioned devices, such as a host or cloud server in an over-the-top (OTT) system. The AI node can communicate with other devices in the communication system, such as one or more of the following: network equipment, terminal equipment, or core network elements.

It is understood that this application does not limit the number of AI nodes. For example, when there are multiple AI nodes, the multiple AI nodes can be divided based on function, such as different AI nodes are responsible for different functions.

It can also be understood that AI nodes can be independent devices, or they can be integrated into the same device to implement different functions, or they can be network elements in hardware devices, or they can be software functions running on dedicated hardware, or they can be virtualized functions instantiated on a platform (for example, a cloud platform). This application does not limit the specific form of the above-mentioned AI nodes.

An AI node can be an AI network element or an AI module.

Figure 3a is a schematic diagram of a possible application framework in a communication system. As shown in Figure 3a, network elements in the communication system are connected through interfaces (e.g., NG, Xn) or air interfaces. One or more AI modules are provided in one or more devices of these network element nodes, such as core network equipment, access network (radio access network, RAN) nodes, terminals or OAM (for clarity, only one is shown in Figure 3a). The access network node can be a separate RAN node or can include multiple RAN nodes, for example, including CU and DU. The CU and/or DU can also be provided with one or more AI modules. Optionally, the CU can also be split into CU-CP and CU-UP. One or more AI models are provided in the CU-CP and/or CU-UP.

The AI module is used to implement the corresponding AI function. The AI modules deployed in different network elements may be the same or different. The model of the AI module can implement different functions according to different parameter configurations. The model of the AI module can be configured based on one or more of the following parameters: structural parameters (such as the number of neural network layers, the width of the neural network, the connection relationship between layers, the weight of the neuron, the activation function of the neuron, or at least one of the bias in the activation function), input parameters (such as the type of input parameters and/or the dimension of the input parameters), or output parameters (such as the type of output parameters and/or the dimension of the output parameters). Among them, the bias in the activation function can also be called the bias of the neural network.

An AI module can have one or more models. A model can infer an output, which includes one or more parameters. The learning, training, or inference processes of different models can be deployed on different nodes or devices, or on the same node or device.

Figure 3b is a schematic diagram of another possible application framework in a communication system. As shown in Figure 3b, the communication system includes a RAN intelligent controller (RIC). For example, the RIC can be the AI module in Figure 3a, which is used to implement AI-related functions. The RIC includes a near-real-time RIC (near-RT RIC) and a non-real-time RIC (non-RT RIC). Among them, the non-real-time RIC mainly processes non-real-time information, such as data that is not sensitive to latency, and the latency of this data can be in the order of seconds. The real-time RIC mainly processes near-real-time information, such as data that is relatively sensitive to latency, and the latency of this data is in the order of tens of milliseconds.

The near real-time RIC is used for model training and reasoning. For example, it is used to train an AI model and use the AI model for reasoning. The near real-time RIC can obtain network-side and/or terminal-side information from a RAN node (e.g., CU, CU-CP, CU-UP, DU, and/or RU) and/or a terminal. This information can be used as training data or reasoning data. Optionally, the near real-time RIC can deliver the reasoning result to the RAN node and/or the terminal. Optionally, the reasoning result can be exchanged between the CU and the DU, and/or between the DU and the RU. For example, the near real-time RIC delivers the reasoning result to the DU, and the DU sends it to the RU.

The non-real-time RIC is also used for model training and reasoning. For example, it is used to train an AI model and use the model for reasoning. The non-real-time RIC can obtain network-side and/or terminal-side information from RAN nodes (such as CU, CU-CP, CU-UP, DU and/or RU) and/or terminals. This information can be used as training data or reasoning data, and the reasoning results can be submitted to the RAN node and/or terminal. Optionally, the reasoning results can be exchanged between the CU and the DU, and/or between the DU and the RU. For example, the non-real-time RIC submits the reasoning results to the DU, and the DU sends it to the RU.

The near-real-time RIC and non-real-time RIC may also be separately configured as network elements. Optionally, the near-real-time RIC and non-real-time RIC may also be part of other devices. For example, the near-real-time RIC may be configured in a RAN node (e.g., a CU or DU), while the non-real-time RIC may be configured in an OAM, a server (e.g., a cloud server), a core network device, or other network devices.

It is understandable that all or part of the functions implemented by one or more of the terminal devices, access network devices, core network devices, or network elements used to implement artificial intelligence functions can be virtualized, that is, implemented by one or more of the proprietary processors or general-purpose processors and the corresponding software modules. Among them, since the terminal devices and access network devices involve interfaces for air interface transmission, the transceiver functions of the interfaces can be implemented by hardware. Core network devices, such as operation administration and maintenance (OAM) network elements, can be virtualized. Optionally, one or more functions of the virtualized terminal devices, access network devices, core network devices, or network elements used to implement artificial intelligence functions can be implemented by cloud devices, such as cloud devices in over-the-top (OTT) systems.

The method provided in the present disclosure can be used for communication between access network equipment and terminal equipment, and can also be used for communication between other communication equipment, such as communication between macro base stations and micro base stations in a wireless backhaul link, and communication between two terminal devices in a side link (SL), etc., without limitation.

In order to facilitate understanding of the solutions of the embodiments of the present application, the terms that may be involved in the embodiments of the present application are explained below with examples.

(1) AI model:

An AI model is an algorithm or computer program that implements AI functionality. It represents the mapping between the model's inputs and outputs. AI models can be neural networks, linear regression models, decision tree models, support vector machines (SVMs), Bayesian networks, Q-learning models, or other machine learning (ML) models.

(2) Two-end model:

The two-end model can also be called a bilateral model, collaborative model, dual model, or two-side model. A two-end model is a model composed of multiple sub-models. The sub-models that make up the model must match each other. These sub-models can be deployed on different nodes.

In one possible design, an embodiment of the present application relates to an encoder for compressing CSI and a decoder for recovering compressed CSI. The encoder and decoder are used in combination, and it can be understood that the encoder and decoder are matching AI models. An encoder can include one or more AI models, and the decoder matched with the encoder also includes one or more AI models. The number of AI models included in the matching encoder and decoder is the same and corresponds one to one.

In one possible design, a matched set of encoders and decoders can be specifically two parts of the same auto-encoder (AE), as shown in Figure 4. An AE model, in which the encoder and decoder are deployed on different nodes, is a typical bilateral model. The encoder and decoder of an AE model are typically trained together and used in pairs. The encoder processes the input V to produce the processed output z, and the decoder decodes the encoder output z into the desired output V'.

An autoencoder is a type of neural network that uses unsupervised learning. Its characteristic is that it uses input data as labels, so it can also be understood as a self-supervised learning neural network. Autoencoders can be used for data compression and recovery. For example, the encoder in an autoencoder can compress (encode) data A to obtain data B; the decoder in the autoencoder can decompress (decode) data B to recover data A. Alternatively, the decoder can be understood as the inverse operation of the encoder.

For example, the AI model in the embodiments of the present application may include an encoder and a decoder. The encoder and decoder are used in combination, and it can be understood that the encoder and decoder are a matching AI model. The encoder and decoder can be deployed on terminal devices and network devices respectively.

Alternatively, the AI model in the embodiment of the present application may be a single-end model, which may be deployed on a terminal device or a network device.

(3) Neural network (NN):

Neural networks are a specific implementation of AI or machine learning. According to the universal approximation theorem, neural networks can theoretically approximate any continuous function, giving them the ability to learn arbitrary mappings.

A neural network can be composed of neural units, which can be a computational unit that takes xs and an intercept 1 as input. A neural network is formed by connecting many of these single neural units, meaning that the output of one neural unit can be the input of another. The input of each neural unit can be connected to the local receptive field of the previous layer to extract features from that local receptive field, which can be an area consisting of several neural units.

Taking neural networks as an example, the AI models involved in this disclosure may be deep neural networks (DNNs). Depending on how the network is constructed, DNNs can include feedforward neural networks (FNNs), convolutional neural networks (CNNs), and recurrent neural networks (RNNs).

(4) Training data set and inference data:

In the field of machine learning, ground truth usually refers to data that is believed to be accurate or real.

A training dataset is used to train an AI model. It may include the input to the AI model, or the input and target output of the AI model. A training dataset includes one or more training data. Training data may include training samples input to the AI model, or the target output of the AI model. The target output may also be referred to as a label, sample label, or labeled sample. A label is the true value.

In the communications field, training datasets can include simulated data collected through simulation platforms, experimental data collected in experimental scenarios, or measured data collected in actual communication networks. Because the geographical environments and channel conditions in which data are generated vary, such as indoor and outdoor locations, mobile speeds, frequency bands, or antenna configurations, the collected data can be categorized during acquisition. For example, data with the same channel propagation environment and antenna configuration can be grouped together.

Model training essentially involves learning certain characteristics from training data. When training an AI model (such as a neural network), the goal is to ensure that the model's output is as close as possible to the desired predicted value. This is done by comparing the network's predictions with the desired target values. The weight vectors of each layer of the AI model are then updated based on the difference between the two. (Of course, this initialization process typically precedes the first update, where parameters are preconfigured for each layer of the AI model.) For example, if the network's prediction is too high, the weight vectors are adjusted to predict a lower value. This adjustment is repeated until the AI model predicts the desired target value, or a value very close to it. Therefore, it's necessary to predefine how to compare the difference between the predicted and target values. This is known as the loss function, or objective function. These are crucial equations used to measure the difference between the predicted and target values. For example, a higher loss function indicates a greater discrepancy. Therefore, training the AI model becomes a process of minimizing this loss, keeping the loss function below a threshold or ensuring that the loss function meets the desired target. For example, the AI model is a neural network, and adjusting the model parameters of the neural network includes adjusting at least one of the following parameters: the number of layers, width, weights of neurons, or parameters in the activation function of neurons of the neural network.

Inference data can be used as input to a trained AI model for inference. During the inference process, the inference data is input into the AI model, and the corresponding output is the inference result.

(5) AI model design:

The design of an AI model primarily involves data collection (e.g., collecting training data and/or inference data), model training, and model inference. Furthermore, it can also include the application of inference results.

FIG5 shows an AI application framework.

In the aforementioned data collection phase, the data source provides training datasets and inference data. In the model training phase, an AI model is generated by analyzing or training the training data provided by the data source. The AI model represents the mapping relationship between the model's inputs and outputs. Learning the AI model through the model training node is equivalent to learning the mapping relationship between the model's inputs and outputs using the training data. In the model inference phase, the AI model, trained in the model training phase, performs inference based on the inference data provided by the data source, generating an inference result. This phase can also be understood as inputting inference data into the AI model and generating an output, which is the inference result. The inference result can indicate the configuration parameters used (executed) by the execution object and/or the operations performed by the execution object. In the inference result application phase, the inference result is published. For example, the inference result can be centrally planned by an actor, for example, the actor can send the inference result to one or more actors (e.g., network devices or terminal devices) for execution. Furthermore, the actor can provide feedback on model performance to the data source to facilitate subsequent model updates and training.

It is understandable that a communication system may include network elements with artificial intelligence functions. The above-mentioned AI model design-related links can be performed by one or more network elements with artificial intelligence functions. In one possible design, AI functions (such as AI modules or AI entities) can be configured in existing network elements in the communication system to implement AI-related operations, such as training and/or reasoning of AI models. For example, the existing network element can be a network device or a terminal device. Or in another possible design, an independent network element can also be introduced into the communication system to perform AI-related operations, such as training an AI model. The independent network element can be called an AI network element, an AI node, or an AI entity, etc., and the embodiments of the present application do not limit this name. For example, the AI network element can be directly connected to the network device in the communication system, or it can be indirectly connected through a third-party network element and the network device. Among them, the third-party network element can be a core network network element such as an authentication management function (AMF) network element, a user plane function (UPF) network element, an operation administration and maintenance (OAM), a server (such as a cloud server), an over-the-top (OTT) device or other network element, without limitation. Exemplarily, the independent AI network element or AI entity or AI node can be deployed on one or more of the network device side, the terminal device side, or the core network side. Optionally, it can be deployed on a server, such as a cloud server, or an OTT device, or other device. Exemplarily, an AI network element 240 is introduced in the communication system shown in Figure 2b. It will be understood that the aforementioned AI modules, AI entities, AI network elements, or AI nodes can be used to perform one or more AI functions, where the AI functions may include: processing of AI models, such as training and/or updating of AI models, monitoring of AI models, management of AI models, such as registration and/or deregistration of AI models, or application reasoning of AI models.

The training process of different models can be deployed in different devices or nodes, or in the same device or node. The inference process of different models can be deployed in different devices or nodes, or in the same device or node. Taking the completion of the model training phase of a terminal device as an example, the terminal device can train the matching encoder and decoder, and then send the model parameters of the decoder to the network device. Taking the completion of the model training phase of a network device as an example, after the network device trains the matching encoder and decoder, it can indicate the model parameters of the encoder to the terminal device. Taking the completion of the model training phase of an independent AI network element as an example, the AI network element can train the matching encoder and decoder, and then send the model parameters of the encoder to the terminal device and the model parameters of the decoder to the network device. Then, the model inference phase corresponding to the encoder is performed in the terminal device, and the model inference phase corresponding to the decoder is performed in the network device.

Among them, the model parameters may include one or more of the following structural parameters of the model (such as the number of layers and/or weights of the model, etc.), the input parameters of the model (such as input dimension, number of input ports), or the output parameters of the model (such as output dimension, number of output ports). It can be understood that the input dimension may refer to the size of an input data. For example, when the input data is a sequence, the input dimension corresponding to the sequence may indicate the length of the sequence. The number of input ports may refer to the number of input data. Similarly, the output dimension may refer to the size of an output data. For example, when the output data is a sequence, the output dimension corresponding to the sequence may indicate the length of the sequence. The number of output ports may refer to the number of output data.

(6) Channel information:

In communication systems (such as LTE and NR), network equipment needs to determine the resource, MCS, and precoding configurations for downlink data channels of terminal devices based on channel information. Channel information, also known as channel state information (CSI) or channel environment information, reflects channel characteristics and quality. In the present application, the meaning of CSI is broader than that of CSI in traditional schemes, and is not limited to channel quality indication (CQI), precoding matrix indicator (PMI), rank indicator (RI), or CSI-RS resource indicator (CRI). It can also be one or more of channel response information (such as channel response matrix), weight information or precoding information corresponding to the channel response, a matrix composed of eigenvectors of the channel response, reference signal receiving power (RSRP) or signal to interference plus noise ratio (SINR) or other information that can characterize the channel state.

CSI measurement involves the receiver determining channel information based on a reference signal sent by the transmitter, i.e., estimating the channel information using a channel estimation method. For example, the reference signal may include one or more of a channel state information reference signal (CSI-RS), a synchronizing signal/physical broadcast channel block (SSB), a sounding reference signal (SRS), or a demodulation reference signal (DMRS). CSI-RS, SSB, and DMRS can be used to measure downlink CSI. SRS and DMRS can be used to measure uplink CSI.

Taking FDD communication scenarios as an example, in FDD communication scenarios, because uplink and downlink channels are not reciprocal or cannot be guaranteed, network equipment typically transmits a downlink reference signal to the terminal device. The terminal device performs channel and interference measurements based on the received downlink reference signal to estimate the downlink CSI. The terminal device generates a CSI report based on a protocol predefined method or a network device configuration method and feeds it back to the network device to obtain the downlink CSI.

Exemplarily, CSI may include at least one of the following: channel quality indication (CQI), precoding matrix indicator (PMI), rank indicator (RI), CSI-RS resource indicator (CRI), layer indicator (LI), reference signal receiving power (RSRP), or signal to interference plus noise ratio (SINR). The signal to interference plus noise ratio may also be called signal to interference plus noise ratio.

The RI indicates the number of downlink transmission layers recommended by the terminal device, the CQI indicates the modulation and coding scheme supported by the current channel conditions as determined by the terminal device, and the PMI indicates the precoding recommended by the terminal device. The number of precoding layers indicated by the PMI corresponds to the RI.

It should be understood that the RI, CQI, and PMI indicated in the above CSI report are only recommended values for the terminal device, and the network device may perform downlink transmission according to part or all of the information indicated in the CSI report. Alternatively, the network device may not perform downlink transmission according to the information indicated in the CSI report.

The introduction of AI technology into wireless communication networks has resulted in a CSI feedback method based on AI models. Terminal devices use AI models to compress and feedback CSI, and network equipment uses AI models to recover the compressed CSI. AI-based CSI feedback transmits a sequence (such as a bit sequence), resulting in lower overhead than traditional CSI feedback.

Taking Figure 4 as an example, the encoder in Figure 4 can be a CSI generator, and the decoder can be a CSI reconstructor. The encoder can be deployed in a terminal device, and the decoder can be deployed in a network device. The terminal device can use the encoder to generate CSI feedback information z from the original CSI information V. The terminal device reports a CSI report, which can include the CSI feedback information z. The network device can use the decoder to reconstruct the CSI information, thereby obtaining the recovered CSI information V'.

The CSI original information V may be obtained by the terminal device through CSI measurement. For example, the CSI original information V may include the channel response of the downlink channel or the eigenvector matrix of the downlink channel (a matrix composed of eigenvectors). The encoder processes the eigenvector matrix of the downlink channel to obtain CSI feedback information z. In other words, the compression and/or quantization operation of the eigenmatrix according to the codebook in the related scheme is replaced by the operation of processing the eigenmatrix by the encoder to obtain CSI feedback information z. The terminal device reports the CSI feedback information z. The network device processes the CSI feedback information z through the decoder to obtain CSI recovery information V'.

The following further illustrates the training process and reasoning process of the AI model in the embodiments of the present application.

The training data used to train AI models includes training samples and sample labels. For example, the training samples are channel information determined by the terminal device, and the sample labels are the actual channel information, i.e., the true value CSI. If the encoder and decoder belong to the same autoencoder, the training data can only include the training samples, or the training samples are the sample labels.

In the field of wireless communications, true CSI may be uncompressed CSI, that is, high-precision CSI.

The specific training process is as follows: the model training node uses an encoder to process channel information, that is, training samples, to obtain channel feedback information, such as CSI feedback information, and uses a decoder to process the feedback information to obtain recovered channel information, that is, channel recovery information, such as CSI recovery information. Then, the difference between the channel recovery information and the corresponding sample label is calculated, that is, the value of the loss function, and the parameters of the encoder and decoder are updated according to the value of the loss function, so that the difference between the recovered channel information and the corresponding sample label is minimized, that is, the loss function is minimized. Exemplarily, the loss function can be the minimum mean square error (MSE) or cosine similarity. Repeat the above operations to obtain an encoder and decoder that meet the target requirements. The above model training node can be a terminal device, a network device, or other network elements with AI functions in a communication system.

It should be understood that the above description uses the AI model for CSI compression as an example. The AI model can also be used in other scenarios in CSI feedback. For example, the AI model can be used for CSI prediction, that is, predicting channel information at one or more future moments based on channel information measured at one or more historical moments. The embodiments of this application do not limit the specific use of the AI model in CSI feedback scenarios.

It should be understood that, in this application, indication includes direct indication (also known as explicit indication) and implicit indication. Direct indication of information A refers to including information A; implicit indication of information A refers to indicating information A through the correspondence between information A and information B and the direct indication of information B. The correspondence between information A and information B can be predefined, pre-stored, pre-burned, or pre-configured.

It should be understood that, in this application, information C is used to determine information D, which includes both information D being determined solely based on information C and information D being determined based on information C and other information. Furthermore, information C can also be used to determine information D indirectly, for example, where information D is determined based on information E, and information E is determined based on information C.

In addition, in each embodiment of the present application, "network element A sends information A to network element B" can be understood as the destination end of the information A or the intermediate network element in the transmission path between the destination end and the network element B, which may include directly or indirectly sending information to network element B. "Network element B receives information A from network element A" can be understood as the source end of the information A or the intermediate network element in the transmission path between the source end and the network element A, which may include directly or indirectly receiving information from network element A. The information may be processed as necessary between the source end and the destination end of the information transmission, such as format changes, but the destination end can understand the valid information from the source end. Similar expressions in this application can be understood similarly and will not be elaborated here.

The method of the embodiment of the present application is described in detail below.

Referring to Figure 6, it is a flow chart of a model monitoring method provided by an embodiment of the present application. Optionally, the method can be applied to the aforementioned communication system, such as the communication system shown in Figure 1. The model monitoring method shown in Figure 6 may include steps 601-603. It should be understood that this application is described in the order of 601-603 for the convenience of description, and is not intended to limit execution to the above order. The embodiment of the present application does not limit the order of execution of one or more steps above, the time of execution, the number of executions, etc. Steps 601-603 are as follows:

601. A network device sends a reference signal to a user equipment. Correspondingly, the user equipment receives the reference signal.

Exemplarily, the reference signal may be a downlink reference signal, such as a channel state information reference signal CSI-RS.

602. The user equipment sends first information and second information to the network device. The first information includes true CSI, which is obtained based on the reference signal; the second information includes a first CSI report, which is obtained based on the true CSI; the first CSI report is a complete report. Accordingly, the network device receives the first information and the second information.

It is understandable that the first information and the second information may be sent in the same message, or the first information and the second information may be sent in two different messages. When the first information and the second information are sent in two different messages, this solution does not restrict the sending order, sending time, etc. of the two messages.

The true CSI can be understood as the CSI obtained by the user equipment (UE) by measuring the downlink reference signal. This CSI is uncompressed CSI and can be the channel response matrix measured by the UE or the precoding matrix after processing the channel response matrix. The true CSI can also be called input CSI, model input, measured CSI, original CSI, or ground-truth CSI, which is not limited in this solution. The true CSI is obtained based on the reference signal.

Illustratively, the true CSI may be obtained by measuring the reference signal, or by performing eigendecomposition or singular value decomposition on the measured CSI.

This first CSI report can be referred to as CSI feedback, CSI latent space, quantized CSI, or compressed CSI (CSI compression). This first CSI report can be used for model monitoring. Model monitoring involves monitoring the performance of, for example, an AI model to determine whether the AI model is functioning properly. For example, if the AI model performs poorly, it is necessary to switch to a non-AI mode, replace the AI model, or update the AI model. Model monitoring can be achieved by monitoring the accuracy of the AI model output (also known as an intermediate key performance indicator (KPI)) or by monitoring system performance (also known as monitoring the final KPI). Monitoring the accuracy of the AI model output involves comparing the difference between the AI model output and the corresponding label or ground-truth to determine whether the AI model's performance meets the requirements. Monitoring system performance involves monitoring whether the performance of the communication system meets the requirements after using the AI model. Intermediate KPIs usually include generalized cosine similarity GCS (generalized consine similarity), squared cosine similarity SGCS (squre GCS), mean squared error MSE (mean squared error), normalized mean squared error NMSE (normalized mean squared error), etc. Final KPIs usually include throughput, spectrum efficiency, transmission rate, block error rate BLER (block error rate), hypothetical BLER (hypothetical BLER), hybrid automatic repeat request (HARQ) feedback, etc.

The first CSI report may be a complete report, wherein the complete report may be understood as a CSI report without omissions, and the complete report may include information such as compressed CSI or quantized CSI.

In one possible implementation, an encoder in an autoencoder (AE) model is deployed on the user equipment side. This encoder may also be referred to as a CSI generator, a CSI generation model, or a CSI generation portion. The first CSI report can be obtained by inputting true CSI into the encoder for CSI compression and quantization.

In a possible implementation, the user equipment and the network device use a complete CSI report for model monitoring based on a protocol definition. The user equipment sends a first CSI report to the network device, where the first CSI report is a complete report.

In another possible implementation, a network device sends first indication information to a user equipment, where the first indication information indicates the use of a complete CSI report for model monitoring; or, the first indication information instructs the user equipment to send a complete CSI report. Accordingly, the user equipment receives the first indication information. Furthermore, the user equipment sends a first CSI report based on the first indication information, where the first CSI report is a complete report.

In a possible implementation, the network device sends fifth information to the user equipment, where the fifth information is used to indicate a first resource, and the first resource is used to transmit a complete CSI report.

During the model monitoring process, or when the network device configures the user equipment to feedback a CSI report for model monitoring, the network device needs to allocate sufficient uplink resources to the user equipment for transmitting the complete CSI report, so that the user equipment can complete the transmission of the complete CSI report based on the resources.

In one possible implementation, the user equipment does not expect CSI omission to occur in the CSI report for model monitoring, or the user equipment does not expect to omit the CSI report for model monitoring, or the user equipment does not expect that resources used to transmit the CSI report for model monitoring are less than resources required for the CSI report for model monitoring.

In this way, the network device needs to configure sufficient resources for the user equipment to transmit a complete CSI report.

In one possible implementation, when the CSI report for model monitoring is omitted, or the resources used to transmit the CSI report for model monitoring are less than the resources required for the CSI report for model monitoring, the user equipment sends sixth information to the network device, where the sixth information includes at least one of the size of the CSI report for model monitoring, the size of the omitted part of the CSI report for model monitoring, the resources required for the CSI report for model monitoring, and the resources required for the omitted part of the CSI report for model monitoring.

In this way, the network device can allocate additional resources for the transmission of the CSI report to transmit the complete CSI report.

In one possible implementation, the priority of a CSI report used for model monitoring (i.e., the first CSI report described above, or the second CSI report described below, etc.) is higher than that of other CSI reports (e.g., a report used for CSI feedback, such as the third CSI report described below, etc.), or the priority of bits in the CSI report used for model monitoring (i.e., the first CSI report described above, or the second CSI report described below, etc.) is not distinguished, or the priority of the CSI report used for model monitoring is the same as that of the report used to feedback true CSI, and is higher than that of other CSI reports.

Among them, when the priority of the CSI report used for model monitoring is higher than other CSI reports, when two or more CSI reports of the above user equipment conflict in the time domain, in some cases the user equipment will not send the CSI report with a lower priority.

The above-mentioned CSI report for model monitoring does not distinguish between priorities between bits, that is, the CSI report for model monitoring does not distinguish between priorities between report contents. For example, the report content in the CSI report for model monitoring includes compressed CSI of different ranks (layers or streams) or different segments. The compressed CSI of different ranks or different segments are distinguished using different bits, and these bits do not distinguish between priorities.

In one possible implementation, the user equipment uses high-layer signaling to report a CSI report for model monitoring (i.e., the first CSI report mentioned above, or the second CSI report described below, etc.). The high-layer signaling can be, for example, a medium access control (MAC) layer signaling or a radio resource control (RRC) signaling. For example, the user equipment can use RRC signaling to send the second information, or the first information and the second information, to the network device. That is, regardless of whether the user equipment sends a complete or omitted CSI report during the CSI feedback process of model inference, the user equipment will use high-layer signaling to send a complete CSI report during the model monitoring process. In other words, the user equipment will use high-layer signaling and uplink control information (UCI) to send CSI reports representing the same CSI, respectively, where UCI is used for the CSI feedback process of model inference and high-layer signaling is used for model monitoring.

603. The network device obtains a first model monitoring performance based on the first information and the second information.

In a possible implementation, the network device obtains the restored CSI based on the second information.

The recovered CSI can be understood as the CSI obtained by recovering the compressed CSI. The recovered CSI can also be called output CSI, reconstructed CSI, recovery CSI, reconstructed CSI, output CSI, or CSI reconstruction.

In one possible implementation, a decoder in the autoencoder (AE) model is deployed on the network device side. This decoder may also be referred to as a CSI reconstructor, a CSI reconstruction model, or a CSI reconstruction portion. The first CSI report is input into the decoder to recover the CSI, thereby obtaining the recovered CSI.

Furthermore, the network device obtains a first model monitoring performance based on the first information (true CSI) and the recovered CSI.

Exemplarily, when the first model monitoring performance is an intermediate KPI (such as GCS), then is the recovered CSI of the i-th resource unit, _wi is the true CSI of the i-th resource unit, for The norm of, N is the total number of resource units, H is the true value CSI, To restore CSI.

Exemplarily, when the first model monitoring performance is an intermediate KPI (such as SGCS), then is the recovered CSI of the i-th resource unit, and _wi is the true CSI of the i-th resource unit.

Exemplarily, when the first model monitoring performance is an intermediate KPI (such as MSE), then is the recovered CSI of the i-th resource unit, and _wi is the true CSI of the i-th resource unit.

Exemplarily, when the first model monitoring performance is an intermediate KPI (such as NMSE), then is the recovered CSI of the i-th resource unit, and _wi is the true CSI of the i-th resource unit.

Based on the above processing, the performance of the monitoring model can be obtained.

In one possible implementation, the method further includes step 604: the user equipment further sends third information to the network device, where the third information includes a second CSI report, where the second CSI report is an omitted report and is obtained based on the reference signal. Accordingly, the network device receives the third information.

The omitted report can be understood as a CSI report that discards or omits part of its content. The omitted report may include part of the compressed CSI or quantized CSI, that is, a report obtained by omitting the compressed CSI or quantized CSI information in the complete report. For example, when the uplink resources used to transmit the CSI report are insufficient to transmit the complete CSI report, the user equipment may omit some bits or content of the CSI report with lower priority.

The second CSI report is also used for model monitoring. The second CSI report can be obtained by measuring the reference signal. For example, the second CSI report and the first CSI report are obtained by measuring the reference signal at the same time, that is, the omitted CSI report is obtained by omitting the first CSI report (the complete CSI report); or the second CSI report and the first CSI report are obtained by measuring the reference signal at different times, which is not limited in this solution.

Accordingly, the method further includes step 605: the network device obtains the second model monitoring performance based on the first information and the third information. For the introduction of this part, please refer to the above description of obtaining the first model monitoring performance, which will not be repeated here.

In this example, the user equipment sends not only a complete CSI report (first CSI report) but also an omitted CSI report (second CSI report) to the network device. Both the first and second CSI reports are used for model monitoring. Based on the first and second CSI reports, the network device can obtain first and second model monitoring performance. Based on this example, both the performance of the model itself and its robustness to CSI omission can be monitored simultaneously.

Optionally, the second CSI report may also be a complete report, which is not limited in this solution.

In a possible implementation, the method further includes step 606: the user equipment sends fourth information to the network device, where the fourth information includes a third CSI report, the third CSI report is an omitted report, and the third CSI report is used for CSI feedback.

The third CSI report is used for CSI feedback, for example, when performing model inference, using an AI model for CSI feedback so that the network device can obtain precoding for downlink transmission. Model inference can be understood as using an AI model for CSI feedback.

The third CSI report omits low-priority bits or contents in the complete report.

It is understandable that the third CSI report may also be a complete report, and this solution does not limit this.

In this embodiment of the present application, a user device sends first information and second information to a network device. The first information includes true CSI, and the second information includes a first CSI report. The first CSI report is a complete report. The network device can monitor model performance based on the true CSI and the first CSI report. This approach allows the network device to monitor model performance using the complete CSI report, eliminating the impact of omitted CSI and maintaining the performance of the model.

The example shown in Figure 6 is introduced by taking the first CSI report as a complete report as an example, and the following is introduced as the first CSI report as an omitted report. Referring to Figure 7, it is a flow chart of a model monitoring method provided by an embodiment of the present application. Optionally, the method can be applied to the aforementioned communication system, such as the communication system shown in Figure 1. The model monitoring method shown in Figure 7 may include steps 701-703. It should be understood that this application is described in the order of 701-703 for the convenience of description, and is not intended to be limited to execution in the above order. The embodiment of the present application does not limit the order of execution, execution time, number of executions, etc. of the above one or more steps. Steps 701-703 are as follows:

701. A network device sends a reference signal to a user equipment. Correspondingly, the user equipment receives the reference signal.

Exemplarily, the reference signal may be a downlink reference signal, such as a channel state information reference signal CSI-RS.

702. The user equipment sends first information and second information to the network device. The first information includes true CSI, which is obtained based on the reference signal; the second information includes a first CSI report, which is obtained based on the true CSI; the first CSI report is an omitted report. Accordingly, the network device receives the first information and the second information.

The first CSI report is an omitted report. This omitted report can be understood as a CSI report that discards or omits some of its content. This omitted report may include some compressed CSI or quantized CSI content, i.e., a report obtained by omitting the compressed CSI or quantized CSI information in a complete report. For example, when the uplink resources used to transmit the CSI report are insufficient to transmit the complete CSI report, the user equipment may omit some lower-priority bits or content in the CSI report.

In a possible implementation, the user equipment and the network device use omitted CSI reporting for model monitoring based on protocol definition, and the user equipment sends a first CSI report to the network device, where the first CSI report is an omitted report.

In another possible implementation, the network device sends second indication information to the user equipment, where the second indication information instructs the user equipment to use the omitted CSI report for model monitoring; or, alternatively, the second indication information instructs the user equipment to send the omitted CSI report. Accordingly, the user equipment receives the second indication information. Furthermore, the user equipment sends a first CSI report based on the second indication information, where the first CSI report is the omitted report.

In one possible implementation, the user equipment (UE) is deployed with an encoder in an autoencoder (AE) model. This encoder may also be referred to as a CSI generator, CSI generation model, or CSI generation component. By inputting the true CSI into the encoder for CSI compression and quantization, a complete CSI report can be obtained. Furthermore, by performing omission processing based on this complete CSI report, the aforementioned first CSI report can be obtained.

In one possible implementation, the priority of a CSI report used for model monitoring (i.e., the first CSI report described above, or the second CSI report described below, etc.) is higher than that of other CSI reports (e.g., a report used for CSI feedback, such as the third CSI report described below, etc.), or the priority of bits in the CSI report used for model monitoring (i.e., the first CSI report described above, or the second CSI report described below, etc.) is not distinguished, or the priority of the CSI report used for model monitoring is the same as that of the report used to feedback true CSI, and is higher than that of other CSI reports.

Among them, when the priority of the CSI report used for model monitoring is higher than other CSI reports, when two or more CSI reports of the above user equipment conflict in the time domain, in some cases the user equipment will not send the CSI report with a lower priority.

The above-mentioned CSI report for model monitoring does not distinguish between priorities between bits, that is, the CSI report for model monitoring does not distinguish between priorities between report contents. For example, the report content in the CSI report for model monitoring includes compressed CSI of different ranks (layers or streams) or different segments. The compressed CSI of different ranks or different segments are distinguished using different bits, and these bits do not distinguish between priorities.

In one possible implementation, the user equipment uses high-layer signaling to report a CSI report for model monitoring (i.e., the first CSI report mentioned above, or the second CSI report described below, etc.). The high-layer signaling can be, for example, a media access control MAC layer signaling or a radio resource control RRC signaling. For example, the user equipment can use RRC signaling to send the second information, or the first information and the second information, to the network device. That is, regardless of whether the user equipment sends a complete or omitted CSI report during the CSI feedback process of model reasoning, the user equipment will use high-layer signaling to send a complete CSI report during the model monitoring process. In other words, the user equipment will use high-layer signaling and UCI to send CSI reports representing the same CSI, respectively, where UCI is used for the CSI feedback process of model reasoning and high-layer signaling is used for model monitoring.

703. The network device obtains a first model monitoring performance based on the first information and the second information.

In one possible implementation, the network device recovers the CSI based on the second information. Exemplarily, the network device deploys a decoder in an autoencoder (AE) model. The decoder may also be referred to as a CSI reconstructor, a CSI reconstruction model, or a CSI reconstruction component. The recovered CSI can be obtained by inputting the first CSI report into the decoder for CSI recovery.

Furthermore, the network device obtains a first model monitoring performance based on the first information (true CSI) and the recovered CSI.

For the introduction of this step, please refer to the description of step 603 in the embodiment shown in FIG6 , which will not be repeated here.

In one possible implementation, the method further includes step 704: the user equipment further sends third information to the network device, where the third information includes a second CSI report, where the second CSI report is a complete report and is obtained based on the reference signal. Accordingly, the network device receives the third information.

The second CSI report is also used for model monitoring. The second CSI report can be obtained by measuring the reference signal. For example, the second CSI report and the first CSI report are obtained by measuring the reference signal at the same time, that is, the omitted CSI report (first CSI report) is obtained by omitting the second CSI report (complete CSI report); or the second CSI report and the first CSI report are obtained by measuring the reference signal at different times, which is not limited in this solution.

Accordingly, the method further includes step 705: the network device obtains the second model monitoring performance based on the first information and the third information. For the introduction of this part, please refer to the above description of obtaining the first model monitoring performance, which will not be repeated here.

In this example, the user equipment not only sends an omitted CSI report (the first CSI report) but also sends a complete CSI report (the second CSI report) to the network device. Both the first CSI report and the second CSI report are used for model monitoring. The network device can obtain first model monitoring performance and second model monitoring performance based on the first and second CSI reports.

Optionally, the second CSI report may also be an omitted report, which is not limited in this solution.

In a possible implementation, the method further includes step 706: the user equipment sends fourth information to the network device, where the fourth information includes a third CSI report, the third CSI report is an omitted report, and the third CSI report is used for CSI feedback.

The third CSI report is used for CSI feedback. For example, when performing model inference, an AI model is used for CSI feedback so that the network device can obtain precoding for downlink transmission. Model inference can be understood as using an AI model for CSI feedback.

The third CSI report omits low-priority bits or contents in the complete report. For an introduction to this part, please refer to the aforementioned record in step 702 and will not be repeated here.

It is understandable that the third CSI report may also be a complete report, and this solution does not limit this.

In this embodiment of the present application, a user device sends first information and second information to a network device. The first information includes true CSI, and the second information includes a first CSI report. The first CSI report is an omitted report. In this way, the network device can monitor model performance based on the true CSI and the first CSI report. Using this approach, the network device uses the omitted CSI report for model monitoring, enabling monitoring of the model's robustness to CSI omissions.

The above example uses the network device side to perform model performance monitoring as an example. The following example uses the user device side to perform model performance monitoring.

Referring to Figure 8, it is a flow chart of a model monitoring method provided by an embodiment of the present application. Optionally, the method can be applied to the aforementioned communication system, such as the communication system shown in Figure 1. The model monitoring method shown in Figure 8 may include steps 801-804. It should be understood that this application is described in the order of 801-804 for the convenience of description, and is not intended to limit execution to the above order. The embodiment of the present application does not limit the order of execution of one or more steps above, the time of execution, the number of executions, etc. Steps 801-804 are as follows:

801. A network device sends a reference signal to a user equipment. Correspondingly, the user equipment receives the reference signal.

For the introduction of this step, please refer to the description of step 601 in the embodiment shown in FIG6 , which will not be repeated here.

802. The user equipment sends first information to the network device. The first information includes a first CSI report, which is obtained based on the reference signal. The first CSI report is a complete report. In response, the network device receives the first information.

Exemplarily, the user equipment obtains the true CSI by measuring the reference signal, or performs eigendecomposition or singular value decomposition on the measured CSI to obtain the true CSI. Furthermore, the user equipment may obtain the first CSI report by inputting the true CSI into an encoder for CSI compression and quantization.

In a possible implementation, the user equipment and the network device use a complete CSI report for model monitoring based on a protocol definition. The user equipment sends a first CSI report to the network device, where the first CSI report is a complete report.

In another possible implementation, a network device sends first indication information to a user equipment, where the first indication information indicates the use of a complete CSI report for model monitoring; or, the first indication information instructs the user equipment to send a complete CSI report. Accordingly, the user equipment receives the first indication information. Furthermore, the user equipment sends a first CSI report based on the first indication information, where the first CSI report is a complete report.

In a possible implementation, the network device sends fifth information to the user equipment, where the fifth information is used to indicate a first resource, and the first resource is used to transmit a complete CSI report.

During the model monitoring process, or when the network device configures the user equipment to feedback a CSI report for model monitoring, the network device needs to allocate sufficient uplink resources to the user equipment for transmitting the complete CSI report, so that the user equipment can complete the transmission of the complete CSI report based on the resources.

In one possible implementation, the user equipment does not expect CSI omission to occur in the CSI report for model monitoring, or the user equipment does not expect to omit the CSI report for model monitoring, or the user equipment does not expect that resources used to transmit the CSI report for model monitoring are less than resources required for the CSI report for model monitoring.

In this way, the network device needs to configure sufficient resources for the user equipment to transmit a complete CSI report.

In one possible implementation, when the CSI report for model monitoring is omitted, or the resources used to transmit the CSI report for model monitoring are less than the resources required for the CSI report for model monitoring, the user equipment sends sixth information to the network device, where the sixth information includes at least one of the size of the CSI report for model monitoring, the size of the omitted part of the CSI report for model monitoring, the resources required for the CSI report for model monitoring, and the resources required for the omitted part of the CSI report for model monitoring.

In this way, the network device can allocate additional resources for the transmission of the CSI report to transmit the complete CSI report.

In one possible implementation, the priority of a CSI report used for model monitoring (i.e., the first CSI report described above, or the second CSI report described below, etc.) is higher than that of other CSI reports (e.g., a report used for CSI feedback, such as the third CSI report described below, etc.), or the priority of bits in the CSI report used for model monitoring (i.e., the first CSI report described above, or the second CSI report described below, etc.) is not distinguished, or the priority of the CSI report used for model monitoring is the same as that of the report used to feedback true CSI, and is higher than that of other CSI reports.

In one possible implementation, the user equipment uses high-layer signaling to report a CSI report for model monitoring (i.e., the first CSI report described above, or the second CSI report described below, etc.). The high-layer signaling may be, for example, medium access control (MAC) layer signaling or radio resource control (RRC) signaling. For example, the user equipment may use RRC signaling to send the first information to the network device.

For the introduction of this part, please refer to the description of step 602 in the embodiment shown in FIG6 , which will not be repeated here.

803. The network device sends second information to the user equipment, where the second information is used to indicate first restored CSI, where the first restored CSI is obtained based on the first CSI report. Correspondingly, the user equipment receives the second information.

Exemplarily, the network device may obtain the first recovered CSI by inputting the first CSI report into a decoder for processing. The network device then transmits the first recovered CSI to the user equipment. Alternatively, the second information transmitted by the network device to the user equipment may include a reference signal, in which the first recovered CSI is integrated (carried) within the reference signal. This solution is not limited to this.

804. The user equipment obtains a first model monitoring performance based on the true CSI and the second information, where the true CSI is obtained based on the reference signal.

The user equipment obtains a first model monitoring performance based on the true CSI and the first restored CSI. For an introduction to this step, please refer to the description of step 603 in the embodiment shown in FIG6 , which will not be repeated here.

In one possible implementation, the user device sends the first model monitoring performance to the network device. Accordingly, the network device receives the first model monitoring performance. This allows the network device to switch to a non-AI model or replace the AI model when the AI model performance is poor.

In one possible implementation, the method further includes step 805: the user equipment further sends third information to the network device, where the third information includes a second CSI report, where the second CSI report is an omitted report and is obtained based on the reference signal. Accordingly, the network device receives the third information.

The method further includes step 806: the network device further sends fourth information to the user equipment, the fourth information being used to indicate second restored CSI, the second restored CSI being obtained based on the second CSI report. Accordingly, the user equipment receives the fourth information.

Accordingly, step 807 is also included: the user equipment obtains a second model monitoring performance based on the true CSI and the fourth information (the second restored CSI). For the introduction of this part, please refer to the description of step 603 in the embodiment shown in Figure 6 above, and will not be repeated here.

In this example, the user equipment sends not only a complete CSI report (first CSI report) but also an omitted CSI report (second CSI report) to the network device. Both the first CSI report and the second CSI report are used for model monitoring. The network device can obtain first and second model monitoring performance based on the first and second CSI reports.

In a possible implementation, the method further includes step 808: the user equipment sends fifth information to the network equipment, where the fifth information includes a third CSI report, the third CSI report is an omitted report, and the third CSI report is used for CSI feedback.

The third CSI report is used for CSI feedback. For example, when performing model inference, an AI model is used for CSI feedback so that the network device can obtain precoding for downlink transmission.

For an introduction to the third CSI report, please refer to the description of step 603 in the embodiment shown in FIG6 , which will not be repeated here.

In an embodiment of the present application, a user device sends first information to a network device, where the first information includes a first CSI report. The first CSI report is a complete report. The network device recovers CSI based on the first CSI report and sends the recovered CSI to the user device. The user device then monitors model performance based on the true CSI and the recovered CSI. This approach allows the user device to monitor the model using the complete CSI report, eliminating the impact of omitted CSI and enabling the monitoring of the model's performance.

The example shown in Figure 8 is introduced by taking the first CSI report as a complete report as an example, and the following introduction is based on the first CSI report being an omitted report. Referring to Figure 9, it is a flow chart of a model monitoring method provided in an embodiment of the present application. Optionally, the method can be applied to the aforementioned communication system, such as the communication system shown in Figure 1. The model monitoring method shown in Figure 9 may include steps 901-904. It should be understood that this application is described in the order of 901-904 for the convenience of description, and is not intended to be limited to execution in the above order. The embodiment of the present application does not limit the order of execution, execution time, number of executions, etc. of the above one or more steps. Steps 901-904 are as follows:

901. A network device sends a reference signal to a user equipment. Correspondingly, the user equipment receives the reference signal.

For the introduction of this step, please refer to the description of step 601 in the embodiment shown in FIG6 , which will not be repeated here.

902. The user equipment sends first information to the network device. The first information includes a first CSI report, which is obtained based on the reference signal. The first CSI report is an omitted report. Accordingly, the network device receives the first information.

In one possible implementation, the user equipment and the network device perform model monitoring based on the protocol definition using the omitted CSI report. The user equipment sends a first CSI report to the network device, where the first CSI report is an omitted report.

In another possible implementation, the network device sends second indication information to the user equipment, where the second indication information instructs the user equipment to use the omitted CSI report for model monitoring; or, alternatively, the second indication information instructs the user equipment to send the omitted CSI report. Accordingly, the user equipment receives the second indication information. Furthermore, the user equipment sends a first CSI report based on the second indication information, where the first CSI report is the omitted report.

In one possible implementation, the priority of the CSI report used for model monitoring (i.e., the first CSI report mentioned above, or the second CSI report described below, etc.) is higher than that of other CSI reports (e.g., reports used for CSI feedback, such as the third CSI report described below, etc.), or the priority of bits in the CSI report used for model monitoring (i.e., the first CSI report mentioned above, or the second CSI report described below, etc.) is not distinguished, or the priority of the CSI report used for model monitoring is the same as the priority of the report used to feedback true CSI.

In one possible implementation, the user equipment uses high-layer signaling to report a CSI report for model monitoring (i.e., the first CSI report mentioned above, or the second CSI report as described below, etc.). The high-layer signaling can be, for example, a media access control MAC layer signaling or a radio resource control RRC signaling. For example, the user equipment can use RRC signaling to send the first information to the network device. That is, regardless of whether the user equipment sends a complete or omitted CSI report during the CSI feedback process of model reasoning, the user equipment will use high-layer signaling to send a complete CSI report during the model monitoring process. In other words, the user equipment will use high-layer signaling and UCI to send CSI reports representing the same CSI, respectively, where UCI is used for the CSI feedback process of model reasoning and high-layer signaling is used for model monitoring.

For the introduction of this step, please refer to the description of step 602 in the embodiment shown in FIG6 and step 703 in the embodiment shown in FIG7 , and will not be repeated here.

903. The network device sends second information to the user equipment, where the second information is used to indicate first restored CSI, where the first restored CSI is obtained based on the first CSI report. Correspondingly, the user equipment receives the second information.

Exemplarily, the network device inputs the first CSI report into a decoder for processing to obtain the first recovered CSI. The network device then transmits the first recovered CSI to the user equipment. For an introduction to this step, please refer to step 603 in the embodiment shown in FIG. 6 , and will not be repeated here.

904. The user equipment obtains a first model monitoring performance based on the true CSI and the second information, where the true CSI is obtained based on the reference signal.

The user equipment obtains a first model monitoring performance based on the true CSI and the first restored CSI. For an introduction to this step, please refer to the description of step 603 in the embodiment shown in FIG6 , which will not be repeated here.

In one possible implementation, the user device sends the first model monitoring performance to the network device. Accordingly, the network device receives the first model monitoring performance. This allows the network device to switch to a non-AI model or replace the AI model when the AI model performance is poor.

In one possible implementation, the method further includes step 905: the user equipment further sends third information to the network device, where the third information includes a second CSI report, where the second CSI report is a complete report and is obtained based on the reference signal. Accordingly, the network device receives the third information.

The method further includes step 906: the network device further sends fourth information to the user equipment, the fourth information being used to indicate second restored CSI, where the second restored CSI is obtained based on the second CSI report. Accordingly, the user equipment receives the fourth information.

Accordingly, the method further includes step 907: the user equipment obtains the second model monitoring performance based on the true CSI and the fourth information (the second restored CSI). For the introduction of this part, please refer to the above description of obtaining the first model monitoring performance, which will not be repeated here.

In this example, the user equipment not only sends an omitted CSI report (the first CSI report) but also sends a complete CSI report (the second CSI report) to the network device. Both the first CSI report and the second CSI report are used for model monitoring. The network device can obtain first model monitoring performance and second model monitoring performance based on the first and second CSI reports.

In a possible implementation, the method further includes step 908: the user equipment sends fifth information to the network equipment, where the fifth information includes a third CSI report, the third CSI report is an omitted report, and the third CSI report is used for CSI feedback.

The third CSI report is used for CSI feedback. For example, when performing model inference, an AI model is used for CSI feedback so that the network device can obtain precoding for downlink transmission.

For the introduction of this part, please refer to the description of step 603 in the embodiment shown in FIG6 , which will not be repeated here.

In an embodiment of the present application, a user device transmits first information to a network device, the first information including a first CSI report. The first CSI report is an omitted report. The network device obtains recovered CSI based on the first CSI report and transmits the recovered CSI to the user device. The user device can monitor model performance based on the true CSI and the recovered CSI. This approach allows the user device to monitor the model using the omitted CSI report, thereby monitoring the model's robustness to CSI omissions.

For another example, this example introduces model performance monitoring based on a proxy model on the user equipment side. Among them, the proxy model is a model used by the user equipment side to simulate the CSI reconstructor on the network equipment side. Referring to Figure 10, it is a flow chart of another model monitoring method provided by an embodiment of the present application. Optionally, the method can be applied to the aforementioned communication system, such as the communication system shown in Figure 1. The model monitoring method shown in Figure 10 may include steps 1001-1004. It should be understood that this application is described in the order of 1001-1004 for the convenience of description, and is not intended to be limited to execution in the above order. The embodiment of the present application does not limit the order of execution, execution time, number of executions, etc. of the above one or more steps. Steps 1001-1004 are as follows:

1001. A network device sends a reference signal to a user equipment. Correspondingly, the user equipment receives the reference signal.

For the introduction of this step, please refer to the description of step 601 in the embodiment shown in FIG6 , which will not be repeated here.

1002. The user equipment obtains true CSI based on the reference signal.

Illustratively, the user equipment may obtain the true CSI by measuring the reference signal, or may obtain the true CSI by performing eigendecomposition or singular value decomposition on the measured CSI.

For the introduction of this step, please refer to the description of step 601 in the embodiment shown in FIG6 , which will not be repeated here.

1003. The user equipment obtains first recovered CSI based on a first CSI report; the first CSI report is obtained based on the true CSI, wherein the first CSI report is a complete CSI report.

Exemplarily, the user equipment obtains the first CSI report based on the true CSI, and then processes the first CSI report using a proxy model to obtain first recovered CSI. That is, unlike the examples shown in Figures 8 and 9 where the first recovered CSI is obtained based on the network device, in this example, the first recovered CSI is obtained by the user equipment using a proxy model.

In a possible implementation, the user equipment and the network device use a complete CSI report to perform model monitoring based on the protocol definition. The user equipment then obtains the first recovered CSI using the complete report.

In another possible implementation, the network device sends first indication information to the user equipment, where the first indication information indicates the use of a complete CSI report for model monitoring, or the first indication information instructs the user equipment to report model monitoring performance based on the complete CSI report. Accordingly, the user equipment receives the first indication information. Furthermore, the user equipment obtains first recovered CSI using the complete report.

For the introduction of this part, please refer to the description in the aforementioned embodiment, which will not be repeated here.

1004. The user equipment obtains a first model monitoring performance based on the true CSI and the first restored CSI.

For the introduction of this step, please refer to the description of step 603 in the embodiment shown in FIG6 , which will not be repeated here.

In one possible implementation, the user device sends the first model monitoring performance to the network device. Accordingly, the network device receives the first model monitoring performance. This allows the network device to switch to a non-AI model or replace the AI model when the AI model performance is poor.

In one possible implementation, the method also includes step 1005: the user equipment obtains a second model monitoring performance based on the true CSI and the second recovered CSI, the second recovered CSI is obtained based on a second CSI report, the second CSI report is an omitted report, and the second CSI report is obtained based on the reference signal.

In a possible implementation, the user equipment further reports the second model monitoring performance to the network device.

In a possible implementation, the method further includes step 1006: the user equipment sends first information to the network equipment, where the first information includes a third CSI report, the third CSI report is an omitted report, and the third CSI report is used for CSI feedback.

For the introduction of this part, please refer to the description of the embodiment shown in Figure 6, Figure 7, Figure 8 or Figure 9, which will not be repeated here.

In this embodiment of the present application, a user equipment (UE) obtains true CSI based on a reference signal and obtains a first CSI report based on the true CSI. This first CSI report is a complete report. The UE also obtains recovered CSI based on the first CSI report. Thus, the UE can monitor model performance based on the true CSI and the recovered CSI. This approach allows the UE to monitor model performance using the complete CSI report, eliminating the impact of omitted CSI and enabling the monitoring of model performance.

The example shown in Figure 10 is introduced by taking the first CSI report as a complete report as an example, and the following introduction is based on the first CSI report being an omitted report. Referring to Figure 11, it is a flow chart of another model monitoring method provided in an embodiment of the present application. Optionally, the method can be applied to the aforementioned communication system, such as the communication system shown in Figure 1. The model monitoring method shown in Figure 11 may include steps 1101-1104. It should be understood that for the convenience of description, this application is described in the order of 1101-1104, and is not intended to be limited to execution in the above order. The embodiment of the present application does not limit the order of execution, execution time, number of executions, etc. of the above one or more steps.

Steps 1101-1104 are as follows:

1101. A network device sends a reference signal to a user equipment. Correspondingly, the user equipment receives the reference signal.

For the introduction of this step, please refer to the description of step 601 in the embodiment shown in FIG6 , which will not be repeated here.

1102. The user equipment obtains true CSI based on the reference signal.

Illustratively, the user equipment may obtain the true CSI by measuring the reference signal, or may obtain the true CSI by performing eigendecomposition or singular value decomposition on the measured CSI.

For the introduction of this step, please refer to the description of step 601 in the embodiment shown in FIG6 , which will not be repeated here.

1103. The user equipment obtains first recovered CSI based on a first CSI report; the first CSI report is obtained based on the true CSI, wherein the first CSI report is an omitted report.

Exemplarily, the user equipment obtains a complete CSI report based on the true CSI and omits the complete CSI report to obtain the first CSI report. The user equipment then processes the first CSI report using a proxy model to obtain first recovered CSI. That is, unlike the examples shown in Figures 8 and 9 where the first recovered CSI is obtained based on the network device, in this example, the first recovered CSI is obtained by the user equipment using a proxy model.

In one possible implementation, the user equipment and the network device use the omitted CSI report to perform model monitoring based on the protocol definition. The user equipment then obtains the first recovered CSI using the omitted report.

In another possible implementation, the network device sends second indication information to the user equipment, where the second indication information instructs the user equipment to use the omitted CSI report for model monitoring, or instructs the user equipment to report model monitoring performance based on the omitted CSI report. Accordingly, the user equipment receives the second indication information. Furthermore, the user equipment obtains the first recovered CSI using the omitted report.

For the introduction of this part, please refer to the description in the aforementioned embodiment, which will not be repeated here.

1104. The user equipment obtains a first model monitoring performance based on the true CSI and the first restored CSI.

For the introduction of this step, please refer to the description of step 603 in the embodiment shown in FIG6 , which will not be repeated here.

In one possible implementation, the user device sends the first model monitoring performance to the network device. Accordingly, the network device receives the first model monitoring performance. This allows the network device to switch to a non-AI model or replace the AI model when the AI model performance is poor.

In one possible implementation, the method also includes step 1105: the user equipment obtains a second model monitoring performance based on the true CSI and the second recovered CSI, the second recovered CSI is obtained based on a second CSI report, the second CSI report is a complete report, and the second CSI report is obtained based on the reference signal.

In a possible implementation, the user equipment further reports the second model monitoring performance to the network device.

In a possible implementation, the method further includes step 1106: the user equipment sends first information to the network equipment, where the first information includes a third CSI report, the third CSI report is an omitted report, and the third CSI report is used for CSI feedback.

For the introduction of this part, please refer to the description of the embodiments shown in Figures 6, 7, 8, 9 or 10 above, and will not be repeated here.

In this embodiment of the present application, a user equipment (UE) obtains true CSI based on a reference signal and obtains a first CSI report based on the true CSI. This first CSI report is an omitted report. The UE also obtains recovered CSI based on the first CSI report. Thus, the UE can monitor model performance based on the true CSI and the recovered CSI. This approach allows the UE to monitor the model using the omitted CSI report, thereby monitoring the robustness of the model to CSI omission.

The above examples are described using the example of deploying models on both the user equipment and network equipment sides. The present application also provides a model monitoring method in which a model is deployed only on the user equipment side, for example, in scenarios such as user equipment side CSI prediction or user equipment side beam prediction. The method may include steps A11-A14, as follows:

A11. The network device sends a reference signal to the user equipment. Correspondingly, the user equipment receives the reference signal.

For the introduction of this step, please refer to the description of step 601 in the embodiment shown in FIG6 , which will not be repeated here.

A12. The user equipment obtains predicted CSI based on the reference signal.

The predicted CSI is the CSI at a future time predicted based on the current and/or past CSI.

In one possible implementation, the user equipment measures the downlink reference signal to obtain the true value CSI1, and then performs CSI prediction based on the true value CSI1 to obtain predicted CSI (as shown in Figure 12, the predicted CSI may be, for example, CSI3'). Alternatively, the user equipment measures the downlink reference signal at times t1 and t2 to obtain the true value CSI1 and the true value CSI2, respectively. The user equipment obtains predicted CSI (as shown in Figure 12, CSI3') based on the true value CSI1 and the true value CSI2. Of course, the user equipment may also perform prediction based on at least three true values of CSI, and this solution is not limited to this.

A13. The user equipment obtains a true CSI corresponding to the predicted CSI based on the reference signal.

Exemplarily, the true CSI is CSI3 in Figure 12. For example, the user equipment measures the downlink reference signal at time t3 to obtain true CSI3, which is the true CSI corresponding to the predicted CSI3'.

A14. The user equipment obtains a model monitoring performance based on a first CSI report and a true CSI corresponding to the predicted CSI. The first CSI report is an omitted report and is obtained based on the predicted CSI.

Among them, the first CSI report is used to indicate the CSI feedback corresponding to the predicted CSI (CSI3” as shown in Figure 12), and the CSI3” is the CSI represented by the CSI report corresponding to CSI3’ after being omitted. For example, CSI3” is a precoding matrix, and the first CSI report includes CSI3” or a compressed representation of CSI3”. For another example, CSI3” is a channel response, and the first CSI report includes the precoding matrix corresponding to CSI3” or a compressed representation of the precoding matrix, etc.

Exemplarily, the user equipment uses CSI3" and the true CSI (CSI3) calculation model to monitor performance, such as calculating intermediate KPIs.

In a possible implementation, the user equipment sends the first CSI report to the network device, so that the network device (such as a base station) determines downlink precoding according to the predicted CSI.

In an embodiment of the present application, a user equipment obtains predicted CSI and true CSI based on the reference signal, and then the user equipment obtains a model-monitored performance based on a first CSI report and the true CSI corresponding to the predicted CSI. The first CSI report is an omitted report, obtained based on the predicted CSI. In this way, the user equipment can monitor the actual performance corresponding to the omitted CSI report it reports, rather than directly using the predicted CSI for model monitoring. This allows the monitored performance to take into account the impact of the omitted CSI.

It should be noted that in the various embodiments of the present application, unless otherwise specified or there is a logical conflict, the terms and/or descriptions between the various embodiments are consistent and can be referenced by each other. The technical features in different embodiments can be combined to form new embodiments according to their internal logical relationships.

The above describes in detail the method of the embodiment of the present application, and the following provides the device of the embodiment of the present application. It will be understood that in the various device embodiments of the present application, the division of multiple units or modules is only a logical division based on function, and is not intended to limit the specific structure of the device. In a specific implementation, some functional modules may be subdivided into more small functional modules, and some functional modules may be combined into one functional module, but no matter whether these functional modules are subdivided or combined, the general process performed by the device is the same. For example, some devices include a receiving unit and a sending unit. In some designs, the sending unit and the receiving unit can also be integrated into a communication unit, which can implement the functions implemented by the receiving unit and the sending unit. Typically, each unit corresponds to its own program code (or program instructions), and when the program code corresponding to each of these units runs on the processor, the unit is controlled by the processing unit to execute the corresponding process to implement the corresponding function.

The embodiments of the present application also provide an apparatus for implementing any of the above methods. For example, a model monitoring apparatus is provided, which includes modules (or means) for implementing each step performed by a user equipment in any of the above methods.

For example, referring to FIG13 , which is a schematic diagram of the structure of a model monitoring device provided in an embodiment of the present application, the model monitoring device is used to implement the aforementioned model monitoring method, such as the model monitoring method shown in FIG6 and FIG7 .

As shown in FIG13 , the apparatus may include a transceiver module 1301 , specifically as follows:

The transceiver module 1301 is configured to receive a reference signal;

The transceiver module 1301 is further used to send first information and second information, where the first information includes true CSI, which is obtained based on the reference signal; and the second information includes a first CSI report, which is obtained based on the true CSI; wherein the first CSI report is a complete report, or the first CSI report is an omitted report.

In one possible implementation, the first CSI report is a complete report, and the transceiver module 1301 is further used to receive first indication information, where the first indication information indicates the use of a complete CSI report for model monitoring; or, the first indication information indicates the sending of a complete CSI report.

In a possible implementation, the transceiver module 1301 is further configured to send third information, where the third information includes a second CSI report, where the second CSI report is an omitted report, and where the second CSI report is obtained based on the reference signal.

In one possible implementation, the first CSI report is an omitted report, and the transceiver module 1301 is further used to receive second indication information, where the second indication information indicates the use of the omitted CSI report for model monitoring; or, the second indication information indicates the sending of the omitted CSI report.

In a possible implementation, the transceiver module 1301 is further configured to send fourth information, where the fourth information includes a third CSI report, where the third CSI report is an omitted report, and where the third CSI report is used for CSI feedback.

In a possible implementation manner, the first information and the second information are reported through high-layer signaling.

In a possible implementation, the transceiver module 1301 is further configured to receive fifth information, where the fifth information is configured to indicate a first resource, and the first resource is configured to transmit a complete CSI report.

In one possible implementation, the user equipment does not expect CSI omission to occur in the CSI report for model monitoring, or the user equipment does not expect the CSI report for model monitoring to be omitted, or the user equipment does not expect that resources used to transmit the CSI report for model monitoring are less than resources required for the CSI report for model monitoring.

In one possible implementation, when the first CSI report is an omitted report, or when the resources used to transmit the first CSI report are less than the resources required for the first CSI report, the transceiver module 1301 is further used to send sixth information, where the sixth information includes at least one of the size of the CSI report used for model monitoring, the size of the omitted part of the CSI report used for model monitoring, the resources required for the CSI report used for model monitoring, and the resources required for the omitted part of the CSI report used for model monitoring.

In a possible implementation, the priority of the first CSI report is higher than that of the third CSI report, or the priority of the report contents is not distinguished within the first CSI report.

For example, referring to Figure 14 , which is a schematic diagram of the structure of another model monitoring device provided in an embodiment of the present application, the model monitoring device is used to implement the aforementioned model monitoring method, such as the model monitoring method shown in Figures 8 and 9 .

As shown in FIG14 , the apparatus may include a transceiver module 1401 and a processing module 1402 , specifically as follows:

The transceiver module 1401 is configured to receive a reference signal;

The transceiver module 1401 is further configured to send first information, where the first information includes a first CSI report, where the first CSI report is obtained based on the reference signal; the first CSI report is a complete report, or the first CSI report is an omitted report;

The transceiver module 1401 is further configured to receive second information, where the second information is used to indicate first restored CSI, where the first restored CSI is obtained based on the first CSI report;

The processing module 1402 is configured to obtain a first model monitoring performance based on a true CSI and the first restored CSI, where the true CSI is obtained based on the reference signal.

In one possible implementation, the first CSI report is a complete report, and the transceiver module 1401 is further used to receive first indication information, where the first indication information indicates the use of a complete CSI report for model monitoring; or, the first indication information indicates that the user equipment sends a complete CSI report.

In a possible implementation, the transceiver module 1401 is further configured to send third information, where the third information includes a second CSI report, where the second CSI report is an omitted report, and the second CSI report is obtained based on the reference signal;

receiving fourth information, where the fourth information is used to indicate second restored CSI, where the second restored CSI is obtained based on the second CSI report;

The processing module 1402 is configured to obtain a second model monitoring performance based on the true CSI and the second restored CSI.

In one possible implementation, the first CSI report is an omitted report, and the transceiver module 1401 is further used to receive second indication information, where the second indication information indicates the use of the omitted CSI report for model monitoring; or, the second indication information instructs the user equipment to send the omitted CSI report.

In a possible implementation, the transceiver module 1401 is further configured to send fifth information, where the fifth information includes a third CSI report, where the third CSI report is an omitted report, and where the third CSI report is used for CSI feedback.

In a possible implementation manner, the first information is reported through high-layer signaling.

In a possible implementation, the transceiver module 1401 is further configured to receive sixth information, where the sixth information is configured to indicate a first resource, and the first resource is configured to transmit a complete CSI report.

In one possible implementation, the user equipment does not expect CSI omission to occur in the CSI report for model monitoring, or the user equipment does not expect the CSI report for model monitoring to be omitted, or the user equipment does not expect that resources used to transmit the CSI report for model monitoring are less than resources required for the CSI report for model monitoring.

In one possible implementation, the first CSI report is an omitted report, or when the resources used to transmit the first CSI report are less than the resources required for the first CSI report, the transceiver module 1401 is further used to send seventh information, where the seventh information includes at least one of the size of the CSI report used for model monitoring, the size of the omitted part of the CSI report used for model monitoring, the resources required for the CSI report used for model monitoring, and the resources required for the omitted part of the CSI report used for model monitoring.

In a possible implementation, the priority of the first CSI report is higher than that of the third CSI report, or the priority of the report contents is not distinguished within the first CSI report.

For example, referring to FIG14 , which is a schematic diagram of the structure of another model monitoring device provided in an embodiment of the present application, the model monitoring device is used to implement the aforementioned model monitoring method, such as the model monitoring method shown in FIG10 and FIG11 .

As shown in FIG14 , the apparatus may include a transceiver module 1401 and a processing module 1402 , specifically as follows:

The transceiver module 1401 is configured to receive a reference signal;

A processing module 1402 is configured to obtain a true CSI based on the reference signal;

The processing module 1402 is further configured to obtain first recovered CSI based on a first CSI report, wherein the first CSI report is obtained based on the true CSI, and the first CSI report is a complete CSI report or an omitted CSI report.

The processing module 1402 is further configured to obtain a first model monitoring performance based on the true CSI and the first restored CSI.

In one possible implementation, the first CSI report is a complete report, and the transceiver module 1401 is further used to receive first indication information, where the first indication information indicates the use of a complete CSI report for model monitoring; or, the first indication information indicates that the user equipment sends a complete CSI report.

In one possible implementation, the processing module 1402 is further used to obtain a second model monitoring performance based on the true CSI and the second recovered CSI, where the second recovered CSI is obtained based on a second CSI report, the second CSI report is an omitted report, and the second CSI report is obtained based on the reference signal.

In one possible implementation, the first CSI report is an omitted report, and the transceiver module 1401 is further used to receive second indication information, where the second indication information indicates the use of the omitted CSI report for model monitoring; or, the second indication information indicates that the user equipment sends the omitted CSI report.

In a possible implementation, the transceiver module 1401 is further configured to send first information, where the first information includes a third CSI report, where the third CSI report is an omitted report, and where the third CSI report is used for CSI feedback.

An embodiment of the present application further provides a model monitoring device including modules (or means) for implementing each step performed by the network device in any of the above methods.

For example, referring to FIG14 , which is a schematic diagram of the structure of another model monitoring device provided in an embodiment of the present application, the model monitoring device is used to implement the aforementioned model monitoring method, such as the model monitoring method shown in FIG6 and FIG7 .

As shown in FIG14 , the apparatus may include a transceiver module 1401 and a processing module 1402 , specifically as follows:

The transceiver module 1401 is configured to send a reference signal;

The transceiver module 1401 is further configured to receive first information and second information, where the first information includes true CSI, where the true CSI is obtained based on the reference signal; and the second information includes a first CSI report, where the first CSI report is obtained based on the true CSI. The first CSI report is a complete report, or an omitted report.

The processing module 1402 is configured to obtain a first model monitoring performance based on the first information and the second information.

In one possible implementation, the first CSI report is a complete report, and the transceiver module 1401 is further used to send first indication information, where the first indication information indicates the use of a complete CSI report for model monitoring; or, the first indication information instructs the user equipment to send a complete CSI report.

In a possible implementation, the transceiver module 1401 is further configured to receive third information, where the third information includes a second CSI report, where the second CSI report is an omitted report, and the second CSI report is obtained based on the reference signal;

The processing module 1402 is configured to obtain a second model monitoring performance based on the third information and the true CSI.

In one possible implementation, the first CSI report is an omitted report, and the transceiver module 1401 is further used to send second indication information, where the second indication information indicates the use of the omitted CSI report for model monitoring; or, the second indication information instructs the user equipment to send the omitted CSI report.

In a possible implementation, the transceiver module 1401 is further configured to receive fourth information, where the fourth information includes a third CSI report, where the third CSI report is an omitted report, and where the third CSI report is used for CSI feedback.

In a possible implementation manner, the first information and the second information are reported through high-layer signaling.

In a possible implementation, the transceiver module 1401 is further configured to send fifth information, where the fifth information is used to indicate a first resource, and the first resource is used to transmit a complete CSI report.

In one possible implementation, the user equipment does not expect CSI omission to occur in the CSI report for model monitoring, or the user equipment does not expect the CSI report for model monitoring to be omitted, or the user equipment does not expect that resources used to transmit the CSI report for model monitoring are less than resources required for the CSI report for model monitoring.

In one possible implementation, when the first CSI report is an omitted report, or when the resources used to transmit the first CSI report are less than the resources required for the first CSI report, the transceiver module 1401 is further used to receive sixth information, where the sixth information includes at least one of the size of the CSI report used for model monitoring, the size of the omitted portion of the CSI report used for model monitoring, the resources required for the CSI report used for model monitoring, and the resources required for the omitted portion of the CSI report used for model monitoring.

In a possible implementation, the priority of the first CSI report is higher than that of the third CSI report, or the priority of the report contents is not distinguished within the first CSI report.

For example, referring to Figure 13 , which is a schematic diagram of the structure of another model monitoring device provided in an embodiment of the present application, the model monitoring device is used to implement the aforementioned model monitoring method, such as the model monitoring method shown in Figures 8 and 9 .

As shown in FIG13 , the apparatus may include a transceiver module 1301 , specifically as follows:

The transceiver module 1301 is configured to send a reference signal;

The transceiver module 1301 is further configured to receive first information, where the first information includes a first CSI report, where the first CSI report is obtained based on the reference signal; the first CSI report is a complete report, or the first CSI report is an omitted report;

The transceiver module 1301 is further configured to send second information, where the second information is used to indicate first restored CSI, where the first restored CSI is obtained based on the first CSI report.

In one possible implementation, the first CSI report is a complete report, and the transceiver module 1301 is further used to send first indication information, where the first indication information indicates the use of a complete CSI report for model monitoring; or, the first indication information instructs the user equipment to send a complete CSI report.

In a possible implementation, the transceiver module 1301 is further configured to receive third information, where the third information includes a second CSI report, where the second CSI report is an omitted report and is obtained based on the reference signal;

Send fourth information, where the fourth information is used to indicate second restored CSI, where the second restored CSI is obtained based on the second CSI report.

In one possible implementation, the first CSI report is an omitted report, and the transceiver module 1301 is further used to send second indication information, where the second indication information indicates the use of the omitted CSI report for model monitoring; or, the second indication information instructs the user equipment to send the omitted CSI report.

In a possible implementation, the transceiver module 1301 is further configured to receive fifth information, where the fifth information includes a third CSI report, where the third CSI report is an omitted report, and where the third CSI report is used for CSI feedback.

In a possible implementation manner, the first information is reported through high-layer signaling.

In a possible implementation, the transceiver module 1301 is further configured to send sixth information, where the sixth information is used to indicate a first resource, and the first resource is used to transmit a complete CSI report.

In one possible implementation, the user equipment does not expect CSI omission to occur in the CSI report for model monitoring, or the user equipment does not expect the CSI report for model monitoring to be omitted, or the user equipment does not expect that resources used to transmit the CSI report for model monitoring are less than resources required for the CSI report for model monitoring.

In one possible implementation, when the first CSI report is an omitted report, or when the resources used to transmit the first CSI report are less than the resources required for the first CSI report, the transceiver module 1301 is further used to receive seventh information, where the seventh information includes at least one of the size of the CSI report used for model monitoring, the size of the omitted portion of the CSI report used for model monitoring, the resources required for the CSI report used for model monitoring, and the resources required for the omitted portion of the CSI report used for model monitoring.

In a possible implementation, the priority of the first CSI report is higher than that of the third CSI report, or the priority of the report contents is not distinguished within the first CSI report.

For example, referring to FIG13 , which is a schematic diagram of the structure of another model monitoring device provided in an embodiment of the present application, the model monitoring device is used to implement the aforementioned model monitoring method, such as the model monitoring method shown in FIG10 and FIG11 .

As shown in FIG13 , the apparatus may include a transceiver module 1301 , specifically as follows:

The transceiver module 1301 is configured to send a reference signal;

The transceiver module 1301 is also used to receive a first model monitoring performance, where the first model monitoring performance is obtained based on the true CSI and a first recovered CSI, where the first recovered CSI is obtained based on a first CSI report, where the first CSI report is obtained based on the true CSI, and where the true CSI is obtained based on the reference signal; wherein the first CSI report is a complete CSI report, or the first CSI report is an omitted report.

In one possible implementation, the first CSI report is a complete report, and the transceiver module 1301 is further used to send first indication information, where the first indication information indicates the use of a complete CSI report for model monitoring; or, the first indication information indicates that the user equipment sends a complete CSI report.

In one possible implementation, the first CSI report is an omitted report, and the transceiver module 1301 is further used to send second indication information, where the second indication information indicates the use of the omitted CSI report for model monitoring; or, the second indication information instructs the user equipment to send the omitted CSI report.

In a possible implementation, the transceiver module 1301 is further configured to receive first information, where the first information includes a third CSI report, where the third CSI report is an omitted report, and where the third CSI report is used for CSI feedback.

The introduction of the above modules can be found in the description of the aforementioned embodiments and will not be repeated here.

It should be understood that the division of the modules in the above devices is only a division of logical functions. In actual implementation, they can be fully or partially integrated into a physical entity, or they can be physically separated. In addition, the modules in the model monitoring device can be implemented in the form of a processor calling software; for example, the model monitoring device includes a processor, the processor is connected to a memory, and the memory stores instructions. The processor calls the instructions stored in the memory to implement any of the above methods or realize the functions of the modules of the device, wherein the processor is, for example, a general-purpose processor, such as a central processing unit (CPU) or a microprocessor, and the memory is a memory within the device or a memory outside the device. Alternatively, the modules in the device may be implemented in the form of hardware circuits, and the functions of some or all of the units may be implemented by designing the hardware circuits. The hardware circuits may be understood as one or more processors. For example, in one implementation, the hardware circuit is an application-specific integrated circuit (ASIC), and the functions of some or all of the above units may be implemented by designing the logical relationships between the components within the circuit. For another example, in another implementation, the hardware circuit may be implemented by a programmable logic device (PLD). For example, a field programmable gate array (FPGA) may include a large number of logic gate circuits, and the connection relationships between the logic gate circuits may be configured through configuration files, thereby implementing the functions of some or all of the above units. All modules of the above devices may be implemented entirely by a processor calling software, or entirely by a hardware circuit, or partially by a processor calling software, with the remaining portion implemented by a hardware circuit.

FIG15 is a schematic diagram illustrating the hardware structure of another model monitoring device provided in an embodiment of the present application. The model monitoring device 1500 shown in FIG15 includes one or more processing circuits 1501 (one processing circuit is illustrated in the figure). The processing circuit 1501 may be one or more processors, or a processing circuit within one or more processors.

Optionally, the model monitoring device 1500 may further include a transceiver circuit 1502 (indicated by a dotted line in the figure). The processing circuit 1501 and the transceiver circuit 1502 are coupled to each other. The transceiver circuit 1502 may be a transceiver or an interface circuit. For example, when the device 1500 is a network device, a terminal device, a core network device, or an AI entity, the transceiver circuit 1502 may be a transceiver or an interface circuit; when the device 1500 is a chip for a network device, a terminal device, a core network device, or an AI entity, the transceiver circuit 1502 may be an interface circuit. For example, the AI entity may be a third-party device, such as an OTT, or a cloud server.

Optionally, the model monitoring device 1500 may further include a memory 1503 (indicated by a dotted line in the figure). The memory 1503 is used to store instructions executed by the processing circuit 1501, or to store input data required by the processing circuit 1501 to execute instructions, or to store data generated after the processing circuit 1501 executes instructions.

Optionally, the memory 1503 may be located in the one or more processors, or located outside the one or more processors, or may include a storage part located in the one or more processors and a storage part located outside the one or more processors.

Memory 1503 can be a read-only memory (ROM), a static storage device, a dynamic storage device or a random access memory (RAM).

The memory 1503 can store programs. When the program stored in the memory 1503 is executed by the processing circuit 1501, the processing circuit 1501 and the transceiver circuit 1502 are used to execute the various steps of the model monitoring method of the embodiment of the present application.

The processing circuit 1501 is a circuit capable of processing signals. In one implementation, the processing circuit 1501 may be a circuit capable of reading and executing instructions, such as one or more of the following processors: a central processing unit (CPU), a microprocessor, a graphics processing unit (GPU) (which can be understood as a microprocessor), or a digital signal processor (DSP), or a processing circuit in the aforementioned processors. In another implementation, the processing circuit 1501 may implement certain functions through the logical relationship of a hardware circuit, and the logical relationship of the hardware circuit is fixed or reconfigurable. For example, the processing circuit 1501 is one or more of the following processors: a hardware circuit implemented by an ASIC or a programmable logic device (PLD), such as an FPGA or a processing circuit in the aforementioned processor. In a reconfigurable hardware circuit, the process of the processor loading a configuration document to implement the hardware circuit configuration can be understood as the process of the processor loading instructions to implement the functions of some or all of the above modules. Alternatively, it may be a hardware circuit designed for artificial intelligence, which can be understood as an ASIC or a processing circuit within an ASIC, such as one or more of the following processors: a neural network processing unit (NPU), a tensor processing unit (TPU), a deep learning processing unit (DPU), or the processing circuits within the aforementioned processors. Processing circuit 1501 is used to execute relevant programs to implement the functions required to be performed by the units in the model monitoring device of the embodiment of the present application, or to execute the model monitoring method of the method embodiment of the present application.

It can be seen that each module in the above device can be one or more processors (or processing circuits) configured to implement the above method, such as: CPU, GPU, NPU, TPU, DPU, microprocessor, DSP, ASIC, FPGA, or a combination of at least two of these processor forms or part of the processing circuits in these processors.

In addition, the modules in the above device can be fully or partially integrated together, or can be implemented independently. In one implementation, these modules are integrated together and implemented in the form of a system-on-a-chip (SOC). The SOC may include at least one processor for implementing any of the above methods or implementing the functions of the modules of the device. The type of the at least one processor can be different, for example, including a CPU and FPGA, a CPU and an artificial intelligence processor, a CPU and a GPU, etc.

The transceiver circuit 1502 uses a transceiver device such as, but not limited to, a transceiver to implement communication between the apparatus 1500 and other devices or a communication network. For example, information can be obtained through the transceiver circuit 1502.

It should be noted that although the device 1500 shown in FIG15 only shows a processing circuit, a transceiver circuit, and a memory, during the specific implementation process, those skilled in the art will understand that the device 1500 also includes other components necessary for normal operation. At the same time, according to specific needs, those skilled in the art will understand that the device 1500 may also include hardware components that implement other additional functions. Furthermore, those skilled in the art will understand that the device 1500 may also include only the components necessary to implement the embodiments of the present application, and does not necessarily include all of the components shown in FIG15.

An embodiment of the present application also provides a computer-readable storage medium, which stores instructions. When the computer-readable storage medium is executed on a computer or a processor, the computer or processor executes one or more steps in any of the above methods.

The present application also provides a computer program product comprising instructions, which, when executed on a computer or processor, causes the computer or processor to execute one or more steps in any of the above methods.

It should be understood that in the description of this application, unless otherwise specified, "/" indicates that the objects associated with each other are in an "or" relationship. For example, A/B can mean A or B, where A and B can be singular or plural. Furthermore, in the description of this application, unless otherwise specified, "multiple" means two or more than two. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, or c can mean: a, b, c, a-b, a-c, b-c, or a-b-c, where a, b, and c can be single or plural. In addition, to facilitate the clear description of the technical solutions of the embodiments of this application, the words "first" and "second" are used in the embodiments of this application to distinguish between identical or similar items with substantially the same functions and effects. Those skilled in the art will understand that the words "first" and "second" do not limit the quantity or execution order, and the words "first" and "second" do not necessarily mean different. At the same time, in the embodiments of this application, words such as "exemplary" or "for example" are used to indicate examples, illustrations, or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of this application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Rather, the use of words such as "exemplary" or "for example" is intended to present the relevant concepts in a concrete manner to facilitate understanding.

In the several embodiments provided in this application, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. For example, the division of the units is only a logical function division, and there may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. The mutual coupling, direct coupling, or communication connection shown or discussed can be through some interface, indirect coupling or communication connection of devices or units, and can be electrical, mechanical or other forms.

Units described as separate components may or may not be physically separate, and components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function according to the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted through the computer-readable storage medium. The computer instructions can be transmitted from one website, computer, server or data center to another website, computer, server or data center by wired (such as coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (such as infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that includes one or more available media integrated. The available medium can be a read-only memory (ROM), or a random access memory (RAM), or a magnetic medium, such as a floppy disk, a hard disk, a tape, a disk, or an optical medium, such as a digital versatile disc (DVD), or a semiconductor medium, such as a solid state disk (SSD), etc.

The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions within the technical scope disclosed in the present invention should be included in the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be based on the scope of protection of the claims.

Claims (46)

A model monitoring method, characterized by comprising: receiving a reference signal; Sending first information and second information, where the first information includes true CSI, where the true CSI is obtained based on the reference signal, and the second information includes a first CSI report, where the first CSI report is obtained based on the true CSI; wherein the first CSI report is a complete report or an omitted report. The method according to claim 1, wherein the first CSI report is a complete report, and the method further comprises: First indication information is received, where the first indication information indicates using a complete CSI report for model monitoring; or, the first indication information indicates sending a complete CSI report. The method according to claim 2, further comprising: Third information is sent, where the third information includes a second CSI report, where the second CSI report is an omitted report, and where the second CSI report is obtained based on the reference signal. The method according to claim 1, wherein the first CSI report is an omitted report, and the method further comprises: Second indication information is received, where the second indication information indicates using the omitted CSI report for model monitoring; or, the second indication information indicates sending the omitted CSI report. The method according to any one of claims 1 to 4, characterized in that the method further comprises: Fourth information is sent, where the fourth information includes a third CSI report, where the third CSI report is an omitted report, and where the third CSI report is used for CSI feedback. The method according to claim 5, characterized in that the first information and the second information are reported through high-layer signaling. The method according to any one of claims 1 to 3, characterized in that the method further comprises: Fifth information is received, where the fifth information is used to indicate a first resource, where the first resource is used to transmit a complete CSI report. The method according to any one of claims 1 to 3, characterized in that the user equipment does not expect CSI omission to occur in the CSI report for model monitoring, or the user equipment does not expect the CSI report for model monitoring to be omitted, or the user equipment does not expect that resources used to transmit the CSI report for model monitoring are less than resources required for the CSI report for model monitoring. The method according to any one of claims 1 to 3, 7 or 8, characterized in that when the CSI report for model monitoring is omitted, or the resources used to transmit the CSI report for model monitoring are less than the resources required for the CSI report for model monitoring, the method further comprises: Send sixth information, where the sixth information includes at least one of the size of the CSI report for model monitoring, the size of the portion omitted from the CSI report for model monitoring, the resources required for the CSI report for model monitoring, and the resources required for the portion omitted from the CSI report for model monitoring. The method according to claim 5 or 6 is characterized in that the priority of the first CSI report is higher than that of the third CSI report, or that the priority between report contents is not distinguished within the first CSI report. A model monitoring method, characterized by comprising: Sending a reference signal; receiving first information and second information, where the first information includes true CSI, the true CSI being obtained based on the reference signal, and the second information includes a first CSI report, the first CSI report being obtained based on the true CSI; wherein the first CSI report is a complete report or an omitted report; A first model monitoring performance is obtained based on the first information and the second information. The method according to claim 11, wherein the first CSI report is a complete report, and the method further comprises: Sending first indication information, where the first indication information indicates using a complete CSI report for model monitoring; or, the first indication information instructs the user equipment to send a complete CSI report. The method according to claim 12, further comprising: receiving third information, where the third information includes a second CSI report, where the second CSI report is an omitted report, and where the second CSI report is obtained based on the reference signal; A second model monitoring performance is obtained based on the third information and the true CSI. The method according to claim 11, wherein the first CSI report is an omitted report, and the method further comprises: Sending second indication information, where the second indication information instructs the user equipment to use the omitted CSI report for model monitoring; or, the second indication information instructs the user equipment to send the omitted CSI report. The method according to any one of claims 11 to 14, further comprising: Fourth information is received, where the fourth information includes a third CSI report, where the third CSI report is an omitted report, and where the third CSI report is used for CSI feedback. The method according to claim 15 is characterized in that the first information and the second information are reported through high-layer signaling. The method according to any one of claims 11 to 13, characterized in that the method further comprises: Fifth information is sent, where the fifth information is used to indicate a first resource, and the first resource is used to transmit a complete CSI report. The method according to any one of claims 11 to 13 and 17 is characterized in that the user equipment does not expect CSI omission to occur in the CSI report for model monitoring, or the user equipment does not expect the CSI report for model monitoring to be omitted, or the user equipment does not expect that the resources used to transmit the CSI report for model monitoring are less than the resources required for the CSI report for model monitoring. The method according to any one of claims 11 to 13, 17 or 18, characterized in that when the CSI report for model monitoring is omitted, or the resources used to transmit the CSI report for model monitoring are less than the resources required for the CSI report for model monitoring, the method further comprises: Receive sixth information, where the sixth information includes at least one of a size of a CSI report for model monitoring, a size of a portion omitted from the CSI report for model monitoring, resources required for the CSI report for model monitoring, and resources required for the portion omitted from the CSI report for model monitoring. The method according to claim 15 or 16 is characterized in that the priority of the first CSI report is higher than that of the third CSI report, or the priority between report contents is not distinguished within the first CSI report. A model monitoring method, characterized by comprising: receiving a reference signal; sending first information, where the first information includes a first CSI report, where the first CSI report is obtained based on the reference signal; the first CSI report is a complete report, or the first CSI report is an omitted report; receiving second information indicating first recovered CSI, where the first recovered CSI is obtained based on the first CSI report; A first model monitoring performance is obtained based on the true CSI and the first restored CSI, where the true CSI is obtained based on the reference signal. The method according to claim 21, wherein the first CSI report is a complete report, and the method further comprises: First indication information is received, where the first indication information indicates using a complete CSI report for model monitoring; or, the first indication information indicates that the user equipment sends a complete CSI report. The method according to claim 22, further comprising: sending third information, where the third information includes a second CSI report, where the second CSI report is an omitted report, and where the second CSI report is obtained based on the reference signal; receiving fourth information, where the fourth information is used to indicate second restored CSI, where the second restored CSI is obtained based on the second CSI report; A second model monitoring performance is obtained based on the true CSI and the second restored CSI. The method according to claim 21, wherein the first CSI report is an omitted report, and the method further comprises: Second indication information is received, where the second indication information indicates using the omitted CSI report for model monitoring; or, the second indication information instructs the user equipment to send the omitted CSI report. The method according to any one of claims 21 to 24, further comprising: Fifth information is sent, where the fifth information includes a third CSI report, where the third CSI report is an omitted report, and where the third CSI report is used for CSI feedback. A model monitoring method, characterized by comprising: Sending a reference signal; receiving first information, where the first information includes a first CSI report, where the first CSI report is obtained based on the reference signal; the first CSI report is a complete report, or the first CSI report is an omitted report; Second information is sent, where the second information is used to indicate first restored CSI, where the first restored CSI is obtained based on the first CSI report. The method according to claim 26, wherein the first CSI report is a complete report, and the method further comprises: Sending first indication information, where the first indication information indicates using a complete CSI report for model monitoring; or, the first indication information instructs the user equipment to send a complete CSI report. The method according to claim 27, further comprising: receiving third information, where the third information includes a second CSI report, where the second CSI report is an omitted report, and where the second CSI report is obtained based on the reference signal; Send fourth information, where the fourth information is used to indicate second restored CSI, where the second restored CSI is obtained based on the second CSI report. The method according to claim 26, wherein the first CSI report is an omitted report, and the method further comprises: Sending second indication information, where the second indication information instructs the user equipment to use the omitted CSI report for model monitoring; or, the second indication information instructs the user equipment to send the omitted CSI report. The method according to any one of claims 26 to 29, further comprising: Fifth information is received, where the fifth information includes a third CSI report, where the third CSI report is an omitted report, and where the third CSI report is used for CSI feedback. A model monitoring method, characterized by comprising: receiving a reference signal; Obtaining a true CSI based on the reference signal; Obtaining first recovered CSI based on a first CSI report; wherein the first CSI report is obtained based on the true CSI, and the first CSI report is a complete CSI report, or the first CSI report is an omitted report; A first model monitoring performance is obtained based on the true CSI and the first restored CSI. The method according to claim 31, wherein the first CSI report is a complete report, and the method further comprises: First indication information is received, where the first indication information indicates using a complete CSI report for model monitoring; or, the first indication information indicates that the user equipment sends a complete CSI report. The method according to claim 32, further comprising: A second model monitoring performance is obtained based on the true CSI and a second restored CSI, where the second restored CSI is obtained based on a second CSI report, where the second CSI report is an omitted report, and where the second CSI report is obtained based on the reference signal. The method according to claim 31, wherein the first CSI report is an omitted report, and the method further comprises: Second indication information is received, where the second indication information indicates using the omitted CSI report for model monitoring; or, the second indication information instructs the user equipment to send the omitted CSI report. The method according to any one of claims 31 to 34, further comprising: First information is sent, where the first information includes a third CSI report, where the third CSI report is an omitted report, and where the third CSI report is used for CSI feedback. A model monitoring method, characterized by comprising: Sending a reference signal; Receive a first model monitoring performance, where the first model monitoring performance is obtained based on a true CSI and a first recovered CSI, where the first recovered CSI is obtained based on a first CSI report, where the first CSI report is obtained based on the true CSI, and where the true CSI is obtained based on the reference signal; wherein the first CSI report is a complete CSI report, or the first CSI report is an omitted report. The method according to claim 36, wherein the first CSI report is a complete report, and the method further comprises: Sending first indication information, where the first indication information indicates using a complete CSI report for model monitoring; or, the first indication information instructs the user equipment to send a complete CSI report. The method according to claim 36, wherein the first CSI report is an omitted report, and the method further comprises: Sending second indication information, where the second indication information instructs the user equipment to use the omitted CSI report for model monitoring; or, the second indication information instructs the user equipment to send the omitted CSI report. The method according to any one of claims 36 to 38, further comprising: First information is received, where the first information includes a third CSI report, where the third CSI report is an omitted report, and where the third CSI report is used for CSI feedback. A model monitoring device, characterized in that it includes a module or unit for implementing the method according to any one of claims 1 to 10, or includes a module or unit for implementing the method according to any one of claims 11 to 20, or includes a module or unit for implementing the method according to any one of claims 21 to 25, or includes a module or unit for implementing the method according to any one of claims 26 to 30, or includes a module or unit for implementing the method according to any one of claims 31 to 35, or includes a module or unit for implementing the method according to any one of claims 36 to 39. A model monitoring device, characterized in that the device includes a processor, and the processor is used to cause the device to perform the method according to any one of claims 1 to 10, or the method according to any one of claims 21 to 25, or the method according to any one of claims 31 to 35 by executing a computer program (or computer-executable instructions) stored in a memory and/or through a logic circuit. A model monitoring device, characterized in that the device includes a processor, and the processor is used to cause the device to perform the method according to any one of claims 11 to 20, or the method according to any one of claims 26 to 30, or the method according to any one of claims 36 to 39 by executing a computer program (or computer-executable instructions) stored in a memory and/or through a logic circuit. The device according to claim 41 or 42 is characterized in that it also includes the memory. A model monitoring system, characterized in that the system includes the model monitoring device as described in claim 41 and the model monitoring device as described in claim 42. A computer-readable storage medium, characterized in that a computer program is stored therein, and when the computer program is executed by a processor, the method according to any one of claims 1 to 10 is implemented; or the method according to any one of claims 11 to 20 is implemented; or the method according to any one of claims 21 to 25 is implemented; or the method according to any one of claims 26 to 30 is implemented; or the method according to any one of claims 31 to 35 is implemented; or the method according to any one of claims 36 to 39 is implemented. A computer program product comprising instructions which, when executed on a processor, causes the method according to any one of claims 1 to 10 to be implemented; or causes the method according to any one of claims 11 to 20 to be implemented; or causes the method according to any one of claims 21 to 25 to be implemented; or causes the method according to any one of claims 26 to 30 to be implemented; or causes the method according to any one of claims 31 to 35 to be implemented; or causes the method according to any one of claims 36 to 39 to be implemented.