Wireless communication method, terminal device, and network device

Abstract

Provided are a wireless communication method, a terminal device, and a network device. The wireless communication method comprises: a terminal device sends first information or a first report to a network device, the first report being used for determining the first information, and the first information being used for indicating the accuracy of downlink reference signal resource prediction, wherein the accuracy of downlink reference signal resource prediction is determined on the basis of K downlink reference signal resources in a predicted resource set and M downlink reference signal resources in a monitored resource set, K is greater than or equal to 1, and M is greater than or equal to 1; and prediction results of the K downlink reference signal resources are higher than or equal to prediction results of the remaining downlink reference signal resources in the predicted resource set, and measurement results of the M downlink reference signal resources are higher than or equal to measurement results of the remaining downlink reference signal resources in the monitored resource set.

Description

Wireless communication methods, terminal devices, and network devices Technical Field

[0001] This application relates to the field of communication technology, and more specifically, to a wireless communication method, terminal device, and network device. Background Technology

[0002] To reduce the measurement burden on terminal devices, some communication systems (such as new radio (NR) systems) have introduced beam management mechanisms based on artificial intelligence (AI) / machine learning (ML). In AI / ML-based beam management scenarios, how to monitor the performance of AI / ML-based beam prediction models has become a pressing issue. Summary of the Invention

[0003] This application provides a wireless communication method, terminal device, and network device. The various aspects covered by this application are described below.

[0004] In a first aspect, a wireless communication method is provided, comprising: a terminal device sending first information or a first report to a network device, the first report being used to determine the first information, the first information being used to indicate the accuracy of downlink reference signal resource prediction; wherein the accuracy of the downlink reference signal resource prediction is determined based on K downlink reference signal resources in a prediction resource set and M downlink reference signal resources in a monitoring resource set, K being greater than or equal to 1, M being greater than or equal to 1, the prediction results of the K downlink reference signal resources being higher than or equal to the prediction results of other downlink reference signal resources in the prediction resource set, and the measurement results of the M downlink reference signal resources being higher than or equal to the measurement results of other downlink reference signal resources in the monitoring resource set.

[0005] In a second aspect, a wireless communication method is provided, comprising: a network device receiving first information or a first report sent by a terminal device, the first report being used to determine the first information, the first information being used to indicate the accuracy of downlink reference signal resource prediction; wherein the accuracy of the downlink reference signal resource prediction is determined based on K downlink reference signal resources in a prediction resource set and M downlink reference signal resources in a monitoring resource set, K being greater than or equal to 1, M being greater than or equal to 1, the prediction results of the K downlink reference signal resources being higher than or equal to the prediction results of other downlink reference signal resources in the prediction resource set, and the measurement results of the M downlink reference signal resources being higher than or equal to the measurement results of other downlink reference signal resources in the monitoring resource set.

[0006] Thirdly, a terminal device is provided, comprising: a transmitting module, configured to transmit first information or a first report to a network device, wherein the first report is configured to determine the first information, and the first information is configured to indicate the accuracy of downlink reference signal resource prediction; wherein the accuracy of the downlink reference signal resource prediction is determined based on K downlink reference signal resources in a prediction resource set and M downlink reference signal resources in a monitoring resource set, where K is greater than or equal to 1, M is greater than or equal to 1, the prediction results of the K downlink reference signal resources are higher than or equal to the prediction results of other downlink reference signal resources in the prediction resource set, and the measurement results of the M downlink reference signal resources are higher than or equal to the measurement results of other downlink reference signal resources in the monitoring resource set.

[0007] Fourthly, a network device is provided, comprising: a receiving module, configured to receive first information or a first report sent by a terminal device, wherein the first report is configured to determine the first information, and the first information is configured to indicate the accuracy of downlink reference signal resource prediction; wherein the accuracy of the downlink reference signal resource prediction is determined based on K downlink reference signal resources in a prediction resource set and M downlink reference signal resources in a monitoring resource set, wherein K is greater than or equal to 1, M is greater than or equal to 1, the prediction results of the K downlink reference signal resources are higher than or equal to the prediction results of other downlink reference signal resources in the prediction resource set, and the measurement results of the M downlink reference signal resources are higher than or equal to the measurement results of other downlink reference signal resources in the monitoring resource set.

[0008] Fifthly, a terminal device is provided, including a processor, a memory, and a communication interface, wherein the memory is used to store one or more computer programs, and the processor is used to invoke the computer programs in the memory to cause the terminal device to perform some or all of the steps in the method of the first aspect.

[0009] In a sixth aspect, a network device is provided, including a processor, a memory, and a communication interface, wherein the memory is used to store one or more computer programs, and the processor is used to invoke the computer programs in the memory to cause the network device to perform some or all of the steps in the method of the second aspect.

[0010] Seventhly, embodiments of this application provide a communication system including the aforementioned terminal device and / or network device. In another possible design, the system may further include other devices that interact with the terminal device or network device as described in the embodiments of this application.

[0011] Eighthly, embodiments of this application provide a computer-readable storage medium storing a computer program that causes a computer to perform some or all of the steps in the methods described above.

[0012] Ninthly, embodiments of this application provide a computer program product, wherein the computer program product includes a non-transitory computer-readable storage medium storing a computer program operable to cause a computer to perform some or all of the steps of the methods described in the foregoing aspects. In some implementations, the computer program product may be a software installation package.

[0013] In a tenth aspect, embodiments of this application provide a chip including a memory and a processor, the processor being able to call and run a computer program from the memory to implement some or all of the steps described in the methods of the foregoing aspects.

[0014] In this embodiment, the accuracy of downlink reference signal resource (i.e., beam) prediction can be determined based on the top K best downlink reference signal resources in the prediction resource set and the top M best downlink reference signal resources in the monitoring resource set. In this way, this embodiment can monitor the performance of the beam prediction model by monitoring the accuracy of the downlink reference signal resource prediction, thereby facilitating better utilization of the beam prediction model for beam management. Attached Figure Description

[0015] Figure 1 is a system architecture example diagram of a wireless communication system applicable to embodiments of this application.

[0016] Figure 2 is an example diagram of a beam prediction model.

[0017] Figure 3 is another example diagram of the beam prediction model.

[0018] Figure 4 is an example diagram of the measurement window and prediction window in a time-domain beam prediction scenario.

[0019] Figure 5 is a flowchart illustrating a wireless communication method provided in an embodiment of this application.

[0020] Figure 6 is a schematic diagram of determining whether a downlink reference signal is quasi-co-located according to an embodiment of this application.

[0021] Figure 7 is a schematic diagram of determining whether a downlink reference signal has a quasi-co-addressable source, provided in an embodiment of this application.

[0022] Figure 8 is a flowchart illustrating a wireless communication method provided in another embodiment of this application.

[0023] Figure 9 is a schematic diagram of the relationship between the prediction time and the performance monitoring time provided in the embodiments of this application.

[0024] Figure 10 is a schematic diagram of the structure of the terminal device provided in an embodiment of this application.

[0025] Figure 11 is a schematic diagram of the network device provided in an embodiment of this application.

[0026] Figure 12 is a schematic structural diagram of the communication device provided in an embodiment of this application. Detailed Implementation

[0027] Communication system architecture

[0028] Figure 1 is a system architecture example diagram of a wireless communication system 100 to which embodiments of this application can be applied. The wireless communication system 100 may include a network device 110 and a terminal device 120. The network device 110 may be a device that communicates with the terminal device 120. The network device 110 may provide communication coverage for a specific geographical area and may communicate with the terminal device 120 located within that coverage area.

[0029] Figure 1 illustrates an exemplary network device and two terminal devices. Optionally, the wireless communication system 100 may include multiple network devices, and each network device may include other numbers of terminal devices within its coverage area. This application embodiment does not limit this.

[0030] Optionally, the wireless communication system 100 may also include other network entities such as a network controller and a mobility management entity, which is not limited in this embodiment.

[0031] It should be understood that the technical solutions of the embodiments of this application can be applied to various communication systems, such as: 5th generation (5G) systems or new radio (NR), long term evolution (LTE) systems, LTE frequency division duplex (FDD) systems, LTE time division duplex (TDD) systems, etc. The technical solutions provided in this application can also be applied to future communication systems, such as 6th generation mobile communication systems, satellite communication systems, and so on.

[0032] The terminal device in this application embodiment can also be referred to as user equipment (UE), access terminal, user unit, user station, mobile station, mobile station (MS), mobile terminal (MT), remote station, remote terminal, mobile device, user terminal, terminal, wireless communication device, user agent, or user device. The terminal device in this application embodiment can be a device that provides voice and / or data connectivity to a user, and can be used to connect people, objects, and machines, such as a handheld device with wireless connectivity, vehicle-mounted device, etc. The terminal devices in the embodiments of this application can be mobile phones, tablets, laptops, PDAs, mobile internet devices (MIDs), wearable devices, virtual reality (VR) devices, augmented reality (AR) devices, wireless terminals in industrial control, self-driving, remote medical surgery, smart grids, transportation safety, smart cities, and smart homes, etc. Optionally, the UE can act as a base station. For example, the UE can act as a scheduling entity, providing sidelink signals between UEs in V2X or D2D, etc. For example, cellular phones and cars communicate with each other using sidelink signals. Cellular phones and smart home devices communicate without relaying communication signals through a base station.

[0033] The network device in this application embodiment can be a device used to communicate with a terminal device. This network device can also be called an access network device or a wireless access network device, such as a base station. In this application embodiment, the network device can refer to a radio access network (RAN) node (or device) that connects the terminal device to the wireless network. A base station can broadly encompass, or be replaced by, various names including: NodeB, evolved NodeB (eNB), next-generation NodeB (gNB), relay station, transmitting and receiving point (TRP), transmitting point (TP), master MeNB, auxiliary SeNB, multi-mode radio (MSR) node, home base station, network controller, access node, wireless node, access point (AP), transmission node, transceiver node, baseband unit (BBU), remote radio unit (RRU), active antenna unit (AAU), remote radio head (RRH), central unit (CU), distributed unit (DU), positioning node, etc. A base station can be a macro base station, micro base station, relay node, donor node, or similar, or a combination thereof. A base station can also refer to a communication module, modem, or chip installed within the aforementioned equipment or apparatus. Base stations can also be mobile switching centers, devices that perform base station functions in device-to-device (D2D), vehicle-to-everything (V2X), and machine-to-machine (M2M) communications, network-side devices in 6G networks, and devices that perform base station functions in future communication systems. Base stations can support networks using the same or different access technologies. The embodiments of this application do not limit the specific technologies or device forms used in the network equipment.

[0034] Base stations can be fixed or mobile. For example, a helicopter or drone can be configured to act as a mobile base station, and one or more cells can move depending on the location of the mobile base station. In other examples, a helicopter or drone can be configured as a device to communicate with another base station.

[0035] In some deployments, the network device in this application embodiment may refer to a CU or a DU, or the network device may include both a CU and a DU. The gNB may also include an AAU.

[0036] Network devices and terminal devices can be deployed on land, including indoors or outdoors, handheld or vehicle-mounted; they can also be deployed on water; and they can also be deployed in the air on airplanes, balloons, and satellites. This application does not limit the scenario in which the network devices and terminal devices are located.

[0037] It should be understood that all or part of the functions of the communication device in this application can also be implemented by software functions running on hardware, or by virtualization functions instantiated on a platform (e.g., a cloud platform).

[0038] AI / ML-based beam management

[0039] Currently, AI / ML-based beam management has received widespread attention. For example, in the discussions of the 3rd generation partnership project (3GPP) Release 18 (R18) study item (SI) phase, AI / ML-based beam management was widely recognized as a key use case in the R18 AI project. In the 3GPP R19 work item (WI) phase, 3GPP defined two typical AI / ML-based beam management use cases: downlink beam prediction in the spatial domain and downlink beam prediction in the temporal domain. These two beam management use cases can be used for benchmark performance evaluation. Downlink beam prediction in the spatial domain is referred to as beam management-case 1 (BM-case1), and downlink beam prediction in the temporal domain is referred to as beam management-case 2 (BM-case2). It should be noted that for BM-case1 and BM-case2, beams in set A and beams in set B can be located in the same frequency range. BM-case1 and BM-case2 will be introduced below.

[0040] BM-case1

[0041] In BM-case1, spatial domain prediction of the downlink transmit beam in set A can be performed by measuring the downlink transmit beam in set B, or in other words, spatial domain prediction of the downlink transmit beam in set A can be performed by measuring the downlink transmit beam in set B.

[0042] In some embodiments, set B can be a subset of set A. That is, set A can be understood as the entire set of downlink transmit beams, while set B can be understood as a partial subset of downlink transmit beams. In this way, the best beam (or optimal beam) in the entire set can be predicted by measuring the subset, reducing the measurement burden on the terminal equipment.

[0043] In some embodiments, set B and set A can be two different beam sets; for example, the types of beams in set B and set A can be different. As an example, set B can be a set of synchronization signal block (SSB) resources with a small number of beams (each SSB resource corresponds to a large coverage area), while set A can be a set of channel state information reference signal (CSI-RS) resources with a large number of beams (each CSI-RS corresponds to a smaller spatial coverage area).

[0044] In some embodiments, beam prediction in the spatial domain can be implemented using different sub-models. The models for beam prediction in the spatial domain are illustrated below with reference to Figures 2 and 3.

[0045] Figure 2 illustrates a beam prediction model. As shown in Figure 2, the input of this beam prediction model is a partial set of transmitted beam measurements, specifically a portion of the layer 1 reference signal receiving power (L1-RSRP) measured across the entire set. The output is the indices of the K optimal transmitted beams (K greater than or equal to 1) selected from the entire set, representing the K transmitted beams with the highest L1-RSRP. In other words, the relationship between the input and output of the model shown in Figure 2 represents the relationship from the partial subset of L1-RSRP input to the optimal K transmitted beams. From the input and output relationship of the beam prediction model shown in Figure 2, it can be considered that this model solves a multi-classification problem. In the beam prediction model shown in Figure 2, the labels used by this model are the indices of the K optimal (i.e., those with the highest L1-RSRP) transmitted beams measured across the entire set.

[0046] Figure 3 illustrates another beam prediction model that can be used to predict optimal beam quality. As shown in Figure 3, the input of this beam prediction model is a partial set of transmitted beam measurements, i.e., a portion of the total set of L1-RSRP measurements, and the output is K (K greater than or equal to 1) L1-RSRPs. In other words, compared to the beam prediction model in Figure 2, the two models have the same input but different outputs. It can be seen that the relationship between the input and output of the model shown in Figure 3 is the relationship from the partial subset of input L1-RSRPs to the optimal K transmitted beam L1-RSRPs. From the input and output relationship of the beam prediction model shown in Figure 3, the model can be understood as a linear regression problem. In the beam prediction model shown in Figure 3, the labels used are the first K L1-RSRPs measured in the total set, and the corresponding indices of the K transmitted beams.

[0047] BM-case2

[0048] In BM-case2, the optimal beam for the downlink transmit beam in set A at one or more future times can be predicted by measuring the transmit beam in set B at one or more historical times. In other words, the time-domain prediction of the beam in set A can be performed based on the historical measurement results of the beams in set B.

[0049] In some embodiments, set B can be the same as set A, meaning set B and set A are the same set. For example, in the use case of purely time-domain beam prediction, set B and set A can be the same.

[0050] In some embodiments, set B may be different from set A. For example, considering hybrid temporal and spatial beam prediction, set B may be a subset of set A, or the beam types in set B may be different from those in set A (e.g., set B may be an SSB resource set, and set A may be a CSI-RS resource set).

[0051] Figure 4 illustrates an example of the measurement window and prediction window in a time-domain beam prediction scenario. In the example of Figure 4, the downlink history measurement window is 100ms, meaning that beams in set B can be measured at 100ms intervals, i.e., the downlink reference signal (DL RS) corresponding to the beams in set B can be measured. Similarly, in the example of Figure 4, the prediction window for the future optimal beam is also 100ms, meaning that beams in set A can be predicted at 100ms intervals. It should be noted that the time lengths of the measurement window and the prediction window can be different, and this embodiment of the application does not limit this.

[0052] In some embodiments, a long short-term memory (LSTM) network model can be used for beam prediction in the time domain.

[0053] Performance monitoring of AI / ML models

[0054] Performance monitoring of AI / ML models can include performance monitoring of models on the terminal device side and performance monitoring of models on the network device side. Since the performance monitoring of network-side models depends on the implementation on the network device side, the following sections will primarily focus on performance monitoring of models on the terminal device side.

[0055] For performance monitoring of models on the terminal device side, Type 1 performance monitoring is currently supported. Type 1 performance monitoring means that the network device ultimately performs subsequent operations based on the performance monitoring results, such as changing the model or falling back to the traditional beam measurement and reporting scheme.

[0056] Type 1 performance monitoring can include two options: Option 1 and Option 2. In Option 1, the network device performs performance monitoring. One possible implementation is that the terminal device sends a measurement report to the network device, which then calculates the model's performance metric. In Option 2, the terminal device assists in performance monitoring. One possible implementation is that the terminal device performs measurements and calculates the model's performance metric, then reports the result to the network device.

[0057] The measurement report sent by the terminal device to the network device may include measurement results of the monitoring resource set. For example, the measurement report may include the L1-RSRP and / or the index of the beam in the monitoring resource set.

[0058] In some embodiments, the transmission of the measurement report is configured or triggered by the network device.

[0059] It should be noted that, regardless of whether it is Option 1 or Option 2, the network equipment will perform subsequent operations based on performance indicators, such as changing the model or reverting to the traditional beam measurement and reporting scheme.

[0060] Regarding the performance metrics for monitoring, the following consensus has been reached. In BM-case1 and BM-case2 scenarios, for the AI / ML model on the terminal device side, at least Option 1 is supported for the aforementioned optional scheme 2. Option 1 refers to the monitoring performance metric being the top 1 or top K beam prediction accuracy. It should be noted that beam prediction accuracy is obtained by comparing the prediction results with the actual measurement results; that is, beam prediction accuracy is obtained by comparing the prediction results with the measurement results of the top 1 or top K beams in the monitoring resource set.

[0061] Furthermore, the protocol reached the following consensus regarding the configuration of the monitoring resource set used for model performance monitoring. For AI / ML models on the terminal device side, at least for Option 2 in Type 1 performance monitoring, the reuse of the CSI framework is supported to configure the reporting of monitoring results for Layer 1 signaling. Specifically, the dedicated monitoring resource set for performance monitoring and the reporting configuration for performance monitoring can be configured within a dedicated CSI reporting configuration for performance monitoring.

[0062] In other words, currently, the monitoring resource set used for model performance monitoring and the prediction resource set used for prediction are configured separately, meaning that the monitoring resource set and the prediction resource set have independent CSI reporting configurations. Specifically, the terminal device needs to report prediction results according to the configuration of the prediction resource set, and report model performance monitoring results according to the configuration of the monitoring resource set.

[0063] However, while there is a certain correlation between the two, they belong to two different CSI reporting configurations from the signaling perspective of radio resource control (RRC). Therefore, in some embodiments, the identifier (ID) of the prediction result reporting configuration can be configured in the monitoring configuration to associate the prediction result reporting configuration with the monitoring reporting configuration.

[0064] As can be seen from the above description, the proposed technologies suggest that beam management can be performed using AI / ML models. In AI / ML-based beam management scenarios, how to monitor the performance of AI / ML-based beam prediction models becomes a pressing issue.

[0065] To address the aforementioned issues, this application will introduce the performance monitoring of AI / ML-based beam prediction models from multiple aspects. The method embodiments of this application will be described first below.

[0066] It should be noted that the embodiments of this application can be applied to any beam prediction or beam management scenario. For example, the embodiments of this application can be applied to a scenario where the model is deployed on the terminal device side. As another example, the embodiments of this application can be applied to a scenario where the model is deployed on the network device side (the network device can determine the first information itself and determine subsequent operations based on the first information).

[0067] Taking the scenario where the model is deployed on the terminal device side as an example, the embodiments of this application can be applied to a performance monitoring scenario of type 1 (i.e., the network device determines or performs subsequent operations based on the performance monitoring results, such as replacing the model or falling back to the traditional beam measurement and reporting scheme). For example, the embodiments of this application can be applied to optional scheme 1 mentioned above, or to optional scheme 2 mentioned above.

[0068] Figure 5 is a schematic flowchart of a wireless communication method provided in an embodiment of this application. The method shown in Figure 5 is described from the perspective of interaction between a terminal device and a network device, which can be, for example, the terminal device 120 and the network device 110 shown in Figure 1. The method shown in Figure 5 may include step S510, which will be described below.

[0069] In step S510, the terminal device sends the first information or the first report to the network device.

[0070] In the embodiments of this application, the first information or first report can be used for performance monitoring of a prediction model (such as a beam prediction model). For example, when the prediction model is deployed on the terminal device side, the terminal device can send the first information or first report to the network device, so that the network device can determine the performance monitoring results of the prediction model based on the first information or first report, and determine subsequent operations based on the performance monitoring results of the prediction model. For example, the network device can determine to replace the currently used prediction model based on the first information or first report. As another example, the network device can determine to revert to a traditional beam measurement and reporting scheme based on the first information or first report.

[0071] In some embodiments, the terminal device may send first information to the network device. For example, when the prediction model is deployed on the terminal device side and this application is applied to a scenario of terminal device-assisted performance monitoring (i.e., the optional scheme 2 mentioned above), the terminal device may send first information to the network device.

[0072] In some embodiments, the terminal device may send a first report to the network device. For example, when the prediction model is deployed on the terminal device side and this application is applied to a scenario where the network device performs performance monitoring (i.e., Option 1 mentioned above), the terminal device may send a first report to the network device.

[0073] In some embodiments, the first report can be used to determine first information. That is, after receiving the first report, the network device can determine the first information based on the content contained in the first report. Subsequently, the network device can determine subsequent operations based on the first information, such as changing the model or reverting to a traditional beam measurement and reporting scheme.

[0074] This application does not limit the information contained in the first report. For example, the first report may include one or more of the following: prediction results of downlink reference signal resources in the prediction resource set, and measurement results of downlink reference signal resources in the monitoring resource set.

[0075] As an example, the first report may include measurement results of downlink reference signal resources in the monitoring resource set.

[0076] As another example, the first report may include the prediction results of downlink reference signal resources in the prediction resource set.

[0077] As another example, the first report may include the prediction results of downlink reference signal resources in the prediction resource set and the measurement results of downlink reference signal resources in the monitoring resource set.

[0078] In some embodiments, when the first report includes one of the above-described information, the other of the above-described information can be reported to the network device through other reports. That is, in some embodiments, the prediction results of downlink reference signal resources in the prediction resource set and the measurement results of downlink reference signal resources in the monitoring resource set can be reported to the network device through different reports (or signaling).

[0079] In some embodiments, after receiving the measurement results of downlink reference signal resources in the monitoring resource set and the prediction results of downlink reference signal resources in the prediction resource set sent by the terminal device, the network device can determine the first information based on this information.

[0080] The first information will be described below with reference to Example 1.

[0081] Example 1:

[0082] In the embodiments of this application, the first information can be used to indicate the accuracy of downlink reference signal resource prediction (also referred to as the accuracy of downlink reference signal prediction, beam prediction accuracy, etc.).

[0083] It should be noted that the "downlink reference signal resource" mentioned in the embodiments of this application can also be understood as or replaced by one or more of the following: downlink reference signal, beam, downlink transmit beam, downlink reference signal resource corresponding to the beam, spatial filter, spatial transmit filter. Unless otherwise specified, the embodiments of this application do not distinguish between these concepts.

[0084] It should also be noted that the term "beam" mentioned in the embodiments of this application can be understood or replaced as one or more of the following: spatial filter, spatial transmit filter, downlink reference signal, and transmission configuration indicator (TCI) state. For example, embodiments of this application may use a downlink reference signal (such as CSI-RS or SSB) to associate a beam (such as a transmit beam). As another example, in the beam indication process, embodiments of this application may use a TCI state (which includes a downlink reference signal) to refer to a beam (such as a transmit beam).

[0085] This application does not limit the indication method of the first information (or the accuracy of the downlink reference signal resource prediction). In some embodiments, the first information (or the accuracy of the downlink reference signal resource prediction) can be used to indicate whether a single downlink reference signal resource prediction is accurate. In some embodiments, the first information (or the accuracy of the downlink reference signal resource prediction) can be used to indicate the accuracy of multiple downlink reference signal resource predictions. In some embodiments, the first information (or the accuracy of the downlink reference signal resource prediction) can be used to indicate the accuracy of the downlink reference signal resource prediction over a period of time.

[0086] Taking the first information indicating whether a downlink reference signal resource prediction is accurate as an example, the first information may include one or more of the following: prediction is accurate, prediction is inaccurate, prediction accuracy is 100%, and prediction accuracy is 0%.

[0087] Taking the accuracy of multiple downlink reference signal resource predictions as an example, the first information may include one or more of the following: the accuracy rate of downlink reference signal resource predictions within a fixed number of predictions, the number of times downlink reference signal resources were correctly predicted (or successfully predicted) within a fixed number of predictions, and the number of times downlink reference signal resources were incorrectly predicted (or failed to be predicted) within a fixed number of predictions. Alternatively, the accuracy of downlink reference signal resource predictions can be determined by one or more of the following: the accuracy rate of downlink reference signal resource predictions within a fixed number of predictions, the number of times downlink reference signal resources were correctly predicted within a fixed number of predictions, and the number of times downlink reference signal resources were incorrectly predicted within a fixed number of predictions.

[0088] As an example, the first piece of information may include the accuracy of downlink reference signal resource prediction over a fixed number of cycles.

[0089] As another example, the first information may include the number of times the downlink reference signal resource was correctly predicted within a fixed number of attempts.

[0090] As yet another example, the first piece of information may include the number of times downlink reference signal resources are incorrectly predicted within a fixed number of attempts.

[0091] As another example, the first information may include the accuracy of downlink reference signal resource prediction within a fixed number of attempts and the number of times downlink reference signal resources were correctly predicted within a fixed number of attempts.

[0092] As another example, the first information may include the accuracy of downlink reference signal resource prediction within a fixed number of attempts and the number of times downlink reference signal resources were incorrectly predicted within a fixed number of attempts.

[0093] As another example, the first information may include the number of times the downlink reference signal resource was correctly predicted within a fixed number of attempts and the number of times the downlink reference signal resource was correctly predicted within a fixed number of attempts.

[0094] As another example, the first information may include the accuracy of downlink reference signal resource prediction within a fixed number of attempts, the number of times downlink reference signal resources were correctly predicted within a fixed number of attempts, and the number of times downlink reference signal resources were incorrectly predicted within a fixed number of attempts.

[0095] This application does not limit the configuration method of the fixed number of times. In some embodiments, the fixed number of times is configured by the network device. In some embodiments, the fixed number of times is predefined or preconfigured by the protocol.

[0096] The embodiments of this application do not limit the value of the fixed number of times. For example, the fixed number of times can be 10 times, 50 times, 100 times, etc.

[0097] Taking the accuracy of downlink reference signal resource prediction over a certain period as an example, the first information may include one or more of the following: the accuracy rate of downlink reference signal resource prediction within a first time window, the number of times downlink reference signal resources are correctly predicted within the first time window, and the number of times downlink reference signal resources are incorrectly predicted within the first time window. Alternatively, the accuracy of downlink reference signal resource prediction can be determined by one or more of the following: the accuracy rate of downlink reference signal resource prediction within the first time window, the number of times downlink reference signal resources are correctly predicted within the first time window, and the number of times downlink reference signal resources are incorrectly predicted within the first time window.

[0098] As an example, the first piece of information may include the accuracy of the downlink reference signal resource prediction within the first time window.

[0099] As another example, the first information may include the number of times downlink reference signal resources are correctly predicted within a first time window.

[0100] As yet another example, the first information may include the number of times downlink reference signal resources are incorrectly predicted within the first time window.

[0101] As another example, the first information may include the accuracy of downlink reference signal resource prediction within the first time window and the number of times downlink reference signal resources were correctly predicted within the first time window.

[0102] As another example, the first information may include the accuracy of downlink reference signal resource prediction within the first time window and the number of times downlink reference signal resources were incorrectly predicted within the first time window.

[0103] As another example, the first information may include the number of times downlink reference signal resources were correctly predicted within the first time window and the number of times downlink reference signal resources were correctly predicted within the first time window.

[0104] As another example, the first information may include the accuracy of downlink reference signal resource prediction within the first time window, the number of times downlink reference signal resources were correctly predicted within the first time window, and the number of times downlink reference signal resources were incorrectly predicted within the first time window.

[0105] For more information on the first-time window, please refer to the following text; it will not be detailed here.

[0106] In some embodiments, when the first information includes the number of correct and / or incorrect predictions of downlink reference signal resources, it can be understood that the terminal device can report the first information to the network device in integer form. This helps avoid quantifying the prediction accuracy, thereby avoiding quantization errors. The terminal device only needs to report the number of correct and / or incorrect predictions of downlink reference signal resources to the network device, and the network device can calculate the accuracy of the downlink reference signal resource prediction itself.

[0107] In some embodiments, the accuracy of downlink reference signal resource prediction can be indicated as a percentage. That is, the terminal device can report the accuracy of downlink reference signal resource prediction as a percentage.

[0108] In some embodiments, the accuracy of downlink reference signal resource prediction = total number of successful predictions ÷ total number of predictions. Wherein, the total number of predictions = total number of correct predictions + total number of incorrect predictions. Taking the accuracy of downlink reference signal resource prediction including the accuracy of downlink reference signal resource prediction within a first time window as an example, the accuracy of downlink reference signal resource prediction within the first time window = total number of successful predictions within the first time window ÷ total number of predictions within the first time window.

[0109] In some embodiments, the accuracy of downlink reference signal resource prediction can be indicated by a prediction accuracy level; that is, the accuracy of resource prediction can be quantified as a prediction accuracy level. In this case, the terminal device simply reports the prediction accuracy level.

[0110] This application does not limit how the accuracy of resource prediction is quantified into prediction accuracy levels, such as how many prediction accuracy levels it is quantified into, or the range of accuracy corresponding to each prediction accuracy level.

[0111] For example, in this embodiment of the application, the accuracy of downlink reference signal resource prediction can be quantified into 20 prediction accuracy levels with a granularity of 5%. For instance, the accuracy of downlink reference signal resource prediction is 0% to 5% as the lowest level of prediction accuracy, 5%-10% as the second level of prediction accuracy, ..., and 95%-100% as the highest level of prediction accuracy.

[0112] For example, in the embodiments of this application, the accuracy of downlink reference signal resource prediction can be quantified into 5 prediction accuracy levels. For instance, the prediction accuracy of downlink reference signal resource is 0% to 50% as the lowest level of prediction accuracy, 50%-70% as the second level of prediction accuracy, 70%-80% as the third level of prediction accuracy, 80%-90% as the fourth level of prediction accuracy, and 90%-100% as the highest level of prediction accuracy.

[0113] To avoid unnecessary duplicate reporting, in some embodiments, the terminal device may not report the first piece of information when the model is functioning correctly. In other words, when the model is working normally and running well, the terminal device does not need to report, thus helping to avoid wasting uplink control channel resources.

[0114] This application does not limit the way it represents the model's good performance. For example, when the model's prediction accuracy is greater than or equal to a certain threshold (such as 95%, 90%, etc.), the model can be considered to be in good performance. As another example, when the number of correct predictions by the model is greater than or equal to a certain threshold (such as 20 times, 50 times, etc.), the model can be considered to be in good performance. It should be noted that the number of correct predictions is relative to the total number of predictions or relative to the first time window. When the total number of predictions and / or the first time window are different, the threshold corresponding to the number of correct predictions may be different.

[0115] In some embodiments, when one or more of the first conditions are met, the terminal device needs to report the first information; otherwise, the terminal device only measures the monitoring resource set but does not report it. The first conditions may include one or more of the following: the accuracy of the model prediction is less than or equal to a first threshold, the number of successful predictions by the model is less than or equal to a second threshold, and the number of incorrect predictions by the model is greater than or equal to a third threshold.

[0116] The embodiments of this application do not limit the first threshold. For example, the first threshold can be 90%. Or, for example, the first threshold can be 80%.

[0117] The embodiments of this application do not limit the second threshold. For example, the second threshold can be 20 times. Or, for example, the second threshold can be 30 times. It should be noted that the number of times the model correctly predicts is relative to the total number of predictions or relative to the first time window. When the total number of predictions and / or the first time window are different, the threshold corresponding to the number of times the model correctly predicts may be different.

[0118] The embodiments of this application do not limit the third threshold. For example, the third threshold can be 5 times. Or, for example, the third threshold can be 20 times. It should be noted that the number of times the model makes incorrect predictions is relative to the total number of predictions or relative to the first time window. When the total number of predictions and / or the first time window are different, the threshold corresponding to the number of times the model makes incorrect predictions may be different.

[0119] In some embodiments, the accuracy of downlink reference signal resource prediction can be determined based on K downlink reference signal resources in the predicted resource set and M downlink reference signal resources in the monitored resource set. In this way, embodiments of this application can monitor the performance of the beam prediction model by monitoring the accuracy of the downlink reference signal resource prediction, thereby facilitating better utilization of the beam prediction model for beam management.

[0120] In some embodiments, the prediction resource set can be used by the terminal device to perform downlink reference signal resource prediction. Alternatively, the prediction resource set can be used by the terminal device to perform beam prediction.

[0121] This application does not limit the type of downlink reference signal resources in the prediction resource set. In some embodiments, the downlink reference signal resources in the prediction resource set may include SSB resources. In some embodiments, the downlink reference signal resources in the prediction resource set may include CSI-RS resources.

[0122] In some embodiments, the prediction resource set may also be understood as or referred to as the set B mentioned above.

[0123] In some embodiments, the monitoring resource set can be used to monitor the performance of the beam prediction model. Alternatively, the monitoring resource set can be used to monitor the accuracy of downlink reference signal resource prediction.

[0124] In some embodiments, the monitoring resource set and the prediction resource set can be the same. That is, the downlink reference signal resources in the monitoring resource set and the downlink reference signal resources in the prediction resource set can be the same.

[0125] In some embodiments, the monitoring resource set and the prediction resource set may be different. For example, the types of downlink reference signal resources in the monitoring resource set and the downlink reference signal resources in the prediction resource set may be different. As another example, the number of downlink reference signal resources in the monitoring resource set and the number of downlink reference signal resources in the prediction resource set may be different.

[0126] As an example, the monitoring resource set differs from the prediction resource set in that the types of downlink reference signal resources in the monitoring resource set and the prediction resource set can be different. For instance, the downlink reference signal resources in the monitoring resource set might be SSB resources, while those in the prediction resource set could be CSI-RS resources. This difference in the monitoring and prediction resource sets helps reduce the measurement overhead of model performance monitoring. For example, as a performance monitoring resource set, the network device can transmit wider beamwidth SSB resources, while as a prediction resource set, the network device can transmit narrower beamwidth CSI-RS resources.

[0127] As another example, the difference between the monitoring resource set and the prediction resource set can include: the number of downlink reference signal resources in the monitoring resource set can differ from the number of downlink reference signal resources in the prediction resource set. For instance, the monitoring resource set can be a subset of the prediction resource set. That is, the downlink reference signal resources in the monitoring resource set can be a subset of the downlink reference signal resources in the prediction resource set (i.e., the downlink reference signal resources in the monitoring resource set are a part of the downlink reference signal resources in the prediction resource set). Having a monitoring resource set as a subset of the prediction resource set helps reduce the measurement overhead of model performance monitoring. In other words, network devices may only send a portion of the downlink reference signals from the prediction resource set as the monitoring resource set to reduce the measurement overhead of performance monitoring.

[0128] As another example, the difference between the monitoring resource set and the prediction resource set can include that the downlink reference signal resources in the monitoring resource set are different in both type and quantity from those in the prediction resource set.

[0129] In some embodiments, the K downlink reference signal resources in the prediction resource set are the top K downlink reference signal resources in the prediction resource set with the best prediction results (i.e., the top K downlink reference signal resources). That is, the prediction results of these K downlink reference signal resources are higher than or equal to the prediction results of other downlink reference signal resources in the prediction resource set.

[0130] In some embodiments, the K downlink reference signal resources in the prediction resource set are obtained through model prediction.

[0131] In some embodiments, K is greater than or equal to 1, or in other words, K is a positive integer. As an example, K can be 1. As another example, K can be a positive integer greater than 1.

[0132] In some embodiments, the M downlink reference signal resources in the monitoring resource set are the top K downlink reference signal resources (i.e., the top M downlink reference signal resources) with the best measurement results in the monitoring resource set. That is, the measurement results of these M downlink reference signal resources are higher than or equal to the measurement results of other downlink reference signal resources in the monitoring resource set.

[0133] In some embodiments, the M downlink reference signal resources in the monitoring resource set are measured by the terminal device.

[0134] In some embodiments, M is greater than or equal to 1, or in other words, M is a positive integer. As an example, M can be 1. As another example, K can be a positive integer greater than 1.

[0135] This application does not limit the method for determining the values ​​of K and M in its embodiments. In some embodiments, K and / or M may be predefined or preconfigured, such as K and / or M being predefined by the protocol. In some embodiments, K and / or M may be configured by the network device.

[0136] This application does not limit the configuration signaling carrying K and / or M in its embodiments. For example, the network device can configure K and / or M to the terminal device through higher-layer signaling (such as RRC signaling). As another example, the network device can configure K and / or M to the terminal device through a medium access control element (MAC CE). Yet another example, the network device can configure K and / or M to the terminal device through downlink control information (DCI).

[0137] In some embodiments, K and / or M are determined by the network device based on capability information reported by the terminal device. This capability information can be used to indicate the range of values ​​for K and / or M supported by the terminal device. For example, the terminal device can report K = 1, 2, ..., K through the capability information. max For example, terminal devices can report capability information M=1, 2, ..., M max .

[0138] In some embodiments, the terminal device can report the range of values ​​for K and M through capability information.

[0139] In some embodiments, the terminal device can report the range of values ​​for K and M through different capability information.

[0140] In some embodiments, K and M can be configured in the same way. For example, both K and M may be predefined or preconfigured. Or, both K and M may be configured by the network device.

[0141] In some embodiments, K and M can be configured differently. For example, K may be predefined or preconfigured, while M may be configured by the network device. Alternatively, K may be configured by the network device, while M may be predefined or preconfigured. Or, K and M may be configured using different signaling methods, such as different RRC signaling; or K may be configured using RRC signaling, while M may be configured using MAC CE.

[0142] In some embodiments, the prediction resource set and the monitoring resource set affect the determination of the accuracy of downlink reference signal resource prediction. That is, the relationship between the prediction resource set and the monitoring resource set may need to be considered when determining the accuracy of downlink reference signal resource prediction. For example, the method for determining the accuracy of downlink reference signal resource prediction when the prediction resource set and the monitoring resource set are the same may differ from the method for determining the accuracy of downlink reference signal resource prediction when the prediction resource set and the monitoring resource set are different.

[0143] The following describes different methods for determining the accuracy of downlink reference signal resource prediction, using various embodiments.

[0144] Example 1.1:

[0145] In Example 1.1, if, during a downlink reference signal resource prediction process, one or more of the aforementioned K downlink reference signal resources belong to the aforementioned M downlink reference signal resources, then the downlink reference signal resource prediction can be considered accurate. In other words, in Example 1.1, an accurate downlink reference signal resource prediction can be defined by whether any of the K downlink reference signal resources belongs to the M downlink reference signal resources.

[0146] In some embodiments, when K equals 1, an accurate downlink reference signal resource prediction can be understood as the downlink reference signal resource with the best prediction result in the prediction resource set belonging to one of the top M downlink reference signal resources with better measurement results in the monitoring resource set. In other words, the reference signal resource corresponding to the optimal beam predicted by the model ranks among the top M in actual measurement.

[0147] In some embodiments, when M equals 1, an accurate downlink reference signal resource prediction can be understood as at least one of the top K downlink reference signal resources with the best prediction results in the predicted resource set being the downlink reference signal resource with the best measurement results in the monitored resource set. In other words, at least one of the predicted K best beams ranks first in actual measurement.

[0148] It should be noted that the optimal downlink reference signal resource in the prediction resource set can be one or more. For example, there can be multiple optimal downlink reference signal resources in the prediction resource set, and these multiple downlink reference signal resources may correspond to the same prediction result. It should also be noted that the optimal downlink reference signal resource in the monitoring resource set can be one or more. For example, there can be multiple optimal downlink reference signal resources in the monitoring resource set, and these multiple downlink reference signal resources may correspond to the same measurement result.

[0149] In some embodiments, Example 1.1 can be applied to scenarios where the monitoring resource set and the prediction resource set are the same. That is, Example 1.1 can be applied to scenarios where the downlink reference signal resources contained in the monitoring resource set and the downlink reference signal resources contained in the prediction resource set are the same.

[0150] Example 1.2:

[0151] In Example 1.2, if one or more of the K downlink reference signal resources are quasi-co-located with one or more of the M downlink reference signal resources during a downlink reference signal resource prediction process, then the downlink reference signal resource prediction can be considered accurate.

[0152] In some embodiments, when K equals 1, an accurate downlink reference signal resource prediction can be understood as the quasi-co-addressing of at least one downlink reference signal resource among the top M downlink reference signal resources with better measurement results in the prediction resource set and the top M downlink reference signal resources with better measurement results in the monitoring resource set.

[0153] In some embodiments, when M equals 1, an accurate downlink reference signal resource prediction can be understood as at least one downlink reference signal among the top K downlink reference signal resources with better prediction results in the prediction resource set is quasi-co-located with the downlink reference signal resource with the best measurement results in the monitoring resource set.

[0154] In some embodiments, the aforementioned quasi-colocation refers to spatial quasi-colocation, i.e., quasi-colocation type D specified in the protocol. In other words, assuming that two downlink reference signals transmitted by a network device have approximately the same transmit beam direction, and a terminal device can receive these two downlink reference signals using the same receive beam, then it can be considered that these two downlink reference signals have a spatial quasi-colocation relationship.

[0155] For ease of understanding, the following section, in conjunction with Figure 6, explains whether the downlink reference signals in the prediction resource set and the downlink reference signals in the monitoring resource set are quasi-co-located. As shown in Figure 6, the shaded circles represent downlink reference signal resources in the prediction resource set, and the unshaded large circles represent downlink reference signal resources in the monitoring resource set. If any one (or at least one) of the K downlink reference signal resources with better prediction results in the prediction resource set has a quasi-co-located relationship with the M downlink reference signal resources with better measurement results in the monitoring resource set, then the downlink reference signal resource prediction (or beam prediction) can be considered accurate.

[0156] In some embodiments, whether one or more reference signal resources among the K downlink reference signal resources are quasi-co-located with one or more reference signal resources among the M downlink reference signal resources is determined by a first signaling. The first signaling can be used to configure the quasi-co-location relationship between two reference signal resources. In other words, whether one or more reference signal resources among the K downlink reference signal resources are quasi-co-located with one or more reference signal resources among the M downlink reference signal resources is configured (or activated) by the network device through signaling.

[0157] In some embodiments, the first signaling can be used to configure or activate the TCI state.

[0158] The embodiments of this application do not limit the first signaling. Exemplarily, the first signaling may include one or more of the following: RRC signaling, MAC CE, DCI.

[0159] In some embodiments, Example 1.2 can be applied to scenarios where the prediction resource set and the monitoring resource set are different. For example, Example 1.2 can be applied to scenarios where the type of downlink reference signal resources in the prediction resource set is different from the type of downlink reference signal resources in the monitoring resource set. For instance, the downlink reference signal resources included in the monitoring resource set are SSB resources, while the downlink reference signal resources included in the prediction resource set are CSI-RS resources. As another example, Example 1.2 can be applied to scenarios where the monitoring resource set is a subset of the prediction resource set. When the prediction resource set and the monitoring resource set are different, the prediction results of the downlink reference signal resources in the prediction resource set cannot be directly compared with the measurement results of the downlink reference signals in the monitoring resource set. This problem can be effectively solved by determining whether they are quasi-co-located.

[0160] In some embodiments, Example 1.2 can be applied to scenarios where the prediction resource set and the monitoring resource set are the same.

[0161] Example 1.3:

[0162] In Example 1.3, if one or more of the K downlink reference signal resources have the same quasi-co-location source as one or more of the M downlink reference signal resources during a downlink reference signal resource prediction process, then the downlink reference signal resource prediction can be considered accurate.

[0163] In some embodiments, when K equals 1, an accurate beam prediction can be understood as the optimal downlink reference signal resource in the prediction resource set having the same quasi-co-located source as at least one of the M downlink reference signal resources in the monitoring resource set with better measurement results.

[0164] In some embodiments, when M equals 1, an accurate downlink reference signal resource prediction can be understood as at least one downlink reference signal among the top K downlink reference signal resources with better prediction results in the prediction resource set has the same quasi-co-located source as the downlink reference signal resource with the best measurement results in the monitoring resource set.

[0165] In some embodiments, the aforementioned quasi-co-location source refers to a spatial quasi-co-location source, i.e., the source of quasi-co-location type D specified in the protocol. In this case, the fact that one or more reference signal resources among the K downlink reference signal resources have the same quasi-co-location source as one or more reference signals among the M downlink reference signal resources can also be understood as follows: if, during a downlink reference signal resource prediction process, one or more reference signal resources among the K downlink reference signal resources have the same source of quasi-co-location type D as one or more reference signals among the M downlink reference signal resources, then the current downlink reference signal resource prediction can be considered accurate.

[0166] In some embodiments, the quasi-co-address source of the reference signal resource may be an SSB resource.

[0167] For ease of understanding, the following section, in conjunction with Figure 7, explains whether the downlink reference signals in the prediction resource set and the downlink reference signals in the monitoring resource set have the same quasi-co-located source. As shown in Figure 7, the shaded circles represent downlink reference signal resources in the prediction resource set and the monitoring resource set, respectively. Large, unfilled circles indicate that the reference signal resources within those large circles have the same quasi-co-located source. If any one (or at least one) of the K downlink reference signal resources with better prediction results in the prediction resource set has the same quasi-co-located source as any one (or at least one) of the M downlink reference signal resources with better measurement results in the monitoring resource set, then the downlink reference signal resource prediction (or beam prediction) can be considered accurate.

[0168] In some embodiments, Example 1.3 can be applied to scenarios where the prediction resource set and the monitoring resource set are different. For example, Example 1.3 can be applied to scenarios where the type of downlink reference signal resources in the prediction resource set is different from the type of downlink reference signal resources in the monitoring resource set. For instance, the downlink reference signal resources included in the monitoring resource set are SSB resources, while the downlink reference signal resources included in the prediction resource set are CSI-RS resources. As another example, Example 1.3 can be applied to scenarios where the monitoring resource set is a subset of the prediction resource set. When the prediction resource set and the monitoring resource set are different, the prediction results of the downlink reference signal resources in the prediction resource set cannot be directly compared with the measurement results of the downlink reference signals in the monitoring resource set. This problem can be effectively solved by determining whether they have the same quasi-co-located source.

[0169] In some embodiments, Example 1.3 can be applied to scenarios where the prediction resource set and the monitoring resource set are the same.

[0170] In Examples 1.1 to 1.3, the accuracy of a single downlink reference signal resource prediction is absolute. For example, when comparing the predicted optimal downlink reference signal resource with the measured optimal downlink reference signal resource, if the index of the predicted optimal downlink reference signal resource is 2, while the index of the measured optimal downlink reference signal resource is 5, then in Examples 1.1 to 1.3, the prediction can be considered inaccurate. However, in reality, there may be situations where the predicted optimal downlink reference signal resource, although not the measured optimal downlink reference signal resource, has performance similar to the measured optimal downlink reference signal resource. To address this situation, this application proposes Example 1.4, a method for determining the accuracy of a single downlink reference signal resource prediction.

[0171] Example 1.4:

[0172] In Example 1.4, if, during a downlink reference signal resource prediction process, the prediction results of one or more reference signal resources out of K downlink reference signal resources are close to the measurement results of one or more reference signal resources out of M downlink reference signal resources, then the downlink reference signal resource prediction can be considered accurate. In other words, in Example 1.4, the calculation of prediction performance accuracy has a certain tolerance for prediction deviation.

[0173] The embodiments of this application do not limit the implementation method for determining whether the prediction result of one or more reference signal resources among K downlink reference signal resources is close to the measurement result of one or more reference signal resources among M downlink reference signal resources.

[0174] As one possible implementation, the proximity of the predicted results of one or more downlink reference signal resources out of K downlink reference signal resources to the measured results of one or more downlink reference signal resources out of M downlink reference signal resources can be determined by whether the difference between these two measurements is less than or equal to a certain threshold. For example, if the difference between the predicted results of one or more downlink reference signal resources out of K downlink reference signal resources and the measured results of one or more downlink reference signal resources out of M downlink reference signal resources is less than the threshold, then the predicted results of one or more downlink reference signal resources out of K downlink reference signal resources and the measured results of one or more downlink reference signal resources out of M downlink reference signal resources are considered to be close; otherwise, they are considered not close. That is, in some embodiments, if the difference between the predicted results of one or more downlink reference signal resources out of K downlink reference signal resources and the measured results of one or more downlink reference signal resources out of M downlink reference signal resources is less than or equal to a first threshold during a downlink reference signal resource prediction process, then the downlink reference signal resource prediction is considered to be accurate.

[0175] This application does not limit the configuration of the first threshold. In some embodiments, the first threshold may be predefined or preconfigured. In some embodiments, the first threshold may be configured by a network device. In some embodiments, the first threshold may be determined by the terminal device based on a second threshold, which may be configured by a network device or predefined.

[0176] This application does not limit the signaling carrying the first threshold in its embodiments. Exemplarily, the first threshold may be carried in one or more of the following: RRC signaling, MAC CE, and DCI. As an example, the first threshold may be carried in RRC signaling.

[0177] The embodiments of this application do not limit the value of the first threshold. For example, the first threshold can be 3dB. Another example is -3dB. Yet another example is 5dB. And yet another example is 0dB. It should be noted that if the first threshold is configured to 0dB, it means that the calculation of the accuracy of the prediction performance has no tolerance or that the tolerance is 0.

[0178] In some embodiments, the first threshold may be determined based on the difference in transmit power between one or more of the K downlink reference signal resources and one or more of the M downlink reference signal resources. For example, the first threshold may be determined based on the difference in transmit power between the optimal downlink reference signal resource among the K downlink reference signal resources and the optimal downlink reference signal resource among the M downlink reference signal resources. As another example, the first threshold may be determined based on the difference in transmit power between the average transmit power of the K downlink reference signal resources and the average transmit power of the M downlink reference signal resources. For another example, the first threshold may be determined based on a second threshold and the difference in transmit power between one or more of the K downlink reference signal resources and one or more of the M downlink reference signal resources. As an example, assuming the transmit power of the SSB in the monitored resource set is 2 dB higher than the transmit power of the CSI-RS in the predicted resource set, then this transmit power difference can be considered when determining the first threshold; that is, the first threshold can be determined based on this 2 dB transmit power difference. For example, suppose the network device configures a second threshold of 3dB to the terminal device. The terminal device determines the first threshold as 3dB = second threshold + difference in transmission power = 3dB + 2dB = 5dB based on the second threshold and the difference in transmission power.

[0179] As another possible implementation, the proximity of the predicted results of one or more downlink reference signal resources out of K downlink reference signal resources to the measured results of one or more downlink reference signal resources out of M downlink reference signal resources can be determined by whether the quotient of the predicted results of one or more downlink reference signal resources out of K downlink reference signal resources to the measured results of one or more downlink reference signal resources to M downlink reference signal resources is close to 1. For example, if the quotient of the predicted results of one or more downlink reference signal resources out of K downlink reference signal resources to the measured results of one or more downlink reference signal resources to M ...

[0180] In some embodiments, Example 1.4 can be applied to scenarios where the prediction resource set and the monitoring resource set are different. For example, Example 1.4 can be applied to scenarios where the type of downlink reference signal resources in the prediction resource set is different from the type of downlink reference signal resources in the monitoring resource set; for instance, the downlink reference signal resources included in the monitoring resource set are SSB resources, while the downlink reference signal resources included in the prediction resource set are CSI-RS resources. As another example, Example 1.4 can be applied to scenarios where the monitoring resource set is a subset of the prediction resource set.

[0181] In some embodiments, Example 1.4 can be applied to scenarios where the prediction resource set and the monitoring resource set are the same.

[0182] It should be noted that the above embodiments 1.1 to 1.4 can be used individually or in combination. For example, embodiments 1.1, 1.2, 1.3, and 1.4 can all be used individually. Furthermore, different embodiments can be used for different situations to determine whether a downlink reference signal resource prediction is accurate. As an example, when the monitored resource set and the predicted resource set are the same, embodiment 1.1 can be used; when the type of the monitored resource set is different from the type of the predicted resource set, embodiment 1.2 can be used; when the monitored resource set is a subset of the predicted resource set, embodiment 1.3 can be used. As another example, when the type of the monitored resource set is different from the type of the predicted resource set, embodiment 1.2 can be used; when the monitored resource set is a subset of the predicted resource set or the monitored resource set is the same as the predicted resource set, embodiment 1.3 can be used. As yet another example, when the monitored resource set and the predicted resource set are the same, embodiment 1.1 can be used; when the monitored resource set and the predicted resource set are different (including different types and / or different quantities of downlink reference signal resources included), embodiment 1.3 can be used.

[0183] Example 2:

[0184] Example 2 aims to introduce the configuration of performance monitoring. Figure 8 is a flowchart illustrating a wireless communication method provided in another embodiment of this application. The method shown in Figure 8 includes step S810, in which the terminal device receives a first configuration sent by the network device.

[0185] In some embodiments, the first configuration can be used to report measurement results of downlink reference signal resources in the monitoring resource set. In other words, the terminal device can report measurement results of downlink reference signal resources in the monitoring resource set according to the first configuration. For example, the first configuration can be used to configure CSI reporting for one or more performance monitoring functions.

[0186] In some embodiments, the first configuration may include one or more of the following: one or more identifiers, one or more metrics indicating the performance of downlink reference signal resource prediction.

[0187] As an example, the first configuration may include one or more identifiers.

[0188] As another example, the first configuration may include one or more metrics that indicate the performance of downlink reference signal resource prediction.

[0189] As yet another example, the first configuration may include one or more identifiers, as well as one or more metrics that indicate the performance of downlink reference signal resource prediction.

[0190] The aforementioned identifiers can be used to indicate the configuration for reporting the prediction results of downlink reference signal resources in the prediction resource set. That is, the first configuration can include one or more configuration identifiers for indicating the prediction results of downlink reference signal resources in the prediction resource set. For example, the first configuration may include one or more identifiers for CSI reporting configurations used for beam prediction. As mentioned above, the first configuration for performance monitoring (such as the CSI reporting configuration for performance monitoring) and the CSI reporting configuration for beam prediction are independent in the RRC configuration (i.e., using different CSI reporting configurations), but these two need to be associated at the signaling layer so that the terminal equipment knows how to compare the prediction results of downlink reference signal resources in the prediction resource set with the measurement results of downlink reference signal resources in the monitoring resource set.

[0191] In some embodiments, the first configuration may include an identifier that indicates a configuration for reporting the prediction results of downlink reference signal resources in a prediction resource set.

[0192] In some embodiments, the first configuration may include multiple identifiers that can be used to indicate the configuration of prediction results for downlink reference signal resources in multiple reporting prediction resource sets. In this way, even if the terminal device performs multiple CSI reports based on downlink reference signal resources, performance monitoring of downlink reference signal resource predictions in multiple prediction resource sets can be completed by configuring only one performance monitoring resource set, thereby reducing the measurement overhead of the terminal device.

[0193] The aforementioned metrics indicating the performance of downlink reference signal resource prediction may include, for example, the accuracy of one or more downlink reference signal resource predictions.

[0194] Taking the first configuration as an example, which includes an identifier and a downlink reference signal resource prediction performance index, the terminal device can determine the prediction resource set associated with the first configuration based on the identifier, compare the prediction result of the downlink reference signal resource in the prediction resource set with the measurement result of the downlink reference signal resource in a monitoring resource set associated with the first configuration, and then report the performance monitoring result (i.e., report the first information).

[0195] Taking the first configuration as an example, which includes multiple identifiers and multiple downlink reference signal resource prediction performance indicators, the terminal device can determine multiple prediction resource sets associated with the first configuration based on the multiple identifiers, compare the prediction results of downlink reference signal resources in the multiple prediction resource sets with the measurement results of downlink reference signal resources in a monitoring resource set associated with the first configuration, and then report multiple performance monitoring results.

[0196] In some embodiments, when the first configuration includes multiple identifiers, it may include only one metric for downlink reference signal resource prediction performance.

[0197] In some embodiments, when the first configuration includes multiple identifiers, it may include multiple metrics for predicting downlink reference signal resources.

[0198] For ease of understanding, the following example uses the first configuration, which includes one or more identifiers and one or more metrics indicating the performance of downlink reference signal resource prediction, as an example to illustrate the first configuration.

[0199] Taking the CSI reporting configuration as the first configuration as an example, the first configuration can be as follows:

[0200] In some embodiments, the method shown in FIG8 may further include step S820. In step S820, the terminal device sends first information or a first report to the network device. For example, the terminal device may send the first information or the first report to the network device according to a first configuration.

[0201] For details regarding step S820, please refer to the above text. For the sake of brevity, it will not be repeated here.

[0202] It should be noted that Embodiment 2 and Embodiment 1 can be used individually or in combination. For example, after configuration using Embodiment 2, the first information or first report can be reported using Embodiment 1.

[0203] In some embodiments, the monitoring resource set and the prediction resource set in this application are related, for example, in terms of their configuration relationship (see the description in Embodiment 2), or in terms of their relationship in the time domain. The relationship between them in the time domain is described below.

[0204] In some embodiments, the method of this application may further include the following steps: the terminal device measures downlink reference signal resources in the monitoring resource set at one or more times, and the terminal device predicts downlink reference signal resources in the prediction resource set at a first time.

[0205] In some embodiments, the prediction result obtained by the terminal device from predicting the downlink reference signal resources in the prediction resource set at a first moment is monitored by using the measurement result obtained by the terminal device from measuring the downlink reference signal resources in the monitoring resource set at one of the aforementioned one or more moments.

[0206] In some embodiments, the terminal device can monitor the prediction result of the first time using the measurement result of the time closest to the first time among the one or more times mentioned above. That is, in some embodiments, the prediction result of the first time can be monitored by the measurement result of a second time, where the second time is the time closest to the first time among the one or more times mentioned above. This is because the closer the monitored resource set is to the predicted resource set, the more accurate the prediction of downlink reference signal resources can be determined using these two resource sets.

[0207] In some embodiments, the terminal device can monitor the prediction result at the first time point using the measurement result of the time point closest to and following the first time point among the one or more aforementioned time points. That is, in some embodiments, the prediction result at the first time point can be monitored using the measurement result at a second time point, which is the time point closest to and following the first time point among the one or more aforementioned time points. Using the measurement result of a time point following the first time point to monitor the prediction result at the first time point helps reduce the computational complexity of performance monitoring for the terminal device, for example, it helps reduce the number of calculations.

[0208] As shown in Figure 9, multiple prediction times and multiple performance monitoring times in the time domain are illustrated. The arrows in Figure 9 indicate that the prediction times and performance monitoring times associated with each other can be used by the terminal device to monitor whether the prediction results obtained at the prediction time are accurate.

[0209] In some embodiments, the terminal device needs to continuously determine the accuracy of the downlink reference signal resource prediction, or in other words, the terminal device needs to continuously monitor the prediction performance of the downlink reference signal resource. In this scenario, the terminal device can send a first message or a first report to the network device after each monitoring, such as reporting the accuracy (accurate or inaccurate) of a prediction or reporting a prediction result and the corresponding monitoring result; the terminal device can also send a first message or a first report to the network device after multiple monitoring (e.g., 10 times, 50 times, etc.), such as reporting the accuracy rate of multiple predictions (e.g., 50%, 80%, etc.) or reporting multiple prediction results and the corresponding monitoring results.

[0210] In some embodiments, the terminal device can determine the accuracy of downlink reference signal resource prediction within a certain time window. In other words, the terminal device only needs to monitor the prediction performance of downlink reference signal resources within a certain time window, and does not monitor it outside of that time window. The following describes a scheme for the terminal device to perform performance monitoring within the first time window, taking this time window as the first time window.

[0211] In some embodiments, the determination of the accuracy of downlink reference signal resource prediction is performed within a first time window. That is, the terminal device can determine the accuracy of the downlink reference signal resource prediction by comparing the K best downlink reference signal resources in the predicted resource set obtained within the first time window with the M best downlink reference signal resources in the measured monitoring resource set. In other words, the terminal device needs to monitor the model's performance within the first time window, but not outside the first time window.

[0212] This application does not limit the configuration method of the first time window in its embodiments. In some embodiments, the first time window is configured by the network device. In some embodiments, the first time window is predefined or preconfigured. In some embodiments, the first time window is determined based on network device configuration information and predefined information (e.g., network device configuration time domain start time, protocol predefined duration).

[0213] This application does not limit the method of indicating the first time window in its embodiments. In some embodiments, the first time window is indicated by its time-domain start position and its time-domain end position. In some embodiments, the first time window is indicated by its time-domain start position and its duration.

[0214] In some embodiments, the first time window can be indicated by the absolute time in the system. This application embodiment does not limit the absolute time. Exemplarily, the absolute time can be indicated by one or more of the following: Coordinated Universal Time (UTC), system frame number, subframe number, slot number, and symbol number.

[0215] Taking the first time window as an example, indicated by its time-domain start and end positions, both the time-domain start and end positions can be absolute times within the system. In some embodiments, the time-domain start and end positions of the first time window have the same form; for example, both can be indicated by the system frame number, or both by the time slot number, or both by the subframe number and the time slot number, etc.

[0216] Taking the time domain start position and duration indication of the first time window as an example, the time domain start position of the first time window can be the absolute time in the system.

[0217] In some embodiments, the duration of the first time window may be predefined by the protocol. In some embodiments, the duration of the first time window may be configured by the network device.

[0218] In some embodiments, the duration of the first time window can be indicated by a timer. For example, the terminal device can start the timer at the beginning of the first time window in the time domain, and the duration of the timer is equal to the duration of the first time window. That is, the terminal device can start the timer when the model performance monitoring function is activated. As an example, the timer can be started when the terminal device completes the measurement of the downlink reference signal resources in the monitoring resource set associated with the timer for the first time.

[0219] In some embodiments, when the timer expires, the terminal device will stop (not continue) measuring the downlink reference signal resources in the monitored resource set. In some embodiments, when the timer expires, the terminal device will no longer determine the accuracy of the downlink reference signal resource prediction. In some embodiments, when the timer expires, the terminal device will stop (not continue) measuring the downlink reference signal resources in the monitored resource set and will no longer determine the accuracy of the downlink reference signal resource prediction. That is, when the timer expires, the terminal device considers the performance monitoring time window to have ended, so the terminal device will stop performing operations related to determining the accuracy of the downlink reference signal resource prediction.

[0220] The method embodiments of this application have been described in detail above with reference to Figures 1 to 9. The apparatus embodiments of this application will be described in detail below with reference to Figures 10 to 12. It should be understood that the descriptions of the method embodiments correspond to the descriptions of the apparatus embodiments; therefore, any parts not described in detail can be referred to the preceding method embodiments.

[0221] Figure 10 is a schematic diagram of the structure of a terminal device provided in an embodiment of this application. The terminal device 1000 shown in Figure 10 includes a transmitting module 1010. The transmitting module 1010 can be used to transmit first information or a first report to a network device. The first report is used to determine the first information, and the first information is used to indicate the accuracy of downlink reference signal resource prediction. The accuracy of the downlink reference signal resource prediction is determined based on K downlink reference signal resources in the prediction resource set and M downlink reference signal resources in the monitoring resource set, where K is greater than or equal to 1, M is greater than or equal to 1, the prediction results of the K downlink reference signal resources are higher than or equal to the prediction results of other downlink reference signal resources in the prediction resource set, and the measurement results of the M downlink reference signal resources are higher than or equal to the measurement results of other downlink reference signal resources in the monitoring resource set.

[0222] In some embodiments, if one or more of the K downlink reference signal resources belong to the M downlink reference signal resources during a downlink reference signal resource prediction process, then the current downlink reference signal resource prediction is accurate.

[0223] In some embodiments, the downlink reference signal resources included in the monitoring resource set are the same as those included in the prediction resource set.

[0224] In some embodiments, if one or more of the K downlink reference signal resources are quasi-co-located with one or more of the M downlink reference signal resources during a downlink reference signal resource prediction process, then the current downlink reference signal resource prediction is accurate.

[0225] In some embodiments, whether one or more of the K downlink reference signal resources are quasi-co-located with one or more of the M downlink reference signal resources is determined by a first signaling, which is used to configure the quasi-co-location relationship between the two reference signal resources.

[0226] In some embodiments, the type of downlink reference signal resources included in the monitoring resource set is different from the type of downlink reference signal resources included in the prediction resource set.

[0227] In some embodiments, the downlink reference signal resources included in the monitoring resource set are SSB resources, and the downlink reference signal resources included in the prediction resource set are CSI-RS resources.

[0228] In some embodiments, if one or more of the K downlink reference signal resources have the same quasi-co-located source as one or more of the M downlink reference signal resources during a downlink reference signal resource prediction process, then the current downlink reference signal resource prediction is accurate.

[0229] In some embodiments, the downlink reference signal resources included in the monitoring resource set are a subset of the downlink reference signal resources included in the prediction resource set.

[0230] In some embodiments, if the difference between the prediction result of one or more of the K downlink reference signal resources and the measurement result of one or more of the M downlink reference signal resources is less than or equal to a first threshold during a downlink reference signal resource prediction process, then the current downlink reference signal resource prediction is accurate.

[0231] In some embodiments, the first threshold is determined based on the difference in transmit power between one or more of the K downlink reference signal resources and one or more of the M downlink reference signal resources.

[0232] In some embodiments, K and / or M are configured by the network device.

[0233] In some embodiments, K and / or M are determined by the network device based on capability information reported by the terminal device, wherein the capability information is used to indicate the range of values ​​for K and / or M supported by the terminal device.

[0234] In some embodiments, the terminal device further includes: a receiving module 1020, configured to receive a first configuration sent by the network device, the first configuration being configured to report measurement results of downlink reference signal resources in the monitoring resource set, wherein the first configuration includes one or more of the following: one or more identifiers for indicating the configuration for reporting prediction results of downlink reference signal resources in the prediction resource set; one or more indicators indicating the prediction performance of downlink reference signal resources.

[0235] In some embodiments, the terminal device further includes a processing module, the processing module being configured to: measure downlink reference signal resources in the monitoring resource set at one or more times; predict downlink reference signal resources in the prediction resource set at a first time; wherein the prediction result at the first time is monitored by the measurement result at a second time, the second time being the time closest to the first time among the one or more times.

[0236] In some embodiments, the second moment occurs after the first moment.

[0237] In some embodiments, the determination of the accuracy of the downlink reference signal resource prediction is performed within a first time window.

[0238] In some embodiments, the first time window is indicated by the time domain start position and the time domain end position of the first time window, or the first time window is indicated by the time domain start position and the duration of the first time window.

[0239] In some embodiments, the accuracy of the downlink reference signal resource prediction is determined by one or more of the following: the accuracy of the downlink reference signal resource prediction within the first time window; the number of times the downlink reference signal resource is correctly predicted within the first time window; and the number of times the downlink reference signal resource is incorrectly predicted within the first time window.

[0240] In some embodiments, the first report includes one or more of the following: prediction results of downlink reference signal resources in the prediction resource set; measurement results of downlink reference signal resources in the monitoring resource set.

[0241] In some embodiments, the transmitting module 1010 may be a transceiver 1230. The terminal device 1000 may also include a processor 1210 and a memory 1220, as shown in FIG12.

[0242] Figure 11 is a schematic diagram of the structure of a network device provided in an embodiment of this application. The network device 1100 shown in Figure 11 may include a receiving module 1110. The receiving module 1110 can be used to receive first information or a first report sent by a terminal device. The first report is used to determine the first information, which is used to indicate the accuracy of downlink reference signal resource prediction. The accuracy of the downlink reference signal resource prediction is determined based on K downlink reference signal resources in the prediction resource set and M downlink reference signal resources in the monitoring resource set, where K is greater than or equal to 1, M is greater than or equal to 1, the prediction results of the K downlink reference signal resources are higher than or equal to the prediction results of other downlink reference signal resources in the prediction resource set, and the measurement results of the M downlink reference signal resources are higher than or equal to the measurement results of other downlink reference signal resources in the monitoring resource set.

[0243] In some embodiments, if one or more of the K downlink reference signal resources belong to the M downlink reference signal resources during a downlink reference signal resource prediction process, then the current downlink reference signal resource prediction is accurate.

[0244] In some embodiments, the downlink reference signal resources included in the monitoring resource set are the same as those included in the prediction resource set.

[0245] In some embodiments, if one or more of the K downlink reference signal resources are quasi-co-located with one or more of the M downlink reference signal resources during a downlink reference signal resource prediction process, then the current downlink reference signal resource prediction is accurate.

[0246] In some embodiments, whether one or more of the K downlink reference signal resources are quasi-co-located with one or more of the M downlink reference signal resources is determined by a first signaling, which is used to configure the quasi-co-location relationship between the two reference signal resources.

[0247] In some embodiments, the type of downlink reference signal resources included in the monitoring resource set is different from the type of downlink reference signal resources included in the prediction resource set.

[0248] In some embodiments, the downlink reference signal resources included in the monitoring resource set are SSB resources, and the downlink reference signal resources included in the prediction resource set are CSI-RS resources.

[0249] In some embodiments, if one or more of the K downlink reference signal resources have the same quasi-co-located source as one or more of the M downlink reference signal resources during a downlink reference signal resource prediction process, then the current downlink reference signal resource prediction is accurate.

[0250] In some embodiments, the downlink reference signal resources included in the monitoring resource set are a subset of the downlink reference signal resources included in the prediction resource set.

[0251] In some embodiments, if the difference between the prediction result of one or more of the K downlink reference signal resources and the measurement result of one or more of the M downlink reference signal resources is less than or equal to a first threshold during a downlink reference signal resource prediction process, then the current downlink reference signal resource prediction is accurate.

[0252] In some embodiments, the first threshold is determined based on the difference in transmit power between one or more of the K downlink reference signal resources and one or more of the M downlink reference signal resources.

[0253] In some embodiments, K and / or M are configured by the network device.

[0254] In some embodiments, K and / or M are determined by the network device based on capability information reported by the terminal device, wherein the capability information is used to indicate the range of values ​​for K and / or M supported by the terminal device.

[0255] In some embodiments, the network device further includes: a sending module 1120, configured to send a first configuration to the terminal device, the first configuration being configured to report measurement results of downlink reference signal resources in the monitoring resource set, wherein the first configuration includes one or more of the following: one or more identifiers for indicating the configuration for reporting prediction results of downlink reference signal resources in the prediction resource set; one or more indicators indicating the prediction performance of downlink reference signal resources.

[0256] In some embodiments, the downlink reference signal resources in the monitoring resource set are measured at one or more times, and the downlink reference signal resources in the prediction resource set are predicted at a first time, wherein the prediction result at the first time is monitored by the measurement result at a second time, the second time being the time closest to the first time among the one or more times.

[0257] In some embodiments, the second moment occurs after the first moment.

[0258] In some embodiments, the determination of the accuracy of the downlink reference signal resource prediction is performed within a first time window.

[0259] In some embodiments, the first time window is indicated by the time domain start position and the time domain end position of the first time window, or the first time window is indicated by the time domain start position and the duration of the first time window.

[0260] In some embodiments, the accuracy of the downlink reference signal resource prediction is determined by one or more of the following: the accuracy of the downlink reference signal resource prediction within the first time window; the number of times the downlink reference signal resource is correctly predicted within the first time window; and the number of times the downlink reference signal resource is incorrectly predicted within the first time window.

[0261] In some embodiments, the first report includes one or more of the following: prediction results of downlink reference signal resources in the prediction resource set; measurement results of downlink reference signal resources in the monitoring resource set.

[0262] In some embodiments, the receiving module 1110 may be a transceiver 1230. The network device 1100 may also include a processor 1210 and a memory 1220, as shown in FIG12.

[0263] Figure 12 is a schematic structural diagram of a communication device according to an embodiment of this application. The dashed lines in Figure 12 indicate that the unit or module is optional. This device 1200 can be used to implement the methods described in the above method embodiments. Device 1200 can be a chip, a terminal device, or a network device.

[0264] Apparatus 1200 may include one or more processors 1210. The processor 1210 may support apparatus 1200 in implementing the methods described in the preceding method embodiments. The processor 1210 may be a general-purpose processor or a special-purpose processor. For example, the processor may be a central processing unit (CPU). Alternatively, the processor may be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor.

[0265] The apparatus 1200 may further include one or more memories 1220. The memories 1220 store a program that can be executed by the processor 1210, causing the processor 1210 to perform the methods described in the preceding method embodiments. The memories 1220 may be independent of the processor 1210 or integrated within the processor 1210.

[0266] The device 1200 may also include a transceiver 1230. The processor 1210 can communicate with other devices or chips via the transceiver 1230. For example, the processor 1210 can send and receive data with other devices or chips via the transceiver 1230.

[0267] This application also provides a computer-readable storage medium for storing a program. This computer-readable storage medium can be applied to a terminal device or network device provided in this application embodiment, and the program causes a computer to execute the methods performed by the terminal device or network device in the various embodiments of this application.

[0268] This application also provides a computer program product. The computer program product includes a program. This computer program product can be applied to a terminal device or network device provided in the embodiments of this application, and the program causes a computer to execute the methods performed by the terminal device or network device in the various embodiments of this application.

[0269] This application also provides a computer program. This computer program can be applied to the terminal device or network device provided in this application, and the computer program causes the computer to execute the methods performed by the terminal device or network device in various embodiments of this application.

[0270] It should be understood that the terms "system" and "network" in this application can be used interchangeably. Furthermore, the terminology used in this application is only for explaining specific embodiments of the application and is not intended to limit the application. The terms "first," "second," "third," and "fourth," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish different objects, not to describe a specific order. In addition, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion.

[0271] In the embodiments of this application, the term "instruction" can be a direct instruction, an indirect instruction, or an indication of a relationship. For example, A instructing B can mean that A directly instructs B, such as B being able to obtain information through A; it can also mean that A indirectly instructs B, such as A instructing C, so B can obtain information through C; or it can mean that there is a relationship between A and B.

[0272] In the embodiments of this application, "B corresponding to A" means that B is associated with A, and B can be determined based on A. However, it should also be understood that determining B based on A does not mean that B is determined solely based on A; B can also be determined based on A and / or other information.

[0273] In the embodiments of this application, the term "correspondence" can indicate a direct or indirect correspondence between two things, or an association between two things, or a relationship such as instruction and being instructed, configuration and being configured.

[0274] In the embodiments of this application, the term "comprising" can refer to direct inclusion or indirect inclusion. Optionally, "comprising" in the embodiments of this application can be replaced with "instructing" or "used to determine". For example, "A includes B" can be replaced with "A instructs B" or "A is used to determine B".

[0275] In this application embodiment, "predefined" or "preconfigured" can be implemented by pre-storing corresponding codes, tables, or other means that can be used to indicate relevant information in the device (e.g., including terminal devices and network devices). This application does not limit the specific implementation method. For example, predefined can refer to what is defined in the protocol.

[0276] In this application embodiment, the "protocol" may refer to a standard protocol in the field of communication, such as the LTE protocol, the NR protocol, and related protocols applied to future communication systems. This application does not limit this.

[0277] In the embodiments of this application, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this document generally indicates that the preceding and following related objects have an "or" relationship.

[0278] In the various embodiments of this application, the order of the above-mentioned processes does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0279] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0280] The units described as separate components may or may not be physically separate. The 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 the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0281] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0282] In the above embodiments, implementation can be achieved entirely or partially through software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented entirely or partially 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, all or part of the processes or functions described in the embodiments of this application are generated. 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 from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can read or a data storage device such as a server or data center that integrates one or more available media. The available media may be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., digital video discs, DVDs) or semiconductor media (e.g., solid-state disks, SSDs), etc.

[0283] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for wireless communication, characterized in that, include: The terminal device sends a first message or a first report to the network device, wherein the first report is used to determine the first message, and the first message is used to indicate the accuracy of the downlink reference signal resource prediction; The accuracy of the downlink reference signal resource prediction is determined based on K downlink reference signal resources in the prediction resource set and M downlink reference signal resources in the monitoring resource set, where K is greater than or equal to 1 and M is greater than or equal to 1. The prediction results of the K downlink reference signal resources are higher than or equal to the prediction results of other downlink reference signal resources in the prediction resource set, and the measurement results of the M downlink reference signal resources are higher than or equal to the measurement results of other downlink reference signal resources in the monitoring resource set.

2. The method according to claim 1, characterized in that, If, during a downlink reference signal resource prediction process, one or more of the K downlink reference signal resources belong to the M downlink reference signal resources, then the current downlink reference signal resource prediction is accurate.

3. The method according to claim 2, characterized in that, The downlink reference signal resources included in the monitoring resource set are the same as those included in the prediction resource set.

4. The method according to any one of claims 1-3, characterized in that, If, during a downlink reference signal resource prediction process, one or more of the K downlink reference signal resources are quasi-co-located with one or more of the M downlink reference signal resources, then the current downlink reference signal resource prediction is accurate.

5. The method according to claim 4, characterized in that, Whether one or more of the K downlink reference signal resources are quasi-co-located with one or more of the M downlink reference signal resources is determined by a first signaling, which is used to configure the quasi-co-location relationship between the two reference signal resources.

6. The method according to claim 4 or 5, characterized in that, The type of downlink reference signal resources included in the monitoring resource set is different from the type of downlink reference signal resources included in the prediction resource set.

7. The method according to any one of claims 4-6, characterized in that, The monitoring resource set includes downlink reference signal resources that are synchronization signal blocks (SSBs), and the prediction resource set includes downlink reference signal resources that are channel state information reference signals (CSI-RS).

8. The method according to any one of claims 1-7, characterized in that, If, during a downlink reference signal resource prediction process, one or more of the K downlink reference signal resources have the same quasi-co-addressable source as one or more of the M downlink reference signal resources, then the downlink reference signal resource prediction is accurate.

9. The method according to claim 8, characterized in that, The downlink reference signal resources included in the monitoring resource set are a subset of the downlink reference signal resources included in the prediction resource set.

10. The method according to any one of claims 1-9, characterized in that, If, during a downlink reference signal resource prediction process, the difference between the prediction result of one or more of the K downlink reference signal resources and the measurement result of one or more of the M downlink reference signal resources is less than or equal to a first threshold, then the downlink reference signal resource prediction is accurate.

11. The method according to claim 10, characterized in that, The first threshold is determined based on the difference in transmit power between one or more of the K downlink reference signal resources and one or more of the M downlink reference signal resources.

12. The method according to any one of claims 1-11, characterized in that, The K and / or the M are configured in the network device.

13. The method according to claim 12, characterized in that, The K and / or M are determined by the network device based on the capability information reported by the terminal device, and the capability information is used to indicate the range of values ​​for K and / or M supported by the terminal device.

14. The method according to any one of claims 1-13, characterized in that, The method further includes: The terminal device receives a first configuration sent by the network device, the first configuration being used to report the measurement results of downlink reference signal resources in the monitoring resource set, wherein the first configuration includes one or more of the following: One or more identifiers are used to indicate the configuration of the prediction results for the downlink reference signal resources in the reported prediction resource set; One or more metrics that indicate the performance of downlink reference signal resource prediction.

15. The method according to any one of claims 1-14, characterized in that, The method further includes: The terminal device measures the downlink reference signal resources in the monitoring resource set at one or more times; The terminal device predicts the downlink reference signal resources in the prediction resource set at a first moment; The prediction result at the first moment is monitored by the measurement result at the second moment, which is the moment closest to the first moment among the one or more moments.

16. The method according to claim 15, characterized in that, The second moment is after the first moment.

17. The method according to any one of claims 1-16, characterized in that, The accuracy of the downlink reference signal resource prediction is determined within the first time window.

18. The method according to claim 17, characterized in that, The first time window is indicated by the time domain start position and the time domain end position of the first time window, or the first time window is indicated by the time domain start position and the duration of the first time window.

19. The method according to claim 17 or 18, characterized in that, The accuracy of the downlink reference signal resource prediction is determined by one or more of the following: The accuracy of downlink reference signal resource prediction within the first time window; The number of times downlink reference signal resources are correctly predicted within the first time window; The number of times downlink reference signal resources are incorrectly predicted within the first time window.

20. The method according to any one of claims 1-19, characterized in that, The first report includes one or more of the following information: The prediction results of the downlink reference signal resources in the prediction resource set; The measurement results of the downlink reference signal resources in the monitoring resource set.

21. A method for wireless communication, characterized in that, include: The network device receives first information or a first report sent by the terminal device, wherein the first report is used to determine the first information, and the first information is used to indicate the accuracy of the downlink reference signal resource prediction; The accuracy of the downlink reference signal resource prediction is determined based on K downlink reference signal resources in the prediction resource set and M downlink reference signal resources in the monitoring resource set, where K is greater than or equal to 1 and M is greater than or equal to 1. The prediction results of the K downlink reference signal resources are higher than or equal to the prediction results of other downlink reference signal resources in the prediction resource set, and the measurement results of the M downlink reference signal resources are higher than or equal to the measurement results of other downlink reference signal resources in the monitoring resource set.

22. The method according to claim 21, characterized in that, If, during a downlink reference signal resource prediction process, one or more of the K downlink reference signal resources belong to the M downlink reference signal resources, then the current downlink reference signal resource prediction is accurate.

23. The method according to claim 22, characterized in that, The downlink reference signal resources included in the monitoring resource set are the same as those included in the prediction resource set.

24. The method according to any one of claims 21-23, characterized in that, If, during a downlink reference signal resource prediction process, one or more of the K downlink reference signal resources are quasi-co-located with one or more of the M downlink reference signal resources, then the current downlink reference signal resource prediction is accurate.

25. The method according to claim 24, characterized in that, Whether one or more of the K downlink reference signal resources are quasi-co-located with one or more of the M downlink reference signal resources is determined by a first signaling, which is used to configure the quasi-co-location relationship between the two reference signal resources.

26. The method according to claim 24 or 25, characterized in that, The type of downlink reference signal resources included in the monitoring resource set is different from the type of downlink reference signal resources included in the prediction resource set.

27. The method according to any one of claims 24-26, characterized in that, The monitoring resource set includes downlink reference signal resources that are synchronization signal blocks (SSBs), and the prediction resource set includes downlink reference signal resources that are channel state information reference signals (CSI-RS).

28. The method according to any one of claims 21-27, characterized in that, If, during a downlink reference signal resource prediction process, one or more of the K downlink reference signal resources have the same quasi-co-addressable source as one or more of the M downlink reference signal resources, then the downlink reference signal resource prediction is accurate.

29. The method according to claim 28, characterized in that, The downlink reference signal resources included in the monitoring resource set are a subset of the downlink reference signal resources included in the prediction resource set.

30. The method according to any one of claims 21-29, characterized in that, If, during a downlink reference signal resource prediction process, the difference between the prediction result of one or more of the K downlink reference signal resources and the measurement result of one or more of the M downlink reference signal resources is less than or equal to a first threshold, then the downlink reference signal resource prediction is accurate.

31. The method according to claim 30, characterized in that, The first threshold is determined based on the difference in transmit power between one or more of the K downlink reference signal resources and one or more of the M downlink reference signal resources.

32. The method according to any one of claims 21-31, characterized in that, The K and / or the M are configured in the network device.

33. The method according to claim 32, characterized in that, The K and / or M are determined by the network device based on the capability information reported by the terminal device, and the capability information is used to indicate the range of values ​​for K and / or M supported by the terminal device.

34. The method according to any one of claims 21-33, characterized in that, The method further includes: The network device sends a first configuration to the terminal device, the first configuration being used to report the measurement results of downlink reference signal resources in the monitoring resource set, wherein the first configuration includes one or more of the following: One or more identifiers are used to indicate the configuration of the prediction results for the downlink reference signal resources in the reported prediction resource set; One or more metrics that indicate the performance of downlink reference signal resource prediction.

35. The method according to any one of claims 21-34, characterized in that, The downlink reference signal resources in the monitoring resource set are measured at one or more times, and the downlink reference signal resources in the prediction resource set are predicted at a first time. The prediction result at the first time is monitored using the measurement result at a second time, which is the time closest to the first time among the one or more times.

36. The method according to claim 35, characterized in that, The second moment is after the first moment.

37. The method according to any one of claims 21-36, characterized in that, The accuracy of the downlink reference signal resource prediction is determined within the first time window.

38. The method according to claim 37, characterized in that, The first time window is indicated by the time domain start position and the time domain end position of the first time window, or the first time window is indicated by the time domain start position and the duration of the first time window.

39. The method according to claim 37 or 38, characterized in that, The accuracy of the downlink reference signal resource prediction is determined by one or more of the following: The accuracy of downlink reference signal resource prediction within the first time window; The number of times downlink reference signal resources are correctly predicted within the first time window; The number of times downlink reference signal resources are incorrectly predicted within the first time window.

40. The method according to any one of claims 21-39, characterized in that, The first report includes one or more of the following information: The prediction results of the downlink reference signal resources in the prediction resource set; The measurement results of the downlink reference signal resources in the monitoring resource set.

41. A terminal device, characterized in that, include: The sending module is used to send first information or a first report to the network device, wherein the first report is used to determine the first information, and the first information is used to indicate the accuracy of the downlink reference signal resource prediction; The accuracy of the downlink reference signal resource prediction is determined based on K downlink reference signal resources in the prediction resource set and M downlink reference signal resources in the monitoring resource set, where K is greater than or equal to 1 and M is greater than or equal to 1. The prediction results of the K downlink reference signal resources are higher than or equal to the prediction results of other downlink reference signal resources in the prediction resource set, and the measurement results of the M downlink reference signal resources are higher than or equal to the measurement results of other downlink reference signal resources in the monitoring resource set.

42. The terminal device according to claim 41, characterized in that, If, during a downlink reference signal resource prediction process, one or more of the K downlink reference signal resources belong to the M downlink reference signal resources, then the current downlink reference signal resource prediction is accurate.

43. The terminal device according to claim 42, characterized in that, The downlink reference signal resources included in the monitoring resource set are the same as those included in the prediction resource set.

44. The terminal device according to any one of claims 41-43, characterized in that, If, during a downlink reference signal resource prediction process, one or more of the K downlink reference signal resources are quasi-co-located with one or more of the M downlink reference signal resources, then the current downlink reference signal resource prediction is accurate.

45. The terminal device according to claim 44, characterized in that, Whether one or more of the K downlink reference signal resources are quasi-co-located with one or more of the M downlink reference signal resources is determined by a first signaling, which is used to configure the quasi-co-location relationship between the two reference signal resources.

46. ​​The terminal device according to claim 44 or 45, characterized in that, The type of downlink reference signal resources included in the monitoring resource set is different from the type of downlink reference signal resources included in the prediction resource set.

47. The terminal device according to any one of claims 44-46, characterized in that, The monitoring resource set includes downlink reference signal resources that are synchronization signal blocks (SSBs), and the prediction resource set includes downlink reference signal resources that are channel state information reference signals (CSI-RS).

48. The terminal device according to any one of claims 41-47, characterized in that, If, during a downlink reference signal resource prediction process, one or more of the K downlink reference signal resources have the same quasi-co-addressable source as one or more of the M downlink reference signal resources, then the downlink reference signal resource prediction is accurate.

49. The terminal device according to claim 48, characterized in that, The downlink reference signal resources included in the monitoring resource set are a subset of the downlink reference signal resources included in the prediction resource set.

50. The terminal device according to any one of claims 41-49, characterized in that, If, during a downlink reference signal resource prediction process, the difference between the prediction result of one or more of the K downlink reference signal resources and the measurement result of one or more of the M downlink reference signal resources is less than or equal to a first threshold, then the downlink reference signal resource prediction is accurate.

51. The terminal device according to claim 50, characterized in that, The first threshold is determined based on the difference in transmit power between one or more of the K downlink reference signal resources and one or more of the M downlink reference signal resources.

52. The terminal device according to any one of claims 41-51, characterized in that, The K and / or the M are configured in the network device.

53. The terminal device according to claim 52, characterized in that, The K and / or M are determined by the network device based on the capability information reported by the terminal device, and the capability information is used to indicate the range of values ​​for K and / or M supported by the terminal device.

54. The terminal device according to any one of claims 41-53, characterized in that, The terminal device also includes: A receiving module is configured to receive a first configuration sent by the network device, the first configuration being used to report measurement results of downlink reference signal resources in the monitoring resource set, wherein the first configuration includes one or more of the following: One or more identifiers are used to indicate the configuration of the prediction results for the downlink reference signal resources in the reported prediction resource set; One or more metrics that indicate the performance of downlink reference signal resource prediction.

55. The terminal device according to any one of claims 41-54, characterized in that, The terminal device further includes a processing module, the processing module being used for: Measure the downlink reference signal resources in the monitoring resource set at one or more times; Predict the downlink reference signal resources in the predicted resource set at the first moment; The prediction result at the first moment is monitored by the measurement result at the second moment, which is the moment closest to the first moment among the one or more moments.

56. The terminal device according to claim 55, characterized in that, The second moment is after the first moment.

57. The terminal device according to any one of claims 41-56, characterized in that, The accuracy of the downlink reference signal resource prediction is determined within the first time window.

58. The terminal device according to claim 57, characterized in that, The first time window is indicated by the time domain start position and the time domain end position of the first time window, or the first time window is indicated by the time domain start position and the duration of the first time window.

59. The terminal device according to claim 57 or 58, characterized in that, The accuracy of the downlink reference signal resource prediction is determined by one or more of the following: The accuracy of downlink reference signal resource prediction within the first time window; The number of times downlink reference signal resources are correctly predicted within the first time window; The number of times downlink reference signal resources are incorrectly predicted within the first time window.

60. The terminal device according to any one of claims 41-59, characterized in that, The first report includes one or more of the following information: The prediction results of the downlink reference signal resources in the prediction resource set; The measurement results of the downlink reference signal resources in the monitoring resource set.

61. A network device, characterized in that, include: A receiving module is configured to receive first information or a first report sent by a terminal device, wherein the first report is used to determine the first information, and the first information is used to indicate the accuracy of the downlink reference signal resource prediction. The accuracy of the downlink reference signal resource prediction is determined based on K downlink reference signal resources in the prediction resource set and M downlink reference signal resources in the monitoring resource set, where K is greater than or equal to 1 and M is greater than or equal to 1. The prediction results of the K downlink reference signal resources are higher than or equal to the prediction results of other downlink reference signal resources in the prediction resource set, and the measurement results of the M downlink reference signal resources are higher than or equal to the measurement results of other downlink reference signal resources in the monitoring resource set.

62. The network device according to claim 61, characterized in that, If, during a downlink reference signal resource prediction process, one or more of the K downlink reference signal resources belong to the M downlink reference signal resources, then the current downlink reference signal resource prediction is accurate.

63. The network device according to claim 62, characterized in that, The downlink reference signal resources included in the monitoring resource set are the same as those included in the prediction resource set.

64. The network device according to any one of claims 61-63, characterized in that, If, during a downlink reference signal resource prediction process, one or more of the K downlink reference signal resources are quasi-co-located with one or more of the M downlink reference signal resources, then the current downlink reference signal resource prediction is accurate.

65. The network device according to claim 64, characterized in that, Whether one or more of the K downlink reference signal resources are quasi-co-located with one or more of the M downlink reference signal resources is determined by a first signaling, which is used to configure the quasi-co-location relationship between the two reference signal resources.

66. The network device according to claim 64 or 65, characterized in that, The type of downlink reference signal resources included in the monitoring resource set is different from the type of downlink reference signal resources included in the prediction resource set.

67. The network device according to any one of claims 64-66, characterized in that, The monitoring resource set includes downlink reference signal resources that are synchronization signal blocks (SSBs), and the prediction resource set includes downlink reference signal resources that are channel state information reference signals (CSI-RS).

68. The network device according to any one of claims 61-67, characterized in that, If, during a downlink reference signal resource prediction process, one or more of the K downlink reference signal resources have the same quasi-co-addressable source as one or more of the M downlink reference signal resources, then the downlink reference signal resource prediction is accurate.

69. The network device according to claim 68, characterized in that, The downlink reference signal resources included in the monitoring resource set are a subset of the downlink reference signal resources included in the prediction resource set.

70. The network device according to any one of claims 61-69, characterized in that, If, during a downlink reference signal resource prediction process, the difference between the prediction result of one or more of the K downlink reference signal resources and the measurement result of one or more of the M downlink reference signal resources is less than or equal to a first threshold, then the downlink reference signal resource prediction is accurate.

71. The network device according to claim 70, characterized in that, The first threshold is determined based on the difference in transmit power between one or more of the K downlink reference signal resources and one or more of the M downlink reference signal resources.

72. The network device according to any one of claims 61-71, characterized in that, The K and / or the M are configured in the network device.

73. The network device according to claim 72, characterized in that, The K and / or M are determined by the network device based on the capability information reported by the terminal device, and the capability information is used to indicate the range of values ​​for K and / or M supported by the terminal device.

74. The network device according to any one of claims 61-73, characterized in that, The network device also includes: The sending module is configured to send a first configuration to the terminal device, the first configuration being used to report the measurement results of downlink reference signal resources in the monitoring resource set, wherein the first configuration includes one or more of the following: One or more identifiers are used to indicate the configuration of the prediction results for the downlink reference signal resources in the reported prediction resource set; One or more metrics that indicate the performance of downlink reference signal resource prediction.

75. The network device according to any one of claims 61-74, characterized in that, The downlink reference signal resources in the monitoring resource set are measured at one or more times, and the downlink reference signal resources in the prediction resource set are predicted at a first time. The prediction result at the first time is monitored using the measurement result at a second time, which is the time closest to the first time among the one or more times.

76. The network device according to claim 75, characterized in that, The second moment is after the first moment.

77. The network device according to any one of claims 61-76, characterized in that, The accuracy of the downlink reference signal resource prediction is determined within the first time window.

78. The network device according to claim 77, characterized in that, The first time window is indicated by the time domain start position and the time domain end position of the first time window, or the first time window is indicated by the time domain start position and the duration of the first time window.

79. The network device according to claim 77 or 78, characterized in that, The accuracy of the downlink reference signal resource prediction is determined by one or more of the following: The accuracy of downlink reference signal resource prediction within the first time window; The number of times downlink reference signal resources are correctly predicted within the first time window; The number of times downlink reference signal resources are incorrectly predicted within the first time window.

80. The network device according to any one of claims 61-79, characterized in that, The first report includes one or more of the following information: The prediction results of the downlink reference signal resources in the prediction resource set; The measurement results of the downlink reference signal resources in the monitoring resource set.

81. A terminal device, characterized in that, The device includes a transceiver, a memory, and a processor. The memory stores a program, and the processor invokes the program in the memory and controls the transceiver to receive or send signals so that the terminal device performs the method as described in any one of claims 1-20.

82. A network device, characterized in that, The device includes a transceiver, a memory, and a processor. The memory stores a program, and the processor invokes the program in the memory and controls the transceiver to receive or transmit signals so that the network device performs the method as described in any one of claims 21-40.

83. An apparatus, characterized in that, Includes a processor for calling a program from memory to cause the apparatus to perform the method as described in any one of claims 1-20 or 21-40.

84. A chip, characterized in that, Includes a processor for calling a program from memory, causing a device on which the chip is mounted to perform the method as described in any one of claims 1-20 or 21-40.

85. A computer-readable storage medium, characterized in that, It contains a program that causes a computer to perform the method as described in any one of claims 1-20 or 21-40.

86. A computer program product, characterized in that, Includes a program that causes a computer to perform the method as described in any one of claims 1-20 or 21-40.

87. A computer program, characterized in that, The computer program causes the computer to perform the method as described in any one of claims 1-20 or 21-40.

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