Communication method and apparatus

Abstract

A communication method and apparatus, which are applied to the technical field of communications. The method comprises: receiving first information, wherein the first information is used for instructing a terminal device to determine a first monitoring report; on the basis of N prediction results and M measurement results, determining a first indicator, wherein N and M are positive integers greater than or equal to 1, the M measurement results include a first measurement result, the N prediction results include a first prediction result, and a first time unit corresponding to the first measurement result has a first temporal relationship with a second time unit corresponding to the first prediction result; and on the basis of the first indicator, determining the first monitoring report. In the embodiments of the present application, by means of standardizing a binding manner between prediction results and measurement results, for example, determining the binding manner between the prediction results and the measurement results on the basis of a first temporal relationship, it is possible to effectively prevent interference with performance indicator calculations caused by the prediction results being unable to correspond to the measurement results on a one-to-one basis due to the number of prediction results being inconsistent with the number of measurement results, thereby enabling a UE to more precisely calculate a performance indicator.

Description

A communication method and apparatus

[0001] Cross-references to related applications

[0002] This application claims priority to Chinese Patent Application No. 202510102701.4, filed on January 21, 2025, entitled "A Communication Method and Apparatus", the entire contents of which are incorporated herein by reference; and to Chinese Patent Application No. 202510392571.2, filed on March 28, 2025, entitled "A Communication Method and Apparatus", the entire contents of which are incorporated herein by reference. Technical Field

[0003] This application relates to the field of communication technology, and in particular to a communication method and apparatus. Background Technology

[0004] Currently, during communication transmission, if the number of predicted results and the number of measured results within the observation window are inconsistent, scenarios may arise where one predicted result corresponds to multiple measured results, or vice versa. There is currently no effective solution for this scenario, often resulting in inaccurate calculations due to the large time-domain distance between predicted and measured results. Furthermore, a new resource counting method is urgently needed for this scenario. Summary of the Invention

[0005] This application provides a communication method and apparatus to improve the performance of random access.

[0006] In a first aspect, embodiments of this application provide a communication method that can be applied to a first device. The first device may be a terminal, or a device within the terminal (e.g., a module, a communication module, a circuit or chip responsible for communication functions (such as a modem chip, also known as a baseband chip, or a system-on-chip (SoC) chip or system-in-package (SIP) chip containing a modem core), a chip system, or a processor), or a logical node, logical module, or software capable of implementing all or part of the terminal's functions.

[0007] The method may include: determining a first count of a first resource based on the number of prediction windows, or the number of prediction windows and the number of observation windows, wherein the first count corresponds to a resource count, and / or a port count within the resource. Through the above scheme, this embodiment of the application, by standardizing the resource / port counting method corresponding to resources, enables network devices and terminals to align storage capabilities, effectively improving the utilization rate of storage resources on the terminal side.

[0008] In one possible approach, the first resource is the first monitoring resource corresponding to the first monitoring report, and the first count is determined based on the number of prediction windows. Through this method, embodiments of this application provide a resource / port counting method for resources in a monitoring scenario, enabling network devices and terminals to align storage capabilities and effectively improving the utilization rate of storage resources on the terminal side.

[0009] In one possible approach, the first count is determined by one or more of the following: the number of prediction windows corresponding to the first inference report, the number of pairings between the prediction results in the first inference report and the first monitoring resource, the number of first inference reports corresponding to the first monitoring report, a first capability coefficient, the number of observation windows corresponding to the first inference report, or the number of prediction windows corresponding to the first monitoring report and the number of observation windows corresponding to the first monitoring report; the first inference report is an inference report associated with the first monitoring report. In this way, embodiments of this application provide a method for determining the first count in a monitoring scenario. For example, embodiments of this application can select appropriate calculation parameters based on actual conditions to calculate the first count, effectively adapting to various scenario requirements, making it more flexible and applicable.

[0010] In one possible manner, the first capability coefficient is predefined; or, the first capability coefficient is determined by the first device; or, the first capability coefficient is determined by the second device.

[0011] In one possible manner, the first count is one of the following counting methods:

[0012] The first count is the number of prediction windows corresponding to the first inference report; the first count is the number of pairings between the prediction results in the first inference report and the first monitoring resource; the first count is the product of the following: the number of prediction windows corresponding to the first inference report, and the number of first inference reports corresponding to the first monitoring report; the first count is the product of the following: the prediction results in the first inference report, the number of pairings between the first monitoring resources, and the number of first inference reports corresponding to the first monitoring report; the first count is the product of the following: the number of prediction windows corresponding to the first inference report, and the first capability coefficient; the first count is the product of the following: the prediction results in the first inference report, the number of pairings between the first monitoring resources, and the number of pairings between the first monitoring resources. The first count is the product of the following multiple terms: the number of pairings between the first inference report and the first monitoring resource; or, the first count is the product of the following multiple terms: the number of prediction windows corresponding to the first inference report, the number of first inference reports corresponding to the first monitoring report, and the first capability coefficient; or, the first count is the product of the following multiple terms: the number of pairings between the prediction results in the first inference report and the first monitoring resource, the number of first inference reports corresponding to the first monitoring report, and the first capability coefficient; the first count is the sum of the number of observation windows in the first inference report and the number of prediction windows in the first monitoring report; the first count is the sum of the number of observation windows in the first inference report and the number of observation windows in the first monitoring report; wherein, the first inference report is associated with the first monitoring report. Through this method, the various methods for determining the first count listed in the embodiments of this application can effectively adapt to various scenario requirements, are more flexible, and have stronger applicability.

[0013] As an example, in an embodiment of this application, the observation window of the first monitoring report can be replaced with the prediction window of the first inference report.

[0014] As an example, the first counting method varies depending on the scenario in this application embodiment, and is not limited to the following situations:

[0015] Case 1: When the first monitored resource is a semi-persistent resource and / or a periodic resource, the first count can be one of the following counting methods:

[0016] (1) The first count is the number of prediction windows corresponding to the first inference report;

[0017] (2) The first count is the number of pairs between the prediction results in the first inference report and the first monitoring resource;

[0018] (3) The first count is the product of the following: the number of prediction windows corresponding to the first inference report, and the number of the first inference reports corresponding to the first monitoring report;

[0019] (4) The first count is the product of the following: the prediction results in the first inference report, the number of pairings between the first monitoring resources, and the number of the first inference reports corresponding to the first monitoring report;

[0020] (5) The first count is the product of the following: the number of prediction windows corresponding to the first inference report, and the first capability coefficient;

[0021] (6) The first count is the product of the following: the prediction result in the first inference report, the number of pairings between the first monitoring resources, and the first capability coefficient;

[0022] (7) The first count is the product of the following: the number of prediction windows corresponding to the first inference report, the number of first inference reports corresponding to the first monitoring report, and the first capability coefficient; or,

[0023] (8) The first count is the product of the following: the number of pairs between the prediction results in the first inference report and the first monitoring resource, the number of the first inference reports corresponding to the first monitoring report, and the first capability coefficient.

[0024] Scenario 2: When the first monitoring resource and the inference resource corresponding to the first inference report are the same resource, and are indicated in the same channel state information report configuration, the first count can be one of the following counting methods:

[0025] (1) The first count is the sum of the number of observation windows in the first inference report and the number of prediction windows in the first monitoring report.

[0026] (2) The first count is the sum of the number of observation windows in the first inference report and the number of observation windows in the first monitoring report.

[0027] In one possible approach, the method further includes: sending first information, the first information being used to indicate the counting method supported by the first device.

[0028] As an example, when the first device in this application embodiment does not support storing the channel matrix or the precoding matrix, the first information indicates that the first counting method supported by the first device includes the first count being the number of prediction windows in the first inference report; as another example, when the first device supports storing the content of the channel matrix or the precoding matrix, the first information indicates that the first counting method supported by the first device includes the first count being the product of the number of prediction windows in the first inference report and the first capability coefficient.

[0029] In one possible approach, the first resource is a first training resource corresponding to a first training configuration, and the first count is determined based on the number of prediction windows and / or the number of observation windows. Through this method, embodiments of this application provide a resource / port counting method for resources corresponding to training scenarios, enabling network devices and terminals to align storage capabilities and effectively improving the utilization rate of storage resources on the terminal side.

[0030] In one possible approach, the first training resource includes model input resources and model output resources; a first count of the first training resource is the sum of a second count of the model input resources and a third count of the model output resources, wherein the model input resources and the model output resources are different; or, the first count of the first training resource is the second count of the model input, wherein the model input resources and the model output resources are the same; or the first count of the first training resource is the third count of the model output, wherein the model input resources and the model output resources are the same. Through this approach, embodiments of this application provide a method for determining the first count in a training scenario. For example, embodiments of this application can select appropriate calculation parameters based on actual conditions to calculate the first count, effectively adapting to various scenario requirements, making it more flexible and applicable.

[0031] As an example, in this embodiment of the application, the first training resource can be split into two resources, such as model input resources and model output resources. In this case, the model input resources and model output resources are different, and the model input resources and model output resources can be configured in different channel state information report configurations.

[0032] As an example, in the embodiments of this application, the first training resource can be the same resource. For example, the first training resource can also be used for both model input resources and model output resources. That is, the model input resources and model output resources are the same, and the model input resources and model output resources can be configured in the same channel state information configuration.

[0033] In one possible manner, the second count is one of the following counting methods:

[0034] The second count is the number of observation windows corresponding to the first training report; the second count is the value of the temporal dimension of the model input data; the second count is the product of the following multiple terms: the number of observation windows corresponding to the first training report, and the second capability coefficient; or, the second count is the product of the following multiple terms: the value of the temporal dimension of the model input data, and the second capability coefficient. In this way, the embodiments of this application provide a method for determining the second count, which can effectively adapt to various scenario requirements, is more flexible, and has stronger applicability.

[0035] In one possible manner, the second capability coefficient is predefined; or, the second capability coefficient is reported by the second device; or, the second capability coefficient is determined by the first device.

[0036] In one possible approach, the second count is determined by one or more of the following: the number of observation windows corresponding to the first training report, the temporal dimension corresponding to the model input data, or the second capability coefficient.

[0037] In one possible manner, the third count is one of the following counting methods:

[0038] The third count is the number of prediction windows corresponding to the first training report; the third count is the temporal dimension of the model output data; the third count is the product of the following multiple terms: the number of prediction windows corresponding to the first training report, and the third capability coefficient; or, the third count is the product of the following multiple terms: the temporal dimension of the model output data, and the third capability coefficient. In this way, the embodiments of this application provide a method for determining the third count, which can effectively adapt to various scenario requirements, is more flexible, and has stronger applicability.

[0039] In one possible manner, the third capability coefficient is predefined; or, the second capability coefficient is determined by the first device; or, the second capability coefficient is determined by the second device.

[0040] In one possible approach, the third count is determined by one or more of the following: the number of prediction windows corresponding to the first training report, the temporal dimension corresponding to the model output data, or the third capability coefficient.

[0041] In one possible approach, the method further includes sending a second message indicating the counting method supported by the first device.

[0042] In one possible approach, the CPU usage start time corresponding to the first monitoring report corresponds to the earliest time unit among all resource opportunities corresponding to the first monitoring resource, and the number of all resource opportunities corresponding to the first monitoring resource is determined based on the number of prediction windows corresponding to the first inference report; the first inference report is an inference report associated with the first monitoring report. Through this approach, embodiments of this application further provide a CPU timeline usage method, thereby making CPU usage more consistent with the resource counting design of embodiments of this application, and better ensuring communication performance.

[0043] As an example, the CPU usage start time corresponding to the first monitoring report corresponds to the earliest time unit among all resource occasions corresponding to the first monitored resource. This can be understood as the first monitored resource including multiple resources, and the earliest symbol / time unit among the earliest resources is selected to correspond to the CPU usage start time. It should be noted that "resource occasion" is only a translation of CSI-RS occasions; any other applicable Chinese names for CSI-RS occasions are within the protection scope of this application. Furthermore, the time unit in this application embodiment can also be a symbol, which is not limited here.

[0044] In one possible approach, the number of all resource opportunities corresponding to the first monitored resource is equal to the number of prediction windows corresponding to the first inference report; or, the number of all resource opportunities corresponding to the first monitored resource is the product of the following: the number of prediction windows corresponding to the first inference report, and the number of first inference reports corresponding to the first monitoring report.

[0045] In one possible approach, the prediction results in the first prediction report are paired with the first monitoring resource in the following manner: the first prediction result is paired with the first measurement result, wherein the first time unit corresponding to the first measurement result and the second time unit corresponding to the first prediction result have a first time relationship; the N prediction results in the first prediction report include the first prediction result, and the M measurement results of the first monitoring resource include the first measurement result.

[0046] Secondly, embodiments of this application provide a communication method that can be applied to a second device. The second device is, for example, a network device, or a component within a network device, such as a communication module, circuitry or chip responsible for communication functions (e.g., a modem chip, also known as a baseband chip, or a SoC chip or SIP chip containing a modem core, a chip system, or a processor, etc.) or other functional module applicable to the network device. This chip (or chip system) or functional module can implement the functions of the network device. This chip (or chip system) or other functional module, for example, may be disposed within the network device and can also be a logic module or software capable of implementing all or part of the functions of the network device. Optionally, the network device may include an access network device and / or a core network device. Optionally, the access network device may be an open radio access network (ORAN) architecture or an ORAN architecture; or, the access network device may be a centralized unit (CU), a distributed unit (DU), or a radio unit (RU) under an ORAN architecture. The access network device may be located on the ground, or it may be a non-ground device such as a satellite or an airborne aircraft.

[0047] The method may include: determining a first count of a first resource based on the number of prediction windows, or the number of prediction windows and the number of observation windows, the first count corresponding to a resource count, and / or a port count within the resource.

[0048] In one possible approach, the first resource is the first monitoring resource corresponding to the first monitoring report, and the first count is determined based on the number of prediction windows.

[0049] In one possible approach, the first count is determined by one or more of the following: the number of prediction windows corresponding to the first inference report, the number of pairings between the prediction results in the first inference report and the first monitoring resource, the number of first inference reports corresponding to the first monitoring report, a first capability coefficient, the number of observation windows corresponding to the first inference report, or the number of prediction windows corresponding to the first monitoring report, and the number of observation windows corresponding to the first monitoring report; the first inference report is an inference report associated with the first monitoring report.

[0050] In one possible manner, the first capability coefficient is predefined; or, the first capability coefficient is determined by the first device; or, the first capability coefficient is determined by the second device.

[0051] In one possible manner, the first count is one of the following counting methods:

[0052] The first count is the number of prediction windows corresponding to the first inference report; the first count is the number of pairings between the prediction results in the first inference report and the first monitoring resource; the first count is the product of the following: the number of prediction windows corresponding to the first inference report, and the number of first inference reports corresponding to the first monitoring report; the first count is the product of the following: the prediction results in the first inference report, the number of pairings between the first monitoring resources, and the number of first inference reports corresponding to the first monitoring report; the first count is the product of the following: the number of prediction windows corresponding to the first inference report, and the first capability coefficient; the first count is the product of the following: the prediction results in the first inference report, the number of pairings between the first monitoring resources, and the number of pairings between the first monitoring resources. The first count is the product of the following: the number of pairings between the first inference report and the first capability coefficient; the first count is the product of the following: the number of prediction windows corresponding to the first inference report, the number of first inference reports corresponding to the first monitoring report, and the first capability coefficient; or, the first count is the product of the following: the number of pairings between the prediction results in the first inference report and the first monitoring resource, the number of first inference reports corresponding to the first monitoring report, and the first capability coefficient; the first count is the sum of the number of observation windows in the first inference report and the number of prediction windows in the first monitoring report; the first count is the sum of the number of observation windows in the first inference report and the number of observation windows in the first monitoring report; wherein, the first inference report is associated with the first monitoring report.

[0053] As an example, in an embodiment of this application, the observation window of the first monitoring report can be replaced with the prediction window of the first inference report.

[0054] As an example, the first counting method varies depending on the scenario in this application embodiment, and is not limited to the following situations:

[0055] Case 1: When the first monitored resource is a semi-persistent resource and / or a periodic resource, the first count can be one of the following counting methods:

[0056] (1) The first count is the number of prediction windows corresponding to the first inference report;

[0057] (2) The first count is the number of pairs between the prediction results in the first inference report and the first monitoring resource;

[0058] (3) The first count is the product of the following: the number of prediction windows corresponding to the first inference report, and the number of the first inference reports corresponding to the first monitoring report;

[0059] (4) The first count is the product of the following: the prediction results in the first inference report, the number of pairings between the first monitoring resources, and the number of the first inference reports corresponding to the first monitoring report;

[0060] (5) The first count is the product of the following: the number of prediction windows corresponding to the first inference report, and the first capability coefficient;

[0061] (6) The first count is the product of the following: the prediction result in the first inference report, the number of pairings between the first monitoring resources, and the first capability coefficient;

[0062] (7) The first count is the product of the following: the number of prediction windows corresponding to the first inference report, the number of first inference reports corresponding to the first monitoring report, and the first capability coefficient; or,

[0063] (8) The first count is the product of the following: the number of pairs between the prediction results in the first inference report and the first monitoring resource, the number of the first inference reports corresponding to the first monitoring report, and the first capability coefficient.

[0064] Scenario 2: When the first monitoring resource and the inference resource corresponding to the first inference report are the same resource, and are indicated in the same channel state information report configuration, the first count can be one of the following counting methods:

[0065] (1) The first count is the sum of the number of observation windows in the first inference report and the number of prediction windows in the first monitoring report.

[0066] (2) The first count is the sum of the number of observation windows in the first inference report and the number of observation windows in the first monitoring report.

[0067] In one possible approach, the method further includes receiving first information, the first information being used to indicate the counting mode supported by the first device.

[0068] As an example, in an embodiment of this application, when the first device does not support storing the channel matrix or the precoding matrix, the first information indicates that the first counting method supported by the first device includes the first count being the number of prediction windows in the first inference report; as another example, when the first device supports storing the contents of the channel matrix or the precoding matrix, the first information indicates that the first counting method supported by the first device includes the first count being the product of the number of prediction windows in the first inference report and the first capability coefficient, so that after receiving the first information, the second device can know the counting method supported by the first device and use the counting method supported by the first device to perform counting.

[0069] In one possible approach, the first resource is a first training resource corresponding to a first training configuration, and the first count is determined based on the number of prediction windows and / or the number of observation windows.

[0070] In one possible approach, the first training resource includes model input resources and model output resources; a first count of the first training resource is the sum of a second count of the model input resources and a third count of the model output resources, and the model input resources are different from the model output resources; or, the first count of the first training resource is the second count of the model input, and the model input resources are the same as the model output resources; or the first count of the first training resource is the third count of the model output, and the model input resources are the same as the model output resources.

[0071] As an example, in this embodiment of the application, the first training resource can be split into two resources, such as model input resources and model output resources. In this case, the model input resources and model output resources are different, and the model input resources and model output resources can be configured in different channel state information report configurations.

[0072] As an example, in the embodiments of this application, the first training resource can be the same resource. For example, the first training resource can also be used for both model input resources and model output resources. That is, the model input resources and model output resources are the same, and the model input resources and model output resources can be configured in the same channel state information configuration.

[0073] In one possible manner, the second count is one of the following counting methods:

[0074] The second count is the number of observation windows corresponding to the first training report; the second count is the value of the temporal dimension of the model input data; the second count is the product of the following multiple terms: the number of observation windows corresponding to the first training report, and the second capability coefficient; or, the second count is the product of the following multiple terms: the value of the temporal dimension of the model input data, and the second capability coefficient.

[0075] In one possible manner, the second capability coefficient is predefined; or, the second capability coefficient is reported by the second device; or, the second capability coefficient is determined by the first device.

[0076] In one possible approach, the second count is determined by one or more of the following: the number of observation windows corresponding to the first training report, the temporal dimension corresponding to the model input data, or the second capability coefficient.

[0077] In one possible manner, the third count is one of the following counting methods:

[0078] The third count is the number of prediction windows corresponding to the first training report; the third count is the temporal dimension of the model output data; the third count is the product of the following multiple terms: the number of prediction windows corresponding to the first training report, and the third capability coefficient; or, the third count is the product of the following multiple terms: the temporal dimension of the model output data, and the third capability coefficient.

[0079] In one possible manner, the third capability coefficient is predefined; or, the second capability coefficient is determined by the first device; or, the second capability coefficient is determined by the second device.

[0080] In one possible approach, the third count is determined by one or more of the following: the number of prediction windows corresponding to the first training report, the temporal dimension corresponding to the model output data, or the third capability coefficient.

[0081] In one possible approach, the method further includes:

[0082] Receive second information, which indicates the counting method supported by the first device.

[0083] As an example, in a training scenario, the second information in this application embodiment may include, but is not limited to, the supported counting methods for the first count, the supported counting methods for the second count, the supported counting methods for the third count, and may further indicate whether the counting methods for the second and third counts are the same. This allows the second device, upon receiving the second information, to know the counting methods supported by the first device and to use those supported counting methods for counting.

[0084] In one possible approach, the CPU usage start time corresponding to the first monitoring report corresponds to the earliest time unit among all resource timings corresponding to the first monitoring resource, and the number of all resource timings corresponding to the first monitoring resource is determined based on the number of prediction windows corresponding to the first inference report; the first inference report is an inference report associated with the first monitoring report.

[0085] As an example, the CPU usage start time corresponding to the first monitoring report corresponds to the earliest time unit among all resource occasions corresponding to the first monitored resource. This can be understood as the first monitored resource including multiple resources, and the earliest symbol / time unit among the earliest resources is selected to correspond to the CPU usage start time. It should be noted that "resource occasion" is only a translation of CSI-RS occasions; any other applicable Chinese names for CSI-RS occasions are within the protection scope of this application. Furthermore, the time unit in this application embodiment can also be a symbol, which is not limited here.

[0086] In one possible approach, the number of all resource opportunities corresponding to the first monitored resource is equal to the number of prediction windows corresponding to the first inference report; or, the number of all resource opportunities corresponding to the first monitored resource is the product of the following: the number of prediction windows corresponding to the first inference report, and the number of first inference reports corresponding to the first monitoring report.

[0087] In one possible approach, the prediction results in the first prediction report are paired with the first monitoring resource in the following manner: the first prediction result is paired with the first measurement result, wherein the first time unit corresponding to the first measurement result and the second time unit corresponding to the first prediction result have a first time relationship; the N prediction results in the first prediction report include the first prediction result, and the M measurement results of the first monitoring resource include the first measurement result.

[0088] Thirdly, embodiments of this application provide a communication method that can be applied to a first device. The first device is, for example, a terminal device, or a component within a terminal device. For a component within a terminal device, please refer to the first aspect.

[0089] The method may include: receiving first information, the first information being used to instruct a terminal device to determine a first monitoring report; determining a first indicator based on N prediction results and M measurement results; wherein N and M are positive integers greater than or equal to 1; the M measurement results include the first measurement result, and the N prediction results include the first prediction result; a first time unit corresponding to the first measurement result and a second time unit corresponding to the first prediction result have a first time relationship; and determining the first monitoring report according to the first indicator. Through this method, the embodiments of this application, by standardizing the binding method between prediction results and measurement results, such as determining the binding method between prediction results and measurement results based on a first time relationship, can effectively avoid interference to performance indicator calculation when the number of prediction results and measurement results is inconsistent and cannot be matched one-to-one, enabling the UE to calculate performance indicators more accurately.

[0090] It is understood that the names used for prediction results in this application embodiment are merely examples, and any content with the same or similar function (or similar role) as the prediction result can be replaced. For example, the prediction result can be replaced with prediction information, prediction instance, or prediction time instance, etc., without limitation. Here, prediction time instance can represent the time corresponding to the prediction information / prediction result. Similarly, the names used for measurement results in this application embodiment are merely examples, and any content with the same or similar function (or similar role) as the measurement result can be replaced. For example, the measurement result can be replaced with monitoring occasion, CSI-RS transmission occasion for performance monitoring, monitoring time instance, monitoring instance, or measurement instance for performance monitoring, etc., without limitation. In this application embodiment, the term "CSI-RS transmission occasion" is merely an example. Any content with the same or similar function (or the same or similar role) as "CSI-RS transmission occasion" can be replaced. For example, "CSI-RS transmission occasion" can be replaced with "CSI-RS occasion" or "transmission occasion" to indicate the time of CSI-RS resource transmission. For BM, there are generally multiple CSI-RS resources transmitted in a CSI-RS occasion; for CSI, there is generally only one CSI-RS resource transmitted in a CSI-RS occasion, which is not limited here.

[0091] As an example, the first metric of this application includes, but is not limited to, performance monitoring metrics. For example, embodiments of this application can evaluate and monitor key data points of system, network, or application performance based on the performance monitoring metrics, thereby better helping to ensure a high-quality user experience and optimize network resources.

[0092] As an example, the first index determined by embodiments of this application based on N prediction results and M measurement results includes, but is limited to, the following cases:

[0093] Case 1: Based on N prediction results and M measurement results, the number of first indicators is determined to be one.

[0094] Scenario 2: Based on N prediction results and M measurement results, the number of first indicators is multiple.

[0095] In one possible approach, the first time unit corresponding to the first measurement result includes at least one of the following: a time unit for determining the location of a first set of measurement resources for the first measurement result; a time unit for the location of the Channel State Information (CSI) reference resource corresponding to the first measurement result; a time unit in which the first measurement result takes effect; and a CSI reference resource corresponding to the CSI report carrying the first prediction result bound to the first measurement result. Through this approach, embodiments of this application provide multiple scenarios for the first time unit, effectively adapting to different scenario requirements, offering greater flexibility and stronger applicability.

[0096] As an example, the first set of measurement resources in this application embodiment may include a set of resources in a wireless communication system for the UE to perform channel quality estimation, signal strength measurement, and interference assessment, including but not limited to synchronization signal blocks (SSBs), channel state information reference signals (CSI-RS), etc. For example, the UE can obtain the synchronization information of the cell by detecting the SSB and identify the interference situation of neighboring cells; as another example, the UE can generate a channel quality indicator (CQI), a precoding matrix indicator (PMI), and a rank indicator (RI) based on CSI-RS measurements and feed them back to the base station for downlink quality assessment and handover decision-making.

[0097] As an example, the time unit in this embodiment is used to define and synchronize the basic time intervals of various communication processes, including but not limited to subframes, slots, symbols, and frames. Optionally, the time unit containing the first measurement resource set may include, but is not limited to, the time unit corresponding to the NW transmitting CSI-RS, the time unit corresponding to the UE receiving CSI-RS, etc.

[0098] In one possible approach, the second time unit corresponding to the first prediction result includes at least one of the following: the time unit where the CSI reference resource corresponding to the first prediction result is located; the time unit in which the first prediction result takes effect; and the CSI reference resource corresponding to the CSI report carrying the first prediction result. This application provides various scenarios for the second time unit, effectively adapting to different scenario requirements, offering greater flexibility and applicability.

[0099] In one possible approach, the first time relationship between the first time unit and the second time unit includes at least one of the following: the time interval between the first time unit and the second time unit is less than or equal to a first time interval; the first time unit is the Xth time unit closest to the second time unit, where X is a positive integer; the first time unit is not later than the second time unit; the second time unit is the Yth time unit closest to the first time unit, where Y is a positive integer; or, the second time unit is not later than the first time unit. This application provides multiple first time relationships. Through this approach, this application can provide different schemes for determining the binding relationship between measurement results and prediction results based on different first time relationships, effectively enriching the ways in which this application determines the correspondence between prediction results and measurement results. This effectively adapts to different scenario requirements, is more flexible, and has stronger applicability.

[0100] As an example, in this embodiment of the application, when X is 1, the first time unit being the Xth time unit closest to the second time unit means that the first time unit is the time unit closest to the second time unit.

[0101] As an example, in this embodiment of the application, when Y is 1, the second time unit being the Y-th time unit closest to the first time unit means that the second time unit is the time unit closest to the first time unit. As an example, in this embodiment of the application, X and Y may be equal or unequal, and this is not limited here.

[0102] In one possible approach, the method further includes: determining M time units corresponding to M measurement results, and then determining a second time unit based on the first time unit corresponding to any one of the M measurement results. In this way, embodiments of this application provide a reference benchmark for determining the binding relationship between prediction results and measurement results. For example, embodiments of this application can determine the corresponding bound prediction results based on the measurement results, effectively adapting to scenarios where measurement results are of high importance, offering greater flexibility and stronger applicability.

[0103] In one possible approach, the method further includes: when multiple measurement results correspond to the same second time unit, selecting one time unit from the multiple measurement results as the first time unit. Through this approach, the embodiments of this application provide a solution for determining the same prediction result from multiple measurement results when determining the prediction result based on the measurement results. For example, the multiple measurement results can be further filtered; for instance, the optimal measurement result can be selected and bound to the corresponding prediction result, or a measurement result can be randomly selected and bound to the corresponding prediction result, thus improving adaptability.

[0104] As an example, when determining the second time unit based on the first time unit in this application embodiment, it can be determined by the first time relationship described above. For example, the second time unit includes, but is not limited to, the prediction time unit closest to the first time unit, or the prediction time unit whose time interval with the first time unit is less than or equal to the first time interval, etc., and is not limited here.

[0105] In one possible approach, the method further includes: determining N time units corresponding to N prediction results; and determining a first time unit based on a second time unit corresponding to any one of the N prediction results. In this way, embodiments of this application provide a reference benchmark for determining the binding relationship between prediction results and measurement results. For example, embodiments of this application can determine the corresponding bound measurement results based on the prediction results, effectively adapting to scenarios where prediction results are of high importance, offering greater flexibility and stronger applicability.

[0106] In one possible approach, the method further includes: determining a binding relationship between the forecast results used to generate the first indicator and the measurement results based on the first forecast report.

[0107] As an example, embodiments of this application can first find the corresponding N prediction results based on the first prediction report, and then further determine the corresponding measurement results based on the N prediction results found. For example, based on the first prediction report, N corresponding prediction results are found, and N time units corresponding to the N prediction results are determined. Then, based on the second time unit corresponding to any one of the N prediction results, a first time unit is determined, and the first measurement result corresponding to the first time unit is bound to the corresponding first prediction result.

[0108] In one possible approach, the method further includes: when multiple prediction results correspond to the same first time unit, selecting one time unit from the multiple prediction results as the second time unit. Through this approach, the embodiments of this application provide a solution for determining the same measurement result from multiple prediction results when determining the measurement result based on the prediction results. For example, the multiple prediction results can be further filtered; for instance, the optimal prediction result can be selected and bound to the corresponding measurement result, or a prediction result can be randomly selected and bound to the corresponding measurement result, thus improving adaptability.

[0109] As an example, when determining the first time unit based on the second time unit in this application embodiment, it can be determined by the first time relationship described above. For example, the first time unit includes, but is not limited to, the monitoring time unit closest to the second time unit, or the monitoring time unit whose time interval with the second time unit is less than or equal to the first time interval, etc., and is not limited here.

[0110] In one possible approach, the N prediction results are the N prediction results most recent to the first reference time unit corresponding to the first monitoring report. This embodiment of the application further provides a method for selecting the N prediction results.

[0111] As an example, in this application embodiment, a report can be determined first, and then N prediction results within it can be determined; or, in this application embodiment, N prediction results within multiple reports can be used as the N prediction results corresponding to the first monitoring report, etc., without limitation.

[0112] In one possible approach, the CPU occupancy start time corresponding to the first monitoring report corresponds to the earliest time unit in at least one first time unit, where the at least one first time unit is a first time unit determined based on the second time units corresponding to the N prediction results. Through this approach, embodiments of this application further provide a CPU timeline occupancy method, such as a method for determining the CPU occupancy start time, thereby making the CPU occupancy more consistent with the binding relationship between the prediction results and measurement results of embodiments of this application, and better ensuring communication performance.

[0113] In one possible approach, the CPU occupancy termination time corresponding to the first monitoring report is determined by one or more of the following methods: determining the CPU occupancy termination time based on the time when the first indicator calculation is completed; or, determining the CPU occupancy termination time based on the time when the CSI calculation is completed; or, determining the CPU occupancy termination time based on the last symbol of the PUSCH / PUCCH carrying the first monitoring report; or, the Z′ symbols of the last symbol of the time window for Channel State Information-Reference Signal (CSI-RS) transmission used for performance monitoring. Through this method, embodiments of this application further provide a CPU timeline occupancy method, such as a method for determining the CPU occupancy termination time, thereby making the CPU occupancy more consistent with the binding relationship between the prediction results and measurement results of embodiments of this application, and better ensuring communication performance.

[0114] As an example, Z′ in the embodiments of this application may include one or more of the following:

[0115] Case 1: Z′ represents the distance from the end time of the last symbol of the CSI-RS resource to the first symbol of the PUSCH carrying the CSI report.

[0116] Case 2: Z′ includes the time for calculating the first index.

[0117] Case 3: Z′ includes the time of packet assembly.

[0118] As an example, in communication systems such as 5G NR systems, a CSI-RS occasion refers to the time and frequency location of reference signal resource allocation used to measure channel state information. The time window for CSI-RS transmission can be configured by the base station, informing the user equipment (UE) when and where to monitor CSI-RS. A CSI-RS occasion can contain multiple OFDM symbols, depending on the configuration. In some configurations, CSI-RS does not occupy all symbols in the entire time slot, but only a portion of them. Z′ can represent the number of symbols counting backwards from the last symbol of this CSI-RS occasion. For example, if Z′ = 3, it means that the CPU occupies 3 symbols counting backwards from the last symbol of the CSI-RS occasion.

[0119] For example, suppose a time slot has 14 OFDM symbols and the CSI-RS occasion is configured to use symbols 5-9. Then: if Z' = 5, the CPU occupies the 14th symbol; if Z' = 4, the CPU occupies the 13th symbol.

[0120] In one possible approach, before determining the N time units corresponding to the N prediction results, the method further includes: determining a second reference time unit corresponding to the first prediction report based on the first reference time unit corresponding to the first monitoring report; the first prediction report includes the N prediction results.

[0121] In one possible manner, the first prediction report meets a third constraint, which includes, but is not limited to, one or more of the following: at least one of the N prediction results corresponds to a measurement result before the first reference time unit corresponding to the first monitoring report; or, the first prediction report contains at least one valid prediction result, and the measurement result corresponding to the valid prediction result is before the first reference time unit corresponding to the first monitoring report.

[0122] For example, in this embodiment of the application, the second reference time unit determined based on the first reference time unit corresponding to the first monitoring report is the second reference time unit 1. The second reference time unit 1 corresponds to prediction report 1. If none of the N prediction results included in the prediction report 1 corresponds to a measurement result before the CSI reference resource corresponding to the first monitoring report, or if all the prediction results included in the prediction report 1 are invalid prediction results, that is, the prediction results included in the prediction report 1 do not have a corresponding measurement result before the first reference time unit corresponding to the first monitoring report, then this embodiment of the application can discard the prediction report 1, search for another prediction report, and continue to determine whether the found prediction report meets the third constraint condition, until it is determined that the found prediction report meets the third constraint condition, then the prediction report that meets the third constraint condition is determined as the first prediction report.

[0123] In one possible approach, the first reference time unit includes one or more of the following: the uplink time unit where the first monitoring report is located; the CSI reference resource corresponding to the first monitoring report; or, a set of reference measurement resources for generating the first monitoring report. In this way, the embodiments of this application provide multiple scenarios for the first reference time unit, effectively adapting to different scenario requirements, making it more flexible and applicable.

[0124] As an example, the reference measurement resources included in the reference measurement resource set in this application embodiment may be the first, the last, or a specific reference measurement resource predefined / NW specified, without limitation here.

[0125] As an example, in the first reference time unit, this application embodiment may or may not send the first monitoring report, and no limitation is made here.

[0126] In one possible approach, the second reference time unit includes one or more of the following: the uplink time unit where the first prediction report is located; the CSI reference resource corresponding to the first prediction report; or the time unit corresponding to the reference prediction result included in the first prediction report. In this way, the embodiments of this application provide multiple scenarios for the second reference time unit, which can effectively adapt to different scenario requirements, making it more flexible and applicable.

[0127] As an example, the reference prediction result in the embodiments of this application may be the first, the last, any one, a predefined / NW-specified / determined specific reference prediction result, and is not limited here.

[0128] As an example, in the second reference time unit, this application embodiment may or may not send the first prediction report, and no limitation is made here.

[0129] In one possible approach, the second time unit satisfies a first constraint condition, which includes at least one of the following conditions: the first time unit corresponding to the second time unit is within the valid time range corresponding to the first monitoring report; the second time unit is within the valid time range corresponding to the first monitoring report. In this way, embodiments of this application provide a constraint condition for determining the binding relationship between prediction results and measurement results, such as a first constraint condition, which can make the binding relationship between the obtained prediction results and measurement results more effective, or make the prediction results and / or measurement results in the binding relationship more accurate and effective. Therefore, when determining the first indicator based on the prediction results and measurement results, the corresponding first indicator can be obtained more accurately and efficiently, reducing the error rate.

[0130] As an example, if the monitoring result corresponding to the prediction result closest to the first reference time unit is later than the prediction result, meaning the measurement result may be after the first reference time unit (i.e., not within the valid interval), then, according to the method described above, the UE can disregard the measurement result and its corresponding prediction result. In this case, the UE can look back for another prediction result, which is no longer the prediction result closest to the first reference time unit, but rather the prediction result closest to the first reference time unit that satisfies the first constraint condition.

[0131] In one possible approach, the first prediction result satisfies a second constraint condition, which includes at least one of the following conditions: the second reference time unit corresponding to the first prediction report is within a valid time range; the first prediction report includes the first prediction result; the time during which the first prediction result takes effect is within a valid time range; wherein the first prediction result is determined based on the first prediction report, or the first prediction result has been acquired by the terminal device. In this way, embodiments of this application provide a constraint condition for determining the binding relationship between prediction results and measurement results, such as a second constraint condition, which can make the binding relationship between the obtained prediction results and measurement results more effective, or make the prediction results and / or measurement results in the binding relationship more accurate and effective. Therefore, when determining the first indicator based on the prediction results and measurement results, the corresponding first indicator can be obtained more accurately and efficiently, reducing the error rate.

[0132] As an example, when the prediction result is determined based on the measurement result in this application embodiment, the second time unit needs to meet the following constraints. For example, when the inference result is reported (wherein, the second time unit is obtained by the UE through inference, or has been acquired by the UE), the second reference time unit corresponding to the found second time unit (e.g., the reporting time of the inference report) is not later than the first reference time unit (e.g., the reference resource corresponding to the monitoring report), or: the found second time unit is not later than the first reference time unit; as another example, when no inference result is reported, the found second time unit is not later than the first reference time unit. It is understood that the name of the inference result in this application embodiment is only an example, and any content with the same or similar function (or the same or similar role) as the inference result can be replaced. For example, the inference result can be replaced with the prediction result, the result obtained based on the AI ​​model, etc., which is not limited here. Similarly, the name of the prediction report in this application embodiment is only an example. Any content with the same or similar function as the prediction report can be replaced. For example, the prediction report can be replaced with the inference report, the CSI report containing the inference results, the UE report containing the inference results, etc., without limitation.

[0133] In one possible approach, the effective time range includes one or more of the following: no later than a first reference time unit corresponding to the first monitoring report; no earlier than a time unit indicating the location of control information in the first monitoring report; or, no earlier than a first offset time unit, the time interval between the first offset time unit and the time unit indicating the location of control information in the first monitoring report being a first time length; and no later than a second time offset unit, the time interval between the second time offset unit and the second reference time unit corresponding to the first prediction report being a second time length. In this way, embodiments of this application provide multiple effective time ranges, effectively adapting to different scenario requirements, offering greater flexibility and stronger applicability.

[0134] For example, one scenario in which the effective time range of this application embodiment is applied is that the second reference time unit corresponding to the first prediction report is no later than the second time offset unit, and the time interval between the second time offset unit and the second reference time unit corresponding to the first prediction report is the second time length. This allows the interval between the reference resources of the prediction report and the reference resources of the monitoring report in this application embodiment to be greater than or equal to the second time length, providing sufficient completion time for the calculation of the first indicator and / or packaging, etc., thus making it more adaptable.

[0135] In one possible approach, the method further includes: if the second time unit does not satisfy the first constraint and / or the second constraint, the first prediction result is not used for the calculation of the first indicator; or, if the first time unit does not satisfy the first constraint, the first measurement result is not used for the calculation of the first indicator.

[0136] As an example, when determining the prediction result based on the measurement result, the embodiments of this application may first filter the multiple measurement results obtained, select the measurement results that meet the first constraint condition, and then determine the corresponding prediction result for the measurement results that meet the condition; or, when determining the prediction result based on the measurement result, the corresponding prediction result may first be determined for each of the multiple measurement results obtained, and then the prediction results corresponding to the measurement results that do not meet the first constraint condition may be removed.

[0137] As an example, in this embodiment of the application, when determining the measurement result based on the prediction result, the corresponding measurement result can be determined for each of the multiple prediction results obtained, and then the measurement result corresponding to the prediction result that does not meet the first constraint condition can be removed.

[0138] In one possible approach, N satisfies at least one of the following conditions: the maximum value of N is configured or indicated by the network; or, N is preset by the protocol. This approach enriches the methods for determining the value of N in the embodiments of this application, making it more adaptable.

[0139] In one possible approach, M satisfies at least one of the following conditions: M is configured or indicated by the network; or M is preset by the protocol. This approach enriches the methods for determining the value of M in the embodiments of this application, making it more adaptable.

[0140] Understandably, this is to prevent the UE from addressing the issue of not being able to obtain some valid resources based on the implementation. For example, if the first resource associated with a certain predicted instance is invalid, and the UE obtains measurement information of a resource that satisfies a first temporal relationship at a distance from the predicted instance based on implementation filtering (e.g.), then NW configuration N and / or N is still feasible.

[0141] Fourthly, this application provides a communication device. In some examples, the communication device may be a terminal or a component within a terminal device. For a component within a terminal device, please refer to the first aspect. This communication device possesses the functions described in the first aspect.

[0142] In one possible embodiment, the communication device includes modules, units, or means that perform the operations involved in any of the first aspects described above. These modules, units, or means can be implemented in software, hardware, or a combination of both. For example, the communication device includes an interface unit and a processing unit. The interface unit can be used to transmit and receive signals to enable communication between the communication device and other devices; the processing unit can be used to perform some internal operations of the communication device. The functions performed by the processing unit and the interface unit can correspond to the operations involved in any of the first aspects described above.

[0143] In some implementations, the communication device may be the first device in the first aspect. The communication device includes an interface unit and a processing unit. The processing unit is configured to: determine a first count of a first resource based on the number of prediction windows, or the number of prediction windows and the number of observation windows, wherein the first count corresponds to a resource count, and / or a port count within the resource.

[0144] In one possible approach, the first resource is the first monitoring resource corresponding to the first monitoring report, and the first count is determined based on the number of prediction windows.

[0145] In one possible approach, the processing unit is configured to determine the first count using one or more of the following: the number of prediction windows corresponding to the first inference report, the number of pairings between the prediction results in the first inference report and the first monitoring resource, the number of first inference reports corresponding to the first monitoring report, a first capability coefficient, the number of observation windows corresponding to the first inference report, or the number of prediction windows corresponding to the first monitoring report, and the number of observation windows corresponding to the first monitoring report; the first inference report is an inference report associated with the first monitoring report.

[0146] In one possible manner, the first capability coefficient is predefined; or, the first capability coefficient is determined by the first device; or, the first capability coefficient is determined by the second device.

[0147] In one possible manner, the first count is one of the following counting methods:

[0148] The first count is the number of prediction windows corresponding to the first inference report;

[0149] The first count is the number of pairs between the prediction results in the first inference report and the first monitoring resource;

[0150] The first count is the product of the following: the number of prediction windows corresponding to the first inference report, and the number of the first inference reports corresponding to the first monitoring report;

[0151] The first count is the product of the following: the prediction results within the first inference report, the number of pairings between the first monitoring resources, and the number of the first inference reports corresponding to the first monitoring report;

[0152] The first count is the product of the following: the number of prediction windows corresponding to the first inference report, and the first capability coefficient;

[0153] The first count is the product of the following: the prediction results in the first inference report, the number of pairings between the first monitoring resources, and the first capability coefficient;

[0154] The first count is the product of the following: the number of prediction windows corresponding to the first inference report, the number of first inference reports corresponding to the first monitoring report, and the first capability coefficient; or,

[0155] The first count is the product of the following: the number of pairs between the prediction results in the first inference report and the first monitoring resource, the number of the first inference reports corresponding to the first monitoring report, and the first capability coefficient;

[0156] The first count is the sum of the number of observation windows in the first inference report and the number of prediction windows in the first monitoring report;

[0157] The first count is the sum of the number of observation windows in the first inference report and the number of observation windows in the first monitoring report;

[0158] The first reasoning report is associated with the first monitoring report.

[0159] In one possible approach, the processing unit is further configured to send first information via an interface unit, the first information being used to indicate the counting method supported by the first device.

[0160] In one possible approach, the first resource is a first training resource corresponding to a first training configuration, and the first count is determined based on the number of prediction windows and / or the number of observation windows.

[0161] In one possible approach, the first training resource includes model input resources and model output resources;

[0162] The first count of the first training resource is the sum of the second count of the model input resource and the third count of the model output resource, and the model input resource is different from the model output resource; or, the first count of the first training resource is the second count of the model input, and the model input resource is the same as the model output resource; or the first count of the first training resource is the third count of the model output, and the model input resource is the same as the model output resource.

[0163] In one possible manner, the second count is one of the following counting methods:

[0164] The second count is the number of observation windows corresponding to the first training report;

[0165] The second count is the value of the time domain dimension of the model input data;

[0166] The second count is the product of the following terms: the number of observation windows corresponding to the first training report, and the second capability coefficient; or,

[0167] The second count is the product of the following terms: the value of the time-domain dimension of the model input data, and the second capability coefficient.

[0168] In one possible manner, the second capability coefficient is predefined; or, the second capability coefficient is reported by the second device; or, the second capability coefficient is determined by the first device.

[0169] In one possible approach, the processing unit is configured to determine the second count using one or more of the following: the number of observation windows corresponding to the first training report, the temporal dimension corresponding to the model input data, or the second capability coefficient.

[0170] In one possible manner, the third count is one of the following counting methods:

[0171] The third count is the number of prediction windows corresponding to the first training report;

[0172] The third count is the temporal dimension of the model output data;

[0173] The third count is the product of the following terms: the number of prediction windows corresponding to the first training report, and the third capability coefficient; or,

[0174] The third count is the product of the following: the temporal dimension of the model output data, and the third capability coefficient.

[0175] In one possible manner, the third capability coefficient is predefined; or, the second capability coefficient is determined by the first device; or, the second capability coefficient is determined by the second device.

[0176] In one possible approach, the processing unit is configured to determine the third count using one or more of the following: the number of prediction windows corresponding to the first training report, the temporal dimension corresponding to the model output data, or a third capability coefficient.

[0177] In one possible approach, the processing unit is further configured to send second information via an interface unit, the second information indicating the counting method supported by the first device.

[0178] In one possible approach, the CPU usage start time corresponding to the first monitoring report corresponds to the earliest time unit among all resource timings corresponding to the first monitoring resource, and the number of all resource timings corresponding to the first monitoring resource is determined based on the number of prediction windows corresponding to the first inference report; the first inference report is an inference report associated with the first monitoring report.

[0179] In one possible approach, the number of all resource opportunities corresponding to the first monitored resource is equal to the number of prediction windows corresponding to the first inference report; or, the number of all resource opportunities corresponding to the first monitored resource is the product of the following: the number of prediction windows corresponding to the first inference report and the number of first inference reports corresponding to the first monitoring report.

[0180] In one possible approach, the processing unit is further configured to pair the first prediction result with the first measurement result, wherein the first time unit corresponding to the first measurement result and the second time unit corresponding to the first prediction result have a first time relationship; the N prediction results in the first prediction report include the first prediction result, and the M measurement results of the first monitoring resource include the first measurement result.

[0181] Fifthly, this application provides a communication device. In some examples, the communication device may be a network device or a component within a network device. For a component within a network device, please refer to the second aspect. This communication device possesses the functions described in the second aspect.

[0182] In one possible embodiment, the communication device includes modules, units, or means that perform the operations involved in any of the second aspects described above. These modules, units, or means can be implemented in software, hardware, or a combination of both. For example, the communication device includes an interface unit and a processing unit. The interface unit can be used to transmit and receive signals to enable communication between the communication device and other devices; the processing unit can be used to perform some internal operations of the communication device. The functions performed by the processing unit and the interface unit can correspond to the operations involved in any of the second aspects described above.

[0183] In some implementations, the communication device may be the second device in the second aspect. The communication device includes an interface unit and a processing unit. The processing unit is configured to: determine a first count of a first resource based on the number of prediction windows, or the number of prediction windows and the number of observation windows, wherein the first count corresponds to a resource count, and / or a port count within the resource.

[0184] In one possible approach, the first resource is the first monitoring resource corresponding to the first monitoring report, and the first count is determined based on the number of prediction windows.

[0185] In one possible approach, the processing unit is configured to determine the first count using one or more of the following: the number of prediction windows corresponding to the first inference report, the number of pairings between the prediction results in the first inference report and the first monitoring resource, the number of first inference reports corresponding to the first monitoring report, a first capability coefficient, the number of observation windows corresponding to the first inference report, or the number of prediction windows corresponding to the first monitoring report, and the number of observation windows corresponding to the first monitoring report; the first inference report is an inference report associated with the first monitoring report.

[0186] In one possible manner, the first capability coefficient is predefined; or, the first capability coefficient is determined by the first device; or, the first capability coefficient is determined by the second device.

[0187] In one possible manner, the first count is one of the following counting methods:

[0188] The first count is the number of prediction windows corresponding to the first inference report;

[0189] The first count is the number of pairs between the prediction results in the first inference report and the first monitoring resource;

[0190] The first count is the product of the following: the number of prediction windows corresponding to the first inference report, and the number of the first inference reports corresponding to the first monitoring report;

[0191] The first count is the product of the following: the prediction results within the first inference report, the number of pairings between the first monitoring resources, and the number of the first inference reports corresponding to the first monitoring report;

[0192] The first count is the product of the following: the number of prediction windows corresponding to the first inference report, and the first capability coefficient;

[0193] The first count is the product of the following: the prediction results in the first inference report, the number of pairings between the first monitoring resources, and the first capability coefficient;

[0194] The first count is the product of the following: the number of prediction windows corresponding to the first inference report, the number of first inference reports corresponding to the first monitoring report, and the first capability coefficient; or,

[0195] The first count is the product of the following: the number of pairs between the prediction results in the first inference report and the first monitoring resource, the number of the first inference reports corresponding to the first monitoring report, and the first capability coefficient;

[0196] The first count is the sum of the number of observation windows in the first inference report and the number of prediction windows in the first monitoring report;

[0197] The first count is the sum of the number of observation windows in the first inference report and the number of observation windows in the first monitoring report;

[0198] The first reasoning report is associated with the first monitoring report.

[0199] In one possible approach, the processing unit is further configured to receive first information via an interface unit, the first information being used to indicate the counting method supported by the first device.

[0200] In one possible approach, the first resource is a first training resource corresponding to a first training configuration, and the first count is determined based on the number of prediction windows and / or the number of observation windows.

[0201] In one possible approach, the first training resource includes model input resources and model output resources;

[0202] The first count of the first training resource is the sum of the second count of the model input resource and the third count of the model output resource, and the model input resource is different from the model output resource; or, the first count of the first training resource is the second count of the model input, and the model input resource is the same as the model output resource; or the first count of the first training resource is the third count of the model output, and the model input resource is the same as the model output resource.

[0203] In one possible manner, the second count is one of the following counting methods:

[0204] The second count is the number of observation windows corresponding to the first training report;

[0205] The second count is the value of the time domain dimension of the model input data;

[0206] The second count is the product of the following terms: the number of observation windows corresponding to the first training report, and the second capability coefficient; or,

[0207] The second count is the product of the following terms: the value of the time-domain dimension of the model input data, and the second capability coefficient.

[0208] In one possible manner, the second capability coefficient is predefined; or, the second capability coefficient is reported by the second device; or, the second capability coefficient is determined by the first device.

[0209] In one possible approach, the processing unit is configured to determine the second count using one or more of the following: the number of observation windows corresponding to the first training report, the temporal dimension corresponding to the model input data, or the second capability coefficient.

[0210] In one possible manner, the third count is one of the following counting methods:

[0211] The third count is the number of prediction windows corresponding to the first training report;

[0212] The third count is the temporal dimension of the model output data;

[0213] The third count is the product of the following terms: the number of prediction windows corresponding to the first training report, and the third capability coefficient; or,

[0214] The third count is the product of the following: the temporal dimension of the model output data, and the third capability coefficient.

[0215] In one possible manner, the third capability coefficient is predefined; or, the second capability coefficient is determined by the first device; or, the second capability coefficient is determined by the second device.

[0216] In one possible approach, the processing unit is configured to determine the third count using one or more of the following: the number of prediction windows corresponding to the first training report, the temporal dimension corresponding to the model output data, or a third capability coefficient.

[0217] In one possible approach, the processing unit is further configured to receive second information via an interface unit, the second information indicating the counting method supported by the first device.

[0218] In one possible approach, the CPU usage start time corresponding to the first monitoring report corresponds to the earliest time unit among all resource timings corresponding to the first monitoring resource, and the number of all resource timings corresponding to the first monitoring resource is determined based on the number of prediction windows corresponding to the first inference report; the first inference report is an inference report associated with the first monitoring report.

[0219] In one possible approach, the number of all resource opportunities corresponding to the first monitored resource is equal to the number of prediction windows corresponding to the first inference report; or, the number of all resource opportunities corresponding to the first monitored resource is the product of the following: the number of prediction windows corresponding to the first inference report, and the number of first inference reports corresponding to the first monitoring report.

[0220] In one possible approach, the processing unit is further configured to pair the first prediction result with the first measurement result, wherein the first time unit corresponding to the first measurement result and the second time unit corresponding to the first prediction result have a first time relationship; the N prediction results in the first prediction report include the first prediction result, and the M measurement results of the first monitoring resource include the first measurement result.

[0221] Sixthly, this application provides a communication device. In some examples, the communication device may be a terminal device or a component within a terminal device. For a component within a terminal device, please refer to the first aspect. This communication device possesses the functions described in the third aspect above.

[0222] In one possible embodiment, the communication device includes modules, units, or means corresponding to the operations involved in any of the third aspects described above. These modules, units, or means can be implemented in software, hardware, or a combination of both. For example, the communication device includes an interface unit and a processing unit. The interface unit can be used to send and receive signals to enable communication between the communication device and other devices; the processing unit can be used to perform some internal operations of the communication device. The functions performed by the processing unit and the interface unit can correspond to the operations involved in any of the third aspects described above.

[0223] In some implementations, the communication device may be the first device in the third aspect. The communication device includes an interface unit and a processing unit. The processing unit is configured to: receive first information, which instruct a terminal device to determine a first monitoring report; determine a first indicator based on N prediction results and M measurement results; wherein N and M are positive integers greater than or equal to 1; the M measurement results include the first measurement result, and the N prediction results include the first prediction result; a first time unit corresponding to the first measurement result and a second time unit corresponding to the first prediction result have a first time relationship; and determine the first monitoring report according to the first indicator.

[0224] In one possible design, the first time unit corresponding to the first measurement result includes at least one of the following:

[0225] The time unit in which the first set of measurement resources is located to determine the first measurement result;

[0226] The time unit in which the Channel State Information (CSI) reference resource corresponding to the first measurement result is located;

[0227] The time unit in which the first measurement result takes effect;

[0228] The CSI reference resource corresponding to the CSI report that carries the first prediction result bound to the first measurement result.

[0229] In one possible design, the second time unit corresponding to the first prediction result includes at least one of the following:

[0230] The time unit in which the CSI reference resource corresponding to the first prediction result is located;

[0231] The time unit in which the first prediction result takes effect;

[0232] The CSI reference resource corresponding to the CSI report carrying the first prediction result.

[0233] In one possible design, the first time relationship between the first time unit and the second time unit includes at least one of the following:

[0234] The time interval between the first time unit and the second time unit is less than or equal to the first time interval;

[0235] The first time unit is the Xth time unit closest to the second time unit, where X is a positive integer;

[0236] The first time unit is no later than the second time unit;

[0237] The second time unit is the Y-th time unit closest to the first time unit, where Y is a positive integer;

[0238] The second time unit is no later than the first time unit.

[0239] In one possible design, the processing unit is further used for:

[0240] Determine the M time units corresponding to the M measurement results; based on the first time unit corresponding to any one of the M measurement results, determine the second time unit.

[0241] In one possible design, the processing unit is further used for:

[0242] When multiple measurement results correspond to the same second time unit, one time unit is selected from the multiple measurement results as the first time unit.

[0243] In one possible design, the processing unit is further used for:

[0244] Determine N time units corresponding to N prediction results; determine the first time unit based on the second time unit corresponding to any one of the N prediction results.

[0245] In one possible design, the processing unit is further used for:

[0246] When multiple prediction results correspond to the same first time unit, one time unit is selected from the multiple prediction results as the second time unit.

[0247] In one possible design, the N prediction results are the N prediction results closest to the first reference time unit corresponding to the first monitoring report.

[0248] In one possible design, the CPU usage start time corresponding to the first monitoring report corresponds to the earliest time unit in at least one first time unit, and the at least one first time unit is a first time unit determined based on the second time units corresponding to the N prediction results.

[0249] In one possible design, the CPU usage termination time corresponding to the first monitoring report is determined by one or more of the following methods:

[0250] The CPU usage termination time is determined based on the time it takes to complete the calculation of the first indicator; or...

[0251] The CPU occupancy termination time is determined based on the time when the CSI calculation is completed; or...

[0252] The CPU occupancy termination time is determined based on the last symbol of the PUSCH / PUCCH carrying the first monitoring report; or,

[0253] The last symbol of the Z′ symbol used for CSI-RS occasions for performance monitoring.

[0254] In one possible design, the processing unit is further used for:

[0255] The second reference time unit corresponding to the first prediction report is determined based on the first reference time unit corresponding to the first monitoring report; the first prediction report includes the N prediction results.

[0256] In one possible manner, the first prediction report meets a third constraint, which includes, but is not limited to, one or more of the following: at least one of the N prediction results corresponds to a measurement result before the first reference time unit corresponding to the first monitoring report; or, the first prediction report contains at least one valid prediction result, and the measurement result corresponding to the valid prediction result is before the first reference time unit corresponding to the first monitoring report.

[0257] In one possible design, the first reference time unit includes one or more of the following:

[0258] The uplink time unit where the first monitoring report is located;

[0259] The CSI reference resource corresponding to the first monitoring report;

[0260] The reference measurement resource set used to generate the first monitoring report.

[0261] In one possible design, the second reference time unit includes one or more of the following:

[0262] The uplink time unit in which the first forecast report is located;

[0263] The CSI reference resource corresponding to the first forecast report;

[0264] The first prediction report includes the time unit corresponding to the reference prediction results.

[0265] In one possible design, the second time unit satisfies a first constraint, which includes at least one of the following conditions:

[0266] The first time unit corresponding to the second time unit is within the valid time range corresponding to the first monitoring report;

[0267] The second time unit is within the valid time range corresponding to the first monitoring report.

[0268] In one possible design, the first prediction result satisfies a second constraint, which includes at least one of the following conditions:

[0269] The second reference time unit corresponding to the first prediction report is within the valid time range, the first prediction report includes the first prediction result; the time during which the first prediction result takes effect is within the valid time range; wherein, the first prediction result is determined based on the first prediction report, or, the first prediction result has been acquired by the terminal device.

[0270] In one possible design, the effective time range includes one or more of the following:

[0271] Not later than the first reference time unit corresponding to the first monitoring report;

[0272] No earlier than the time unit in which the control information used to indicate the first monitoring report is located;

[0273] Not earlier than the first offset time unit, the time interval between the first offset time unit and the time unit where the control information used to indicate the first monitoring report is located is the first time length;

[0274] No later than the second time offset unit, the time interval between the second time offset unit and the second reference time unit corresponding to the first prediction report is the second time length.

[0275] In one possible design, the processing unit is further used for:

[0276] If the second time unit does not meet the first constraint, the first prediction result is not used for the calculation of the first index; or,

[0277] If the first time unit does not meet the first constraint condition, the first measurement result is not used for the calculation of the first index.

[0278] In one possible design, N satisfies at least one of the following conditions:

[0279] The maximum value of N is configured or indicated by the network;

[0280] N is preset by the protocol.

[0281] In a seventh aspect, this application provides a communication system that may include a first device and a second device. The first device may execute the communication method provided in the first or third aspect, and the second device may execute the communication method provided in the second aspect, or be used to obtain a first monitoring report determined by the first device.

[0282] In some possible designs, the first device is a terminal and the second device is an access network device.

[0283] Eighthly, this application provides a computer-readable storage medium storing a computer program or instructions, wherein when the computer program or instructions are executed, the method in any of the possible designs in the first to third aspects described above is implemented.

[0284] Ninthly, this application provides a computer program product comprising computer program code, wherein when the computer program code is run, the method in any of the possible designs in the first to third aspects described above is implemented.

[0285] In a tenth aspect, this application provides a chip that may include at least one processor for executing computer programs or instructions in a memory to implement the methods in any of the possible designs in the first to third aspects described above.

[0286] The technical effects that can be achieved by any of the second to tenth aspects mentioned above can be described with reference to the technical effects that can be achieved by any possible design in the first aspect mentioned above, and the repetitions will not be discussed. Attached Figure Description

[0287] Figure 1 is a schematic diagram of a CSI prediction inference process provided by related technologies;

[0288] Figure 2 is a schematic diagram of a CSI compressed inference process provided by related technologies;

[0289] Figure 3 is a schematic diagram of a BM case reasoning process provided by related technologies;

[0290] Figure 4 is a schematic diagram of a CSI processing rule provided by related technologies;

[0291] Figure 5 is a schematic diagram of another CSI processing rule provided by related technologies;

[0292] Figure 6 is a schematic diagram of CSI calculation time provided by related technologies;

[0293] Figures 7, 8, 9, and 10 are schematic diagrams of the network architecture provided in the embodiments of this application;

[0294] Figure 11 is a flowchart illustrating a communication method according to an embodiment of this application;

[0295] Figures 12, 13, 14, 15, and 16 are schematic diagrams of a binding method according to an embodiment of this application;

[0296] Figures 17, 18, 19, 20, and 21 are schematic diagrams of another binding method according to an embodiment of this application;

[0297] Figure 22 is a schematic diagram of the strategy flow of an application example of this application;

[0298] Figure 23 is a schematic diagram of a scenario in which multiple measurement results correspond to the same prediction result according to an embodiment of this application;

[0299] Figure 24 is a schematic diagram of a scenario in which a virtual CSI report is introduced according to an embodiment of this application;

[0300] Figure 25 is a schematic diagram of a scenario of NW indicator target test results according to an embodiment of this application;

[0301] Figure 26 is a schematic diagram of a scenario for NW based on large and small periodic cluster monitoring and measurement according to an embodiment of this application;

[0302] Figure 27 is a schematic diagram of the strategy flow of an application example two of the embodiments of this application;

[0303] Figure 28 is a schematic diagram of a scenario in which multiple prediction results correspond to the same measurement result according to an embodiment of this application;

[0304] Figure 29 is a schematic diagram of another scenario for introducing a virtual CSI report according to an embodiment of this application;

[0305] Figure 30 is a schematic diagram of a scenario showing the prediction result of an NW indicator target according to an embodiment of this application;

[0306] Figure 31 is a schematic diagram of the first scenario of determining the binding relationship based on the validity of prediction results and measurement results according to an embodiment of this application;

[0307] Figure 32 is a schematic diagram of the first scenario of determining the binding relationship based on the validity of prediction results and measurement results according to an embodiment of this application;

[0308] Figure 33 is a schematic diagram of the strategy flow of an application example four of this application;

[0309] Figure 34 is a schematic diagram of the strategy flow of an application example five of this application;

[0310] Figure 35 is a schematic diagram of a scenario for determining measurement results based on a prediction report according to an embodiment of this application;

[0311] Figure 36 is a schematic diagram of an application scenario of protocol content 1 according to an embodiment of this application;

[0312] Figure 37 is a schematic diagram of an application scenario of protocol content 2 according to an embodiment of this application;

[0313] Figure 38 is a schematic diagram of another application scenario of protocol content 2 in this application embodiment;

[0314] Figure 39 is a schematic diagram of another communication method according to an embodiment of this application;

[0315] Figure 40 is a schematic diagram of the structure of a communication device according to an embodiment of this application;

[0316] Figure 41 is a schematic diagram of the structure of a communication device according to an embodiment of this application. Detailed Implementation

[0317] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the embodiments of this application will be further described in detail below with reference to the accompanying drawings.

[0318] The relevant terms used in the embodiments of this application will be explained below. It should be noted that these explanations are for the purpose of making the embodiments of this application easier to understand, and should not be regarded as a limitation on the scope of protection claimed by this application.

[0319] 1. Channel State Information (CSI) Prediction: Time-domain CSI prediction based on the UE-side model.

[0320] Referring to Figure 1, an example of the inference process for CSI prediction provided by related technologies is shown. The CSI prediction model based on Artificial Intelligence (AI) or Machine Learning (ML) is used to predict future CSI based on historical CSI. The input / output CSI types can be: the original channel matrix or a precoded matrix. To generate the input to the CSI prediction model, some further preprocessing of the measured channels may be required; similarly, some further post-processing may be needed for the output of the CSI prediction model.

[0321] From the perspectives of training, inference, and monitoring, the data collection for CSI prediction use cases may include the following information:

[0322] (1) Training: Target CSI within the observation window / prediction window.

[0323] (2) Reasoning: Predicted CSI.

[0324] (3) Monitoring: Actual measured channel state information (Ground-truth CSI), calculated performance indicators (e.g., PMI difference), and performance monitoring output.

[0325] 2. CSI Compression: Spatial-frequency domain / spatial-temporal-frequency domain CSI compression based on a two-side model.

[0326] Referring to Figure 2, an example of the inference process for CSI compression provided by related technologies is shown. The AI / ML-based CSI generation part is used to generate CSI feedback information on the UE side; the AI / ML-based CSI reconstruction part is used to reconstruct the CSI on the gNB side based on the received CSI feedback information. The AI / ML model input (for the CSI generation part) / output (for the CSI reconstruction part) types can be: original channel matrix, precoding matrix. To generate the input to the CSI generation model, some further preprocessing on the measured channel may be required; similarly, some further post-processing may be required for the output of the CSI reconstruction model.

[0327] For CSI feedback enhancement use cases, the monitoring method can be:

[0328] (1) NW-side monitoring, such as estimating AI model / AI performance based on the target CSI reported by the UE (the actual channel estimate associated with the CSI report) and further generating monitoring decisions.

[0329] (2) UE-side monitoring: Based on the output of the CSI reconstruction model indicated by NW (the UE needs to associate it with the CSI report in an aligned format), or based on the output of the CSI reconstruction model of the UE-side agent, or directly estimating intermediate KPIs, or estimating monitoring output. NW can configure thresholds to instruct the UE to perform monitoring.

[0330] 3. Beam Management Enhancement

[0331] AI-based beam management enhancements can include sub-scenarios such as beam scanning matrix prediction and optimal beam prediction. AI / ML-based sparse beam prediction aims to improve accuracy; a possible workflow is as follows:

[0332] (1) Generation of the initial model. By having a certain number of UEs report the results of full-beam scanning of the Synchronizing signal block (SSB), a sparse scanning matrix is ​​trained. This matrix is ​​usually unique to each cell.

[0333] (2) The base station sends the sparse model to the UE (which can be done through System Information Block (SIB) messages, etc.), and the UE performs beam scanning in the P1 stage based on this matrix;

[0334] (3) Based on the sparse scanning results of the UE, the base station infers the optimal Channel State Information reference signal (CSI-RS) beam and starts P2 scanning of the UE, and the UE feeds back the optimal CSI-RS beam ID.

[0335] For example, the BM cases can be divided into two types: BM case1 and BM case2. Figure 3 illustrates examples of the inference process for beam management in BM-Case1 and BM-Case2. The model in the BM case is a one-side model, meaning the model is deployed on either the NW side or the UE side. For BM-Case1 and BM-Case2, the UE can report the prediction results to the NW based on the output of the UE-side model, or the NW can predict the Top-1 / N beams based on the reported measurements of the set B of NW-side models.

[0336] (a) BM Case 1: Predicting downlink beamform under Set A based on measurement results of Set B. One possible procedure is as follows:

[0337] (1) gNB scans Set B beam, gNB / UE obtains Set B measurement results;

[0338] (2) The AI ​​model on the gNB / UE side uses the measurement results of SetB as the model input to predict the TopK beam on Set A.

[0339] (b) BM Case 2: Predicting future downlink beamforming under Set A based on historical measurement results of Set B. One possible procedure is as follows:

[0340] (1) gNB scans Set B beam, gNB / UE obtains Set B measurement results;

[0341] (2) The AI ​​model on the gNB / UE side uses the measurement results of SetB as the model input to predict the TopK beam on Set A at future times.

[0342] For the UE side model, the model monitoring methods are divided into the following types:

[0343] (1)Type 1 (NW side monitoring):

[0344] For example, when based on network-side monitoring (NW side monitoring), the UE reports the NW's labels and inference outputs to calculate metrics; or, when based on UE-assisted monitoring (UE side monitoring), the UE reports performance metrics or events based on performance metrics.

[0345] (2) Type 2 (UE side monitoring): UE reports monitoring decisions (e.g., model selection / activation / deactivation / switching / fallback operations).

[0346] 4. CSI measurement:

[0347] CSI measurement refers to the process by which the receiver deciphers channel information based on a reference signal transmitted by the transmitter; that is, it uses channel estimation methods to estimate channel information. In communication systems (e.g., LTE or NR systems), network equipment needs to use CSI to determine the allocation of downlink data channel resources, modulation and coding schemes (MCS), and precoding configurations for terminal equipment. CSI can be understood as a type of channel information, reflecting channel characteristics and quality.

[0348] 5. CSI processing rules:

[0349] Among them, the UE can report the number N of CSI calculations that it can support being processed simultaneously, based on its own capabilities. CPU That is, the UE is configured with N CPU Each CPU (CSI processing unit) can be used to process CSI reports configured on all configuration CCs.

[0350] The CPU usage rules provided by the relevant technologies are as follows:

[0351] At a given symbol, if the computation reported by the CSI uses L CPUs, then the terminal device has N CPUs. CPU -L unused CPUs. For a given symbol, there are N... CPU If -L CPUs are not currently occupied, and N CSI reports require CPUs to be used starting from this symbol, where each CSI report (n = 0, ..., N-1) corresponds to a number of CPUs... Then the terminal device does not need to update NM lowest priority CSI reports, where 0≤M≤N, and M is a set of CSI reports that satisfy the condition that M is the lowest priority CSI report. The maximum value.

[0352] When there is not enough idle CPU, the UE does not need to update the CSI report, but rather does not need to provide feedback. When there is not enough CPU, the CSI report provided by the UE can be a cached previous CSI report or anything else, depending entirely on the UE implementation.

[0353] The amount of CPU used varies depending on the type of CSI report. For example, when performing time-frequency tracking for TRS, i.e., when the report quantity is configured to 'none' and the CSI-RS-ResourceSet contains the high-level parameter trs-Info, no CPU is used. CPU =0; L1-Reference Signal Received Power (RSRP) measurement, i.e., when reportQuantity is configured as 'Cell Resource Indicator (cri)-RSRP', 'ssb-Index-RSRP', or 'none' (and CSI-RS-ResourceSet does not contain the higher-layer parameter trs-Info), the CPU usage is 1, i.e., O. CPU =1. For CSI-ReportConfig high-level parameter reportQuantity of 'tdcp', and the latency Y is configured by the high-level parameter Y in the CSI report, O_CPU = (Y+1)÷X, where the value of X is reported by the UE capability. When reportQuantity is configured as 'cri-RI-PMI-CQI', 'cri-RI-i1', 'cri-RI-i1-CQI', 'cri-RI-CQI', or 'cri-RI-LI-PMI-CQI', O CPU =K s K here s This indicates the number of NZP CSI-RS resources in CMR.

[0354] When an AP CSI report is triggered, if there is no Physical Uplink Shared Channel (PUSCH) transmission and no CPU is occupied, and this CSI report is wideband, Type I codebook, or has no PMI feedback, and there is only one CSI-RS resource with 4 or fewer ports in the CMR, then all CPU is occupied, i.e., 0. CPU =N CPU .

[0355] For each CSI report processed, the CPU will continuously occupy a certain number of symbols. The protocol specifies that when the report type (reportConfigType) is not set to 'none', the number of CPU symbols occupied is determined according to the following rules:

[0356] Referring to Figure 4, the CPU time occupied by periodic or semi-persistent CSI reports (excluding the initial semi-persistent CSI report on the PUSCH after the Physical Downlink Control Channel (PDCCH) trigger report) is as follows: starting from the first Orthogonal Frequency-Division Multiplexing (OFDM) symbol of the earliest resource in the latest CSI-RS / CSI-IM / SSB occasion for channel or interference measurement that is earlier than the CSI reference resource, until the last symbol of the PUSCH / Physical Uplink Control Channel (PUCCH) carrying the report.

[0357] The CPU time consumed by aperiodic CSI reporting is from the first symbol after the PDCCH that triggers the CSI report to the last symbol of the PUSCH carrying the report. The CPU time consumed by the initial semi-persistent CSI report on the PUSCH after PDCCH triggering is from the first symbol after the PDCCH until the last symbol of the PUSCH carrying the report. Referring to Figure 5, the CPU time consumed by a semi-static CSI report on the PUSCH configured with the R18 Doppler codebook is from the first symbol of the latest consecutive Kp P / SP CSI-RS Occasions earlier than the CSI reference resource until the last symbol of the PUSCH carrying the report. Here, Kp∈{1,2,4} is indicated by the UE capability and can be understood as the observation window supported by the UE.

[0358] The NR protocol also specifies the CSI calculation time. Network devices must allow sufficient time for terminal devices when triggering CSI reporting. For CSI reports triggered by DCI on the PUSCH, a terminal device will only report a valid CSI report if the following two conditions are met:

[0359] Condition 1: The first uplink symbol carrying the corresponding CSI report (including the impact of timing advance) must not start earlier than symbol Zref;

[0360] Condition 2: The first uplink symbol carrying the nth CSI report (including the effects of timing advance) must start no earlier than symbol Z'ref(n).

[0361] Here, Zref is defined as an uplink symbol whose interval between the start time of its Cyclic Prefix (CP) and the end time of the last symbol of the PDCCH that triggers the CSI report is greater than or equal to T. proc,CSI =(Z)(2048+144)·κ2 -μ ·T C Furthermore, it is the earliest uplink symbol to satisfy this condition. When aperiodic CSI-RS is used for channel measurements of the nth triggered CSI report, Z'ref(n) is defined as an uplink symbol whose CP start time is greater than or equal to the interval between the start time of the CP and the end time of the last symbol of the resource that ended latest below it. proc,CSI =(Z′)(2048+144)·κ2 -μ ·T C Furthermore, it must be the earliest uplink symbol to meet this condition. The above provision can be understood as the time interval between the end time of the first symbol of the PUSCH carrying the CSI report and the end time of the last symbol of the PDCCH triggering the CSI report being greater than or equal to the specified time parameter T. proc,CSI Furthermore, the time interval between the first symbol of the PUSCH carrying the CSI report and the end time of all reference resources used for channel measurements must be greater than or equal to the specified time parameter T′. proc,CSISee Figure 6. When the above conditions are not met, the terminal device does not need to update the reported CSI. The values ​​of Z and Z′ in the above formula are determined according to the tables and principles given by the protocol. Furthermore, for non-DCI-triggered reporting (periodic and semi-persistent reporting), the protocol limits the CSI calculation time by defining a CSI reference resource, ensuring that the terminal device only needs to update the reported CSI when it has sufficient calculation time. The CSI reference resource is defined as a time-frequency resource. In the frequency domain, the CSI reference resource is defined by a set of downlink physical resource blocks corresponding to the frequency band related to CSI calculation. In the time domain, the CSI reference resource is defined as a valid timeslot preceding the uplink timeslot for CSI reporting. The number of symbols between the timeslot containing the CSI reference resource and the CSI reporting timeslot must be greater than the value specified by the protocol. The CSI-RS used to calculate the CSI report cannot be later than the CSI reference resource. If there is no valid downlink timeslot corresponding to a certain CSI reporting configuration, the terminal device may not report the CSI. The above provision can be understood as the time interval between the CSI-RS used to calculate the CSI report and the CSI reporting time slot being greater than or equal to the specified time parameter.

[0362] The NR specifies the activation and counting rules for CSI-RS ports / resources. In any time slot, the number of active CSI-RS ports or resources a UE has in an active BWP will not exceed what is reported as capability. NZP CSI-RS resources are active for the duration defined below:

[0363] (1) AP CSI-RS: Starts from the end of the PDCCH containing the request and ends at the end of the scheduling PUSCH containing the report associated with the non-periodic CSI-RS.

[0364] (2) SP CSI-RS: Starts from the end of the activation command and ends at the end of the deactivation command.

[0365] (3) P CSI-RS: Starts from the high-level signaling configuration period CSI-RS and ends when the release period CSI-RS configuration is completed.

[0366] If a CSI-RS resource is referenced N times by one or more CSI Reporting Settings that do not have the higher-layer parameter csi-ReportSubConfigToAddModList configured, the CSI-RS resource and the CSI-RS ports within the CSI-RS resource are counted N times. For periodic or semi-static CSI-RS resources in the set of channel measurement CSI-RS resources linked by a CSI-ReportConfig with the higher-layer parameter codebookType configured as 'typeII-Doppler-r18' or 'typeII-Doppler-PortSelection-r18', the CSI-RS resource and the CSI-RS ports within the CSI-RS resource are counted K_P times, where the value of K_P ∈ {1,2,4} is indicated by the UE capability.

[0367] 6. Channel State Information Report Configuration (CSI-ReportConfig) defines how the UE measures and reports channel state information. The CSI-ReportConfig link corresponding to performance monitoring associates specific CSI report configurations with performance monitoring tasks, enabling the network to obtain necessary channel state information and thus optimize network performance.

[0368] CSI-ReportConfig can be used to define parameters for CSI reports, such as report type, report content, and resource allocation. Report types include periodic reports, non-periodic reports, or semi-continuous reports.

[0369] CSI-ReportConfig links can be used to associate performance monitoring tasks, such as associating a specific CSI-ReportConfig with a performance monitoring task to ensure that the network can obtain the necessary channel state information to support performance monitoring and optimization. They can also be used to dynamically adjust configurations, such as by dynamically adjusting the CSI-ReportConfig based on performance monitoring results, for example, by changing the reporting frequency or content, to more accurately monitor and optimize network performance.

[0370] 7. In this application, "instruction" or "for instruction" may include explicit instruction (or direct instruction) and implicit instruction (or indirect instruction). When describing information for instructing A, it may include whether the information explicitly instructs A or implicitly instructs A, but does not necessarily mean that the information carries A.

[0371] The indication methods involved in the embodiments of this application should be understood to cover various methods that enable the party to be indicated to obtain the information to be indicated. The information to be indicated can be sent as a whole or divided into multiple sub-information and sent separately. Moreover, the sending period and / or sending time of these sub-information can be the same or different, without limitation.

[0372] In the embodiments of this application, "information" can be an explicit indication, that is, a direct indication through signaling, or obtained by combining other rules or parameters with parameters indicated by signaling, or by deduction. It can also be an implicit indication, that is, obtained based on rules or relationships, or based on other parameters, or by deduction. No limitation is imposed.

[0373] 8. In this application, communication between different devices can refer to direct communication between different devices (i.e., without the need for relaying or forwarding by other devices), or communication between different devices through other devices (i.e., requiring relaying or forwarding by other devices), or communication between a functional unit within a device and other devices through another functional unit. For example, "sending information to…(terminal)" can be understood as the destination of the information being the terminal, and may include sending information directly or indirectly to the terminal. "Receiving information from…(terminal)" can be understood as the source of the information being the terminal, and may include receiving information directly or indirectly from the terminal. Information may undergo necessary processing between the source and destination ends, such as format changes, digital-to-analog conversion, amplification, filtering, etc., but the destination end can understand the valid information from the source end. Similar expressions in this application can be understood in a similar way, and will not be elaborated further here.

[0374] 9. In this application, the words "exemplarily," "for example," "for instance," and "example" are used to indicate examples, illustrations, or descriptions, and are not intended to limit the scope of protection of this application. It should be understood that the examples in this application may also be implemented in other ways.

[0375] 10. In this application, any two of the programs, instructions and code may be substituted for one another.

[0376] 11. In this application, wireless frames and system frames can be interchanged.

[0377] 12. In this application, “in the case of…”, “when…”, “if…”, and “if…” can have the same meaning and can be used interchangeably.

[0378] 13. In this application, broadcast information may also have other names, such as broadcast message. For example, broadcast information may be system information block 1 (SIB1).

[0379] The preceding text introduced some terms and concepts involved in the embodiments of this application. The following text introduces the technical features involved in the embodiments of this application.

[0380] Currently, during communication transmission, if the number of prediction results (e.g., prediction instances) and measurement results (e.g., monitoring events) within the observation window are inconsistent, scenarios may arise where one prediction result corresponds to multiple measurement results, or one measurement result corresponds to multiple prediction results. There may also be scenarios where the prediction and measurement results are too far apart in the time domain, leading to inaccurate calculations. For these scenarios, existing technologies cannot accurately standardize the binding method between prediction and measurement results in the time domain. Furthermore, the CPU timeline occupancy rules of existing technologies are not applicable to the CPU timeline occupancy of P / SP monitoring reports.

[0381] Based on this, embodiments of this application provide a communication method and apparatus for offering a more efficient and convenient binding method for prediction and measurement results, thereby effectively improving the accuracy of subsequent calculations. Furthermore, embodiments of this application also provide corresponding CPU timeline occupancy methods and active port / resource counting methods based on different binding methods between prediction and measurement results, which better meet the corresponding needs of actual presets and monitoring, and have stronger applicability. The method and apparatus are based on the same inventive concept. Since the principles by which the method and apparatus solve problems are similar, the implementation of the apparatus and method can refer to each other, and repeated details will not be elaborated further.

[0382] The communication method provided in this application embodiment can be applied to the network architecture shown in Figures 7-10.

[0383] As shown in Figure 7, the network architecture may include terminal devices and a wireless access network.

[0384] A terminal device is a device with wireless transceiver capabilities. It connects wirelessly to a wireless access network device to access a communication system. Terminal devices can also be called terminals, UEs, mobile stations, mobile terminals, etc. Terminal devices can be mobile phones, tablets, computers with wireless transceiver capabilities, virtual reality (VR) terminals, augmented reality (AR) terminals, wireless terminals in industrial control, complete vehicles, wireless communication modules within vehicles, telematics boxes (T-boxes), roadside units (RSUs), terminal devices in autonomous driving, terminal devices in Internet of Things (IoT) networks, terminal devices in remote medical care, terminal devices in smart grids, terminal devices in transportation safety, terminal devices in smart cities, or terminal devices in smart homes, etc. This application's embodiments are not limited to these categories. For ease of description, the following embodiments of this application will use UEs as examples.

[0385] A wireless access network (WAN) is used to implement functions related to wireless access. Also known as access network equipment or a base station, the WAN connects terminal devices to a wireless network. The WAN can be a base station, an evolved NodeB (eNodeB) in an LTE system or an evolved LTE-A system, a gNB in ​​a 5G communication system, a transmission reception point (TRP), a base band unit (BBU), a WiFi access point (AP), a base station in a future mobile communication system, or an access node in a WiFi system. The WAN can also be a module or unit that performs some of the functions of a base station; for example, it can be a central unit (CU), a distributed unit (DU), a CU-control plane (CP), a CU-user plane (UP), or a radio unit (RU). The wireless access network can also be an open RAN (O-RAN or ORAN). In an ORAN system, the CU can also be called an open CU (O-CU), the DU can also be called an O-DU, the CU-CP can also be called an O-CU-CP, the CU-UP can also be called an O-CU-UP, and the RU can also be called an O-RU. This application does not limit the specific technology or equipment form used in the wireless access network. For ease of description, the wireless access network equipment is simply referred to as a network device in this application.

[0386] CU and DU can be understood as a logical functional division of a base station. Physically, CU and DU can be separate or deployed together; this application does not specifically limit this. One CU can connect to one DU, or multiple DUs can share one CU, which can save costs and facilitate network expansion. The division of CU and DU can be based on the protocol stack. One possible approach is to deploy the RRC, Service Data Adaptation Protocol (SDAP), and Packet Data Convergence Protocol (PDCP) layers in the CU, and the remaining Radio Link Control (RLC), Media Access Control (MAC), and physical layers in the DU. This application does not limit the above protocol stack division method; other division methods are also possible.

[0387] Network devices and terminal devices can be deployed on land, including indoors or outdoors, handheld or vehicle-mounted, etc.; 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 application scenarios of network devices and terminal devices.

[0388] AI modules can also be deployed in network devices and / or terminal devices to perform AI-related operations, such as building training datasets, training AI models, and making predictions and optimizations based on the AI ​​models. In the network architecture shown in Figure 8, network devices can include CUs and DUs, and AI modules are deployed in CUs, DUs, and terminal devices.

[0389] Optionally, the division of CU and DU can be as shown in Figure 9, with RRC and PDCP-C deployed in CU-CP, SDAP and PDCP-U deployed in CU-UP, and RLC, MAC, and physical layer (PHY) deployed in DU.

[0390] This application's embodiments can also be applied to ORAN, as illustrated in Figure 10, which provides an exemplary ORAN architecture diagram. The radio intelligent controller (RIC) can achieve intelligent and automated RAN operation and maintenance by introducing AI. The RIC can include near real-time RIC and non-real-time RIC.

[0391] Near real-time RICs can be used for model training and inference, such as training AI models and using them for inference. Near real-time RICs can obtain network-side and / or terminal-side information from RAN nodes (e.g., CUs, CU-CPs, CU-UPs, DUs, and / or RUs) and / or terminal devices, which can be used as training or inference data. Optionally, near real-time RICs can deliver inference results to RAN nodes and / or terminal devices. Optionally, inference results can be exchanged between CUs and DUs, and / or between DUs and RUs; for example, a near real-time RIC can deliver inference results to a DU, which then forwards them to an RU.

[0392] Non-real-time RICs can be used for model training and inference, such as training AI models and using these models for inference. Non-real-time RICs can obtain network-side and / or terminal-side information from RAN nodes (e.g., CUs, CU-CPs, CU-UPs, DUs, and / or RUs) and / or terminal devices. This information can be used as training data or inference data, and the inference results can be delivered to the RAN nodes and / or terminal devices. Optionally, inference results can be exchanged between CUs and DUs, and / or between DUs and RUs. For example, a non-real-time RIC can deliver inference results to a DU, which then forwards them to an RU.

[0393] The communication systems and service scenarios described in the embodiments of this application are for the purpose of more clearly illustrating the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions provided in the embodiments of this application. As those skilled in the art will know, with the evolution of network architecture and the emergence of new service scenarios, the technical solutions provided in the embodiments of this application are also applicable to similar technical problems.

[0394] The method provided in this application will now be described with reference to the accompanying drawings. It will be understood that in this application, terminal devices and / or network devices may perform some or all of the steps described herein. These steps are merely examples, and this application may also perform other steps or variations thereof. Furthermore, the steps may be performed in different orders as presented in this application, and it is not necessary to perform all the steps described herein.

[0395] To better illustrate the application of the communication method of this application, Figure 11 shows a flowchart of the communication method provided in the embodiment of this application. Figure 11 uses the first device and the second device as examples of the execution entities in this interaction to illustrate the method. The first device can be a terminal or a device within a terminal (e.g., a module, circuit, chip (such as a modem chip, or a SoC chip or SIP chip containing a modem core), a chip system, or a processor), or a logical node, logical module, or software that implements all or part of the terminal's functions. The second device can be an access network device or a device within an access network device (e.g., a module, circuit, chip (such as a modem chip, or a SoC chip or SIP chip containing a modem core), a chip system, or a processor), or a logical node, logical module, or software that implements all or part of the access network device's functions.

[0396] As shown in Figure 11, the method includes:

[0397] S1101: The second device sends the first information.

[0398] In some implementations, the first information in the embodiments of this application is used to instruct the terminal device to determine the first monitoring report.

[0399] In some implementations, the time unit corresponding to the first monitoring report in this application embodiment can be referred to as the first reference time unit. The first reference time unit in this application embodiment includes, but is not limited to, one or more of the following: the uplink time unit where the first monitoring report is located, the CSI reference resource corresponding to the first monitoring report, and the set of reference measurement resources used to generate the first monitoring report.

[0400] As an example, the reference measurement resources included in the reference measurement resource set in this application embodiment may be the first, the last, or a specific reference measurement resource predefined / NW specified, without limitation here.

[0401] As an example, in the first reference time unit, this application embodiment may or may not send the first monitoring report, and no limitation is made here.

[0402] S1102: The first device receives the first information.

[0403] S1101 and S1102 are optional steps, such as the terminal device actively reporting the first monitoring report.

[0404] S1103: Based on N prediction results and M measurement results, a first indicator is determined, wherein the M measurement results include the first measurement result, and the N prediction results include the first prediction result; the first time unit corresponding to the first measurement result and the second time unit corresponding to the first prediction result have a first time relationship.

[0405] It is understood that the names used for prediction results in this application embodiment are merely examples, and any content with the same or similar function (or similar role) as the prediction result can be replaced. For example, the prediction result can be replaced with prediction information, prediction instance, or prediction time instance, etc., without limitation. Here, prediction time instance can represent the time corresponding to the prediction information / prediction result. Similarly, the names used for measurement results in this application embodiment are merely examples, and any content with the same or similar function (or similar role) as the measurement result can be replaced. For example, the measurement result can be replaced with monitoring occasion, CSI-RS transmission occasion for performance monitoring, monitoring time instance, monitoring instance, or measurement instance for performance monitoring, etc., without limitation. The term "CSI-RS transmission occasion" in this application embodiment is merely an example. Any content with the same or similar function (or role) as "CSI-RS transmission occasion" can be replaced. For example, "CSI-RS transmission occasion" can be replaced with "CSI-RS occasion" or "transmission occasion," etc., to indicate the time of CSI-RS resource transmission. For BM, generally, multiple CSI-RS resources are transmitted within a single CSI-RS occasion; for CSI, generally, only one CSI-RS resource is transmitted within a single CSI-RS occasion, and this is not limited here. As an example, the first indicator in this application includes, but is not limited to, performance monitoring metrics. For example, embodiments of this application can use these performance monitoring metrics to evaluate and monitor key data points of system, network, or application performance, thereby better helping to ensure a high-quality user experience and optimize network resources.

[0406] As an example, the first index determined by embodiments of this application based on N prediction results and M measurement results includes, but is limited to, the following cases:

[0407] Case 1: Based on N prediction results and M measurement results, the number of first indicators is determined to be one.

[0408] Scenario 2: Based on N prediction results and M measurement results, the number of first indicators is multiple.

[0409] As an example, after determining the first monitoring report based on the first indicator, the UE may report the monitoring report, for example, the UE may obtain and report a CSI report; or, after determining the first monitoring report based on the first indicator, the UE may choose not to report it, for example, for a determined virtual report, the UE may calculate the result but not report it, which is not limited here.

[0410] It is understood that in the embodiments of this application, the first prediction result can be any one of N prediction results; the first measurement result can also be any one of M measurement results. Optionally, the N prediction results are the N prediction results closest to the first reference time unit corresponding to the first monitoring report.

[0411] In this embodiment, N and M are positive integers greater than or equal to 1. Optionally, N is equal to M; or, N is not equal to M. Furthermore, this embodiment can determine the value of N and / or M based on various situations. For example, the number of prediction results within the time period A preceding the first reference time unit corresponding to the first monitoring report can be determined as N; or, for another example, the maximum value of N is configured or indicated by the network, or preset by the protocol. It is understood that to prevent the UE from failing to obtain some valid resources based on implementation, for example, if the first resource associated with a certain prediction instance is invalid, and the UE obtains measurement information of a resource satisfying the first time relationship at a distance from the prediction instance through filtering based on implementation (e.g.), then configuring N in NW is still feasible.

[0412] In some implementations, the first time unit corresponding to the first measurement result includes, but is not limited to, one or more of the following:

[0413] Content 1: The time unit in which the first set of measurement resources is located to determine the first measurement result.

[0414] Content 2: The time unit in which the Channel State Information (CSI) reference resource corresponding to the first measurement result is located.

[0415] Content 3: The time unit in which the first measurement result takes effect.

[0416] Content 4: CSI reference resources corresponding to the CSI report that carries the first prediction result bound to the first measurement result.

[0417] In some implementations, the second time unit corresponding to the first prediction result includes, but is not limited to, one or more of the following:

[0418] Content 1: The time unit in which the CSI reference resource corresponding to the first prediction result is located;

[0419] Content 2: The time unit in which the first prediction result takes effect.

[0420] Content 3: CSI reference resources corresponding to the CSI report carrying the first prediction result.

[0421] As an example, the first set of measurement resources in this application embodiment may include a set of resources in a wireless communication system for the UE to perform channel quality estimation, signal strength measurement, and interference assessment, including but not limited to synchronization signal blocks (SSBs), channel state information reference signals (CSI-RS), etc. For example, the UE can obtain the synchronization information of the cell by detecting the SSB and identify the interference situation of neighboring cells; as another example, the UE can generate channel quality indicators (CQI), precoding matrix indicators (PMI), and rank indicators (RI) based on CSI-RS measurements and feed them back to the base station for downlink quality assessment and handover decisions.

[0422] As an example, the time unit in which the CSI reference resource corresponding to the first measurement result in the embodiments of this application is located may include, but is not limited to, a specific time interval or time period used to transmit the CSI reference signal (Channel State Information Reference Signal, CSI-RS).

[0423] As an example, the time unit in which the first measurement result applies in the embodiments of this application may include, but is not limited to, the specific time interval or time period for performing the monitoring operation.

[0424] As an example, the VSI reference resource in this application embodiment may include a module for monitoring and displaying signal status or quality. It can display key parameters such as Received Signal Strength Indicator (RSSI) and Signal-to-Noise Ratio (SNR) in real time, helping users understand the quality of the current communication link, helping to identify situations with weak signals or severe interference, facilitating quick troubleshooting, and by monitoring signal quality, adjusting parameters such as transmit power and frequency to optimize communication performance and ensure the stability and reliability of signal transmission.

[0425] As an example, the time unit in this embodiment is used to define and synchronize the basic time intervals of various communication processes, including but not limited to subframes, slots, symbols, and frames. Optionally, the time unit containing the first measurement resource set may include, but is not limited to, the time unit corresponding to the NW transmitting CSI-RS, the time unit corresponding to the UE receiving CSI-RS, etc.

[0426] In some implementations, embodiments of this application can determine the binding relationship between prediction results and measurement results in various ways, including but not limited to the following methods:

[0427] Binding method 1: Determine the prediction result based on the measurement result.

[0428] As an example, embodiments of this application can determine M time units corresponding to M measurement results, and then determine a second time unit based on the first time unit corresponding to any one of the M measurement results.

[0429] In some implementations, when matching prediction results with measurement results based on binding method 1, the following matching scenarios may also occur:

[0430] For example, if multiple measurement results correspond to the same second time unit, then in this embodiment of the application, one time unit can be selected from the multiple measurement results as the first time unit.

[0431] In some implementations, when determining the second time unit based on the first time unit in the embodiments of this application, it can be determined by one of a variety of determination methods alone, or by a combination of any number of methods. The determination methods include, but are not limited to:

[0432] Method 1: Combine the first time relationship to help determine the second time unit from the first time unit.

[0433] In some implementations, the first time relationship between the first time unit and the second time unit includes at least one of the following:

[0434] Relationship 1: The time interval between the first time unit and the second time unit is less than or equal to the first time interval.

[0435] Relationship 2: The first time unit is the Xth time unit closest to the second time unit, where X is a positive integer.

[0436] Relationship 3: The first time unit is not later than the second time unit.

[0437] Relationship 4: The second time unit is the Y-th time unit closest to the first time unit, where Y is a positive integer.

[0438] Relationship 5: The second time unit is not later than the first time unit.

[0439] It is understandable that when X is 1, "the first time unit is the Xth closest time unit to the second time unit" means that the first time unit is the closest time unit to the second time unit. When Y is 1, "the second time unit is the Yth closest time unit to the first time unit" means that the second time unit is the closest time unit to the first time unit. In this application embodiment, X and Y may be equal or unequal, and this is not limited here.

[0440] When determining the second time unit based on the first time unit in this application embodiment, it can be determined by the first time relationship described above. For example, the second time unit includes, but is not limited to, the prediction time unit closest to the first time unit, or the prediction time unit whose time interval with the first time unit is less than or equal to the first time interval, etc., and is not limited here.

[0441] For example, the first time relationship is that the time interval between the first time unit and the second time unit is less than or equal to a first time interval.

[0442] For example, as shown in Figure 12, assuming the first time unit is time unit A and the first time interval is B, then based on the time interval B, the time unit C to the left of time unit A can be determined as the second time unit.

[0443] For example, as shown in Figure 13, assuming the first time unit is time unit A and the first time interval is B, then based on the time interval B, the second time unit to the right of time unit A can be determined to be time unit E.

[0444] For example, as shown in Figure 14, assuming the first time unit is time unit A and the first time interval is B, then based on time interval B, if both time unit C and time unit E meet the conditions, then the second time unit can be determined by combining time unit C and time unit E; or, a time unit can be randomly selected from time unit C and time unit E, such as selecting time unit E as the second time unit, etc., without limitation here.

[0445] Wherein, when the first time relationship includes two conditions, namely, the time interval between the first time unit and the second time unit is less than or equal to the first time interval, and the first time unit is not later than the second time unit, in the scenario of Figure 14 above, time unit E can be determined as the second time unit from time unit C and time unit E.

[0446] Similarly, when the first time relationship includes the two conditions that the time interval between the first time unit and the second time unit is less than or equal to the first time interval, and the second time unit is not later than the first time unit, in the scenario of Figure 14 above, time unit C can be determined as the second time unit from time unit C and time unit E.

[0447] For example, taking the first time relationship as the first time unit being the closest or Xth closest time unit to the second time unit as an example:

[0448] For example, as shown in Figure 15, assuming the first time unit is time unit A and X is 1, then time unit C can be determined as the second time unit from time units E, C, and F.

[0449] If the first time relationship includes two conditions, namely that the time interval between the first time unit and the second time unit is less than or equal to the first time interval (e.g., time interval B) and that the first time unit is the Xth closest (e.g., the most recent) time unit of the second time unit, then in the scenario of Figure 15, the time units that meet the conditions can be determined first based on time interval B as time unit C and time unit E, and then the time unit C closest to time unit A can be selected from time unit C and time unit E as the second time unit.

[0450] If the first time relationship includes two conditions, namely that the time interval between the first time unit and the second time unit is less than or equal to the first time interval (e.g., time interval B) and that the first time unit is the Xth closest (e.g., the most recent) time unit of the second time unit, then in the scenario of Figure 15, the time unit that meets the conditions can be determined as time unit C based on the time unit closest to time unit A, and then it can be further determined whether time unit C satisfies the condition that the time interval between it and time unit A is not greater than time interval B.

[0451] For example, as shown in Figure 16, assuming the first time unit is time unit A and X is 1, the time units closest to time unit A include time unit C and time unit D. At this time, a time unit can be randomly selected from time unit C and time unit D. For example, time unit D can be randomly selected as the second time unit; or, the second time unit can be obtained by integrating time unit C and time unit D.

[0452] Method 2: Combine the second constraint condition to assist the first time unit in determining the second time unit.

[0453] In some implementations, the first prediction result determined by the first measurement result of this application can satisfy a second constraint condition, which includes at least one of the following conditions:

[0454] Condition 1: If the UE reports the first prediction report, then the second reference time unit corresponding to the first prediction result for reporting the first prediction report is within the valid time range.

[0455] Condition 2: If the UE reports the first prediction report, then the first prediction result will be effective within the valid time range.

[0456] Condition 3: If the UE does not report the first prediction report, then the first prediction result is effective within the valid time range.

[0457] Condition 4: The second time unit is within the valid time range.

[0458] In some implementations, the second constraint in the embodiments of this application may also determine the included condition content based on whether there is a reasoning result report.

[0459] For example, when there is a reasoning result reporting in this application embodiment, the second constraint condition may include that the second reference time unit (e.g., the reporting time of the reasoning report corresponding to the found prediction result) is not later than the first reference time unit (e.g., the reference resource corresponding to the monitoring report), and / or that the second time unit (e.g., the time when the found prediction instance takes effect) is not later than the first reference time unit (e.g., the reference resource corresponding to the monitoring report); when there is no reasoning result reporting in this application embodiment, the second constraint condition may include that the second time unit (e.g., the time when the found prediction result takes effect) is not later than the first reference time unit (e.g., the reference resource corresponding to the monitoring report).

[0460] Optionally, in this application embodiment, the first prediction result is determined based on the first prediction report, or the first prediction result has been obtained by the terminal device. It is understood that the terminology used for the inference result in this application embodiment is merely an example, and any content with the same or similar function (or similar role) as the inference result can be replaced. For example, the inference result can be replaced with the prediction result, the result obtained based on an AI model, etc., without limitation. Similarly, the terminology used for the prediction report in this application embodiment is merely an example, and any content with the same or similar function as the prediction report can be replaced. For example, the prediction report can be replaced with the inference report, the CSI report containing the inference result, the UE report containing the inference result, etc., without limitation.

[0461] Furthermore, as an example, to better ensure the accuracy of the reported first monitoring report, in this embodiment of the application, the second reference time unit corresponding to the first prediction report is no later than the second time offset unit. The time interval between the second time offset unit and the second reference time unit corresponding to the first prediction report is the second time length. This ensures that the interval between the reference resources of the prediction report and the reference resources of the monitoring report is greater than or equal to the second time length, providing sufficient completion time for the calculation of the first indicator and / or packet assembly, etc., thus enhancing adaptability. Optionally, the second time length in this embodiment of the application can be agreed upon by the protocol, indicated in the UE capability reporting, or configured by NW, etc., and is not limited here. For example, the second time length can be set according to actual experience and can be set to the general UE packet assembly time.

[0462] In some implementations, the second reference time unit in this application embodiment includes, but is not limited to, one or more of the following: the uplink time unit where the first prediction report is located, the CSI reference resource corresponding to the first prediction report, and the time unit corresponding to the reference prediction result included in the first prediction report. Optionally, the reference prediction result in this application embodiment can be the first, the last, any one, a predefined / NW-specified / determined specific reference prediction result, which is not limited here. Furthermore, in this application embodiment, the first prediction report may or may not be sent in the second reference time unit, which is not limited here.

[0463] In some implementations, the effective time range of the embodiments of this application includes one or more of the following:

[0464] Range 1: No later than the first reference time unit corresponding to the first monitoring report.

[0465] Range 2: No earlier than the time unit in which the control information used to indicate the first monitoring report is located.

[0466] Range 3: Not earlier than the first offset time unit, where the time interval between the first offset time unit and the time unit used to indicate the location of the control information in the first monitoring report is the first time length;

[0467] Range 4: No later than the second time offset unit, where the time interval between the second time offset unit and the second reference time unit corresponding to the first prediction report is the second time length.

[0468] For example, in the embodiments of this application, when determining the prediction result based on the measurement result, not only can the second time unit corresponding to the first time unit be determined based on the first time relationship between the first time unit and the second time unit, but the obtained second time unit can also be further filtered based on the second constraint condition. For example, if the second time unit does not meet the second constraint condition, the first prediction result is not used for the calculation of the first index, which can be understood as deleting the second time unit that does not meet the second constraint condition.

[0469] Method 3: Combine the first constraint condition to assist the first time unit in determining the second time unit.

[0470] In some implementations, the second time unit determined by the first time unit of this application can satisfy a first constraint condition, which includes at least one of the following conditions:

[0471] Condition 1: The first time unit corresponding to the second time unit is within the valid time range corresponding to the first monitoring report.

[0472] Condition 2: The second time unit is within the valid time range corresponding to the first monitoring report.

[0473] For example, in the embodiments of this application, when determining the prediction result based on the measurement result, not only can the second time unit corresponding to the first time unit be determined based on the first time relationship between the first time unit and the second time unit, but the obtained second time unit can also be further filtered based on the first constraint condition. For example, if the second time unit does not meet the first constraint condition, the first prediction result is not used for the calculation of the first index, which can be understood as deleting the second time unit that does not meet the first constraint condition; or, in the embodiments of this application, when determining the prediction result based on the measurement result, the first measurement result that meets the first constraint condition can be selected from the multiple obtained measurement results based on the first constraint condition, and then the second time unit corresponding to the first time unit that meets the first constraint condition can be determined based on the first time relationship between the first time unit and the second time unit.

[0474] Furthermore, when determining the second time unit based on the first time unit (or determining the first time unit based on the second time unit) in this embodiment of the application, in combination with the first time relationship and the first constraint condition, there may be a situation where the monitoring result corresponding to the prediction result closest to the first reference time unit is later than the prediction result. For example, the monitoring result may be after the first reference time unit, which can be understood as not being within the valid interval. Based on this, this embodiment of the application provides an optional application scheme. For example, when the terminal device determines that the monitoring result corresponding to the prediction result closest to the first reference time unit is later than the prediction result, the terminal may disregard the monitoring result and the prediction result corresponding to the monitoring result, and then the UE finds a prediction result further back. At this time, the prediction result found by the terminal is no longer the prediction result closest to the first reference time unit, but the prediction result closest to the first reference time unit that satisfies the first constraint condition.

[0475] Binding method 2: Determine the measurement result based on the prediction result.

[0476] As an example, embodiments of this application can determine N time units corresponding to N prediction results, and then determine a first time unit based on the second time unit corresponding to any one of the N prediction results.

[0477] In some implementations, the N prediction results described in this application embodiment may be the N prediction results most recent to the first reference time unit corresponding to the first monitoring report.

[0478] As an example, this application embodiment may first determine a report, and then determine the N prediction results within it; or, this application embodiment may use the N prediction results within multiple reports as the N prediction results corresponding to the first monitoring report, etc., without limitation. Optionally, the first monitoring report is obtained by integrating multiple monitoring reports. For example, there may be multiple virtual reports, and the first monitoring report can be obtained by merging multiple virtual reports.

[0479] In one possible manner, the first prediction report meets a third constraint, which includes, but is not limited to, one or more of the following: at least one of the N prediction results corresponds to a measurement result before the first reference time unit corresponding to the first monitoring report; or, the first prediction report contains at least one valid prediction result, and the measurement result corresponding to the valid prediction result is before the first reference time unit corresponding to the first monitoring report.

[0480] For example, in this embodiment of the application, the second reference time unit determined based on the first reference time unit corresponding to the first monitoring report is the second reference time unit 1. The second reference time unit 1 corresponds to prediction report 1. If none of the N prediction results included in the prediction report 1 corresponds to a measurement result before the CSI reference resource corresponding to the first monitoring report, or if all the prediction results included in the prediction report 1 are invalid prediction results, that is, the prediction results included in the prediction report 1 do not have a measurement result bound to them before the first reference time unit corresponding to the first monitoring report, then this embodiment of the application can discard the prediction report 1, search for another prediction report, and continue to determine whether the found prediction report meets the third constraint condition, until it is determined that the found prediction report meets the third constraint condition, then the prediction report that meets the third constraint condition is determined as the first prediction report.

[0481] In some implementations, when matching prediction results with measurement results based on binding method 2, the following matching scenarios may also occur:

[0482] For example, if multiple prediction results correspond to the same first time unit, then in this embodiment of the application, one time unit can be selected from the multiple prediction results as the second time unit.

[0483] In some implementations, when determining the first time unit based on the second time unit in the embodiments of this application, the first time unit corresponding to the second time unit can be determined by one of a variety of determination methods alone, or by a combination of any number of determination methods. The determination methods include, but are not limited to:

[0484] Method 1: Combine the first time relationship to assist the second time unit in determining the first time unit.

[0485] The details of determining the first time relationship in method 1 in this binding method 2 can be found in the above introduction of the first time relationship in binding method 1. For the sake of brevity, it will not be elaborated here.

[0486] For example, the first time relationship is that the time interval between the first time unit and the second time unit is less than or equal to a first time interval.

[0487] For example, as shown in Figure 17, assuming the second time unit is time unit A and the first time interval is B, then based on the time interval B, the time unit E to the left of time unit A can be determined as the first time unit.

[0488] For example, as shown in Figure 18, assuming the second time unit is time unit A and the first time interval is B, then based on the time interval B, the time unit C to the right of time unit A can be determined as the first time unit.

[0489] For example, as shown in Figure 19, assuming the second time unit is time unit A and the first time interval is B, then based on time interval B, if both time units C and E satisfy the conditions, then the first time unit can be determined by combining time units C and E; or, a time unit can be randomly selected from time units C and E, such as selecting time unit E as the first time unit, etc., without limitation here.

[0490] Wherein, when the first time relationship includes two conditions, namely, the time interval between the first time unit and the second time unit is less than or equal to the first time interval, and the second time unit is not later than the first time unit, in the scenario of Figure 19 above, time unit C can be determined as the first time unit from time unit C and time unit E.

[0491] Similarly, when the first time relationship includes the two conditions that the time interval between the first time unit and the second time unit is less than or equal to the first time interval, and the first time unit is not later than the second time unit, in the scenario of Figure 19 above, time unit E can be determined as the first time unit from time unit C and time unit E.

[0492] For example, taking the case where the first time relationship is such that the second time unit is the Yth closest time unit to the first time unit as an example:

[0493] For example, as shown in Figure 20, assuming the second time unit is time unit A and Y is 1, then time unit E can be determined as the first time unit from time units E, C and F.

[0494] If the first time relationship includes two conditions, namely, the time interval between the first time unit and the second time unit is less than or equal to the first time interval (e.g., time interval B), and the second time unit is the Yth closest time unit to the first time unit (e.g., the closest), then in the scenario of Figure 20, the time units that meet the conditions can first be determined as time unit F and time unit E based on time interval B, and then the time unit E closest to time unit A can be selected from time unit F and time unit E as the first time unit.

[0495] If the first time relationship includes two conditions, namely that the time interval between the first time unit and the second time unit is less than or equal to the first time interval (e.g., time interval B) and that the second time unit is the Yth closest (e.g., the most recent) time unit of the first time unit, then in the scenario of Figure 20, the time unit that meets the conditions can be determined as time unit E based on the time unit closest to time unit A, and then it can be further determined whether time unit E satisfies the condition that the time interval between it and time unit A is not greater than time interval B.

[0496] For example, as shown in Figure 21, assuming the second time unit is time unit A and Y is 1, the time units closest to time unit A include time unit C and time unit D. At this time, a time unit can be randomly selected from time unit C and time unit D. For example, time unit D can be randomly selected as the first time unit; or, the first time unit can be obtained by integrating time unit C and time unit D.

[0497] Method 2: Combine the second constraint condition to assist the second time unit in determining the first time unit.

[0498] In some implementations, the first time unit determined by the second time unit of this application can satisfy the second constraint condition. The relevant content of the second constraint condition can be found in the above-mentioned binding method 1. For the sake of brevity, it will not be repeated here.

[0499] For example, in the embodiments of this application, when determining the measurement result based on the prediction result, not only can the first time unit corresponding to the second time unit be determined based on the first time relationship between the second time unit and the first time unit, but the obtained second time unit can also be further filtered based on the second constraint condition. For example, if the second time unit does not meet the second constraint condition, the first prediction result is not used for the calculation of the first index, which can be understood as deleting the second time unit that does not meet the second constraint condition and the corresponding first time unit; or, in the embodiments of this application, when determining the measurement result based on the prediction result, the obtained second time unit can be filtered based on the second constraint condition first, and the second time unit that meets the second constraint condition can be selected. Then, the corresponding first time unit is determined for the second time unit that meets the second constraint condition.

[0500] Method 3: Combine the first constraint condition to assist the second time unit in determining the first time unit.

[0501] In some implementations, the first time unit determined by the second time unit of this application can satisfy the first constraint condition. For details of the first constraint condition, please refer to the introduction in the above binding method 1. For the sake of brevity, it will not be elaborated here.

[0502] For example, in the embodiments of this application, when determining the measurement result based on the prediction result, not only can the first time unit corresponding to the second time unit be determined based on the first time relationship between the second time unit and the first time unit, but the obtained second time unit can also be further filtered based on the first constraint condition. For example, if the second time unit does not meet the first constraint condition, the first prediction result is not used for the calculation of the first index, which can be understood as deleting the second time unit that does not meet the first constraint condition; or, in the embodiments of this application, when determining the measurement result based on the prediction result, the first prediction result that meets the first constraint condition can be selected from the multiple obtained measurement results based on the first constraint condition, and then the first time unit corresponding to the second time unit that meets the first constraint condition can be determined based on the first time relationship between the first time unit and the second time unit.

[0503] It should be noted that the above-described method for determining the first time unit and / or the second time unit is only an example of the embodiments of this application and does not constitute a limitation on the embodiments of this application. The embodiments of this application can also be determined based on other combinations.

[0504] The process described in Figure 11 continues below.

[0505] S1104: The first device determines the first monitoring report based on the first indicator.

[0506] In some implementations, the start position and / or end position of the first monitoring report can be determined in the following ways:

[0507] Start time: The CPU usage start time corresponding to the first monitoring report corresponds to the earliest time unit in at least one first time unit, wherein at least one first time unit can be a first time unit determined based on the second time units corresponding to the N prediction results.

[0508] For example, the start time of CPU usage varies depending on the binding method in this application. Examples are given below:

[0509] For example, in the scenario of the above binding method one, that is, when the prediction result is determined based on the measurement result, the earliest first time unit corresponding to the start time of the CPU occupation of the first monitoring report is the earliest first time unit among the first time units corresponding to the N measurement results.

[0510] For example, in the scenario of the above binding method two, that is, when the measurement result is determined based on the prediction result, the start time of CPU occupation corresponding to the first monitoring report corresponds to the earliest resource in the CSI-RS occasion corresponding to the earliest first time unit. The earliest first time unit is the earliest time unit among the first time units determined by the second time units corresponding to the N prediction results, or the earliest time unit among the first time units determined by the second time units corresponding to the prediction results of the most recent N prediction reports.

[0511] For example, in scenarios where invalid measurement results or prediction results exist, and the corresponding invalid measurement results are discarded, the earliest first time unit corresponding to the start time of CPU usage of the first monitoring report is not considered as the first time unit corresponding to the earliest discarded measurement result.

[0512] Termination Time: In this application embodiment, the CPU occupation termination time can be determined based on the time when the calculation of the first indicator is completed; or, the CPU occupation termination time can be determined based on the time when the CSI calculation is completed; or, the CPU occupation termination time can be determined based on the last symbol of the PUSCH / PUCCH carrying the first monitoring report; or, the termination time can be determined based on the Z′ symbols of the last symbol of the CSI-RS occasion used for performance monitoring, etc.

[0513] As an example, Z′ in the embodiments of this application may include one or more of the following:

[0514] Case 1: Z′ represents the distance from the end time of the last symbol of the CSI-RS resource to the first symbol of the PUSCH carrying the CSI report.

[0515] Case 2: Z′ includes the time for calculating the first index.

[0516] Case 3: Z′ includes the time of packet assembly.

[0517] As an example, in communication systems such as 5G NR systems, a CSI-RS occasion refers to the time and frequency location of reference signal resource allocation used to measure channel state information. The time window for CSI-RS transmission can be configured by the base station, informing the user equipment (UE) when and where to monitor CSI-RS. A CSI-RS occasion can contain multiple OFDM symbols, depending on the configuration. In some configurations, CSI-RS does not occupy all symbols in the entire time slot, but only a portion of them. Z′ can represent the number of symbols counting backwards from the last symbol of this CSI-RS occasion. For example, if Z′ = 3, it means that the CPU occupies 3 symbols counting backwards from the last symbol of the CSI-RS occasion.

[0518] For example, suppose a time slot has 14 OFDM symbols and the CSI-RS occasion is configured to use symbols 5-9. Then: if Z' = 5, the CPU will use symbol 14; if Z' = 4, the CPU will use symbol 13.

[0519] It should be noted that the steps and processes in the above embodiments of this application do not constitute a limitation on the embodiments of this application. For example, the order of the steps in the above embodiments can be adjusted according to the actual situation. For another example, there are steps in the above embodiments that can be executed simultaneously, which are not limited here.

[0520] To better illustrate the embodiments of this application, examples of different applications are provided below, but are not limited to the following application examples:

[0521] Application Example 1: The UE determines the corresponding prediction result based on the M most recent measurement results before the first reference time unit corresponding to the first monitoring report (i.e., the binding method 1 described in Figure 11 above).

[0522] For example, the UE binds the nearest prediction instance to each of the M most recent monitoring results before the CSI reference resource.

[0523] The specific binding strategy (also known as the binding mechanism) of this binding method one can be understood as determining the prediction result based on the monitoring results. The relevant reference steps are shown in Figure 22:

[0524] Step S2201: NW sends the first information to UE.

[0525] As an example, in this application embodiment, the NW can send an RRC configuration to the UE, which can be used to instruct the UE to periodically / semi-persistently report the first monitoring report.

[0526] In some implementations, the content of the first monitoring report reported in each cycle of this application embodiment may include one metric or multiple metrics. It can also be understood that the first monitoring report is based on one or more metrics. Specifically, this application embodiment may obtain one or more metrics based on a certain number of prediction results (e.g., N prediction results) and a certain number of measurement results (e.g., M measurement results). That is, the first metric described in Figure 11 above may include one metric or multiple metrics, without limitation. For example, in this application embodiment, one metric may represent that the UE only calculated one metric corresponding to one measurement result (monitoring instance), or it may represent that the UE obtained one metric by statistically calculating the metrics corresponding to multiple measurement results; A metrics (e.g., A is greater than or equal to 2) represent that the UE calculated A metrics corresponding to B measurement results, where A may not be consistent with B.

[0527] As an example, the indicators in embodiments of this application include, but are not limited to, some or all of the following:

[0528] (1) Top K refers to selecting the K strongest channel paths or antenna combinations for data transmission in a multi-antenna system (such as Massive MIMO). By selecting the best path or combination, the spectral efficiency and throughput of the system can be maximized.

[0529] (2) Layer 1 Reference Signal Received Power (L1-RSRP) refers to the power of the reference signal received by Layer 1 (physical layer), which is used to measure the strength of the reference signal received by the user equipment (UE) from a specific cell or base station.

[0530] (3) Precoding Matrix Indicator Accuracy (PMI Accuracy) refers to the accuracy of the precoding matrix indication. The precoding matrix is ​​used for beamforming, which optimizes the signal transmission direction by adjusting the phase and amplitude of the transmitted signal, thereby improving spectral efficiency and link quality.

[0531] (4) PMI difference per instance refers to the difference or change between the PMI values ​​of each individual measurement or event.

[0532] For example, one indicator in this application embodiment may include, but is not limited to, one or more of Top K, L1-RSRP, or PMI accuracy; multiple indicators in this application embodiment may include, but are not limited to, L1-RSRP and / or PMI difference per instance. Optionally, the number of L1-RSRP / PMI accuracies in this application embodiment may be (KL) / K, where K is the number of valid measurement results, and L is the number of valid measurement results where the L1-RSRP / PMI difference is greater than a threshold A. Optionally, the threshold A may be configured by NW and used for indicator calculation, rather than for triggering indicator reporting; the L1-RSRP / PMI difference may be the predicted L1-RSRP / PMI and the normallyized mean squared error (NMSE) of the monitored L1-RSRP / PMI, the Spatial Geometry Channel Simulator (SGCS), or other calculated indicators, and this invention does not limit this.

[0533] Step S2202: The UE determines the M most recent measurement results based on the first reference time unit corresponding to the first monitoring report.

[0534] For example, the UE determines the M most recent measurements based on the CSI reference resources.

[0535] As an example, in this application embodiment, M can be predefined by the protocol or configured by NW. The value can be 1 or greater than 1. The configuration method can be based on RRC signaling, DCI, MAC CE, etc., and is not limited here.

[0536] Step S2203: The UE determines N prediction results based on M measurement results.

[0537] For example, the UE can determine and bind the nearest predicted result to each of the M measurement results based on the M measurement results. For instance, in this embodiment, the number of measurement results found is N, where N can be less than or equal to M. The M measurement results and the N predicted results found must be available before the CSI reference resource corresponding to the first monitoring report.

[0538] Step S2204: The UE determines the first indicator based on N prediction results and M measurement results.

[0539] Step S2205: The UE determines the first monitoring report based on the first indicator.

[0540] As an example, in this application embodiment, the UE can report N indicators, such as L1-RSRP and PMI; or it can report one indicator obtained by statistically analyzing N indicators, such as average L1-RSRP accuracy or top1 beam accuracy.

[0541] For example, in this embodiment, the CPU usage corresponding to the first monitoring report starts from the first OFDM symbol of the earliest resource among the most recent M (e.g., valid measurement results out of M measurement results) resources used for performance monitoring for CSI-RS / CSI-IM / SSB occasions prior to the CSI reference resource, and ends at the last symbol of the PUSCH / PUCCH carrying the first monitoring report. Optionally, the active CSI-RS resource / port count is N.

[0542] It should be noted that the examples above in the embodiments of this application are only illustrative of the corresponding steps and do not constitute a limitation on the corresponding steps. For example, the CPU termination time corresponding to the first monitoring report in the embodiments of this application can also be determined by other methods of CPU occupation termination described in Figure 11 above, which are not limited here.

[0543] The following scenarios will be selected to further illustrate the content of the first application example above, and are not limited to these scenarios:

[0544] Scenario 1: In the actual binding process, as shown in Figure 23, multiple measurement results may correspond to one prediction result.

[0545] Based on scenario 1, the terminal device can process the data in various ways, including but not limited to the following:

[0546] Processing method 1: The UE can discard some measurement results.

[0547] For example, the discarding method in processing method 1 may include, but is not limited to, calculating based on the measurement result closest to the prediction result and discarding the remaining measurement results. The number of final measurement results (e.g., CSI-RS, CSI-IM, or SSB instances for performance monitoring) may be determined based on the number of prediction results associated with M measurement results, with the calculated index number being M1 (M1 less than or equal to M). Alternatively, the NW sets an offset to determine whether to discard some measurement results; that is, the UE only considers prediction results within the offset range. The number of final measurement results (e.g., CSI-RS, CSI-IM, or SSB instances for performance monitoring) may be determined based on the number of prediction results associated with M measurement results, and may be equal to M2 (M2 less than M). Optionally, the activated CSI-RS resource / port count is M1 or M2. At this time, the UE can report N, M1, or M2 indicators (e.g., L1-RSRP, PMI); the UE can also report one indicator obtained by statistically analyzing N, M1, or M2 indicators (e.g., average L1-RSRP accuracy, Top1 beam accuracy).

[0548] Processing Method 2: The UE calculates the index corresponding to multiple measurement results and a single prediction result.

[0549] Scenario 2: For application example 1, during the actual binding process, NW can further instruct the UE to merge multiple monitoring reports into one monitoring report for reporting (for example, the UE only counts some CSI reports and does not report them), or simply have the UE count indicators at equal intervals.

[0550] Based on scenario 2, the terminal device can process the data in various ways, including but not limited to the following:

[0551] Solution 1: Introduce virtual CSI reports.

[0552] For example, as shown in Figure 24, the UE determines that the first monitoring includes the data after referring to the above steps S2203-S2205, but does not report it.

[0553] In some implementations, the NW can indicate the number of virtual monitoring reports to the UE. For example, indicating that the number of virtual monitoring reports is 1 means that the indicators of a virtual monitoring report need to be measured and calculated before the actual monitoring report is reported. As another example, if the NW indicates that the number of merged monitoring reports is 2, it means that the number of virtual monitoring reports is 1, that is, the indicators of two monitoring reports are measured and calculated each time, and then merged and reported.

[0554] In some implementations, when the UE determines CPU usage based on virtual monitoring reports and actual monitoring reports, the specific usage method of the actual monitoring reports can be found in the CPU usage description shown in Figure 11 above, and will not be repeated here. When the UE determines CPU usage based on virtual monitoring reports and actual monitoring reports, the start time of CPU usage in the virtual monitoring reports includes, but is not limited to, the earliest time unit in at least one first time unit. The first time unit identifies the time unit corresponding to the first measurement result. For example, the start time of CPU usage in the virtual monitoring reports starts from the first OFDM symbol in the earliest of the N most recent performance monitoring measurement results (e.g., CSI-RS / CSI-IM / SSB occasions) that are earlier than the CSI reference resource. When the UE determines CPU usage based on virtual monitoring reports and actual monitoring reports, the end time of CPU usage in the virtual monitoring reports includes, but is not limited to, until the performance index calculation is completed or the CSI calculation is completed. Optionally, the activated CSI-RS resource / port count is N*N0. If Scenario Example 2 is combined with the scheme in Scenario Example 1 where the UE discards some measurement results, then the activated CSI-RS resource / port count can be N*N0 minus the number of discarded measurement results, or M1*N0, or M2*N0, without limitation here.

[0555] In some implementations, the UE can report M3 (i.e., the number of virtual reports plus one, or the number of combined monitoring reports) indicators (such as L1-RSRP, PMI), or it can report a single indicator obtained by statistically analyzing M3 indicators (such as average L1-RSRP accuracy, Top1 beam accuracy).

[0556] Processing Method 2: NW indicates the test results that need to be predicted.

[0557] For example, as shown in Figure 25, the NW in this embodiment can indicate which test results to predict. For instance, if NW indicates N1=2 and N2=2, it means that N measurement results are monitored each time, N2 times, and the interval between each monitoring is N1 measurement results.

[0558] In some implementations, the UE can determine multiple (N2 segments) of CPU usage based on NW indication information and monitoring report configuration (monitoring resource cycle, reporting time, etc.). For example, in this application embodiment, the start time of the last segment of CPU usage includes, but is not limited to, starting from the first OFDM symbol of the earliest resource among the N most recent measurement results earlier than the CSI reference resource; the end time of the last segment of CPU usage includes, but is not limited to, ending with the last symbol of the PUSCH / PUCCH of the bearer report. The start time of the remaining segments of CPU usage includes, but is not limited to, starting from the first OFDM symbol of the earliest resource among the N most recent measurement results earlier than the CSI reference resource; the end time of the remaining segments of CPU usage includes, but is not limited to, usage every N1 measurement results until the performance metric calculation is completed or the CSI calculation is completed. Optionally, the CSI-RS resource / port count is activated at this time as N*N2; where, if scenario example 2 is combined with the scheme in scenario example 1 above where the UE discards some measurement results, then the activated CSI-RS resource / port count is N*N2 - the number of discarded CSI-RS occasions, or M1*N2, or M2*N2.

[0559] In some implementations, the UE can report N2 or N2*N indicators (such as L1-RSRP, PMI), or it can report a single indicator obtained by statistically analyzing N2 indicators (such as average L1-RSRP accuracy, Top1 beam accuracy).

[0560] Processing Method 3: NW is based on large and small periodic cluster CSI-RS occasion monitoring and measurement.

[0561] For example, as shown in Figure 26, the relevant parameters for the resource cycle of monitoring measurements (e.g., CSI-RS) issued by the NW are T1, N, and T2, indicating that CSI-RS resources are issued once every T2 clusters, with N measurement results issued each time, and the period interval of these N measurement results is T1; T2 can be equal to the monitoring report cycle. In this case, the NW and UE do not need to calculate the N1 measurement results to be avoided; they can measure and calculate based on the resources issued by the NW.

[0562] In some implementations, the UE determines multiple CPU usage segments based on the configuration of clustered resources and monitoring reports. For example, when determining the CPU usage of the N3 clustered resource segments within a monitoring period, the start time of the last CPU usage segment includes, but is not limited to, starting from the first OFDM symbol of the earliest resource among the N most recent measurement results earlier than the CSI reference resource; the end time of the last CPU usage segment includes, but is not limited to, until the last symbol of the PUSCH / PUCCH of the bearer report. The UE determines multiple CPU usage segments based on the configuration of clustered resources and monitoring reports. For example, when determining the CPU usage of the N3 clustered resource segments within a monitoring period, the start time of the remaining CPU usage segments (excluding the last segment) includes, but is not limited to, starting from the first OFDM symbol of the earliest resource among the N most recent measurement results earlier than the virtual CSI report; the end time of the remaining CPU usage segments includes, but is not limited to, until the performance metric calculation or CSI calculation is completed, with usage occurring every T2. Optionally, the CSI-RS resource / port count is N*N3; where, if scenario example 2 is combined with the scheme in scenario example 1 above where the UE discards some measurement results, then the CSI-RS resource / port count is N*N3 - the number of discarded CSI-RS occasions, or M1*N3, or M2*N3.

[0563] In some implementations, based on this binding method, if the last monitoring instance 1 before the monitoring report does not have time to perform measurement, for example, CSI-RS occasion1 is later than the CSI reference resource, then CSI-RS occasion1 can be used for the calculation of the next monitoring report; accordingly, the selection of N monitoring instances, the start time of the CPU, and the determination of the number of activated resources can take into account the monitoring instances of the previous observation window.

[0564] Through the content of this binding method one, this application embodiment provides a binding method for normalized prediction results and measurement results, as well as the corresponding CPU usage method and active port / resource count method, so that the UE can calculate performance indicators more accurately.

[0565] Application Example 2: The UE determines the corresponding measurement result based on the N most recent prediction results before the first reference time unit corresponding to the first monitoring report (binding method 2 as shown in Figure 11 above).

[0566] For example, the UE binds the nearest measurement result to each prediction result based on the N most recent prediction results before the CSI reference resource.

[0567] The specific binding strategy (also known as the binding mechanism) of this binding method two can be understood as determining the measurement result based on prediction. The relevant reference steps are shown in Figure 27.

[0568] Step S2701: NW sends the first information to UE.

[0569] For details, please refer to step S2201 above. For the sake of brevity, it will not be repeated here.

[0570] Step S2702: The UE determines the N most recent prediction results based on the first reference time unit corresponding to the first monitoring report.

[0571] As an example, in this application embodiment, N can be predefined by the protocol or configured by NW. The value can be 1 or greater than 1. The configuration method can be based on RRC signaling, DCI, MAC CE, etc., and is not limited here.

[0572] Step S2703: The UE determines M1 measurement results based on N prediction results.

[0573] For example, the UE can determine and bind the measurement result closest to each of the N prediction results based on N prediction results. For instance, in this embodiment, the number of measurement results found is M1, where M1 can be less than or equal to N. Optionally, the N prediction results and the M1 found measurement results need to be available before the CSI reference resource corresponding to the first monitoring report.

[0574] Step S2704: The UE determines the first indicator based on N prediction results and M1 measurement results.

[0575] Step S2705: The UE determines the first monitoring report based on the first indicator.

[0576] For example, in this embodiment, the CPU usage corresponding to the first monitoring report starts from the first OFDM symbol of the earliest resource among the most recent M (e.g., valid measurement results out of M measurement results) resources used for performance monitoring in CSI-RS / CSI-IM / SSB occasions prior to the CSI reference resource, and ends at the last symbol of the PUSCH / PUCCH carrying the first monitoring report. Optionally, the active CSI-RS resource / port count is N. Optionally, the active CSI-RS resource / port count is M.

[0577] It should be noted that the examples above in the embodiments of this application are only illustrative of the corresponding steps and do not constitute a limitation on the corresponding steps. For example, the CPU termination time corresponding to the first monitoring report in the embodiments of this application can also be determined by other methods of CPU occupation termination described in Figure 11 above, which are not limited here.

[0578] The following are some application scenarios to further illustrate the content of application example two above, and are not limited to these scenarios:

[0579] Scenario 1: For application example 2, in the actual binding process, a scenario may occur as shown in Figure 28, where multiple prediction results correspond to one measurement result.

[0580] Based on scenario 1, the terminal device can process the data in various ways, including but not limited to the following:

[0581] Processing method 1: The UE can discard part of the prediction results.

[0582] For example, the discarding method in processing method 1 may include, but is not limited to, calculating based on the prediction result closest to the distance measurement result and discarding the remaining prediction results, with the number of calculated indicators being M1; or, NW sets an offset to determine whether to discard some prediction results, that is, the UE only considers the measurement results whose distance prediction results are within the offset, with the number of calculated indicators being M2, where M2 is less than or equal to N. In this case, the UE may report N, M1, or M2 indicators (e.g., L1-RSRP, PMI); the UE may also report an indicator obtained by statistically analyzing N, M1, or M2 indicators (e.g., average L1-RSRP accuracy, Top1 beam accuracy).

[0583] Processing Method 2: The UE calculates the index corresponding to multiple prediction results and one measurement result respectively.

[0584] Scenario 2: For application example 2, in the actual binding process, NW can further instruct UE to merge multiple monitoring reports into one monitoring report for reporting (for example, UE only counts part of the CSI report and does not report it), or simply have UE count indicators at equal intervals.

[0585] Based on scenario 2, the terminal device can process the data in various ways, including but not limited to the following:

[0586] Solution 1: Introduce virtual CSI reports.

[0587] For example, as shown in Figure 29, the UE determines that the first monitoring includes the data after referring to the above steps S2703-S2705, but does not report it.

[0588] In some implementations, the NW can indicate the number of virtual monitoring reports to the UE. For example, indicating that the number of virtual monitoring reports is 1 means that the indicators of a virtual monitoring report need to be measured and calculated before the actual monitoring report is reported. As another example, if the NW indicates that the number of merged monitoring reports is 2, it means that the number of virtual monitoring reports is 1, that is, the indicators of two monitoring reports are measured and calculated each time, and then merged and reported.

[0589] In some implementations, when the UE determines CPU usage based on virtual monitoring reports and actual monitoring reports, the specific usage method of the actual monitoring reports can be found in the CPU usage description shown in Figure 11 above, and will not be repeated here. When the UE determines CPU usage based on virtual monitoring reports and actual monitoring reports, the start time of CPU usage in the virtual monitoring reports includes, but is not limited to, the earliest time unit in at least one first time unit. The first time unit identifies the time unit corresponding to the first measurement result. For example, the start time of CPU usage in the virtual monitoring reports starts from the first OFDM symbol in the earliest of the M most recent performance monitoring measurement results (e.g., CSI-RS / CSI-IM / SSB occasions) earlier than the CSI reference resource. When the UE determines CPU usage based on virtual monitoring reports and actual monitoring reports, the end time of CPU usage in the virtual monitoring reports includes, but is not limited to, until the performance index calculation is completed or the CSI calculation is completed. Optionally, the active CSI-RS resource / port count is M*N0.

[0590] In some implementations, the UE can report M3 (i.e., the number of virtual reports plus one, or the number of combined monitoring reports) indicators (such as L1-RSRP, PMI), or it can report a single indicator obtained by statistically analyzing M3 indicators (such as average L1-RSRP accuracy, Top1 beam accuracy).

[0591] Processing Method 2: NW indicates the forecast results that need to be monitored.

[0592] For example, as shown in FIG30, the NW in this embodiment of the application can indicate which prediction results to monitor, and then the UE and the NW determine the measurement results associated with the prediction results. For example, if the NW indicates N1=2 and N2=2, it means that N prediction results and associated measurement results are monitored each time, and the monitoring is performed N2 times, with an interval of N1 prediction results between each monitoring.

[0593] In some implementations, the UE can determine multiple (N2 segments) of CPU usage based on NW indication information and monitoring report configuration (monitoring resource cycle, reporting time, etc.). For example, in this embodiment, the start time of the last segment of CPU usage includes, but is not limited to, starting from the first OFDM symbol of the earliest resource among the M measurement results associated with the most recent N prediction results earlier than the CSI reference resource; the end time of the last segment of CPU usage includes, but is not limited to, ending with the last symbol of the PUSCH / PUCCH of the bearer report. The start time of the remaining segment of CPU usage includes, but is not limited to, starting from the first OFDM symbol of the earliest resource among the M measurement results associated with the most recent N prediction results earlier than the CSI reference resource; the end time of the remaining segment of CPU usage includes, but is not limited to, usage every N1 prediction results until the performance metric calculation is completed or the CSI calculation is completed. Optionally, the active CSI-RS resource / port count is M*N2 at this time.

[0594] In some implementations, the UE can report N2 or N2*N indicators (such as L1-RSRP, PMI), or it can report a single indicator obtained by statistically analyzing N2 indicators (such as average L1-RSRP accuracy, Top1 beam accuracy).

[0595] In some implementations, based on this binding method, if the last monitoring instance 1 before the monitoring report does not have time to perform measurement, for example, CSI-RS occasion1 is later than the CSI reference resource, then CSI-RS occasion1 can be used for the calculation of the next monitoring report; accordingly, the selection of N monitoring instances, the start time of the CPU, and the determination of the number of activated resources can take into account the monitoring instances of the previous observation window.

[0596] Through this second binding method, this application embodiment provides a binding method for normalized prediction results and measurement results, as well as corresponding CPU usage methods and active port / resource count methods, enabling the UE to calculate performance indicators more accurately.

[0597] Application Example 3: Based on the above binding method, this application embodiment can further add examples illustrating the binding effectiveness between prediction results and measurement results.

[0598] For example, referring to the binding method described in Application Example 2 above, when the UE binds the corresponding measurement results based on N prediction results, it can better determine the binding relationship between the prediction results and the measurement results by combining the effectiveness, so that the obtained binding relationship can be more effectively used to determine the first monitoring report.

[0599] The following are a few scenarios that further illustrate the application of the above-mentioned effective time range, and are not limited to these scenarios:

[0600] Scenario 1: The NW sends the first information to the UE, which is used to instruct the UE to report the performance monitoring report non-periodically.

[0601] In some implementations, the content of the first monitoring report reported in each cycle of this application embodiment may include one metric or multiple metrics.

[0602] In some implementations, for example, under the above binding method two, the earliest measurement result may be earlier than the PDCCH that triggers the CSI report, or the latest measurement result may be later than the CSI reference resource. In this case, when binding the prediction result and the measurement result based on binding method two under AP, the validity of the prediction result and the measurement result and the binding method can be further normalized. Specifically, it is not limited to the following processing methods:

[0603] Processing Method 1: The process of binding prediction results and measurement results is based on finding the corresponding measurement results based on valid prediction results, and discarding invalid measurement results and their corresponding prediction results.

[0604] For example, as shown in Figure 31, the prediction result is considered valid between the PDCCH that triggers the monitoring report and the CSI reference resource corresponding to the monitoring report, thereby determining the valid prediction result from the multiple prediction results obtained, and binding the measurement result closest to each prediction result based on the valid prediction result; in addition, the measurement result needs to be considered valid between the PDCCH that triggers the monitoring report and the CSI reference resource corresponding to the monitoring report, otherwise invalid measurement results and corresponding prediction results are discarded.

[0605] Processing Method 2: The process of binding prediction results and measurement results is to find the corresponding valid measurement results based on valid prediction results.

[0606] For example, as shown in Figure 32, the prediction result is considered valid between the PDCCH that triggers the monitoring report and the CSI reference resource corresponding to the monitoring report. The measurement result needs to be considered valid between the PDCCH that triggers the monitoring report and the CSI reference resource corresponding to the monitoring report. Based on the valid prediction result, the corresponding measurement result is found within the valid measurement results. Optionally, when multiple prediction results correspond to one measurement result, if it is necessary to discard some prediction results, the discarding method described in the binding method two above can be referred to.

[0607] In some implementations, the start time for CPU usage in AP CSI reporting includes, but is not limited to, starting from the first OFDM symbol of the M earliest resources used for performance monitoring, which are associated with the most recent N predicted instances of the CSI reference resource; the end time for CPU usage in AP CSI reporting includes, but is not limited to, until the last symbol of the PUSCH / PUCCH carrying the report. Optionally, the active CSI-RS resource / port count is M.

[0608] Scenario 2: NW sends the first information to UE, which is used to instruct UE to periodically / semi-statically report performance monitoring reports.

[0609] In some implementations, the content of the first monitoring report reported in each cycle of this application embodiment may include one metric or multiple metrics.

[0610] In some implementations, such as the most recent measurement result associated with the prediction result under the above binding method two, which may be later than the CSI reference resource, when binding the prediction result and the measurement result based on binding method two under P / SP CSI, the validity of the prediction result and the measurement result and the binding method can be further normalized. Specifically, this is not limited to the following processing methods:

[0611] Processing Method 1: The process of binding prediction results and measurement results is based on finding the corresponding measurement results based on valid prediction results, and discarding invalid measurement results and their corresponding prediction results.

[0612] For example, a prediction result is considered valid only if it is before the CSI reference resource corresponding to the monitoring report. Based on the valid prediction result, the measurement result closest to each prediction result is bound. In this case, the measurement result is considered valid only if it is before the CSI reference resource corresponding to the monitoring report; otherwise, invalid measurement results and their corresponding prediction results are discarded.

[0613] Processing Method 2: The process of binding prediction results and measurement results is to find the corresponding valid measurement results based on valid prediction results.

[0614] For example, prediction results are considered valid up to the CSI reference resource corresponding to the monitoring report, and measurement results are also considered valid up to the CSI reference resource corresponding to the monitoring report. The corresponding measurement result is found within the valid measurement results based on the valid prediction results. Optionally, when multiple prediction results correspond to one measurement result, if it is necessary to discard some predictions, the discarding method described in Binding Method Two above can be referred to.

[0615] The CPU usage method reported by P / SP CSI can be found in the relevant description in the second binding method above. For the sake of brevity, it will not be elaborated here.

[0616] Application Example 4: This application also provides content for monitoring based on each (per) prediction report.

[0617] For example, as shown in Figure 33, this embodiment of the application, when reporting CSI aperiodic (AP), semi-static (SP), or periodic (P) reports, can instruct the UE to monitor based on each prediction report, rather than based on each prediction result, through the NW. See the following example for specific steps:

[0618] Step S3301: The NW sends an RRC configuration to the UE, which instructs the UE to report performance monitoring reports (e.g., non-periodic, periodic, or semi-static) and to monitor based on each prediction report.

[0619] Step S3302: The UE monitors each prediction report and binds the prediction report to the corresponding measurement results.

[0620] As an example, as shown in Figure 34, in the implementation of this application embodiment, when performing step S3302, the corresponding prediction result can be found based on the prediction report first, and then the corresponding measurement result can be determined based on the found prediction result.

[0621] In some implementations, the binding method, CPU usage, and number of active ports vary depending on the CSI reporting method (e.g., P, SP, or AP). The following sections describe these differences based on the various reporting methods:

[0622] Reporting Method 1: P / SP Report.

[0623] For example, when based on P / SP reports, the UE can bind the measurement result closest to each prediction result to the prediction results within N prediction reports preceding the CSI reference resource. The prediction results within the N prediction reports and the corresponding M4 measurement results must be located before the CSI reference resource corresponding to the monitoring report. Optionally, the NW can instruct the UE to statistically analyze and report based on each prediction report, or based on statistically analyzing and reporting based on each prediction result within each prediction report, or based on statistically analyzing and reporting one indicator across N prediction reports.

[0624] In some implementations, when based on P / SP reports, the starting time unit for CPU usage includes, but is not limited to, starting from the first OFDM symbol of the earliest resource among the most recent M4 CSI-RS / CSI-IM / SSB occasions for performance monitoring that are earlier than the CSI reference resource; when based on P / SP reports, the ending time unit for CPU usage includes, but is not limited to, until the last symbol of the PUSCH / PUCCH carrying the report. Optionally, the active CSI-RS resource / port count is M4.

[0625] Reporting Method 2: AP Report.

[0626] For example, when based on AP reports, the UE can bind the nearest measurement result to each prediction result based on the prediction results within the N nearest prediction reports that are valid and close to the CSI reference resource, discarding invalid measurement results and their corresponding prediction results; or the UE can bind the nearest valid measurement result to each prediction result based on the prediction results within the N nearest prediction reports that are valid and close to the CSI reference resource. Optionally, the NW can instruct the UE to collect and report statistical indicators based on each prediction report, collect and report statistical indicators based on each prediction indicator within each prediction report, or collect and report statistical indicators based on N prediction reports.

[0627] In some implementations, when based on AP reports, the starting time unit for CPU usage includes, but is not limited to, starting from the first OFDM symbol of the earliest resource in the earliest CSI-RS / CSI-IM / SSB occasions associated with the prediction results in the most recent N prediction reports for performance monitoring, which are later than the first symbol after the PDCCH that triggered the CSI report and earlier than the CSI reference resource. When based on AP reports, the ending time unit for CPU usage includes, but is not limited to, until the last symbol of the PUSCH / PUCCH carrying the report. The active CSI-RS resource / port count is M4.

[0628] Through this content, the embodiments of this application provide a binding method for standardized prediction results and measurement results, as well as corresponding CPU timeline occupancy methods and active port / resource count methods, enabling the UE to calculate performance indicators more accurately.

[0629] Application Example 5: In order to simplify the problems that arise during the binding of prediction results and measurement results, such as one-to-many or many-to-one relationships between prediction results and measurement results, or inconsistent correspondence between prediction results and measurement results in different monitoring periods, this application embodiment also provides content on configuration of performance monitoring reports and corresponding resources based on protocol standardization.

[0630] For example, as shown in Figure 35, the steps for configuring performance monitoring reports and corresponding resources based on protocol standardization in this embodiment of the application are illustrated in the following example:

[0631] Step S3501: The NW sends an RRC configuration to the UE to instruct the UE performance monitoring report (e.g., non-periodic, periodic, or semi-static reporting).

[0632] Step S3502: The UE limits the binding of prediction results and measurement results according to the newly introduced protocol.

[0633] In some implementations, the protocol content related to binding prediction results and measurement results in this application embodiment is limited to, but not limited to, the following:

[0634] Agreement Content 1: It is stipulated that the monitoring resource cycle = P1 * the prediction report cycle, where P1 can be equal to 1 or greater than 1.

[0635] For example, as shown in Figure 36, in this case, the prediction result and the measurement result are one-to-one. For multiple prediction results from a single prediction report, the NW can configure multiple CSI reports, such as monitoring reports 1 through 3, and multiple channel state information report configurations (CSI-reportConfig), such as CSI-reportConfig1, CSI-reportConfig2, and CSI-reportConfig3, to perform monitoring, measurement, and reporting respectively; alternatively, the NW can also configure multiple CSI-reportConfigs within a single CSI report, such as monitoring report 3, for example, CSI-reportConfig 1-3. Optionally, the binding method between the prediction result and the measurement result, as well as CPU usage rules, can refer to the binding method one or binding method two described above, and are not limited here.

[0636] Agreement Content 2: It is stipulated that the forecast report period = P2 * forecast interval, and the monitoring resource period = P3 * an integer multiple of the forecast interval or the forecast interval = P4 * monitoring resource period. In this case, the monitoring and forecast are aligned and there is no inconsistency in the correlation between the forecast results and the measurement results in different monitoring periods. P2, P3, and P4 can be equal to 1 or greater than 1.

[0637] For example, if the forecast report period is an integer multiple of the forecast interval, and the monitoring resource period is equal to the forecast interval, then there is no one-to-many or many-to-many problem between forecasting and monitoring. Compared to the above protocol content 2, NW only needs to configure one type of CSI-RS resource, eliminating resource waste.

[0638] For example, if the monitoring resource period is not equal to the prediction interval, the problem of one-to-many or many-to-one relationship between prediction results and measurement results will still occur. Since there are no irregular misalignment scenarios, the binding method between prediction results and monitoring results can be standardized: For example, as shown in Figure 37, when the monitoring resource period is N times the prediction interval, that is, the number of measurement results is less than the number of prediction results, it is more reasonable to bind the prediction results based on the measurement results. Accordingly, the CPU usage rules can refer to the CPU usage rules under the binding method below. As another example, as shown in Figure 38, when the prediction interval is N times the monitoring resource period, that is, the number of measurement results is greater than the number of prediction results, it is more reasonable to bind the measurement results based on the prediction results. Accordingly, the CPU usage rules can refer to the CPU usage rules under the binding method two.

[0639] Through the content of this binding method one, this application embodiment provides a way to simplify issues related to prediction and monitoring binding by standardizing the configuration of monitoring reports and their monitoring resources, enabling the UE to calculate performance indicators more accurately.

[0640] It should be noted that the above examples are only illustrative of the embodiments of this application and do not constitute a limitation on the embodiments of this application. For example, the embodiments of this application also include examples after integrating the above multiple examples, or examples obtained after other modifications, which are not limited here.

[0641] In addition, there is currently no comprehensive and effective way to determine resource counting or port counting within resources during communication transmission. For example, there are no resource / port counting rules for monitoring and training resources of P / SP in related technologies.

[0642] Based on this, embodiments of this application provide another communication method and apparatus for providing a comprehensive and efficient way to determine resource counts or intra-resource port counts. This allows for the alignment of storage capabilities between the network network (NW) and the user equipment (UE) by standardizing the monitoring and training of resource / port counting methods, thereby improving the storage resource utilization rate on the UE side. The communication method provided in these embodiments can also be applied to the network architecture shown in Figures 7-10.

[0643] To better illustrate the application of this communication method, Figure 39 shows a schematic diagram of the main steps of the communication method provided in this application embodiment. The executing entity in Figure 39 can be a first device and / or a second device. The first device can be a terminal or a device within a terminal (e.g., a module, circuit, chip (such as a modem chip, or a SoC chip or SIP chip containing a modem core), a chip system, or a processor), or a logical node, logical module, or software that implements all or part of the terminal's functions. The second device can be an access network device or a device within an access network device (e.g., a module, circuit, chip (such as a modem chip, or a SoC chip or SIP chip containing a modem core), a chip system, or a processor), or a logical node, logical module, or software that implements all or part of the access network device's functions.

[0644] As shown in Figure 39, the method includes:

[0645] S3901: Determine the first count of the first resource based on the number of prediction windows, or the number of prediction windows and the number of observation windows.

[0646] As an example, the first resource in this application embodiment can be a resource for channel measurement or a resource for CSI report processing. This resource can be CSI-RS or SSB, etc., and is not limited here.

[0647] As an example, in the embodiments of this application, the first count corresponds to the resource count and / or the port count within the resource.

[0648] In some implementations, the methods for determining the first count vary depending on the application scenario, and are not limited to the following two scenarios:

[0649] Counting Scenario 1: Monitoring Scenario.

[0650] As an example, in this scenario, the first resource can be the first monitoring resource corresponding to the first monitoring report, and the first count is determined based on the number of prediction windows. For instance, in a monitoring scenario, the terminal device needs to measure the monitoring resource corresponding to the predicted instance to obtain a label, and then perform operations such as metric calculation.

[0651] In some implementations, embodiments of this application may determine the first count using one or more parameters, including but not limited to the following:

[0652] Parameter 1: The number of prediction windows corresponding to the first inference report.

[0653] As an example, parameter 1 can be understood as the number of prediction results (or prediction instances, prediction time units) in the first inference report, or the window length of the first inference report. The number of prediction windows corresponding to the first inference report can also be expressed as the number of prediction results in the first inference report, the number of prediction instances in the first inference report, the time window length or time domain window length of the first inference report, the number of prediction time units in the first inference report, etc., without limitation here.

[0654] In this context, reasoning can be replaced or understood as prediction, and prediction can be replaced or understood as reasoning.

[0655] In practical applications, performance monitoring can be performed on one or more inference reports or one or more inference results. Since an inference report can include inference results corresponding to N4 prediction instances, for P / SP CSI-RS resources, N4 can determine the count of the first resource that needs to be monitored and measured, as well as the count of resource ports within the first resource.

[0656] Understandably, the UE can report the number of prediction windows corresponding to the first inference report, and the NW can configure the number of prediction windows corresponding to the first inference report. Parameter 2: The number of pairings between the prediction results in the first inference report and the first monitoring resource.

[0657] As an example, parameter 2 can be understood as the number of entries in the first inference report that match all prediction results with the first monitoring resource (such as equipment, indicators, etc.). The number of pairings between prediction results and the first monitoring resource in the first inference report can also be expressed as the number of prediction-monitoring matching pairs, the number of associations between inference results and monitoring resources, the number of valid prediction-resource correspondences, etc., which are not limited here.

[0658] Parameter 3: The number of the first inference reports corresponding to the first monitoring report.

[0659] As an example, parameter 3 can be understood as the number of first inference reports associated with the first monitoring report (possibly a one-to-many relationship). The number of first inference reports corresponding to the first monitoring report can also be expressed as the number of inference reports referenced by the monitoring report, the number of related inference report instances, the number of prediction reports corresponding to the monitoring data, etc., without limitation here.

[0660] Parameter 4: First capability coefficient.

[0661] As an example, parameter 4 can be understood as a quantitative indicator representing a certain capability (such as storage capacity, monitoring capability, prediction accuracy, system performance, etc.). The first capability coefficient can also be expressed as a performance score, efficiency coefficient, etc., without limitation here.

[0662] In some implementations, to better adapt to the performance monitoring calculation method, such as whether the performance monitoring calculation method needs to calculate performance indicators such as SGCS or NMSE based on the channel matrix / precoding matrix, a first capability coefficient can be introduced when determining the first count. The value of the first capability coefficient can be reported by the capability of the first device, configured by the second device, or predefined by the protocol, and is not limited here. For example, when the first device stores the channel matrix or precoding matrix instead of the codebook for the measurement results of CSI-RS resources, the storage overhead increases, so the corresponding resource count value also needs to be increased by a factor. In this case, the increase factor, i.e., the first capability coefficient, can be determined according to the actual situation.

[0663] Parameter 5: The number of observation windows corresponding to the first inference report.

[0664] As an example, parameter 5 can be replaced or understood as the number of measurement resources corresponding to the first inference report, or the number of measurement resources required to generate the first inference report, the number of historical data corresponding to the first inference report, or the number of (time units or time samples or samples) used to observe historical data in the first inference report, etc., without limitation here.

[0665] If the type of the measurement resource is aperiodic, the number of observation windows corresponding to the first inference report can be understood as the number of resources within the aperiodic resource set. If the type of the measurement resource is periodic or semi-persistent, the number of observation windows corresponding to the first inference report can be understood as the count value for the resource, or the number of times the resource is stored.

[0666] Understandably, the UE can report the number of observation windows corresponding to the first inference report, and the NW can configure the number of observation windows corresponding to the first inference report.

[0667] Parameter 6: The number of prediction windows corresponding to the first monitoring report.

[0668] As an example, parameter 6 can be understood as the number of future prediction results monitored in the first monitoring report. The number of prediction windows corresponding to the first monitoring report can also be expressed as the number of prediction results associated with the first monitoring report, the number of prediction instances associated with the first monitoring report, the number of observation windows corresponding to the first monitoring report, the number of prediction windows corresponding to the first prediction report associated with the first monitoring report, etc., without limitation here.

[0669] Parameter 7: The number of observation windows corresponding to the first monitoring report.

[0670] As an example, parameter 7 can be understood as the number of measurement / monitoring resources corresponding to the first monitoring report, or the number of measurement / monitoring resources required to generate the first monitoring report. The number of observation windows corresponding to the first monitoring report can also be expressed as the number of prediction windows corresponding to the first monitoring report, the number of prediction windows corresponding to the first prediction report associated with the first monitoring report, etc., without limitation here.

[0671] In this embodiment, the first inference report refers to an inference report associated with the first monitoring report. For example, in this embodiment, the ID of the inference report can be linked in the configuration of the monitoring report.

[0672] Furthermore, the embodiments of this application may determine the first counting method based on the resource situation, and are not limited to the following situations:

[0673] Resource status 1: The first monitored resource is a semi-persistent resource and / or a periodic resource.

[0674] As an example, under resource scenario 1, the first count can be one of the following counting methods:

[0675] Method 1: The first count is the number of prediction windows corresponding to the first inference report.

[0676] For example, assuming the number of prediction windows corresponding to the first inference report is N4, then the first count can be N4.

[0677] Method 2: The first count is the number of pairs between the prediction results in the first inference report and the first monitoring resource.

[0678] For example, assuming the number of pairs between the prediction results in the first inference report and the first monitoring resource is M, then the first count can be M.

[0679] Method 3: The first count is the product of the following terms:

[0680] The number of prediction windows corresponding to the first inference report, and the number of the first inference reports corresponding to the first monitoring report.

[0681] For example, assuming that the first monitoring report corresponds to multiple first inference reports, and the number of prediction windows corresponding to the first inference report is N4, then the first count can be N4 * the number of first inference reports.

[0682] Method 4: The first count is the product of the following terms:

[0683] The number of pairings between the prediction results in the first inference report and the first monitoring resource, and the number of the first inference reports corresponding to the first monitoring report.

[0684] For example, assuming that the first monitoring report corresponds to multiple first inference reports, and the number of pairings between the prediction results in the first inference report and the first monitoring resource is M, then the first count can be M * the number of first inference reports.

[0685] Method 5: The first count is the product of the following terms:

[0686] The number of prediction windows corresponding to the first inference report, and the first capability coefficient.

[0687] For example, assuming the number of prediction windows corresponding to the first inference report is N4, when the resource count value needs to be increased by a factor of several, the first count can be N4 * the first capability coefficient.

[0688] Method 6: The first count is the product of the following terms:

[0689] The number of pairs between the prediction results in the first inference report and the first monitoring resource, and the first capability coefficient.

[0690] For example, assuming the number of pairs between the prediction results in the first inference report and the first monitored resource is M, and the resource count needs to be increased by a factor of several, then the first count can be M * the first capability coefficient.

[0691] Method 7: The first count is the product of the following terms:

[0692] The number of prediction windows corresponding to the first inference report, the number of first inference reports corresponding to the first monitoring report, and the first capability coefficient.

[0693] For example, assuming that the first monitoring report corresponds to multiple first inference reports, and the number of prediction windows corresponding to the first inference report is N4, when the resource count value needs to be increased by a factor of several, the first count can be N4 * the number of first inference reports * the first capability coefficient.

[0694] Method 8: The first count is the product of the following terms:

[0695] The number of pairs between the prediction results in the first inference report and the first monitoring resource, the number of the first inference reports corresponding to the first monitoring report, and the first capability coefficient.

[0696] For example, assuming that the first monitoring report corresponds to multiple first inference reports, and the number of pairings between the prediction results in the first inference report and the first monitoring resource is M, when the resource count value needs to be increased by a factor of several, the first count can be M * the number of first inference reports * the first capability coefficient.

[0697] As an example, in this embodiment of the application, the first device may also send first information to the second device, which may be used to indicate the counting method supported by the first device under resource condition 1. For example, if the terminal does not support a stored channel matrix or a precoding matrix, the first information may include a counting method that supports method 1; as another example, if the terminal can support a stored channel matrix or a precoding matrix, the first information may include a counting method that supports method 5.

[0698] Resource scenario 2: The first monitoring resource and the inference resource corresponding to the first inference report are the same resource (denoted as resource X), and are indicated in the same channel state information report configuration. It can be understood that resource X is both a monitoring resource and an inference resource.

[0699] In this resource scenario 2, it can be understood that the terminal device needs to save both the measurement results corresponding to the inference observation window and the measurement results corresponding to the monitoring observation window.

[0700] As an example, in resource scenario 2, the first count of resource X can be: the first count is the sum of the number of observation windows in the first inference report and the number of observation windows in the first monitoring report.

[0701] For example, assuming the number of observation windows corresponding to the first inference report is Kp and the number of observation windows corresponding to the first monitoring report is N4, then the first count can be (N4+Kp).

[0702] Counting Scenario 2: Training Scenario.

[0703] As an example, in this second scenario, the first resource can be the first training resource corresponding to the first training configuration, and the first count is determined based on the number of prediction windows and / or the number of observation windows. For example, in a training scenario, the terminal needs to obtain the measurement results corresponding to the model input (i.e., the CSI-RS measurement results within the observation window, which can be understood as input) and the measurement results corresponding to the model output (i.e., the CSI-RS measurement results within the prediction window, which can be understood as label) to perform model training and other operations. Understandably, since the measurement results are used internally by the terminal and not by the network device, the network device can instruct the terminal not to report measurement information when configuring CSI reporting, but will configure the corresponding CSI-RS configuration information.

[0704] In some implementations, embodiments of this application may determine the first count using one or more parameters, including but not limited to the following:

[0705] Parameter 1: The number of observation windows corresponding to the first training report.

[0706] As an example, parameter 1 can be understood as the number of data time windows (or sample intervals) corresponding to the model input required for model training in the first training report. The number of observation windows corresponding to the first training report can also be expressed as the number of historical windows of training data corresponding to the model input, the number of observation intervals, the number of reference data time periods, etc., without limitation here. The number of observation windows corresponding to the first training report can be consistent with the number of observation windows corresponding to the first inference report supported by the UE.

[0707] Parameter 2: The numerical value of the time domain dimension of the model input data.

[0708] As an example, parameter 2 can be understood as the length of the model input data in the time dimension (such as the number of time steps or the sequence length). The numerical value of the time dimension of the model input data can also be expressed as the input time step, the length of the time series input, the size of the data time window, etc., without limitation here.

[0709] Parameter 3: Second capability coefficient.

[0710] As an example, parameter 3 can be understood as a quantitative indicator representing a certain capability (such as storage capacity, monitoring capability, training capability, prediction accuracy, system performance, etc.). The first capability coefficient can also be expressed as a performance score, efficiency coefficient, etc., without limitation here.

[0711] In this application embodiment, the second capability coefficient is predefined; or, the second capability coefficient is determined by the first device; or, the second capability coefficient is determined by the second device.

[0712] Parameter 4: The number of prediction windows corresponding to the first training report.

[0713] As an example, parameter 4 can be understood as the number of time windows (or sample intervals) of data corresponding to the model output required for model training in the first training report. The number of prediction windows corresponding to the first training report can also be expressed as the number of prediction intervals corresponding to the model output, the number of future time steps, the output window size, etc., without limitation here. The number of prediction windows corresponding to the first training report can be consistent with the number of prediction windows corresponding to the first inference report supported by the UE.

[0714] Parameter 5: The time domain dimension of the model output data.

[0715] As an example, parameter 5 can be understood as the length of the model output data in the time dimension (such as the number of predicted future time steps). The time dimension of the model output data can also be expressed as the output time step, the length of the predicted sequence, the size of the future window, etc., without limitation here.

[0716] Parameter 6: Third capability coefficient.

[0717] As an example, parameter 6 can be understood as a quantitative indicator representing a certain capability (such as storage capacity, monitoring capability, training capability, prediction accuracy, system performance, etc.). The first capability coefficient can also be expressed as a performance score, efficiency coefficient, etc., without limitation here.

[0718] In this application embodiment, the third capability coefficient is predefined; or, the third capability coefficient is determined by the first device; or, the third capability coefficient is determined by the second device.

[0719] In this embodiment, the first inference report refers to an inference report associated with the first monitoring report. For example, in this embodiment, the ID of the inference report can be linked in the configuration of the monitoring report.

[0720] Furthermore, the embodiments of this application may determine the first counting method based on the resource situation, and are not limited to the following situations:

[0721] Resource Situation 1: The first training resource was split into two resources.

[0722] As an example, the first training resources may include model input resources and model output resources, where the model input resources and model output resources are different, and the model input resources and model output resources can be configured in different channel state information reporting configurations.

[0723] As an example, in resource case 1, the first count can be the first count of the first training resource and the second count of the model input resource; and / or, the first count of the first training resource can be the third count of the model output resource.

[0724] In some implementations, the second count in the embodiments of this application can be one of the following counting methods:

[0725] Method 1: The second count is the number of observation windows corresponding to the first training report.

[0726] For example, if the number of observation windows corresponding to the first training report is Kp, then the second count can be Kp.

[0727] Method 2: The second count is the value of the time domain dimension of the model input data.

[0728] For example, assuming the time-domain dimension of the model input data is Kp, the second count can be Kp.

[0729] Method 3: The second count is the product of the following terms:

[0730] The number of observation windows corresponding to the first training report, and the second capability coefficient.

[0731] For example, assuming the number of observation windows corresponding to the first training report is Kp, when the resource count needs to be increased by a factor, the second count can be Kp * the second capability coefficient.

[0732] Method 4: The second count is the product of the following terms:

[0733] The model input data includes the time-domain dimension values ​​and the second capability coefficient.

[0734] For example, assuming the time-domain dimension of the model input data is Kp, when the resource count needs to be increased by a factor, the second count can be Kp * the second capability coefficient.

[0735] In some implementations, the third count in the embodiments of this application can be one of the following counting methods:

[0736] Method 1: The third count is the number of prediction windows corresponding to the first training report.

[0737] For example, if the number of prediction windows corresponding to the first training report is N4, then the third count can be N4.

[0738] Method 2: The third count is the value of the time domain dimension of the model output data.

[0739] For example, assuming the time-domain dimension of the model output data is N4, then the third count can be N4.

[0740] Method 3: The third count is the product of the following terms:

[0741] The number of prediction windows corresponding to the first training report, and the third capability coefficient.

[0742] For example, assuming the number of prediction windows corresponding to the first training report is N4, when the resource count needs to be increased by a factor of several, the third count can be N4 * the second capability coefficient.

[0743] Method 4: The third count is the product of the following terms:

[0744] The model outputs data in the time domain and a third capability coefficient.

[0745] For example, assuming the time-domain dimension of the model output data is N4, and the resource count needs to be increased by a factor of several, the third count can be N4 * the third capability coefficient.

[0746] Resource scenario 2: The first training resource can be the same resource.

[0747] As an example, the first training resource can also be used as both a model input resource and a model output resource, in which case the model input resource and the model output resource are the same, and the model input resource and the model output resource can be configured in the same channel state information configuration.

[0748] As an example, in resource case 2, the first count of the first training resource is the sum of the second count of the model input resource and the third count of the model output resource.

[0749] For example, assuming the second count is Kp and the third count is N4, then the first count is (Kp + N4); assuming the second count is (Kp * second ability coefficient) and the third count is (N4 * third ability coefficient), then the first count is (Kp * second ability coefficient + N4 * third ability coefficient). Wherein, when the second ability coefficient and the third ability coefficient are the same, the first count is ((Kp + N4) * ability coefficient).

[0750] As an example, in resource case 2, the first count of the first training resource is one of the following:

[0751] The first count is (Kp+N4);

[0752] The first count is (Kp * second ability coefficient + N4 * third ability coefficient). When the second ability coefficient and the third ability coefficient are the same ability coefficient, the first count is ((Kp + N4) * ability coefficient).

[0753] As an example, in this embodiment of the application, the first device can also send second information to the second device. This second information can be used to indicate the counting method supported by the first device under resource condition 2. For example, the terminal can indicate the resource counting method corresponding to the supported input, or the resource counting method corresponding to the supported label, or the resource counting method corresponding to the supported input is different from the resource counting method corresponding to the supported label, or the resource counting method corresponding to the supported input is the same as the resource counting method corresponding to the supported label, through capability reporting (i.e., sending the second information).

[0754] As an example, in the above resource counting scenario, in this embodiment, the CPU occupancy start time corresponding to the first monitoring report corresponds to the earliest time unit among all resource opportunities corresponding to the first monitored resource. The number of all resource opportunities corresponding to the first monitored resource is determined based on the number of prediction windows corresponding to the first inference report; the first inference report is an inference report associated with the first monitoring report. Optionally, the number of all resource opportunities corresponding to the first monitored resource is the number of prediction windows corresponding to the first inference report; or, the number of all resource opportunities corresponding to the first monitored resource is the product of the following: the number of prediction windows corresponding to the first inference report and the number of first inference reports corresponding to the first monitoring report.

[0755] In this embodiment, the time unit can refer to the smallest time granularity in system monitoring or resource scheduling, that is, the time interval unit for recording or allocating resources (such as CPU usage). The time unit can also be expressed as time granularity (such as the earliest time granularity of the monitored resource corresponding to the start time of CPU usage), time step, slot, time slot, symbol, OFDM, etc., which are not limited here.

[0756] Through the above scheme, this application embodiment enables network devices and terminals to align storage capabilities by standardizing the resource / port counting method corresponding to monitoring and training resources, effectively improving the storage resource utilization rate on the terminal side. Furthermore, regarding the pairing content between the prediction result in the first inference report and the first monitoring resource described in the above counting scenario one (monitoring scenario), this application embodiment can refer to the embodiment content described in Figures 11 to 38 above to pair the prediction result in the first inference report with the measurement result corresponding to the first monitoring resource, thereby obtaining the pairing quantity. For the sake of brevity, this will not be elaborated upon here.

[0757] Based on the same technical concept as the above-described method embodiments, this application provides a corresponding communication device that can be used to perform the functions of the relevant steps in the above-described method embodiments. This function can be implemented in hardware, software, or by hardware executing corresponding software. The hardware or software includes one or more modules corresponding to the above functions. The communication device can be a terminal or access network device, or a device within the terminal or access network device (e.g., a module, communication module, circuit or chip responsible for communication functions (such as a modem chip, or a SoC chip or SIP chip containing a modem core), chip system, or processor), or a logical node, logical module, or software capable of implementing all or part of the terminal or functions.

[0758] In one possible implementation, the communication device provided in this application embodiment has the structure shown in FIG40, including a processing unit 4002. Optionally, the communication device further includes an interface unit 4001. The functions of each unit in the communication device 4000 are described below.

[0759] Interface unit 4001 is used for inputting and / or outputting information. Input information can be replaced by received information, and output information can be replaced by transmitted information. When outputting information, interface unit 4001 can output information to other devices outside of communication device 4000, or to other units within communication device 4000. In some embodiments, interface unit 4001 can be implemented through at least one of a physical interface, a communication module, a communication interface, and an input / output interface. In other embodiments, interface unit 4001 can be implemented through an interface circuit, such as a mobile communication module. The mobile communication module may include one or more of at least one antenna, at least one filter, a switch, a power amplifier, a low-noise amplifier (LNA), etc. Interface unit 4001 is used to perform the receiving and transmitting operations in the above method embodiments.

[0760] In this application, the interface unit 4001 may also have other names, such as a transceiver unit or a communication unit. Optionally, the interface unit 4001 may include a receiving unit and / or a sending unit, used for inputting information and outputting information, respectively. The receiving unit is used to perform the receiving operation in the above method embodiments. The sending unit is used to perform the sending operation in the above method embodiments.

[0761] The processing unit 4002 can be used to support the communication device 4000 in performing the processing actions in the above method embodiments. The processing unit 4002 can be implemented by one or more processors. For example, the processor can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), microprocessors (MCUs), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. A general-purpose processor can be a microprocessor or any conventional processor. The processing unit 4002 is used to perform processing-related operations in the above method embodiments, for example, to instruct operations other than receiving and sending operations in the above method embodiments.

[0762] In one embodiment, the communication device 4000 is applied to the first device in any of Figures 11 to 37 shown in the embodiments of this application. The specific functions of the processing unit 4002 in this embodiment will be described below.

[0763] The processing unit 4002 is configured to: receive first information through the interface unit 4001, the first information being used to instruct the terminal device to determine a first monitoring report; determine a first indicator based on N prediction results and M measurement results; wherein N and M are positive integers greater than or equal to 1; the M measurement results include the first measurement result, and the N prediction results include the first prediction result; the first time unit corresponding to the first measurement result and the second time unit corresponding to the first prediction result have a first time relationship; and determine the first monitoring report according to the first indicator.

[0764] In one possible design, the first time unit corresponding to the first measurement result includes at least one of the following:

[0765] The time unit in which the first set of measurement resources is located to determine the first measurement result;

[0766] The time unit in which the Channel State Information (CSI) reference resource corresponding to the first measurement result is located;

[0767] The time unit in which the first measurement result takes effect;

[0768] The CSI reference resource corresponding to the CSI report that carries the first prediction result bound to the first measurement result.

[0769] In one possible design, the second time unit corresponding to the first prediction result includes at least one of the following:

[0770] The time unit in which the CSI reference resource corresponding to the first prediction result is located;

[0771] The time unit in which the first prediction result takes effect;

[0772] The CSI reference resource corresponding to the CSI report carrying the first prediction result.

[0773] In one possible design, the first time relationship between the first time unit and the second time unit includes at least one of the following:

[0774] The time interval between the first time unit and the second time unit is less than or equal to the first time interval;

[0775] The first time unit is the Xth time unit closest to the second time unit, where X is a positive integer;

[0776] The first time unit is no later than the second time unit;

[0777] The second time unit is the Y-th time unit closest to the first time unit, where Y is a positive integer;

[0778] The second time unit is no later than the first time unit.

[0779] In one possible design, the processing unit 4002 is further configured to:

[0780] Determine the M time units corresponding to the M measurement results; based on the first time unit corresponding to any one of the M measurement results, determine the second time unit.

[0781] In one possible design, the processing unit 4002 is further configured to:

[0782] When multiple measurement results correspond to the same second time unit, one time unit is selected from the multiple measurement results as the first time unit.

[0783] In one possible design, the processing unit 4002 is further configured to:

[0784] Determine N time units corresponding to N prediction results; determine the first time unit based on the second time unit corresponding to any one of the N prediction results.

[0785] In one possible design, the processing unit 4002 is further configured to:

[0786] When multiple prediction results correspond to the same first time unit, one time unit is selected from the multiple prediction results as the second time unit.

[0787] In one possible design, the N prediction results are the N prediction results closest to the first reference time unit corresponding to the first monitoring report.

[0788] In one possible design, the CPU usage start time corresponding to the first monitoring report corresponds to the earliest time unit in at least one first time unit, and the at least one first time unit is a first time unit determined based on the second time units corresponding to the N prediction results.

[0789] In one possible design, the CPU usage termination time corresponding to the first monitoring report is determined by one or more of the following methods:

[0790] The CPU usage termination time is determined based on the time it takes to complete the calculation of the first indicator; or...

[0791] The CPU occupancy termination time is determined based on the time when the CSI calculation is completed; or...

[0792] The CPU occupancy termination time is determined based on the last symbol of the PUSCH / PUCCH carrying the first monitoring report; or,

[0793] The last symbol of the Z′ symbol used for CSI-RS occasions for performance monitoring.

[0794] In one possible design, the processing unit 4002 is further configured to:

[0795] The second reference time unit corresponding to the first prediction report is determined based on the first reference time unit corresponding to the first monitoring report; the first prediction report includes the N prediction results.

[0796] In one possible manner, the first prediction report meets a third constraint, which includes, but is not limited to, one or more of the following: at least one of the N prediction results corresponds to a measurement result before the first reference time unit corresponding to the first monitoring report; or, the first prediction report contains at least one valid prediction result, and the measurement result corresponding to the valid prediction result is before the first reference time unit corresponding to the first monitoring report.

[0797] In one possible design, the first reference time unit includes one or more of the following:

[0798] The uplink time unit where the first monitoring report is located;

[0799] The CSI reference resource corresponding to the first monitoring report;

[0800] The reference measurement resource set used to generate the first monitoring report.

[0801] In one possible design, the second reference time unit includes one or more of the following:

[0802] The uplink time unit in which the first forecast report is located;

[0803] The CSI reference resource corresponding to the first forecast report;

[0804] The first prediction report includes the time unit corresponding to the reference prediction results.

[0805] In one possible design, the second time unit satisfies a first constraint, which includes at least one of the following conditions:

[0806] The first time unit corresponding to the second time unit is within the valid time range corresponding to the first monitoring report;

[0807] The second time unit is within the valid time range corresponding to the first monitoring report.

[0808] In one possible design, the first prediction result satisfies a second constraint, which includes at least one of the following conditions:

[0809] The second reference time unit corresponding to the first prediction report is within the valid time range, the first prediction report includes the first prediction result; the time during which the first prediction result takes effect is within the valid time range; wherein, the first prediction result is determined based on the first prediction report, or, the first prediction result has been acquired by the terminal device.

[0810] In one possible design, the effective time range includes one or more of the following:

[0811] Not later than the first reference time unit corresponding to the first monitoring report;

[0812] No earlier than the time unit in which the control information used to indicate the first monitoring report is located;

[0813] Not earlier than the first offset time unit, the time interval between the first offset time unit and the time unit where the control information used to indicate the first monitoring report is located is the first time length;

[0814] No later than the second time offset unit, the time interval between the second time offset unit and the second reference time unit corresponding to the first prediction report is the second time length.

[0815] In one possible design, the processing unit 4002 is further configured to:

[0816] If the second time unit does not meet the first constraint, the first prediction result is not used for the calculation of the first index; or,

[0817] If the first time unit does not meet the first constraint condition, the first measurement result is not used for the calculation of the first index.

[0818] In one possible design, N satisfies at least one of the following conditions:

[0819] The maximum value of N is configured or indicated by the network;

[0820] N is preset by the protocol.

[0821] The communication device can be a terminal.

[0822] A more detailed description of the processing unit 4002 and the interface unit 4001 can be obtained directly from the relevant description in the method embodiment shown in Figure 11, and will not be repeated here.

[0823] In one embodiment, the communication device 4000 is applied to the first or second device in the embodiment of this application shown in FIG38. The specific functions of the processing unit 4002 in this embodiment will be described below.

[0824] The processing unit 4002 is configured to: determine a first count of a first resource based on the number of prediction windows, or the number of prediction windows and the number of observation windows, wherein the first count corresponds to a resource count, and / or a port count within the resource.

[0825] In one possible approach, the first resource is the first monitoring resource corresponding to the first monitoring report, and the first count is determined based on the number of prediction windows.

[0826] In one possible approach, the processing unit 4002 is configured to determine the first count using one or more of the following: the number of prediction windows corresponding to the first inference report, the number of pairings between the prediction results in the first inference report and the first monitoring resource, the number of first inference reports corresponding to the first monitoring report, a first capability coefficient, the number of observation windows corresponding to the first inference report, or the number of prediction windows corresponding to the first monitoring report, and the number of observation windows corresponding to the first monitoring report; the first inference report is an inference report associated with the first monitoring report.

[0827] In one possible manner, the first capability coefficient is predefined; or, the first capability coefficient is determined by the first device; or, the first capability coefficient is determined by the second device.

[0828] In one possible manner, the first count is one of the following counting methods:

[0829] The first count is the number of prediction windows corresponding to the first inference report;

[0830] The first count is the number of pairs between the prediction results in the first inference report and the first monitoring resource;

[0831] The first count is the product of the following: the number of prediction windows corresponding to the first inference report, and the number of the first inference reports corresponding to the first monitoring report;

[0832] The first count is the product of the following: the prediction results within the first inference report, the number of pairings between the first monitoring resources, and the number of the first inference reports corresponding to the first monitoring report;

[0833] The first count is the product of the following: the number of prediction windows corresponding to the first inference report, and the first capability coefficient;

[0834] The first count is the product of the following: the prediction results in the first inference report, the number of pairings between the first monitoring resources, and the first capability coefficient;

[0835] The first count is the product of the following: the number of prediction windows corresponding to the first inference report, the number of first inference reports corresponding to the first monitoring report, and the first capability coefficient; or,

[0836] The first count is the product of the following: the number of pairs between the prediction results in the first inference report and the first monitoring resource, the number of the first inference reports corresponding to the first monitoring report, and the first capability coefficient;

[0837] The first count is the sum of the number of observation windows in the first inference report and the number of prediction windows in the first monitoring report;

[0838] The first count is the sum of the number of observation windows in the first inference report and the number of observation windows in the first monitoring report;

[0839] The first reasoning report is associated with the first monitoring report.

[0840] In one possible approach, the processing unit 4002 is further configured to send or receive first information via the interface unit 4001, the first information being used to indicate the counting method supported by the first device.

[0841] In one possible approach, the first resource is a first training resource corresponding to a first training configuration, and the first count is determined based on the number of prediction windows and / or the number of observation windows.

[0842] In one possible approach, the first training resource includes model input resources and model output resources;

[0843] The first count of the first training resource is the sum of the second count of the model input resource and the third count of the model output resource, and the model input resource is different from the model output resource; or, the first count of the first training resource is the second count of the model input, and the model input resource is the same as the model output resource; or the first count of the first training resource is the third count of the model output, and the model input resource is the same as the model output resource.

[0844] In one possible manner, the second count is one of the following counting methods:

[0845] The second count is the number of observation windows corresponding to the first training report;

[0846] The second count is the value of the time domain dimension of the model input data;

[0847] The second count is the product of the following terms: the number of observation windows corresponding to the first training report, and the second capability coefficient; or,

[0848] The second count is the product of the following terms: the value of the time-domain dimension of the model input data, and the second capability coefficient.

[0849] In one possible manner, the second capability coefficient is predefined; or, the second capability coefficient is reported by the second device; or, the second capability coefficient is determined by the first device.

[0850] In one possible approach, the processing unit 4002 is used to determine the second count by one or more of the following: the number of observation windows corresponding to the first training report, the time domain dimension corresponding to the model input data, or the second capability coefficient.

[0851] In one possible manner, the third count is one of the following counting methods:

[0852] The third count is the number of prediction windows corresponding to the first training report;

[0853] The third count is the temporal dimension of the model output data;

[0854] The third count is the product of the following terms: the number of prediction windows corresponding to the first training report, and the third capability coefficient; or,

[0855] The third count is the product of the following: the temporal dimension of the model output data, and the third capability coefficient.

[0856] In one possible manner, the third capability coefficient is predefined; or, the second capability coefficient is determined by the first device; or, the second capability coefficient is determined by the second device.

[0857] In one possible approach, the processing unit 4002 is used to determine the third count by one or more of the following: the number of prediction windows corresponding to the first training report, the temporal dimension corresponding to the model output data, or the third capability coefficient.

[0858] In one possible approach, the processing unit 4002 is further configured to send or receive second information via the interface unit 4001, the second information being used to indicate the counting method supported by the first device.

[0859] In one possible approach, the CPU usage start time corresponding to the first monitoring report corresponds to the earliest time unit among all resource timings corresponding to the first monitoring resource, and the number of all resource timings corresponding to the first monitoring resource is determined based on the number of prediction windows corresponding to the first inference report; the first inference report is an inference report associated with the first monitoring report.

[0860] In one possible approach, the number of all resource opportunities corresponding to the first monitored resource is equal to the number of prediction windows corresponding to the first inference report; or, the number of all resource opportunities corresponding to the first monitored resource is the product of the following: the number of prediction windows corresponding to the first inference report and the number of first inference reports corresponding to the first monitoring report.

[0861] In one possible approach, the processing unit 4002 is further configured to pair the first prediction result with the first measurement result, wherein the first time unit corresponding to the first measurement result and the second time unit corresponding to the first prediction result have a first time relationship; the N prediction results in the first prediction report include the first prediction result, and the M measurement results of the first monitoring resource include the first measurement result.

[0862] A more detailed description of the processing unit 4002 and the interface unit 4001 can be obtained directly from the relevant description in the method embodiment shown in Figure 38, and will not be repeated here.

[0863] It should be noted that the module division in the above embodiments of this application is illustrative and only represents a logical functional division. In actual implementation, there may be other division methods. Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, exist as separate physical units, or have two or more units integrated into one unit. The integrated units can be implemented in hardware, as software functional units, or in a combination of hardware and software. Whether a function is executed in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0864] For example, the functional unit in any of the above devices may be one or more integrated circuits configured to implement the above methods, such as one or more ASICs, one or more CPUs, one or more MCUs, one or more DSPs, or one or more FPGAs, or a combination of at least two of these integrated circuit forms.

[0865] If the aforementioned integrated units are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) or processor to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0866] In one possible implementation, the communication device provided in this application embodiment is shown in FIG41. The communication device 4100 includes a processor 4102. Optionally, the communication device 4100 further includes an interface circuit 4101 and a memory 4103. The interface circuit 4101, the processor 4102, and the memory 4103 are coupled to each other.

[0867] Optionally, the interface circuit 4101, processor 4102, and memory 4103 are coupled to each other via bus 4104. Bus 4004 can be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. Buses can be divided into address buses, data buses, control buses, etc. For ease of illustration, only one thick line is used in Figure 41, but this does not mean that there is only one bus or one type of bus.

[0868] Interface circuit 4101 is used for inputting and / or outputting information. Input information can be replaced with received information, and output information can be replaced with transmitted information. When outputting information, interface circuit 4101 can output information to other devices outside of communication device 4100, or to other units within communication device 4100. For example, interface circuit 4101 can be implemented through at least one of a physical interface, a communication module, a communication interface, an input / output interface, and a mobile communication module. The mobile communication module may include one or more of at least one antenna, at least one filter, a switch, a power amplifier, an LNA, etc. Interface circuit 4101 is used to perform the receiving and transmitting operations in the above method embodiments.

[0869] Interface circuit 4101 may be one of the following: a transceiver, a transceiver circuit, a communication circuit, an interface, a communication interface, or an input / output interface (e.g., a chip's input / output interface). Interface circuit 4101 may include an input interface circuit and an output interface circuit, used for inputting information and outputting information, respectively. The input interface circuit is used to perform the receiving operation in the above method embodiments. The output interface circuit is used to perform the transmitting operation in the above method embodiments.

[0870] The transceiver can be used for communication with other communication devices. For example, if communication device 4100 is a terminal, the transceiver can be used to communicate with an access network device or with another terminal. As another example, if communication device 4100 is an access network device, the transceiver can be used to communicate with a terminal or with another access network device.

[0871] Optionally, the transceiver may include a receiver and / or a transmitter. The receiver is used to perform the receiving operation in the above method embodiments. The transmitter is used to perform the sending operation in the above method embodiments.

[0872] Optionally, the transceiver can be integrated with the processor 4102 or exist independently and be coupled to the processor 4102 through the interface circuit of the communication device 4100. This application embodiment does not specifically limit this.

[0873] Processor 4102 can be used to support communication device 4100 in performing the processing actions in the above method embodiments. When communication device 4100 is used to implement the above method embodiments, processor 4102 can also be used to implement the functions of processing unit 4002. Processor 4102 can be a CPU, or other general-purpose processors, DSPs, ASICs, FPGAs, or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. General-purpose processors can be microprocessors or any conventional processor. Processor 4102 is used to perform processing-related operations in the above method embodiments, for example, to instruct operations other than receiving and sending operations in the above method embodiments.

[0874] In one embodiment, the communication device 4100 is applied to the first device in any of the embodiments of this application shown in Figures 11 to 38. The specific functions of the processor 4102 in this embodiment will be described below.

[0875] The processor 4102 is configured to: receive first information via interface circuit 4101, the first information being used to instruct a terminal device to determine a first monitoring report; determine a first indicator based on N prediction results and M measurement results; wherein N and M are positive integers greater than or equal to 1; the M measurement results include the first measurement result, and the N prediction results include the first prediction result; the first time unit corresponding to the first measurement result and the second time unit corresponding to the first prediction result have a first time relationship; and determine the first monitoring report according to the first indicator.

[0876] In one embodiment, the communication device 4100 is applied to the first or second device in the embodiment of this application shown in FIG39. The specific functions of the processor 4102 in this embodiment will be described below.

[0877] Processor 4102 is configured to: determine a first count of a first resource based on the number of prediction windows, or the number of prediction windows and the number of observation windows, the first count corresponding to a resource count, and / or a port count within the resource.

[0878] The specific functions of processor 4102 can be found in the description of the communication methods provided in the above embodiments and examples of this application, as well as the specific functional description of communication device 4000 in the embodiment of this application shown in FIG40, which will not be repeated here.

[0879] Memory 4103 is used to store program instructions and / or data. Specifically, program instructions may include program code, which includes computer operation instructions. Memory 4103 may include RAM and may also include non-volatile memory, such as at least one disk storage device. Processor 4102 executes the program instructions stored in memory 4103 and uses the data stored in memory 4103 to implement the above-mentioned functions, thereby realizing the communication method provided in the embodiments of this application. Memory 4103 may be integrated with processor 4102 or may be a memory outside the communication device.

[0880] It is understood that the memory 4103 in Figure 41 of this application can be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory. The non-volatile memory can be ROM, programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory can be RAM, which is used as an external cache. By way of example, but not limitation, many forms of RAM are available, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous linked dynamic random access memory (SLDRAM), and direct rambus RAM (DR RAM). It should be noted that the memory of the systems and methods described herein is intended to include, but is not limited to, these and any other suitable types of memory.

[0881] Based on the above embodiments, this application also provides a computer program product including computer-executable instructions, which, when run, causes the methods provided in the above embodiments to be executed.

[0882] Based on the above embodiments, this application also provides a computer-readable storage medium storing a computer program, which, when executed by a computer, causes the computer to perform the methods provided in the above embodiments.

[0883] The storage medium can be any available medium that a computer can access. For example, but not limited to, a computer-readable medium can include RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage media or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer.

[0884] Based on the above embodiments, this application also provides a chip for reading a computer program stored in a memory and implementing the method provided in the above embodiments.

[0885] Based on the above embodiments, this application provides a chip system including a processor for supporting a computer device in implementing the functions involved in the devices in the above embodiments. In one possible design, the chip system further includes a memory for storing necessary programs and data of the computer device. The chip system may be composed of chips or may include chips and other discrete components.

[0886] In the various embodiments of this application, unless otherwise specified or in case of logical conflict, the terminology and / or descriptions of different embodiments are consistent and can be referenced by each other. The technical features of different embodiments can be combined to form new embodiments according to their inherent logical relationship.

[0887] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to this application. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in one or more blocks of the flowchart illustrations and / or one or more blocks of the block diagrams.

[0888] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means that implement the functions specified in one or more flowcharts and / or one or more block diagrams.

[0889] These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process, such that the instructions, which execute on the computer or other programmable apparatus, provide steps for implementing the functions specified in one or more flowcharts and / or one or more block diagrams.

[0890] In this application, the terms "system" and "network" are used interchangeably. "At least one item" refers to one or more items, and "more than one item" refers to two or more items. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone, where A and B can be singular or plural. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. In the textual description of this application, the character " / " generally indicates that the preceding and following related objects have an "or" relationship.

[0891] It is understood that the various numerical designations used in the embodiments of this application are merely for descriptive convenience and are not intended to limit the scope of the embodiments of this application. The order of the process numbers described above does not imply the order of execution; the execution order of each process should be determined by its function and internal logic.

[0892] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

Claims

1. A communication method applied to a first device, the method comprising: include: A first count of a first resource is determined based on the number of prediction windows, or the number of prediction windows and the number of observation windows, where the first count corresponds to the resource count and / or the port count within the resource.

2. The method of claim 1, wherein, The first resource is the first monitoring resource corresponding to the first monitoring report, and the first count is determined based on the number of prediction windows.

3. The method of claim 2, wherein, The first count is one of the following counting methods: The first count is the number of prediction windows corresponding to the first inference report; The first count is the number of pairs between the prediction results in the first inference report and the first monitoring resource; The first count is the product of the following: the number of prediction windows corresponding to the first inference report, and the number of the first inference reports corresponding to the first monitoring report; The first count is the product of the following: the number of pairs between the prediction results in the first inference report and the first monitoring resource, and the number of the first inference reports corresponding to the first monitoring report; The first count is the product of the following: the number of prediction windows corresponding to the first inference report, and the first capability coefficient; The first count is the product of the following: the number of pairs between the prediction results in the first inference report and the first monitoring resource, and the first capability coefficient; The first count is the product of the following: the number of prediction windows corresponding to the first inference report, the number of first inference reports corresponding to the first monitoring report, and the first capability coefficient; or, The first count is the product of the following: the number of pairs between the prediction results in the first inference report and the first monitoring resource, the number of the first inference reports corresponding to the first monitoring report, and the first capability coefficient; The first reasoning report is associated with the first monitoring report.

4. The method of claim 3, wherein, The first capability coefficient is predefined; or, the first capability coefficient is determined by the first device; or, the first capability coefficient is determined by the second device.

5. The method according to claim 3 or 4, characterized in that, The method further includes: Sending or receiving first information, the first information being used to indicate the counting method supported by the first device.

6. The method of claim 1, wherein, The first resource is the first training resource corresponding to the first training configuration, and the first count is determined based on the number of prediction windows and / or the number of observation windows.

7. The method of claim 6, wherein, The first training resources include model input resources and model output resources; The first count of the first training resource is the sum of the second count of the model input resource and the third count of the model output resource, and the model input resource and the model output resource are the same; or, The first count of the first training resource is the second count of the model input, and the model input resource is not the same as the model output resource; or The first count of the first training resource is the third count of the model output, and the model input resource is different from the model output resource.

8. The method according to claim 6 or 7, characterized in that, The second count is one of the following counting methods: The second count is the number of observation windows corresponding to the first training report; The second count is the value of the time domain dimension of the model input data; The second count is the product of the following terms: the number of observation windows corresponding to the first training report, and the second capability coefficient; or, The second count is the product of the following terms: the value of the time-domain dimension of the model input data, and the second capability coefficient.

9. The method of claim 8, wherein, The second capability coefficient is predefined; or, the second capability coefficient is reported by the second device; or, the second capability coefficient is determined by the first device.

10. The method of claim 6 or 7, wherein, The third count is one of the following counting methods: The third count is the number of prediction windows corresponding to the first training report; The third count is the value of the time domain dimension of the model output data; The third count is the product of the following terms: the number of prediction windows corresponding to the first training report, and the third capability coefficient; or, The third count is the product of the following: the temporal dimension of the model output data, and the third capability coefficient.

11. The method of claim 10, wherein, The third capability coefficient is predefined; or the second capability coefficient is determined by the first device; or the second capability coefficient is determined by the second device.

12. The method according to any one of claims 6 to 11, characterized in that, The method further includes: Send or receive second information, the second information being used to indicate the counting method supported by the first device.

13. The method according to any one of claims 1 to 12, characterized in that, The CPU usage start time corresponding to the first monitoring report corresponds to the earliest time unit among all resource timings corresponding to the first monitoring resource. The number of all resource timings corresponding to the first monitoring resource is determined based on the number of prediction windows corresponding to the first inference report. The first inference report is an inference report associated with the first monitoring report.

14. The method of claim 13, wherein, The number of all resource timings corresponding to the first monitored resource is equal to the number of prediction windows corresponding to the first inference report; or, The number of all resource opportunities corresponding to the first monitoring resource is the product of the following: the number of prediction windows corresponding to the first inference report, and the number of first inference reports corresponding to the first monitoring report.

15. The method of claim 3, wherein, The prediction results in the first prediction report are paired with the first monitoring resource in the following manner: The first prediction result is paired with the first measurement result, and the first time unit corresponding to the first measurement result and the second time unit corresponding to the first prediction result have a first time relationship; the N prediction results in the first prediction report include the first prediction result, and the M measurement results of the first monitoring resource include the first measurement result.

16. A method of communication, comprising: include: Receive first information, the first information being used to instruct the terminal device to determine the first monitoring report; A first indicator is determined based on N prediction results and M measurement results; where N and M are positive integers greater than or equal to 1; the M measurement results include the first measurement result, and the N prediction results include the first prediction result; the first time unit corresponding to the first measurement result and the second time unit corresponding to the first prediction result have a first time relationship. The first monitoring report is determined based on the first indicator.

17. The method of claim 16, wherein, The first time unit corresponding to the first measurement result includes at least one of the following: The time unit in which the first set of measurement resources is located to determine the first measurement result; The time unit in which the Channel State Information (CSI) reference resource corresponding to the first measurement result is located; The time unit in which the first measurement result takes effect; The visible signal indicator CSI reference resource corresponding to the CSI report that carries the first prediction result bound to the first measurement result.

18. The method of claim 16 or 17, wherein, The second time unit corresponding to the first prediction result includes at least one of the following: The time unit in which the CSI reference resource corresponding to the first prediction result is located; The time unit in which the first prediction result takes effect; The CSI reference resource corresponding to the CSI report carrying the first prediction result.

19. The method according to any one of claims 16-18, characterized by, The first time relationship between the first time unit and the second time unit includes at least one of the following: The time interval between the first time unit and the second time unit is less than or equal to the first time interval; The first time unit is the Xth time unit closest to the second time unit, where X is a positive integer; The first time unit is no later than the second time unit; The second time unit is the Y-th time unit closest to the first time unit, where Y is a positive integer; The second time unit is no later than the first time unit.

20. The method of any one of claims 16-19, wherein, The method further includes: Determine the M time units corresponding to the M measurement results; The second time unit is determined based on the first time unit corresponding to any one of the M measurement results.

21. The method of claim 20, wherein, The method further includes: When multiple measurement results correspond to the same second time unit, one time unit is selected from the multiple measurement results as the first time unit.

22. The method of any one of claims 16-21, wherein, The method further includes: Determine the N time units corresponding to the N prediction results; The first time unit is determined based on the second time unit corresponding to any one of the N prediction results.

23. The method of claim 22, wherein, The method further includes: When multiple prediction results correspond to the same first time unit, one time unit is selected from the multiple prediction results as the second time unit.

24. The method of any one of claims 16-23, wherein, The N prediction results are the N prediction results that are closest to the first reference time unit corresponding to the first monitoring report.

25. The method of any one of claims 16-24, wherein, The CPU usage start time corresponding to the first monitoring report corresponds to the earliest time unit in at least one first time unit, and the at least one first time unit is a first time unit determined based on the second time units corresponding to the N prediction results.

26. The method of any one of claims 16-25, wherein, The CPU usage termination time corresponding to the first monitoring report is determined by one or more of the following methods: The CPU usage termination time is determined based on the time it takes to complete the calculation of the first indicator; or... The CPU occupancy termination time is determined based on the time when the CSI calculation is completed; or... The CPU occupancy termination time is determined based on the last symbol of the PUSCH / PUCCH carrying the first monitoring report; or, Z of the last symbol of a time window of channel state information reference signal transmission, CSI-RS occasion, for performance monitoring ′ symbols.

27. The method of any one of claims 22-26, wherein, Before determining the N time units corresponding to the N prediction results, the method further includes: The second reference time unit corresponding to the first prediction report is determined based on the first reference time unit corresponding to the first monitoring report; the first prediction report includes the N prediction results.

28. The method of claim 24 or 27, wherein, The first reference time unit includes one or more of the following: The uplink time unit where the first monitoring report is located; The CSI reference resource corresponding to the first monitoring report; The reference measurement resource set used to generate the first monitoring report.

29. The method of claim 27, wherein, The second reference time unit includes one or more of the following: The uplink time unit in which the first forecast report is located; The CSI reference resource corresponding to the first forecast report; The first prediction report includes the time unit corresponding to the reference prediction results.

30. The method of any one of claims 16-29, wherein, The second time unit satisfies the first constraint condition, which includes at least one of the following conditions: The first time unit corresponding to the second time unit is within the valid time range corresponding to the first monitoring report; The second time unit is within the valid time range corresponding to the first monitoring report.

31. The method of any one of claims 16-29, wherein, The first prediction result satisfies the second constraint, which includes at least one of the following conditions: The second reference time unit corresponding to the first forecast report is within the valid time range, and the first forecast report includes the first forecast result; The first prediction result takes effect within the valid timeframe. Wherein, the first prediction result is determined based on the first prediction report, or the first prediction result has been acquired by the terminal device.

32. The method of claim 30 or 31, wherein, The effective time range includes one or more of the following: Not later than the first reference time unit corresponding to the first monitoring report; No earlier than the time unit in which the control information used to indicate the first monitoring report is located; Not earlier than the first offset time unit, the time interval between the first offset time unit and the time unit where the control information used to indicate the first monitoring report is located is the first time length; No later than the second time offset unit, the time interval between the second time offset unit and the second reference time unit corresponding to the first prediction report is the second time length.

33. The method of any one of claims 30-32, wherein, The method further includes: If the second time unit does not meet the first constraint and / or the second constraint, the first prediction result is not used for the calculation of the first index; or, If the first time unit does not meet the first constraint condition and / or the second constraint condition, the first measurement result will not be used for the calculation of the first index.

34. The method of any one of claims 16-33, wherein, The N satisfies at least one of the following conditions: The maximum value of N is configured or indicated by the network; N is preset by the protocol.

35. A communications device, characterized by include: An interface unit and a processing unit, wherein the processing unit is used for: A first count of a first resource is determined based on the number of prediction windows, or the number of prediction windows and the number of observation windows, where the first count corresponds to the resource count and / or the port count within the resource.

36. A communications device, characterized by include: An interface unit and a processing unit, wherein the processing unit is used for: The interface unit receives first information, which instructs the terminal device to determine a first monitoring report; a first indicator is determined based on N prediction results and M measurement results; N and M are positive integers greater than or equal to 1; the M measurement results include the first measurement result, and the N prediction results include the first prediction result; the first time unit corresponding to the first measurement result and the second time unit corresponding to the first prediction result have a first time relationship; and the first monitoring report is determined according to the first indicator.

37. A communications device, characterized by Includes a processor for executing a computer program or instructions that cause the device to perform the method as claimed in any one of claims 1-15; or to perform the method as claimed in any one of claims 16-34.

38. A chip, characterized by It includes at least one processor, the processor being configured to execute a computer program or instructions that cause the chip to perform the method as claimed in any one of claims 1-15; or to perform the method as claimed in any one of claims 16-34.

39. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program or instructions that, when executed, implement the method as described in any one of claims 1-15; or implement the method as described in any one of claims 16-34.

40. A computer program product, characterised in that, The computer program product includes: computer program code, which, when the computer program code is run, implements the method as described in any one of claims 1-15; or implements the method as described in any one of claims 16-34.

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