Communication method and related device

Abstract

The present application provides a communication method and a related device. The method comprises: determining a first monitoring result and first indication information, wherein the first monitoring result is used for determining whether a first reasoning result is accurate or determining the accuracy of the first reasoning result, the first reasoning result is used for determining k1 optimal reference signal resources determined by means of prediction in a first subset of a first reference signal resource set, and the first indication information is used for indicating the k1 optimal reference signal resources determined by means of prediction; and sending first information, wherein the first information is used for indicating the first monitoring result and the first indication information. In the method, a terminal device reports, to a network device, at least one optimal reference signal resource determined by means of prediction in a first subset, so that the network device determines whether at least one optimal reference signal resource determined by means of prediction in a complete set of a first reference signal resource set is the same as at least one optimal reference signal resource determined by means of prediction in the first subset, and thus the network device adjusts the first subset, thereby improving accuracy of monitoring results.

Description

A communication method and related equipment

[0001] This application claims priority to Chinese Patent Application No. 202411600151.0, filed on November 8, 2024, with the China National Intellectual Property Administration, entitled “A Communication Method and Related Device”, the entire contents of which are incorporated herein by reference. Technical Field

[0002] This application relates to the field of communications, and more specifically, to a communication method, a communication device, a computer-readable storage medium, a chip, and a computer program product. Background Technology

[0003] In beam management scenarios based on artificial intelligence (AI), network devices determine the resources for communication with terminal devices based on at least one predicted optimal reference signal resource. Since this predicted optimal reference signal resource is determined based on an AI model, the AI ​​model needs to be monitored to facilitate the determination of suitable communication resources.

[0004] However, the monitoring results obtained from the inference results of AI models in the current solution may have low accuracy. How to improve the accuracy of the monitoring results in order to monitor AI models has become an urgent problem to be solved. Summary of the Invention

[0005] This application provides a communication method, communication device, computer-readable storage medium, chip, and computer program product, which aim to improve the accuracy of monitoring results for monitoring AI models.

[0006] In a first aspect, a communication method is provided. The method includes: determining a first monitoring result and first indication information, wherein the first monitoring result is used to determine whether a first inference result is accurate or the accuracy of the first inference result, the first inference result is used to determine k1 predicted optimal reference signal resources in a first subset (set M) of a first reference signal resource set (set A), and the first indication information is used to indicate the k1 predicted optimal reference signal resources, wherein the first reference signal resource set includes at least one reference signal resource, and k1 is a positive integer; and sending first information, wherein the first information is used to indicate the first monitoring result and the first indication information.

[0007] In this embodiment, when the terminal device reports the monitoring result to the network device, it also reports at least one predicted optimal reference signal resource in the first subset (set M) of the first reference signal resource set (set A). This facilitates the network device in determining whether at least one predicted optimal reference signal resource in the full set of the first reference signal resource set (set A) is the same as at least one predicted optimal reference signal resource in the first subset (set M). This allows the network device to adjust the reference signal resources included in the reference signal resource set (i.e., the first subset) used to obtain the monitoring result, so that at least one predicted optimal reference signal resource in the first reference signal resource set (set A) is as similar as possible to at least one predicted optimal reference signal resource in the first subset, thereby improving the accuracy of the monitoring result.

[0008] In some embodiments, the first inference result is obtained by a device deploying the first AI model using the first AI model. The device deploying the first AI model is a terminal-side device, such as the terminal device itself or a device or server connected to the terminal device.

[0009] In some embodiments, the first AI model is a regression model or a classification model.

[0010] In conjunction with the first aspect, in some implementations, the first information is also used to indicate second indication information, which is used to indicate information about the same reference signal resources among the k1 predicted optimal reference signal resources and the k2 predicted optimal reference signal resources in the first set of reference signal resources, where k2 is a positive integer.

[0011] In some embodiments, the second indication information includes information about the same reference signal resources among the k1 predicted optimal reference signal resources and the k2 predicted optimal reference signal resources in the first set of reference signal resources; or, the second indication information includes the following information to indicate the same reference signal resources among the k1 predicted optimal reference signal resources and the k2 predicted optimal reference signal resources in the first set of reference signal resources: the number of different reference signal resources among the k1 predicted optimal reference signal resources and the k2 predicted optimal reference signal resources in the first set of reference signal resources, and the ratio of the number of different reference signal resources among the k1 predicted optimal reference signal resources and the k2 predicted optimal reference signal resources in the first set of reference signal resources to k2.

[0012] In this embodiment of the application, when the terminal device reports the monitoring results and at least one predicted optimal reference signal resource in the first subset to the network device, it can also report information on at least one predicted optimal reference signal resource in the first reference signal resource set and information on the same reference signal resource in at least one predicted optimal reference signal resource in the first subset, thereby facilitating the network device to directly determine whether the reference signal resources included in the first subset need to be adjusted based on the second indication information.

[0013] In conjunction with the first aspect, in some implementations, the information on the reference signal resources that are the same among the k1 predicted optimal reference signal resources and the k2 predicted optimal reference signal resources in the first set of reference signal resources includes one or more of the following: whether each reference signal resource among the k1 predicted optimal reference signal resources belongs to the k2 predicted optimal reference signal resources, the number of reference signal resources in the k1 predicted optimal reference signal resources that are the same as those in the k2 predicted optimal reference signal resources, or the ratio of the number of reference signal resources in the k1 predicted optimal reference signal resources that are the same as those in the k2 predicted optimal reference signal resources to k2.

[0014] In this embodiment, the second indication information includes k1 pieces of information or a single value. Each of the k1 pieces of information may include one or more binary bits. When each of the k1 pieces of information includes one binary bit, the k1 pieces of information may also be referred to as a k1-bit binary value or a bitmap including k1 bits. Each of the k1 pieces of information is used to indicate whether the predicted optimal reference signal resource corresponding to the first subset belongs to the k2 predicted optimal reference signal resources. When the second indication information includes a k1-bit binary value, each of the k1-bit binary values ​​is used to indicate whether the predicted optimal reference signal resource corresponding to the first subset belongs to the k2 predicted optimal reference signal resources. When the second indication information includes a single value, the value is the number of reference signal resources in the k1 predicted optimal reference signal resources that are identical to those in the k2 predicted optimal reference signal resources, or the value is the ratio of the number of reference signal resources in the k1 predicted optimal reference signal resources that are identical to those in the k2 predicted optimal reference signal resources to k2.

[0015] In conjunction with the first aspect, in some implementations, the first information is also used to indicate the third indication information, which is used to indicate the reference signal resources among the k2 predicted optimal reference signal resources in the first reference signal resource set that do not belong to the k1 predicted optimal reference signal resources, where k2 is a positive integer.

[0016] In this embodiment of the application, when the terminal device reports the monitoring results and at least one predicted optimal reference signal resource in the first subset to the network device, it can also report reference signal resources in the first reference signal resource set that do not belong to the first subset. This facilitates the network device in determining whether at least one predicted optimal reference signal resource in the full set of the first reference signal resource set (set A) is the same as at least one predicted optimal reference signal resource in the first subset (set M). This facilitates the network device in adjusting the reference signal resources included in the reference signal resource set (i.e., the first subset) used to obtain the monitoring results.

[0017] In conjunction with the first aspect, in some implementations, the first information is also used to indicate the third indication information, which is used to indicate the k2 predicted optimal reference signal resources in the first reference signal resource set, where k2 is a positive integer.

[0018] In this embodiment of the application, when the terminal device reports the monitoring results and at least one predicted optimal reference signal resource in the first subset to the network device, it can also report at least one predicted optimal reference signal resource in the first reference signal resource set to the network device. This facilitates the network device in determining whether at least one predicted optimal reference signal resource in the full set of the first reference signal resource set (set A) is the same as at least one predicted optimal reference signal resource in the first subset (set M). This facilitates the network device in adjusting the reference signal resources included in the reference signal resource set (i.e., the first subset) used to obtain the monitoring results.

[0019] In conjunction with the first aspect, in some implementations, the first indication information includes the identification information of k1 predicted optimal reference signal resources in the first subset (set M).

[0020] In this embodiment of the application, "identification information" and "index" have similar meanings and can be used interchangeably.

[0021] In this embodiment of the application, the identification information of the reference signal resources reported by the terminal device is the identification information of the reference signal resources in the first subset, which can reduce the number of bits of the reported information and thus reduce communication overhead.

[0022] In conjunction with the first aspect, in some implementations, first configuration information is received, which is used to configure a second subset (set M') of a first set of reference signal resources, the second subset (set M') being different from at least one reference signal resource included in the first subset (set M).

[0023] In this embodiment of the application, the network device may configure a new subset of the first reference signal resource set to the terminal device, and the new subset is different from the previously configured subset, so that the new subset includes at least one predicted and determined best reference signal resource in the first reference signal resource set as much as possible, thereby improving the accuracy of the monitoring results determined by the measurement values ​​of the channel state information corresponding to the reference signal resources in the new subset.

[0024] In conjunction with the first aspect, in some implementations, the second subset (set M') does not include reference signal resources among the k1 predicted optimal reference signal resources that are not among the k2 predicted optimal reference signal resources in the first reference signal resource set, where k2 is a positive integer. Alternatively, the number of reference signal resources in the second subset (set M') that are identical to those in the first subset (set M) is less than or equal to a first preset threshold. Alternatively, the ratio of the number of reference signal resources in the second subset (set M') that are identical to those in the first subset (set M) to a first value is less than or equal to a second preset threshold, where the first value includes any one of the following: the number of reference signal resources in the second subset (set M') and the number of reference signal resources in the first subset (set M). Alternatively, the second subset (set M') includes the k2 predicted optimal reference signal resources in the first reference signal resource set. Alternatively, the number of reference signal resources in the second subset (set M') that belong to the k2 predicted optimal reference signal resources in the first reference signal resource set is greater than or equal to a third preset threshold. Alternatively, the ratio of the number of reference signal resources in the second subset (set M') that belong to the k2 predicted optimal reference signal resources in the first reference signal resource set to the second value is greater than or equal to a fourth preset threshold, where the second value includes any one of the following: the number of reference signal resources in the second subset (set M'), the number of reference signal resources in the first reference signal resource set, and k2. Here, k2 is a positive integer.

[0025] In this embodiment, the second subset includes as many of the k2 predicted optimal reference signal resources as possible by limiting the second subset to exclude reference signal resources that are not among the k1 predicted optimal reference signal resources, or by limiting the number or proportion of reference signal resources that are the same in the second subset and the first subset, or by limiting the number of reference signal resources that are the same in the second subset and the k1 predicted optimal reference signal resources.

[0026] In conjunction with the first aspect, in some implementations, the predicted values ​​of the channel state information corresponding to the k1 predicted optimal reference signal resources are greater than or equal to the predicted values ​​of the channel state information corresponding to the reference signal resources in the first subset (set M) excluding the k1 predicted optimal reference signal resources. Alternatively, the probability corresponding to the k1 predicted optimal reference signal resources is greater than or equal to the probability corresponding to the reference signal resources in the first subset (set M) excluding the k1 predicted optimal reference signal resources, where the probability corresponding to a reference signal resource is the probability that the reference signal resource is an optimal reference signal resource in the first reference signal resource set (set A) or the first subset (set M). Alternatively, the k1 predicted optimal reference signal resources are the reference signal resources in the first subset (set M) that belong to the k2 predicted optimal reference signal resources in the first reference signal resource set. The predicted value of the channel state information corresponding to the k2 predicted optimal reference signal resources is greater than or equal to the predicted value of the channel state information corresponding to the reference signal resources in the first reference signal resource set (set A) other than the k2 predicted optimal reference signal resources. Or, the probability corresponding to the k2 predicted optimal reference signal resources is greater than or equal to the probability corresponding to the reference signal resources in the first reference signal resource set (set A) other than the k2 predicted optimal reference signal resources. The probability corresponding to the reference signal resources is the probability that the reference signal resources are the best reference signal resources in the first reference signal resource set (set A), where k2 is a positive integer.

[0027] In conjunction with the first aspect, in some implementations, the first inference result includes the predicted value of the channel state information corresponding to each reference signal resource in the first reference signal resource set (set A), and the first monitoring result is determined based on the measured value of the channel state information corresponding to at least one first reference signal resource in the first subset (set M) and the predicted value of the channel state information corresponding to at least one second reference signal resource in the entire first reference signal resource set (set A) or the first subset (set M). Alternatively, the first monitoring result includes the measured value of the channel state information corresponding to at least one reference signal resource in the first subset (set M). Alternatively, the first inference result includes the probability that each reference signal resource in the first reference signal resource set (set A) is the best reference signal resource in the first reference signal resource set (set A), and the first monitoring result is determined based on the best reference signal resource determined by at least one measurement in the first subset (set M) and the best reference signal resource determined by the entire set of the first reference signal resource set (set A) or by at least one prediction in the first subset (set M). Or, the first monitoring result includes the identification information of at least one best reference signal resource determined by measurement in the first subset (set M), wherein the measured value of the channel state information corresponding to at least one best reference signal resource determined by measurement is greater than or equal to the measured value of the channel state information corresponding to the reference signal resources in the first subset (set M) other than the at least one best reference signal resource determined by measurement.

[0028] In the embodiments of this application, "at least one measurement-determined optimal reference signal resource" and "x1 measurement-determined optimal reference signal resources, where x1 is a positive integer" have similar meanings and can be substituted for each other. "At least one prediction-determined optimal reference signal resource" and "x2 prediction-determined optimal reference signal resources, where x2 is a positive integer" have similar meanings and can be substituted for each other.

[0029] In this embodiment of the application, the k1 predicted optimal reference signal resources are the k1 reference signal resources selected in the first subset using the first inference result, or the k1 predicted optimal reference signal resources are the k1 reference signal resources belonging to the first subset among the k2 reference signal resources selected in the first reference signal resource set using the first inference result.

[0030] In conjunction with the first aspect, in some implementations, a measured value of the channel state information corresponding to each reference signal resource in the second reference signal resource set (set B) is determined, the second reference signal resource set including at least one reference signal resource; and a first inference result is determined using the measured value of the channel state information corresponding to each reference signal resource in the second reference signal resource set.

[0031] In this embodiment of the application, the terminal device uses the measured value of the channel state information corresponding to each reference signal resource in the second reference signal resource set and the AI ​​model to obtain the output of the AI ​​model, namely the first inference result.

[0032] Secondly, a communication method is provided. The method includes: receiving first information, the first information being used to indicate a first monitoring result and first indication information, the first monitoring result being used to determine whether a first inference result is accurate or the accuracy of the first inference result, the first inference result being used to determine k1 predicted optimal reference signal resources in a first subset (set M) of a first reference signal resource set (set A), and the first indication information being used to indicate the k1 predicted optimal reference signal resources, wherein the first reference signal resource set includes at least one reference signal resource, and k1 is a positive integer.

[0033] In this embodiment, when the network device receives the first monitoring result from the terminal device, it also receives at least one predicted optimal reference signal resource from the first subset (set M) of the first reference signal resource set (set A). This facilitates determining whether at least one predicted optimal reference signal resource in the entire set of the first reference signal resource set (set A) is the same as at least one predicted optimal reference signal resource in the first subset (set M). This facilitates adjusting the reference signal resources included in the reference signal resource set (i.e., the first subset) used to obtain the monitoring result, so that at least one predicted optimal reference signal resource in the first reference signal resource set (set A) is as similar as possible to at least one predicted optimal reference signal resource in the first subset, thereby improving the accuracy of the monitoring result.

[0034] In some embodiments, the first inference result is obtained by a device deploying the first AI model using the first AI model. The device deploying the first AI model is a terminal-side device, such as the terminal device itself or a device or server connected to the terminal device.

[0035] In some embodiments, the first AI model is a regression model or a classification model.

[0036] In conjunction with the second aspect, in some implementations, the first information is also used to indicate second indication information, which is used to indicate information about the same reference signal resources among the k1 predicted optimal reference signal resources and the k2 predicted optimal reference signal resources in the first set of reference signal resources, where k2 is a positive integer.

[0037] In some embodiments, the second indication information includes information about the same reference signal resources among the k1 predicted optimal reference signal resources and the k2 predicted optimal reference signal resources in the first set of reference signal resources; or, the second indication information includes the following information to indicate the same reference signal resources among the k1 predicted optimal reference signal resources and the k2 predicted optimal reference signal resources in the first set of reference signal resources: the number of different reference signal resources among the k1 predicted optimal reference signal resources and the k2 predicted optimal reference signal resources in the first set of reference signal resources, and the ratio of the number of different reference signal resources among the k1 predicted optimal reference signal resources and the k2 predicted optimal reference signal resources in the first set of reference signal resources to k2.

[0038] In conjunction with the second aspect, in some implementations, the information on the reference signal resources that are the same among the k1 predicted optimal reference signal resources and the k2 predicted optimal reference signal resources in the first set of reference signal resources includes one or more of the following: whether each reference signal resource among the k1 predicted optimal reference signal resources belongs to the k2 predicted optimal reference signal resources, the number of reference signal resources in the k1 predicted optimal reference signal resources that are the same as those in the k2 predicted optimal reference signal resources, and the ratio of the number of reference signal resources in the k1 predicted optimal reference signal resources that are the same as those in the k2 predicted optimal reference signal resources to k2.

[0039] In conjunction with the second aspect, in some implementations, the first information is also used to indicate the third indication information, which is used to indicate the reference signal resources among the k2 predicted optimal reference signal resources in the first reference signal resource set that do not belong to the k1 predicted optimal reference signal resources, where k2 is a positive integer.

[0040] In conjunction with the second aspect, in some implementations, the first information is also used to indicate the third indication information, which is used to indicate the k2 predicted optimal reference signal resources in the first reference signal resource set, where k2 is a positive integer.

[0041] In conjunction with the second aspect, in some implementations, the first indication information includes the identification information of k1 predicted optimal reference signal resources in the first subset (set M).

[0042] In this embodiment of the application, "identification information" and "index" have similar meanings and can be used interchangeably.

[0043] In conjunction with the second aspect, in some implementations, first configuration information is sent when a first preset condition is met. This first configuration information is used to configure a second subset (set M') of the first reference signal resource set, where the second subset (set M') differs from at least one reference signal resource included in the first subset (set M). The first preset condition includes any one of the following: at least one reference signal resource among the k1 predicted optimal reference signal resources and the k2 predicted optimal reference signal resources in the first reference signal resource set is different; the number of reference signal resources among the k1 predicted optimal reference signal resources that are identical to those among the k2 predicted optimal reference signal resources in the first reference signal resource set is less than or equal to a fifth preset threshold; the ratio of the number of reference signal resources among the k1 predicted optimal reference signal resources that are identical to those among the k2 predicted optimal reference signal resources in the first reference signal resource set to k2 is less than or equal to a sixth preset threshold; where k2 is a positive integer.

[0044] In this embodiment of the application, the network device determines whether a first preset condition is met based on the first indication information, thereby determining whether a new subset of the first reference signal resource set needs to be configured to the terminal device.

[0045] In conjunction with the second aspect, in some implementations, the second subset (set M') does not include reference signal resources among the k1 predicted optimal reference signal resources that are not among the k2 predicted optimal reference signal resources in the first reference signal resource set, where k2 is a positive integer. Alternatively, the number of reference signal resources in the second subset (set M') that are identical to those in the first subset (set M) is less than or equal to a first preset threshold. Alternatively, the ratio of the number of reference signal resources in the second subset (set M') that are identical to those in the first subset (set M) to a first value is less than or equal to a second preset threshold, where the first value includes any one of the following: the number of reference signal resources in the second subset (set M') and the number of reference signal resources in the first subset (set M). Alternatively, the second subset (set M') includes the k2 predicted optimal reference signal resources in the first reference signal resource set. Alternatively, the number of reference signal resources in the second subset (set M') that belong to the k2 predicted optimal reference signal resources in the first reference signal resource set is greater than or equal to a third preset threshold. Alternatively, the ratio of the number of reference signal resources in the second subset (set M') that belong to the k2 predicted optimal reference signal resources in the first reference signal resource set to the second value is greater than or equal to a fourth preset threshold, where the second value includes any one of the following: the number of reference signal resources in the second subset (set M'), the number of reference signal resources in the first reference signal resource set, and k2. Here, k2 is a positive integer.

[0046] In conjunction with the second aspect, in some implementations, the predicted values ​​of the channel state information corresponding to the k1 predicted optimal reference signal resources are greater than or equal to the predicted values ​​of the channel state information corresponding to the reference signal resources in the first subset (set M) excluding the k1 predicted optimal reference signal resources. Alternatively, the probability corresponding to the k1 predicted optimal reference signal resources is greater than or equal to the probability corresponding to the reference signal resources in the first subset (set M) excluding the k1 predicted optimal reference signal resources, where the probability corresponding to a reference signal resource is the probability that the reference signal resource is an optimal reference signal resource in the first set of reference signal resources (set A) or the first subset (set M). Alternatively, the k1 predicted optimal reference signal resources are the reference signal resources in the first subset (set M) that belong to the k2 predicted optimal reference signal resources in the first reference signal resource set. The predicted value of the channel state information corresponding to the k2 predicted optimal reference signal resources is greater than or equal to the predicted value of the channel state information corresponding to the reference signal resources in the first reference signal resource set (set A) other than the k2 predicted optimal reference signal resources. Or, the probability corresponding to the k2 predicted optimal reference signal resources is greater than or equal to the probability corresponding to the reference signal resources in the first reference signal resource set (set A) other than the k2 predicted optimal reference signal resources. The probability corresponding to the reference signal resources is the probability that the reference signal resources are the best reference signal resources in the first reference signal resource set (set A), where k2 is a positive integer.

[0047] In conjunction with the second aspect, in some implementations, the first inference result includes the predicted value of the channel state information corresponding to each reference signal resource in the first reference signal resource set (set A), and the first monitoring result is determined based on the measured value of the channel state information corresponding to at least one first reference signal resource in the first subset (set M) and the predicted value of the channel state information corresponding to at least one second reference signal resource in the entire first reference signal resource set (set A) or the first subset (set M). Alternatively, the first monitoring result includes the measured value of the channel state information corresponding to at least one reference signal resource in the first subset (set M). Alternatively, the first inference result includes the probability that each reference signal resource in the first reference signal resource set (set A) is the best reference signal resource in the first reference signal resource set (set A), and the first monitoring result is determined based on the best reference signal resource determined by at least one measurement in the first subset (set M) and the best reference signal resource determined by the entire set of the first reference signal resource set (set A) or by at least one prediction in the first subset (set M). Or, the first monitoring result includes the identification information of at least one best reference signal resource determined by measurement in the first subset (set M), wherein the measured value of the channel state information corresponding to at least one best reference signal resource determined by measurement is greater than or equal to the measured value of the channel state information corresponding to the reference signal resources in the first subset (set M) other than the at least one best reference signal resource determined by measurement.

[0048] In the embodiments of this application, "at least one measurement-determined optimal reference signal resource" and "x1 measurement-determined optimal reference signal resources, where x1 is a positive integer" have similar meanings and can be substituted for each other. "At least one prediction-determined optimal reference signal resource" and "x2 prediction-determined optimal reference signal resources, where x2 is a positive integer" have similar meanings and can be substituted for each other.

[0049] In conjunction with the second aspect, in some implementations, when the first monitoring result includes measured values ​​of channel state information corresponding to at least one reference signal resource in the first subset (set M), the network device determines a first accuracy based on the measured values ​​of channel state information corresponding to at least one first reference signal resource in the first subset (set M) and the predicted values ​​of channel state information corresponding to the entire set of the first reference signal resource set (set A) or at least one second reference signal resource in the first subset (set M). This first accuracy is used to indicate whether the first inference result is accurate or the accuracy of the first inference result.

[0050] In conjunction with the second aspect, in some implementations, when the first monitoring result includes identification information of at least one measurement-determined optimal reference signal resource in the first subset (set M), the network device determines a second accuracy based on at least one measurement-determined optimal reference signal resource in the first subset (set M) and the entire set of the first reference signal resource set (set A) or at least one prediction-determined optimal reference signal resource in the first subset (set M). This second accuracy is used to indicate whether the first inference result is accurate or the accuracy of the first inference result.

[0051] In this embodiment of the application, if the first monitoring result does not include the first accuracy or the second accuracy, the network device determines the first accuracy or the second accuracy based on the first monitoring result, thereby monitoring the AI ​​model.

[0052] It should be understood that some implementation methods in the second aspect can achieve similar technical effects to the corresponding implementation methods in the first aspect, and will not be elaborated here.

[0053] Thirdly, a communication method is provided. The method includes: determining a first monitoring result and second indication information, wherein the first monitoring result is used to determine whether a first inference result is accurate or the accuracy of the first inference result, the first inference result is used to determine k1 predicted optimal reference signal resources in a first subset (set M) of a first reference signal resource set (set A) and k2 predicted optimal reference signal resources in the first reference signal resource set (set A), and the second indication information is used to indicate information about identical reference signal resources among the k1 predicted optimal reference signal resources in the first subset (set M) of the first reference signal resource set (set A) and the k2 predicted optimal reference signal resources in the first reference signal resource set (set M), where k1 and k2 are positive integers; and sending second information, which is used to indicate the first monitoring result and the second indication information.

[0054] In this embodiment, when the terminal device reports the monitoring results to the network device, it also reports to the network device whether at least one predicted optimal reference signal resource in the entire set of the first reference signal resource set (set A) is the same as at least one predicted optimal reference signal resource in the first subset (set M). This facilitates the network device in determining whether it is necessary to adjust the reference signal resources included in the reference signal resource set (i.e., the first subset) used to obtain the monitoring results, so that at least one predicted optimal reference signal resource in the first reference signal resource set (set A) is as similar as possible to at least one predicted optimal reference signal resource in the first subset, thereby improving the accuracy of the monitoring results.

[0055] In some embodiments, the first inference result is obtained by a device deploying the first AI model using the first AI model. The device deploying the first AI model is a terminal-side device, such as the terminal device itself or a device or server connected to the terminal device.

[0056] In some embodiments, the first AI model is a regression model or a classification model.

[0057] In some embodiments, the second indication information includes information about the same reference signal resources among the k1 predicted optimal reference signal resources and the k2 predicted optimal reference signal resources in the first set of reference signal resources; or, the second indication information includes the following information to indicate the same reference signal resources among the k1 predicted optimal reference signal resources and the k2 predicted optimal reference signal resources in the first set of reference signal resources: the number of different reference signal resources among the k1 predicted optimal reference signal resources and the k2 predicted optimal reference signal resources in the first set of reference signal resources, and the ratio of the number of different reference signal resources among the k1 predicted optimal reference signal resources and the k2 predicted optimal reference signal resources in the first set of reference signal resources to k2.

[0058] In conjunction with the third aspect, in some implementations, the information on the reference signal resources that are the same among the k1 predicted optimal reference signal resources and the k2 predicted optimal reference signal resources in the first set of reference signal resources includes one or more of the following: whether each reference signal resource among the k1 predicted optimal reference signal resources belongs to the k2 predicted optimal reference signal resources, the number of reference signal resources in the k1 predicted optimal reference signal resources that are the same as those in the k2 predicted optimal reference signal resources, and the ratio of the number of reference signal resources in the k1 predicted optimal reference signal resources that are the same as those in the k2 predicted optimal reference signal resources to k2.

[0059] In conjunction with the third aspect, in some implementations, a fourth indication information is sent, which is used to indicate k2 predicted optimal reference signal resources in the first set of reference signal resources, or the fourth indication information is used to indicate the k2 predicted optimal reference signal resources and the predicted value of the channel state information corresponding to each of the k2 predicted optimal reference signal resources.

[0060] In conjunction with the third aspect, in some implementations, first configuration information is received, which is used to configure a second subset (set M') of a first set of reference signal resources, the second subset (set M') being different from at least one reference signal resource included in the first subset (set M).

[0061] In conjunction with the third aspect, in some implementations, the second subset (set M') does not include reference signal resources among the k1 predicted optimal reference signal resources that are not among the k2 predicted optimal reference signal resources in the first reference signal resource set, where k2 is a positive integer. Alternatively, the number of reference signal resources in the second subset (set M') that are identical to those in the first subset (set M) is less than or equal to a first preset threshold. Alternatively, the ratio of the number of reference signal resources in the second subset (set M') that are identical to those in the first subset (set M) to a first value is less than or equal to a second preset threshold, where the first value includes any one of the following: the number of reference signal resources in the second subset (set M') and the number of reference signal resources in the first subset (set M). Alternatively, the second subset (set M') includes the k2 predicted optimal reference signal resources in the first reference signal resource set. Alternatively, the number of reference signal resources in the second subset (set M') that belong to the k2 predicted optimal reference signal resources in the first reference signal resource set is greater than or equal to a third preset threshold. Alternatively, the ratio of the number of reference signal resources in the second subset (set M') that belong to the k2 predicted optimal reference signal resources in the first reference signal resource set to the second value is greater than or equal to a fourth preset threshold, where the second value includes any one of the following: the number of reference signal resources in the second subset (set M'), the number of reference signal resources in the first reference signal resource set, and k2. Here, k2 is a positive integer.

[0062] In conjunction with the third aspect, in some implementations, the predicted values ​​of the channel state information corresponding to the k1 predicted optimal reference signal resources are greater than or equal to the predicted values ​​of the channel state information corresponding to the reference signal resources in the first subset (set M) excluding the k1 predicted optimal reference signal resources. Alternatively, the probability corresponding to the k1 predicted optimal reference signal resources is greater than or equal to the probability corresponding to the reference signal resources in the first subset (set M) excluding the k1 predicted optimal reference signal resources, where the probability corresponding to a reference signal resource is the probability that the reference signal resource is an optimal reference signal resource in the first reference signal resource set (set A) or the first subset (set M). Alternatively, the k1 predicted optimal reference signal resources are the reference signal resources in the first subset (set M) that belong to the k2 predicted optimal reference signal resources in the first reference signal resource set. The predicted value of the channel state information corresponding to the k2 predicted optimal reference signal resources is greater than or equal to the predicted value of the channel state information corresponding to the reference signal resources in the first reference signal resource set (set A) other than the k2 predicted optimal reference signal resources. Or, the probability corresponding to the k2 predicted optimal reference signal resources is greater than or equal to the probability corresponding to the reference signal resources in the first reference signal resource set (set A) other than the k2 predicted optimal reference signal resources. The probability corresponding to the reference signal resources is the probability that the reference signal resources are the best reference signal resources in the first reference signal resource set (set A), where k2 is a positive integer.

[0063] In conjunction with the third aspect, in some implementations, the first inference result includes a predicted value of the channel state information corresponding to each reference signal resource in the first reference signal resource set (set A), and the first monitoring result is determined based on the measured value of the channel state information corresponding to at least one first reference signal resource in the first subset (set M) and the predicted value of the channel state information corresponding to at least one second reference signal resource in the entire first reference signal resource set (set A) or the first subset (set M). Alternatively, the first inference result includes the probability that each reference signal resource in the first reference signal resource set (set A) is the best reference signal resource in the first reference signal resource set (set A), and the first monitoring result is determined based on at least one best reference signal resource determined by measurement in the first subset (set M) and at least one best reference signal resource determined by prediction in the entire first reference signal resource set (set A) or the first subset (set M), wherein the measured value of the channel state information corresponding to at least one best reference signal resource determined by measurement is greater than or equal to the measured values ​​of the channel state information corresponding to the reference signal resources in the first subset (set M) other than the at least one best reference signal resource determined by measurement.

[0064] In the embodiments of this application, "at least one measurement-determined optimal reference signal resource" and "x1 measurement-determined optimal reference signal resources, where x1 is a positive integer" have similar meanings and can be substituted for each other. "At least one prediction-determined optimal reference signal resource" and "x2 prediction-determined optimal reference signal resources, where x2 is a positive integer" have similar meanings and can be substituted for each other.

[0065] In conjunction with the third aspect, in some implementations, when the first monitoring result includes the identification information of the reference signal resource, the identification information of the reference signal resource is the identification information of the reference signal resource in the first subset (set M).

[0066] In this embodiment of the application, "identification information" and "index" have similar meanings and can be used interchangeably.

[0067] In conjunction with the third aspect, in some implementations, the measured value of the channel state information corresponding to each reference signal resource in the second reference signal resource set (set B) is determined, the second reference signal resource set including at least one reference signal resource; and the first inference result is determined by using the measured value of the channel state information corresponding to each reference signal resource in the second reference signal resource set.

[0068] It should be understood that some implementation methods in the third aspect can achieve similar technical effects to the corresponding implementation methods in the first aspect, and will not be elaborated here.

[0069] Fourthly, a communication method is provided. The method includes: receiving second information, the second information being used to indicate a first monitoring result and second indication information. The first monitoring result is used to determine whether a first inference result is accurate or the accuracy of the first inference result, the first inference result being used to determine k1 predicted optimal reference signal resources in a first subset (set M) of a first reference signal resource set (set A) and k2 predicted optimal reference signal resources in the first reference signal resource set (set A), the second indication information being used to indicate information about identical reference signal resources among the k1 predicted optimal reference signal resources in the first subset (set M) of the first reference signal resource set (set A) and the k2 predicted optimal reference signal resources in the first reference signal resource set (set M), where k1 and k2 are positive integers.

[0070] In this embodiment of the application, when the network device receives the monitoring results, it also receives whether at least one predicted optimal reference signal resource in the full set of the first reference signal resource set (set A) and at least one predicted optimal reference signal resource in the first subset (set M) are the same. This facilitates the determination of whether it is necessary to adjust the reference signal resources included in the reference signal resource set (i.e., the first subset) used to obtain the monitoring results, so that at least one predicted optimal reference signal resource in the first reference signal resource set (set A) is as similar as possible to at least one predicted optimal reference signal resource in the first subset, thereby improving the accuracy of the monitoring results.

[0071] In some embodiments, the first inference result is obtained by a device deploying the first AI model using the first AI model. The device deploying the first AI model is a terminal-side device, such as the terminal device itself or a device or server connected to the terminal device.

[0072] In some embodiments, the first AI model is a regression model or a classification model.

[0073] In some embodiments, the second indication information includes information about the same reference signal resources among the k1 predicted optimal reference signal resources and the k2 predicted optimal reference signal resources in the first set of reference signal resources; or, the second indication information includes the following information to indicate the same reference signal resources among the k1 predicted optimal reference signal resources and the k2 predicted optimal reference signal resources in the first set of reference signal resources: the number of different reference signal resources among the k1 predicted optimal reference signal resources and the k2 predicted optimal reference signal resources in the first set of reference signal resources, and the ratio of the number of different reference signal resources among the k1 predicted optimal reference signal resources and the k2 predicted optimal reference signal resources in the first set of reference signal resources to k2.

[0074] In conjunction with the fourth aspect, in some implementations, the information on the reference signal resources that are the same among the k1 predicted optimal reference signal resources and the k2 predicted optimal reference signal resources in the first set of reference signal resources includes one or more of the following: whether each reference signal resource among the k1 predicted optimal reference signal resources belongs to the k2 predicted optimal reference signal resources, the number of reference signal resources in the k1 predicted optimal reference signal resources that are the same as those in the k2 predicted optimal reference signal resources, or the ratio of the number of reference signal resources in the k1 predicted optimal reference signal resources that are the same as those in the k2 predicted optimal reference signal resources to k2.

[0075] In conjunction with the fourth aspect, in some implementations, a fourth indication information is received, which is used to indicate k2 predicted optimal reference signal resources in the first reference signal resource set, or the fourth indication information is used to indicate the predicted value of the channel state information corresponding to each of the k2 predicted optimal reference signal resources.

[0076] In conjunction with the fourth aspect, in some implementations, first configuration information is sent when a first preset condition is met. This first configuration information is used to configure a second subset (set M') of the first reference signal resource set, where the second subset (set M') differs from at least one reference signal resource included in the first subset (set M). The first preset condition includes any one of the following: at least one reference signal resource among the k1 predicted optimal reference signal resources and the k2 predicted optimal reference signal resources in the first reference signal resource set is different; the number of reference signal resources among the k1 predicted optimal reference signal resources that are identical to those among the k2 predicted optimal reference signal resources in the first reference signal resource set is less than or equal to a fifth preset threshold; the ratio of the number of reference signal resources among the k1 predicted optimal reference signal resources that are identical to those among the k2 predicted optimal reference signal resources in the first reference signal resource set to k2 is less than or equal to a sixth preset threshold; where k2 is a positive integer.

[0077] In conjunction with the fourth aspect, in some implementations, the second subset (set M') does not include reference signal resources among the k1 predicted optimal reference signal resources that are not part of the k2 predicted optimal reference signal resources in the first reference signal resource set, where k2 is a positive integer. Alternatively, the number of reference signal resources in the second subset (set M') that are identical to those in the first subset (set M) is less than or equal to a first preset threshold. Alternatively, the ratio of the number of reference signal resources in the second subset (set M') that are identical to those in the first subset (set M) to a first value is less than or equal to a second preset threshold, where the first value includes any one of the following: the number of reference signal resources in the second subset (set M') and the number of reference signal resources in the first subset (set M). Alternatively, the second subset (set M') includes the k2 predicted optimal reference signal resources in the first reference signal resource set. Alternatively, the number of reference signal resources in the second subset (set M') that belong to the k2 predicted optimal reference signal resources in the first reference signal resource set is greater than or equal to a third preset threshold. Alternatively, the ratio of the number of reference signal resources in the second subset (set M') that belong to the k2 predicted optimal reference signal resources in the first reference signal resource set to the second value is greater than or equal to a fourth preset threshold, where the second value includes any one of the following: the number of reference signal resources in the second subset (set M'), the number of reference signal resources in the first reference signal resource set, and k2. Here, k2 is a positive integer.

[0078] In conjunction with the fourth aspect, in some implementations, the predicted values ​​of the channel state information corresponding to the k1 predicted optimal reference signal resources are greater than or equal to the predicted values ​​of the channel state information corresponding to the reference signal resources in the first subset (set M) excluding the k1 predicted optimal reference signal resources. Alternatively, the probability corresponding to the k1 predicted optimal reference signal resources is greater than or equal to the probability corresponding to the reference signal resources in the first subset (set M) excluding the k1 predicted optimal reference signal resources, where the probability corresponding to a reference signal resource is the probability that the reference signal resource is an optimal reference signal resource in the first reference signal resource set (set A) or the first subset (set M). Alternatively, the k1 predicted optimal reference signal resources are the reference signal resources in the first subset (set M) that belong to the k2 predicted optimal reference signal resources in the first reference signal resource set. The predicted value of the channel state information corresponding to the k2 predicted optimal reference signal resources is greater than or equal to the predicted value of the channel state information corresponding to the reference signal resources in the first reference signal resource set (set A) other than the k2 predicted optimal reference signal resources. Or, the probability corresponding to the k2 predicted optimal reference signal resources is greater than or equal to the probability corresponding to the reference signal resources in the first reference signal resource set (set A) other than the k2 predicted optimal reference signal resources. The probability corresponding to the reference signal resources is the probability that the reference signal resources are the best reference signal resources in the first reference signal resource set (set A), where k2 is a positive integer.

[0079] In conjunction with the fourth aspect, in some implementations, the first inference result includes a predicted value of the channel state information corresponding to each reference signal resource in the first reference signal resource set (set A), and the first monitoring result is determined based on the measured value of the channel state information corresponding to at least one first reference signal resource in the first subset (set M) and the predicted value of the channel state information corresponding to at least one second reference signal resource in the entire first reference signal resource set (set A) or the first subset (set M). Alternatively, the first inference result includes the probability that each reference signal resource in the first reference signal resource set (set A) is the best reference signal resource in the first reference signal resource set (set A), and the first monitoring result is determined based on at least one best reference signal resource determined by measurement in the first subset (set M) and at least one best reference signal resource determined by prediction in the entire first reference signal resource set (set A) or the first subset (set M), wherein the measured value of the channel state information corresponding to at least one best reference signal resource determined by measurement is greater than or equal to the measured values ​​of the channel state information corresponding to the reference signal resources in the first subset (set M) other than the at least one best reference signal resource determined by measurement.

[0080] In the embodiments of this application, "at least one measurement-determined optimal reference signal resource" and "x1 measurement-determined optimal reference signal resources, where x1 is a positive integer" have similar meanings and can be substituted for each other. "At least one prediction-determined optimal reference signal resource" and "x2 prediction-determined optimal reference signal resources, where x2 is a positive integer" have similar meanings and can be substituted for each other.

[0081] In conjunction with the fourth aspect, in some implementations, when the first monitoring result includes the identification information of the reference signal resource, the identification information of the reference signal resource is the identification information of the reference signal resource in the first subset (set M).

[0082] In this embodiment of the application, "identification information" and "index" have similar meanings and can be used interchangeably.

[0083] In conjunction with the fourth aspect, in some implementations, when the first monitoring result includes measured values ​​of channel state information corresponding to at least one reference signal resource in the first subset (set M), the network device determines a first accuracy based on the measured values ​​of channel state information corresponding to at least one first reference signal resource in the first subset (set M) and the predicted values ​​of channel state information corresponding to the entire set of the first reference signal resource set (set A) or at least one second reference signal resource in the first subset (set M). This first accuracy is used to indicate whether the first inference result is accurate or the accuracy of the first inference result.

[0084] In conjunction with the fourth aspect, in some implementations, when the first monitoring result includes identification information of at least one measurement-determined optimal reference signal resource in the first subset (set M), the network device determines a second accuracy based on at least one measurement-determined optimal reference signal resource in the first subset (set M) and the entire set of the first reference signal resource set (set A) or at least one prediction-determined optimal reference signal resource in the first subset (set M). This second accuracy is used to indicate whether the first inference result is accurate or the accuracy of the first inference result.

[0085] It should be understood that some implementation methods in the fourth aspect can achieve similar technical effects to the corresponding implementation methods in the first aspect, and will not be elaborated here.

[0086] Fifthly, a communication device is provided. The device includes modules or units for implementing either the first or third aspect, or any possible implementation thereof.

[0087] In a sixth aspect, a communication device is provided. The device includes modules or units for implementing either the second or fourth aspect, or any possible implementation thereof.

[0088] In a seventh aspect, a communication device is provided. The communication device includes at least one processor and a communication interface, the communication interface being used for the communication device to interact with other communication devices, and when program instructions are executed in the at least one processor, causing the communication device to perform the method as described in any one of the first or third aspects or any possible implementation thereof.

[0089] Eighthly, a communication device is provided. The communication device includes at least one processor and a communication interface for the communication device to interact with other communication devices. When program instructions are executed in the at least one processor, the communication device causes the communication device to perform the method described in any of the second or fourth aspects, or any possible implementation thereof.

[0090] Ninthly, a communication system is provided. This communication system includes the communication devices described in the fifth aspect and the communication devices described in the sixth aspect, or includes the communication devices described in the seventh aspect and the communication devices described in the eighth aspect.

[0091] In a tenth aspect, a computer-readable storage medium is provided that stores program code for execution by a device, wherein when the program code is executed, the method described in any of the first to fourth aspects above, or in any possible implementation thereof, is executed.

[0092] Eleventhly, a chip is provided, the chip including at least one processor, which, when program instructions are executed in the at least one processor, causes the method described in any one of the first to fourth aspects or any possible implementation thereof to be executed.

[0093] In a twelfth aspect, a computer program product is provided, the computer program product including program instructions that, when the computer program product is run on a communication device, cause the communication device to perform the method described in any one of the first to fourth aspects or any possible implementation thereof. Attached Figure Description

[0094] Figure 1 is a schematic structural diagram of a communication system according to an embodiment of this application.

[0095] Figure 2 is a schematic structural diagram of a communication system according to another embodiment of this application.

[0096] Figure 3 is a schematic structural diagram of a communication system according to another embodiment of this application.

[0097] Figure 4 is a schematic diagram of wide beam and narrow beam.

[0098] Figure 5 is a schematic flowchart of a communication method according to an embodiment of this application.

[0099] Figure 6 is a schematic flowchart of a communication method according to another embodiment of this application.

[0100] Figure 7 is a schematic flowchart of a communication method according to another embodiment of this application.

[0101] Figure 8 is a schematic flowchart of a communication method according to another embodiment of this application.

[0102] Figure 9 is a schematic structural block diagram of a communication device according to an embodiment of the present application.

[0103] Figure 10 is a schematic structural block diagram of a communication device according to another embodiment of this application. Detailed Implementation

[0104] The technical solutions in this application will now be described with reference to the accompanying drawings.

[0105] This application will present various aspects, embodiments, or features relating to a system comprising multiple devices, components, modules, etc. It should be understood and appreciated that individual systems may include additional devices, components, modules, etc., and / or may not include all the devices, components, modules, etc. discussed in conjunction with the accompanying drawings. Furthermore, combinations of these approaches are also possible.

[0106] Furthermore, in the embodiments of this application, the words "exemplary," "for example," etc., are used to indicate that they are examples, illustrations, or descriptions. Any embodiment or design scheme described as "exemplary" in the embodiments of this application should not be construed as being better or more advantageous than other embodiments or design schemes. Specifically, the use of the term "exemplary" is intended to present the concept in a concrete manner.

[0107] The business 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 technology and the emergence of new business scenarios, the technical solutions provided in the embodiments of this application are also applicable to similar technical problems.

[0108] References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0109] In this application embodiment, "at least one" refers to one or more, and "more than one" refers to two or more. "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, and B alone, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, or c can represent: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or multiple.

[0110] The technical solutions provided in this application can be applied to various communication systems, such as: 5th generation (5G) or new radio (NR) systems, long term evolution (LTE) systems, LTE frequency division duplex (FDD) systems, LTE time division duplex (TDD) systems, wireless local area network (WLAN) systems, satellite communication systems, future communication networks, such as integrated systems of multiple systems. The technical solutions provided in this application can also be applied to device-to-device (D2D) communication, vehicle-to-everything (V2X) communication, machine-to-machine (M2M) communication, machine-type communication (MTC), and Internet of Things (IoT) communication systems or other communication systems.

[0111] In the communication system described in this application, a device can send signals to or receive signals from another device. These signals may include information, signaling, or data. The device can also be replaced by an entity, network entity, communication device, communication module, node, communication node, network element, etc. This application describes the system using a device as an example. For instance, the communication system may include at least one terminal device and at least one network device. The network device can send downlink signals to the terminal device, and / or the terminal device can send uplink signals to the network device. It is understood that the terminal device in this application can be replaced by a first device, and the network device can be replaced by a second device, both performing the corresponding communication methods described in this disclosure.

[0112] The methods provided in this application embodiment can be executed by a terminal-side device or a network-side device. The terminal-side device can refer to the terminal device itself, a component within the terminal device (e.g., a processor, chip, or chip system), an AI entity serving the terminal device, such as a server (e.g., an over-the-top (OTT) server or a cloud server), or a logic module or software capable of implementing all or part of the terminal device's functions. The network-side device can refer to the network device itself, a component within the network device (e.g., a processor, chip, or chip system), an AI entity serving the network device, such as a RAN intelligent controller (RIC), operation administration and maintenance (OAM), or a server (e.g., an OTT server or a cloud server), or a logic module or software capable of implementing all or part of the network device's functions. Communication between the terminal-side device and the network-side device can be achieved through a communication link between the terminal device and the network device, a communication link between servers, forwarding through other communication devices outside the server, or a wired link. The following description uses terminal devices or network devices as examples. It is understood that terminal devices can be replaced by terminal-side devices, such as one or more of the aforementioned terminal-side devices, and network devices can also be replaced by network-side devices, such as one or more of the aforementioned network-side devices.

[0113] In wireless communication networks, such as mobile communication networks, the services supported by the networks are becoming increasingly diverse, thus requiring increasingly diverse demands. For example, networks need to support ultra-high speeds, ultra-low latency, and / or massive connectivity. This characteristic makes network planning, network configuration, and / or resource scheduling increasingly complex. Furthermore, as network functions become more powerful, such as supporting higher spectrum, supporting higher-order multiple-input multiple-output (MIMO) technologies, supporting beamforming, and / or supporting beam management, network energy efficiency has become a hot research topic. These new demands, new scenarios, and new characteristics bring unprecedented challenges to network planning, operation, and efficient operation. To meet these challenges, artificial intelligence (AI) technology can be introduced into wireless communication networks to achieve network intelligence. To support AI technology in wireless networks, AI nodes may also be introduced.

[0114] Figure 1 is a schematic diagram of a communication system applicable to the communication method of this application embodiment. As shown in Figure 1, the communication system 100 may include at least one network device, such as network device 110 shown in Figure 1. The communication system 100 may also include at least one terminal device, such as terminal device 120 and terminal device 130 shown in Figure 1. Network device 110 and terminal devices (such as terminal devices 120 and 130) can communicate via a wireless link. The communication devices in this communication system, for example, network device 110 and terminal device 120, can communicate via multi-antenna technology.

[0115] In some embodiments, the communication system 100 further includes an AI network element 140. The AI ​​network element 140 is used to perform AI-related operations, such as building training datasets or training AI models.

[0116] In one possible implementation, network device 110 can send data related to the training of the AI ​​model to AI network element 140, which then constructs a training dataset and trains the AI ​​model. For example, the data related to the training of the AI ​​model may include data reported by the terminal device. AI network element 140 can send the results of operations related to the AI ​​model to network device 110, which then forwards them to the terminal device. For example, the results of operations related to the AI ​​model may include at least one of the following: a trained AI model, model evaluation results, or test results. Exemplarily, a portion of the trained AI model may be deployed on network device 110, and another portion on the terminal device. Alternatively, the trained AI model may be deployed on network device 110. Or, the trained AI model may be deployed on the terminal device.

[0117] It should be understood that Figure 1 is only used as an example of the AI ​​network element 140 being directly connected to the network device 110. In other scenarios, the AI ​​network element 140 can also be connected to a terminal device. Alternatively, the AI ​​network element 140 can be connected to both the network device 110 and a terminal device simultaneously. Alternatively, the AI ​​network element 140 can also be connected to the network device 110 through a third-party network element. This application embodiment does not limit the connection relationship between the AI ​​network element and other network elements.

[0118] AI element 140 can also be set as a module in network devices and / or terminal devices, for example, in network device 110 or terminal device shown in Figure 1.

[0119] It should be noted that Figure 1 is a simplified schematic diagram for ease of understanding. For example, the communication system may also include other devices, such as wireless relay devices and / or wireless backhaul devices, which are not shown in Figure 1. In practical applications, the communication system may include multiple network devices or multiple terminal devices. This application embodiment does not limit the number of network devices and terminal devices included in the communication system.

[0120] In the embodiments of this application, the terminal device may also be referred to as user equipment (UE), access terminal, user unit, user station, mobile station, mobile station, remote station, remote terminal, mobile device, user terminal, terminal, wireless communication device, user agent, or user apparatus.

[0121] Terminal devices can be devices that provide voice / data, such as handheld devices with wireless connectivity, in-vehicle devices, etc. Currently, examples of terminals include: mobile phones, tablets, laptops, PDAs, mobile internet devices (MIDs), wearable devices, virtual reality (VR) devices, augmented reality (AR) devices, wireless terminals in industrial control, wireless terminals in self-driving vehicles, wireless terminals in remote medical surgery, wireless terminals in smart grids, wireless terminals in transportation safety, wireless terminals in smart cities, wireless terminals in smart homes, cellular phones, cordless phones, session initiation protocol (SIP) phones, wireless local loop (WLL) stations, personal digital assistants (PDAs), handheld devices with wireless communication capabilities, computing devices or other processing devices connected to wireless modems, wearable devices, terminal devices in 5G networks, or future public land mobile communication networks. Terminal devices in a network (PLMN), etc., are not limited to this in the embodiments of this application.

[0122] By way of example and not limitation, in this embodiment, the terminal device can also be a wearable device. Wearable devices, also known as wearable smart devices, are a general term for devices that utilize wearable technology to intelligently design and develop everyday wearables, such as glasses, gloves, watches, clothing, and shoes. Wearable devices are portable devices that are worn directly on the body or integrated into the user's clothing or accessories. Wearable devices are not merely hardware devices, but also achieve powerful functions through software support, data interaction, and cloud interaction. Broadly speaking, wearable smart devices include those that are feature-rich, large in size, and can achieve complete or partial functions without relying on a smartphone, such as smartwatches or smart glasses, as well as those that focus on a specific type of application function and require the use of other devices such as smartphones, such as various smart bracelets and smart jewelry for vital sign monitoring.

[0123] In this embodiment, the device for implementing the functions of the terminal device can be the terminal device itself, or it can be any device capable of supporting the terminal device in implementing those functions, such as a chip system. This device can be installed in or used in conjunction with the terminal device. In this embodiment, the chip system can be composed of chips or may include chips and other discrete components. This embodiment only uses the terminal device as an example to illustrate the device for implementing the functions of the terminal device, and does not constitute a limitation on the solution of this embodiment.

[0124] The network device in this application embodiment can be a device for communicating with a terminal device. This network device can include an access network device (i.e., an access network node) or a radio access network device, such as a base station. In this application embodiment, the radio access network device can refer to a radio access network (RAN) node (or device) that connects the terminal device to the wireless network. A base station can broadly encompass, or be replaced by, various names including: NodeB, evolved NodeB (eNB), next-generation NodeB (gNB), relay station, access point, transmitting and receiving point (TRP), transmitting point (TP), master station, auxiliary station, motor slide retainer (MSR) node, home base station, network controller, access node, wireless node, access point (AP), transmission node, transceiver node, baseband unit (BBU), remote radio unit (RRU), active antenna unit (AAU), remote radio head (RRH), central unit (CU), distributed unit (DU), radio unit (RU), positioning node, etc. A base station can be a macro base station, micro base station, relay node, donor node, or similar entities, or combinations thereof. A base station can also refer to a communication module, modem, or chip installed within the aforementioned equipment or apparatus. A base station can also be a mobile switching center, equipment performing base station functions in D2D, V2X, and M2M communications, network-side equipment in future communication networks, or equipment performing base station functions in future communication networks. A base station can support networks using the same or different access technologies. Optionally, a RAN node can also be a server, wearable device, vehicle, or in-vehicle equipment. For example, the access network equipment in vehicle-to-everything (V2X) technology can be a roadside unit (RSU). The embodiments of this application do not limit the specific technologies or equipment forms used in the network equipment.

[0125] Base stations can be fixed or mobile. For example, a helicopter or drone can be configured to act as a mobile base station, and one or more cells can move depending on the location of the mobile base station. In other examples, a helicopter or drone can be configured as a device to communicate with another base station.

[0126] In some deployments, the network devices mentioned in the embodiments of this application may be devices including CU, DU, or CU and DU, or devices with control plane CU nodes (central unit-control plane (CU-CP)) and user plane CU nodes (central unit-user plane (CU-UP)) and DU nodes. For example, the network devices may include gNB-CU-CP, gNB-CU-UP, and gNB-DU.

[0127] In some deployments, multiple RAN nodes collaborate to assist terminals in achieving wireless access, with different RAN nodes each implementing some of the base station's functions. For example, RAN nodes can be CUs, DUs, CU-CPs, CU-UPs, or RUs. CUs and DUs can be configured separately or included in the same network element, such as a BBU. RUs can be included in radio frequency equipment or radio frequency units, such as RRUs, AAUs, or RRHs.

[0128] RAN nodes can support one or more types of fronthaul interfaces, with different fronthaul interfaces corresponding to DUs and RUs with different functions. If the fronthaul interface between the DU and RU is a common public radio interface (CPRI), the DU is configured to implement one or more baseband functions, and the RU is configured to implement one or more radio frequency functions. If the fronthaul interface between the DU and RU is another type of interface, relative to CPRI, some downlink and / or uplink baseband functions, such as, for downlink, precoding, digital beamforming (BF), or one or more of inverse fast Fourier transform (IFFT) / cyclic prefix addition (CP), are moved from the DU to the RU; and for uplink, one or more of digital beamforming (BF), or fast Fourier transform (FFT) / cyclic prefix removal (CP), are moved from the DU to the RU. In one possible implementation, the interface can be an enhanced common public radio interface (eCPRI). Under the eCPRI architecture, the segmentation between DU and RU differs, corresponding to different categories (Cat) of eCPRI, such as eCPRI Cat A, B, C, D, E, F.

[0129] Taking eCPRI Cat A as an example, for downlink transmission, the DU is configured to implement one or more functions before and after layer mapping (i.e., coding, rate matching, scrambling, modulation, and layer mapping), while other functions after layer mapping (e.g., resource element (RE) mapping, digital beamforming (BF), or one or more functions of inverse fast Fourier transform (IFFT) / adding cyclic prefix (CP)) are moved to the RU. For uplink transmission, the DU is configured to implement one or more functions before and after demapping (i.e., decoding, rate matching de-matching, descrambling, demodulation, inverse discrete Fourier transform (IDFT), channel equalization, and demapping), while other functions after demapping (e.g., digital BF or one or more functions of fast Fourier transform (FFT) / removing CP) are moved to the RU. It is understandable that the functional descriptions of the DU and RU corresponding to various types of eCPRI can be found in the eCPRI protocol, and will not be elaborated here.

[0130] In one possible design, the processing unit in the BBU used to implement baseband functions is called the baseband high (BBH) unit, and the processing unit in the RRU / AAU / RRH used to implement baseband functions is called the baseband low (BBL) unit.

[0131] In different systems, CU (or CU-CP and CU-UP), DU, or RU may have different names, but those skilled in the art will understand their meaning. For example, in an open radio access network (ORAN / O-RAN) system, CU can also be called O-CU (open CU), DU can also be called O-DU, CU-CP can also be called O-CU-CP, CU-UP can also be called O-CU-UP, and RU can also be called O-RU. Any of the units among CU (or CU-CP, CU-UP), DU, and RU in this application can be implemented through software modules, hardware modules, or a combination of software modules and hardware modules.

[0132] In this embodiment, the apparatus for implementing the functions of a network device can be a network device itself, or an apparatus capable of supporting the network device in implementing those functions, such as a chip system, hardware circuit, software module, or a hardware circuit plus a software module. This apparatus can be installed in or used in conjunction with the network device. In this embodiment, the example of a network device is used only to illustrate the apparatus for implementing the functions of the network device, and does not constitute a limitation on the solutions described in this embodiment.

[0133] Network devices and / or terminal devices can be deployed on land, including indoors or outdoors, handheld or vehicle-mounted; they can also be deployed on water; and they can also be deployed in the air on airplanes, balloons, and satellites. This application does not limit the scenario in which the network devices and terminal devices are located. Furthermore, terminal devices and network devices can be hardware devices, or software functions running on dedicated hardware or general-purpose hardware, such as virtualization functions instantiated on a platform (e.g., a cloud platform), or entities that include dedicated or general-purpose hardware devices and software functions. This application does not limit the specific form of the terminal devices and network devices.

[0134] Optionally, the AI ​​node can be deployed in one or more of the following locations within the communication system: access network equipment, terminal equipment, or core network equipment, etc. Alternatively, the AI ​​node can be deployed independently, for example, in a location other than any of the aforementioned devices, such as in the host or cloud server of an over-the-top (OTT) system. The AI ​​node can communicate with other devices in the communication system, which can be one or more of the following: network equipment, terminal equipment, or core network elements, etc.

[0135] It is understood that this application does not limit the number of AI nodes. For example, when there are multiple AI nodes, these nodes can be divided based on function, such as different AI nodes being responsible for different functions.

[0136] It can also be understood that AI nodes can be AI network elements or AI modules. AI nodes can be independent devices, or they can be integrated into the same device to implement different functions. Alternatively, they can be network elements in hardware devices, software functions running on dedicated hardware, or virtualization functions instantiated on a platform (e.g., a cloud platform). This application does not limit the specific form of the AI ​​nodes described above.

[0137] Figure 2 illustrates a possible application framework in a communication system. As shown in Figure 2, network elements in the communication system are connected via interfaces (e.g., NG, Xn) or air interfaces. These network element nodes, such as core network equipment, access network nodes (RAN nodes), terminal equipment, or one or more devices in operation administration and maintenance (OAM), are equipped with one or more AI modules (only one is shown in Figure 2 for clarity). An access network node can be a single RAN node or can include multiple RAN nodes, for example, including CU and DU. CU and / or DU can also be equipped with one or more AI modules. Optionally, a CU can be further divided into CU-CP and CU-UP. One or more AI models are configured in CU-CP and / or CU-UP. Exemplarily, CU and DU are connected via an F1 interface. CU and CU are connected via an Xn interface.

[0138] AI modules are used to implement corresponding AI functions. AI modules deployed in different network elements can be the same or different. Depending on the parameter configuration, the AI ​​module can implement different functions. The AI ​​module model can be configured based on one or more of the following parameters: structural parameters (e.g., at least one of the following: number of neural network layers, neural network width, inter-layer connections, neuron weights, neuron activation function, or biases in the activation function), input parameters (e.g., the type and / or dimension of the input parameters), or output parameters (e.g., the type and / or dimension of the output parameters). The biases in the activation function can also be referred to as the neural network biases.

[0139] An AI module can have one or more models. A model can infer an output, which includes one or more parameters. The learning, training, or inference processes of different models can be deployed on different nodes or devices, or they can be deployed on the same node or device.

[0140] The network device can be a network device equipped with one or more AI modules. The network device can be one or more devices in the core network, access network node (RAN node), or OAM as shown in Figure 2. For example, the AI ​​module can be the RIC shown in Figure 3, such as a near real-time RIC or a non-real-time RIC. For example, the near real-time RIC is set in the RAN node (e.g., in CU, DU), while the non-real-time RIC is set in the OAM, cloud server, core network device, or other network device. The RIC can obtain data (e.g., a subset of data) from multiple terminal devices from the RAN node (e.g., CU, CU-CP, CU-UP, DU, and / or RU), reassemble it into a training dataset #2, and train based on the training dataset #2. Exemplarily, the near real-time RIC and the non-real-time RIC can also be set up separately as a network element; the network device can be a near real-time RIC or a non-real-time RIC.

[0141] Figure 3 illustrates a possible application framework in a communication system. As shown in Figure 3, the communication system includes a RAN intelligent controller (RIC). For example, the RIC can be the AI ​​module shown in Figure 2, used to implement AI-related functions. RICs include near-real-time RICs (near-RT RICs) and non-real-time RICs (non-RT RICs). Non-real-time RICs primarily process non-real-time information, such as data that is not sensitive to latency, with latency in the order of seconds. Real-time RICs primarily process near-real-time information, such as data that is relatively sensitive to latency, with latency in the order of tens of milliseconds.

[0142] Near real-time RICs are used for model training and inference. For example, they are used to train AI models and then use those models 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 terminals. This information can be used as training data or input data for inference. Optionally, near real-time RICs can deliver inference results to RAN nodes and / or terminals. Optionally, inference results can be exchanged between CUs and DUs, and / or between DUs and RUs. For example, a near real-time RIC delivers an inference result to a DU, which then sends it to an RU.

[0143] Non-real-time RICs are also used for model training and inference. For example, they can be used to train AI models and then use those 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 terminals. This information can be used as training data or inference data, and the inference results can be delivered to RAN nodes and / or terminals. Optionally, inference results can be exchanged between CUs and DUs, and / or between DUs and RUs; for example, a non-real-time RIC delivers inference results to a DU, which then forwards them to an RU.

[0144] Near real-time RICs and non-real-time RICs can also be configured as separate network elements. Optionally, near real-time RICs and non-real-time RICs can also be part of other devices. For example, near real-time RICs can be set in RAN nodes (e.g., CU, DU), while non-real-time RICs can be set in OAM, cloud servers, core network devices, or other network devices.

[0145] Beam management refers to the process by which terminal and network devices periodically identify the optimal beam. The optimal beam can be the beam that maximizes received or transmitted energy. For example, if a receiver uses different receive beams to receive a reference signal, the optimal beam can include the beam with the highest measured value of the corresponding reference signal among multiple different receive beams. Similarly, if a transmitter uses different transmit beams to transmit a signal, the optimal beam can include the beam with the highest measured value of the corresponding reference signal when the transmitted reference signal arrives at the receiver among multiple transmit beams. The measured value of the reference signal can be, for example, the measured reference signal received power (RSRP), signal-to-interference-plus-noise ratio (SINR), or other possible estimates.

[0146] A beam is a communication resource. In the NR protocol, a beam can be represented as a spatial filter, or spatial parameters. The beam used to transmit signals can be called a transmission beam (Tx beam), or a spatial domain transmit filter, or a spatial domain transmit parameter; the beam used to receive signals can be called a reception beam (Rx beam), or a spatial domain receiver filter, or a spatial domain receive parameter. The transmission beam refers to the distribution of signal strength in different directions in space after the signal is transmitted through the antenna, while the reception beam refers to the distribution of signal strength in different directions in space of the wireless signal received from the antenna. Beams can be identified by their identifier (ID). For example, a beam ID can be a Channel State Information Reference Signal Resource Indicator (CSI-RS, CRI), or it can be a bit in a bitmap corresponding to the beam, or it can be the beam's index information within a beam set. For instance, the number of bits in the bitmap is equal to the total number of beams associated with the network device in a single beam management inference task. Beams can be categorized as wide beams and narrow beams. A wide beam refers to a beam with a relatively large radiation range of the transmitting or receiving antenna when transmitting or receiving signals. Wide beams are typically used in applications requiring broadcasting signals to a large area or providing wide coverage. Wide beams can provide a wider coverage area, but the signal strength is relatively weaker. A narrow beam refers to a beam with a relatively small radiation range of the transmitting or receiving antenna. Narrow beams are typically used in applications requiring focusing signals onto a specific target or area. Narrow beams can provide higher signal strength and higher directivity, but the coverage area is relatively smaller.

[0147] The above measurements can also be called information characterizing the channel state, that is, they can be called measurements of channel state information.

[0148] In this application, the channel state information may include one or more of the following: rank indication (RI) information, channel quality indicator (CQI) information, precoding matrix indicator (PMI) information, or reference signal receiver power (RSRP), such as layer 1 reference signal receiver power (L1-RSRP), reference signal receiver quality (RSRQ), and signal to interference plus noise ratio (SINR).

[0149] In this application, reference signal resources are used to carry a reference signal, which includes a synchronizing signal block (SSB) and / or a channel state information reference signal (CSI-RS), etc. The reference signal resources may include a beam, or have a corresponding relationship with a beam. Furthermore, the reference signal resources may also include time-domain resources and / or frequency-domain resources corresponding to the beam, such as time-frequency resources. The beam can also be referred to as a spatial domain resource.

[0150] Alternatively, the beam can be replaced with a first signal, downlink beam, transmit beam, transmit beam, thin beam, narrow beam, wide beam, spatial filter, spatial filter, spatial parameters, spatial transmit filter, port, etc.

[0151] In this application, the information used to indicate the beam used for transmission can be called beam indication information. Beam indication information can be one or more of the following: beam number (or index, identifier, ID, etc.), identifier of signal resources (e.g., identifier of reference signal resources, such as index or number, where the signal resources can be one or more of uplink signal resources, downlink signal resources, or sidelink signal resources, where the index or number can be absolute, relative, or logical, and can include one or more of the following: group or set index or number, or index or number of resources within a group or set, or index or number of resources), absolute index of the beam, relative index of the beam, logical index of the beam, index of the antenna port corresponding to the beam, index of the antenna port group corresponding to the beam, index of the signal (e.g., downlink signal, uplink signal, or sidelink signal, etc.) corresponding to the beam, time index of the SSB corresponding to the beam, beam pair link (BPL) information, transmit parameters (Tx parameter) corresponding to the beam, and receive parameters (Rx parameter) corresponding to the beam. The beam indication information includes at least one of the following: beam parameter, beam-corresponding transmit weight, beam-corresponding weight matrix, beam-corresponding weight vector, beam-corresponding receive weight, beam-corresponding transmit weight index, beam-corresponding weight matrix index, beam-corresponding weight vector index, beam-corresponding receive weight index, beam-corresponding receive codebook, beam-corresponding transmit codebook, beam-corresponding receive codebook index, and beam-corresponding transmit codebook index. The absolute index of the beam includes, for example, the index of the beam in beam set A, and the relative index of the beam includes, for example, the index of the beam in a subset M of beam set A. The logical index of the beam includes, for example, the bit corresponding to the beam in the bitmap. Beam indication information can also be represented as a transmission configuration index (TCI) or a TCI status. A TCI status includes one or more quasi-co-location (QCL) information, each QCL information including a reference signal (or synchronization signal block) ID and a QCL type. For example, a terminal device may need to determine the beam to receive the physical downlink shared channel (PDSCH) based on the TCI status indicated by the network device (typically carried by the physical downlink control channel, PDCCH). In this application, the beam index information, i.e., the beam ID, is a typical example of beam indication information. The beam index can also be replaced with other beam indication information that can indicate a beam.In this application, the identification information of the reference signal resource can be replaced with the identification information of the beam corresponding to the reference signal resource or the index information of the beam (such as one or more of absolute index, relative index, or logical index).

[0152] In this application, prediction information (i.e., predicted values) refers to the prediction results directly output by the AI ​​model, or the result obtained after data processing of the prediction results directly output by the AI ​​model. A single piece of prediction information refers to the prediction result directly output by the AI ​​model in a single prediction process, or the result obtained after processing the prediction result. The AI ​​model can be deployed on a terminal device or on an OTT device on the terminal device side. When the AI ​​model is deployed on an OTT device, the terminal device can receive the prediction results output by the AI ​​model from the OTT device.

[0153] To achieve beam management, one possible approach is to reduce beam scanning overhead through methods such as layered scanning. This involves scanning a wide beam first, followed by scanning a portion of narrow beams within the wide beam, thus reducing overhead. A schematic diagram of wide and narrow beams is shown in Figure 4. As shown in Figure 4, compared to narrow beams, wide beams have a wider beam angle and can transmit signals over a wider range of directions. Conversely, narrow beams have a narrower beam angle and can transmit signals over a smaller range of directions. When the sum of the beam angles of a set of wide beams is the same as the sum of the beam angles of a set of narrow beams, the wide beams contain fewer beams than the narrow beams.

[0154] Beam selection is primarily accomplished through reference signals and corresponding beam measurements. Specifically, the reference signal can include one or more of the following: SSB (i.e., SS / PBCH block or SS block), or CSI-RS. The SSB can be a cell broadcast signal, comprising the primary synchronization signal (PSS), secondary synchronization signal (SSS), physical broadcast channel (PBCH), and demodulation reference signal (DMRS). The SSB can be transmitted periodically according to the cell configuration, and can be considered a wide-beam signal. Correspondingly, the CSI-RS signal can be a user equipment-level signal, and can be understood as a narrow-beam signal.

[0155] AI technology can also be applied to beam scanning to reduce overhead. In AI model-based beam management, the AI ​​model can be a regression model or a classification model. The terminal device or network device determines the input data for the AI ​​model based on the measured values ​​of the channel state information corresponding to each reference signal resource in the reference signal resource set B (set B). This input data includes the measured values ​​of the channel state information corresponding to each reference signal resource in set B. Alternatively, the input data can be determined based on the measured values ​​of the channel state information corresponding to each reference signal resource in set B. For example, the input data could be data obtained after normalizing the measured values ​​of the channel state information corresponding to each reference signal resource in set B, or data obtained after filtering the measured values ​​of the channel state information corresponding to each reference signal resource in set B. Filtering the measured values ​​of the channel state information corresponding to each reference signal resource in set B includes, for example, removing one or more smaller measured values ​​from the measured values ​​of the channel state information corresponding to each reference signal resource in set B.

[0156] When the AI ​​model is a regression model, the terminal device or network device inputs the input data into the AI ​​model to obtain the AI ​​model's output (i.e., the inference result). The AI ​​model's output includes the predicted value of the channel state information corresponding to each reference signal resource in the entire set of reference signal resources A (set A). Based on the AI ​​model's output, the terminal device determines at least one predicted optimal reference signal resource in the entire set or subset M of the reference signal resource set A (set A) and reports it to the network device, for example, reporting the identification information (ID) of the at least one predicted optimal reference signal resource and / or the predicted value of the channel state information corresponding to the at least one predicted optimal reference signal resource. The predicted value of the channel state information corresponding to at least one predicted optimal reference signal resource in the reference signal resource set A (set A) is greater than or equal to the predicted values ​​of the channel state information corresponding to all reference signal resources in the reference signal resource set A except for the at least one predicted optimal reference signal resource. The predicted value of the channel state information corresponding to at least one predicted optimal reference signal resource in subset M is greater than or equal to the predicted value of the channel state information corresponding to reference signal resources in subset M other than the at least one predicted optimal reference signal resource, or the at least one predicted optimal reference signal resource in subset M is a reference signal resource in subset M that belongs to at least one predicted optimal reference signal resource in the reference signal resource set A.

[0157] When the AI ​​model is a classification model, the terminal device or network device inputs the input data into the AI ​​model to obtain the AI ​​model's output (i.e., the inference result). The AI ​​model's output includes the probability that each reference signal resource in the reference signal resource set A (set A) is the best reference signal resource in set A. The measured value of the channel state information corresponding to the best reference signal resource in set A is greater than or equal to the measured values ​​of the channel state information corresponding to other reference signal resources in set A besides the best reference signal resource; that is, the best reference signal resource in set A is the reference signal resource with the best signal transmission performance in set A. Similarly, the measured value of the channel state information corresponding to the best reference signal resource in subset M is greater than or equal to the measured values ​​of the channel state information corresponding to other reference signal resources in subset M besides the best reference signal resource; that is, the best reference signal resource in subset M is the reference signal resource with the best signal transmission performance in subset M. Based on the output of the AI ​​model, the terminal device determines at least one predicted optimal reference signal resource in the entire set or subset M of the reference signal resource set A (set A), and reports it to the network device, for example, reporting the identification information of the at least one predicted optimal reference signal resource. The probability corresponding to at least one predicted optimal reference signal resource in the reference signal resource set A is greater than or equal to the probability corresponding to any other reference signal resource in the reference signal resource set A. The probability corresponding to at least one predicted optimal reference signal resource in the reference signal resource set A is the probability that the reference signal resource is the optimal reference signal resource in the reference signal resource set A. The probability corresponding to at least one predicted optimal reference signal resource in the subset M is greater than or equal to the probability corresponding to any other reference signal resource in the subset M, or, at least one predicted optimal reference signal resource in the subset M is a reference signal resource in the subset M that belongs to at least one predicted optimal reference signal resource in the reference signal resource set A. The probability corresponding to at least one predicted optimal reference signal resource in subset M is the probability that the reference signal resource is the optimal reference signal resource in the entire set or subset M of the reference signal resource set A.

[0158] In this system, the reference signal resources in reference signal resource set A are either real resources (i.e., actually configured resources) or virtual resources (i.e., not actually configured resources). The reference signal resources in subset M are real resources (i.e., actually configured resources). Reference signal resource set B is a subset of reference signal resource set A. Alternatively, the signal angle corresponding to each reference signal resource in reference signal resource set B is greater than the signal angle corresponding to each reference signal resource in reference signal resource set A. For example, each reference signal resource in reference signal resource set B is a wide beam, and each reference signal resource in reference signal resource set A is a narrow beam. The channel state information corresponding to the reference signal resources is, for example, reference signal received power (RSRP) or signal-to-interference-plus-noise ratio (SINR). Each reference signal resource in the reference signal resource set carries a reference signal, which includes a synchronizing signal block (SSB) and / or a channel state information reference signal (CSI-RS). This reference signal resource is, for example, a beam.

[0159] In AI-based beam management, network devices and / or terminal devices need to monitor the AI ​​model to ensure beam management quality. The network devices and / or terminal devices perform measurements based on the entire set or subset M of the reference signal resource set A to determine the measured value of the channel state information corresponding to at least one reference signal resource in the entire set A or subset M, thereby determining at least one optimal reference signal resource determined by measurement in the entire set A or subset M. The measured value of the channel state information corresponding to the optimal reference signal resource determined by measurement in the first reference signal resource set A is greater than or equal to the measured values ​​of the channel state information corresponding to all reference signal resources in the first reference signal resource set A except for the optimal reference signal resource determined by measurement. The measured value of the channel state information corresponding to the optimal reference signal resource determined by measurement in the subset M is greater than or equal to the measured values ​​of the channel state information corresponding to all reference signal resources in the subset M except for the optimal reference signal resource determined by measurement.

[0160] When the AI ​​model is a regression model, the terminal device and / or network device determine the monitoring result of the AI ​​model based on the measured values ​​of channel state information corresponding to at least one first reference signal resource in the entire set or subset M of the reference signal resource set A. Alternatively, the terminal device and / or network device determine the monitoring result of the AI ​​model based on the measured values ​​of channel state information corresponding to at least one first reference signal resource in the entire set or subset M of the reference signal resource set A and the predicted values ​​of channel state information corresponding to at least one second reference signal resource in the entire set or subset M of the reference signal resource set A. The predicted values ​​of the channel state information corresponding to the at least one second reference signal resource are obtained using the AI ​​model. The at least one first reference signal resource and the at least one second reference signal resource are the same, or the at least one first reference signal resource and at least one of the at least one second reference signal resources are different. For example, the at least one first reference signal resource is at least one optimal reference signal resource determined by measurement in the entire set or subset M of the reference signal resource set A (set A). The at least one second reference signal resource is at least one optimal reference signal resource determined by prediction in the entire set or subset M of the reference signal resource set A (set A). The monitoring results of the AI ​​model are used to determine whether the inference result obtained by the AI ​​model is accurate or the accuracy of the inference result. For example, the monitoring results of the AI ​​model include measured values ​​of channel state information corresponding to the at least one first reference signal resource. Alternatively, the monitoring results of the AI ​​model include measured values ​​of channel state information corresponding to the at least one first reference signal resource and predicted values ​​of channel state information corresponding to the at least one second reference signal resource. Alternatively, the monitoring results of the AI ​​model include a first accuracy determined based on the measured values ​​of channel state information corresponding to the at least one first reference signal resource and the predicted values ​​of channel state information corresponding to the at least one second reference signal resource. This first accuracy is used to indicate whether the inference result obtained by the AI ​​model is accurate, or the first accuracy is used to indicate the accuracy of the inference result obtained by the AI ​​model.

[0161] When the AI ​​model is a classification model, the network device and / or terminal device determine the monitoring result of the AI ​​model based on at least one predicted optimal reference signal resource from the entire set or subset M of the reference signal resource set A. Alternatively, the network device and / or terminal device determine the monitoring result of the AI ​​model based on at least one predicted optimal reference signal resource from the entire set or subset M of the reference signal resource set A and at least one measured optimal reference signal resource from the entire set or subset M of the first reference signal resource set (set A). The monitoring result of the AI ​​model is used to determine whether the inference result obtained by using the AI ​​model is accurate or the accuracy of the inference result. For example, the monitoring result of the AI ​​model includes identification information of at least one measured optimal reference signal resource from the entire set or subset M of the reference signal resource set A. Alternatively, the monitoring result of the AI ​​model includes identification information of at least one predicted optimal reference signal resource from the entire set or subset M of the reference signal resource set A and at least one measured optimal reference signal resource from the entire set or subset M of the first reference signal resource set (set A). Alternatively, the monitoring results of the AI ​​model may include a second accuracy determined based on at least one prediction of the best reference signal resource from the entire set or subset M of the first set of reference signal resources (set A) and at least one measurement of the best reference signal resource from the entire set or subset M of the first set of reference signal resources (set A). This second accuracy is used to indicate whether the inference result obtained using the AI ​​model is accurate, or the second accuracy is used to indicate the accuracy of the inference result obtained using the AI ​​model.

[0162] The embodiments of this application do not limit the specific implementation method of determining accuracy. For example, the method of determining accuracy includes any one of the following (1), (2), (3), (4), (5), and (6). Among them, the method of determining the first accuracy includes any one of the following (1), (2), (3), (4), (5), and (6), and the method of determining the second accuracy includes any one of the following (2), (3), (4), (5), and (6):

[0163] (1) The accuracy includes at least one of the following: the difference between the measured value of the channel state information corresponding to at least one first reference signal resource and the predicted value of the channel state information corresponding to at least one second reference signal resource, the mean of the difference, the variance of the difference, or the standard deviation of the difference, wherein the number of the at least one first reference signal resource is the same as the number of the at least one second reference signal resource.

[0164] (2) The accuracy includes an N-bit binary value sequence, where N is a positive integer. The nth bit of this N-bit binary value sequence is used to indicate whether the nth best reference signal resource among the N predicted best reference signal resources in the entire set or subset (set M) of the first reference signal resource set (set A) belongs to the N measured best reference signal resources in the entire set (set A) or subset (set M). n = 1, ..., N. For example, the nth binary value is a third value used to indicate that the nth predicted optimal reference signal resource in the entire set or subset (set M) of the first reference signal resource set (set A) does not belong to the N measured optimal reference signal resources in the entire set or subset (set M) of the first reference signal resource set (set A). The nth binary value is a fourth value used to indicate that the nth predicted optimal reference signal resource in the entire set or subset (set M) of the first reference signal resource set (set A) belongs to the N measured optimal reference signal resources in the entire set or subset (set M) of the first reference signal resource set (set A). This third value is different from the fourth value.

[0165] (3) Accuracy includes the number of identical reference signal resources among the N predicted optimal reference signal resources in the entire set or subset (set M) of the first reference signal resource set (set A) and the N measured optimal reference signal resources in the entire set or subset (set M) of the first reference signal resource set (set A). Alternatively, accuracy includes the ratio of the number of identical reference signal resources among the N predicted optimal reference signal resources in the entire set or subset (set M) of the first reference signal resource set (set A) and the N measured optimal reference signal resources in the entire set or subset (set M) of the first reference signal resource set (set A) to N. N is a positive integer.

[0166] (4) When the N predicted optimal reference signal resources and the N measured optimal reference signal resources in the entire set or subset (set M) of the first reference signal resource set (set A) are arranged in the same order, the accuracy comprises an N-bit binary value sequence, where N is a positive integer. The nth bit of this N-bit binary value sequence is used to indicate whether the nth predicted optimal reference signal resource in the entire set or subset (set M) of the first reference signal resource set (set A) is the same as the nth measured optimal reference signal resource in the N measured optimal reference signal resources. n = 1, ..., N. For example, the nth binary value is a third value used to indicate that the nth predicted best reference signal resource among the N predicted best reference signal resources in the entire set or subset (set M) of the first reference signal resource set (set A) is different from the nth measured best reference signal resource among the N measured best reference signal resources. The nth binary value is a fourth value used to indicate that the nth predicted best reference signal resource among the N predicted best reference signal resources in the entire set or subset (set M) of the first reference signal resource set (set A) is the same as the nth measured best reference signal resource among the N measured best reference signal resources.

[0167] (5) When the N predicted optimal reference signal resources and the N measured optimal reference signal resources in the entire set or subset (set M) of the first reference signal resource set (set A) are arranged in the same order, the accuracy includes the number of reference signal resources in the entire set or subset (set M) of the first reference signal resource set (set A) that have the same arrangement order and the same identification information. Alternatively, when the N predicted optimal reference signal resources and the N measured optimal reference signal resources in the entire set or subset (set M) of the first reference signal resource set (set A) are arranged in the same order, the accuracy includes the ratio of the number of reference signal resources in the entire set or subset (set M) of the first reference signal resource set (set A) that have the same arrangement order and the same identification information to N. N is a positive integer.

[0168] (6) When the N predicted optimal reference signal resources and the N measured optimal reference signal resources in the entire set or subset (set M) of the first reference signal resource set (set A) are arranged in the same order, the accuracy includes N numerical values, or the accuracy includes statistical values ​​of N numerical values ​​(e.g., mean, variance, standard deviation, etc.), where N is a positive integer. The nth value among these N numerical values ​​is the difference between the measured value of the channel state information corresponding to the nth predicted optimal reference signal resource in the entire set or subset (set M) of the first reference signal resource set (set A) and the measured value of the channel state information corresponding to the nth measured optimal reference signal resource in the N measured optimal reference signal resources. n = 1, ..., N.

[0169] It should be understood that the above-described method for determining accuracy is merely an illustrative example, and any existing or future methods for determining the accuracy of inference results of AI models can be applied to the embodiments of this application.

[0170] When at least one predicted optimal reference signal resource in reference signal resource set A differs from one or more predicted optimal reference signal resources in at least one subset M of reference signal resource set A, for example, when subset M does not include one or more predicted optimal reference signal resources in reference signal resource set A, the accuracy of the monitoring result of the AI ​​model is low if the monitoring result is determined based on at least one measured optimal reference signal resource in subset M and at least one predicted optimal reference signal resource in reference signal resource set A. Therefore, this application provides a communication method to improve the accuracy of the monitoring result for monitoring the AI ​​model.

[0171] Figure 5 is a schematic flowchart of a communication method provided in an embodiment of this application. The method in Figure 5 is applied to a communication system, such as the communication system shown in Figure 1, Figure 2, or Figure 3. The network device in Figure 5 is, for example, the network device 110 in Figure 1, the core network device in Figure 2, the access network node, or the access network node in Figure 3. The terminal device in Figure 5 is, for example, the terminal device in Figure 1, Figure 2, or Figure 3. The method in Figure 5 includes the following steps.

[0172] 510, Determine the first monitoring result and the first instruction information.

[0173] The terminal device determines a first monitoring result and a first indication information. The first monitoring result is used to determine whether the first inference result is accurate or the accuracy of the first inference result. The first inference result is used to determine k1 predicted optimal reference signal resources in a first subset (set M) of the first reference signal resource set. The first reference signal resource set includes at least one reference signal resource. k1 is a positive integer. The first indication information is used to indicate the k1 predicted optimal reference signal resources.

[0174] In some embodiments, the first inference result is obtained by a device deploying the first AI model using the first AI model. The device deploying the first AI model is a terminal-side device, such as the terminal device itself or a device or server connected to the terminal device.

[0175] In some embodiments, the first AI model is a regression model or a classification model.

[0176] When the first AI model is a regression model, it is used to obtain a first inference result based on the first input data. This first inference result includes predicted values ​​of channel state information corresponding to each reference signal resource in the first set of reference signal resources. The first input data is determined based on measured values ​​of channel state information corresponding to each reference signal resource in the second set of reference signal resources (set B). This first input data is similar to the input data of the AI ​​model described above and will not be repeated here. The first monitoring result is determined based on measured values ​​of channel state information corresponding to at least one first reference signal resource in the first subset (set M) and predicted values ​​of channel state information corresponding to at least one second reference signal resource in the entire first set of reference signal resources (set A) or the first subset (set M). Alternatively, the first monitoring result includes measured values ​​of channel state information corresponding to at least one reference signal resource in the first subset.

[0177] For example, the first monitoring result is determined based on the measured value of channel state information corresponding to at least one first reference signal resource in the first subset (set M) and the predicted value of channel state information corresponding to at least one second reference signal resource in the entire set of the first reference signal resource set (set A) or the first subset (set M). This includes: the first monitoring result comprising the measured value of the channel state information corresponding to the at least one first reference signal resource and the predicted value of the channel state information corresponding to the at least one second reference signal resource; or the first monitoring result comprising a first accuracy determined based on the measured value of the channel state information corresponding to the at least one first reference signal resource and the predicted value of the channel state information corresponding to the at least one second reference signal resource. The first accuracy is used to indicate whether the first inference result is accurate, or the first accuracy is used to indicate the accuracy of the first inference result. The embodiments of this application do not limit the specific implementation method for determining the first accuracy; for example, the calculation method of the first accuracy is described above.

[0178] For example, the predicted value of the channel state information corresponding to at least one second reference signal resource is obtained using a first AI model. The at least one first reference signal resource is the same as the at least one second reference signal resource, or the at least one of the at least one first reference signal resource and the at least one second reference signal resource is different.

[0179] For example, the at least one first reference signal resource is at least one optimal reference signal resource determined by measurement within a first subset. The measured value of the channel state information corresponding to the at least one optimal reference signal resource determined by measurement within the first subset is greater than or equal to the measured value of the channel state information corresponding to the reference signal resources within the first subset other than the at least one optimal reference signal resource determined by measurement. The at least one second reference signal resource is the entire set of the first reference signal resource set or at least one optimal reference signal resource determined by prediction within the first subset.

[0180] When the first AI model is a regression model, the predicted value of the channel state information corresponding to at least one predicted optimal reference signal resource in the first reference signal resource set is greater than or equal to the predicted value of the channel state information corresponding to reference signal resources in the first reference signal resource set other than the at least one predicted optimal reference signal resource. Alternatively, the predicted value of the channel state information corresponding to at least one predicted optimal reference signal resource in the first subset is greater than or equal to the predicted value of the channel state information corresponding to reference signal resources in the first subset other than the at least one predicted optimal reference signal resource; or, the at least one predicted optimal reference signal resource in the first subset is a reference signal resource in the first subset that belongs to at least one predicted optimal reference signal resource in the first reference signal resource set.

[0181] It is understood that the channel state information corresponding to the reference signal resource in this application can be replaced with the RSRP, RSRQ, SINR, received power, or received quality corresponding to the reference signal resource.

[0182] When the first AI model is a classification model, it obtains a first inference result based on the first input data. This first inference result includes the probability that each reference signal resource in the first reference signal resource set is the best reference signal resource in that set. Alternatively, the first inference result includes the probability that each reference signal resource in the first reference signal resource set is the best reference signal resource in that set and the probability that each reference signal resource in the first subset is the best reference signal resource in that subset. The first input data is similar to the first input data when the first AI model is a regression model, and will not be described further here. The measured value of the channel state information corresponding to the best reference signal resource in the first reference signal resource set is greater than or equal to the measured values ​​of the channel state information corresponding to other reference signal resources in the first reference signal resource set besides the best one; that is, the best reference signal resource in the first reference signal resource set is the reference signal resource with the best signal transmission performance in that set. The measured value of the channel state information corresponding to the best reference signal resource in the first subset is greater than or equal to the measured values ​​of the channel state information corresponding to other reference signal resources in the first subset besides the best reference signal resource. That is, the best reference signal resource in the first subset is the reference signal resource with the best signal transmission performance in the first subset. The first monitoring result is determined based on at least one best reference signal resource determined by measurement in the first subset (set M) and the entire set of the first reference signal resource set (set A) or at least one best reference signal resource determined by prediction in the first subset (set M). Alternatively, the first monitoring result includes the identification information of at least one best reference signal resource determined by measurement in the first subset (set M).

[0183] In the embodiments of this application, "identification information" and "index" have similar meanings and can be substituted for each other. "At least one measurement-determined optimal reference signal resource" and "x1 measurement-determined optimal reference signal resources, where x1 is a positive integer" have similar meanings and can be substituted for each other. "At least one prediction-determined optimal reference signal resource" and "x2 prediction-determined optimal reference signal resources, where x2 is a positive integer" have similar meanings and can be substituted for each other.

[0184] For example, the first monitoring result is determined based on the best reference signal resource determined by at least one measurement in the first subset (set M) and the entire set of the first reference signal resource set (set A) or the best reference signal resource determined by at least one prediction in the first subset (set M). The first monitoring result includes: identification information of the best reference signal resource determined by at least one measurement in the first subset and identification information of the best reference signal resource determined by at least one prediction in the first subset; or, the first monitoring result includes a second accuracy determined based on the best reference signal resource determined by at least one measurement in the first subset and the entire set of the first reference signal resource set or the best reference signal resource determined by at least one prediction in the first subset. The second accuracy is used to indicate whether the first inference result is accurate, or the second accuracy is used to indicate the accuracy of the first inference result. The embodiments of this application do not limit the specific implementation of determining the second accuracy; for example, the calculation method of the second accuracy is described above.

[0185] When the first AI model is a classification model, the measured value of the channel state information corresponding to at least one optimal reference signal resource in the first subset is greater than or equal to the measured value of the channel state information corresponding to reference signal resources in the first subset other than the at least one optimal reference signal resource. The probability corresponding to at least one predicted optimal reference signal resource in the first reference signal resource set is greater than or equal to the probability corresponding to reference signal resources in the first reference signal resource set other than the at least one predicted optimal reference signal resource. The probability corresponding to at least one predicted optimal reference signal resource in the first reference signal resource set is the probability that the reference signal resource is the optimal reference signal resource in the first reference signal resource set. The probability corresponding to at least one predicted optimal reference signal resource in the first subset is greater than or equal to the probability corresponding to reference signal resources in the first subset other than the at least one predicted optimal reference signal resource, or, the probability corresponding to at least one predicted optimal reference signal resource in the first subset is a reference signal resource in the first subset that belongs to at least one predicted optimal reference signal resource in the first reference signal resource set. The probability corresponding to at least one predicted optimal reference signal resource in the first subset is the probability that the reference signal resource is the optimal reference signal resource in the entire set or the first subset of the first reference signal resource set.

[0186] In some embodiments, the reference signal resources in the first subset are real resources (i.e., resources that are actually configured). The reference signal resources in the first set of reference signal resources other than the first subset are virtual resources (i.e., resources that are not actually configured).

[0187] In some embodiments, the second set of reference signal resources is a subset of the first set of reference signal resources. Alternatively, the signal angle corresponding to each reference signal resource in the second set of reference signal resources is greater than the signal angle corresponding to each reference signal resource in the first set of reference signal resources. For example, each reference signal resource in the second set of reference signal resources is a wide beam, and each reference signal resource in the first set of reference signal resources is a narrow beam.

[0188] In some embodiments, the network device configures a second set of reference signal resources (set B) to the terminal device, the second set of reference signal resources including at least one reference signal resource. The terminal device performs measurements based on the second set of reference signal resources to obtain measured values ​​of channel state information corresponding to each reference signal resource in the second set of reference signal resources. The terminal device or inference device uses the measured values ​​of channel state information corresponding to each reference signal resource in the second set of reference signal resources to determine first input data. The terminal device or inference device uses the first input data and a first AI model to determine a first inference result. The inference device is a device with a first AI model deployed, such as a device or server connected to the terminal device.

[0189] For example, the network device sends second configuration information to the terminal device, and the terminal device receives the second configuration information from the network device. This second configuration information is used to configure a second set of reference signal resources.

[0190] In some embodiments, the network device configures a first subset (set M) of a first set of reference signal resources to the terminal device, the first subset including at least one reference signal resource. The terminal device performs measurements based on the first subset to obtain measured values ​​of channel state information corresponding to each reference signal resource in the first subset. The terminal device uses a first inference result and the measured values ​​of channel state information corresponding to at least one reference signal resource in the first subset to determine a first monitoring result.

[0191] For example, the network device sends third configuration information to the terminal device, and the terminal device receives the third configuration information from the network device. This third configuration information is used to configure the first subset.

[0192] In some embodiments, the terminal device determines k1 predicted optimal reference signal resources in a first subset of the first reference signal resource set based on the first inference result, thereby determining the first indication information.

[0193] In some embodiments, the first indication information used to indicate the k1 predicted optimal reference signal resources includes: the first indication information includes identification information of the k1 predicted optimal reference signal resources in a first reference signal resource set (set A). Alternatively, the first indication information used to indicate the k1 predicted optimal reference signal resources includes: the first indication information includes identification information of the k1 predicted optimal reference signal resources in a first subset (set M). Alternatively, the first indication information used to indicate the k1 predicted optimal reference signal resources includes: the first indication information includes identification information of the k1 predicted optimal reference signal resources in a third reference signal resource set. The third reference signal resource set belongs to the first reference signal resource set. The third reference signal resource set includes at least one reference signal resource. The at least one reference signal resource included in the third reference signal resource set is different from that included in the first subset.

[0194] For example, the third reference signal resource set is pre-configured or protocol-predefined information. For instance, before step 510, the network device and / or terminal device determine the third reference signal resource set. Alternatively, before step 510, the network device and / or terminal device determine a method for partitioning the first reference signal resource set, such as based on protocol predefined methods or based on one or more prediction results, thereby determining the third reference signal resource set. For example, through multiple prediction results, the terminal device determines that the best reference signal resources determined in each prediction belong to a certain reference signal resource set, for example, concentrated in a specific third reference signal resource set. Or, the best reference signal resources determined in different predictions belong to different reference signal resource sets. These different reference signal resource sets can form a specific partitioning method for the first reference signal resource set. The terminal device can then notify the network device of information about this specific reference signal resource set, or notify the network device of this specific partitioning method and the specific reference signal resource set to which the best reference signal resources determined in each prediction belong. Thus, when the terminal device provides feedback on the best reference signal resources determined in the prediction, it can use the index or number within the third reference signal resource set, thereby reducing the signaling overhead of the terminal device's feedback.

[0195] For example, the third reference signal resource set is information configured or indicated by the network device to the terminal device. For instance, before step 510, the network device configures the third reference signal resource set to the terminal device. Alternatively, before step 510, the network device sends indication information to the terminal device indicating a method for dividing the first reference signal resource set, and the terminal device determines the method for dividing the first reference signal resource set based on the indication information, thereby determining the third reference signal resource set.

[0196] For example, when the first indication information includes the identification information of the k1 predicted optimal reference signal resources in the third reference signal resource set, the first indication information also includes the identification information of the third reference signal resource set.

[0197] For example, the identification information of the reference signal resource includes any of the following: CRI, SSB resource indicator (SSBRI), or bits in the bitmap corresponding to the reference signal resource.

[0198] For example, when the first indication information includes the identification information of the k1 predicted optimal reference signal resources in the first reference signal resource set (set A), and the identification information includes CRI or SSBRI, the number of bits B1 included in the first indication information is determined according to the following formula (1):

[0199] in, N represents rounding up, log2 represents the logarithm to the base 2, and N represents the integer part of the logarithm. A This indicates the number of reference signal resources included in the first set of reference signal resources.

[0200] For example, when the first indication information includes the identification information of the k1 predicted optimal reference signal resources in the first subset (set M), and the identification information includes CRI or SSBRI, the number of bits B2 included in the first indication information is determined according to the following formula (2):

[0201] in, N represents rounding up, log2 represents the logarithm to the base 2, and N represents the integer part of the logarithm. M This indicates the number of reference signal resources included in the first subset.

[0202] For example, when the first indication information includes the identification information of the k1 predicted best reference signal resources in the first reference signal resource set (set A), and the identification information includes bits in the bitmap corresponding to the reference signal resources, the number of bits B3 included in the first indication information is equal to the number of reference signal resources included in the first reference signal resource set.

[0203] For example, when the first indication information includes the identification information of the k1 predicted optimal reference signal resources in the first subset (set M), and the identification information includes bits in the bitmap corresponding to the reference signal resources, the number of bits B4 included in the first indication information is equal to the number of reference signal resources included in the first subset.

[0204] For example, suppose the first reference signal resource set includes 64 reference signal resources, and the first subset includes 16 reference signal resources. When the first indication information includes the identification information of k1 = 4 predicted optimal reference signal resources in the first reference signal resource set, and this identification information includes CRI or SSBRI, the number of bits included in the first indication information is B1 = 4 × log2(64) = 24. When the first indication information includes the identification information of k1 = 4 predicted optimal reference signal resources in the first subset, and this identification information includes CRI or SSBRI, the number of bits included in the first indication information is B2 = 4 × log2(16) = 16. When the first indication information includes the identification information of the k1 = 4 predicted optimal reference signal resources in the first reference signal resource set, and this identification information includes the bits in the bitmap corresponding to the reference signal resources, the number of bits included in the first indication information is B3 = 64. When the first indication information includes the identification information of the four predicted optimal reference signal resources in the first subset, and the identification information includes the bits in the bitmap corresponding to the reference signal resources, the number of bits included in the first indication information is B4 = 16.

[0205] In some embodiments, the terminal device sends a fifth indication message to the network device, and correspondingly, the network device receives the fifth indication message from the terminal device. This fifth indication message is used to indicate that the identification information of the reference signal resource in the first indication message is the identification information of the reference signal resource in the first reference signal resource set (set A) or the first subset (set M).

[0206] 520, send the first message to the network device.

[0207] The terminal device sends first information to the network device, and correspondingly, the network device receives the first information from the terminal device. This first information is used to indicate a first monitoring result and a first indication.

[0208] In some embodiments, the first information used to indicate the first monitoring result and the first indication information includes: the first information includes the first monitoring result and the first indication information.

[0209] For example, the first information is carried in any of the following: uplink control information (UCI), channel state information report (CSI report), or radio resource control (RRC) signaling.

[0210] For example, the first information may include one or more fields, or the first information may include one or more domains, or the first information may include one or more information elements. For instance, if the first information includes one field (or one domain, or one information element), the first monitoring result and the first indication information are jointly encoded and carried through that one field (or one domain, or one information element). If the first information includes multiple fields (or multiple domains, or multiple information elements), the first monitoring result is carried through one or more fields (or one or more domains, or one or more information elements), and the first indication information is carried through one or more fields (or one or more domains, or one or more information elements).

[0211] It is understood that step 520 can also be replaced by sending a first monitoring result and a first indication information to the network device, or sending information indicating the first monitoring result and information indicating the first indication information to the network device, or sending information indicating the first monitoring result and the first indication information to the network device, or sending information indicating the first monitoring result and information indicating the first indication information to the network device. These substitutions can also be applied to situations where the first information is also used for the second indication information and / or, the third indication information, as described below. For example, sending the first monitoring result, the first indication information, and the second indication information to the network device. Other substitutions will not be elaborated here.

[0212] When the first information is used to indicate the first monitoring result and the first indication information, the terminal device can report at least one predicted optimal reference signal resource in the first subset (set M) of the first reference signal resource set (set A) to the network device. This facilitates the network device in determining whether at least one predicted optimal reference signal resource in the entire set of the first reference signal resource set (set A) is the same as at least one predicted optimal reference signal resource in the first subset (set M). This allows the network device to adjust the reference signal resources included in the reference signal resource set (i.e., the first subset) used to obtain the monitoring result, ensuring that at least one predicted optimal reference signal resource in the first reference signal resource set (set A) is as similar as possible to at least one predicted optimal reference signal resource in the first subset, thereby improving the accuracy of the monitoring result obtained using the inference result of the AI ​​model. The at least one predicted optimal reference signal resource in the entire set of the first reference signal resource set (set A) can be obtained by the network device through a process related to the terminal device reporting inference results, or it can be obtained by the network device through its own inference, or it can be obtained through other means; this application does not limit the specific methods described.

[0213] Optionally, the first information is also used to indicate the second indication information. That is, the first information is used to indicate the first monitoring result, the first indication information, and the second indication information. The second indication information is used to indicate the information of the same reference signal resources among the k1 predicted optimal reference signal resources and the k2 predicted optimal reference signal resources in the first set of reference signal resources (set A), where k2 is a positive integer.

[0214] In some embodiments, the second indication information includes information about the same reference signal resources among the k1 predicted optimal reference signal resources and the k2 predicted optimal reference signal resources in the first set of reference signal resources; or, the second indication information includes the following information to indicate the same reference signal resources among the k1 predicted optimal reference signal resources and the k2 predicted optimal reference signal resources in the first set of reference signal resources: the number of different reference signal resources among the k1 predicted optimal reference signal resources and the k2 predicted optimal reference signal resources in the first set of reference signal resources, and the ratio of the number of different reference signal resources among the k1 predicted optimal reference signal resources and the k2 predicted optimal reference signal resources in the first set of reference signal resources to k2.

[0215] In some embodiments, the first information used to indicate the first monitoring result, the first indication information, and the second indication information includes: the first information includes the first monitoring result, the first indication information, and the second indication information.

[0216] For example, the first information includes one or more fields, or the first information includes one or more domains, or the first information includes one or more information elements. For instance, when the first information includes one field (or one domain, or one information element), the first monitoring result, the first indication information, and the second indication information are jointly encoded and carried through that one field (or one domain, or one information element). When the first information includes multiple fields (or multiple domains, or multiple information elements), the first monitoring result is carried through one or more fields (or one or more domains, or one or more information elements), the first indication information is carried through one or more fields (or one or more domains, or one or more information elements), and the second indication information is carried through one or more fields (or one or more domains, or one or more information elements). Alternatively, when the first information includes multiple fields (or multiple domains, or multiple information elements), the first monitoring result and the first indication information are jointly encoded and carried through one or more fields (or one or more domains, or one or more information elements), and the second indication information is carried through one or more fields (or one or more domains, or one or more information elements). Alternatively, if the first information includes multiple fields (or multiple domains, or multiple information elements), the first monitoring result is carried by one or more fields (or one or more domains, or one or more information elements), and the first indication information and the second indication information are carried by one or more fields (or one or more domains, or one or more information elements) after joint encoding.

[0217] In some embodiments, k2 is equal to k1. Alternatively, k2 is not equal to k1. For example, if the k1 predicted optimal reference signal resources in the first subset are reference signal resources that belong to the k2 predicted optimal reference signal resources in the first reference signal resource set, then k2 is greater than or equal to k1.

[0218] In some embodiments, the terminal device determines the k1 predicted optimal reference signal resources and the k2 predicted optimal reference signal resources based on the first inference result, thereby determining the second indication information.

[0219] In some embodiments, the second indication information is used to indicate whether each of the k1 predicted optimal reference signal resources belongs to the k2 predicted optimal reference signal resources. Alternatively, the second indication information is used to indicate the number of reference signal resources in the k1 predicted optimal reference signal resources that are identical to those in the k2 predicted optimal reference signal resources. Alternatively, the second indication information is used to indicate the number of reference signal resources in the k1 predicted optimal reference signal resources that are different from those in the k2 predicted optimal reference signal resources. Alternatively, the second indication information is used to indicate the ratio of the number of reference signal resources in the k1 predicted optimal reference signal resources that are identical to those in the k2 predicted optimal reference signal resources to k2. Alternatively, the second indication information is used to indicate the ratio of the number of reference signal resources in the k1 predicted optimal reference signal resources that are different from those in the k2 predicted optimal reference signal resources to k2.

[0220] For example, when the second indication information is used to indicate whether each of the k1 predicted optimal reference signal resources belongs to the k2 predicted optimal reference signal resources, the second indication information includes k1 pieces of information. Each of the k1 pieces of information may include one or more binary bits. When each of the k1 pieces of information includes one binary bit, the k1 pieces of information may also be referred to as a k1-bit binary value or a bitmap including k1 bits. Each of the k1 pieces of information is used to indicate whether the corresponding predicted optimal reference signal resource in the first subset belongs to the k2 predicted optimal reference signal resources. That is, the i-th piece of information in the k1 pieces of information is used to indicate whether the i-th reference signal resource among the k1 predicted optimal reference signal resources in the first subset belongs to the k2 predicted optimal reference signal resources in the first reference signal resource set, i = 1, ..., k1. For example, when the i-th piece of information is a fifth value, the i-th piece of information is used to indicate that the i-th reference signal resource among the k1 predicted optimal reference signal resources in the first subset belongs to the k2 predicted optimal reference signal resources in the first reference signal resource set. When the i-th information is the sixth value, this i-th information is used to indicate that the i-th reference signal resource among the k1 predicted optimal reference signal resources in the first subset does not belong to the k2 predicted optimal reference signal resources in the first reference signal resource set. This fifth value is different from the sixth value; for example, the fifth value is 1 and the sixth value is 0; or the fifth value is 0 and the sixth value is 1.

[0221] For example, when k2 equals k1, assume that the identification information of the four predicted optimal reference signal resources in the first reference signal resource set are: identification information 1, identification information 2, identification information 3, and identification information 4, and the identification information of the four predicted optimal reference signal resources in the first subset are: identification information 1, identification information 2, identification information 3, and identification information 5. The first indication information includes: identification information 1, identification information 2, identification information 3, and identification information 5. The first information includes a first monitoring result and third information, which includes the first indication information and the second indication information. The third information, for example, includes: (identification information 1, 1), (identification information 2, 1), (identification information 3, 1), and (identification information 5, 0). Wherein, (identification information 1, 1) is used to indicate that the reference signal resource corresponding to identification information 1 belongs to the four predicted optimal reference signal resources in the first subset, and that the reference signal resource corresponding to identification information 1 belongs to the four predicted optimal reference signal resources in the first reference signal resource set. (Identification information 5, 0) is used to indicate that the reference signal resource corresponding to identification information 5 belongs to the four predicted optimal reference signal resources in the first subset, and that the reference signal resource corresponding to identification information 5 does not belong to the four predicted optimal reference signal resources in the first reference signal resource set. Alternatively, the second indication information includes: 1, 1, 1, 0. Wherein, 1, 1, 1, 0 in the second indication information correspond one-to-one with the four predicted optimal reference signal resources in the first subset indicated in the first indication information. The first 1 in the second indication information is used to indicate that the reference signal resource corresponding to identification information 1 belongs to the four predicted optimal reference signal resources in the first subset, and that the reference signal resource corresponding to identification information 1 belongs to the four predicted optimal reference signal resources in the first reference signal resource set. The fourth 0 in the second indication information is used to indicate that the reference signal resource corresponding to identification information 5 belongs to the four predicted optimal reference signal resources in the first subset, and that the reference signal resource corresponding to identification information 5 does not belong to the four predicted optimal reference signal resources in the first reference signal resource set. Alternatively, the second indication information includes 3, which indicates that the four predicted optimal reference signal resources in the first subset include three identical reference signal resources among the four predicted optimal reference signal resources in the first set of reference signal resources. Alternatively, the second indication information includes 1, which indicates that the four predicted optimal reference signal resources in the first subset include one different reference signal resource among the four predicted optimal reference signal resources in the first set of reference signal resources. Alternatively, the second indication information includes 0.75, which indicates that 75% of the reference signal resources included in the four predicted optimal reference signal resources in the first subset are identical to those in the four predicted optimal reference signal resources in the first set of reference signal resources.Alternatively, the second indication information includes: 0.25, which is used to indicate that the four predicted optimal reference signal resources in the first subset are different from the 25% of reference signal resources included in the four predicted optimal reference signal resources in the first set of reference signal resources.

[0222] For example, when k2 is not equal to k1, assume that the identification information of the four predicted optimal reference signal resources in the first reference signal resource set are: identification information 1, identification information 2, identification information 3, and identification information 4, and the identification information of the three predicted optimal reference signal resources in the first subset are: identification information 1, identification information 2, and identification information 3. The first indication information includes: identification information 1, identification information 2, and identification information 3. The second indication information is similar to the second indication information when k2 equals k1. For example, the third information includes: (identification information 1, 1), (identification information 2, 1), and (identification information 3, 1). The meaning of (identification information 1, 1) is similar to the meaning when k2 equals k1. Alternatively, the second indication information includes: 1, 1, 1. Alternatively, the second indication information includes 3. Alternatively, the second indication information includes 1. Alternatively, the second indication information includes 0.75. Alternatively, the second indication information includes 0.25.

[0223] When the first information is used to indicate the first monitoring result, the first indication information, and the second indication information, the terminal device can report to the network device information about at least one predicted optimal reference signal resource in the first reference signal resource set and at least one predicted optimal reference signal resource in the first subset that are the same. This allows the network device to directly determine, based on the reported information, whether at least one predicted optimal reference signal resource in the entire first reference signal resource set (set A) is the same as at least one predicted optimal reference signal resource in the first subset (set M). This facilitates the network device to adjust the reference signal resources included in the reference signal resource set (i.e., the first subset) used to obtain the monitoring result, so that at least one predicted optimal reference signal resource in the first reference signal resource set (set A) is as similar as possible to at least one predicted optimal reference signal resource in the first subset, thereby improving the accuracy of the monitoring result.

[0224] Optionally, the first information is also used to indicate third indication information. That is, the first information is used to indicate the first monitoring result, the first indication information, and the third indication information. The third indication information is used to indicate reference signal resources in the k2 predicted optimal reference signal resources in the first reference signal resource set that do not belong to the k1 predicted optimal reference signal resources, where k2 is a positive integer.

[0225] In some embodiments, the first information used to indicate the first monitoring result, the first indication information, and the third indication information includes: the first information includes the first monitoring result, the first indication information, and the third indication information.

[0226] For example, the first information includes one or more fields, or the first information includes one or more domains, or the first information includes one or more information elements. For instance, when the first information includes one field (or one domain, or one information element), the first monitoring result, the first indication information, and the third indication information are jointly encoded and carried through that one field (or one domain, or one information element). When the first information includes multiple fields (or multiple domains, or multiple information elements), the first monitoring result is carried through one or more fields (or one or more domains, or one or more information elements), the first indication information is carried through one or more fields (or one or more domains, or one or more information elements), and the third indication information is carried through one or more fields (or one or more domains, or one or more information elements). Alternatively, when the first information includes multiple fields (or multiple domains, or multiple information elements), the first monitoring result and the first indication information are jointly encoded and carried through one or more fields (or one or more domains, or one or more information elements), and the third indication information is carried through one or more fields (or one or more domains, or one or more information elements). Alternatively, if the first information includes multiple fields (or multiple domains, or multiple information elements), the first monitoring result is carried by one or more fields (or one or more domains, or one or more information elements), and the first indication information and the third indication information are carried by one or more fields (or one or more domains, or one or more information elements) after being jointly encoded.

[0227] In some embodiments, the third indication information used to indicate reference signal resources among the k2 predicted optimal reference signal resources that do not belong to the k1 predicted optimal reference signal resources includes: the third indication information includes identification information of the reference signal resources among the k2 predicted optimal reference signal resources that do not belong to the k1 predicted optimal reference signal resources.

[0228] For example, when k2 equals k1, assume that the identification information of the four predicted optimal reference signal resources in the first reference signal resource set are: identification information 1, identification information 2, identification information 3, and identification information 4, and the identification information of the four predicted optimal reference signal resources in the first subset are: identification information 1, identification information 2, identification information 3, and identification information 5. The first indication information includes: identification information 1, identification information 2, identification information 3, and identification information 5. The third indication information includes identification information 4.

[0229] For example, when k2 is not equal to k1, assume that the identification information of the four predicted optimal reference signal resources in the first reference signal resource set are: identification information 1, identification information 2, identification information 3, and identification information 4, and the identification information of the three predicted optimal reference signal resources in the first subset are: identification information 1, identification information 2, and identification information 3. The first indication information includes: identification information 1, identification information 2, and identification information 3. The third indication information includes identification information 4.

[0230] In some embodiments, the third indication information is used to indicate k2 predicted optimal reference signal resources in the first set of reference signal resources. Exemplarily, the third indication information includes identification information of the k2 predicted optimal reference signal resources.

[0231] For example, the identification information of the reference signal resource in the third indication information is the identification information of the reference signal resource in the first reference signal resource set (set A). Alternatively, the identification information of the reference signal resource in the third indication information is the identification information of the reference signal resource in the third reference signal resource set. The third reference signal resource set is described in step 510.

[0232] In some embodiments, the terminal device determines the k1 predicted optimal reference signal resources and the k2 predicted optimal reference signal resources based on the first inference result, thereby determining the third indication information.

[0233] In some embodiments, the terminal device sends a sixth indication message to the network device, and correspondingly, the network device receives the sixth indication message from the terminal device. This sixth indication message is used to indicate the position of the third indication message within the first information and / or the position of the first indication message within the first information.

[0234] When the first information is used to indicate the first monitoring result, the first indication information, and the third indication information, the terminal device may also report to the network device, when reporting the first monitoring result and at least one predicted optimal reference signal resource in the first subset, that does not belong to the first subset. This facilitates the network device in determining, based on the reported information, whether at least one predicted optimal reference signal resource in the full set of the first reference signal resource set (set A) is the same as at least one predicted optimal reference signal resource in the first subset (set M). This allows the network device to adjust the reference signal resources included in the reference signal resource set (i.e., the first subset) used to obtain the monitoring result, so that at least one predicted optimal reference signal resource in the first reference signal resource set (set A) is as similar as possible to at least one predicted optimal reference signal resource in the first subset, thereby improving the accuracy of the monitoring result.

[0235] Optionally, after receiving the first information from the terminal device, the network device sends first configuration information to the terminal device. Correspondingly, the terminal device receives the first configuration information from the network device. This first configuration information is used to configure a second subset (set M') of the first set of reference signal resources. This second subset (set M') is different from at least one reference signal resource included in the first subset (set M).

[0236] In some embodiments, the network device determines whether a first preset condition is met. The first preset condition includes any one of the following: at least one of the k1 predicted optimal reference signal resources and the k2 predicted optimal reference signal resources is different; the number of reference signal resources in the k1 predicted optimal reference signal resources that are identical to those in the k2 predicted optimal reference signal resources is less than or equal to a fifth preset threshold; and the ratio of the number of reference signal resources in the k1 predicted optimal reference signal resources that are identical to those in the k2 predicted optimal reference signal resources to k2 is less than or equal to a sixth preset threshold. The specific values ​​of the fifth and sixth preset thresholds are not limited in the embodiments of this application.

[0237] In some embodiments, when a first preset condition is met, the network device sends first configuration information to the terminal device. Correspondingly, the terminal device receives the first configuration information from the network device.

[0238] In some embodiments, the network device determines a second subset based on a first set of reference signal resources and a first subset.

[0239] In some embodiments, the second subset (set M') does not include reference signal resources among the k1 predicted optimal reference signal resources that are not among the k2 predicted optimal reference signal resources. Alternatively, the number of reference signal resources in the second subset (set M') that are identical to those in the first subset (set M) is less than or equal to a first preset threshold. Alternatively, the ratio of the number of reference signal resources in the second subset (set M') that are identical to those in the first subset (set M) to a first value is less than or equal to a second preset threshold, where the first value includes any one of the following: the number of reference signal resources in the second subset (set M') and the number of reference signal resources in the first subset (set M). Alternatively, the second subset (set M') includes the k2 predicted optimal reference signal resources from the first set of reference signal resources. Alternatively, the number of reference signal resources in the second subset (set M') that belong to the k2 predicted optimal reference signal resources from the first set of reference signal resources is greater than or equal to a third preset threshold. Alternatively, the ratio of the number of reference signal resources in the second subset (set M') that belong to the k2 predicted optimal reference signal resources in the first reference signal resource set to the second value is greater than or equal to the fourth preset threshold. The second value includes any one of the following: the number of reference signal resources in the second subset (set M'), the number of reference signal resources in the first reference signal resource set, and k2. Here, k2 is a positive integer. The specific values ​​of the first, second, third, and fourth preset thresholds are not limited in the embodiments of this application.

[0240] In some embodiments, the network device determines a seventh preset threshold based on a first correspondence, wherein the seventh preset threshold is any one of a first preset threshold, a second preset threshold, a third preset threshold, and a fourth preset threshold. The first correspondence is used to indicate the correspondence between the numerical range of the number of reference signal resources (k1 predicted optimal reference signal resources that are identical to the number of reference signal resources (k2 predicted optimal reference signal resources)) and the seventh preset threshold. The embodiments of this application do not limit the specific form of the first correspondence; for example, it can be represented as a table, function, array, etc.

[0241] For example, the first correspondence is shown in Table 1.

[0242] Table 1 First Correspondence Relationship

[0243] As shown in Table 1, when the number of reference signal resources in the k1 predicted optimal reference signal resources that are identical to those in the k2 predicted optimal reference signal resources falls within value range 1, the network device determines the seventh preset threshold as c1 according to the correspondence in Table 1. Similarly, when the number of reference signal resources in the k1 predicted optimal reference signal resources that are identical to those in the k2 predicted optimal reference signal resources falls within value range 2, the network device determines the seventh preset threshold as c2 according to the correspondence in Table 1. When determining the seventh preset threshold according to the first correspondence shown in Table 1, if the seventh preset threshold is either the first preset threshold or the second preset threshold, the maximum value in value range 1 is less than the minimum value in value range 2, and c1 < c2. In other words, the fewer the number of reference signal resources in the k1 predicted optimal reference signal resources that are identical to those in the k2 predicted optimal reference signal resources, the smaller the value of the first preset threshold or the second preset threshold. When the seventh preset threshold is either the third or fourth preset threshold, the maximum value of the numerical range 1 is less than the minimum value of the numerical range 2, and c1 > c2. In other words, the fewer the number of reference signal resources that are the same as those in the k1 predicted optimal reference signal resources, the larger the value of the third or fourth preset threshold.

[0244] It should be understood that Table 1 is only one possible representation of the first correspondence, and the embodiments of this application do not limit the number of numerical ranges included in the first correspondence. The embodiments of this application do not limit the specific values ​​of numerical range 1, numerical range 2, c1, and c2.

[0245] In some embodiments, the network device determines a seventh preset threshold based on a second correspondence, whereby the seventh preset threshold is any one of a first preset threshold, a second preset threshold, a third preset threshold, and a fourth preset threshold. The second correspondence indicates the correspondence between the numerical range of the ratio of the number of reference signal resources (k1 predicted optimal reference signal resources) identical to the number of the k2 predicted optimal reference signal resources to k2 and the seventh preset threshold. The specific implementation is similar to that of determining the seventh preset threshold based on the first correspondence, and will not be repeated here. The embodiments of this application do not limit the specific form of the second correspondence; for example, it may be represented as a table, function, array, etc.

[0246] For example, when determining the seventh preset threshold based on the second correspondence, if the seventh preset threshold is a first preset threshold or a second preset threshold, the smaller the ratio of the number of reference signal resources that are identical to those in the k1 predicted optimal reference signal resources to k2 predicted optimal reference signal resources, the smaller the value of the first or second preset threshold. If the seventh preset threshold is a third or fourth preset threshold, the smaller the ratio of the number of reference signal resources that are identical to those in the k2 predicted optimal reference signal resources to k2 predicted optimal reference signal resources, the larger the value of the third or fourth preset threshold.

[0247] In some embodiments, after receiving the first configuration information, the terminal device performs measurements based on the second subset to determine the measured value of the channel state information corresponding to each reference signal resource in the second subset. The terminal device then uses the measured value of the channel state information corresponding to at least one reference signal resource in the second subset and the inference result of the AI ​​model to determine the monitoring result of the AI ​​model. The specific implementation is similar to the implementation of determining the first monitoring result based on the measured value of the channel state information corresponding to at least one reference signal resource in the first subset and the first inference result, and will not be described in detail here.

[0248] In the method shown in Figure 5, when the terminal device reports monitoring results to the network device, it also reports at least one predicted optimal reference signal resource from the first subset of the first reference signal resource set. This facilitates the network device in determining whether the entire first reference signal resource set and at least one predicted optimal reference signal resource in the first subset are the same. This allows the network device to adjust the reference signal resources included in the reference signal resource set (i.e., the first subset) used to obtain monitoring results, making the first reference signal resource set as similar as possible to the at least one predicted optimal reference signal resource used in the first subset. This improves the accuracy of the monitoring results obtained using the inference results of the AI ​​model. When the terminal device reports first and second indication information to the network device, or when the terminal device reports both first and third indication information, the network device can directly determine whether the first subset needs adjustment based on the information reported by the terminal device. This allows for the configuration of a more suitable second subset for the terminal device, facilitating the monitoring of the AI ​​model.

[0249] To improve the accuracy of monitoring results and enable monitoring of AI models, this application also provides a communication method, as shown in Figure 6.

[0250] Figure 6 is a schematic flowchart of a communication method provided in an embodiment of this application. The method in Figure 6 is applied to a communication system, such as the communication system shown in Figure 1, Figure 2, or Figure 3. The network device in Figure 6 is, for example, the network device 110 in Figure 1, the core network device in Figure 2, the access network node, or the access network node in Figure 3. The terminal device in Figure 6 is, for example, the terminal device in Figure 1, Figure 2, or Figure 3. The method in Figure 6 includes the following steps.

[0251] 610, determine the first monitoring result and the second instruction information.

[0252] The terminal device determines a first monitoring result and a second indication information. The first monitoring result is used to determine whether the first inference result is accurate or its accuracy. The first inference result is used to determine k1 predicted optimal reference signal resources in a first subset (set M) of the first reference signal resource set (set A) and k2 predicted optimal reference signal resources in the first reference signal resource set, where k1 and k2 are positive integers. The first inference result is determined using a first AI model. The first AI model, the first inference result, and the first monitoring result are described in step 510, and the second indication information is described in the above embodiment.

[0253] In some embodiments, when the first monitoring result includes identification information of a reference signal resource, the identification information of the reference signal resource is the identification information of the reference signal resource in the first subset (set M), or the identification information of the reference signal resource is the identification information of the reference signal resource in the first set of reference signal resources (set A), or the identification information of the reference signal resource is the identification information of the reference signal resource in the third set of reference signal resources. The third reference signal resource is described in step 510.

[0254] In the embodiments of this application, "identification information" and "index" have similar meanings and can be substituted for each other. "At least one measurement-determined optimal reference signal resource" and "x1 measurement-determined optimal reference signal resources, where x1 is a positive integer" have similar meanings and can be substituted for each other. "At least one prediction-determined optimal reference signal resource" and "x2 prediction-determined optimal reference signal resources, where x2 is a positive integer" have similar meanings and can be substituted for each other.

[0255] 620, send the second message to the network device.

[0256] The terminal device sends second information to the network device, and correspondingly, the network device receives the second information from the terminal device. This second information is used to indicate the first monitoring result and the second indication information.

[0257] In some embodiments, the second information used to indicate the first monitoring result and the second indication information includes: the second information includes the first monitoring result and the second indication information.

[0258] For example, the second information includes one or more fields, or the second information includes one or more domains, or the second information includes one or more information elements. For instance, when the second information includes one field (or one domain, or one information element), the first monitoring result and the second indication information, after joint encoding, are carried through that one field (or one domain, or one information element). When the second information includes multiple fields (or multiple domains, or multiple information elements), the first monitoring result is carried through one or more fields (or one or more domains, or one or more information elements), and the second indication information is carried through one or more fields (or one or more domains, or one or more information elements).

[0259] In some embodiments, when the first AI model is a regression model and the terminal device sends second information to the network device, the first monitoring result is determined based on the measured value of channel state information corresponding to at least one first reference signal resource in the first subset (set M) and the predicted value of channel state information corresponding to at least one second reference signal resource in the entire set of the first reference signal resource set (set A) or the first subset (set M). For example, the first monitoring result includes the measured value of channel state information corresponding to the at least one first reference signal resource and the predicted value of channel state information corresponding to the at least one second reference signal resource, or the first monitoring result includes a first accuracy determined based on the measured value of channel state information corresponding to the at least one first reference signal resource and the predicted value of channel state information corresponding to the at least one second reference signal resource. The first accuracy is used to indicate whether the first inference result is accurate, or the first accuracy is used to indicate the accuracy of the first inference result. The embodiments of this application do not limit the specific implementation of determining the first accuracy; for example, the calculation method of the first accuracy is described above.

[0260] In some embodiments, when the first AI model is a classification model and the terminal device sends second information to the network device, the first monitoring result is determined based on the best reference signal resource determined by at least one measurement in the first subset (set M) and the entire set of the first reference signal resource set (set A) or the best reference signal resource determined by at least one prediction in the first subset (set M). The first monitoring result includes identification information of the best reference signal resource determined by at least one measurement in the first subset and identification information of the entire set of the first reference signal resource set or the best reference signal resource determined by at least one prediction in the first subset; alternatively, the first monitoring result includes a second accuracy determined based on the best reference signal resource determined by at least one measurement in the first subset and the entire set of the first reference signal resource set or the best reference signal resource determined by at least one prediction in the first subset. This second accuracy is used to indicate whether the first inference result is accurate, or it is used to indicate the accuracy of the first inference result. The embodiments of this application do not limit the specific implementation of determining the second accuracy; for example, the calculation method of the second accuracy is described above.

[0261] In some embodiments, the terminal device sends fourth indication information to the network device, and correspondingly, the network device receives the fourth indication information from the terminal device. The fourth indication information is used to indicate k2 predicted optimal reference signal resources in the first set of reference signal resources, or the fourth indication information is used to indicate the k2 predicted optimal reference signal resources and the predicted value of the channel state information corresponding to each of the k2 predicted optimal reference signal resources.

[0262] For example, the fourth indication information includes the identification information of each of the k2 predicted optimal reference signal resources in the first reference signal resource set. Alternatively, the fourth indication information includes the predicted value and identification information of the channel state information corresponding to each of the k2 predicted optimal reference signal resources in the first reference signal resource set.

[0263] When the fourth indication information includes the predicted value and identification information of the channel state information corresponding to each of the k2 predicted optimal reference signal resources in the first reference signal resource set, the first monitoring result includes the measured value of the channel state information corresponding to at least one first reference signal resource in the first subset (set M). Alternatively, the first monitoring result is determined based on the measured value of the channel state information corresponding to at least one first reference signal resource in the first subset (set M) and the predicted value of the channel state information corresponding to at least one second reference signal resource in the entire first reference signal resource set (set A) or the first subset (set M).

[0264] When the fourth indication information includes the identification information of each reference signal resource among the k2 predicted optimal reference signal resources in the first reference signal resource set, the first monitoring result includes at least one measured optimal reference signal resource in the first subset (set M). Alternatively, the first monitoring result is determined based on at least one measured optimal reference signal resource in the first subset (set M) and the entire set of the first reference signal resource set (set A) or at least one predicted optimal reference signal resource in the first subset (set M).

[0265] Optionally, after receiving the second information from the terminal device, the network device sends the first configuration information to the terminal device. Correspondingly, the terminal device receives the first configuration information from the network device. This first configuration information is used to configure a second subset (set M') of the first set of reference signal resources. This second subset (set M') differs from at least one reference signal resource included in the first subset (set M). The first configuration information and the second subset are described above.

[0266] In some embodiments, the network device determines whether a first preset condition is met. The first preset condition is described above. If the first preset condition is met, the network device sends first configuration information to the terminal device.

[0267] In some embodiments, the network device determines a second subset based on a first set of reference signal resources and a first subset. See the description above for specific implementation details.

[0268] In some embodiments, after receiving the first configuration information, the terminal device performs measurements based on the second subset to determine the measured value of the channel state information corresponding to each reference signal resource in the second subset. The terminal device then uses the measured value of the channel state information corresponding to at least one reference signal resource in the second subset and the inference result of the AI ​​model to determine the monitoring result of the AI ​​model. For specific implementation details, please refer to the description above.

[0269] In the method shown in Figure 6, when the terminal device reports the monitoring results to the network device, it also reports to the network device whether at least one predicted optimal reference signal resource in the entire set of the first reference signal resource set (set A) is the same as at least one predicted optimal reference signal resource in the first subset (set M). This helps the network device determine whether it is necessary to adjust the reference signal resources included in the reference signal resource set (i.e., the first subset) used to obtain the monitoring results, so that at least one predicted optimal reference signal resource in the first reference signal resource set (set A) is as similar as possible to at least one predicted optimal reference signal resource in the first subset, thereby improving the accuracy of the monitoring results.

[0270] For example, when the AI ​​model is deployed in a terminal device, one implementation of the method in Figure 5 or Figure 6 is shown in Figure 7. Figure 7 is a schematic flowchart of the communication method provided in an embodiment of this application. The method in Figure 7 is applied to a communication system, such as the communication system shown in Figure 1, Figure 2, or Figure 3. The network device in Figure 7 is, for example, the network device 110 in Figure 1, the core network device in Figure 2, the access network node, or the access network node in Figure 3. The terminal device in Figure 7 is, for example, the terminal device in Figure 1, Figure 2, or Figure 3. The method in Figure 7 includes the following steps.

[0271] 701, Determine the first subset of the first reference signal resource set.

[0272] The network device determines a first subset (set M) of a first set of reference signal resources (set A). This first set of reference signal resources includes at least one reference signal resource. The first set of reference signal resources and the first subset are described in Figure 5.

[0273] For example, the network device randomly determines a first subset from the first set of reference signal resources. Alternatively, it determines a default subset, such as a subset predefined by the protocol, as the first subset. Or, the network device determines the first subset based on a third subset (set M”) of the first set of reference signal resources determined before step 701. The method of determining the first subset based on the third subset is similar to the method of determining the second subset based on the first subset in step 709, and will not be described in detail here.

[0274] 702, Send third configuration information to the terminal device.

[0275] The network device sends third configuration information to the terminal device, and correspondingly, the terminal device receives the third configuration information from the network device. This third configuration information is used to configure the first subset (set M).

[0276] Optionally, the terminal device performs measurements based on the first subset to obtain the measured values ​​of channel state information corresponding to each reference signal resource in the first subset.

[0277] For example, the channel state information corresponding to the reference signal resource can be replaced with the RSRP, RSRQ, SINR, received power, or received quality corresponding to the reference signal resource.

[0278] 703, Send the second configuration information to the terminal device.

[0279] The network device sends second configuration information to the terminal device, and correspondingly, the terminal device receives the second configuration information from the network device. This second configuration information is used to configure a second reference signal resource set (set B). This second reference signal resource set includes at least one reference signal resource. The second reference signal resource set is described in Figure 5.

[0280] Optionally, the terminal device performs measurements based on the second set of reference signal resources to obtain the measured value of the channel state information corresponding to each reference signal resource in the second set of reference signal resources.

[0281] Optionally, step 703 may be performed after step 701 or step 702. Alternatively, step 703 may be performed before step 701 or step 702.

[0282] 704. Using the measured values ​​of the channel state information corresponding to each reference signal resource in the second reference signal resource set and the first AI model, the first inference result is obtained.

[0283] The terminal device determines the first input data based on the measured value of the channel state information corresponding to each reference signal resource in the second reference signal resource set, and inputs the first input data into the first AI model to obtain the first inference result. The first input data, the first AI model, and the first inference result are described in step 510.

[0284] 705, Send the seventh instruction message to the network device.

[0285] The terminal device sends a seventh instruction message to the network device, and the network device receives the seventh instruction message from the terminal device.

[0286] When the first AI model is a regression model, the seventh indication information is used to indicate the predicted value of the channel state information corresponding to some or all of the reference signal resources in the entire set or the first subset of the first reference signal resource set, and / or the identification information of some or all of the reference signal resources. When the seventh indication information is used to indicate the predicted value of the channel state information corresponding to some of the reference signal resources in the entire set or the subset of the first reference signal resource set, and / or the identification information of that portion of the reference signal resources, that portion of the reference signal resources is at least one predicted optimal reference signal resource in the entire set or the subset of the first reference signal resource set. The description of at least one predicted optimal reference signal resource in the entire set or the subset of the first reference signal resource set is provided in step 510.

[0287] When the first AI model is a classification model, the seventh indication information is used to indicate the identification information of at least one predicted optimal reference signal resource in the entire set or the first subset of the first reference signal resource set. The description of at least one predicted optimal reference signal resource in the entire set or the first subset of the first reference signal resource set is provided in step 510.

[0288] Optionally, steps 701-703 and 705 are optional steps and can be performed or not.

[0289] 706, First monitoring result obtained.

[0290] The terminal device determines a first monitoring result using measured values ​​of channel state information corresponding to at least one reference signal resource in the first subset. Alternatively, the terminal device determines a first monitoring result using measured values ​​of channel state information corresponding to at least one reference signal resource in the first subset and a first inference result. This first monitoring result is described in step 510.

[0291] 707. Based on the first reasoning result, determine the first instruction information and / or the second instruction information.

[0292] Based on the first inference result, the terminal device determines k1 predicted optimal reference signal resources in a first subset of the first reference signal resource set, thereby determining first indication information. k1 is a positive integer. The k1 predicted optimal reference signal resources and the first indication information are described in step 510. And / or, based on the first inference result, the terminal device determines the k1 predicted optimal reference signal resources and k2 predicted optimal reference signal resources in the first reference signal resource set, thereby determining second indication information. The k2 predicted optimal reference signal resources and the second indication information are described in Figure 5.

[0293] 708, sends the first or second message to the network device.

[0294] Optionally, the terminal device sends first information to the network device, and correspondingly, the network device receives the first information from the terminal device. This first information is used to indicate a first monitoring result and a first indication. The implementation of step 708 is similar to that of step 520, and will not be described again here. The first information is described in Figure 5.

[0295] Optionally, the terminal device sends second information to the network device, and correspondingly, the network device receives the second information from the terminal device. This second information is used to indicate the first monitoring result and the second indication information. The implementation of step 708 is similar to that of step 620, and will not be described again here. The second information is described in Figure 6.

[0296] Optionally, if the first AI model is a regression model and the first monitoring result includes the measured value of the channel state information corresponding to at least one reference signal resource in the first subset (set M), the network device determines the first accuracy based on the measured value of the channel state information corresponding to at least one first reference signal resource in the first subset and the predicted value of the channel state information corresponding to the entire set of the first reference signal resource set (set A) or at least one second reference signal resource in the first subset (set M). For specific implementation, please refer to the description in step 510.

[0297] Optionally, if the first AI model is a classification model and the first monitoring result includes the identification information of at least one optimal reference signal resource determined by measurement in the first subset (set M), the network device determines the second accuracy based on at least one optimal reference signal resource determined by measurement in the first subset (set M) and the entire set of the first reference signal resource set (set A) or at least one optimal reference signal resource determined by prediction in the first subset (set M). For specific implementation, please refer to the description in step 510.

[0298] Optionally, after receiving the first information or the second information, the network device determines whether a first preset condition is met. The first preset condition includes any one of the following: at least one of the k1 predicted optimal reference signal resources and the k2 predicted optimal reference signal resources is different; the number of reference signal resources in the k1 predicted optimal reference signal resources that are identical to those in the k2 predicted optimal reference signal resources is less than or equal to a fifth preset threshold; and the ratio of the number of reference signal resources in the k1 predicted optimal reference signal resources that are identical to those in the k2 predicted optimal reference signal resources to k2 is less than or equal to a sixth preset threshold. The specific values ​​of the fifth and sixth preset thresholds are not limited in this embodiment.

[0299] Optionally, if the first preset condition is met, the network device executes steps 709 and 710. If the first preset condition is not met, the network device does not need to execute steps 709 and 710.

[0300] 709, determine the second subset of the first reference signal resource set.

[0301] The network device determines a second subset (set M') of the first reference signal resource set based on the first reference signal resource set and the first subset. This second subset (set M') is different from at least one reference signal resource included in the first subset (set M).

[0302] In some embodiments, the second subset (set M') does not include reference signal resources among the k1 predicted optimal reference signal resources that are not among the k2 predicted optimal reference signal resources. Alternatively, the number of reference signal resources in the second subset (set M') that are identical to those in the first subset (set M) is less than or equal to a first preset threshold. Alternatively, the ratio of the number of reference signal resources in the second subset (set M') that are identical to those in the first subset (set M) to a first value is less than or equal to a second preset threshold, where the first value includes any one of the following: the number of reference signal resources in the second subset (set M') and the number of reference signal resources in the first subset (set M). Alternatively, the second subset (set M') includes the k2 predicted optimal reference signal resources from the first set of reference signal resources. Alternatively, the number of reference signal resources in the second subset (set M') that belong to the k2 predicted optimal reference signal resources from the first set of reference signal resources is greater than or equal to a third preset threshold. Alternatively, the ratio of the number of reference signal resources in the second subset (set M') that belong to the k2 predicted optimal reference signal resources in the first reference signal resource set to the second value is greater than or equal to the fourth preset threshold. The second value includes any one of the following: the number of reference signal resources in the second subset (set M'), the number of reference signal resources in the first reference signal resource set, and k2. Here, k2 is a positive integer. The specific values ​​of the first, second, third, and fourth preset thresholds are not limited in the embodiments of this application.

[0303] For example, the network device determines any one of the first preset threshold, the second preset threshold, the third preset threshold, and the fourth preset threshold according to the first correspondence or the second correspondence. For specific implementation, please refer to the description in Figure 5.

[0304] 710, Send the first configuration information to the terminal device.

[0305] The network device sends first configuration information to the terminal device. Correspondingly, the terminal device receives the first configuration information from the network device. This first configuration information is used to configure a second subset (set M') of the first reference signal resource set.

[0306] Optionally, the terminal device performs measurements based on the second subset to determine the measured value of the channel state information corresponding to each reference signal resource in the second subset. The terminal device then uses the measured value of the channel state information corresponding to at least one reference signal resource in the second subset and the inference result of the AI ​​model to determine the monitoring result of the AI ​​model. The specific implementation is similar to step 706 and will not be repeated here.

[0307] In the method shown in Figure 7, when the first AI model is deployed in the terminal device, the terminal device uses the measurement value corresponding to each reference signal resource in the second reference signal resource set to determine the first inference result of the first AI model, thereby determining the first information. Furthermore, when the terminal device reports the monitoring result to the network device, it also reports the first indication information and / or the second indication information. This facilitates the network device in determining whether the entire set of the first reference signal resource set and at least one predicted optimal reference signal resource in the first subset are the same. This allows the network device to adjust the reference signal resources included in the reference signal resource set (i.e., the first subset) used to obtain the monitoring result, making the first reference signal resource set as similar as possible to at least one predicted optimal reference signal resource in the first subset, thereby improving the accuracy of the monitoring result obtained using the inference result of the AI ​​model.

[0308] For example, when the AI ​​model is deployed in an inference device, step 704 in Figure 7 can be replaced by steps 801-803 in Figure 8. That is, the method in Figure 8 includes steps 801-803 and steps 701-703, 705-710 in Figure 7. In other words, when the AI ​​model is deployed in an inference device, one implementation of the method in Figure 5 or Figure 6 is shown in Figure 8. The inference device is a device that deploys the first AI model, such as a device connected to a terminal device or a server. The method in Figure 8 is applied to a communication system, such as the communication system shown in Figure 1, Figure 2, or Figure 3. The network device in Figure 8 is, for example, network device 110 in Figure 1, core network device in Figure 2, access network node, or access network node in Figure 3. The terminal device in Figure 8 is, for example, the terminal device in Figure 1, Figure 2, or Figure 3. The inference device in Figure 8 is, for example, an AI entity serving the terminal device side, such as a server, such as an OTT server or a cloud server. Steps 701-703 and 705-710 in Figure 8 are similar to the corresponding steps in Figure 7, and will not be repeated here.

[0309] 801, Send the eighth instruction message to the inference device.

[0310] The terminal device sends an eighth indication message to the inference device, and correspondingly, the inference device sends an eighth indication message to the terminal device. This eighth indication message is used to indicate the first input data. The first input data is described in step 704.

[0311] Optionally, step 801 is performed after step 703.

[0312] 802. Using the first input data and the first AI model, obtain the first inference result.

[0313] In some embodiments, the inference device inputs the received first input data into a first AI model to obtain a first inference result.

[0314] In some embodiments, when the first input data includes the measured value of channel state information corresponding to each reference signal resource in the second reference signal resource set, the inference device processes the measured value of channel state information corresponding to each reference signal resource in the second reference signal resource set to obtain processed data, and inputs the processed data into the first AI model to obtain a first inference result.

[0315] For example, processing the measured values ​​of channel state information corresponding to each reference signal resource in the second reference signal resource set includes: normalizing the measured values ​​of channel state information corresponding to each reference signal resource in the second reference signal resource set, or filtering the measured values ​​of channel state information corresponding to each reference signal resource in the second reference signal resource set. Filtering the measured values ​​of channel state information corresponding to each reference signal resource in the second reference signal resource set includes, for example, removing one or more smaller measured values ​​from the measured values ​​of channel state information corresponding to each reference signal resource in the second reference signal resource set.

[0316] 803, send the ninth instruction message to the terminal device.

[0317] The inference device sends a ninth indication message to the terminal device, and correspondingly, the terminal device receives the ninth indication message from the inference device. This ninth indication message is used to indicate a first inference result, which is described in step 510.

[0318] Optionally, step 705 or 706 can be performed after step 803.

[0319] In the method shown in Figure 8, when the first AI model is deployed in the inference device, the inference device uses the first AI model to determine a first inference result and sends it to the terminal device, thereby enabling the terminal device to determine the first indication information. Furthermore, when the terminal device reports the monitoring result to the network device, it also reports the first indication information and / or the second indication information. This facilitates the network device in determining whether the entire set of the first reference signal resource set and at least one predicted optimal reference signal resource in the first subset are the same. This allows the network device to adjust the reference signal resources included in the reference signal resource set (i.e., the first subset) used to obtain the monitoring result, making the first reference signal resource set as similar as possible to at least one predicted optimal reference signal resource in the first subset, thereby improving the accuracy of the monitoring result obtained using the inference result of the AI ​​model.

[0320] Figures 9 and 10 are schematic diagrams of possible communication devices provided in the embodiments of this application. These communication devices can be used to implement the functions of terminal devices or network devices in the above method embodiments, and thus can also achieve the beneficial effects of the above method embodiments. In the embodiments of this application, the communication device may be the network device 110 shown in Figure 1, the core network device in Figure 2, the access network node, the access network node in Figure 3, the network devices in Figures 5 to 8, or the terminal devices shown in Figures 1 to 8.

[0321] As shown in Figure 9, the communication device 900 includes a processing unit 910 and a transceiver unit 920. The communication device 900 is used to implement the functions of the network device, terminal device, or inference device in the method embodiments shown in Figures 5 to 8 above.

[0322] When the communication device 900 is used to implement the functions of the terminal device in the method embodiment shown in FIG5: the processing unit 910 is used to determine the first monitoring result and the first indication information, and the processing unit 910 is used to execute step 510 in FIG5. The transceiver unit 920 is used to send the first information, and the transceiver unit 920 is used to indicate step 520 in FIG5.

[0323] When the communication device 900 is used to implement the function of the network device in the method embodiment shown in FIG5: the transceiver unit 920 is used to receive first information. The transceiver unit 920 is used to instruct step 520 in FIG5.

[0324] When the communication device 900 is used to implement the functions of the terminal device in the method embodiment shown in FIG6: the processing unit 910 is used to determine the first monitoring result and the second indication information, and the processing unit 910 is used to execute step 610 in FIG6. The transceiver unit 920 is used to send the second information, and the transceiver unit 920 is used to indicate step 620 in FIG6.

[0325] When the communication device 900 is used to implement the function of the network device in the method embodiment shown in FIG6: the transceiver unit 920 is used to receive second information. The transceiver unit 920 is used to instruct step 620 in FIG6.

[0326] When the communication device 900 is used to implement the functions of the terminal device in the method embodiment shown in FIG7: the processing unit 910 is used to: obtain a first inference result using the measured value of the channel state information corresponding to each reference signal resource in the second reference signal resource set and the first AI model; obtain a first monitoring result; and determine first indication information and / or second indication information based on the first inference result. The processing unit 910 is used to execute steps 704, 706, and 707 in FIG7. The transceiver unit 920 is used to send the first information or the second information to the network device. The transceiver unit 920 is used to execute step 708 in FIG7.

[0327] In some embodiments, when the communication device 900 is used to implement the functions of the terminal device in the method embodiment shown in FIG7, the transceiver unit 920 is used to: receive third configuration information; receive second configuration information; send seventh indication information to the network device; and receive first configuration information. The transceiver unit 920 is used to perform at least one of steps 702, 703, 705, and 710 in FIG7.

[0328] When the communication device 900 is used to implement the functions of the network device in the method embodiment shown in FIG7: the transceiver unit 920 is used to receive first information or second information. The transceiver unit 920 is used to execute step 708 in FIG7.

[0329] In some embodiments, when the communication device 900 is used to implement the functions of the network device in the method embodiment shown in FIG7: the processing unit 910 is used to: determine a first subset of the first reference signal resource set; determine a second subset of the first reference signal resource set. The processing unit 910 is used to execute steps 701 or 709 in FIG7.

[0330] In some embodiments, when the communication device 900 is used to implement the functions of the network device in the method embodiment shown in FIG7: the transceiver unit 920 is used to: send third configuration information to the terminal device; send second configuration information to the terminal device; receive seventh indication information; and send first configuration information to the terminal device. The transceiver unit 920 is used to perform at least one of steps 702, 703, 705, and 710 in FIG7.

[0331] When the communication device 900 is used to implement the functions of the terminal device in the method embodiment shown in FIG8: the processing unit 910 is used to: obtain a first monitoring result; determine a first indication information and / or a second indication information based on the first inference result. The processing unit 910 is used to execute steps 706 and 707 in FIG8. The transceiver unit 920 is used to: send an eighth indication information to the inference device; receive a ninth indication information; and send a first information or a second information to the network device. The transceiver unit 920 is used to execute steps 801, 803, and 708 in FIG8.

[0332] In some embodiments, when the communication device 900 is used to implement the functions of the terminal device in the method embodiment shown in FIG8: the transceiver unit 920 is further used to perform at least one of steps 702, 703, 705, and 710 in FIG8.

[0333] When the communication device 900 is used to implement the function of the network device in the method embodiment shown in FIG8: the steps performed by the processing unit 910 are similar to the steps performed by the communication device 900 when it is used to implement the function of the network device in the method embodiment shown in FIG7, and will not be described again here. The steps performed by the transceiver unit 920 are similar to the steps performed by the communication device 900 when it is used to implement the function of the network device in the method embodiment shown in FIG7, and will not be described again here.

[0334] When the communication device 900 is used to implement the function of the inference device in the method embodiment shown in FIG8: the processing unit 910 is used to obtain a first inference result using the first input data and the first AI model. The processing unit 910 is used to execute step 802 in FIG8. The transceiver unit 920 is used to: receive the eighth instruction information; and send the ninth instruction information to the terminal device. The transceiver unit 920 is used to execute steps 801 and 802 in FIG8.

[0335] For a more detailed description of the processing unit 910 and the transceiver unit 920, please refer to the relevant descriptions in the method embodiments shown in Figures 5 to 8.

[0336] As shown in Figure 10, the communication device 1000 includes a processing circuit 1010. Further, the communication device 1000 may also include the processing circuit 1010 and a communication circuit 1020. The processing circuit 1010 and the communication circuit 1020 are coupled to each other. The processing circuit may be one or more processors, or all or part of the circuitry within one or more processors used for control or processing functions. It is understood that when the communication device 1000 is a network device or a terminal device, the communication circuit 1020 may be a transceiver circuit, transceiver, communication interface, or input / output interface. When the communication device 1000 is a chip for a network device or a terminal device, the communication circuit 1020 may be an input / output interface, communication interface, or input / output circuit. Optionally, the communication device 1000 may also include a memory 1030 for storing instructions executed by the processor 1010, or storing input data required by the processor 1010 to execute instructions, or storing data generated after the processor 1010 executes instructions.

[0337] When the communication device 1000 is used to implement the method shown in Figures 5 to 8, the processing circuit 1010 is used to implement the function of the processing unit, and the communication circuit 1020 is used to implement the function of the receiving unit and / or the transmitting unit.

[0338] When the aforementioned communication device is a chip applied to a terminal, the terminal chip implements the functions of the terminal in the above method embodiments. The terminal chip receives information from other modules (such as radio frequency modules or antennas) in the terminal, which is information sent to the terminal by the base station; or, the terminal chip sends information to other modules (such as radio frequency modules or antennas) in the terminal, which is information sent to the base station by the terminal.

[0339] When the aforementioned communication device is a chip applied to an inference device, the chip implements the functions of the inference device in the above method embodiments. The chip receives information from other modules (such as radio frequency modules or antennas) in the inference device, which is sent by the terminal to the inference device; or, the chip sends information to other modules (such as radio frequency modules or antennas) in the inference device, which is sent by the inference device to the terminal.

[0340] When the aforementioned communication device is a module applied to a base station (or network equipment), the base station module implements the functions of the base station in the above method embodiments. The base station module receives information from other modules (such as radio frequency modules or antennas) in the base station, information sent by the terminal to the base station; or, the base station module sends information to other modules (such as radio frequency modules or antennas) in the base station, information sent by the base station to the terminal. Here, the base station module can be the baseband chip of the base station, or a DU (Digital Unit) or other modules. The DU can be a DU under an Open Radio Access Network (O-RAN) architecture.

[0341] It is understood that the processor in the embodiments of this application 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), graphics processing units, neural processing units, 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.

[0342] The method steps in the embodiments of this application can be implemented in hardware or in software instructions executable by a processor. The software instructions can consist of corresponding software modules, which can be stored in random access memory, flash memory, read-only memory, programmable read-only memory, erasable programmable read-only memory, electrically erasable programmable read-only memory, registers, hard disks, portable hard disks, compact disc read-only memory (CD-ROM), or any other form of storage medium well known in the art. An exemplary storage medium is coupled to a processor, enabling the processor to read information from and write information to the storage medium. The storage medium can also be a component of the processor. The processor and storage medium can reside in an ASIC. Alternatively, the ASIC can reside in a base station or terminal. The processor and storage medium can also exist as discrete components in the base station or terminal.

[0343] This application also provides a communication system, which includes the network device and terminal device described in the embodiments of this application. Alternatively, the communication system includes the network device, terminal device, and inference device described in the embodiments of this application.

[0344] This application also provides a computer-readable storage medium. The computer-readable storage medium can be any available medium that a computing device can store, or a data storage device such as a data center containing one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., digital video disc (DVD)), or a semiconductor medium (e.g., a solid-state drive). The computer-readable storage medium includes instructions or program code that, when executed on a computing device, cause the computing device to perform the methods provided above.

[0345] This application also provides a computer program product, which may be a software or program product containing instructions capable of running on a computing device or stored on any usable medium. When the instructions are executed on the computing device, the computing device performs the methods provided above, or enables the computing device to perform the functions of the apparatus provided above.

[0346] This application also provides a chip including at least one processor, which, when program instructions are executed by the at least one processor, causes the at least one processor to perform the methods provided above.

[0347] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented 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.

[0348] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0349] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0350] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0351] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0352] If the aforementioned functions 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 a portion 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.) to execute all or part of the steps of the methods described in 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.

[0353] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A communication method, characterized in that, include: A first monitoring result and a first indication information are determined. The first monitoring result is used to determine whether the first inference result is accurate or the accuracy of the first inference result. The first inference result is used to determine k1 predicted optimal reference signal resources in a first subset (set M) of a first reference signal resource set (set A). The first indication information is used to indicate the k1 predicted optimal reference signal resources. The first reference signal resource set includes at least one reference signal resource, and k1 is a positive integer. Send a first message, which is used to indicate the first monitoring result and the first indication information.

2. The method according to claim 1, characterized in that, The first information is also used to indicate second indication information, which is used to indicate information about the same reference signal resources among the k1 predicted optimal reference signal resources and the k2 predicted optimal reference signal resources in the first set of reference signal resources, where k2 is a positive integer.

3. The method according to claim 2, characterized in that, The information of the k1 predicted optimal reference signal resources and the k2 predicted optimal reference signal resources in the first set of reference signal resources that are the same includes one or more of the following: Does each of the k1 predicted optimal reference signal resources belong to the k2 predicted optimal reference signal resources? The number of reference signal resources that are the same among the k1 predicted optimal reference signal resources and the k2 predicted optimal reference signal resources; or, The ratio of the number of reference signal resources that are the same as those in the k1 predicted optimal reference signal resources to the k2 predicted optimal reference signal resources, to k2.

4. The method according to claim 1, characterized in that, The first information is also used to indicate third indication information, which is used to indicate reference signal resources among the k2 predicted optimal reference signal resources in the first reference signal resource set that do not belong to the k1 predicted optimal reference signal resources, where k2 is a positive integer.

5. The method according to any one of claims 1 to 4, characterized in that, The first indication information includes the identification information of the k1 predicted optimal reference signal resources in the first subset (set M).

6. The method according to any one of claims 1 to 5, characterized in that, The method further includes: Receive first configuration information, the first configuration information being used to configure a second subset (set M') of the first set of reference signal resources, the second subset (set M') being different from at least one reference signal resource included in the first subset (set M).

7. The method according to claim 6, characterized in that, The second subset (set M') does not include reference signal resources among the k1 predicted optimal reference signal resources that do not belong to the k2 predicted optimal reference signal resources in the first reference signal resource set, or; The number of reference signal resources that are identical in the second subset (set M') and the first subset (set M) is less than or equal to a first preset threshold; or, The ratio of the number of identical reference signal resources in the second subset (set M') and the first subset (set M) to a first value is less than or equal to a second preset threshold, where the first value includes any one of the following: the number of reference signal resources in the second subset (set M') and the number of reference signal resources in the first subset (set M); or, The second subset (set M') includes k2 predicted optimal reference signal resources from the first reference signal resource set; or, The number of reference signal resources in the second subset (set M') that belong to the k2 predicted optimal reference signal resources in the first reference signal resource set is greater than or equal to a third preset threshold; or, The ratio of the number of reference signal resources in the second subset (set M') that belong to the k2 predicted best reference signal resources in the first reference signal resource set to the second value is greater than or equal to the fourth preset threshold, where the second value includes any one of the following: the number of reference signal resources in the second subset (set M'), the number of reference signal resources in the first reference signal resource set, and k2; Where k2 is a positive integer.

8. The method according to any one of claims 1 to 7, characterized in that, The predicted values ​​of the channel state information corresponding to the k1 predicted optimal reference signal resources are greater than or equal to the predicted values ​​of the channel state information corresponding to the reference signal resources in the first subset (set M) excluding the k1 predicted optimal reference signal resources; or, The probability corresponding to the k1 predicted optimal reference signal resources is greater than or equal to the probability corresponding to the reference signal resources in the first subset (set M) excluding the k1 predicted optimal reference signal resources, where the probability corresponding to the reference signal resource is the probability that the reference signal resource is the optimal reference signal resource in the first reference signal resource set (set A) or the first subset (set M); or, The k1 predicted optimal reference signal resources are the reference signal resources in the first subset (set M) that belong to the k2 predicted optimal reference signal resources in the first reference signal resource set. The predicted value of the channel state information corresponding to the k2 predicted optimal reference signal resources is greater than or equal to the predicted value of the channel state information corresponding to the reference signal resources in the first reference signal resource set (set A) other than the k2 predicted optimal reference signal resources. Alternatively, the probability corresponding to the k2 predicted optimal reference signal resources is greater than or equal to the probability corresponding to the reference signal resources in the first reference signal resource set (set A) other than the k2 predicted optimal reference signal resources. The probability corresponding to the reference signal resources is the probability that the reference signal resources are the best reference signal resources in the first reference signal resource set (set A). k2 is a positive integer.

9. The method according to any one of claims 1 to 6, characterized in that, The first inference result includes the predicted value of the channel state information corresponding to each reference signal resource in the first reference signal resource set (set A). The first monitoring result is determined based on the measured value of the channel state information corresponding to at least one first reference signal resource in the first subset (set M) and the predicted value of the channel state information corresponding to the entire first reference signal resource set (set A) or at least one second reference signal resource in the first subset (set M); or, the first monitoring result includes the measured value of the channel state information corresponding to at least one reference signal resource in the first subset (set M); or, The first inference result includes the probability that each reference signal resource in the first reference signal resource set (set A) is the best reference signal resource in the first reference signal resource set (set A). The first monitoring result is determined based on the best reference signal resource determined by at least one measurement in the first subset (set M) and the entire set of the first reference signal resource set (set A) or the best reference signal resource determined by at least one prediction in the first subset (set M). Alternatively, the first monitoring result includes the identification information of at least one best reference signal resource determined by at least one measurement in the first subset (set M), wherein the measured value of the channel state information corresponding to the at least one best reference signal resource determined by at least one measurement is greater than or equal to the measured value of the channel state information corresponding to the reference signal resources in the first subset (set M) other than the at least one best reference signal resource determined by at least one measurement.

10. The method according to any one of claims 1 to 9, characterized in that, The method further includes: Determine the measured value of the channel state information corresponding to each reference signal resource in the second reference signal resource set (set B), wherein the second reference signal resource set includes at least one reference signal resource; The first inference result is determined by using the measured values ​​of the channel state information corresponding to each reference signal resource in the second set of reference signal resources.

11. A communication method, characterized in that, include: The system receives first information, which is used to indicate a first monitoring result and a first indication information. The first monitoring result is used to determine whether the first inference result is accurate or the accuracy of the first inference result. The first inference result is used to determine the k1 predicted optimal reference signal resources in the first subset (set M) of the first reference signal resource set (set A). The first indication information is used to indicate the k1 predicted optimal reference signal resources. The first reference signal resource set includes at least one reference signal resource, and k1 is a positive integer.

12. The method according to claim 11, characterized in that, The first information is also used to indicate second indication information, which is used to indicate information about the same reference signal resources among the k1 predicted optimal reference signal resources and the k2 predicted optimal reference signal resources in the first set of reference signal resources, where k2 is a positive integer.

13. The method according to claim 12, characterized in that, The information of the k1 predicted optimal reference signal resources and the k2 predicted optimal reference signal resources in the first set of reference signal resources that are the same includes one or more of the following: Does each of the k1 predicted optimal reference signal resources belong to the k2 predicted optimal reference signal resources? The number of reference signal resources that are the same among the k1 predicted optimal reference signal resources and the k2 predicted optimal reference signal resources; or, The ratio of the number of reference signal resources that are the same as those in the k1 predicted optimal reference signal resources to the k2 predicted optimal reference signal resources, to k2.

14. The method according to claim 11, characterized in that, The first information is also used to indicate third indication information, which is used to indicate reference signal resources among the k2 predicted optimal reference signal resources in the first reference signal resource set that do not belong to the k1 predicted optimal reference signal resources, where k2 is a positive integer.

15. The method according to any one of claims 11 to 14, characterized in that, The first indication information includes the identification information of the k1 predicted optimal reference signal resources in the first subset (set M).

16. The method according to any one of claims 11 to 15, characterized in that, The method further includes: If a first preset condition is met, first configuration information is sent. The first configuration information is used to configure a second subset (set M') of the first reference signal resource set. The second subset (set M') is different from at least one reference signal resource included in the first subset (set M). The first preset condition includes any one of the following: The k1 predicted optimal reference signal resources are different from at least one of the k2 predicted optimal reference signal resources in the first set of reference signal resources; or... The number of reference signal resources among the k1 predicted optimal reference signal resources that are identical to the k2 predicted optimal reference signal resources in the first set of reference signal resources is less than or equal to a fifth preset threshold; or, The ratio of the number of reference signal resources in the k1 predicted optimal reference signal resources that are the same as the k2 predicted optimal reference signal resources in the first reference signal resource set to k2 is less than or equal to a sixth preset threshold. Where k2 is a positive integer.

17. The method according to claim 16, characterized in that, The second subset (set M') does not include reference signal resources among the k1 predicted optimal reference signal resources that do not belong to the k2 predicted optimal reference signal resources, or; The number of reference signal resources that are identical in the second subset (set M') and the first subset (set M) is less than or equal to a first preset threshold; or, The ratio of the number of identical reference signal resources in the second subset (set M') and the first subset (set M) to a first value is less than or equal to a second preset threshold, where the first value includes any one of the following: the number of reference signal resources in the second subset (set M') and the number of reference signal resources in the first subset (set M); or, The second subset (set M') includes k2 predicted optimal reference signal resources from the first reference signal resource set; or, The number of reference signal resources in the second subset (set M') that belong to the k2 predicted optimal reference signal resources in the first reference signal resource set is greater than or equal to a third preset threshold; or, The ratio of the number of reference signal resources in the second subset (set M') that belong to the k2 predicted best reference signal resources in the first reference signal resource set to the second value is greater than or equal to the fourth preset threshold, where the second value includes any one of the following: the number of reference signal resources in the second subset (set M'), the number of reference signal resources in the first reference signal resource set, and k2; Where k2 is a positive integer.

18. The method according to any one of claims 11 to 17, characterized in that, The predicted values ​​of the channel state information corresponding to the k1 predicted optimal reference signal resources are greater than or equal to the predicted values ​​of the channel state information corresponding to the reference signal resources in the first subset (set M) excluding the k1 predicted optimal reference signal resources; or, The probability corresponding to the k1 predicted optimal reference signal resources is greater than or equal to the probability corresponding to the reference signal resources in the first subset (set M) excluding the k1 predicted optimal reference signal resources, where the probability corresponding to the reference signal resource is the probability that the reference signal resource is the optimal reference signal resource in the first reference signal resource set (set A) or the first subset (set M); or, The k1 predicted optimal reference signal resources are the reference signal resources in the first subset (set M) that belong to the k2 predicted optimal reference signal resources in the first reference signal resource set. The predicted value of the channel state information corresponding to the k2 predicted optimal reference signal resources is greater than or equal to the predicted value of the channel state information corresponding to the reference signal resources in the first reference signal resource set (set A) other than the k2 predicted optimal reference signal resources. Alternatively, the probability corresponding to the k2 predicted optimal reference signal resources is greater than or equal to the probability corresponding to the reference signal resources in the first reference signal resource set (set A) other than the k2 predicted optimal reference signal resources. The probability corresponding to the reference signal resources is the probability that the reference signal resources are the best reference signal resources in the first reference signal resource set (set A). k2 is a positive integer.

19. The method according to any one of claims 11 to 18, characterized in that, The first inference result includes the predicted value of the channel state information corresponding to each reference signal resource in the first reference signal resource set (set A). The first monitoring result is determined based on the measured value of the channel state information corresponding to at least one first reference signal resource in the first subset (set M) and the predicted value of the channel state information corresponding to the entire first reference signal resource set (set A) or at least one second reference signal resource in the first subset (set M); or, the first monitoring result includes the measured value of the channel state information corresponding to at least one reference signal resource in the first subset (set M); or, The first inference result includes the probability that each reference signal resource in the first reference signal resource set (set A) is the best reference signal resource in the first reference signal resource set (set A). The first monitoring result is determined based on the best reference signal resource determined by at least one measurement in the first subset (set M) and the entire set of the first reference signal resource set (set A) or the best reference signal resource determined by at least one prediction in the first subset (set M). Alternatively, the first monitoring result includes the identification information of at least one best reference signal resource determined by at least one measurement in the first subset (set M), wherein the measured value of the channel state information corresponding to the at least one best reference signal resource determined by at least one measurement is greater than or equal to the measured value of the channel state information corresponding to the reference signal resources in the first subset (set M) other than the at least one best reference signal resource determined by at least one measurement.

20. A communication method, characterized in that, include: A first monitoring result and a second indication information are determined. The first monitoring result is used to determine whether the first inference result is accurate or the accuracy of the first inference result. The first inference result is used to determine the k1 predicted optimal reference signal resources in the first subset (set M) of the first reference signal resource set (set A) and the k2 predicted optimal reference signal resources in the first reference signal resource set. The second indication information is used to indicate the information of the same reference signal resources among the k1 predicted optimal reference signal resources in the first subset (set M) of the first reference signal resource set (set A) and the k2 predicted optimal reference signal resources in the first reference signal resource set (set A), where k1 and k2 are positive integers. Send a second message, which is used to indicate the first monitoring result and the second indication message.

21. The method according to claim 20, characterized in that, The information of the k1 predicted optimal reference signal resources and the k2 predicted optimal reference signal resources in the first set of reference signal resources that are the same includes one or more of the following: Whether each of the k1 predicted optimal reference signal resources belongs to the k2 predicted optimal reference signal resources; The number of reference signal resources that are the same as those in the k1 predicted optimal reference signal resources; The ratio of the number of reference signal resources that are the same as those in the k1 predicted optimal reference signal resources to the k2 predicted optimal reference signal resources, to k2.

22. The method according to claim 20 or 21, characterized in that, The method further includes: Send a fourth indication message, which is used to indicate k2 predicted optimal reference signal resources in the first set of reference signal resources, or the fourth indication message is used to indicate the k2 predicted optimal reference signal resources and the predicted value of the channel state information corresponding to each of the k2 predicted optimal reference signal resources.

23. The method according to any one of claims 20 to 22, characterized in that, The method further includes: Receive first configuration information, the first configuration information being used to configure a second subset (set M') of the first set of reference signal resources, the second subset (set M') being different from at least one reference signal resource included in the first subset (set M).

24. The method according to claim 23, characterized in that, The second subset (set M') does not include reference signal resources among the k1 predicted optimal reference signal resources that do not belong to the k2 predicted optimal reference signal resources in the first reference signal resource set, where k2 is a positive integer; or, The number of reference signal resources that are identical in the second subset (set M') and the first subset (set M) is less than or equal to a first preset threshold; or, The ratio of the number of identical reference signal resources in the second subset (set M') and the first subset (set M) to a first value is less than or equal to a second preset threshold, where the first value includes any one of the following: the number of reference signal resources in the second subset (set M') and the number of reference signal resources in the first subset (set M); or, The second subset (set M') includes k2 predicted optimal reference signal resources from the first reference signal resource set; or, The number of reference signal resources in the second subset (set M') that belong to the k2 predicted optimal reference signal resources in the first reference signal resource set is greater than or equal to a third preset threshold; or, The ratio of the number of reference signal resources in the second subset (set M') that belong to the k2 predicted optimal reference signal resources in the first reference signal resource set to a second value is greater than or equal to a fourth preset threshold, where the second value includes any one of the following: the number of reference signal resources in the second subset (set M'), the number of reference signal resources in the first reference signal resource set, and k... 2； Where k2 is a positive integer.

25. The method according to any one of claims 20 to 24, characterized in that, The predicted values ​​of the channel state information corresponding to the k1 predicted optimal reference signal resources are greater than or equal to the predicted values ​​of the channel state information corresponding to the reference signal resources in the first subset (set M) excluding the k1 predicted optimal reference signal resources; or, The probability corresponding to the k1 predicted optimal reference signal resources is greater than or equal to the probability corresponding to the reference signal resources in the first subset (set M) excluding the k1 predicted optimal reference signal resources, where the probability corresponding to the reference signal resource is the probability that the reference signal resource is the optimal reference signal resource in the first reference signal resource set (set A) or the first subset (set M); or, The k1 predicted optimal reference signal resources are the reference signal resources in the first subset (set M) that belong to the k2 predicted optimal reference signal resources in the first reference signal resource set. The predicted value of the channel state information corresponding to the k2 predicted optimal reference signal resources is greater than or equal to the predicted value of the channel state information corresponding to the reference signal resources in the first reference signal resource set (set A) other than the k2 predicted optimal reference signal resources. Alternatively, the probability corresponding to the k2 predicted optimal reference signal resources is greater than or equal to the probability corresponding to the reference signal resources in the first reference signal resource set (set A) other than the k2 predicted optimal reference signal resources. The probability corresponding to the reference signal resources is the probability that the reference signal resources are the best reference signal resources in the first reference signal resource set (set A). k2 is a positive integer.

26. The method according to any one of claims 20 to 25, characterized in that, The first inference result includes the predicted value of the channel state information corresponding to each reference signal resource in the first reference signal resource set (set A). The first monitoring result is determined based on the measured value of the channel state information corresponding to at least one first reference signal resource in the first subset (set M) and the predicted value of the channel state information corresponding to at least one second reference signal resource in the entire set of the first reference signal resource set (set A) or the first subset (set M); or, The first inference result includes the probability that each reference signal resource in the first reference signal resource set (set A) is the best reference signal resource in the first reference signal resource set (set A). The first monitoring result is determined based on the best reference signal resource determined by at least one measurement in the first subset (set M) and the entire set of the first reference signal resource set (set A) or the best reference signal resource determined by at least one prediction in the first subset (set M). The measured value of the channel state information corresponding to the best reference signal resource determined by at least one measurement is greater than or equal to the measured value of the channel state information corresponding to the reference signal resources in the first subset (set M) other than the best reference signal resource determined by at least one measurement.

27. The method according to any one of claims 20 to 26, characterized in that, If the first monitoring result includes the identification information of the reference signal resource, the identification information of the reference signal resource is the identification information of the reference signal resource in the first subset (set M).

28. The method according to any one of claims 20 to 26, characterized in that, The method further includes: Determine the measured value of the channel state information corresponding to each reference signal resource in the second reference signal resource set (set B), wherein the second reference signal resource set includes at least one reference signal resource; The first inference result is determined by using the measured values ​​of the channel state information corresponding to each reference signal resource in the second set of reference signal resources.

29. A communication method, characterized in that, include: The system receives second information, which is used to indicate a first monitoring result and a second indication. The first monitoring result is used to determine whether the first inference result is accurate or the accuracy of the first inference result. The first inference result is used to determine k1 predicted optimal reference signal resources in a first subset (set M) of a first reference signal resource set (set A) and k2 predicted optimal reference signal resources in the first reference signal resource set (set A). The second indication information is used to indicate information about the same reference signal resources among the k1 predicted optimal reference signal resources in the first subset (set M) of the first reference signal resource set (set A) and k2 predicted optimal reference signal resources in the first reference signal resource set (set A), where k1 and k2 are positive integers.

30. The method according to claim 29, characterized in that, The information of the k1 predicted optimal reference signal resources and the k2 predicted optimal reference signal resources in the first set of reference signal resources that are the same includes one or more of the following: Whether each of the k1 predicted optimal reference signal resources belongs to the k2 predicted optimal reference signal resources; The number of reference signal resources that are the same as those in the k1 predicted optimal reference signal resources; The ratio of the number of reference signal resources that are the same as those in the k1 predicted optimal reference signal resources to the k2 predicted optimal reference signal resources, to k2.

31. The method according to claim 29 or 30, characterized in that, The method further includes: Receive fourth indication information, which is used to indicate k2 predicted optimal reference signal resources in the first set of reference signal resources, or the fourth indication information is used to indicate the k2 predicted optimal reference signal resources and the predicted value of the channel state information corresponding to each of the k2 predicted optimal reference signal resources.

32. The method according to any one of claims 29 to 31, characterized in that, The method further includes: If a first preset condition is met, first configuration information is sent. The first configuration information is used to configure a second subset (set M') of the first reference signal resource set. The second subset (set M') is different from at least one reference signal resource included in the first subset (set M). The first preset condition includes any one of the following: The k1 predicted optimal reference signal resources are different from at least one of the k2 predicted optimal reference signal resources in the first set of reference signal resources; The number of reference signal resources in the k1 predicted optimal reference signal resources that are the same as those in the k2 predicted optimal reference signal resources in the first reference signal resource set is less than or equal to a fifth preset threshold. The ratio of the number of reference signal resources in the k1 predicted optimal reference signal resources that are the same as the k2 predicted optimal reference signal resources in the first reference signal resource set to k2 is less than or equal to a sixth preset threshold. Where k2 is a positive integer.

33. The method according to claim 32, characterized in that, The second subset (set M') does not include reference signal resources among the k1 predicted optimal reference signal resources that do not belong to the k2 predicted optimal reference signal resources in the first reference signal resource set, where k2 is a positive integer; or, The number of reference signal resources that are identical in the second subset (set M') and the first subset (set M) is less than or equal to a first preset threshold; or, The ratio of the number of identical reference signal resources in the second subset (set M') and the first subset (set M) to a first value is less than or equal to a second preset threshold, where the first value includes any one of the following: the number of reference signal resources in the second subset (set M') and the number of reference signal resources in the first subset (set M); or, The second subset (set M') includes k2 predicted optimal reference signal resources from the first reference signal resource set; or, The number of reference signal resources in the second subset (set M') that belong to the k2 predicted optimal reference signal resources in the first reference signal resource set is greater than or equal to a third preset threshold; or, The ratio of the number of reference signal resources in the second subset (set M') that belong to the k2 predicted optimal reference signal resources in the first reference signal resource set to a second value is greater than or equal to a fourth preset threshold, where the second value includes any one of the following: the number of reference signal resources in the second subset (set M'), the number of reference signal resources in the first reference signal resource set, and k... 2； Where k2 is a positive integer.

34. The method according to any one of claims 29 to 33, characterized in that, The predicted values ​​of the channel state information corresponding to the k1 predicted optimal reference signal resources are greater than or equal to the predicted values ​​of the channel state information corresponding to the reference signal resources in the first subset (set M) excluding the k1 predicted optimal reference signal resources; or, The probability corresponding to the k1 predicted optimal reference signal resources is greater than or equal to the probability corresponding to the reference signal resources in the first subset (set M) excluding the k1 predicted optimal reference signal resources, where the probability corresponding to the reference signal resource is the probability that the reference signal resource is the optimal reference signal resource in the first reference signal resource set (set A) or the first subset (set M); or, The k1 predicted optimal reference signal resources are the reference signal resources in the first subset (set M) that belong to the k2 predicted optimal reference signal resources in the first reference signal resource set. The predicted value of the channel state information corresponding to the k2 predicted optimal reference signal resources is greater than or equal to the predicted value of the channel state information corresponding to the reference signal resources in the first reference signal resource set (set A) other than the k2 predicted optimal reference signal resources. Alternatively, the probability corresponding to the k2 predicted optimal reference signal resources is greater than or equal to the probability corresponding to the reference signal resources in the first reference signal resource set (set A) other than the k2 predicted optimal reference signal resources. The probability corresponding to the reference signal resources is the probability that the reference signal resources are the best reference signal resources in the first reference signal resource set (set A). k2 is a positive integer.

35. The method according to any one of claims 29 to 34, characterized in that, The first inference result includes the predicted value of the channel state information corresponding to each reference signal resource in the first reference signal resource set (set A). The first monitoring result is determined based on the measured value of the channel state information corresponding to at least one first reference signal resource in the first subset (set M) and the predicted value of the channel state information corresponding to at least one second reference signal resource in the entire set of the first reference signal resource set (set A) or the first subset (set M); or, The first inference result includes the probability that each reference signal resource in the first reference signal resource set (set A) is the best reference signal resource in the first reference signal resource set (set A). The first monitoring result is determined based on the best reference signal resource determined by at least one measurement in the first subset (set M) and the entire set of the first reference signal resource set (set A) or the best reference signal resource determined by at least one prediction in the first subset (set M). The measured value of the channel state information corresponding to the best reference signal resource determined by at least one measurement is greater than or equal to the measured value of the channel state information corresponding to the reference signal resources in the first subset (set M) other than the best reference signal resource determined by at least one measurement.

36. The method according to any one of claims 29 to 35, characterized in that, If the first monitoring result includes the identification information of the reference signal resource, the identification information of the reference signal resource is the identification information of the reference signal resource in the first subset (set M).

37. The method according to any one of claims 29 to 36, characterized in that, The method further includes: If the first monitoring result includes the measured value of channel state information corresponding to at least one reference signal resource in the first subset (set M), a first accuracy is determined based on the measured value of channel state information corresponding to at least one first reference signal resource in the first subset (set M) and the predicted value of channel state information corresponding to the entire set of the first reference signal resource set (set A) or at least one second reference signal resource in the first subset (set M). The first accuracy is used to indicate whether the first inference result is accurate or the accuracy of the first inference result.

38. The method according to any one of claims 29 to 37, characterized in that, The method further includes: If the first monitoring result includes identification information of at least one optimal reference signal resource determined by measurement in the first subset (set M), a second accuracy is determined based on at least one optimal reference signal resource determined by measurement in the first subset (set M) and the entire set of the first reference signal resource set (set A) or at least one optimal reference signal resource determined by prediction in the first subset (set M). The second accuracy is used to indicate whether the first inference result is accurate or the accuracy of the first inference result.

39. A communication device, characterized in that, Includes a module for performing the method as claimed in any one of claims 1 to 10, or any one of claims 11 to 19, or any one of claims 20 to 28, or any one of claims 29 to 38.

40. A communication device, characterized in that, The communication device includes: at least one processor and a communication interface, the communication interface being used for the communication device to interact with other communication devices, and when program instructions are executed in the at least one processor, causing the communication device to perform the method as claimed in any one of claims 1 to 10 or any one of claims 20 to 28.

41. A communication device, characterized in that, The communication device includes: at least one processor and a communication interface, the communication interface being used for the communication device to interact with other communication devices, and when program instructions are executed in the at least one processor, causing the communication device to perform the method as claimed in any one of claims 11 to 19 or any one of claims 29 to 38.

42. A communication system, characterized in that, The communication system includes: the communication device as described in claim 40 and the communication device as described in claim 41.

43. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores program code for execution by the device, which, when executed, enables the execution of the method as claimed in any one of claims 1 to 10, or any one of claims 11 to 19, or any one of claims 20 to 28, or any one of claims 29 to 38.

44. A chip, characterized in that, The chip includes at least one processor, which, when program instructions are executed in the at least one processor, causes the method as claimed in any one of claims 1 to 10, or any one of claims 11 to 19, or any one of claims 20 to 28, or any one of claims 29 to 38 to be performed.

45. A computer program product, characterized in that, Includes program instructions that, when the computer program product is run on a computer, the method as claimed in any one of claims 1 to 10, or any one of claims 11 to 19, or any one of claims 20 to 28, or any one of claims 29 to 38, is performed.

Images