Information transmission method, device, and storage medium

Abstract

Embodiments of the present disclosure relate to an information transmission method, a device, and a storage medium. The method comprises: a terminal device sends first information to a network device, wherein the first information is information corresponding to a first function, the first function is supported by the terminal device and is an artificial intelligence (AI) function and / or an AI model used for performing beam prediction, and the first information comprises at least one of the following: second information, comprising information supported by the terminal device and used for performing performance monitoring on the first function; third information, comprising content information output by the first function supported by the terminal device; and fourth information, comprising a function identifier of the first function supported by the terminal device. In this way, the terminal device can report information related to the first function supported by the terminal device, thereby improving the flexibility of first function management.

Description

Information transmission method, device and storage medium Technical Field

[0001] The present disclosure relates to the field of communication technologies, and in particular to an information transmission method, device, and storage medium. Background Art

[0002] With the advancement of communication technology, prediction functions based on artificial intelligence (AI) have been introduced in wireless communication systems. The prediction functions can be AI functions and / or AI models. Through the prediction functions, prediction data in certain scenarios can be obtained, thereby improving network performance.

[0003] Summary of the Invention

[0004] The embodiments of the present disclosure provide an information transmission method, device, and storage medium.

[0005] According to a first aspect of an embodiment of the present disclosure, a method for transmitting information is provided, which is executed by a terminal device. The method includes:

[0006] Sending first information to the network device, where the first information is information corresponding to a first function, where the first function is an artificial intelligence (AI) function and / or AI model supported by the terminal device for performing beam prediction;

[0007] The first information includes at least one of the following:

[0008] second information, the second information including information on performance monitoring of the first function supported by the terminal device;

[0009] third information, the third information including content information output by the first function supported by the terminal device;

[0010] Fourth information, the fourth information includes a function identifier of the first function supported by the terminal device.

[0011] According to a second aspect of an embodiment of the present disclosure, an information transmission method is provided, which is performed by a network device. The method includes:

[0012] Receiving first information sent by a terminal device, where the first information is information corresponding to a first function, where the first function is an artificial intelligence (AI) function and / or AI model supported by the terminal device for performing beam prediction;

[0013] The first information includes at least one of the following:

[0014] second information, the second information including information on performance monitoring of the first function supported by the terminal device;

[0015] third information, the third information including content information output by the first function supported by the terminal device;

[0016] Fourth information, the fourth information includes a function identifier of the first function supported by the terminal device.

[0017] According to a third aspect of an embodiment of the present disclosure, a terminal device is provided, including:

[0018] a transceiver module configured to send first information to the network device, where the first information is information corresponding to a first function, where the first function is an artificial intelligence (AI) function and / or AI model supported by the terminal device for performing beam prediction;

[0019] The first information includes at least one of the following:

[0020] second information, the second information including information on performance monitoring of the first function supported by the terminal device;

[0021] third information, the third information including content information output by the first function supported by the terminal device;

[0022] Fourth information, the fourth information includes a function identifier of the first function supported by the terminal device.

[0023] According to a fourth aspect of an embodiment of the present disclosure, a network device is provided, including:

[0024] a transceiver module configured to receive first information sent by a terminal device, where the first information is information corresponding to a first function, where the first function is an artificial intelligence (AI) function and / or AI model supported by the terminal device for performing beam prediction;

[0025] The first information includes at least one of the following:

[0026] second information, the second information including information on performance monitoring of the first function supported by the terminal device;

[0027] third information, the third information including content information output by the first function supported by the terminal device;

[0028] Fourth information, the fourth information includes a function identifier of the first function supported by the terminal device.

[0029] According to a fifth aspect of an embodiment of the present disclosure, a communication device is proposed, comprising: one or more processors; wherein the communication device can be used to execute an optional implementation of the first aspect or the second aspect.

[0030] According to a sixth aspect of an embodiment of the present disclosure, a storage medium is proposed, which stores instructions. When the instructions are executed on a communication device, the communication device executes the method described in the optional implementation of the first aspect or the second aspect.

[0031] According to the seventh aspect of an embodiment of the present disclosure, a communication system is proposed, which may include: a terminal device and a network device; wherein the terminal device is configured to execute the method described in the optional implementation manner of the first aspect, and the network device is configured to execute the method described in the optional implementation manner of the second aspect.

[0032] The technical solution provided by the embodiment of the present disclosure may include the following beneficial effects: the terminal device sends first information to the network device, the first information being information corresponding to a first function, the first function being an artificial intelligence (AI) function and / or AI model supported by the terminal device for performing beam prediction; wherein the first information includes at least one of the following: second information, the second information including information supported by the terminal device for performance monitoring of the first function; third information, the third information including content information output by the first function supported by the terminal device; and fourth information, the fourth information including a function identifier of the first function supported by the terminal device. In this way, the terminal device can report information related to the first function supported by the terminal device, thereby improving the flexibility of the management of the first function.

[0033] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] In order to more clearly illustrate the technical solutions in the embodiments of the present disclosure, the following drawings required for describing the embodiments are introduced. The following drawings are merely some embodiments of the present disclosure and do not impose specific limitations on the protection scope of the present disclosure.

[0035] FIG1 is a schematic diagram showing the architecture of a communication system according to an embodiment of the present disclosure.

[0036] FIG2A is an interactive schematic diagram illustrating an information transmission method according to an embodiment of the present disclosure.

[0037] FIG2B is an interactive schematic diagram illustrating an information transmission method according to an embodiment of the present disclosure.

[0038] FIG3A is a flow chart showing an information transmission method according to an embodiment of the present disclosure.

[0039] FIG3B is a flow chart illustrating an information transmission method according to an embodiment of the present disclosure.

[0040] FIG4A is a schematic flow chart of an information transmission method according to an embodiment of the present disclosure.

[0041] FIG4B is a flow chart showing an information transmission method according to an embodiment of the present disclosure.

[0042] FIG5 is a flow chart showing an information transmission method according to an embodiment of the present disclosure.

[0043] FIG6A is a schematic structural diagram of a terminal device according to an embodiment of the present disclosure.

[0044] FIG6B is a schematic structural diagram of a network device according to an embodiment of the present disclosure.

[0045] FIG7A is a schematic structural diagram of a communication device according to an embodiment of the present disclosure.

[0046] FIG7B is a schematic structural diagram of a chip according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0047] The embodiments of the present disclosure provide an information transmission method, device, and storage medium.

[0048] In a first aspect, an embodiment of the present disclosure provides an information transmission method, which is executed by a terminal device. The method includes:

[0049] Sending first information to the network device, where the first information is information corresponding to a first function, where the first function is an artificial intelligence (AI) function and / or AI model supported by the terminal device for performing beam prediction;

[0050] The first information includes at least one of the following:

[0051] second information, the second information including information on performance monitoring of the first function supported by the terminal device;

[0052] third information, the third information including content information output by the first function supported by the terminal device;

[0053] Fourth information, the fourth information includes a function identifier of the first function supported by the terminal device.

[0054] In the above embodiment, the terminal device can report information related to the first function supported by the terminal device through the first information, thereby improving the flexibility of the management of the first function.

[0055] In conjunction with some embodiments of the first aspect, in some embodiments, the second information includes a performance monitoring type, and the performance monitoring type includes any one of the following:

[0056] Type 1 performance monitoring;

[0057] Type II performance monitoring;

[0058] The third type of performance monitoring.

[0059] In the above embodiment, the terminal device can report the supported performance monitoring types, thereby improving the flexibility and reliability of the performance monitoring of the first function.

[0060] In conjunction with some embodiments of the first aspect, in some embodiments, the performance monitoring type is first type performance monitoring, and the method further includes at least one of the following:

[0061] receiving fifth information sent by the network device, where the fifth information is used to instruct the terminal device to perform measurement and / or reporting;

[0062] Sending sixth information to the network device, where the sixth information is a report obtained by the terminal device performing the measurement;

[0063] receiving seventh information sent by the network device, where the seventh information is used to instruct the terminal device to perform a first operation on the first function, where the first operation includes any one of the following: selection, activation, deactivation, switching, and fallback;

[0064] The first operation is performed on the first function according to the seventh information.

[0065] In conjunction with some embodiments of the first aspect, in some embodiments, the sixth information includes at least one of the following:

[0066] Measurement beam information, where the measurement beam information includes beam information measured by the terminal device;

[0067] Predicted beam information, where the predicted beam information is beam information predicted by the terminal device based on the first function;

[0068] performance indicator information, where the performance indicator information is used to determine at least one of prediction accuracy, complexity, and signaling overhead of the first function;

[0069] Event information, where the event information is information about a triggering event based on which the terminal device triggers the sixth information.

[0070] In the above embodiment, the terminal device may support the first type of performance monitoring.

[0071] In conjunction with some embodiments of the first aspect, in some embodiments, the performance monitoring type is second-type performance monitoring, and the method further includes at least one of the following:

[0072] Obtaining performance indicator information corresponding to the first function, where the performance indicator information is used to determine at least one of prediction accuracy, complexity, and signaling overhead of the first function;

[0073] Sending eighth information to the network device, where the eighth information includes at least one of the following: the performance indicator information, and information of a triggering event based on which the eighth information is triggered.

[0074] In conjunction with some embodiments of the first aspect, in some embodiments, the performance monitoring type is second-type performance monitoring, and the method further includes at least one of the following:

[0075] Determine a first operation for performing the first function, where the first operation includes any one of the following: selection, activation, deactivation, switching, and rollback;

[0076] Ninth information is sent to the network device, where the ninth information is used to indicate the first operation determined by the terminal device.

[0077] In conjunction with some embodiments of the first aspect, in some embodiments, the method further includes:

[0078] receiving tenth information sent by the network device, where the tenth information is response information to the ninth information;

[0079] The first operation is performed on the first function.

[0080] In conjunction with some embodiments of the first aspect, in some embodiments, the method further includes:

[0081] Sending eleventh information to the network device, where the eleventh information is used to request to start performance monitoring of the first function;

[0082] Receive twelfth information sent by the network device, where the twelfth information is used to respond to the eleventh information.

[0083] In the above embodiment, the terminal device may support the second type of performance monitoring.

[0084] In conjunction with some embodiments of the first aspect, in some embodiments, the performance monitoring type is third type performance monitoring, and the method further includes at least one of the following:

[0085] Obtaining performance indicator information corresponding to the first function, where the performance indicator information is used to determine at least one of prediction accuracy, complexity, and signaling overhead of the first function;

[0086] Thirteenth information is sent to the network device, where the thirteenth information includes at least one of the following: the performance indicator information, and information of a triggering event based on which the thirteenth information is triggered.

[0087] In the above embodiment, the terminal device may support the third type of performance monitoring.

[0088] In combination with some embodiments of the first aspect, in some embodiments, the second information includes a performance indicator type, and the performance indicator type is used to indicate a performance indicator supported by the terminal device.

[0089] In conjunction with some embodiments of the first aspect, in some embodiments, the performance indicator includes at least one of the following:

[0090] a beam prediction accuracy rate, where the beam prediction accuracy rate is a probability that the predicted best reference signal resource includes an actual best reference signal resource, where the predicted best reference signal resource is the best reference signal resource predicted by the first function, the actual best reference signal resource is the best reference signal resource actually measured by the terminal device, and the best reference signal resource is the top N reference signal resources with the best signal strength in the predicted second reference signal resource set, where N is a positive integer;

[0091] a first signal strength difference, where the first signal strength difference is a difference between a first signal strength and a second signal strength, the first signal strength being the actual signal strength of the predicted best reference signal resource, and the second signal strength being the actual signal strength of the actual best reference signal resource;

[0092] a second signal strength difference, where the second signal strength difference is a difference between a first signal strength and a third signal strength, where the first signal strength is an actual signal strength of the predicted best reference signal resource, and the third signal strength is a predicted signal strength of the predicted best reference signal resource;

[0093] a third signal strength difference, where the third signal strength difference is a difference between a second signal strength and a fourth signal strength, where the second signal strength is an actual signal strength of the actual best reference signal resource, and the fourth signal strength is a predicted signal strength of the actual best reference signal resource;

[0094] a first signal strength prediction accuracy indicator, where the first signal strength prediction accuracy indicator is a probability of the first signal strength difference being within a first difference range, or an average value of the first signal strength difference, or a value of a cumulative distribution function of the first signal strength difference at a first distribution ratio, where the first distribution ratio is greater than 0 and less than 1;

[0095] a second signal strength prediction accuracy indicator, where the second signal strength prediction accuracy indicator is a probability that the second signal strength difference is within a first difference range, or an average value of the second signal strength difference, or a value of a cumulative distribution function of the second signal strength difference at a first distribution ratio;

[0096] a third signal strength prediction accuracy indicator, wherein the third signal strength prediction accuracy indicator is a probability that the third signal strength difference is within a first difference range, or an average value of the third signal strength difference, or a value of a cumulative distribution function of the third signal strength difference at a first distribution ratio;

[0097] a throughput difference, where the throughput difference is a difference between a first throughput and a second throughput, where the first throughput is a throughput calculated based on a first SINR, and the second throughput is a throughput calculated based on a second SINR, where the first SINR is an actual SINR of the predicted best reference signal resource, and the second SINR is an actual SINR of the actual best reference signal resource;

[0098] a throughput prediction accuracy indicator, the throughput prediction accuracy indicator being a probability of the throughput difference being within a second difference range, or an average value of the throughput differences, or a value of a cumulative distribution function of the throughput differences at a second distribution ratio, where the second distribution ratio is greater than 0 and less than 1;

[0099] a reference signal overhead, where the reference signal overhead is used to indicate the number of reference signal resources required for the first function;

[0100] Uplink resource overhead, where the uplink resource overhead is used to indicate the amount of uplink resources occupied by information that needs to be reported to the network device for performing prediction and / or performance monitoring of the first function;

[0101] Prediction delay, where the prediction delay is the time taken by the first function to perform beam prediction;

[0102] Input data distribution information, where the input data distribution information is distribution information of input data of the first function;

[0103] Output data distribution information, where the output data distribution information is distribution information of output data of the first function;

[0104] Model complexity.

[0105] In the above embodiment, the terminal device may report the type of event that triggers the performance monitoring through the second information, so as to improve the flexibility and reliability of functional operation.

[0106] In combination with some embodiments of the first aspect, in some embodiments, the second information includes an event type, and the event type is used to indicate the type of event supported by the terminal device that triggers the performance monitoring.

[0107] In conjunction with some embodiments of the first aspect, in some embodiments, the event type includes at least one of the following:

[0108] A first type event, wherein the first type event is used to indicate that a performance indicator of an activated first function is worse than a first threshold;

[0109] a second type of event, where the second type of event is used to indicate that a performance indicator of the deactivated first function is better than a second threshold;

[0110] A third type of event, the third type of event being used to indicate that a performance indicator of the activated first function is worse than a first threshold, and a performance indicator of the deactivated first function is better than a second threshold;

[0111] The fourth type of event is used to indicate that the first difference is better than the fourth threshold, the first difference is the difference between the second performance indicator and the first performance indicator, the first performance indicator is the performance indicator of the deactivated first function, and the second performance indicator is the performance indicator of the activated first function.

[0112] In the above embodiment, the terminal device may report the performance indicators supported by the terminal device through the second information, so as to improve the flexibility and reliability of functional operations.

[0113] In conjunction with some embodiments of the first aspect, in some embodiments, the third information includes at least one of the following:

[0114] Reference signal resource identifier;

[0115] Signal strength;

[0116] The confidence level corresponding to the signal strength.

[0117] In the above embodiment, the terminal device can report the information output by the first function through the third information, so as to improve the flexibility and reliability of the function operation.

[0118] In conjunction with some embodiments of the first aspect, in some embodiments,

[0119] The confidence level is used to indicate whether the signal strength is an actually measured signal strength or a predicted signal strength; or

[0120] The signal strength is a predicted signal strength, and the confidence level is used to indicate a prediction accuracy corresponding to the signal strength.

[0121] In the above embodiment, the terminal device may report the prediction accuracy of the information output by the first function through the confidence level, so as to improve the reliability of the function operation.

[0122] In combination with some embodiments of the first aspect, in some embodiments, the first information is carried by a terminal capability report.

[0123] In the above embodiment, the first information is reported through the existing process.

[0124] In combination with some embodiments of the first aspect, in some embodiments, the multiple information included in the first information includes mandatory information and optional information.

[0125] In the above embodiments, the flexibility of information transmission can be improved.

[0126] In combination with some embodiments of the first aspect, in some embodiments, the first function is deployed in the terminal device and / or the network device.

[0127] In the above embodiment, information related to the first function can be reported for different function deployment scenarios.

[0128] In a second aspect, an embodiment of the present disclosure provides an information transmission method, which is performed by a network device. The method includes:

[0129] Receiving first information sent by a terminal device, where the first information is information corresponding to a first function, where the first function is an artificial intelligence (AI) function and / or AI model supported by the terminal device for performing beam prediction;

[0130] The first information includes at least one of the following:

[0131] second information, the second information including information on performance monitoring of the first function supported by the terminal device;

[0132] third information, the third information including content information output by the first function supported by the terminal device;

[0133] Fourth information, the fourth information includes a function identifier of the first function supported by the terminal device.

[0134] In the above embodiment, the network device can obtain information related to the first function supported by the terminal device through the first information, thereby improving the flexibility of the management of the first function.

[0135] In conjunction with some embodiments of the second aspect, in some embodiments, the second information includes a performance monitoring type, and the performance monitoring type includes any one of the following:

[0136] Type 1 performance monitoring;

[0137] Type II performance monitoring;

[0138] The third type of performance monitoring.

[0139] In conjunction with some embodiments of the second aspect, in some embodiments, the performance monitoring type is first type performance monitoring, and the method further includes at least one of the following:

[0140] Sending fifth information to the terminal device, where the fifth information is used to instruct the terminal device to perform measurement and / or reporting;

[0141] receiving sixth information sent by the terminal device, where the sixth information is a report obtained by the terminal device performing the measurement;

[0142] determining a first operation according to the sixth information;

[0143] Send seventh information to the terminal device, where the seventh information is used to instruct the terminal device to perform the first operation on the first function, where the first operation includes any one of the following: selection, activation, deactivation, switching, and rollback.

[0144] In conjunction with some embodiments of the second aspect, in some embodiments, the sixth information includes at least one of the following:

[0145] Measurement beam information, where the measurement beam information includes beam information measured by the terminal device;

[0146] Predicted beam information, where the predicted beam information is beam information predicted by the terminal device based on the first function;

[0147] performance indicator information, where the performance indicator information is used to determine at least one of prediction accuracy, complexity, and signaling overhead of the first function;

[0148] Event information, where the event information is information about a triggering event based on which the terminal device triggers the sixth information.

[0149] In conjunction with some embodiments of the second aspect, in some embodiments, the performance monitoring type is second type performance monitoring, and the method further includes:

[0150] Receive the eighth information sent by the terminal device, the eighth information including at least one of the following: performance indicator information, information of a triggering event based on which the eighth information is triggered, and the performance indicator information is used to determine at least one of the prediction accuracy, complexity and signaling overhead of the first function.

[0151] In conjunction with some embodiments of the second aspect, in some embodiments, the performance monitoring type is second type performance monitoring, and the method further includes:

[0152] Receive ninth information sent by the terminal device, where the ninth information is used to instruct the terminal device to determine a first operation to perform the first function, where the first operation includes any one of the following: selection, activation, deactivation, switching, and fallback.

[0153] In conjunction with some embodiments of the second aspect, in some embodiments, the method further includes:

[0154] Send tenth information to the terminal device, where the tenth information is response information to the ninth information.

[0155] In conjunction with some embodiments of the second aspect, in some embodiments, the method further includes:

[0156] receiving an eleventh message sent by the terminal device, where the eleventh message is used to request to start performance monitoring of the first function;

[0157] Twelfth information is sent to the terminal device, where the twelfth information is used to respond to the eleventh information.

[0158] In conjunction with some embodiments of the second aspect, in some embodiments, the performance monitoring type is third type performance monitoring, and the method further includes:

[0159] Receive the thirteenth information sent by the terminal device, the thirteenth information including at least one of the following: performance indicator information, information of a triggering event on which the thirteenth information is triggered, and the performance indicator information is used to determine at least one of the prediction accuracy, complexity and signaling overhead of the first function.

[0160] In combination with some embodiments of the second aspect, in some embodiments, the second information includes a performance indicator type, and the performance indicator type is used to indicate a performance indicator supported by the terminal device.

[0161] In conjunction with some embodiments of the second aspect, in some embodiments, the performance indicator includes at least one of the following:

[0162] a beam prediction accuracy rate, where the beam prediction accuracy rate is a probability that the predicted best reference signal resource includes an actual best reference signal resource, where the predicted best reference signal resource is the best reference signal resource predicted by the first function, the actual best reference signal resource is the best reference signal resource actually measured by the terminal device, and the best reference signal resource is the top N reference signal resources with the best signal strength in the predicted second reference signal resource set, where N is a positive integer;

[0163] a first signal strength difference, where the first signal strength difference is a difference between a first signal strength and a second signal strength, the first signal strength being the actual signal strength of the predicted best reference signal resource, and the second signal strength being the actual signal strength of the actual best reference signal resource;

[0164] a second signal strength difference, where the second signal strength difference is a difference between a first signal strength and a third signal strength, where the first signal strength is an actual signal strength of the predicted best reference signal resource, and the third signal strength is a predicted signal strength of the predicted best reference signal resource;

[0165] a third signal strength difference, where the third signal strength difference is a difference between a second signal strength and a fourth signal strength, where the second signal strength is an actual signal strength of the actual best reference signal resource, and the fourth signal strength is a predicted signal strength of the actual best reference signal resource;

[0166] a first signal strength prediction accuracy indicator, where the first signal strength prediction accuracy indicator is a probability of the first signal strength difference being within a first difference range, or an average value of the first signal strength difference, or a value of a cumulative distribution function of the first signal strength difference at a first distribution ratio, where the first distribution ratio is greater than 0 and less than 1;

[0167] a second signal strength prediction accuracy indicator, where the second signal strength prediction accuracy indicator is a probability that the second signal strength difference is within a first difference range, or an average value of the second signal strength difference, or a value of a cumulative distribution function of the second signal strength difference at a first distribution ratio;

[0168] a third signal strength prediction accuracy indicator, wherein the third signal strength prediction accuracy indicator is a probability that the third signal strength difference is within a first difference range, or an average value of the third signal strength difference, or a value of a cumulative distribution function of the third signal strength difference at a first distribution ratio;

[0169] a throughput difference, where the throughput difference is a difference between a first throughput and a second throughput, where the first throughput is a throughput calculated based on a first SINR, and the second throughput is a throughput calculated based on a second SINR, where the first SINR is an actual SINR of the predicted best reference signal resource, and the second SINR is an actual SINR of the actual best reference signal resource;

[0170] a throughput prediction accuracy indicator, the throughput prediction accuracy indicator being a probability of the throughput difference being within a second difference range, or an average value of the throughput differences, or a value of a cumulative distribution function of the throughput differences at a second distribution ratio, where the second distribution ratio is greater than 0 and less than 1;

[0171] a reference signal overhead, where the reference signal overhead is used to indicate the number of reference signal resources required for the first function;

[0172] Uplink resource overhead, where the uplink resource overhead is used to indicate the amount of uplink resources occupied by information that needs to be reported to the network device for performing prediction and / or performance monitoring of the first function;

[0173] Prediction delay, where the prediction delay is the time taken by the first function to perform beam prediction;

[0174] Input data distribution information, where the input data distribution information is distribution information of input data of the first function;

[0175] Output data distribution information, where the output data distribution information is distribution information of output data of the first function;

[0176] Model complexity.

[0177] In combination with some embodiments of the second aspect, in some embodiments, the second information includes an event type, and the event type is used to indicate the type of event supported by the terminal device that triggers the performance monitoring.

[0178] In conjunction with some embodiments of the second aspect, in some embodiments, the event type includes at least one of the following:

[0179] A first type event, wherein the first type event is used to indicate that a performance indicator of an activated first function is worse than a first threshold;

[0180] a second type of event, where the second type of event is used to indicate that a performance indicator of the deactivated first function is better than a second threshold;

[0181] A third type of event, the third type of event being used to indicate that a performance indicator of the activated first function is worse than a first threshold, and a performance indicator of the deactivated first function is better than a second threshold;

[0182] The fourth type of event is used to indicate that the first difference is better than the fourth threshold, the first difference is the difference between the second performance indicator and the first performance indicator, the first performance indicator is the performance indicator of the deactivated first function, and the second performance indicator is the performance indicator of the activated first function.

[0183] In conjunction with some embodiments of the second aspect, in some embodiments, the third information includes at least one of the following:

[0184] Reference signal resource identifier;

[0185] Signal strength;

[0186] The confidence level corresponding to the signal strength.

[0187] In conjunction with some embodiments of the second aspect, in some embodiments,

[0188] The confidence level is used to indicate whether the signal strength is an actually measured signal strength or a predicted signal strength; or

[0189] The signal strength is a predicted signal strength, and the confidence level is used to indicate a prediction accuracy corresponding to the signal strength.

[0190] In combination with some embodiments of the second aspect, in some embodiments, the first information is carried by a terminal capability report.

[0191] In combination with some embodiments of the second aspect, in some embodiments, the multiple information included in the first information includes mandatory information and optional information.

[0192] In combination with some embodiments of the second aspect, in some embodiments, the first function is deployed in the terminal device and / or the network device.

[0193] In a third aspect, an embodiment of the present disclosure proposes a terminal device, which may include at least one of a transceiver module and a processing module; wherein the terminal device can be used to execute the optional implementation method of the first aspect.

[0194] In a fourth aspect, an embodiment of the present disclosure proposes a network device, which may include at least one of a transceiver module and a processing module; wherein the network device can be used to execute the optional implementation method of the second aspect.

[0195] In a fifth aspect, an embodiment of the present disclosure proposes a communication device, which may include: one or more processors; wherein the communication device can be used to execute an optional implementation of the first aspect or the second aspect.

[0196] In a sixth aspect, an embodiment of the present disclosure proposes a storage medium storing instructions, which, when executed on a communication device, enables the communication device to execute the method described in the optional implementation manner of the first aspect or the second aspect.

[0197] In the seventh aspect, an embodiment of the present disclosure proposes a computer program product, which includes a computer program and / or instructions. When the computer program and / or instructions are executed by a communication device, the communication device executes the method described in the optional implementation of the first aspect or the second aspect.

[0198] In an eighth aspect, an embodiment of the present disclosure proposes a computer program, which, when executed on a computer, enables the computer to execute the method described in the optional implementation of the first or second aspect.

[0199] In a ninth aspect, an embodiment of the present disclosure provides a chip or a chip system, wherein the chip or chip system includes a processing circuit configured to execute the method described in the optional implementation of the first aspect or the second aspect.

[0200] In the tenth aspect, an embodiment of the present disclosure proposes a communication system, which may include: a terminal device and a network device; wherein, the terminal device is configured to execute the method described in the optional implementation manner of the first aspect, and the network device is configured to execute the method described in the optional implementation manner of the second aspect.

[0201] It is understandable that the above-mentioned terminal devices, network devices, communication devices, communication systems, storage media, program products, computer programs, chips, or chip systems can all be used to perform the methods proposed in the embodiments of the present disclosure. Therefore, the beneficial effects that can be achieved can refer to the beneficial effects of the corresponding methods and will not be repeated here.

[0202] The present disclosure provides an information transmission method, device, and storage medium. In some embodiments, the terms "information transmission method" and "information processing method" and "communication method" are interchangeable; "information transmission device" and "information processing device" and "communication device" are interchangeable; and "information processing system" and "communication system" are interchangeable.

[0203] The embodiments of the present disclosure are not exhaustive and are merely illustrative of some embodiments, and are not intended to be a specific limitation on the scope of protection of the present disclosure. In the absence of contradiction, each step in a certain embodiment can be implemented as an independent embodiment, and the steps can be arbitrarily combined. For example, a solution after removing some steps in a certain embodiment can also be implemented as an independent embodiment, and the order of the steps in a certain embodiment can be arbitrarily exchanged. In addition, the optional implementation methods in a certain embodiment can be arbitrarily combined; in addition, the embodiments can be arbitrarily combined. For example, some or all steps of different embodiments can be arbitrarily combined, and a certain embodiment can be arbitrarily combined with the optional implementation methods of other embodiments.

[0204] In each embodiment of the present disclosure, unless otherwise specified or provided for by logic, the terms and / or descriptions between the embodiments are consistent and can be referenced by each other. The technical features in different embodiments can be combined to form a new embodiment based on their inherent logical relationships.

[0205] The terms used in the embodiments of the present disclosure are only for the purpose of describing specific embodiments and are not intended to limit the present disclosure.

[0206] In the embodiments of the present disclosure, unless otherwise specified, elements expressed in the singular, such as "a", "an", "the", "above", "said", "the", "the", etc., may mean "one and only one", or "one or more", "at least one", etc. For example, when using articles such as "a", "an", "the" in English in translation, the noun following the article may be understood as a singular expression or a plural expression.

[0207] In some embodiments, "plurality" may refer to two or more.

[0208] In some embodiments, the terms "at least one," "one or more," "a plurality of," "multiple," etc. may be used interchangeably.

[0209] In some embodiments, descriptions such as "at least one of A and B," "A and / or B," "A in one case, B in another case," or "in response to one case A, in response to another case B" may include the following technical solutions depending on the situation: in some embodiments, A (A is executed independently of B); in some embodiments, B (B is executed independently of A); in some embodiments, execution is selected from A and B (A and B are selectively executed); and in some embodiments, A and B (both A and B are executed). The above is also applicable when there are more branches such as A, B, and C.

[0210] In some embodiments, "A or B" and other descriptions may include the following technical solutions depending on the situation: in some embodiments, A (A is executed independently of B); in some embodiments, B (B is executed independently of A); in some embodiments, execution is selected from A and B (A and B are selectively executed). The above is also applicable when there are more branches such as A, B, C, etc.

[0211] The prefixes such as "first" and "second" in the embodiments of the present disclosure are only used to distinguish different description objects and do not constitute any restriction on the position, order, priority, quantity or content of the description objects. For the statement of the description object, please refer to the description in the context of the claims or embodiments, and no unnecessary restriction should be constituted due to the use of prefixes. For example, if the description object is a "field", the ordinal number before the "field" in the "first field" and the "second field" does not limit the position or order between the "fields". "First" and "second" do not limit whether the "fields" they modify are in the same message, nor do they limit the order of the "first field" and the "second field". For another example, if the description object is a "level", the ordinal number before the "level" in the "first level" and the "second level" does not limit the priority between the "levels". For another example, the number of description objects is not limited by the ordinal number and can be one or more. Taking "first device" as an example, the number of "devices" can be one or more. In addition, the objects modified by different prefixes can be the same or different. For example, if the description object is "device", then the "first device" and the "second device" can be the same device or different devices, and their types can be the same or different; for another example, if the description object is "information", then the "first information" and the "second information" can be the same information or different information, and their contents can be the same or different.

[0212] In some embodiments, “including A,” “comprising A,” “used to indicate A,” and “carrying A” can be interpreted as directly carrying A or indirectly indicating A.

[0213] In some embodiments, terms such as "in response to...", "in response to determining...", "in the case of...", "at the time of...", "when...", "if...", "if...", etc. can be used interchangeably.

[0214] In some embodiments, terms such as "greater than", "greater than or equal to", "not less than", "more than", "more than or equal to", "not less than", "higher than", "higher than or equal to", "not less than", and "above" can be replaced with each other, and terms such as "less than", "less than or equal to", "not greater than", "less than", "less than or equal to", "not more than", "lower than", "lower than or equal to", "not higher than", and "below" can be replaced with each other.

[0215] In some embodiments, devices and the like may be interpreted as physical or virtual, and their names are not limited to those described in the embodiments. Terms such as "device," "equipment," "device," "circuit," "network element," "node," "function," "unit," "section," "system," "network," "chip," "chip system," "entity," and "subject" may be used interchangeably.

[0216] In some embodiments, "network" can be interpreted as devices included in the network (eg, network equipment, access network equipment, core network equipment, etc.).

[0217] In some embodiments, the network device may include at least one of an access network device and a core network device.

[0218] In some embodiments, the terms "Access Network Device (AN Device)", "Radio Access Network Device (RAN Device)", "Base Station (BS)", "Radio Base Station (Radio Base Station)", "Fixed Station (Fixed Station)", "Node (Node)", "Access Point (Access Point)", "Transmission Point (TP)", "Reception Point (RP)", "Transmission and / or Reception Point (TRP))", "Panel (Panel)", "Antenna Panel (Antenna Panel)", "Antenna Array (Antenna Array)" "Cell (Cell)", "Macro Cell (Macro Cell)", "Small Cell (Small Cell)", "Femto Cell (Femto Cell)", "Pico Cell (Pico Cell)" "Sector (Sector)", "Cell Group (Cell Group)", "Serving Cell (Cell)", "Carrier (Carrier)", "Component Carrier (Component Carrier)", "Bandwidth Part (BWP)" and the like may be used interchangeably.

[0219] In some embodiments, the terms "terminal", "terminal device", "terminal side device", "user equipment (UE)", "user terminal" "mobile station (MS)", "mobile terminal (MT)", subscriber station (Subscriber Station), mobile unit (Mobile Unit), subscriber unit (Subscriber Unit), wireless unit (Wireless Unit), remote unit (Remote Unit), mobile device (Mobile Device), wireless device (Wireless Device), wireless communication device (Wireless Communication Device), remote device (Remote Device), mobile subscriber station (Mobile Subscriber Station), access terminal (Access Terminal), mobile terminal (Mobile Terminal), wireless terminal (Wireless Terminal), remote terminal (Remote Terminal), handset (Handset), user agent (User Agent), mobile client (Mobile Client), client (Client) and the like can be used interchangeably.

[0220] In some embodiments, the access network device, the core network device, or the network device can be replaced by a terminal device. For example, the various embodiments of the present disclosure can also be applied to a structure in which the communication between the access network device, the core network device, or the network device and the terminal device is replaced by the communication between multiple terminal devices (for example, device-to-device (D2D), vehicle-to-everything (V2X), etc.). In this case, it is also possible to set the structure in which the terminal device has all or part of the functions of the access network device. In addition, terms such as "uplink" and "downlink" can also be replaced by terms corresponding to communication between terminal devices (for example, "side"). For example, uplink channels, downlink channels, etc. can be replaced by side channels or direct channels, and uplinks, downlinks, etc. can be replaced by side links or direct links.

[0221] In some embodiments, the terminal device may be replaced by an access network device, a core network device, or a network device. In this case, the access network device, the core network device, or the network device may have a structure that has all or part of the functions of the terminal device.

[0222] In some embodiments, obtaining data, information, etc. may comply with the laws and regulations of the country where the data is obtained.

[0223] In some embodiments, data, information, etc. may be obtained with the user's consent.

[0224] In addition, each element, each row, or each column in the table of the embodiment of the present disclosure can be implemented as an independent embodiment, and the combination of any elements, any rows, and any columns can also be implemented as an independent embodiment.

[0225] FIG1 is a schematic diagram illustrating an architecture of a communication system according to an embodiment of the present disclosure. As shown in FIG1 , the communication system 100 may include a terminal device 101 and a network device 102 .

[0226] In some embodiments, the terminal device 101 may include at least one of a mobile phone, a wearable device, an Internet of Things device, a car with communication function, a smart car, a vehicle-mounted terminal, a tablet computer, a computer with wireless transceiver function, a road side unit (RSU), a virtual reality (VR) terminal device, an augmented reality (AR) terminal device, a wireless terminal device in industrial control, a wireless terminal device in self-driving, a wireless terminal device in remote medical surgery, a wireless terminal device in smart grid, a wireless terminal device in transportation safety, a wireless terminal device in smart city, and a wireless terminal device in smart home, but is not limited thereto.

[0227] In some embodiments, the network device 102 may include at least one of an access network device and a core network device.

[0228] In some embodiments, the access network device may be a node or device that accesses the terminal device to the wireless network. The access network device may include an evolved NodeB (eNB), a next generation evolved NodeB (ng-eNB), a next generation NodeB (gNB), a NodeB (NB), a home NodeB (HNB), a home evolved NodeB (HeNB), a wireless backhaul device, a radio network controller (RNC), a base station controller (BSC), a base transceiver station (BTS), a base band unit (BBU), a mobile switching center, a base station in a 6G communication system, an open base station (Open RAN), a cloud base station (Cloud RAN), a base station in other communication systems, and at least one of an access node in a Wi-Fi system, but is not limited thereto.

[0229] In some embodiments, the technical solution of the present disclosure can be applied to the Open RAN architecture. In this case, the interfaces between or within the access network devices involved in the embodiments of the present disclosure can be transformed into internal interfaces of the Open RAN, and the processes and information interactions between these internal interfaces can be implemented through software or programs.

[0230] In some embodiments, the access network device can be composed of a centralized unit (CU) and a distributed unit (DU), where the CU can also be called a control unit (Control Unit). The CU-DU structure can be used to split the protocol layer of the access network device, with the functions of some protocol layers centrally controlled by the CU, and the functions of the remaining part or all of the protocol layers distributed in the DU, which is centrally controlled by the CU, but is not limited to this.

[0231] In some embodiments, the core network device may be a single device, or may be multiple devices or a group of devices. The core network may include at least one of an Evolved Packet Core (EPC), a 5G Core Network (5GCN), a 6G Core Network (5GCN), and a Next Generation Core (NGC).

[0232] It can be understood that the communication system described in the embodiment of the present disclosure is to more clearly illustrate the technical solution of the embodiment of the present disclosure, and does not constitute a limitation on the technical solution proposed in the embodiment of the present disclosure. Ordinary technicians in this field can know that with the evolution of system architecture and the emergence of new business scenarios, the technical solution proposed in the embodiment of the present disclosure is also applicable to similar technical problems.

[0233] The following embodiments of the present disclosure may be applied to the communication system 100 shown in FIG1 , or a portion thereof, but are not limited thereto. The entities shown in FIG1 are examples. The communication system may include all or part of the entities shown in FIG1 , or may include other entities outside of FIG1 . The number and form of the entities are arbitrary, and the entities may be physical or virtual. The connection relationship between the entities is an example. The entities may be connected or disconnected, and the connection may be in any manner, including direct or indirect, wired or wireless.

[0234] The embodiments of the present disclosure can be applied to Long Term Evolution (LTE), LTE-Advanced (LTE-A), LTE-Beyond (LTE-B), SUPER 3G, IMT-Advanced, 4th generation mobile communication system (4G), 5th generation mobile communication system (5G), 5G New Radio (NR), Evolved Universal Terrestrial Radio Access (E-UTRA), Future Radio Access (FRA), New-Radio Access Technology (RAT), New Radio (NR), New Radio Access (NX), Future generation radio access (FX), Global System for Mobile communications (GSM (registered trademark)), CDMA2000, Ultra Mobile Broadband (UMB), IEEE 802.11 (Wi-Fi (registered trademark)), IEEE 802.16 (WiMAX (registered trademark)), IEEE 802.20, Ultra-WideBand (UWB), Bluetooth (registered trademark), Public Land Mobile Network (PLMN) networks, Device-to-Device (D2D) systems, Machine-to-Machine (M2M) systems, Internet of Things (IoT) systems, Vehicle-to-Everything (V2X), systems utilizing other communication methods, and next-generation systems based on and extending these methods. Furthermore, multiple systems may be combined (for example, a combination of LTE or LTE-A with 5G).

[0235] In some embodiments of the present disclosure, the communication system may support beam-based transmission and reception. Beam-based transmission and reception can better align useful signals with corresponding terminal devices, prevent signal energy leakage from interfering with other terminal devices, improve the signal-to-interference-and-noise ratio, and enhance the coverage performance of the wireless communication system.

[0236] For example, in a communication system, such as NR communication, for the FR2 (frequency range 2) communication band, since the high-frequency channel attenuates relatively quickly, in order to ensure coverage, beam-based transmission and reception can be used.

[0237] In some embodiments, the network device may be configured with a reference signal resource set for beam measurement, and the terminal device may measure the reference signal resources in the reference signal resource set and report the IDs of X reference signal resources with relatively strong signal quality in the measurement results, as well as the physical layer reference signal received power (Layer 1-Reference Signal Receiving Power, L1-RSRP) and / or physical layer signal to interference plus noise ratio (Layer 1-Signal to Interference plus Noise Ratio, L1-SINR) of each reference signal resource in the X reference signal resources. The reference signal resource set configured by the network device includes X reference signal resources, each reference signal resource corresponds to a different transmit beam of the network device. For each reference signal resource, the terminal device needs to measure the reference signal resource through all receive beams, determine the beam measurement quality corresponding to each receive beam, and determine the strongest beam measurement quality from multiple beam measurement qualities. In the above measurement process, if the number of transmit beams of the network device is M and the number of receive beams of the terminal device is N, then the number of beam pairs that the terminal device needs to measure is M*N.

[0238] In some embodiments, the terms "beam", "beam pair", "beam width", "beam angular degree", "antenna", "antenna element", "antenna port", "antenna port group", "panel", "layer", "the number of layers", "rank", "resource", "resource set", "resource group", "Quasi-Colocation (QCL) Type D", "spatial setting", "spatial filter", "spatial relation info", "spatial RX parameters", "spatial Tx parameter", "Transmission Configuration Indication (TCI) state" and the like may be used interchangeably.

[0239] In some embodiments of the present disclosure, the above-mentioned communication system may support a first function, which may be used to perform beam prediction.

[0240] In some embodiments, the first function may include AI functionality and / or an AI model.

[0241] In some embodiments, the aforementioned AI function may correspond to one or more AI models. For example, an AI function may be a function or module implemented by one or more AI models.

[0242] For example, the terminal device may support a certain AI function. Under this AI function, the terminal device may support one or more AI models, that is, the AI ​​function may correspond to (or include) one or more AI models, and the AI ​​function may be implemented through some or all of the one or more AI models.

[0243] In one implementation, a terminal device may report to a network device that it supports a certain AI function, but the terminal device does not need to report to the network device one or more AI models corresponding to the AI ​​function. When the AI ​​function is activated (e.g., instructed to do so by the network device, or autonomously determined by the terminal device), the terminal device may autonomously activate one or more AI models included in the AI ​​function (either partially or fully), thereby implementing the AI ​​function.

[0244] In one implementation, the terminal device may report to the network device that it supports a certain AI function and report one or more AI models corresponding to the AI ​​function. In this way, operations such as activation or deactivation of the AI ​​function and / or AI model can be completed by the network device or the terminal device. For example, the network device may determine the activated AI function and / or AI model and instruct the terminal device, and the terminal device activates the corresponding AI function and / or AI model according to the instruction of the network device. For another example, the network device may only determine the activated AI function and notify the terminal device, and the terminal device may autonomously activate one or more AI models contained in the AI ​​function (which may be partially activated or fully activated) to implement the AI ​​function.

[0245] In other embodiments, the aforementioned AI model may also correspond to one or more AI functions. For example, an AI model may implement one or more AI functions.

[0246] For example, the terminal device may report to the network device that it supports a certain AI model, which may correspond to one or more AI functions, and the network device may instruct the terminal device to activate or deactivate the AI ​​model.

[0247] For example, the terminal device may support a certain AI model, and based on the AI ​​model, the terminal device may support the implementation of one or more AI functions.

[0248] In one implementation, a terminal device may report to a network device that it supports a certain AI model, but the terminal device does not need to report to the network device one or more AI functions corresponding to the AI ​​model. When the AI ​​model is activated (e.g., instructed to do so by the network device, or determined to do so by the terminal device itself), the terminal device may autonomously implement one or more AI functions supported by the AI ​​model.

[0249] In one implementation, the terminal device may report to the network device that it supports a certain AI model and report one or more AI functions corresponding to the AI ​​model. In this way, operations such as activation or deactivation of the AI ​​model and / or AI function can be completed by the network device or the terminal device. For example, the network device may determine the activated AI model and / or AI function and instruct the terminal device, and the terminal device activates the corresponding AI model and / or AI function according to the instruction of the network device. For another example, the network device may only determine the activated AI model and notify the terminal device, and the terminal device may autonomously activate one or more AI functions contained in the AI ​​model (which may be partially activated or fully activated).

[0250] In some other embodiments, the above-mentioned AI functions and AI models may correspond one to one.

[0251] In some embodiments, the first function may be deployed on a terminal device and / or a network device. For example, the first function may be deployed entirely on the terminal device; another example, the first function may be deployed entirely on the network device; another example, the first function may be deployed simultaneously on the terminal device and the network device, and the terminal device and the network may each deploy part or all of the first function.

[0252] In some embodiments, the name of the first function is not limited, for example, it can be "AI function", "AI model", "AI module", "prediction function", "prediction model", "prediction module", etc.

[0253] In some embodiments, a terminal device and / or network device may perform beam prediction based on the first function. For example, if a terminal device originally needs to measure a total of M*N beam pairs (where M is the number of base station transmit beams and N is the number of terminal receive beams), the first function may reduce the number of beam pairs measured by the terminal device, but the first function may still be used to predict and output beam information (e.g., beam quality, optimal beam, etc.) for the M*N beam pairs.

[0254] For example, for spatial beam prediction, the terminal device may measure only a portion of the multiple beam pairs. For example, the beam pairs measured by the terminal device may be 1 / 8, 1 / 4, etc. of the M*N beam pairs. The beam measurement quality of the measured partial beam pairs is used as the input value of the above-mentioned first function. The corresponding output value can be predicted through the above-mentioned first function. The output value can be the beam information of the M*N beam pairs, such as the beam quality of at least one beam pair, and / or the identifiers of the best K beam pairs. The output value may also be beam information related to the beams transmitted by M base stations, such as the beam quality of at least one base station transmit beam, and / or the identifiers of the best K base stations transmit beams. The beam measurement quality may include L1-RSRP and / or L1-SINR. The above-mentioned beam pair identifier may be a TxRx beam ID, and the Tx beam ID may be a reference signal resource identifier.

[0255] Optionally, the input and output of the first function may not consider the beam quality or beam pair identification of the beam pair, but only consider the beam quality or beam identification of the downlink transmit beam, that is, the first function may be an AI function or AI model based on the downlink beam, not an AI function or AI model based on the beam pair.

[0256] In some embodiments, the terminal device and / or network device may perform beam prediction based on the first function. For example, if the terminal device originally needs to measure a total of M base station transmit beams, the first function may reduce the number of base station transmit beams measured by the terminal device, but the first function may still be used to predict and output beam information (e.g., beam quality, optimal beam, etc.) of the transmit beams of the M base stations.

[0257] For example, for spatial beam prediction, the terminal device may only measure a portion of the multiple transmit beams of the base station. For example, the beam measured by the terminal device may be 1 / 8, 1 / 4, etc. of the M beams. The beam measurement quality of the measured partial beams is used as the input value of the above-mentioned first function. The corresponding output value can be predicted through the above-mentioned first function. The output value can be the beam information of the M transmit beams, such as the beam quality of at least one beam, and / or the best K beam identifiers. The beam measurement quality may include L1-RSRP and / or L1-SINR. The above-mentioned beam identifier may be a Tx beam ID, and the Tx beam ID may be a reference signal resource identifier.

[0258] For another example, for time domain beam prediction, the terminal device can measure the beam pair or the beam quality of the transmission beam at a historical time to obtain the historical beam measurement quality, and use the historical beam measurement quality as the input value of the above-mentioned first function. The corresponding output value is predicted through the above-mentioned first function, and the output value can be the beam pair at a future time or the beam information of the base station transmission beam (such as beam quality, optimal beam, etc.). The beam measurement quality may include L1-RSRP and / or L1-SINR. The best beam may include the best beam pair identifier, which may be a TxRx beam ID, and Tx may be a reference signal resource identifier; the best beam may include the best beam identifier, which may be a reference signal resource identifier. The above-mentioned transmission beam may be a transmission beam sent by the base station to the terminal device.

[0259] In some embodiments, the beam set of the terminal device may include a first beam set setB and a second beam set setA.

[0260] The first beam set setB includes one or more first beams, and the first beam may be a beam corresponding to an input value of the first function. For example, the terminal device measures the beam measurement quality that can be obtained by the first beam in the first beam set setB.

[0261] The second beam set setA includes one or more second beams, and the second beam may be a beam corresponding to the output value of the first function.

[0262] In some embodiments, for spatial beam prediction, the first function may predict the measurement result of the second beam in the second beam set setA based on the measurement result of the first beam in the first beam set setB. For example, the terminal device may measure and obtain the measurement information of setB, and input the measured L1-RSRP and / or L1-SINR of setB into the first function, and the first function may predict and output the prediction information of setA. The measurement information may include the L1-RSRP and / or L1-SINR of the first beam in setB, and may also include the beam identifier or beam pair identifier of the first beam, and the prediction information may include the L1-RSRP and / or L1-SINR of the second beam in setA, and may also include the beam identifier or beam pair identifier of the second beam.

[0263] For spatial beam prediction, the relationship between the first beam set setB and the second beam set setA may include at least one of the following:

[0264] setB can be a subset of setA; for example, setA includes 32 reference signal resources (each reference signal resource corresponds to a beam direction), setB includes N reference signal resources, N can be less than 32, for example, N can be 16, 8 or 4; for another example, if the beam pair is considered, that is, the receiving beam of the terminal device is considered, assuming that the network device has 32 transmitting beams and the terminal device has 4 receiving beams, then setA can include 32*4 reference signal resources (one reference signal resource corresponds to one beam pair), setB can include N reference signal resources, N is less than 32*4, for example, N can be 32, 16 or 8.

[0265] setB is different from setA. The beam corresponding to setB is a wide beam, and the beam corresponding to setA is a narrow beam. Optionally, the beam coverage range of setB and setA can be the same or different. For example, setA includes 32 reference signal resources, each reference signal resource corresponds to a beam direction, and the coverage range of 32 reference signal resources is 120 degrees. setB includes N reference signal resources, for example, N=8, and the coverage range of N reference signal resources is also 120 degrees. That is to say, the beam directions of multiple reference signal resources in setB cover the beam directions of multiple reference signal resources in setA. It can also be understood that the relationship between 32 / N reference signal resources in setA and the same reference signal resource in setB is QCL Type D; similarly, beam pairs can also be considered.

[0266] In some embodiments, if there is no need to monitor the performance of the first function (for example, the first function has been trained in advance), the network device can periodically send the reference signal of the first beam set setB (the sending period can be the first period), and the terminal device can measure the L1-RSRP of the reference signal in setB, input it into the first function, and output the L1-RSRP of the beam or beam pair of the second beam set setA, or output the strongest N reference signal resource identifiers or beam pair identifiers among the multiple reference signals of the second beam set.

[0267] In some embodiments, if it is necessary to monitor the performance of the first function, in addition to sending the first beam set setB, the network device may also periodically send the reference signal of the second beam set setA. The period for sending setA may be the second period, and the period for sending setB may be the first period. The second period may be greater than the first period, for example, it may be a multiple of the first period, or it may not be a multiple of the first period. Optionally, the terminal device may only measure the result of setB and then input it into the first function to obtain the predicted beam information and report it to the network device. At the same time, it also measures the L1-RSRP of all reference signals in setA, and obtains the beam information as the beam information obtained by the traditional method and reports it to the network device. Optionally, if setB is a subset of setA, it is equivalent to the terminal device only needing to measure all beams or beam pairs of setA.

[0268] In some embodiments, for time-domain beam prediction, the first function may predict the measurement result of the second beam in the second beam set setA at a future time based on the measurement result of the first beam in the first beam set setB at a historical time. For example, the terminal device may measure the L1-RSRP and / or L1-SINR of the first beam in setB at a historical time, input the measured L1-RSRP and / or L1-SINR into the first function, and the first function may predict and output the L1-RSRP and / or L1-SINR of the second beam in setA at a future time.

[0269] For time-domain beam prediction, the relationship between the first beam set setB and the second beam set setA may include at least one of the following:

[0270] setB can be a subset of setA;

[0271] SetB is different from setA. The beam corresponding to setB is a wide beam, while the beam corresponding to setA is a narrow beam.

[0272] setB is the same as setA.

[0273] In some embodiments, if based on the first function (such as AI function and / or AI model), the reference signal at the future time may not be sent, and the beam information is obtained based on the AI ​​model output and reported to the network device.

[0274] In some embodiments, based on traditional methods, reference signals at future times also need to be transmitted. The terminal device measures the reference signals at future times and obtains beam information, which is then reported to the network device. Therefore, when monitoring the performance of the first function, time-domain beam prediction is similar to spatial-domain beam prediction. The network device can periodically transmit the transmit beams in setB and setA, and the terminal device can measure all beams or beam pairs in setB and setA.

[0275] In some embodiments, the terminal device may support one or more first functions, and different terminal devices may also support different first functions. Therefore, how the network device obtains information related to the first functions supported by the terminal device becomes an urgent problem to be solved.

[0276] FIG2A is an interactive schematic diagram of an information transmission method according to an embodiment of the present disclosure. The method can be executed by the above-mentioned communication system. As shown in FIG2A , the method may include:

[0277] Step S2101: The terminal device sends first information to the network device.

[0278] In some embodiments, the network device may receive the first information. For example, the network device may receive the first information sent by the terminal device.

[0279] In some embodiments, the first information may be information corresponding to the first function.

[0280] In some embodiments, the first function may be an AI function and / or AI model supported by the terminal device for performing beam prediction.

[0281] In some embodiments, the first information may be used to report information related to the first function.

[0282] In some embodiments, the name of the first information is not limited, for example, it can be "reporting information", "uplink information", "AI function information", "AI model information", etc.

[0283] In some embodiments, the first information may be carried in at least one of a radio resource control (RRC) message, a medium access control element (MAC CE), uplink control information (UCI), or other messages sent by the terminal device to the network device. Optionally, the first information may be carried via an RRC message.

[0284] In some embodiments, the first information is carried by a terminal capability report (UE capability report), that is, the first information can be reported based on a terminal capability reporting mechanism.

[0285] In this way, the terminal device can report the information corresponding to the first function through the terminal capability report, so that the network device can select a suitable function or model according to the information and requirements, thereby improving the flexibility and reliability of function management.

[0286] In some embodiments, the first function may include an AI function and / or an AI model.

[0287] In some embodiments, the aforementioned AI function may correspond to one or more AI models. For example, an AI function may be a function or module implemented by one or more AI models.

[0288] In other embodiments, the aforementioned AI model may also correspond to one or more AI functions. For example, an AI model may implement one or more AI functions.

[0289] In some other embodiments, the above-mentioned AI functions and AI models may correspond one to one.

[0290] In some embodiments, the first function may be deployed on a terminal device and / or a network device. For example, the first function may be deployed entirely on the terminal device; another example, the first function may be deployed entirely on the network device; another example, the first function may be deployed simultaneously on the terminal device and the network device, and the terminal device and the network may each deploy part or all of the first function.

[0291] In some embodiments, the name of the first function is not limited, for example, it can be "AI function", "AI model", "AI module", "prediction function", "prediction model", "prediction module", etc.

[0292] In some embodiments, the above-mentioned first information may be sent by the terminal device during or after the first function authentication process, and the first function authentication may include AI function authentication and / or AI model authentication.

[0293] In some embodiments of the present disclosure, the first information may include at least one of the following:

[0294] second information, the second information including information on performance monitoring of the first function supported by the terminal device;

[0295] third information, the third information including content information output by the first function supported by the terminal device;

[0296] Fourth information, the fourth information includes a function identifier of the first function supported by the terminal device.

[0297] For example, the first information may include only the second information. For another example, the first information may include only the third information. For another example, the first information may include the second information and the fourth information. For another example, the first information may include the third information and the fourth information.

[0298] Optionally, the second information, third information and fourth information may be carried by the same message or by different messages, which is not limited in the embodiment of the present disclosure.

[0299] In some embodiments, the multiple information included in the first information may include mandatory information and optional information.

[0300] For example, the second information may include multiple pieces of information, including mandatory information and optional information. For example, at least part of the information is mandatory to report, and part of the information is optional to report.

[0301] For another example, the third information may include multiple pieces of information, including mandatory information and optional information. For example, at least some of the information is mandatory to report, and some of the information is optional to report.

[0302] For another example, the fourth information may include multiple pieces of information, including mandatory information and optional information. For example, at least some of the information is mandatory to report, and some of the information is optional to report.

[0303] In some embodiments, the fourth information may further include other information about the first function. For example, the fourth information may include at least one of the following:

[0304] A function identifier, where the function identifier is used to determine a first function supported by the terminal device. For example, the function identifier includes an AI function identifier (Functionality ID) and / or an AI model identifier (Model ID);

[0305] An application example, where the application example is an example of applying the first function to perform beam prediction;

[0306] Beam-related information, where the beam-related information is used to determine a first beam (or beam pair) and / or a second beam (or beam pair), where the first beam (or beam pair) is the beam (or beam pair) corresponding to the input value of the first function, and the second beam (or beam pair) is the beam (or beam pair) corresponding to the output value of the first function;

[0307] Network coverage information, which is used to indicate coverage-related information of network devices, such as the deployment type of network devices (e.g., urban macro base station, urban micro base station, indoor base station, dense urban area, rural area, hotspot, etc.), and / or the inter-station spacing of network devices (e.g., 100 meters, 200 meters, 500 meters, 1000 meters, etc.);

[0308] Terminal distribution information, which is used to indicate the distribution of multiple terminal devices within the coverage area of ​​the network device.

[0309] In some embodiments, the above application examples may include any of the following:

[0310] Spatial beam prediction example;

[0311] Time domain beam prediction example;

[0312] Spatial domain beam prediction example and time domain beam prediction example.

[0313] In some embodiments, the beam-related information may include at least one of the following:

[0314] a first reference signal resource set, where reference signal resources in the first reference signal resource set correspond to a first beam (or beam pair), and the first beam (or beam pair) is a beam (or beam pair) corresponding to an input value of a first function; optionally, each reference signal resource in the first reference signal resource set may correspond to a reference signal resource identifier; optionally, a reference signal resource may correspond to a beam (or beam pair), and the first reference signal resource set may also be referred to as a first set, a first beam set, a first beam pair set, or setB;

[0315] a second reference signal resource set, wherein the reference signal resources of the second reference signal resource set correspond to a second beam (or beam pair), and the second beam (or beam pair) is the beam (or beam pair) corresponding to the output value of the first function; optionally, each reference signal resource in the second reference signal resource set may correspond to a reference signal resource identifier; optionally, the second reference signal resource set may also be referred to as a second set, a second beam set, a second beam pair set, or setA;

[0316] A set relationship, the set relationship comprising a relationship between a first reference signal resource set and a second reference signal resource set;

[0317] the number of beams (or beam pairs) included in the first reference signal resource set, or a range of the number;

[0318] the number of beams (or beam pairs) included in the second reference signal resource set, or a range of the number;

[0319] Position of the beam (beam pair) in the second reference signal resource set corresponding to the beam (beam pair) in the first reference signal resource set;

[0320] a ratio of the number of beams (beam pairs) in the first reference signal resource set to the number of beams (beam pairs) in the second reference signal resource set;

[0321] a mapping relationship between beams (beam pairs) in the first reference signal resource set and beams (beam pairs) in the second reference signal resource set;

[0322] Time information corresponding to the first reference signal resource set, where the time information may be a time quantity value, such as the number of historical measurement time instances;

[0323] time information corresponding to the second reference signal resource set, where the time information may be a time quantity value, such as a predicted number of future time instances;

[0324] A time pattern, where the time pattern is a pattern of time corresponding to the first reference signal resource set and time corresponding to the second reference signal resource set.

[0325] In some embodiments, the above-mentioned set relationship may include any of the following:

[0326] The first reference signal resource set is a subset of the second reference signal resource set. For example, the second reference signal resource set may include M reference signal resources (each reference signal resource corresponds to a beam direction), for example, M=32, and the first reference signal resource set may include N reference signal resources, where N is less than M, for example, N=8. Wherein, M and N are both positive integers;

[0327] The first reference signal resource set is different from the second reference signal resource set, the beam corresponding to the first reference signal resource set is a wide beam, and the beam corresponding to the second reference signal resource set is a narrow beam; optionally, the beam coverage ranges corresponding to the first reference signal resource set and the second reference signal resource set may be the same or different;

[0328] The first reference signal resource set is the same as the second reference signal resource set (in the time-domain beam prediction example, this set relationship may be effective).

[0329] In some embodiments of the present disclosure, the second information may include at least one of the following:

[0330] Performance monitoring type, which may be a type of performance monitoring supported by the terminal device;

[0331] Performance indicator type, which can be used to indicate the performance indicators supported by the terminal device;

[0332] Event type: This event type can be used to indicate the type of event that triggers performance monitoring.

[0333] In this way, information related to the performance monitoring of the first function supported by the terminal device can be reported through the second information.

[0334] In some embodiments, the second information may include a performance monitoring type, which may include any one of the following:

[0335] Type 1 performance monitoring: Optionally, the type 1 performance monitoring may be performance monitoring of network device control;

[0336] Type 2 performance monitoring: Optionally, the second type of performance monitoring may be performance monitoring controlled by the terminal device;

[0337] The third type of performance monitoring, optionally, the third type of performance monitoring is terminal device assisted performance monitoring.

[0338] In this way, the terminal device can report the supported performance monitoring type to the network device through the second information, and the network device can configure the performance monitoring type for the terminal device according to the second information, thereby improving the flexibility and reliability of performance monitoring.

[0339] In some embodiments of the present disclosure, for different performance monitoring types, the terminal device and the network device may perform the performance monitoring of the first function in different ways.

[0340] In some embodiments, based on the first type of performance monitoring, the terminal device and / or the network device may perform at least one of the following steps:

[0341] The network device may send a configuration (or signaling) to the terminal device instructing the terminal device to perform measurements and / or reports;

[0342] The terminal device can perform different optional operations: Option 1, the terminal device can send a report to the network device, such as sending measurement beam information and / or predicted beam information, where the measurement beam information includes measurement beam information measured by the terminal device (for example, the measured RSRP of setA), and the predicted beam information is the predicted beam information obtained by the terminal device based on the first function (for example, the predicted RSRP of setA). The measurement beam information and / or predicted beam information can be used by the network device to calculate the performance indicator; Option 2, the terminal device can calculate the performance indicator based on the measurement beam information and the predicted beam information, and send the performance indicator information and / or event information triggered based on the performance indicator information to the network device;

[0343] The network device can instruct the terminal device to perform a first operation on the first function. Optionally, the first operation can be called a lifecycle management (LCM) operation. The first operation can include any one of the following: selection, activation, deactivation, switching, and fallback, for example, selecting the first function, activating the first function, deactivating the first function, switching the first function, and falling back the first function (that is, switching the first function to a state at a historical time node, such as restoring it to an initial state).

[0344] In some other embodiments, based on the second type of performance monitoring, the terminal device and / or the network device may perform at least one of the following steps:

[0345] The terminal device sends a performance monitoring request (or indication, report) to the network device; optionally, the performance monitoring request may not be required in some cases;

[0346] The network device may send a configuration (or signaling) to the terminal device instructing the terminal device to perform measurements and / or reports;

[0347] The terminal device may calculate the performance index based on the predicted beam information and the measured beam information, and send the performance index information and / or event information triggered based on the performance index information to the network device;

[0348] If the first function is deployed on a terminal device, the terminal device may determine to perform a first operation on the first function. Optionally, the first operation may include any one of the following: selection, activation, deactivation, switching, and fallback.

[0349] In some other embodiments, based on the third type of performance monitoring, the terminal device and / or the network device may perform at least one of the following steps:

[0350] The network device may send a configuration (or signaling) to the terminal device instructing the terminal device to perform measurements and / or reports;

[0351] The terminal device may calculate the performance index based on the predicted beam information and the measured beam information, and send the performance index information and / or event information triggered based on the performance index information to the network device;

[0352] The network device may instruct the terminal device to perform a first operation on the first function. Optionally, the first operation may include any one of the following: selection, activation, deactivation, switching, and fallback.

[0353] In some embodiments, the third type of performance monitoring may be a subtype of the first type of performance monitoring.

[0354] In some embodiments, the second information may include a performance indicator type, and the performance indicator type may be used to indicate a performance indicator supported by the terminal device.

[0355] In some embodiments, the performance indicator may include at least one of the following:

[0356] Beam prediction accuracy, where the beam prediction accuracy is the probability that the predicted best reference signal resource includes the actual best reference signal resource, the predicted best reference signal resource is the best reference signal resource predicted by the first function, the actual best reference signal resource is the best reference signal resource actually measured by the terminal device, and the best reference signal resource is the top N reference signal resources with the best signal strength in the predicted second reference signal resource set, where N is a positive integer, such as 1, 2, 4, or 8; optionally, the best signal strength may be the maximum L1-RSRP or L1-SINR; optionally, the beam prediction accuracy may also be referred to as the prediction accuracy of top N beams (or beam pairs); optionally, the reference signal resource in this embodiment may correspond to a beam (or beam pair), for example, the predicted best reference signal resource corresponds to the predicted best beam (or beam pair), the actual best reference signal resource may correspond to the actual best beam (or beam pair), and the reference signal resource identifier may correspond to the beam identifier;

[0357] a first signal strength difference, where the first signal strength difference is the difference between the first signal strength and the second signal strength, where the first signal strength is the actual signal strength of the predicted best reference signal resource, and the second signal strength is the actual signal strength of the actual best reference signal resource; optionally, the first signal strength difference may also be referred to as an L1-RSRP difference;

[0358] a second signal strength difference, where the second signal strength difference is a difference between the first signal strength and the third signal strength, where the first signal strength is an actual signal strength of the predicted best reference signal resource, and the third signal strength is a predicted signal strength of the predicted best reference signal resource; optionally, the second signal strength difference may also be referred to as a Predicted L1-RSRP difference;

[0359] a third signal strength difference, where the third signal strength difference is a difference between the second signal strength and the fourth signal strength, where the second signal strength is the actual signal strength of the actual best reference signal resource, and the fourth signal strength is the predicted signal strength of the actual best reference signal resource;

[0360] a first signal strength prediction accuracy indicator, where the first signal strength prediction accuracy indicator is a probability of the first signal strength difference being within a first difference range, or an average value of the first signal strength difference, or a value of a cumulative distribution function (CDF) of the first signal strength difference at a first distribution ratio, where the first distribution ratio is greater than 0 and less than 1, for example, 5%, 10%, 90%, or 95%; optionally, the first difference range may be a threshold lower than a first threshold, higher than the first threshold, or within a certain interval, for example, the first difference range may be a range less than 1 dB; optionally, the first signal strength prediction accuracy indicator may also be referred to as a beam prediction accuracy of L1-RSRP within 1 dB;

[0361] a second signal strength prediction accuracy indicator, the second signal strength prediction accuracy indicator being a probability that the second signal strength difference is within the first difference range, or an average value of the second signal strength difference, or a value of a cumulative distribution function of the second signal strength difference at a first distribution ratio;

[0362] a third signal strength prediction accuracy indicator, the third signal strength prediction accuracy indicator being a probability that the third signal strength difference is within the first difference range, or an average value of the third signal strength difference, or a value of a cumulative distribution function of the third signal strength difference at a first distribution ratio;

[0363] a throughput difference, where the throughput difference is the difference between a first throughput and a second throughput, where the first throughput is a throughput calculated based on the first SINR, and the second throughput is a throughput calculated based on the second SINR, where the first SINR is an actual SINR of a predicted optimal reference signal resource, and the second SINR is an actual SINR of an actual optimal reference signal resource; optionally, a channel capacity can be calculated based on the SINR based on a Shannon capacity formula, and the difference in the channel capacities is the throughput difference;

[0364] A throughput prediction accuracy indicator, where the throughput prediction accuracy indicator is a probability that the throughput difference is within a second difference range, or an average value of the throughput difference, or a value of a cumulative distribution function of the throughput difference at a second distribution ratio, where the second distribution ratio is greater than 0 and less than 1; optionally, the throughput prediction accuracy indicator may also be referred to as an Average UE throughput difference;

[0365] a reference signal overhead, where the reference signal overhead is used to indicate the number of reference signal resources required by the first function. Optionally, factors affecting the reference signal overhead may include the size of the first reference signal resource set corresponding to the model input and the number of historical measurement times during time domain prediction;

[0366] Uplink resource overhead, where the uplink resource overhead is used to indicate the amount of uplink resources occupied by information that needs to be reported to the network device for performing prediction and / or performance monitoring of the first function; optionally, the uplink resources may include uplink control information resources and / or uplink data resources; optionally, if the first function is deployed on the network device, the measurement results of the first reference signal resource set may be reported to the network device, and the uplink resource overhead may be the uplink resources required for reporting the measurement results (e.g., uplink control information resources);

[0367] Predicted delay, where the predicted delay is the time taken by the first function to perform beam prediction; optionally, the predicted delay may be expressed in milliseconds or microseconds;

[0368] Input data distribution information, where the input data distribution information is distribution information of the input data of the first function; optionally, the input data distribution information may include a value of the input data corresponding to a third distribution ratio (e.g., 5%, 50%, 95%) of a cumulative distribution function of the input data (e.g., measured L1-RSRP);

[0369] Output data distribution information, where the output data distribution information is distribution information of the output data of the first function; optionally, the output data distribution information may include a value of the output data corresponding to a fourth distribution ratio (e.g., 5%, 50%, 95%) of a cumulative distribution function of the output data (e.g., the predicted L1-RSRP);

[0370] Model complexity, which may include at least one of the model size and the model computational load, and the model computational load may include the model floating point operations (FLOPs) and / or other indicators characterizing the computational load; optionally, the model complexity may also be referred to as complexity, functional complexity, etc.

[0371] In some embodiments, the signal strength difference or throughput difference may be an absolute value, regardless of positive or negative, wherein the signal strength difference includes the first signal strength difference, the second signal strength difference, or the third signal strength difference.

[0372] In some embodiments, the above-mentioned performance indicator can be the accuracy of the beam information output after multiple derivations based on the first function, for example, it can be a probability (ratio). Taking the beam prediction accuracy as an example, the prediction accuracy can mean that the best N reference signal resource identifiers predicted by the first function include the actual best reference signal resource identifier, and the reference signal resource identifier can be a synchronization signal block (SSB) identifier, a channel state information reference signal (CSI-RS) identifier, and a sounding reference signal (SRS) identifier; where N is a positive integer. For example, N can be 1 or greater than 1; optionally, the probability corresponding to the beam prediction accuracy can be the ratio between the number of times the predicted best reference signal resource includes the actual best reference signal resource and the total number of predictions. For example, if 100 predictions are made, and the predicted best reference signal resource obtained 90 times includes the actual best reference signal resource, and the predicted best reference signal resource obtained 10 times does not include the actual best reference signal resource, then the probability is 90%, that is, the beam prediction accuracy is 90%.

[0373] In this way, the terminal device can report the supported performance indicator types to the network device through the second information, and the network device can configure the reported performance indicators for the terminal device based on the second information, thereby improving the flexibility and reliability of performance monitoring.

[0374] In some embodiments, the second information may include an event type, which may be used to indicate the type of event that triggers performance monitoring and is supported by the terminal device.

[0375] In some embodiments, the event type includes at least one of the following:

[0376] A first type event, where the first type event is used to indicate that a performance indicator of an activated first function is worse than a first threshold, where the first threshold may be a configuration parameter of the first type event;

[0377] A second type event, where the second type event is used to indicate that a performance indicator of the deactivated first function is better than a second threshold, where the second threshold may be a configuration parameter of the second type event;

[0378] A third type of event, where the third type of event is used to indicate that a performance indicator of the activated first function is worse than a first threshold, and a performance indicator of the deactivated first function is better than a second threshold. The first threshold and the second threshold may be configuration parameters of the third type of event. Optionally, the first threshold may be worse than the second threshold.

[0379] The fourth type of event is used to indicate that the first difference is better than the fourth threshold, the first difference is the difference between the second performance indicator and the first performance indicator, the first performance indicator is the performance indicator of the deactivated first function, and the second performance indicator is the performance indicator of the activated first function. The fourth threshold can be a configuration parameter of the fourth type of event.

[0380] Optionally, the above-mentioned worse than may be less than or greater than, and the meaning of “worse than” may be different according to different performance indicators.

[0381] Optionally, the above-mentioned “better than” may mean greater than or less than, and the meaning of “better than” may also be different depending on different performance indicators.

[0382] In one implementation, the term "better than" means greater than, and the term "worse than" means less than. For example, if the performance indicator is beam prediction accuracy, the term "better than" means greater than, and the term "worse than" means less than. That is, the greater the beam prediction accuracy (the closer it is to 100%), the better (better) the performance of the first function.

[0383] In another implementation, the term "better than" is "less than," and the term "worse than" is "greater than." For example, if the performance indicator is a signal strength difference or a throughput difference, then "better than" is "less than," and "worse than" is "greater than." That is, the smaller the signal strength difference or the throughput difference (the closer to 0), the better (better) the performance of the first function.

[0384] Optionally, the triggering conditions of the above events may be different for different performance indicators.

[0385] In this way, the terminal device can report the supported event types to the network device through the second information, and the network device can configure the terminal device with events for triggering reporting based on the second information, thereby improving the flexibility and reliability of performance monitoring.

[0386] In some embodiments of the present disclosure, the third information may include at least one of the following:

[0387] A reference signal resource identifier, optionally, the reference signal resource identifier may be a beam identifier;

[0388] Signal strength, optionally, the signal strength may be one or more, one signal strength may be a signal strength of a reference signal resource, and the signal strength may be L1-RSRP or L1-SINR;

[0389] The confidence level corresponding to the signal strength.

[0390] In some embodiments, the confidence level may be used to indicate whether the signal strength is an actually measured signal strength or a predicted signal strength.

[0391] In some embodiments, the signal strength is a predicted signal strength, and the confidence level may be used to indicate the prediction accuracy corresponding to the signal strength. Alternatively, when the signal strength is a predicted signal strength, the confidence level may be used to indicate the prediction accuracy corresponding to the signal strength. Alternatively, the prediction accuracy may include a prediction accuracy rate, such as 70%, 80%, or 90%.

[0392] In one implementation, the third information may include at least one reference signal resource identifier, a signal strength corresponding to each reference signal resource identifier, and a confidence level corresponding to each signal strength.

[0393] In another implementation manner, the third information may include at least one reference signal resource identifier and a signal strength corresponding to each reference signal resource identifier.

[0394] In another implementation, the third information may include at least one signal strength, which may indicate the signal strength of a corresponding reference signal resource according to a specific order. For example, the third information may include 32 signal strengths, each signal strength indicating the signal strengths of the first reference signal resource to the thirty-second reference signal resource in sequence. The specific order may be a preset order or an order configured by the network device.

[0395] In yet another implementation, the third information may include a signal strength corresponding to at least one reference signal resource and a confidence level corresponding to each signal strength.

[0396] Step S2102: The terminal device and the network device perform performance monitoring of the first function.

[0397] In some embodiments, the terminal device and the network device may perform a first operation on the first function based on the results of the performance monitoring.

[0398] In some embodiments, the first operation may include any one of the following: selection, activation, deactivation, switching, and rollback. For example, selecting the first function, activating the first function, deactivating the first function, switching the first function, and rolling back the first function (i.e., switching the first function to a state at a historical time node, such as restoring to an initial state).

[0399] In some embodiments, the first function is deployed on a terminal device, and the terminal device can autonomously perform a first operation on the first function. Optionally, the terminal device can send notification information corresponding to the first operation to the network device before, after, or at the same time as performing the first operation.

[0400] In other embodiments, the first function is deployed in a terminal device and / or a network device. The terminal device may perform a first operation on the first function according to an instruction of the network device. Optionally, the terminal device may notify the network device of the execution result of the first operation.

[0401] In some embodiments, the above steps S2101 and S2102 can be executed in an interchangeable order or simultaneously.

[0402] In some embodiments, the above steps S2101 and S2102 are optional steps.

[0403] In some embodiments, reference may be made to other optional implementations described before or after the description corresponding to FIG. 2A .

[0404] Optionally, the specific implementation of step S2102 may be different for different performance monitoring types.

[0405] In some embodiments of the present disclosure, the performance monitoring type is first-type performance monitoring, and step S2102 may include at least one of the following sub-steps:

[0406] S210211. The network device sends the fifth information to the terminal device.

[0407] In some embodiments, the terminal device may receive fifth information sent by the network device.

[0408] In some embodiments, the fifth information may be used to instruct the terminal device to perform measurement and / or reporting.

[0409] In some embodiments, the fifth information can be used to instruct the terminal device to perform performance monitoring of the first function.

[0410] In some embodiments, the fifth information may be a configuration or signaling instructing the terminal device to perform measurement and / or reporting.

[0411] In some embodiments, the name of the fifth information is not limited, for example, it can be "configuration information", "configuration signaling", "measurement configuration", "measurement report configuration", "performance monitoring indication information", etc.

[0412] S210212. The terminal device sends sixth information to the network device.

[0413] In some embodiments, the network device may receive sixth information sent by the terminal device.

[0414] In some embodiments, the sixth information may include a report of the terminal device performing the above-mentioned measurement acquisition.

[0415] In some embodiments, the sixth information may include information obtained by monitoring the performance of the terminal device when executing the first function.

[0416] In some embodiments, the name of the sixth information is not limited, and may be, for example, "measurement report", "performance monitoring report", etc.

[0417] In some embodiments, the sixth information may include at least one of the following:

[0418] Measurement beam information, where the measurement beam information includes beam information measured by the terminal device;

[0419] Predicted beam information, where the predicted beam information is beam information predicted by the terminal device based on the first function;

[0420] performance indicator information, where the performance indicator information is used to determine at least one of prediction accuracy, complexity, and signaling overhead of the first function;

[0421] Event information, which is information about the triggering event based on which the terminal device triggers the sixth information.

[0422] For example, the sixth information may include measurement beam information and predicted beam information.

[0423] For another example, the sixth information may include performance indicator information.

[0424] For another example, the sixth information may include event information.

[0425] For another example, the sixth information may include performance indicator information and event information.

[0426] In some embodiments, the performance indicator information may include the value of at least one performance indicator supported by the terminal device indicated by the above-mentioned performance indicator type.

[0427] In some embodiments, the trigger event may be at least one of the first type event, the second type event, the third type event, and the fourth type event indicated by the event type. The event information may include an event type and / or event parameters.

[0428] S210213. The network device sends the seventh information to the terminal device.

[0429] In some embodiments, the terminal device may receive the seventh information sent by the network device.

[0430] In some embodiments, the seventh information can be used to instruct the terminal device to perform a first operation on the first function, where the first operation includes any one of the following: selection, activation, deactivation, switching, and fallback.

[0431] In some embodiments, the name of the seventh information is not limited, and may be, for example, "control information", "function management information", "first function lifecycle management information", etc.

[0432] In some embodiments, the network device may determine the first operation based on the sixth information and send the seventh information.

[0433] S210214. The terminal device performs the first operation on the first function according to the seventh information.

[0434] In some embodiments, any one or more of the above steps S210211 to S210214 can be implemented as independent embodiments.

[0435] In some embodiments, the above steps S210211 to S210214 can be executed in a swapped order or simultaneously.

[0436] In some embodiments, the above steps S210211 to S210214 are all optional steps.

[0437] In this way, the terminal device and the network device can support the first type of performance monitoring.

[0438] In some embodiments of the present disclosure, the performance monitoring type is second-type performance monitoring, and step S2102 may include at least one of the following sub-steps:

[0439] S210221. The terminal device sends the eleventh information to the network device.

[0440] In some embodiments, the network device may receive the eleventh information sent by the terminal device.

[0441] In some embodiments, the eleventh information is used to request to start performance monitoring of the first function.

[0442] In some embodiments, the name of the eleventh information is not limited, and may be, for example, "performance monitoring request information", "performance monitoring indication information", "performance monitoring report information", etc.

[0443] Optionally, step S210221 is an optional step. For example, in some cases, the eleventh information may not need to be exchanged.

[0444] S210222. The network device sends twelfth information to the terminal device.

[0445] In some embodiments, the terminal device may receive the twelfth information sent by the network device.

[0446] In some embodiments, the twelfth information may be used to respond to the eleventh information.

[0447] In some embodiments, the name of the twelfth information is not limited, for example, it can be "configuration information", "configuration signaling", "measurement configuration", "measurement report configuration", "performance monitoring indication information", etc.

[0448] Optionally, the twelfth information may be the same as or different from the fifth information in the aforementioned embodiment of the present disclosure.

[0449] S210223. The terminal device obtains performance indicator information corresponding to the first function.

[0450] In some embodiments, the performance indicator information is used to determine at least one of prediction accuracy, complexity, and signaling overhead of the first function.

[0451] In some embodiments, the performance indicator information may include the value of at least one performance indicator supported by the terminal device indicated by the above-mentioned performance indicator type.

[0452] S210224. The terminal device sends the eighth information to the network device.

[0453] In some embodiments, the network device may receive the eighth information sent by the terminal device.

[0454] In some embodiments, the eighth information may include at least one of the following: performance indicator information, and information about a triggering event based on which the eighth information is triggered.

[0455] In some embodiments, the name of the eighth information is not limited, and may be, for example, "event report", "performance indicator report", etc.

[0456] S210225. The terminal device determines to perform a first operation of the first function.

[0457] In some embodiments, the first operation includes any one of the following: selection, activation, deactivation, switching, and fallback.

[0458] S210226. The terminal device sends ninth information to the network device.

[0459] In some embodiments, the network device may receive ninth information sent by the terminal device.

[0460] In some embodiments, the ninth information may be used to indicate the first operation determined by the terminal device.

[0461] In some embodiments, the ninth information may be used to instruct the terminal device to determine a first operation to perform the first function.

[0462] In some embodiments, the terminal device may send ninth information to the network device when determining to perform the first operation of the first function.

[0463] In some embodiments, the name of the ninth information is not limited, for example, it can be "operation notification information", "function operation notification information", "function operation instruction information", etc.

[0464] S210227. The network device sends the tenth information to the terminal device.

[0465] In some embodiments, the terminal device may receive the tenth information sent by the network device.

[0466] In some embodiments, the tenth message is a response message to the ninth message.

[0467] In some embodiments, the name of the tenth information is not limited, and may be, for example, "operation response information", "function operation response information", etc.

[0468] S210228. The terminal device performs a first operation on the first function.

[0469] In some embodiments, the above S210226 and S210227 can be omitted.

[0470] In some embodiments, the terminal device may perform the first operation before, after, or simultaneously with receiving the tenth information.

[0471] In some embodiments, the terminal device may perform the first operation before, after, or simultaneously with sending the ninth information.

[0472] In some embodiments, any one or more of the above steps S210221 to S210228 can be implemented as independent embodiments.

[0473] In some embodiments, the above steps S210221 to S210228 can be executed in a swapped order or simultaneously.

[0474] In some embodiments, the above steps S210221 to S210228 are all optional steps.

[0475] In this way, terminal devices and network devices can support the second type of performance monitoring.

[0476] In some embodiments of the present disclosure, the performance monitoring type is the third type performance monitoring, and step S2102 may include at least one of the following sub-steps:

[0477] S210231. The terminal device obtains performance indicator information corresponding to the first function.

[0478] In some embodiments, the performance indicator information may be used to determine the prediction accuracy of the first function.

[0479] S210232. The terminal device sends the thirteenth information to the network device.

[0480] In some embodiments, the network device may receive the thirteenth information sent by the terminal device.

[0481] In some embodiments, the thirteenth information may include at least one of the following: performance indicator information, and information about a triggering event based on which the thirteenth information is triggered.

[0482] In some embodiments, the name of the thirteenth information is not limited, and may be, for example, "event report", "performance indicator report", etc.

[0483] In some embodiments, the above steps S210231 and S210232 can be implemented as independent embodiments.

[0484] In some embodiments, the above steps S210231 and S210232 can be executed in an interchanged order or simultaneously.

[0485] In some embodiments, the above steps S210231 and S210232 are optional steps.

[0486] In some embodiments, step S210231 and step S210232 may be combined with one or more steps S210211 to S210214 in the aforementioned embodiments of the present disclosure as a new embodiment.

[0487] In this way, terminal devices and network devices can support the third type of performance monitoring.

[0488] FIG2B is an interactive diagram illustrating an information transmission method according to an embodiment of the present disclosure. As shown in FIG2B , the present disclosure embodiment relates to an information transmission method, which can be executed by a communication system and may include:

[0489] Step S2201: The terminal device sends first information to the network device.

[0490] The optional implementation of step S2201 can refer to the optional implementation of step S2101 in Figure 2A and other related parts in the embodiment involved in Figure 2A, which will not be repeated here.

[0491] In some embodiments, the embodiment shown in FIG. 2B may also be combined with any one or more steps in the embodiment shown in FIG. 2A to form a new embodiment.

[0492] FIG3A is a flow chart of an information transmission method according to an embodiment of the present disclosure. As shown in FIG3A , the embodiment of the present disclosure relates to an information transmission method, which can be executed by a terminal device. The method may include:

[0493] Step S3101: Send the first information.

[0494] The optional implementation of step S3101 can refer to the optional implementation of step S2101 in Figure 2A and other related parts in the embodiment involved in Figure 2A, which will not be repeated here.

[0495] In some embodiments, the terminal device may send the first information to the network device, but is not limited thereto. The terminal device may also send the first information to other entities.

[0496] Step S3102: Execute performance monitoring of the first function.

[0497] The optional implementation of step S3102 can refer to the optional implementation of step S2102 in Figure 2A and other related parts in the embodiment involved in Figure 2A, which will not be repeated here.

[0498] In some embodiments, the above steps S3101 and S3102 can be executed in an interchanged order or simultaneously.

[0499] In some embodiments, the above steps S3101 and S3102 are optional steps.

[0500] FIG3B is a flow chart of an information transmission method according to an embodiment of the present disclosure. As shown in FIG3B , the embodiment of the present disclosure relates to an information transmission method, which can be executed by a terminal device. The method may include:

[0501] Step S3201: Send the first information.

[0502] The optional implementation of step S3201 can be found in step S2101 of FIG. 2A , the optional implementation of step S3101 of FIG. 3A , and other related parts in the embodiments involved in FIG. 2A and FIG. 3A , which will not be repeated here.

[0503] In some embodiments, the embodiment shown in FIG. 3B may also be combined with any one or more steps in the embodiment shown in FIG. 3A to form a new embodiment.

[0504] In some embodiments, the first information is information corresponding to a first function, and the first function is an artificial intelligence AI function and / or AI model supported by the terminal device for performing beam prediction.

[0505] In some embodiments, the first information includes at least one of the following:

[0506] second information, the second information including information on performance monitoring of the first function supported by the terminal device;

[0507] third information, the third information including content information output by the first function supported by the terminal device;

[0508] Fourth information, the fourth information includes a function identifier of the first function supported by the terminal device.

[0509] In some embodiments, the second information includes a performance monitoring type, and the performance monitoring type includes any one of the following:

[0510] Type 1 performance monitoring;

[0511] Type II performance monitoring;

[0512] The third type of performance monitoring.

[0513] In some embodiments, the performance monitoring type is first type performance monitoring, and the method further includes at least one of the following:

[0514] receiving fifth information sent by the network device, where the fifth information is used to instruct the terminal device to perform measurement and / or reporting;

[0515] Sending sixth information to the network device, where the sixth information is a report obtained by the terminal device performing the measurement;

[0516] receiving seventh information sent by the network device, where the seventh information is used to instruct the terminal device to perform a first operation on the first function, where the first operation includes any one of the following: selection, activation, deactivation, switching, and fallback;

[0517] The first operation is performed on the first function according to the seventh information.

[0518] In some embodiments, the sixth information includes at least one of the following:

[0519] Measurement beam information, where the measurement beam information includes beam information measured by the terminal device;

[0520] Predicted beam information, where the predicted beam information is beam information predicted by the terminal device based on the first function;

[0521] performance indicator information, where the performance indicator information is used to determine at least one of prediction accuracy, complexity, and signaling overhead of the first function;

[0522] Event information, where the event information is information about a triggering event based on which the terminal device triggers the sixth information.

[0523] In some embodiments, the performance monitoring type is second type performance monitoring, and the method further includes:

[0524] Obtaining performance indicator information corresponding to the first function, where the performance indicator information is used to determine at least one of prediction accuracy, complexity, and signaling overhead of the first function;

[0525] Sending eighth information to the network device, where the eighth information includes at least one of the following: the performance indicator information, and information of a triggering event based on which the eighth information is triggered.

[0526] In some embodiments, the performance monitoring type is second type performance monitoring, and the method further includes:

[0527] Determine a first operation for performing the first function, where the first operation includes any one of the following: selection, activation, deactivation, switching, and rollback;

[0528] Ninth information is sent to the network device.

[0529] In some embodiments, the method further comprises:

[0530] receiving tenth information sent by the network device, where the tenth information is response information to the ninth information;

[0531] The first operation is performed on the first function.

[0532] In some embodiments, the method further comprises:

[0533] Sending eleventh information to the network device, where the eleventh information is used to request to start performance monitoring of the first function;

[0534] Receive twelfth information sent by the network device, where the twelfth information is used to respond to the eleventh information.

[0535] In some embodiments, the performance monitoring type is third type performance monitoring, and the method further includes at least one of the following:

[0536] Obtaining performance indicator information corresponding to the first function, where the performance indicator information is used to determine at least one of prediction accuracy, complexity, and signaling overhead of the first function;

[0537] Thirteenth information is sent to the network device, where the thirteenth information includes at least one of the following: the performance indicator information, and information of a triggering event based on which the thirteenth information is triggered.

[0538] In some embodiments, the second information includes a performance indicator type, and the performance indicator type is used to indicate a performance indicator supported by the terminal device.

[0539] In some embodiments, the performance indicator includes at least one of the following:

[0540] a beam prediction accuracy rate, where the beam prediction accuracy rate is a probability that the predicted best reference signal resource includes an actual best reference signal resource, where the predicted best reference signal resource is the best reference signal resource predicted by the first function, the actual best reference signal resource is the best reference signal resource actually measured by the terminal device, and the best reference signal resource is the top N reference signal resources with the best signal strength in the predicted second reference signal resource set, where N is a positive integer;

[0541] a first signal strength difference, where the first signal strength difference is a difference between a first signal strength and a second signal strength, the first signal strength being the actual signal strength of the predicted best reference signal resource, and the second signal strength being the actual signal strength of the actual best reference signal resource;

[0542] a second signal strength difference, where the second signal strength difference is a difference between a first signal strength and a third signal strength, where the first signal strength is an actual signal strength of the predicted best reference signal resource, and the third signal strength is a predicted signal strength of the predicted best reference signal resource;

[0543] a third signal strength difference, where the third signal strength difference is a difference between a second signal strength and a fourth signal strength, where the second signal strength is an actual signal strength of the actual best reference signal resource, and the fourth signal strength is a predicted signal strength of the actual best reference signal resource;

[0544] a first signal strength prediction accuracy indicator, where the first signal strength prediction accuracy indicator is a probability of the first signal strength difference being within a first difference range, or an average value of the first signal strength difference, or a value of a cumulative distribution function of the first signal strength difference at a first distribution ratio, where the first distribution ratio is greater than 0 and less than 1;

[0545] a second signal strength prediction accuracy indicator, where the second signal strength prediction accuracy indicator is a probability that the second signal strength difference is within a first difference range, or an average value of the second signal strength difference, or a value of a cumulative distribution function of the second signal strength difference at a first distribution ratio;

[0546] a third signal strength prediction accuracy indicator, wherein the third signal strength prediction accuracy indicator is a probability that the third signal strength difference is within a first difference range, or an average value of the third signal strength difference, or a value of a cumulative distribution function of the third signal strength difference at a first distribution ratio;

[0547] a throughput difference, where the throughput difference is a difference between a first throughput and a second throughput, where the first throughput is a throughput calculated based on a first SINR, and the second throughput is a throughput calculated based on a second SINR, where the first SINR is an actual SINR of the predicted best reference signal resource, and the second SINR is an actual SINR of the actual best reference signal resource;

[0548] a throughput prediction accuracy indicator, the throughput prediction accuracy indicator being a probability of the throughput difference being within a second difference range, or an average value of the throughput differences, or a value of a cumulative distribution function of the throughput differences at a second distribution ratio, where the second distribution ratio is greater than 0 and less than 1;

[0549] a reference signal overhead, where the reference signal overhead is used to indicate the number of reference signal resources required for the first function;

[0550] Uplink resource overhead, where the uplink resource overhead is used to indicate the amount of uplink resources occupied by information that needs to be reported to the network device for performing prediction and / or performance monitoring of the first function;

[0551] Prediction delay, where the prediction delay is the time taken by the first function to perform beam prediction;

[0552] Input data distribution information, where the input data distribution information is distribution information of input data of the first function;

[0553] Output data distribution information, where the output data distribution information is distribution information of output data of the first function;

[0554] Model complexity.

[0555] In some embodiments, the second information includes an event type, where the event type is used to indicate a type of event supported by the terminal device that triggers the performance monitoring.

[0556] In some embodiments, the event type includes at least one of the following:

[0557] A first type event, wherein the first type event is used to indicate that a performance indicator of an activated first function is worse than a first threshold;

[0558] a second type of event, where the second type of event is used to indicate that a performance indicator of the deactivated first function is better than a second threshold;

[0559] A third type of event, the third type of event being used to indicate that a performance indicator of the activated first function is worse than a first threshold, and a performance indicator of the deactivated first function is better than a second threshold;

[0560] The fourth type of event is used to indicate that the first difference is better than the fourth threshold, the first difference is the difference between the second performance indicator and the first performance indicator, the first performance indicator is the performance indicator of the deactivated first function, and the second performance indicator is the performance indicator of the activated first function.

[0561] In some embodiments, the third information includes at least one of the following:

[0562] Reference signal resource identifier;

[0563] Signal strength;

[0564] The confidence level corresponding to the signal strength.

[0565] In some embodiments,

[0566] The confidence level is used to indicate whether the signal strength is an actually measured signal strength or a predicted signal strength; or

[0567] The signal strength is a predicted signal strength, and the confidence level is used to indicate a prediction accuracy corresponding to the signal strength.

[0568] In some embodiments, the first information is carried by a terminal capability report.

[0569] In some embodiments, the first information includes multiple pieces of information including mandatory information and optional information.

[0570] In some embodiments, the first function is deployed on the terminal device and / or the network device.

[0571] FIG4A is a flow chart of an information transmission method according to an embodiment of the present disclosure. As shown in FIG4A , the present disclosure embodiment relates to an information transmission method, which can be executed by a network device, and the method includes:

[0572] Step S4101: Obtain first information.

[0573] The optional implementation of step S4101 can refer to the optional implementation of step S2101 in Figure 2A and other related parts in the embodiment involved in Figure 2A, which will not be repeated here.

[0574] In some embodiments, the network device may receive the first information sent by the terminal device, but is not limited thereto. The network device may also receive the first information sent by other entities.

[0575] In some embodiments, the network device may obtain first information specified by a protocol.

[0576] In some embodiments, the network device may perform processing to obtain the first information.

[0577] Step S4102: Execute performance monitoring of the first function.

[0578] The optional implementation of step S4102 can refer to the optional implementation of step S2102 in Figure 2A and other related parts in the embodiment involved in Figure 2A, which will not be repeated here.

[0579] In some embodiments, the above steps S4101 and S4102 can be executed in an interchanged order or simultaneously.

[0580] In some embodiments, the above steps S4101 and S4102 are optional steps.

[0581] FIG4B is a flow chart of an information transmission method according to an embodiment of the present disclosure. As shown in FIG4B , the embodiment of the present disclosure relates to an information transmission method, which can be executed by a network device. The method may include:

[0582] Step S4201: Obtain first information.

[0583] The optional implementation of step S4201 can be found in step S2101 of FIG. 2A , the optional implementation of step S4101 of FIG. 4A , and other related parts in the embodiments involved in FIG. 2A and FIG. 4A , which will not be repeated here.

[0584] In some embodiments, the embodiment shown in FIG. 4B may also be combined with any one or more steps in the embodiment shown in FIG. 4A to form a new embodiment.

[0585] In some embodiments, the first information is information corresponding to a first function, and the first function is an artificial intelligence AI function and / or AI model supported by the terminal device for performing beam prediction.

[0586] In some embodiments, the first information includes at least one of the following:

[0587] second information, the second information including information on performance monitoring of the first function supported by the terminal device;

[0588] third information, the third information including content information output by the first function supported by the terminal device;

[0589] Fourth information, the fourth information includes a function identifier of the first function supported by the terminal device.

[0590] In some embodiments, the second information includes a performance monitoring type, and the performance monitoring type includes any one of the following:

[0591] Type 1 performance monitoring;

[0592] Type II performance monitoring;

[0593] The third type of performance monitoring.

[0594] In some embodiments, the performance monitoring type is first type performance monitoring, and the method further includes at least one of the following:

[0595] Sending fifth information to the terminal device, where the fifth information is used to instruct the terminal device to perform measurement and / or reporting;

[0596] receiving sixth information sent by the terminal device, where the sixth information is a report obtained by the terminal device performing the measurement;

[0597] determining a first operation according to the sixth information;

[0598] Send seventh information to the terminal device, where the seventh information is used to instruct the terminal device to perform the first operation on the first function, where the first operation includes any one of the following: selection, activation, deactivation, switching, and rollback.

[0599] In some embodiments, the sixth information includes at least one of the following:

[0600] Measurement beam information, where the measurement beam information includes beam information measured by the terminal device;

[0601] Predicted beam information, where the predicted beam information is beam information predicted by the terminal device based on the first function;

[0602] performance indicator information, where the performance indicator information is used to determine at least one of prediction accuracy, complexity, and signaling overhead of the first function;

[0603] Event information, where the event information is information about a triggering event based on which the terminal device triggers the sixth information.

[0604] In some embodiments, the performance monitoring type is second type performance monitoring, and the method further includes:

[0605] Receive the eighth information sent by the terminal device, the eighth information including at least one of the following: performance indicator information, information of a triggering event based on which the eighth information is triggered, and the performance indicator information is used to determine at least one of the prediction accuracy, complexity and signaling overhead of the first function.

[0606] In some embodiments, the performance monitoring type is second type performance monitoring, and the method further includes:

[0607] Receive ninth information sent by the terminal device, where the ninth information is used to instruct the terminal device to determine a first operation to perform the first function, where the first operation includes any one of the following: selection, activation, deactivation, switching, and fallback.

[0608] In some embodiments, the method further comprises:

[0609] Send tenth information to the terminal device, where the tenth information is response information to the ninth information.

[0610] In some embodiments, the method further comprises:

[0611] receiving an eleventh message sent by the terminal device, where the eleventh message is used to request to start performance monitoring of the first function;

[0612] Twelfth information is sent to the terminal device, where the twelfth information is used to respond to the eleventh information.

[0613] In some embodiments, the performance monitoring type is third type performance monitoring, and the method further includes:

[0614] Receive the thirteenth information sent by the terminal device, the thirteenth information including at least one of the following: performance indicator information, information of a triggering event on which the thirteenth information is triggered, and the performance indicator information is used to determine at least one of the prediction accuracy, complexity and signaling overhead of the first function.

[0615] In some embodiments, the second information includes a performance indicator type, and the performance indicator type is used to indicate a performance indicator supported by the terminal device.

[0616] In some embodiments, the performance indicator includes at least one of the following:

[0617] a beam prediction accuracy rate, where the beam prediction accuracy rate is a probability that the predicted best reference signal resource includes an actual best reference signal resource, where the predicted best reference signal resource is the best reference signal resource predicted by the first function, the actual best reference signal resource is the best reference signal resource actually measured by the terminal device, and the best reference signal resource is the top N reference signal resources with the best signal strength in the predicted second reference signal resource set, where N is a positive integer;

[0618] a first signal strength difference, where the first signal strength difference is a difference between a first signal strength and a second signal strength, the first signal strength being the actual signal strength of the predicted best reference signal resource, and the second signal strength being the actual signal strength of the actual best reference signal resource;

[0619] a second signal strength difference, where the second signal strength difference is a difference between a first signal strength and a third signal strength, where the first signal strength is an actual signal strength of the predicted best reference signal resource, and the third signal strength is a predicted signal strength of the predicted best reference signal resource;

[0620] a third signal strength difference, where the third signal strength difference is a difference between a second signal strength and a fourth signal strength, where the second signal strength is an actual signal strength of the actual best reference signal resource, and the fourth signal strength is a predicted signal strength of the actual best reference signal resource;

[0621] a first signal strength prediction accuracy indicator, where the first signal strength prediction accuracy indicator is a probability of the first signal strength difference being within a first difference range, or an average value of the first signal strength difference, or a value of a cumulative distribution function of the first signal strength difference at a first distribution ratio, where the first distribution ratio is greater than 0 and less than 1;

[0622] a second signal strength prediction accuracy indicator, where the second signal strength prediction accuracy indicator is a probability that the second signal strength difference is within a first difference range, or an average value of the second signal strength difference, or a value of a cumulative distribution function of the second signal strength difference at a first distribution ratio;

[0623] a third signal strength prediction accuracy indicator, wherein the third signal strength prediction accuracy indicator is a probability that the third signal strength difference is within a first difference range, or an average value of the third signal strength difference, or a value of a cumulative distribution function of the third signal strength difference at a first distribution ratio;

[0624] a throughput difference, where the throughput difference is a difference between a first throughput and a second throughput, where the first throughput is a throughput calculated based on a first SINR, and the second throughput is a throughput calculated based on a second SINR, where the first SINR is an actual SINR of the predicted best reference signal resource, and the second SINR is an actual SINR of the actual best reference signal resource;

[0625] a throughput prediction accuracy indicator, the throughput prediction accuracy indicator being a probability of the throughput difference being within a second difference range, or an average value of the throughput differences, or a value of a cumulative distribution function of the throughput differences at a second distribution ratio, where the second distribution ratio is greater than 0 and less than 1;

[0626] a reference signal overhead, where the reference signal overhead is used to indicate the number of reference signal resources required for the first function;

[0627] Uplink resource overhead, where the uplink resource overhead is used to indicate the amount of uplink resources occupied by information that needs to be reported to the network device for performing prediction and / or performance monitoring of the first function;

[0628] Prediction delay, where the prediction delay is the time taken by the first function to perform beam prediction;

[0629] Input data distribution information, where the input data distribution information is distribution information of input data of the first function;

[0630] Output data distribution information, where the output data distribution information is distribution information of output data of the first function;

[0631] Model complexity.

[0632] In some embodiments, the second information includes an event type, where the event type is used to indicate a type of event supported by the terminal device that triggers the performance monitoring.

[0633] In some embodiments, the event type includes at least one of the following:

[0634] A first type event, wherein the first type event is used to indicate that a performance indicator of an activated first function is worse than a first threshold;

[0635] a second type of event, where the second type of event is used to indicate that a performance indicator of the deactivated first function is better than a second threshold;

[0636] A third type of event, the third type of event being used to indicate that a performance indicator of the activated first function is worse than a first threshold, and a performance indicator of the deactivated first function is better than a second threshold;

[0637] The fourth type of event is used to indicate that the first difference is better than the fourth threshold, the first difference is the difference between the second performance indicator and the first performance indicator, the first performance indicator is the performance indicator of the deactivated first function, and the second performance indicator is the performance indicator of the activated first function.

[0638] In some embodiments, the third information includes at least one of the following:

[0639] Reference signal resource identifier;

[0640] Signal strength;

[0641] The confidence level corresponding to the signal strength.

[0642] In some embodiments,

[0643] The confidence level is used to indicate whether the signal strength is an actually measured signal strength or a predicted signal strength; or

[0644] The signal strength is a predicted signal strength, and the confidence level is used to indicate a prediction accuracy corresponding to the signal strength.

[0645] In some embodiments, the first information is carried by a terminal capability report.

[0646] In some embodiments, the first information includes multiple pieces of information including mandatory information and optional information.

[0647] In some embodiments, the first function is deployed on the terminal device and / or the network device.

[0648] Figure 5 is a flow chart of an information transmission method according to an embodiment of the present disclosure. As shown in Figure 5, the embodiment of the present disclosure relates to an information transmission method, which can be executed by a communication system and may include:

[0649] Step S5101: The terminal device reports information corresponding to the first function.

[0650] In some embodiments, the first function is an AI functionality or an AI model.

[0651] In some embodiments, the information corresponding to the first function may be referred to as first information.

[0652] In some embodiments, the information corresponding to the first function includes second information when the corresponding first function performs performance monitoring.

[0653] In some embodiments, the second information may include a performance monitoring type, which may include any one of the following:

[0654] Type 1 performance monitoring; optionally, the type 1 performance monitoring may be performance monitoring of network device control;

[0655] Type 2 performance monitoring; optionally, the type 2 performance monitoring may be performance monitoring controlled by the terminal device;

[0656] The third type of performance monitoring: Optionally, the third type of performance monitoring may be performance monitoring in which the network device controls and the terminal device reports performance indicator information or event information.

[0657] In this way, the terminal device can report the supported performance monitoring type to the network device through the second information, and the network device can configure the performance monitoring type for the terminal device according to the second information, thereby improving the flexibility and reliability of performance monitoring.

[0658] In some embodiments of the present disclosure, for different performance monitoring types, the terminal device and the network device may perform the performance monitoring of the first function in different ways.

[0659] In some embodiments, based on the first type of performance monitoring, the terminal device and / or the network device may perform at least one of the following steps:

[0660] The network device may send a configuration (or signaling) to the terminal device instructing the terminal device to perform measurements and / or reports;

[0661] The terminal device can perform different optional operations: Option 1, the terminal device can send a report to the network device, such as sending measurement beam information and / or predicted beam information, where the measurement beam information includes measurement beam information measured by the terminal device (for example, the measured RSRP of setA), and the predicted beam information is the predicted beam information obtained by the terminal device based on the first function (for example, the predicted RSRP of setA). The measurement beam information and / or predicted beam information can be used by the network device to calculate the performance indicator; Option 2, the terminal device can calculate the performance indicator based on the measurement beam information and the predicted beam information, and send the performance indicator information and / or event information triggered based on the performance indicator information to the network device;

[0662] The network device can instruct the terminal device to perform a first operation on the first function. Optionally, the first operation can be called a lifecycle management (LCM) operation. The first operation can include any one of the following: selection, activation, deactivation, switching, and fallback, for example, selecting the first function, activating the first function, deactivating the first function, switching the first function, and falling back the first function (that is, switching the first function to a state at a historical time node, such as restoring it to an initial state).

[0663] In some other embodiments, based on the second type of performance monitoring, the terminal device and / or the network device may perform at least one of the following steps:

[0664] The terminal device sends a performance monitoring request (or indication, report) to the network device; optionally, the performance monitoring request may not be required in some cases;

[0665] The network device may send a configuration (or signaling) to the terminal device instructing the terminal device to perform measurements and / or reports;

[0666] The terminal device may calculate the performance index based on the predicted beam information and the measured beam information, and send the performance index information and / or event information triggered based on the performance index information to the network device;

[0667] If the first function is deployed on a terminal device, the terminal device may determine to perform a first operation on the first function. Optionally, the first operation may include any one of the following: selection, activation, deactivation, switching, and fallback.

[0668] In some other embodiments, based on the third type of performance monitoring, the terminal device and / or the network device may perform at least one of the following steps:

[0669] The network device may send a configuration (or signaling) to the terminal device instructing the terminal device to perform measurements and / or reports;

[0670] The terminal device may calculate the performance index based on the predicted beam information and the measured beam information, and send the performance index information and / or event information triggered based on the performance index information to the network device;

[0671] The network device may instruct the terminal device to perform a first operation on the first function. Optionally, the first operation may include any one of the following: selection, activation, deactivation, switching, and fallback.

[0672] In some embodiments, the third type of performance monitoring may be a subtype of the first type of performance monitoring.

[0673] In some embodiments, the second information may include at least one of the following performance metrics supported by the terminal:

[0674] Beam prediction accuracy of top 1 / K beam (pair): Correct prediction means that the predicted strongest beam (pair) ID contains the actual strongest beam (pair) ID or the predicted strongest beam (pair) ID is contained in the actual strongest N beam (pair) IDs. The downlink transmit beam ID can be equivalent to the reference signal resource ID, such as the SSB ID or CSI-RS ID or SRS ID. The downlink receive beam ID is the Rx beam ID of the terminal. The beam pair ID is the ID corresponding to the combination of the downlink transmit beam and the downlink receive beam. The strongest means that the L1-RSRP or L1-SINR is the strongest. Optionally, this indicator can be the accuracy of the beam information output based on multiple derivations of the model, such as a ratio.

[0675] Beam prediction accuracy within 1 dB of L1-RSRP: This metric measures the accuracy of the predicted optimal beam (or pair) when the actual L1-RSRP is within 1 dB of the actual L1-RSRP of the optimal beam. Alternatively, this metric can be the accuracy of beam information output from multiple model derivations, for example, as a ratio.

[0676] L1-RSRP Difference: The difference between the predicted L1-RSRP of the best beam (or beam pair) and the actual L1-RSRP of the best beam (or beam pair). For example, the average value is X dB, or the value at the 5% percentile of the cumulative distribution function is Y dB. Optionally, it can also be the percentage of L1-RSRP differences below or above a threshold.

[0677] Predicted L1-RSRP difference: The difference between the actual L1-RSRP of the predicted best beam (or beam pair) and the predicted L1-RSRP of the predicted best beam (or beam pair), such as an average of X dB or a cumulative distribution function of Y dB at the 5% percentile. Optionally, this metric can also be the percentage of predicted L1-RSRP differences below or above a threshold.

[0678] Average UE throughput, or the 5% cumulative distribution function (CDF) throughput, is calculated by calculating the SINRs of the predicted and actual strongest beams (or beam pairs). This metric is derived from the Shannon capacity difference between the two beams (or beam pairs).

[0679] Reference signal overhead: refers to the amount of reference signal resources required for the first function. The main influencing factors include the size of setB corresponding to the model input and the number of historical measurement times during time domain prediction.

[0680] Uplink control information overhead: If the first function is deployed on the network device (eg, NW-side model), the measurement results of setB need to be reported to the network device, ie, the signaling overhead of the report.

[0681] The predicted delay can be t milliseconds.

[0682] Model input data distribution.

[0683] Model output data distribution.

[0684] In some embodiments, the second information may include an event supported by the terminal, and the event may be an event for triggering performance monitoring reporting.

[0685] Optionally, each performance metric can correspond to at least one of the following four events:

[0686] Event #1: The performance of the currently active first functionality (functionality / model) is lower than the threshold.

[0687] Event #2: the performance of the currently inactive first function is higher than the threshold.

[0688] Event #3, the performance of the currently activated first function is lower than the threshold, and the performance of the currently deactivated first function is higher than the threshold.

[0689] Event #4: the performance of the currently deactivated first function is higher than the performance of the currently activated first function by an offset.

[0690] It's important to note that a high performance indicator value may indicate good performance. For example, a high beam prediction accuracy value indicates good model performance, but a high L1-RSRP difference value indicates poor model performance. Therefore, the event description can be different for different performance indicators.

[0691] In some embodiments, the information corresponding to the first function may further include third information, which may include content output by a model supported by the terminal. For example, the third information may include at least one of the following:

[0692] Reference signal resource identifier (beam ID);

[0693] L1-RSRP corresponding to each reference signal resource identifier;

[0694] The confidence level corresponding to each L1-RSRP.

[0695] In one implementation, the confidence level may be used to indicate whether the L1-RSRP is actually measured or predicted.

[0696] In one implementation, if the L1-RSRP is predicted, the confidence level may indicate the prediction accuracy of the L1-RSRP.

[0697] In some embodiments, the information corresponding to the first function may further include fourth information, and the fourth information may include at least one of the following:

[0698] AI function identification;

[0699] An application example corresponding to the AI ​​function, wherein the application example may include any one of the following: spatial beam prediction, time beam prediction, spatial beam prediction, and time beam prediction;

[0700] The relationship between the first set (setB) and the second set (setA) corresponding to the AI ​​function may include at least one of the following: SetB is a subset of setA (both spatial and time domain beam prediction are applicable); SetB and setA are different (both spatial and time domain beam prediction are applicable); SetB and setA are the same (only time domain beam prediction is applicable);

[0701] The number of beams (beam pairs) in a first set, or the range of the number, where the first set is the set of beams (beam pairs) corresponding to the model input value;

[0702] Positions of beams (beam pairs) in a first set corresponding to beams (beam pairs) in a second set, where the first set is a subset of the second set;

[0703] The number of beams (beam pairs) in the second set, where the second set is the set of beams (beam pairs) corresponding to the model output;

[0704] a ratio of the number of beams (beam pairs) in a first set to the number of beams (beam pairs) in a second set, where the first set and the second set are different;

[0705] a mapping relationship between beams (beam pairs) in a first set and beams (beam pairs) in a second set, where the first set and the second set are different;

[0706] The time quantity value corresponding to the second set (the number of predicted future time instances) may only be applicable to time domain beam prediction;

[0707] The pattern of the time corresponding to the first set and the time corresponding to the second set may be applicable only to time-domain beam prediction;

[0708] Base station coverage related parameter information: The base station coverage related parameter information includes deployment type: Urban macro, Urban micro, indoor, dense urban, rural; the base station coverage related parameter information may also include the inter-base station spacing, such as ISD of 200m, 500m, 1000m, 100m, etc.

[0709] User distribution.

[0710] In some embodiments, at least part of the second information, third information, and fourth information is mandatory to report, and part of the information is optional to report.

[0711] In some embodiments, the above information may be reported based on a mechanism for reporting terminal capabilities (UE capability).

[0712] In some embodiments, the first function may include an AI function and an AI model, and the terminal device may perform AI function identification (functionality identification) and / or AI model identification (model identification).

[0713] In some embodiments, AI function authentication simply informs the network device that it supports a certain AI function. The network device does not need to be informed whether the terminal device supports one or multiple AI models under this AI function. Therefore, when the network device instructs the terminal device to activate the AI ​​function, the terminal device can independently determine which AI model to activate under this AI function. Furthermore, the terminal device does not need to inform the network device when switching between different AI models under this AI function.

[0714] In some embodiments, AI model authentication can inform a network device that the terminal device supports a certain AI model. The AI ​​model can correspond to one or more AI functions. The network device can instruct the terminal to activate or deactivate the AI ​​model.

[0715] In this way, through the reporting of AI function or model authentication, the terminal device can report the performance monitoring type, performance indicator or event type, and supported model output supported by the terminal corresponding to the function or model, so that the network device can select the appropriate function or model according to the needs.

[0716] In some embodiments of the present disclosure, a communication system is provided, which may include a terminal device and a network device, wherein the terminal device can execute the information transmission method executed by the terminal device in the aforementioned embodiment of the present disclosure; the network device can execute the information transmission method executed by the network device in the aforementioned embodiment of the present disclosure.

[0717] The embodiments of the present disclosure further provide an apparatus for implementing any of the above methods. For example, an apparatus is provided, comprising units or modules for implementing each step performed by a terminal device in any of the above methods. For another example, another apparatus is provided, comprising units or modules for implementing each step performed by a network device (e.g., an access network device, a core network function node, a core network device, etc.) in any of the above methods.

[0718] It should be understood that the division of the various units or modules in the above device is merely a division of logical functions. In actual implementation, they may be fully or partially integrated into a physical entity, or they may be physically separated. In addition, the units or modules in the device may be implemented in the form of a processor calling software: for example, the device includes a processor, the processor is connected to a memory, and the memory stores instructions. The processor calls the instructions stored in the memory to implement any of the above methods or implement the functions of the various units or modules of the above device, wherein the processor is, for example, a general-purpose processor, such as a central processing unit (CPU) or a microprocessor, and the memory is a memory within the device or a memory outside the device. Alternatively, the units or modules in the device can be implemented in the form of hardware circuits, and the functions of some or all of the units or modules can be realized by designing the hardware circuits. The above-mentioned hardware circuits can be understood as one or more processors; for example, in one implementation, the above-mentioned hardware circuit is an application-specific integrated circuit (ASIC), and the functions of some or all of the above units or modules are realized by designing the logical relationship of the components in the circuit; for example, in another implementation, the above-mentioned hardware circuit can be realized by a programmable logic device (PLD). Taking a field programmable gate array (FPGA) as an example, it can include a large number of logic gate circuits, and the connection relationship between the logic gate circuits is configured by configuring the configuration file, thereby realizing the functions of some or all of the above units or modules. All units or modules of the above devices can be realized in the form of software called by the processor, or in the form of hardware circuits, or in part by the form of software called by the processor, and the rest by hardware circuits.

[0719] In the embodiments of the present disclosure, the processor is a circuit with signal processing capabilities. In one implementation, the processor can be a circuit with instruction reading and execution capabilities, such as a central processing unit (CPU), a microprocessor, a graphics processing unit (GPU) (which can be understood as a microprocessor), or a digital signal processor (DSP); in another implementation, the processor can implement certain functions through the logical relationship of the hardware circuit, and the logical relationship of the above hardware circuit is fixed or reconfigurable, such as a hardware circuit implemented by a processor as an application-specific integrated circuit (ASIC) or a programmable logic device (PLD), such as an FPGA. In a reconfigurable hardware circuit, the process of the processor loading a configuration document to implement the hardware circuit configuration can be understood as the process of the processor loading instructions to implement the functions of some or all of the above units or modules. In addition, it can also be a hardware circuit designed for artificial intelligence, which can be understood as ASIC, such as a neural network processing unit (NPU), a tensor processing unit (TPU), a deep learning processing unit (DPU), etc.

[0720] Figure 6A is a structural diagram of a terminal device proposed in an embodiment of the present disclosure. As shown in Figure 6A, the terminal device 101 may include: at least one of a transceiver module 211, a processing module 212, etc. In some embodiments, the transceiver module 211 is configured to send a first message to a network device, wherein the first information is information corresponding to a first function, and the first function is an artificial intelligence AI function and / or AI model supported by the terminal device for performing beam prediction; wherein the first information includes at least one of the following: second information, wherein the second information includes information supported by the terminal device for performance monitoring of the first function; third information, wherein the third information includes content information output by the first function supported by the terminal device; fourth information, wherein the fourth information includes a function identifier of the first function supported by the terminal device. Optionally, the transceiver module 211 can be used to execute at least one of the communication steps such as sending and / or receiving performed by the terminal device in any of the above methods (for example, step S2101, but not limited thereto), which will not be repeated here. Optionally, the processing module 212 may be configured to execute at least one of the other steps (such as step S2102 , but not limited thereto) executed by the terminal device in any of the above methods, which will not be described in detail here.

[0721] Figure 6B is a structural diagram of a network device proposed in an embodiment of the present disclosure. As shown in Figure 6B, the network device 102 may include: at least one of a transceiver module 221, a processing module 222, etc. In some embodiments, the transceiver module 221 is configured to receive first information sent by a terminal device, wherein the first information is information corresponding to a first function, and the first function is an artificial intelligence AI function and / or AI model supported by the terminal device for performing beam prediction; wherein the first information includes at least one of the following: second information, wherein the second information includes information supported by the terminal device for performance monitoring of the first function; third information, wherein the third information includes content information output by the first function supported by the terminal device; fourth information, wherein the fourth information includes a function identifier of the first function supported by the terminal device. Optionally, the transceiver module 221 can be used to execute at least one of the communication steps such as sending and / or receiving performed by the network device in any of the above methods (for example, step S2101, but not limited thereto), which will not be repeated here. Optionally, the processing module 222 may be configured to execute at least one of the other steps (such as step S2102 , but not limited thereto) executed by the network device in any of the above methods, which will not be described in detail here.

[0722] In some embodiments, the transceiver module may include a transmitting module and / or a receiving module, and the transmitting module and the receiving module may be separate or integrated. Optionally, the transceiver module may be interchangeable with the transceiver.

[0723] In some embodiments, the processing module can be a single module or can include multiple submodules. Optionally, the multiple submodules respectively execute all or part of the steps required to be executed by the processing module. Optionally, the processing module can be interchangeable with the processor.

[0724] Figure 7A is a schematic diagram of the structure of the communication device proposed in the embodiment of the present disclosure. The communication device 300 can be a network device (such as an access network device, a core network device, etc.), or a terminal device (such as a user device, etc.), or a chip, chip system, or processor that supports the network device to implement any of the above methods, or a chip, chip system, or processor that supports the terminal device to implement any of the above methods. The communication device 300 can be used to implement the method described in the above method embodiment. For details, please refer to the description of the above method embodiment.

[0725] As shown in Figure 7A, the communication device 300 includes one or more processors 301. The processor 301 can be a general-purpose processor or a dedicated processor, for example, a baseband processor or a central processing unit. The baseband processor can be used to process the communication protocol and communication data, and the central processing unit can be used to control the communication device (such as a base station, a baseband chip, a terminal device, a terminal device chip, a DU or a CU, etc.), execute programs, and process program data. Optionally, the communication device 300 can be used to perform any of the above methods. Optionally, one or more processors 301 are used to call instructions to enable the communication device 300 to perform any of the above methods.

[0726] In some embodiments, the communication device 300 may further include one or more transceivers 302. When the communication device 300 includes one or more transceivers 302, the transceiver 302 may perform at least one of the communication steps such as sending and / or receiving in the above method (for example, step S2101, but not limited thereto), and the processor 301 may perform at least one of the other steps (for example, step S2102, but not limited thereto).

[0727] In some embodiments, a transceiver may include a receiver and / or a transmitter. The receiver and transmitter may be separate or integrated. Optionally, the terms transceiver, transceiver unit, transceiver, transceiver circuit, interface circuit, and interface may be used interchangeably; the terms transmitter, transmitting unit, transmitter, and transmitting circuit may be used interchangeably; and the terms receiver, receiving unit, receiver, and receiving circuit may be used interchangeably.

[0728] In some embodiments, the communication device 300 also includes one or more memories 303 for storing data. Alternatively, all or part of the memories 303 may be located outside the communication device 300. In alternative embodiments, the communication device 300 may include one or more interface circuits 304. Optionally, the interface circuits 304 are connected to the memories 303 and can be used to receive data from the memories 303 or other devices, or to send data to the memories 303 or other devices. For example, the interface circuits 304 can read data stored in the memories 303 and send the data to the processor 301.

[0729] The communication device 300 described in the above embodiment may be a network device or a terminal device, but the scope of the communication device 300 described in the present disclosure is not limited thereto, and the structure of the communication device 300 may not be limited by FIG. 7A. The communication device may be an independent device or may be part of a larger device. For example, the communication device 300 may be: 1) an independent integrated circuit IC, or a chip, or a chip system or subsystem; (2) a collection of one or more ICs, optionally, the above IC collection may also include a storage component for storing data or programs; (3) an ASIC, such as a modem; (4) a module that can be embedded in other devices; (5) a receiver, a terminal device, an intelligent terminal device, a cellular phone, a wireless device, a handheld device, a mobile unit, an in-vehicle device, a network device, a cloud device, an artificial intelligence device, etc.; (6) others, etc.

[0730] FIG7B is a schematic diagram of the structure of the chip 400 proposed in an embodiment of the present disclosure. If the communication device 300 can be a chip or a chip system, please refer to the schematic diagram of the structure of the chip 400 shown in FIG7B , but the present disclosure is not limited thereto.

[0731] The chip 400 includes one or more processors 401 , and the chip 400 is configured to execute any of the above methods.

[0732] In some embodiments, chip 400 further includes one or more interface circuits 404. Alternatively, the terms interface circuit, interface, and transceiver pins may be used interchangeably. In some embodiments, chip 400 further includes one or more memories 403 for storing data. Alternatively, all or part of memories 403 may be located external to chip 400.

[0733] Optionally, the interface circuit 404 is connected to the memory 403. The interface circuit 404 can be used to receive data from the memory 403 or other devices, and the interface circuit 404 can be used to send data to the memory 403 or other devices. For example, the interface circuit 404 can read data stored in the memory 403 and send the data to the processor 401.

[0734] In some embodiments, the interface circuit 404 performs at least one of the communication steps (e.g., step S2101, but not limited thereto) in the above method, such as sending and / or receiving. For example, the interface circuit 404 performing the communication steps (e.g., sending and / or receiving) in the above method means that the interface circuit 404 performs data exchange between the processor 401, chip 400, memory 403, or a transceiver device. In some embodiments, the processor 401 may perform at least one of the other steps (e.g., step S2102, but not limited thereto).

[0735] The modules and / or devices described in various embodiments, such as virtual devices, physical devices, and chips, can be arbitrarily combined or separated according to circumstances. Optionally, some or all steps can also be performed collaboratively by multiple modules and / or devices, which is not limited here.

[0736] The embodiments of the present disclosure further provide a storage medium having instructions stored thereon. When the instructions are executed on the communication device 300, the communication device 300 executes any of the above methods. Optionally, the storage medium is an electronic storage medium. Optionally, the storage medium is a computer-readable storage medium, but is not limited thereto and may also be a storage medium readable by other devices. Optionally, the storage medium may be a non-transitory storage medium, but is not limited thereto and may also be a transient storage medium.

[0737] The embodiments of the present disclosure also provide a program product that, when executed by the communication device 300, causes the communication device 300 to perform any of the above optional methods. Optionally, the program product may be a computer program product. Optionally, the computer program product may include a computer program and / or instructions that, when executed by the communication device, implement any of the above optional methods.

[0738] The embodiment of the present disclosure also provides a computer program, which, when executed on a computer, enables the computer to execute any of the above optional methods.

Claims

1. An information transmission method, characterized in that: Executed by a terminal device, the method includes: Sending first information to the network device, where the first information is information corresponding to a first function, where the first function is an artificial intelligence (AI) function and / or AI model supported by the terminal device for performing beam prediction; The first information includes at least one of the following: second information, the second information including information on performance monitoring of the first function supported by the terminal device; third information, the third information including content information output by the first function supported by the terminal device; Fourth information, the fourth information includes a function identifier of the first function supported by the terminal device.

2. The method according to claim 1, characterized in that The second information includes a performance monitoring type, and the performance monitoring type includes any one of the following: Type 1 performance monitoring; Type II performance monitoring; The third type of performance monitoring.

3. The method according to claim 2, characterized in that The performance monitoring type is first type performance monitoring, and the method further includes at least one of the following: receiving fifth information sent by the network device, where the fifth information is used to instruct the terminal device to perform measurement and / or reporting; Sending sixth information to the network device, where the sixth information is a report obtained by the terminal device performing the measurement; receiving seventh information sent by the network device, where the seventh information is used to instruct the terminal device to perform a first operation on the first function, where the first operation includes any one of the following: selection, activation, deactivation, switching, and fallback; The first operation is performed on the first function according to the seventh information.

4. The method according to claim 3, characterized in that The sixth information includes at least one of the following: Measurement beam information, where the measurement beam information includes beam information measured by the terminal device; Predicted beam information, where the predicted beam information is beam information predicted by the terminal device based on the first function; performance indicator information, where the performance indicator information is used to determine at least one of prediction accuracy, complexity, and signaling overhead of the first function; Event information, where the event information is information about a triggering event based on which the terminal device triggers the sixth information.

5. The method according to claim 2, characterized in that The performance monitoring type is second-type performance monitoring, and the method further includes at least one of the following: Obtaining performance indicator information corresponding to the first function, where the performance indicator information is used to determine at least one of prediction accuracy, complexity, and signaling overhead of the first function; Sending eighth information to the network device, where the eighth information includes at least one of the following: the performance indicator information, and information of a triggering event based on which the eighth information is triggered.

6. The method according to claim 2, characterized in that The performance monitoring type is second-type performance monitoring, and the method further includes at least one of the following: Determine a first operation for performing the first function, where the first operation includes any one of the following: selection, activation, deactivation, switching, and rollback; Ninth information is sent to the network device, where the ninth information is used to indicate the first operation determined by the terminal device.

7. The method according to claim 6, characterized in that The method further comprises: receiving tenth information sent by the network device, where the tenth information is response information to the ninth information; The first operation is performed on the first function.

8. The method according to any one of claims 5 to 7, characterized in that The method further comprises at least one of the following: Sending eleventh information to the network device, where the eleventh information is used to request to start performance monitoring of the first function; Receive twelfth information sent by the network device, where the twelfth information is used to respond to the eleventh information.

9. The method according to claim 2, characterized in that The performance monitoring type is the third type of performance monitoring, and the method further includes at least one of the following: Obtaining performance indicator information corresponding to the first function, where the performance indicator information is used to determine at least one of prediction accuracy, complexity, and signaling overhead of the first function; Thirteenth information is sent to the network device, where the thirteenth information includes at least one of the following: the performance indicator information, and information of a triggering event based on which the thirteenth information is triggered.

10. The method according to any one of claims 1 to 9, characterized in that The second information includes a performance indicator type, and the performance indicator type is used to indicate a performance indicator supported by the terminal device.

11. The method according to claim 10, characterized in that The performance indicators include at least one of the following: a beam prediction accuracy rate, where the beam prediction accuracy rate is a probability that the predicted best reference signal resource includes an actual best reference signal resource, where the predicted best reference signal resource is the best reference signal resource predicted by the first function, the actual best reference signal resource is the best reference signal resource actually measured by the terminal device, and the best reference signal resource is the top N reference signal resources with the best signal strength in the predicted second reference signal resource set, where N is a positive integer; a first signal strength difference, where the first signal strength difference is a difference between a first signal strength and a second signal strength, the first signal strength being the actual signal strength of the predicted best reference signal resource, and the second signal strength being the actual signal strength of the actual best reference signal resource; a second signal strength difference, where the second signal strength difference is a difference between a first signal strength and a third signal strength, where the first signal strength is an actual signal strength of the predicted best reference signal resource, and the third signal strength is a predicted signal strength of the predicted best reference signal resource; a third signal strength difference, where the third signal strength difference is a difference between a second signal strength and a fourth signal strength, where the second signal strength is an actual signal strength of the actual best reference signal resource, and the fourth signal strength is a predicted signal strength of the actual best reference signal resource; a first signal strength prediction accuracy indicator, where the first signal strength prediction accuracy indicator is a probability of the first signal strength difference being within a first difference range, or an average value of the first signal strength difference, or a value of a cumulative distribution function of the first signal strength difference at a first distribution ratio, where the first distribution ratio is greater than 0 and less than 1; a second signal strength prediction accuracy indicator, where the second signal strength prediction accuracy indicator is a probability that the second signal strength difference is within a first difference range, or an average value of the second signal strength difference, or a value of a cumulative distribution function of the second signal strength difference at a first distribution ratio; a third signal strength prediction accuracy indicator, wherein the third signal strength prediction accuracy indicator is a probability that the third signal strength difference is within a first difference range, or an average value of the third signal strength difference, or a value of a cumulative distribution function of the third signal strength difference at a first distribution ratio; a throughput difference, where the throughput difference is a difference between a first throughput and a second throughput, where the first throughput is a throughput calculated based on a first SINR, and the second throughput is a throughput calculated based on a second SINR, where the first SINR is an actual SINR of the predicted best reference signal resource, and the second SINR is an actual SINR of the actual best reference signal resource; a throughput prediction accuracy indicator, the throughput prediction accuracy indicator being a probability of the throughput difference being within a second difference range, or an average value of the throughput differences, or a value of a cumulative distribution function of the throughput differences at a second distribution ratio, where the second distribution ratio is greater than 0 and less than 1; a reference signal overhead, where the reference signal overhead is used to indicate the number of reference signal resources required for the first function; Uplink resource overhead, where the uplink resource overhead is used to indicate the amount of uplink resources occupied by information that needs to be reported to the network device for performing prediction and / or performance monitoring of the first function; Prediction delay, where the prediction delay is the time taken by the first function to perform beam prediction; Input data distribution information, where the input data distribution information is distribution information of input data of the first function; Output data distribution information, where the output data distribution information is distribution information of output data of the first function; Model complexity.

12. The method according to any one of claims 1 to 11, characterized in that The second information includes an event type, where the event type is used to indicate a type of event supported by the terminal device that triggers the performance monitoring.

13. The method according to claim 12, characterized in that The event type includes at least one of the following: A first type event, wherein the first type event is used to indicate that a performance indicator of an activated first function is worse than a first threshold; a second type of event, where the second type of event is used to indicate that a performance indicator of the deactivated first function is better than a second threshold; The third type of event is used to indicate that the performance indicator of the activated first function is worse than the first threshold, and the deactivated The performance index of the first function is better than the second threshold; The fourth type of event is used to indicate that the first difference is better than the fourth threshold, the first difference is the difference between the second performance indicator and the first performance indicator, the first performance indicator is the performance indicator of the deactivated first function, and the second performance indicator is the performance indicator of the activated first function.

14. The method according to any one of claims 1 to 13, characterized in that The third information includes at least one of the following: Reference signal resource identifier; Signal strength; The confidence level corresponding to the signal strength.

15. The method according to claim 14, characterized in that The confidence level is used to indicate whether the signal strength is an actually measured signal strength or a predicted signal strength; or The signal strength is a predicted signal strength, and the confidence level is used to indicate a prediction accuracy corresponding to the signal strength.

16. The method according to any one of claims 1 to 15, characterized in that The first information is carried by a terminal capability report.

17. The method according to any one of claims 1 to 16, characterized in that The multiple information included in the first information includes mandatory information and optional information.

18. The method according to any one of claims 1 to 17, characterized in that The first function is deployed on the terminal device and / or the network device.

19. An information transmission method, characterized in that: Executed by a network device, the method includes: Receiving first information sent by a terminal device, where the first information is information corresponding to a first function, where the first function is an artificial intelligence (AI) function and / or AI model supported by the terminal device for performing beam prediction; The first information includes at least one of the following: second information, the second information including information on performance monitoring of the first function supported by the terminal device; third information, the third information including content information output by the first function supported by the terminal device; Fourth information, the fourth information includes a function identifier of the first function supported by the terminal device.

20. The method according to claim 19, characterized in that The second information includes a performance monitoring type, and the performance monitoring type includes any one of the following: Type 1 performance monitoring; Type II performance monitoring; The third type of performance monitoring.

21. The method according to claim 20, characterized in that The performance monitoring type is first type performance monitoring, and the method further includes at least one of the following: Sending fifth information to the terminal device, where the fifth information is used to instruct the terminal device to perform measurement and / or reporting; receiving sixth information sent by the terminal device, where the sixth information is a report obtained by the terminal device performing the measurement; determining a first operation according to the sixth information; Send seventh information to the terminal device, where the seventh information is used to instruct the terminal device to perform the first operation on the first function, where the first operation includes any one of the following: selection, activation, deactivation, switching, and rollback.

22. The method according to claim 21, characterized in that The sixth information includes at least one of the following: Measurement beam information, where the measurement beam information includes beam information measured by the terminal device; Predicted beam information, where the predicted beam information is beam information predicted by the terminal device based on the first function; performance indicator information, where the performance indicator information is used to determine at least one of prediction accuracy, complexity, and signaling overhead of the first function; Event information, where the event information is information about a triggering event based on which the terminal device triggers the sixth information.

23. The method according to claim 20, characterized in that The performance monitoring type is second type performance monitoring, and the method further includes: Receive the eighth information sent by the terminal device, the eighth information including at least one of the following: performance indicator information, triggering the eighth The information is based on information of a triggering event, and the performance indicator information is used to determine at least one of the prediction accuracy, complexity and signaling overhead of the first function.

24. The method according to claim 20, characterized in that The performance monitoring type is second type performance monitoring, and the method further includes: Receive ninth information sent by the terminal device, where the ninth information is used to instruct the terminal device to determine a first operation to perform the first function, where the first operation includes any one of the following: selection, activation, deactivation, switching, and fallback.

25. The method according to claim 24, characterized in that The method further comprises: Send tenth information to the terminal device, where the tenth information is response information to the ninth information.

26. The method according to any one of claims 23 to 25, characterized in that The method further comprises at least one of the following: receiving an eleventh message sent by the terminal device, where the eleventh message is used to request to start performance monitoring of the first function; Twelfth information is sent to the terminal device, where the twelfth information is used to respond to the eleventh information.

27. The method according to claim 20, characterized in that The performance monitoring type is the third type of performance monitoring, and the method further includes: Receive the thirteenth information sent by the terminal device, the thirteenth information including at least one of the following: performance indicator information, information of a triggering event on which the thirteenth information is triggered, and the performance indicator information is used to determine at least one of the prediction accuracy, complexity and signaling overhead of the first function.

28. The method according to any one of claims 19 to 27, characterized in that The second information includes a performance indicator type, and the performance indicator type is used to indicate a performance indicator supported by the terminal device.

29. The method according to claim 28, characterized in that The performance indicators include at least one of the following: a beam prediction accuracy rate, where the beam prediction accuracy rate is a probability that the predicted best reference signal resource includes an actual best reference signal resource, where the predicted best reference signal resource is the best reference signal resource predicted by the first function, the actual best reference signal resource is the best reference signal resource actually measured by the terminal device, and the best reference signal resource is the top N reference signal resources with the best signal strength in the predicted second reference signal resource set, where N is a positive integer; a first signal strength difference, where the first signal strength difference is a difference between a first signal strength and a second signal strength, the first signal strength being the actual signal strength of the predicted best reference signal resource, and the second signal strength being the actual signal strength of the actual best reference signal resource; a second signal strength difference, where the second signal strength difference is a difference between a first signal strength and a third signal strength, where the first signal strength is an actual signal strength of the predicted best reference signal resource, and the third signal strength is a predicted signal strength of the predicted best reference signal resource; a third signal strength difference, where the third signal strength difference is a difference between a second signal strength and a fourth signal strength, where the second signal strength is an actual signal strength of the actual best reference signal resource, and the fourth signal strength is a predicted signal strength of the actual best reference signal resource; a first signal strength prediction accuracy indicator, where the first signal strength prediction accuracy indicator is a probability of the first signal strength difference being within a first difference range, or an average value of the first signal strength difference, or a value of a cumulative distribution function of the first signal strength difference at a first distribution ratio, where the first distribution ratio is greater than 0 and less than 1; a second signal strength prediction accuracy indicator, where the second signal strength prediction accuracy indicator is a probability that the second signal strength difference is within a first difference range, or an average value of the second signal strength difference, or a value of a cumulative distribution function of the second signal strength difference at a first distribution ratio; a third signal strength prediction accuracy indicator, wherein the third signal strength prediction accuracy indicator is a probability that the third signal strength difference is within a first difference range, or an average value of the third signal strength difference, or a value of a cumulative distribution function of the third signal strength difference at a first distribution ratio; a throughput difference, where the throughput difference is a difference between a first throughput and a second throughput, where the first throughput is a throughput calculated based on a first SINR, and the second throughput is a throughput calculated based on a second SINR, where the first SINR is an actual SINR of the predicted best reference signal resource, and the second SINR is an actual SINR of the actual best reference signal resource; a throughput prediction accuracy indicator, the throughput prediction accuracy indicator being a probability of the throughput difference being within a second difference range, or an average value of the throughput differences, or a value of a cumulative distribution function of the throughput differences at a second distribution ratio, where the second distribution ratio is greater than 0 and less than 1; a reference signal overhead, where the reference signal overhead is used to indicate the number of reference signal resources required for the first function; Uplink resource overhead, where the uplink resource overhead is used to indicate the amount of uplink resources occupied by information that needs to be reported to the network device for performing prediction and / or performance monitoring of the first function; Prediction delay, where the prediction delay is the time taken by the first function to perform beam prediction; Input data distribution information, where the input data distribution information is distribution information of input data of the first function; Output data distribution information, where the output data distribution information is distribution information of output data of the first function; Model complexity.

30. The method according to any one of claims 19 to 29, characterized in that The second information includes an event type, where the event type is used to indicate a type of event supported by the terminal device that triggers the performance monitoring.

31. The method according to claim 30, characterized in that The event type includes at least one of the following: A first type event, wherein the first type event is used to indicate that a performance indicator of an activated first function is worse than a first threshold; a second type of event, where the second type of event is used to indicate that a performance indicator of the deactivated first function is better than a second threshold; A third type of event, the third type of event being used to indicate that a performance indicator of the activated first function is worse than a first threshold, and a performance indicator of the deactivated first function is better than a second threshold; The fourth type of event is used to indicate that the first difference is better than the fourth threshold, the first difference is the difference between the second performance indicator and the first performance indicator, the first performance indicator is the performance indicator of the deactivated first function, and the second performance indicator is the performance indicator of the activated first function.

32. The method according to any one of claims 19 to 31, characterized in that The third information includes at least one of the following: Reference signal resource identifier; Signal strength; The confidence level corresponding to the signal strength.

33. The method according to claim 32, characterized in that The confidence level is used to indicate whether the signal strength is an actually measured signal strength or a predicted signal strength; or The signal strength is a predicted signal strength, and the confidence level is used to indicate a prediction accuracy corresponding to the signal strength.

34. The method according to any one of claims 19 to 33, characterized in that The first information is carried by a terminal capability report.

35. The method according to any one of claims 19 to 34, characterized in that The multiple information included in the first information includes mandatory information and optional information.

36. The method according to any one of claims 19 to 35, characterized in that The first function is deployed on the terminal device and / or the network device.

37. A terminal device, characterized in that: include: a transceiver module configured to send first information to the network device, where the first information is information corresponding to a first function, where the first function is an artificial intelligence (AI) function and / or AI model supported by the terminal device for performing beam prediction; The first information includes at least one of the following: second information, the second information including information on performance monitoring of the first function supported by the terminal device; third information, the third information including content information output by the first function supported by the terminal device; Fourth information, the fourth information includes a function identifier of the first function supported by the terminal device.

38. A network device, characterized in that: include: a transceiver module configured to receive first information sent by a terminal device, where the first information is information corresponding to a first function, where the first function is an artificial intelligence (AI) function and / or AI model supported by the terminal device for performing beam prediction; The first information includes at least one of the following: second information, the second information including information on performance monitoring of the first function supported by the terminal device; third information, the third information including content information output by the first function supported by the terminal device; Fourth information, the fourth information includes a function identifier of the first function supported by the terminal device.

39. A communication device, characterized in that: include: one or more processors; The communication device is used to execute the information transmission method according to any one of claims 1 to 18 or claims 19 to 36.

40. A storage medium storing instructions, characterized in that: When the instruction is executed on a communication device, the communication device is caused to execute the information transmission method according to any one of claims 1 to 18 or claims 19 to 36.

41. A communication system, characterized in that The communication system includes a terminal device and a network device, wherein the terminal device is configured to implement the information transmission method according to any one of claims 1 to 18, and the network device is configured to implement the information transmission method according to any one of claims 19 to 36.

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