Communication method and communication apparatus

Abstract

Provided in the present application are a communication method and a communication apparatus. The method can comprise: a network side sending a measurement configuration, wherein the measurement configuration is used for querying AI-related configuration applicability in the measurement configuration; and a terminal side sending first information, the first information indicating the applicability of a first trigger state in the measurement configuration, or indicating the applicability of a first trigger state list, wherein the applicability of the first trigger state is related to a first association report configuration. In this way, a network side can learn about the applicability of N first report configurations associated with a first trigger state and / or the applicability of a resource set corresponding to each of N report configurations. This, in turn, facilitates subsequent re-execution of a measurement configuration or indication of the configuration of a CSI report, thereby improving the system efficiency.

Description

Communication methods and communication devices

[0001] This application claims priority to Chinese Patent Application No. 202510391952.9, filed on March 28, 2025, entitled "Communication Method and Communication Device", the entire contents of which are incorporated herein by reference. Technical Field

[0002] This application relates to the field of communications, and more particularly to a communication method and a communication device. Background Technology

[0003] Artificial intelligence (AI) or machine learning (ML) time-domain prediction scenarios involve applicability inquiry behavior. For example, in channel state information (CSI) measurement, network devices send configuration information to terminal devices, and the terminal devices provide feedback on the applicability of the configuration. The network devices can then adjust the configuration based on the feedback.

[0004] However, in the current inquiry method, network devices cannot accurately know the reason why the terminal device is not suitable for the configuration based on the feedback information, which leads to low efficiency in configuration adjustment. Therefore, how to improve the effectiveness of applicability inquiry and thus improve system efficiency is an urgent problem to be solved. Summary of the Invention

[0005] This application provides a communication method and a communication device, which are intended to help the network side clarify the applicability of the measurement configuration to the terminal device, thereby facilitating the network device to determine the measurement configuration and improving system efficiency.

[0006] Firstly, this application provides a communication method that can be applied to the terminal side, for example, it can be executed by a terminal device; or it can be executed by a component deployed in the terminal device, such as a circuit or chip used in the terminal device (e.g., a modem chip, also known as a baseband chip, or a system-on-chip (SoC) chip containing a modem core, or a system-in-package (SIP) chip, etc.); or it can be executed by a device deployed outside the terminal device (e.g., a host or cloud server in an over-the-top (OTT) system) or a component in the device (e.g., a chip, processor, or circuit used in the device); or it can be implemented by a logic module or software capable of realizing all or part of the functions of the terminal device, etc. Alternatively, the method can be executed by a first device, which can be a terminal device; it can also be a component within the terminal device, such as a circuit or chip used in the terminal device (e.g., a modem chip), or a SoC chip or SIP chip containing a modem core; it can also be a device outside the terminal device (e.g., the host of an OTT system or a cloud server) or a component within the device (e.g., a chip, processor, or circuit used in the device); it can also be a logic module or software capable of implementing some or all of the functionalities on the terminal side, etc. This application does not limit this.

[0007] The method may include receiving a measurement configuration associated with a first trigger state list, the first trigger state list including multiple first trigger states, each first trigger state including or associated with N first associated report configurations, the first associated report configuration indicating the association between the first report configuration and a first resource set, where N is a positive integer;

[0008] Send a first message indicating the applicability of a first trigger state, or the first message indicating the applicability of a list of first trigger states, the applicability of which is related to the configuration of N first associated reports.

[0009] The measurement configuration may include trigger status, report configuration, and resource sets.

[0010] The applicability of the first triggering state can include whether the first triggering state is applicable or not. The applicability of the first triggering state can mean that the terminal side supports the first triggering state. In other words, the terminal side supports the relevant configurations included in the first triggering state, such as report configurations, resource sets, etc. The inapplicability of the first triggering state means that the terminal side does not support all or some of the relevant configurations included in the first triggering state.

[0011] Based on the above technical solution, the network side sends the measurement configuration, and the terminal side receives and provides feedback on the applicability of that measurement configuration. Specifically, the terminal side provides feedback on the applicability of the first trigger state, or the applicability of the list of first trigger states. By providing feedback on the applicability of the first trigger state or the list of first trigger states, the network side can determine the applicability of the N first report configurations included in the first trigger state and / or the applicability of the resource set corresponding to each of the N report configurations. In this way, the network side can gain a more detailed understanding of the terminal side's suitability for the measurement configuration by knowing the applicability of the first trigger state. This facilitates subsequent reconfiguration of measurement settings or instruction configuration of CSI reports, improving system efficiency.

[0012] Secondly, a communication method is provided, which can be applied to the network side. For example, it can be executed by a network device; or by a component deployed within the network device, such as circuits or chips used in the network device (e.g., modem chips, also known as baseband chips, or SoC chips or SIP chips containing modem cores); or by a device outside the network device (e.g., intelligent network elements on the network side) or a component within the device (e.g., chips, processors, or circuits used in the device); or by a logic module or software capable of implementing all or part of the functions of the network device, etc. Alternatively, the method can be executed by a second device, which can be a network device; or a component within the network device, such as circuits or chips used in the network device (e.g., modem chips, or SoC chips or SIP chips containing modem cores); or a device outside the network device (e.g., intelligent network elements) or a component within the device (e.g., chips, processors, or circuits used in the device); or a logic module or software capable of implementing some or all of the functions of the network side, etc. This application does not limit this.

[0013] The method may include: sending a measurement configuration associated with a first trigger state list, the first trigger state list including multiple first trigger states, each first trigger state including N first associated report configurations, the first associated report configuration indicating the association between the first report configuration and a first resource set, where N is a positive integer;

[0014] Receive first information, which indicates the applicability of a first trigger state, or the first information indicates the applicability of a list of first trigger states, the applicability of which is related to the configuration of N first associated reports.

[0015] In conjunction with the first aspect or the second aspect, the applicability of the first triggering state in some implementations of the first aspect or the second aspect includes: the first triggering state is applicable when all N first associated report configurations are applicable; the first triggering state is not applicable when one of the N first associated report configurations is not applicable.

[0016] In conjunction with the first or second aspect, in some implementations of the first or second aspect, the first information indicating the applicability of the first triggering state further includes: the first information indicating the applicability of each of the N first associated report configurations included in the first triggering state.

[0017] Based on the above technical solution, the terminal side provides feedback on the applicability of the first trigger state by assessing the applicability of the N first associated report configurations included in the first trigger state. Optionally, the terminal side can choose a coarser feedback, for example, feeding back that the first trigger state is applicable if all N first associated report configurations are applicable, and feeding back that the first trigger state is not applicable if at least one of the N first associated reports is not applicable. Alternatively, a more detailed feedback can be chosen, for example, feeding back the applicability of each of the first associated report configurations included in the first trigger state.

[0018] In conjunction with the first or second aspect, the applicability of the first associated report configuration in certain implementations of the first or second aspect includes: the first associated report configuration is applicable when both the first report configuration and the first resource set are applicable; or the first associated report configuration is not applicable when either the first report configuration or the first resource set is not applicable.

[0019] Based on the above technical solution, the first associated report configuration indicates the association between the first report configuration and the first resource set. This can be understood as the first associated report configuration being used to associate the first report configuration and the first resource set. Therefore, the applicability of the first report configuration and the first resource set can indicate the applicability of the first associated report configuration. Specifically, the first associated report configuration is applicable when both the first report configuration and the first resource set are applicable; it is not applicable when either the first report configuration or the first resource set is not applicable. In other words, the applicability of the first associated report configuration reflects both the applicability of the first report configuration associated with it and the applicability of the first resource set associated with it.

[0020] In conjunction with the first or second aspect, in certain implementations of the first or second aspect, the first report configuration includes multiple first time slot offsets. The first report configuration is applicable in the following ways: all configuration information in the first report configuration is applicable, and the first report configuration is applicable, wherein the configuration information includes the multiple first time slot offsets; or, at least one first time slot offset in the first report configuration is applicable, and the first report configuration is applicable; or, none of the multiple first time slot offsets in the first report configuration are applicable, and the first report configuration is not applicable.

[0021] In conjunction with the first or second aspect, in some implementations of the first or second aspect, the first information also indicates the applicability of each of the plurality of first time slot offsets.

[0022] Based on the above technical solution, the first information fed back by the terminal side can also include the applicability of each first time slot offset included in the first report configuration. This is because as long as there is an applicable first time slot offset, the first report configuration can be applicable. Therefore, the terminal side can also feed back the applicability of each first time slot offset through the first information, so that the network side can have a more detailed understanding of the applicability of the first report configuration in the measurement configuration.

[0023] In conjunction with the first or second aspect, the applicability of the first triggering state list in some implementations of the first or second aspect includes: the first triggering state list is applicable when all the first triggering states included in the first triggering state list are applicable; or the first triggering state list is not applicable when there is one first triggering state that is not applicable among all the first triggering states included in the first triggering state list.

[0024] In conjunction with the first or second aspect, in some implementations of the first or second aspect, the first information indicating the applicability of the first trigger state list further includes: the first information indicating the applicability of each first trigger state in the first trigger state list; or, the first information indicating the applicability of each first associated report configuration included in each first trigger state in the first trigger state list.

[0025] Based on the above technical solution, the terminal side can provide a relatively coarse feedback on the applicability of the first trigger state list. For example, if all the first trigger states included in the first trigger state list are applicable, the first trigger state list is applicable; if there is one first trigger state among all the first trigger states included in the first trigger state list that is not applicable, the first trigger state list is not applicable. The terminal side can also provide more detailed feedback on the applicability of the configurations associated with the first trigger state list. For example, the terminal side can provide feedback on the applicability of each first trigger state in the first trigger state list; or, for example, the terminal side can also provide feedback on the applicability of each first associated report configuration included in each first trigger state in the first trigger state list.

[0026] In conjunction with the first or second aspect, in some implementations of the first or second aspect, at least one of the following is related to AI: the first trigger state list, the first trigger state, the first associated report configuration, the resource set list associated with the first report configuration, the first resource set, or the first time slot offset.

[0027] Among them, "related to AI" can be understood as being used for AI-related operations, or being used for AI model-related operations, or being used for model-related operations.

[0028] The first trigger state list is related to AI, which can be understood as the first trigger state list being used for AI-related operations; or it can also be understood as the first trigger state list including the first trigger state used for AI-related operations.

[0029] The first trigger state is related to AI, which can be understood as the first trigger state being used for AI-related operations.

[0030] The first associated report configuration is AI-related, which can be understood as the first associated report configuration being used for AI-related operations; or, the first report configuration associated with the first associated report configuration being used for AI-related operations, and / or the first resource set associated with the associated first report configuration being used for AI-related operations.

[0031] The resource set list associated with the first report configuration is related to AI. This can be understood as at least one resource set in the resource set list associated with the first report configuration being used for AI-related operations.

[0032] The first resource set is related to AI, which can be understood as the first resource set being used for AI-related operations.

[0033] The time slot offset is related to AI, which can be understood as the time slot offset being used for AI-related operations.

[0034] Based on the above technical solution, the terminal side only reflects the applicability of AI-related configurations in the measurement configuration. This can reduce system overhead and will not affect traditional (legacy) applications or non-AI use cases / scenarios. In this case, legacy applications can also be replaced or understood as non-AI use cases / scenarios.

[0035] In conjunction with the first or second aspect, in some implementations of the first or second aspect, the first triggering state is included in the first W first triggering states in the first triggering state list, and / or, the first resource set is included in the first Z first resource sets in the resource set list associated with the first report configuration, where W and Z are both positive integers.

[0036] Based on the above technical solution, it is pre-set that the first W first trigger states in the measurement configuration sent by the network side are related to AI, and / or the first Z first resource sets are related to AI. In this way, the terminal side can only reply with the applicability of the first W first trigger states in the first trigger state sequence, and / or the network side can query the applicability of the first Z first resource sets in the first resource set sequence, which can reduce system overhead.

[0037] In conjunction with the first or second aspect, in some implementations of the first or second aspect, the measurement configuration further includes first indication information, which indicates one or more of the following related to AI: a first trigger state list, a first trigger state, a first associated report configuration, a list of resource sets associated with the first report configuration, a first resource set, and a time slot offset.

[0038] Based on the above technical solution, the network side indicates which parameters in the measurement configuration it sends are AI-related. In other words, the network side only queries the applicability of AI-related parameters in the measurement configuration, which can reduce system overhead.

[0039] In conjunction with the first or second aspect, in some implementations of the first or second aspect, the first triggering state is the Channel State Information (CSI) Aperiodic Trigger State.

[0040] Based on the above technical solution, in the measurement configuration of non-periodic CSI, one non-periodic CSI trigger state is associated with multiple report configurations, and multiple report configurations include multiple resource sets. Through the above technical solution, in the non-periodic CSI report, the terminal side provides more detailed feedback on the measurement configuration by feeding back the applicability of the trigger state of the non-periodic CSI report, which is beneficial for the network side to determine the applicability of the measurement configuration to the terminal side.

[0041] Thirdly, this application provides a communication method that can be applied to the terminal side. For example, it can be executed by a terminal device; or it can be executed by a component deployed in the terminal device, such as a circuit or chip used in the terminal device (e.g., a modem chip, also known as a baseband chip, or a SoC chip or SIP chip containing a modem core, etc.); or it can be executed by a device deployed outside the terminal device (e.g., the host or cloud server of an over-the-top (OTT) system) or a component in the device (e.g., a chip, processor, or circuit used in the device, etc.); or it can be implemented by a logic module or software capable of implementing all or part of the functions of the terminal device, etc. Alternatively, the method can be executed by a first device, which can be a terminal device; or it can be a component in the terminal device, such as a circuit or chip used in the terminal device (e.g., a modem chip, or a SoC chip or SIP chip containing a modem core, etc.); or it can be a device outside the terminal device (e.g., the host or cloud server of an OTT system, etc.) or a component in the device (e.g., a chip, processor, or circuit used in the device, etc.); or it can be a logic module or software capable of implementing some or all of the functions of the terminal side, etc. This application does not impose any limitations on this.

[0042] The method may include receiving a first query parameter, the first query parameter being related to at least one of the following: a first resource set list, R first resource sets in the first resource set list, a first time slot offset list, or a first time slot offset in the first time slot offset list, wherein R is a positive integer; and sending second information, the second information indicating the applicability of the first query parameter.

[0043] The first query parameter refers to the set of parameters related to the inference of the adaptive report. Specifically, the first query parameter can be the inference-related parameters in the information elements in the report configuration or the information elements referenced (or associated) in the report configuration.

[0044] Based on the above technical solution, the network side sends the first query parameter, the terminal side receives the first query parameter and provides feedback on the applicability of the first query parameter. By providing feedback on the applicability of the first query parameter, the network side can know the applicability of the first query parameter to the terminal side, thereby facilitating subsequent measurement configuration instructions.

[0045] Fourthly, a communication method is provided, which can be applied to the network side. For example, it can be executed by a network device; or by a component deployed within the network device, such as circuits or chips used in the network device (e.g., modem chips, also known as baseband chips, or SoC chips or SIP chips containing modem cores); or by a device outside the network device (e.g., intelligent network elements on the network side) or a component within the device (e.g., chips, processors, or circuits used in the device); or by a logic module or software capable of implementing all or part of the functions of the network device, etc. Alternatively, the method can be executed by a second device, which can be a network device; or a component within the network device, such as circuits or chips used in the network device (e.g., modem chips, or SoC chips or SIP chips containing modem cores); or a device outside the network device (e.g., intelligent network elements) or a component within the device (e.g., chips, processors, or circuits used in the device); or a logic module or software capable of implementing some or all of the functions of the network side, etc. This application does not limit this.

[0046] The method may include sending a first query parameter, the first query parameter being related to at least one of the following: a first resource set list, R first resource sets in the first resource set list, a first time slot offset list, or a first time slot offset in the first time slot offset list, wherein R is a positive integer; and receiving second information, the second information indicating the applicability of the first query parameter.

[0047] In conjunction with the third or fourth aspect, in some implementations of the third or fourth aspect, the applicability of the first query parameter includes one or more of the following: the applicability of the first resource set list; the applicability of each of the R first resource sets; the applicability of the first time slot offset list; and the applicability of each first time slot offset in the first time slot offset list.

[0048] Based on the above technical solution, the terminal side can provide feedback on the applicability of the resource set included in the first query parameters, thereby facilitating the network side to perform measurement configuration.

[0049] In conjunction with the third or fourth aspect, the applicability of the first resource set list in certain implementations of the third or fourth aspect includes: the first resource set list is not applicable if one of the R first resource sets is not applicable; and the first resource set list is applicable if each of the R first resource sets is applicable.

[0050] In conjunction with the third or fourth aspect, the applicability of the first time slot offset list in certain implementations of the third or fourth aspect includes: the first time slot offset list is not applicable if there is one first time slot offset in the first time slot offset list that is not applicable; or, the first time slot offset list is applicable if all first time slot offsets in the first time slot offset list are applicable; or, the first time slot offset list is applicable if every first time slot offset in the first time slot offset list is applicable.

[0051] Based on the above technical solution, depending on the different parameter sets related to the inference of the adaptive report, that is, when the parameters included in the first query parameters are different, the network side can select the applicability of the parameter set included in the first query parameters according to the specific situation.

[0052] In conjunction with the third or fourth aspect, in certain implementations of the third or fourth aspect, the applicability of the first query parameter includes one or more of the following: The first query parameter is applicable when it is related to the first resource set list and the first resource set list is applicable; the first query parameter is not applicable when it is related to the first resource set list but the first resource set list is not applicable; the first query parameter is applicable when it is related to the first time slot offset list and the first time slot offset list is applicable; the first query parameter is not applicable when it is related to the first time slot offset list but the first time slot offset list is not applicable; the first query parameter is applicable when it is related to both the first time slot offset list and the first resource set list, and both the first resource set list and the first time slot offset list are applicable; the first query parameter is not applicable when it is related to both the first time slot offset list and the first resource set list, but either the first resource set list or the first time slot offset list is not applicable.

[0053] Based on the above technical solution, the applicability of the first query parameter can provide more detailed feedback. For example, the applicability of the first query parameter may include the applicability of the first resource set list and / or the applicability of the first time slot offset list. The applicability of the first query parameter can also provide more coarse feedback. For example, the applicability of the first query parameter can be determined based on the applicability of the first resource list and / or the applicability of the first time slot offset list.

[0054] In conjunction with the third or fourth aspect, in some implementations of the third or fourth aspect, R first resource sets are located in the first R of the resource set list, or each of the R first resource sets is indicated as AI-related.

[0055] Based on the above technical solution, the terminal side only reflects the applicability of AI-related configurations in the measurement setup, thus reducing system overhead. Furthermore, it will not affect legacy applications or non-AI use cases / scenarios.

[0056] In conjunction with the third or fourth aspect, in some implementations of the third or fourth aspect, the first triggering state is the triggering state of the aperiodic channel state information reference signal CSI-RS.

[0057] It should be understood that the technical effects not described in the third and fourth aspects can be found in the first or second aspects, and will not be repeated here.

[0058] Fifthly, an apparatus is provided. This apparatus may include functional modules corresponding to each of the methods / operations / steps / actions described in any possible implementation of the first or third aspect, or may include functional modules corresponding to each of the methods / operations / steps / actions described in any of the second or fourth aspects. The module may be hardware circuitry, software, or a combination of hardware circuitry and software implementation.

[0059] In one design, the device may include a processing module and a communication module. The communication module is used to perform the sending and receiving actions performed by the terminal side in the methods described in the first or third aspect above, while the processing module is used to perform processing-related actions performed by the terminal side in the methods described in the first or third aspect above.

[0060] In one design, the device can be a terminal device, or a device, module, circuit, or chip configured in the terminal device, or a device that can be used in conjunction with the terminal device, such as an OTT host or cloud server.

[0061] In one design, the device may include a processing module and a communication module. The communication module is used to perform the sending and receiving actions performed by the network side in the methods described in the second or fourth aspect above, while the processing module is used to perform processing-related actions performed by the network side in the methods described in the second or fourth aspect above.

[0062] In one design, the device can be a network device, or a device, module, circuit, or chip configured in the network device, or a device that can be used in conjunction with the network device, such as an intelligent network element with a radio access network (RAN) intelligent controller (RIC) deployed thereon.

[0063] A sixth aspect provides an apparatus comprising at least one processor coupled to at least one memory storing instructions which, when executed by the processor, cause a method as in any possible implementation of the first or third aspect to be implemented, or cause a method as in any possible implementation of the second or fourth aspect to be implemented.

[0064] A seventh aspect provides an apparatus comprising a processing circuit for processing data and / or information such that a method as in any possible implementation of the first or third aspect is implemented, or a method as in any possible implementation of the second or fourth aspect is implemented.

[0065] The processing circuit may include one or more processors, or all or part of the circuitry in one or more processors used for control or processing functions.

[0066] Optionally, the apparatus may further include at least one memory for storing a program or instructions, and the processor for running the program or instructions to implement the method as in any possible implementation of the first or third aspect, or to implement the method as in any possible implementation of the second or fourth aspect.

[0067] Optionally, the device may also include the transceiver circuit, or an input / output interface.

[0068] Eighthly, a chip is provided, including processing circuitry for running a program or instructions to cause the method in any possible implementation of the first or third aspect to be implemented, or to cause the method in any possible implementation of the second or fourth aspect to be implemented.

[0069] Optionally, the chip may further include a memory for storing programs or instructions.

[0070] Optionally, the chip may also include transceiver circuitry, or input / output interfaces.

[0071] A ninth aspect provides a computer-readable storage medium comprising instructions that, when executed by a processor, cause a method as in any possible implementation of the first or third aspect to be implemented, or a method as in any possible implementation of the second or fourth aspect to be implemented.

[0072] In a tenth aspect, a computer program product is provided, the computer program product comprising computer program code or instructions that, when the computer program code or instructions are executed, cause the methods of the first or third aspect and any possible implementation thereof to be implemented, or cause the methods of the second or fourth aspect and any possible implementation thereof to be implemented.

[0073] Eleventhly, a communication system is provided, the communication system including means for performing the first aspect or the third aspect and any possible implementation thereof, or including means for performing the second aspect or the fourth aspect and any possible implementation thereof.

[0074] It should be understood that aspects five to eleven of this application correspond to the technical solutions of aspects one to four of this application, and the beneficial effects achieved by each aspect and the corresponding feasible implementation are similar, and will not be repeated here. Attached Figure Description

[0075] Figure 1 is a schematic diagram of a communication system applicable to the communication method of this application embodiment.

[0076] Figure 2 is a schematic diagram of another communication system applicable to the communication method of the embodiments of this application.

[0077] Figure 3 is a schematic diagram of a possible application framework in a communication system.

[0078] Figure 4 is a schematic diagram of another possible application framework in a communication system.

[0079] Figure 5 is a schematic flowchart of a communication method provided in an embodiment of this application.

[0080] Figure 6 is a schematic diagram illustrating the association between the configuration of the associated report and the resource set according to an embodiment of this application.

[0081] Figure 7 is a schematic flowchart of another communication method provided in an embodiment of this application.

[0082] Figure 8 is a schematic flowchart of another communication method provided in an embodiment of this application.

[0083] Figure 9 is a schematic flowchart of another communication method provided in an embodiment of this application.

[0084] Figure 10 is a schematic block diagram of a communication device provided in an embodiment of this application.

[0085] Figure 11 is a schematic diagram of another communication device provided in an embodiment of this application.

[0086] Figure 12 is a schematic diagram of the structure of an AI processor provided in an embodiment of this application. Detailed Implementation

[0087] The technical solutions in this application will now be described with reference to the accompanying drawings.

[0088] To facilitate understanding of the embodiments of this application, the following points will be explained first:

[0089] First, in this application, the terminal side can also be referred to as the user equipment (UE) side, terminal-side equipment, etc., including: terminal equipment (or user equipment, terminal, etc.), components deployed in the terminal equipment (such as circuits or chips inside the terminal equipment), equipment deployed outside the terminal equipment (such as the host or cloud server of an over-the-top (OTT) system, hereinafter referred to as the OTT system server), or components deployed in equipment outside the terminal equipment (such as circuits or chips inside the equipment). The network side (NW side) can also be referred to as network-side equipment, including: network equipment that communicates with the terminal equipment, components deployed in the network equipment (such as circuits or chips inside the network equipment with near real-time radio access network (RAN) intelligent control functions), equipment deployed outside the network equipment (such as intelligent network elements, for example, intelligent network elements with near real-time RAN intelligent control functions), or components deployed in the intelligent network element (such as circuits or chips inside the intelligent network element). Network equipment may include: access network equipment, core network equipment, or operation administration and maintenance (OAM) equipment.

[0090] Second, in this application, the indication includes direct indication (also known as explicit indication) and indirect indication (also known as implicit indication). Directly indicating information A means including information A; indirectly indicating information A can mean indicating information A through the correspondence between information A and information B and by directly indicating information B; or by indicating information A through a preset rule that can be used to determine A based on B and by directly indicating information B. The correspondence between information A and information B, and the preset rule, can be predefined, pre-stored, pre-burned, or pre-configured.

[0091] Third, in this application, "at least one" means one or more, and "more than one" means two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can mean: A alone, A and B simultaneously, or B alone, where A and B can be singular or plural. The character " / " generally indicates an "or" relationship between the preceding and following related objects, but it does not exclude the possibility of indicating an "and" relationship; the specific meaning can be understood in context. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, or c can mean: a, b, c; a and b; a and c; b and c; or a and b and c. Here, a, b, and c can be single or multiple.

[0092] Fourth, the use of prefixes such as "first" and "second" in this application is merely for the purpose of distinguishing and describing different things belonging to the same category of names, and does not constrain the order, size, or quantity of things. For example, "first information" and "second information" are simply different indicative information, and do not limit the quantity, chronological order, size, or priority of the information.

[0093] Fifth, in this application, "send" and "receive" indicate the direction of signal transmission. For example, "send information to a terminal device" can be understood as the destination of the information being the terminal device, which may include direct transmission via the air interface or indirect transmission via the air interface from other units or modules. "Receive information from a network device" can be understood as the source of the information being the network device, which may include direct reception from the network device via the air interface or indirect reception from the network device via the air interface from other units or modules. Furthermore, information may undergo necessary processing between the source and destination, such as format changes, but the destination can understand the valid information from the source. "Send" can also be understood as the "output" of the chip interface, and "receive" can be understood as the "input" of the chip interface. In other words, sending and receiving can occur between devices, such as between a terminal device and a computing node, or within a device, such as between components, modules, chips, software modules, or hardware modules within the device via a bus, wiring, or interface.

[0094] Sixth, in the embodiments of this application, "when," "if," and "if" all refer to the device making corresponding processing under certain objective circumstances, and are not limited to a time, nor do they require the device to make a judgment action when it is implemented, nor do they mean that there are other limitations.

[0095] Seventh, in this application, the words "example," "exemplarily," "for example," or "such as" are used to indicate that something is an example, illustration, or description. Any embodiment or design described as "example," "exemplarily," "for example," or "such as" in this application should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of the words "example," "exemplarily," "for example," or "such as" is intended to present the relevant concepts in a specific manner.

[0096] The communication system to which this application applies is described below.

[0097] The technical solutions provided in this application can be applied to various communication systems, such as 5th generation (5G) or new radio (NR) systems, frequency division duplex (FDD) systems, time division duplex (TDD) systems, wireless local area network (WLAN) systems, satellite communication systems, future communication systems, or integrated systems of multiple systems. The technical solutions provided in this application can also be applied to device-to-device (D2D) communication, vehicle-to-everything (V2X) communication, machine-to-machine (M2M) communication, machine-type communication (MTC), and Internet of Things (IoT) communication systems or other communication systems.

[0098] In a communication system, one network element can send signals to or receive signals from another network element. These signals can include information, signaling, or data. The term "network element" can also be replaced by an entity, network entity, device, communication equipment, communication module, node, communication node, etc. This disclosure uses a network element as an example. For instance, a communication system can include at least one terminal device and at least one network device. The network device can send downlink signals to the terminal device, and / or the terminal device can send uplink signals to the network device. It is understood that the terminal device in this disclosure can be replaced by a first network element, and the network device can be replaced by a second network element, both performing the corresponding methods described in this disclosure.

[0099] Figure 1 is a schematic diagram of a communication system applicable to the communication method of this application embodiment. As shown in Figure 1, the communication system 100A may include at least one access network device, such as access network device 110 shown in Figure 1; the communication system 100A may also include at least one terminal device, such as terminal device 120 and terminal device 130 shown in Figure 1. Access network device 110 and terminal devices (such as terminal device 120 and terminal device 130) can communicate via a wireless link. The communication devices in this communication system, for example, access network device 110 and terminal device 120, can communicate via multi-antenna technology.

[0100] In wireless communication networks, such as mobile communication networks, the services supported by the networks are becoming increasingly diverse, thus requiring increasingly diverse demands. For example, networks need to support ultra-high speeds, ultra-low latency, and / or massive connectivity. This characteristic makes network planning, network configuration, and / or resource scheduling increasingly complex. Furthermore, as network functions become more powerful, such as supporting higher spectrum levels, supporting higher-order multiple-input multiple-output (MIMO) technologies, supporting beamforming (BF), and supporting beam management, network energy efficiency has become a hot research topic. These new demands, new scenarios, and new characteristics bring unprecedented challenges to network planning, operation, and efficient operation. To meet these challenges, artificial intelligence (AI) technology can be introduced into wireless communication networks to achieve network intelligence. To support AI technology in wireless networks, AI nodes may also be introduced. AI nodes can be AI network elements or AI modules.

[0101] AI can endow machines with human-like intelligence, for example, allowing them to use computer hardware and software to simulate certain intelligent human behaviors. To achieve artificial intelligence, machine learning methods can be employed. In machine learning, machines learn (or train) a model using training data. This model represents the mapping between inputs and outputs. The learned model can be used for reasoning (or prediction), that is, it can be used to predict the output corresponding to a given input. This output can also be called the reasoning result (or prediction result).

[0102] This document explains some basic concepts in the field of AI, which does not limit the scope of protection of the embodiments of this application.

[0103] (1) Machine learning (ML)

[0104] Machine learning is a crucial technological approach to achieving AI. AI endows machines with human-like intelligence, using computer hardware and software to simulate certain intelligent human behaviors, including machine learning and other methods. Machine learning refers to learning models or rules from raw data, such as neural networks, decision trees, and support vector machines. Machine learning can be categorized into supervised learning, unsupervised learning, and reinforcement learning.

[0105] Supervised learning, based on collected sample values ​​and labels, uses machine learning algorithms to learn the mapping relationship between sample values ​​and labels, and expresses this learned mapping relationship using a machine learning model. The process of training the machine learning model is the process of learning this mapping relationship. For example, in signal detection, the noisy received signal is the sample, and the corresponding real constellation point is the label. Machine learning aims to learn the mapping relationship between samples and labels through training, that is, to enable the machine learning model to learn a signal detector. During training, the model parameters are optimized by calculating the error between the model's predicted values ​​and the real labels. Once the mapping relationship is learned, it can be used to predict the sample label of each new sample. The mapping relationship learned in supervised learning can include linear mappings and nonlinear mappings. Based on the type of label, the learning task can be divided into classification tasks and regression tasks.

[0106] Unsupervised learning relies solely on collected sample values, using algorithms to discover inherent patterns within the samples. One type of unsupervised learning algorithm uses the samples themselves as supervisory signals; that is, the model learns the mapping relationship from sample to sample, which is called self-supervised learning. During training, model parameters are optimized by calculating the error between the model's predictions and the samples themselves. Self-supervised learning can be used for signal compression and decompression recovery applications; common algorithms include autoencoders and generative adversarial networks.

[0107] Reinforcement learning, unlike supervised learning, is a type of algorithm that learns problem-solving strategies through interaction with the environment. Unlike supervised and unsupervised learning, reinforcement learning problems do not have explicit "correct" action labels. The algorithm needs to interact with the environment to obtain reward signals from the environment, and then adjust its decision actions to obtain a larger reward signal value. For example, in downlink power control, the reinforcement learning model adjusts the downlink transmission power of each terminal device based on the total system throughput feedback from the wireless network, aiming to achieve a higher system throughput. The goal of reinforcement learning is also to learn the mapping relationship between the environment state and the optimal decision action. However, because the label of the "correct action" cannot be obtained in advance, the network cannot be optimized by calculating the error between the action and the "correct action." Reinforcement learning training is achieved through iterative interaction with the environment.

[0108] Deep neural networks (DNNs) are a specific implementation of machine learning. According to the general approximation theorem, neural networks can theoretically approximate any continuous function, thus enabling them to learn arbitrary mappings. Traditional communication systems rely on extensive expert knowledge to design communication modules, while DNN-based deep learning communication systems can automatically discover hidden pattern structures from large datasets, establish mapping relationships between data, and achieve performance superior to traditional modeling methods.

[0109] Based on their construction method, DNNs can be divided into feedforward neural networks (FNNs), convolutional neural networks (CNNs), and recurrent neural networks (RNNs). FNNs can be neural networks where neurons in adjacent layers are completely connected pairwise, which makes FNNs typically require a large amount of storage space and have high computational complexity.

[0110] CNNs are neural networks specifically designed to process data with a grid-like structure. For example, time-series data (discrete sampling along the time axis) and image data (two-dimensional discrete sampling) can both be considered grid-like data. CNNs do not use all the input information at once for computation; instead, they use a fixed-size window to extract a portion of the information for convolution operations, which significantly reduces the computational cost of model parameters. Furthermore, depending on the type of information extracted by the window (such as people and objects in an image representing different types of information), each window can use different convolution kernels, allowing CNNs to better extract features from the input data.

[0111] Recurrent Neural Networks (RNNs) are a type of distributed neural network (DNN) that utilizes feedback time-series information. Their input includes the current input value and their own output value from the previous time step. RNNs are well-suited for acquiring temporally correlated sequence features, and are particularly applicable to applications such as speech recognition and channel coding / decoding.

[0112] AI models refer to function models that map inputs of a certain dimension to outputs of a certain dimension, and their parameters can be obtained through machine learning training. For example, f(x) = ax 2+b is a quadratic function model, which can be viewed as an AI model. a and b correspond to the parameters of this model and can be obtained through machine learning training. In machine learning, the data used for model training, validation, and / or testing can form a dataset or training dataset. The quantity and / or quality of data in the dataset or training dataset will affect the effectiveness of machine learning. Model training involves selecting an appropriate loss function (which measures the difference between the model's predictions and the true values) and using optimization algorithms to train the model parameters to minimize the loss function value. Model testing involves evaluating the model's performance using test data after training. Model application involves using the trained model to solve real-world problems.

[0113] A neural network, or artificial neural network, is a mathematical model that mimics the behavioral characteristics of animal neural networks to perform distributed parallel information processing. It is a special form of AI model.

[0114] (2) Model Training

[0115] Model training involves selecting an appropriate function (such as a loss function) and using optimization algorithms to train the model parameters so that the difference between the model's predicted values ​​and the ground truth (or target values, labels) tends to be minimized.

[0116] For example, model training methods include, but are not limited to, supervised learning, self-supervised learning, and knowledge distillation.

[0117] (3) Model files and model parameters

[0118] Model files and / or model parameters can be used to determine the model. Optionally, the model in this application may refer to the model itself, or it may refer to the model files and / or model parameters used to determine the model.

[0119] The model file can be used to indicate the model structure, which may include, but is not limited to, FNN, CNN, or RNN. The model file can have a fixed format, such as a standard predefined format, or a format pre-negotiated by both ends of the interface. Model parameters can refer to parameters in the neural network model, such as, but not limited to, the number of layers in the neural network, the type and weights of neurons in each layer, etc. This application does not limit the method of distributing model parameters.

[0120] Take DNN as an example. The idea behind DNN comes from the neuronal structure of the brain. Each neuron can perform a weighted summation operation on its inputs and then use the result of the weighted summation operation to generate the output through a non-linear function. For example, the input of a neuron is x = [x0, x1, ..., x...]. N-1The weights corresponding to the inputs are w = [w0, w1, ..., w] N-1 The bias of the weighted summation is b. The nonlinear function f() can take many forms; for example, the nonlinear function f() can be the maximum value function max{0, x}. Then the effect of a neuron's execution is... Where N is a positive integer, and n is a positive integer greater than or equal to 0 and less than or equal to (N-1). The weights of the weighted summation operation of neurons in a neural network and the nonlinear function are called the parameters of the neural network. The parameters of all neurons in a neural network constitute the parameters of the neural network.

[0121] A DNN typically has multiple neural network layers, including an input layer, one or more hidden layers, and an output layer. Generally, the first layer is the input layer, the last layer is the output layer, and the layers in between are hidden layers. Each layer contains multiple neurons. Layers are fully connected; that is, any neuron in the i-th layer is connected to any neuron in the (i+1)-th layer. The input layer processes the received values ​​(i.e., the DNN's input) through neurons and then passes them to the hidden layers. Similarly, the hidden layers pass the computation results to the final output layer, producing the DNN's output. This application does not limit the structure and parameters used in the AI ​​model.

[0122] One of the model structure or model parameters can be predefined, while the other can be sent by the sender (e.g., the network side). Alternatively, both the model structure and model parameters can be sent by the sender (e.g., the network side). This application does not impose any restrictions on this.

[0123] The transmitting model can refer to sending model files and / or model parameters, while the receiving model can refer to receiving model files and / or model parameters. Currently, AI technology is being introduced into wireless communication systems. AI technology can be used for wireless channel information compression and reconstruction, beam management, and positioning enhancement, improving wireless communication performance based on trained AI models. A wireless AI framework can include multiple modules such as data collection, model training, model management, model inference, and model storage.

[0124] Figure 2 is a schematic diagram of another communication system applicable to the communication method of this application embodiment. Compared with the communication system 100A shown in Figure 1, the communication system 100B shown in Figure 2 further includes an AI network element 140. The AI ​​network element 140 is used to perform AI-related operations, such as building datasets or AI models. The AI ​​network element can also be simply referred to as an intelligent network element. In this disclosure, the AI ​​model can be simply referred to as a model.

[0125] In one possible implementation, access network device 110 can send data related to the training of the AI ​​model to AI network element 140, whereby AI network element 140 constructs a dataset and trains the AI ​​model. For example, the data related to the training of the AI ​​model may include data reported by terminal devices. AI network element 140 can send the results of operations related to the AI ​​model to access network device 110, and then forward them to terminal devices via access network device 110. For example, the results of operations related to the AI ​​model may include at least one of the following: a trained AI model, model evaluation results, or test results, etc. Exemplarily, a portion of the trained AI model may be deployed on access network device 110, and another portion on terminal devices 120 and / or 130. Alternatively, the trained AI model may be deployed on access network device 110. Or, the trained AI model may be deployed on terminal devices 120 and / or 130.

[0126] It should be understood that Figure 2 is only used as an example of the AI ​​network element 140 being directly connected to the access network device 110. In other scenarios, the AI ​​network element 140 can also be connected to the terminal device. Alternatively, the AI ​​network element 140 can be connected to both the access network device 110 and the terminal device simultaneously. Alternatively, the AI ​​network element 140 can also be connected to the access network device 110 through a third-party network element. This application embodiment does not limit the connection relationship between the AI ​​network element and other network elements. For example, the AI ​​network element 140 can also be set as a module in the access network device and / or the terminal device, for example, in the access network device 110 or the terminal device shown in Figure 1.

[0127] It should be noted that Figures 1 and 2 are simplified schematic diagrams for ease of understanding. For example, the communication system may also include other devices, such as wireless relay devices and / or wireless backhaul devices, which are not shown in Figures 1 and 2. In practical applications, the communication system may include multiple access network devices and multiple terminal devices. The embodiments of this application do not limit the number of access network devices and terminal devices included in the communication system.

[0128] In the embodiments of this application, the terminal device may also be referred to as UE, access terminal, user unit, user station, mobile station, mobile station, remote station, remote terminal, mobile device, user terminal, terminal, wireless communication device, user agent, or user equipment.

[0129] Terminal devices can be devices that provide voice / data, such as handheld devices with wireless connectivity, in-vehicle devices, etc. Currently, examples of terminals include: mobile phones, tablets, laptops, PDAs, mobile internet devices (MIDs), wearable devices, virtual reality (VR) devices, augmented reality (AR) devices, wireless terminals in industrial control, wireless terminals in self-driving, wireless terminals in remote medical surgery, wireless terminals in smart grids, wireless terminals in transportation safety, wireless terminals in smart cities, wireless terminals in smart homes, cellular phones, cordless phones, session initiation protocol (SIP) phones, wireless local loop (WLL) stations, personal digital assistants (PDAs), handheld devices with wireless communication capabilities, computing devices or other processing devices connected to a wireless modem, wearable devices, terminal devices in 5G networks, or future public land mobile communication networks. Terminal devices in a network (PLMN), etc., are not limited to this in the embodiments of this application.

[0130] By way of example and not limitation, in this embodiment, the terminal device can also be a wearable device. Wearable devices, also known as wearable smart devices, are a general term for devices that utilize wearable technology to intelligently design and develop everyday wearables, such as glasses, gloves, watches, clothing, and shoes. Wearable devices are portable devices that are worn directly on the body or integrated into the user's clothing or accessories. Wearable devices are not merely hardware devices, but also achieve powerful functions through software support, data interaction, and cloud interaction. Broadly speaking, wearable smart devices include those that are feature-rich, large in size, and can achieve complete or partial functions without relying on a smartphone, such as smartwatches or smart glasses, as well as those that focus on a specific type of application function and require the use of other devices such as smartphones, such as various smart bracelets and smart jewelry for vital sign monitoring.

[0131] In this embodiment, the device for implementing the functions of the terminal device can be the terminal device itself, or it can be any device capable of supporting the terminal device in implementing those functions, such as a chip system. This device can be installed in or used in conjunction with the terminal device. In this embodiment, the chip system can be composed of chips or may include chips and other discrete components. This embodiment only uses the terminal device as an example to illustrate the device for implementing the functions of the terminal device, and does not constitute a limitation on the solution of this embodiment.

[0132] The network device in this application embodiment can be a device for communicating with a terminal device. This network device may include an access network device, a core network device, or other devices in the communication system. The access network device may be, for example, a base station. In this application embodiment, the access network device may refer to a radio access network (RAN) node (or device) that connects the terminal device to the wireless network. A base station can broadly encompass, or be replaced by, various names such as: NodeB, evolved NodeB (eNB), next-generation NodeB (gNB), relay station, access point, transmitting and receiving point (TRP), transmitting point (TP), master station, auxiliary station, motor slide retainer (MSR) node, home base station, network controller, access node, wireless node, access point (AP), transmission node, transceiver node, baseband unit (BBU), remote radio unit (RRU), active antenna unit (AAU), remote radio head (RRH), central unit (CU), distributed unit (DU), radio unit (RU), positioning node, etc. A base station can be a macro base station, micro base station, relay node, donor node, or similar entities, or combinations thereof. A base station can also refer to a communication module, modem, or chip installed within the aforementioned equipment or apparatus. A base station can also be a mobile switching center, a device that performs base station functions in D2D, V2X, and M2M communications, or a device that performs base station functions in future communication systems. A base station can support networks using the same or different access technologies. Optionally, a RAN node can also be a server, wearable device, vehicle, or in-vehicle equipment. For example, the access network equipment in V2X technology can be a roadside unit (RSU). The embodiments of this application do not limit the specific technology or equipment form used in the access network equipment.

[0133] Base stations can be fixed or mobile. For example, a helicopter or drone can be configured to act as a mobile base station, and one or more cells can move depending on the location of the mobile base station. In other examples, a helicopter or drone can be configured as a device to communicate with another base station.

[0134] In some deployments, the access network equipment mentioned in the embodiments of this application may be a device including a CU, or a DU, or a device including both CU and DU, or a device with a control plane CU node (central unit-control plane (CU-CP)) and a user plane CU node (central unit-user plane (CU-UP)) and a DU node. For example, the access network equipment may include gNB-CU-CP, gNB-CU-UP, and gNB-DU.

[0135] In some deployments, multiple RAN nodes collaborate to assist terminals in achieving wireless access, with different RAN nodes each implementing some of the base station's functions. For example, RAN nodes can be CUs, DUs, CU-CPs, CU-UPs, or RUs. CUs and DUs can be configured separately or included in the same network element, such as a BBU. RUs can be included in radio frequency equipment or radio frequency units, such as RRUs, AAUs, or RRHs.

[0136] RAN nodes can support one or more types of fronthaul interfaces, each corresponding to a DU and RU with different functions. If the fronthaul interface between the DU and RU is a Common Public Radio Interface (CPRI), the DU is configured to implement one or more baseband functions, and the RU is configured to implement one or more radio frequency functions. If the fronthaul interface between the DU and RU is another type of interface, relative to CPRI, it moves some downlink and / or uplink baseband functions—for example, for downlink, precoding, digital beamforming, or one or more of inverse fast Fourier transform (IFFT) / adding a cyclic prefix (CP)—from the DU to the RU; and for uplink, digital beamforming, or one or more of fast Fourier transform (FFT) / removing CP—from the DU to the RU. In one possible implementation, this interface can be an enhanced common public radio interface (eCPRI). Under the eCPRI architecture, the splitting methods between DU and RU are different, corresponding to different types (category, Cat) of eCPRI, such as eCPRI Cat A, B, C, D, E, F.

[0137] Taking eCPRI Cat A as an example, for downlink transmission, layer mapping is used as the dividing line. The DU is configured to implement one or more functions preceding layer mapping (i.e., coding, rate matching, scrambling, modulation, and layer mapping itself), while other functions following layer mapping (e.g., resource element (RE) mapping, digital beamforming, or one or more of IFFT / CP addition) are implemented in the RU. For uplink transmission, de-RE mapping is used as the dividing line. The DU is configured to implement one or more functions preceding de-mapping (i.e., decoding, rate matching de-matching, descrambling, demodulation, inverse discrete Fourier transform (IDFT), channel equalization, and de-RE mapping itself), while other functions following de-mapping (e.g., digital BF or FFT / CP removal) are implemented in the RU. It is understood that descriptions of the functions of the DU and RU corresponding to various types of eCPRI can be found in the eCPRI protocol and will not be elaborated upon here.

[0138] In one possible design, the processing unit in the BBU used to implement baseband functions is called the baseband high (BBH) unit, and the processing unit in the RRU / AAU / RRH used to implement baseband functions is called the baseband low (BBL) unit.

[0139] In different systems, CU (or CU-CP and CU-UP), DU, or RU may have different names, but those skilled in the art will understand their meaning. For example, in an open RAN (ORAN) architecture, CU can also be called open CU (open-CU, O-CU), DU can also be called open DU (open-DU, O-DU), CU-CP can also be called open CU-CP (open-CU-CP) O-CU-CP, CU-UP can also be called open CU-UP (open-CU-UP, O-CU-UP), and RU can also be called open RU (open-RU, O-RU). Any of the units among CU (or CU-CP, CU-UP), DU, and RU in this application can be implemented through software modules, hardware modules, or a combination of software modules and hardware modules.

[0140] In this embodiment, the apparatus for implementing the functions of a network device can be a network device itself; it can also be an apparatus capable of supporting the network device in implementing those functions, such as a chip system, hardware circuit, software module, or a hardware circuit plus a software module. This apparatus can be installed in the network device or used in conjunction with the network device. In this embodiment, the example of a network device being used to implement the functions of a network device is provided only and does not constitute a limitation on the solutions described in this embodiment.

[0141] Network devices and / or terminal devices can be deployed on land, including indoors or outdoors, handheld or vehicle-mounted; they can also be deployed on water; and they can also be deployed in the air on airplanes, balloons, and satellites. This application does not limit the scenario in which the network devices and terminal devices are located. Furthermore, terminal devices and network devices can be hardware devices, or software functions running on dedicated hardware or general-purpose hardware, such as virtualization functions instantiated on a platform (e.g., a cloud platform), or entities that include dedicated or general-purpose hardware devices and software functions. This application does not limit the specific form of the terminal devices and network devices.

[0142] Optionally, the AI ​​node can be deployed in one or more of the following locations within the communication system: access network equipment, terminal equipment, or core network elements. Alternatively, the AI ​​node can also be deployed independently, for example, in a location other than any of the aforementioned devices, such as in the host or cloud server of an OTT system. The AI ​​node can communicate with other devices in the communication system, which can be one or more of the following: access network equipment, terminal equipment, or core network elements.

[0143] It is understood that this application does not limit the number of AI nodes. For example, when there are multiple AI nodes, these nodes can be divided based on function, such as different AI nodes being responsible for different functions.

[0144] It can also be understood that AI nodes can be independent devices, or they can be integrated into the same device to achieve different functions. Alternatively, they can be network elements in hardware devices, software functions running on dedicated hardware, or virtualization functions instantiated on a platform (e.g., a cloud platform). This application does not limit the specific form of the aforementioned AI nodes.

[0145] Figure 3 is a schematic diagram of a possible application framework in a communication system. As shown in Figure 3, network elements in the communication system are connected through interfaces (such as next-generation (NG) interfaces or Xn interfaces) or air interfaces. The NG interface is the interface between the radio access network and the 5G core network. The Xn interface is the interface between access network devices, and the air interface is the interface between access network devices and terminal devices. These network element nodes, such as core network devices, RAN nodes, terminal devices, or one or more devices in the OAM, are equipped with one or more AI modules (only one is shown in Figure 3 for clarity). The access network node can be a single RAN node or can include multiple RAN nodes, for example, including CU and DU. The CU and / or DU can also be equipped with one or more AI modules. Optionally, the CU can also be split into CU-CP and CU-UP. One or more AI models are configured in the CU-CP and / or CU-UP.

[0146] The AI ​​module is used to implement corresponding AI functions. AI modules deployed in different network elements can be the same or different. Depending on the parameter configuration, the AI ​​module can implement different functions. The AI ​​module model can be configured based on one or more of the following parameters: structural parameters (e.g., at least one of the following: number of neural network layers, neural network width, inter-layer connections, neuron weights, neuron activation function, or bias in the activation function), input parameters (e.g., type and / or dimension of input parameters), or output parameters (e.g., type and / or dimension of output parameters). The bias in the activation function can also be referred to as the neural network bias.

[0147] An AI module can have one or more models. A model can infer an output, which includes one or more parameters. The learning, training, or inference processes of different models can be deployed on different nodes or devices, or they can be deployed on the same node or device.

[0148] Network devices can be network devices equipped with one or more AI modules. These network devices can include one or more devices in the core network, RAN, or OAM as shown in Figure 3. For example, the AI ​​module can be a RAN intelligent controller (RIC) as shown in Figure 4, such as a near-real-time RIC (near-RT RIC) or a non-real-time RIC (non-RT RIC). For instance, a near-real-time RIC is located in a RAN node (e.g., in a CU or DU), while a non-real-time RIC is located in the OAM, a cloud server, a core network device, or other access network devices. The RIC can obtain subsets from multiple terminal devices from RAN nodes (e.g., CU, CU-CP, CU-UP, DU, and / or RU), reassemble them into a dataset, and train based on the dataset. Exemplarily, near-real-time RICs and non-real-time RICs can also be configured as separate network elements, and access network devices can be either near-real-time or non-real-time RICs.

[0149] Figure 4 illustrates another possible application framework in a communication system. In addition to access network nodes (CU, DU, and RU are shown in the figure) and terminals, the communication system shown in Figure 4 also includes an RIC (Regulator-Integrated Circuit). For example, the RIC could be the AI ​​module shown in Figure 3, which can be used to implement AI-related functions. The RIC includes near-real-time RICs and non-real-time RICs. Non-real-time RICs primarily process non-real-time information, such as data that is not sensitive to latency, with latency in the order of seconds. Real-time RICs primarily process near-real-time information, such as data that is relatively sensitive to latency, with latency in the order of tens of milliseconds.

[0150] The near real-time RIC is used for model training and inference. For example, it is used to train an AI model and then use that AI model for inference. The near real-time RIC can obtain network-side and / or terminal-side information from RAN nodes (e.g., CU, CU-CP, CU-UP, DU, and / or RU) and / or terminals. This information can be used as training data or inference data. Optionally, the near real-time RIC can deliver the inference results to the RAN nodes and / or terminals. Optionally, inference results can be exchanged between CU and DU, and / or between DU and RU. For example, the near real-time RIC delivers the inference results to the DU, and the DU sends them to the RU.

[0151] The non-real-time RIC is also used for model training and inference. For example, it can be used to train an AI model and then use that model for inference. The non-real-time RIC can obtain network-side and / or terminal-side information from RAN nodes (e.g., one or more of CU, CU-CP, CU-UP, DU, or RU) and / or terminals. This information can be used as training data or inference data, and the inference results can be delivered to the RAN nodes and / or terminals. Optionally, inference results can be exchanged between CU and DU, and / or between DU and RU; for example, the non-real-time RIC delivers the inference results to the DU, which then forwards them to the RU.

[0152] The near real-time RIC and non-real-time RIC can also be set up as separate network elements. Optionally, the near real-time RIC and non-real-time RIC can also be part of other devices. For example, the near real-time RIC can be set in the RAN node (e.g., in CU, DU), while the non-real-time RIC can be set in the OAM, cloud server, core network device, or other network device.

[0153] To facilitate understanding of the embodiments of this application, the terms involved in this application will be briefly explained below.

[0154] (1) Channel state information (CSI) measurement:

[0155] In communication systems (e.g., Long-Term Evolution (LTE) or NR communication systems), network devices can use Channel Information Structure (CSI) to determine the resources, modulation and coding scheme (MCS), and precoding configurations of downlink data channels for terminal devices. CSI is understood to be a type of channel information, reflecting channel characteristics and quality. For example, CSI can be represented using a channel matrix, such as including the channel matrix, or it can include the channel's eigenvectors.

[0156] CSI measurement refers to the process by which the receiver deciphers channel information based on a reference signal transmitted by the transmitter; that is, it uses channel estimation methods to estimate channel information. The propagation of a wireless signal in a channel can be represented as Y = HX + N. noise Where H is CSI, X is the reference signal, and N is the reference signal. noiseLet Y be the noise and Y be the received signal. The reference signal X is known information specified by the terminal equipment and network equipment. After acquiring the received signal Y, channel estimation algorithms, such as least squares method and least mean square error method, can be used to perform channel estimation. For example, the reference signal X may include one or more of the following: channel state information reference signal (CSI-RS), synchronizing signal / physical broadcast channel block (SSB), sounding reference signal (SRS), or demodulation reference signal (DMRS). CSI-RS, SSB, and DMRS can be used to measure downlink CSI. SRS and DMRS can be used to measure uplink CSI.

[0157] Taking FDD communication as an example, in FDD communication, since the uplink and downlink channels are not reciprocal or their reciprocity cannot be guaranteed, network devices typically send downlink reference signals to terminal devices. The terminal devices then perform channel measurements and interference measurements based on the received downlink reference signals to estimate the downlink CSI. The terminal devices generate a CSI report according to a predefined protocol method or a network device configuration method and feed it back to the network devices so that they can obtain the downlink CSI.

[0158] For example, CSI may include at least one of the following: channel quality indication (CQI), precoding matrix indicator (PMI), rank indicator (RI), CSI-RS resource indicator (CRI), layer indicator (LI), reference signal receiving power (RSRP), or signal to interference plus noise ratio (SINR), etc. The signal to interference plus noise ratio can also be called the signal-to-interference-plus-noise ratio.

[0159] In this diagram, RI indicates the number of downlink transmission layers suggested by the terminal device, CQI indicates the modulation and coding schemes supported by the current channel conditions as determined by the terminal device, and PMI indicates the precoding suggested by the terminal device. The number of precoding layers indicated by PMI corresponds to RI. For example, if RI is n, then PMI indicates n layers of precoding, where n is a positive integer.

[0160] It should be understood that the RI, CQI, and PMI values ​​indicated in the aforementioned CSI report are merely suggested values ​​for the terminal device. The network device may perform downlink transmission according to some or all of the information indicated in the CSI report. Alternatively, the network device may choose not to perform downlink transmission according to the information indicated in the CSI report.

[0161] (2) CSI measurement configuration:

[0162] The network side can issue CSI measurement configuration information elements (such as CSI-MeasConfig IE) through radio resource control (RRC), including CSI-RS resource configuration and CSI report configuration. Each CSI-MeasConfig IE contains one or more non-zero power (NZP) CSI-RS resources (e.g., NZP-CSI-RS-Resource) and resource sets (e.g., NZP-CSI-RS-ResourceSet), and / or one or more CSI-IM resources (e.g., CSI-IM-Resource) and resource sets (e.g., CSI-IM-ResourceSet), and / or one or more SSB resource sets (e.g., CSI-SSB-ResourceSet), one or more CSI report configurations (e.g., CSI-ReportConfig), one or more CSI resource configurations (e.g., CSI-ResourceConfig), and one or two trigger state lists (e.g., CSI-AperiodicTriggerStateList and CSI-SemiPersistentOnPUSCH-TriggerStateList).

[0163] For example, a single CSI-MeasConfig can configure a maximum of 192 NZP-CSI-RS-Resources, a maximum of 64 NZP-CSI-RS-ResourceSets, a maximum of 64 NZP-SSB-ResourceSets, a maximum of 112 CSI-ResourceConfigs, a maximum of 128 CSI-AperiodicTriggerStates, a maximum of 64 CSI-SemiPersistentOnPUSCH-TriggerStates, and a maximum of 48 CSI-ReportConfigs. The length of the CSI request in the configured downlink control information (DCI) is a maximum of 6 bits.

[0164] The CSI-AperiodicTriggerStateList IE (information element) is used to configure one or more trigger states for aperiodic CSI reporting for the UE, namely CSI-AperiodicTriggerState. Each CSI-AperiodicTriggerState contains one or more associated CSI-ReportConfigs, and one or more of the NZP CSI-RS resource set, CSI-IM resource set, or SSB resource set associated with it for channel measurement and / or interference measurement. The CSI-SemiPersistentOnPUSCH-TriggerStateList IE is used to configure one or more trigger states for PUSCH-based semi-static CSI reporting for the UE, namely CSI-SemiPersistentOnPUSCH-TriggerState. Each CSI-SemiPersistentOnPUSCH-TriggerState contains only one associated CSI-ReportConfig.

[0165] Resource configuration is used to configure the reference signals for calculating CSI. Resource configuration is primarily accomplished through CSI measurement configuration information elements, such as the CSI-ResourceConfig IE. For example, each CSI-ResourceConfig corresponds to a CSI-ResourceConfigId, and each CSI-ResourceConfig corresponds to a CSI-RS-ResourceSetList. This CSI-RS-ResourceSetList includes one or more CSI Resource Sets, meaning each CSI-ResourceConfig contains / is associated with one or more CSI resource sets. If resourceType is "aperiodic", then the NZP-CSI-RS-ResourceSetList can contain / are associated with a maximum of 16 NZP CSI-RS resource sets; otherwise, it contains / is associated with only one NZP CSI-RS resource set. The NZP-CSI-RS-ResourceSet IE is used to configure NZP CSI-RS resource sets and resource set-specific parameters. Each NZP CSI-RS resource set contains / is associated with one or more NZP CSI-RS resources, where maxNrofNZP-CSI-RS-ResourcesPerSet is 64. The NZP-CSI-RS-Resource IE is used to configure NZP CSI-RS, mainly specifying the structure of the NZP CSI-RS, the physical resource blocks (PRBs) occupied in the frequency domain, and the transmission period and time slot offset.

[0166] The report configuration is used to configure the behavior of CSI reporting. The report configuration is mainly completed through the RRC layer signaling CSI-ReportConfig IE. Each CSI-ReportConfig contains / is associated with one or more resource configurations (associated to a certain CSI-ResourceConfig through CSI-ResourceConfigId), indicating the resource configurations used for channel measurement and / or interference measurement. In addition, each CSI-ReportConfig includes codebook configuration, including Type I, Type II, or enhanced Type II codebooks, and may also include a subset of codebook restrictions; time-domain behavior, including periodic (P), semi-static (e.g., semiPersistentOnPUCCH) based on the physical uplink control channel (PUCCH), semi-static (e.g., semiPersistentOnPUSCH) based on PUSCH, and aperiodic (AP); frequency-domain granularity of CQI and PMI, including wideband and subband; measurement restriction configuration, including restrictions on channel measurements and restrictions on interference measurements; and CSI-related indicators reported by the UE, including CQI, PMI, CRI, SS / PBCH block resource indicator (SSBRI), LI, RI, layer 1 reference signal received power (L1-RSRP), or layer 1 signal to interference plus noise ratio. Configuration parameters such as ratio (L1-SINR) etc.

[0167] The above descriptions of measurement configuration, resource configuration, and reporting configuration are simplified examples; please refer to the specific descriptions in the protocol. Furthermore, if measurement configuration, resource configuration, and reporting configuration are replaced with other similar terms in future communication networks, the proposed solution will still be applicable.

[0168] In the AP CSI report, the NW can indicate the CSI aperiodic triggering state through DCI information. The UE receives the DCI information, determines the triggered CSI aperiodic triggering state based on the CSI request field of the aperiodic triggering state, and further determines the resource set associated with the CSI aperiodic triggering state.

[0169] In AI functionality alignment, the NW queries the UE for measurement-related configurations, and the UE provides feedback on the applicability of the queried configuration. Two scenarios can be involved. In one scenario, when the NW sends RRC information as measurement configuration (e.g., CSI-measConfig), and the CSI resource type involved in the measurement configuration is an aperiodic CSI reference signal, the list of aperiodic CSI trigger states in the measurement configuration may include multiple aperiodic CSI trigger states. Different aperiodic CSI trigger states correspond to different aperiodic CSI reporting configurations and aperiodic CSI-RS resource sets. Therefore, the UE does not know which specific aperiodic CSI trigger state's corresponding CSI reporting configuration and the associated CSI resource set to match or download the model. In the other scenario, when the NW sends RRC information as measurement-related parameters (e.g., inference combination parameters involving reporting configurations), and the CSI resource type involved is an aperiodic CSI reference signal, the list of CSI resource sets associated with the measurement-related parameters includes multiple CSI resource sets. Therefore, the UE does not know which specific aperiodic CSI resource set to download or match the model.

[0170] Based on this, this application provides a communication method that can improve system efficiency by restricting the query behavior of the NW and the feedback behavior of the UE, so that the NW receives more detailed feedback from the UE.

[0171] The methods provided by the embodiments of this application will be described in detail below with reference to the accompanying drawings. The embodiments provided by this application can be applied to the scenarios shown in the above figures and are not limited thereto. In addition, the terms used below can be referred to the foregoing explanations and will not be repeated hereafter. Furthermore, for ease of description, the terminal side and network side are used as examples for illustrative purposes. As an example, the terminal side method can be executed by a terminal device, or by a component of the terminal device (e.g., a chip, chip system, circuit, or communication module), or by a device deployed outside the terminal device (e.g., the host or cloud server of an OTT system) or a component within the device (e.g., a chip, processor, or circuit inside the device). As an example, the network side method can be executed by a network device, or by a component of the network device (e.g., a chip, chip system, circuit, or communication module), or by a device outside the network device (e.g., a smart network element on the network side) or a component within the device (e.g., a chip, processor, or circuit inside the device). Furthermore, the steps described below as being executed by a single execution entity can also be divided into being executed by multiple execution entities, which can be logically and / or physically separated.

[0172] Figure 5 is a schematic flowchart of a communication method 500 provided in an embodiment of this application. This method involves interaction between the network side and the terminal side, and method 500 includes steps S510 and S520.

[0173] S510: The network side sends the measurement configuration, and the terminal side receives the measurement configuration accordingly.

[0174] The measurement configuration can be information used for applicability inquiries within an AI or ML scenario (scenarios can also be referred to as information, use cases, etc., the name is not limited). The following description uses the CSI-MeansConfig IE as an example of the measurement configuration in a CSI measurement scenario. The measurement configuration indicates the configuration and resources used when performing measurement actions. A CSI measurement configuration can include one or more CSI report configurations (CSI-MeansConfig, one or more of CSI-ReportConfig).

[0175] As an example, this measurement configuration can be carried over radio resource control (RRC) information.

[0176] Measurement configurations can include trigger states, reporting configurations, and resource sets. For an introduction to measurement configurations, please refer to the above text; it will not be repeated here.

[0177] Since AI-related descriptions appear repeatedly in the text, a unified explanation is provided here. "AI-related" can be understood as: x is used for AI-related operations, or for operations related to AI models, or for operations related to models. For example, x is used for AI-based CSI-RS feedback enhancement; another example is x used for AI-based beam management enhancement.

[0178] Specifically, for example, the first trigger state list is related to AI, which can be understood as the first trigger state list being used for AI-related operations; or it can also be understood as the first trigger state list including first trigger states used for AI-related operations.

[0179] For example, the first triggering state is related to AI, which can be understood as the first triggering state being used for AI-related operations.

[0180] For example, if the first associated report configuration is related to AI, it can be understood as the first associated report configuration being used for AI-related operations; or, the first report configuration associated with the first associated report configuration being used for AI-related operations, or the first resource set associated with the associated first report configuration being used for AI-related operations.

[0181] For example, if the list of resource sets associated with the first report configuration is related to AI, it can be understood that at least one resource set in the list of resource sets associated with the first report configuration is used for AI-related operations.

[0182] For example, if the first resource set is related to AI, it can be understood as the first resource set being used for AI-related operations.

[0183] For example, the first time slot offset is related to AI, which can be understood as the first time slot offset being used for AI-related operations.

[0184] It should be understood that, for ease of distinction, the terms "first trigger state list," "first trigger state," "first associated report configuration," "first report configuration associated resource set list," and "first resource set" in this application are all related to AI. Terms not modified by "first" are generic, meaning they may or may not be related to AI. For example, "first trigger state list" indicates something related to AI, while "trigger state list" is a generic term; the trigger state list may or may not be related to AI.

[0185] It should also be understood that being related to AI does not mean that all of the configurations are related to AI. For example, if the first trigger state list is related to AI, it does not mean that all the trigger states in the first trigger state list are related to AI. As long as at least one trigger state is related to AI, the first trigger state list can be considered to be related to AI.

[0186] The measurement configuration is associated with a list of first trigger states, which includes multiple first trigger states. Alternatively, it can be described as the measurement configuration including a list of first trigger states, or the measurement configuration associating with multiple first trigger states. In other words, the measurement configuration includes multiple first trigger states.

[0187] A measurement configuration may include one or two first trigger state lists. These first trigger state lists are used to configure one or more trigger states on the terminal side. There are two types of first trigger state lists: one is a channel state information aperiodic trigger state list (e.g., CSI-AperiodicTriggerStateList) IE, and the other is a channel state information PUCCH-based semi-static trigger state list (e.g., CSI-SemiPersistentOnPUSCH-TriggerStateList) IE. The CSI-AperiodicTriggerStateList information element (IE) is used to configure one or more CSI aperiodic trigger states (CSI-AperiodicTriggerState) on the terminal side. The CSI-SemiPersistentOnPUSCH-TriggerStateList IE is used to configure one or more channel state information PUCCH-based semi-static trigger states (CSI-SemiPersistentOnPUSCH-TriggerState) on the terminal side. Each CSI-AperiodicTriggerState contains one or more associated CSI-ReportConfigs, and one or more of the NZP CSI-RS resource set, CSI-IM resource set, or SSB resource set associated with it for channel measurement and / or interference measurement. Each CSI-SemiPersistentOnPUSCH-TriggerState contains only one associated CSI-ReportConfig.

[0188] The following description uses CSI-AperiodicTriggerStateList IE as an example, where the first trigger state list is CSI-AperiodicTriggerState and the first trigger state is CSI-AperiodicTriggerState. For CSI-SemiPersistentOnPUSCH-TriggerStateList IE, you can refer to the case where CSI-AperiodicTriggerState is associated with a CSI-ReportConfig.

[0189] The first trigger state list is a list containing multiple trigger states. Each trigger state specifies a set of CSI measurement parameters, such as measurement resources, reporting modes, and trigger conditions. A trigger state can be understood as a trigger state used to configure CSI reporting on the terminal side. A trigger state may contain one or more associated report configuration (CSI-ReportConfig) IEs, and associated measurement resource IEs (e.g., one or more NZP CSI-RS resource sets, CSI-IM resource sets, or SSB resource sets used for channel and / or interference measurements). The implementation of the first trigger state list can include the following two scenarios.

[0190] In the first scenario, all trigger states in the first trigger state list are AI-related; in other words, all trigger states in the first trigger state list are first trigger states. For example, the first trigger state list can include 16 first trigger states. Specifically, trigger state list #1 includes the following trigger states: {First trigger state #1, First trigger state #2, First trigger state #3, First trigger state #4, First trigger state #5, First trigger state #6, First trigger state #7, First trigger state #8, First trigger state #9, First trigger state #10, First trigger state #11, First trigger state #12, First trigger state #13, First trigger state #14, First trigger state #15, First trigger state #16}.

[0191] In the second scenario, some of the first trigger states are related to AI; in other words, the list of first trigger states includes at least one first trigger state. For example, the list of first trigger states may include 5 first trigger states, or it may include 16 trigger states. Specifically, trigger state list #2 includes the following trigger states: {First Trigger State #1, First Trigger State #2, First Trigger State #3, First Trigger State #4, First Trigger State #5, Trigger State #6, Trigger State #7, Trigger State #8, Trigger State #9, Trigger State #10, Trigger State #11, Trigger State #12, Trigger State #13, Trigger State #14, Trigger State #15, Trigger State #16}.

[0192] The first trigger state is associated with N first associated report configurations (e.g., associatedReportConfigInfo), where N is a positive integer. The first trigger state being associated with N first associated report configurations can also be described as the first trigger state including N first associated report configurations. The first trigger state being associated with N first associated report configurations can include the following two cases.

[0193] In the first scenario, all associated report configurations related to the first trigger state are AI-related; in other words, all associated report configurations related to the first trigger state are the first associated report configurations.

[0194] For example, when N equals 16, the first trigger state #1 can be associated with 16 first associated report configurations. Specifically, the associated report configurations of the first trigger state #1 are: {First Associated Report Configuration #1, First Associated Report Configuration #2, First Associated Report Configuration #3, First Associated Report Configuration #4, First Associated Report Configuration #5, First Associated Report Configuration #6, First Associated Report Configuration #7, First Associated Report Configuration #8, First Associated Report Configuration #9, First Associated Report Configuration #10, First Associated Report Configuration #11, First Associated Report Configuration #12, First Associated Report Configuration #13, First Associated Report Configuration #14, First Associated Report Configuration #15, First Associated Report Configuration #16}.

[0195] In the second scenario, the associated report configuration of the first trigger state is related to AI; in other words, the first trigger state is associated with at least one first report configuration.

[0196] For example, when N equals 5, the first trigger state #2 can be associated with 16 report configurations. Specifically, the associated report configurations of the first trigger state #2 are: {First associated report configuration #1, First associated report configuration #2, First associated report configuration #3, First associated report configuration #4, First associated report configuration #5, Associated report configuration #6, Associated report configuration #7, Associated report configuration #8, Associated report configuration #9, Associated report configuration #10, Associated report configuration #11, Associated report configuration #12, Associated report configuration #13, Associated report configuration #14, Associated report configuration #15, Associated report configuration #16}.

[0197] Measurement configurations include multiple report configurations, with one trigger state associated with multiple report configurations. It should be understood that the report configuration is either a ReportConfig IE or a CSI-ReportConfig IE. Associating one trigger state with multiple report configurations includes two scenarios.

[0198] In the first scenario, all report configurations associated with the first trigger state are AI-related; in other words, all report configurations associated with the first trigger state are first report configurations. For example, the first trigger state may include 16 first report configurations. Specifically, report configuration list #1 includes the following report configurations: {First report configuration #1, First report configuration #2, First report configuration #3, First report configuration #4, First report configuration #5, First report configuration #6, First report configuration #7, First report configuration #8, First report configuration #9, First report configuration #10, First report configuration #11, First report configuration #12, First report configuration #13, First report configuration #14, First report configuration #15, First report configuration #16}.

[0199] In the second scenario, some report configurations associated with the first trigger state are related to AI; in other words, the first trigger state is associated with at least one first report configuration. For example, the first trigger state may include 5 first report configurations, or a total of 16 report configurations. Specifically, report configuration list #2 includes the following report configurations: {First report configuration #1, First report configuration #2, First report configuration #3, First report configuration #4, First report configuration #5, Report configuration #6, Report configuration #7, Report configuration #8, Report configuration #9, Report configuration #10, Report configuration #11, Report configuration #12, Report configuration #13, Report configuration #14, Report configuration #15, Report configuration #16}.

[0200] The report configurations associated with different trigger states can be completely different, partially the same, or completely identical.

[0201] The report configurations associated with different trigger states can be completely different. For example, the 16 report configurations associated with trigger state #1 are completely different from the 16 report configurations associated with trigger state #2.

[0202] Report configurations associated with different trigger states can be partially the same. For example, report configuration #1 associated with trigger state #1 is different from report #1 associated with trigger state #2, while report configurations #2 to #16 associated with trigger state #1 are the same as report configurations #2 to #16 associated with trigger state #2.

[0203] Report configurations associated with different trigger states can be exactly the same. For example, the report configurations #1 to #16 associated with trigger state #1 are the same as those associated with trigger state #2.

[0204] It should be understood that whether a report configuration is related to AI can be determined based on whether the resource set associated with the report configuration is related to AI, or based on whether the report configuration includes model configurations related to AI applications, such as coding models.

[0205] It should also be understood that the measurement configuration includes multiple reporting configurations, which may include a primary reporting configuration related to AI, or reporting configurations that are not related to AI.

[0206] A report configuration is associated with a resource set list, which includes multiple resource sets. The resource set list can represent any of the following: NZP-CSI-RS-ResourceSetList IE, CSI-IM-ResourceSetList IE, or CSI-SSB-ResourceSetList IE.

[0207] In the first scenario, all resource sets in the first resource set list are AI-related; in other words, all resource sets in the first resource set list are first resource sets. For example, the first resource set list can include 16 first resource sets. Specifically, resource set list #1 includes the following resource sets: {First Resource Set #1, First Resource Set #2, First Resource Set #3, First Resource Set #4, First Resource Set #5, First Resource Set #6, First Resource Set #7, First Resource Set #8, First Resource Set #9, First Resource Set #10, First Resource Set #11, First Resource Set #12, First Resource Set #13, First Resource Set #14, First Resource Set #15, First Resource Set #16}.

[0208] In the second scenario, some resource sets in the first resource set are related to AI. In other words, the list of first resource sets includes at least one first resource set. For example, the list of first resource sets may include 5 first resource sets, or it may include 16 resource sets. Specifically, resource set list #2 includes the following resource sets: {First Resource Set #1, First Resource Set #2, First Resource Set #3, First Resource Set #4, First Resource Set #5, Resource Set #6, Resource Set #7, Resource Set #8, Resource Set #9, Resource Set #10, Resource Set #11, Resource Set #12, Resource Set #13, Resource Set #14, Resource Set #15, Resource Set #16}.

[0209] The resource sets associated with different report configurations can be completely different, partially the same, or completely identical.

[0210] The resource sets associated with different report configurations can be completely different. For example, the 16 resource sets associated with report configuration #1 are completely different from the 16 resource sets associated with report configuration #2.

[0211] The resource sets associated with different report configurations can be partially the same. For example, the resource set #1 associated with report configuration #1 is different from the report #1 associated with report configuration #2, while the resource sets #2 to #16 associated with report configuration #1 are the same as the resource sets #2 to #16 associated with report configuration #2.

[0212] The resource sets associated with different report configurations can be exactly the same. For example, the resource sets #1 to #16 associated with report configuration #1 are all the same as the resource sets associated with report configuration #2.

[0213] It should be understood that whether a resource set is related to AI can be determined based on whether the resource set is used for AI-related operations, or the network side can also indicate that the resource set is the first resource set in the measurement configuration.

[0214] It should also be understood that a report configuration associated with multiple resource sets may include a first resource set related to AI, or it may include resource sets that are not related to AI.

[0215] Each report configuration is associated with a slot offset list, which contains multiple slot offsets. The slot offset list can be a `reportSlotOffsetList` IE, and the slot offsets can be `reportSlotOffset` IE. A slot offset list containing multiple slot offsets can include two scenarios.

[0216] In the first case, all time slot offsets in the first time slot offset list are AI-related; in other words, all time slot offsets in the first time slot offset list are first time slot offsets. For example, the first time slot offset list may include 16 first time slot offsets. Specifically, time slot offset list #1 includes the following time slot offsets: {first time slot offset #1, first time slot offset #2, first time slot offset #3, first time slot offset #4, first time slot offset #5, first time slot offset #6, first time slot offset #7, first time slot offset #8, first time slot offset #9, first time slot offset #10, first time slot offset #11, first time slot offset #12, first time slot offset #13, first time slot offset #14, first time slot offset #15, first time slot offset #16}.

[0217] In the second scenario, some time slot offsets in the first time slot offset are related to AI. In other words, the first time slot offset list includes at least one first time slot offset. For example, the first time slot offset list may include 5 first time slot offsets, or 16 time slot offsets. Specifically, time slot offset list #2 includes the following time slot offsets: {first time slot offset #1, first time slot offset #2, first time slot offset #3, first time slot offset #4, first time slot offset #5, time slot offset #6, time slot offset #7, time slot offset #8, time slot offset #9, time slot offset #10, time slot offset #11, time slot offset #12, time slot offset #13, time slot offset #14, time slot offset #15, time slot offset #16}.

[0218] The time slot offsets included in different time slot offset lists can be completely different, partially the same, or completely the same.

[0219] The time slot offsets included in different time slot offset lists can be completely different. For example, the 16 time slot offsets included in time slot offset list #1 are completely different from the 16 time slot offsets included in time slot offset list #2.

[0220] The time slot offsets included in different time slot offset lists may be partially the same. For example, the time slot offset #1 included in time slot offset list #1 is different from the time slot offset #1 included in time slot offset list #2, while the time slot offsets #2 to #16 included in time slot offset list #1 are the same as the time slot offsets #2 to #16 included in time slot offset list #2.

[0221] The time slot offsets included in different time slot offset lists can be exactly the same. For example, the time slot offsets #1 to #16 included in time slot offset list #1 are the same as those included in time slot offset list #2.

[0222] The first associated report configuration indicates the association between the first report configuration and the first resource set.

[0223] Figure 6 is a schematic diagram illustrating the association between the configuration of the associated report and the resource set according to an embodiment of this application.

[0224] As shown in Figure 6, the first associated report configuration includes a report configuration identifier (ReportConfigId). Based on this identifier, a first report configuration can be associated with a first resource set list. The first report configuration also includes a resource index (e.g., resourcesForChannel) for channel state information measurement. This resourcesForChannel index indicates the index of a resource set in the first resource set list. In other words, the first associated report configuration indicates the association between the first report configuration and the first resource set; further, the first associated report configuration and the first report configuration are associated with a first resource.

[0225] In S510, the network side queries the terminal side about the applicability of the measurement configuration by sending a measurement configuration. In this embodiment, the network side only queries the applicability of configurations related to AI. Specifically, the measurement configuration may include first indication information, which indicates one or more of the following related to AI: the first trigger state list, the first trigger state, the first associated report configuration, the resource set list associated with the first report configuration, the first resource set, and the first time slot offset.

[0226] The first indication information can be provided in two ways. The first way is to set the L AI-related configurations in the first L positions of the sequence, with the first information indicating the value of L. The second way is to set an index for each configuration, with the first indication information indicating the index of the AI-related configuration in the measurement configuration. The following example uses a first resource set list. If the first resource set list includes M resource sets, where L are first resource sets, and M and L are both positive integers, with M greater than or equal to L. For example, M could be 16 and L could be 5.

[0227] The first approach involves setting the L AI-related configurations in the first L positions of the sequence, with the first indication indicating the value of L. For example, resource set list #2 includes the following resource sets: {First Resource Set #1, First Resource Set #2, First Resource Set #3, First Resource Set #4, First Resource Set #5, Resource Set #6, Resource Set #7, Resource Set #8, Resource Set #9, Resource Set #10, Resource Set #11, Resource Set #12, Resource Set #13, Resource Set #14, Resource Set #15, Resource Set #16}. Among these, First Resource Set #1, First Resource Set #2, First Resource Set #3, First Resource Set #4, and First Resource Set #5 are AI-related, while Resource Set #6, Resource Set #7, Resource Set #8, Resource Set #9, Resource Set #10, Resource Set #11, Resource Set #12, Resource Set #13, Resource Set #14, Resource Set #15, and Resource Set #16 are not used for AI-related operations and can be considered as not being AI-related.

[0228] It should be understood that L can be indicated by the first indication information, that is, L can be indicated by the network side. In addition, L can also be predefined or configured, without limitation.

[0229] The second approach involves setting an index for each configuration, with the first indication information pointing to the index of the AI-related configuration in the measurement configuration. For example, resource set list #3 includes resource sets: {first resource set #1, resource set #2, first resource set #3, resource set #4, first resource set #5, resource set #6, first resource set #7, resource set #8, first resource set #9, resource set #10, resource set #11, resource set #12, resource set #13, resource set #14, resource set #15, resource set #16}. Among these, first resource sets #1, #3, #5, #7, and #9 are AI-related, while resource sets #2, #4, #6, #8, #10, #11, #12, #13, #14, #15, and #16 are not used for AI-related operations and can be understood as not being AI-related. In this approach, the resource set indexed {1,3,5,7,9} is AI-related, while the remaining resource sets are not AI-related.

[0230] The index can be implemented using a subset list, which indicates which resource sets in the first resource set list are AI-related resource sets indicated by resource set identifiers (id).

[0231] In one implementation, the subsetlist index is at the same level as the ResourceConfigId. For example, in a beam management (BM) scenario, there are two subsetlists, and the index can be implemented as follows: SetA has the CSI-ResourceConfigId and the subsetlist index of SetA, and SetB has the CSI-ResourceConfigId and the subsetlist index of SetB.

[0232] In another implementation, the subsetlist index is at the same level as CSI-ReportConfigId.

[0233] For example, in the BM scenario, the subsetlist includes two sets, and the index can be implemented as follows: CSI-ReportConfigId and the subsetlist index corresponding to setA, and the subsetlist index corresponding to setB.

[0234] In the measurement configuration, by setting AI-related identifiers for resource sets (e.g., the first method in the above example (setting the first n resource sets to be AI-related) or the second method (indicating the index of the resource set used for AI operations)), the implementation of the measurement configuration can avoid affecting the resource usage of legacy applications or applications in non-AI use cases / scenarios. Legacy applications can also be replaced or understood as applications in non-AI use cases / scenarios. For example, if the network side only wants the terminal side to predict the Top1 beam or RSRP of the 8-beam (set1) and 16-beam (set2) resource sets, and does not need the terminal side to predict the Top1 beam or RSRP of the 32-beam (set3) resource set based on AI, then the 8-beam (set1) and 16-beam (set2) resource sets can be set to be AI-related. This allows the network side to only query the applicability of resources set to be AI-related, without affecting legacy applications or applications in non-AI use cases / scenarios, while the terminal side reports the RSRP of sets1, 2, and 3.

[0235] The above describes the contents of the measurement configuration. The network side queries the terminal side about the applicability of the measurement configuration. The following describes how the terminal side provides feedback on the applicability of the measurement configuration.

[0236] S520, the terminal side sends first information, and correspondingly, the network side receives the first information, wherein the first information indicates the applicability of the measurement configuration.

[0237] The first information indicating the suitability of the measurement configuration can be implemented in two ways: the first method is that the first information indicates the suitability of the first trigger state; the second method is that the first information indicates the suitability of the first trigger state list.

[0238] In the first implementation, the first information indicates the applicability of the first triggering state. The applicability of the first triggering state is related to the configuration of the N first associated reports.

[0239] Method 1: The first information indicates whether the first trigger state is applicable or not.

[0240] Scenario 1: When the configuration of N first associated reports associated with the first trigger state is applicable, the first trigger state is applicable. In this case, the first information indicates that the first trigger state is applicable.

[0241] For example, if the first trigger state is associated with 16 associated report configurations, and 5 of these are first associated report configurations (i.e., the first trigger state is associated with 5 first associated report configurations, and N equals 5), then when these 5 first associated report states are applicable, or in other words, the terminal side supports these 5 first associated report configurations, the first information indicates that the first trigger state is applicable.

[0242] For example, when the first trigger state is associated with 16 associated report configurations, where all 16 associated report configurations are the first associated report configuration, that is, the first trigger state is associated with 16 first associated report configurations, and N equals 16. When these 16 first associated report states are applicable, or in other words, the terminal side supports these 16 first associated report configurations, then the first information indicates that the first trigger state is applicable.

[0243] Scenario 2: If one of the N first associated report configurations associated with the first trigger state is not applicable, the first trigger state is not applicable. In this case, the first information indicates that the first trigger state is not applicable.

[0244] For example, if a first trigger state is associated with 16 associated report configurations, and 5 of these are first associated report configurations (i.e., the first trigger state is associated with 5 first associated report configurations, and N equals 5), and one of these 5 first associated report states is inapplicable, or in other words, at least one of these 5 first associated report configurations is inapplicable on the terminal side, then the first information indicates that the first trigger state is inapplicable.

[0245] For example, when the first trigger state is associated with 16 associated report configurations, where all 16 associated report configurations are first associated report configurations (i.e., the first trigger state is associated with 16 first associated report configurations, and N equals 16), if any of these 16 first associated report states is inapplicable, or in other words, at least one of the 16 first associated report configurations is inapplicable on the terminal side, then the first information indicates that the first trigger state is inapplicable.

[0246] Method 2: The first information indicates the applicability of each of the N first associated report configurations associated with the first trigger state.

[0247] Specifically, for example, when the first trigger state is associated with 16 associated report configurations, and 5 of these are first associated report configurations, that is, the first trigger state is associated with 5 first associated report configurations, and N equals 5. The first information indicates the applicability of each of these 5 first associated report configurations.

[0248] For example, when the first trigger state is associated with 16 associated report configurations, where all 16 associated report configurations are first associated report configurations, that is, the first trigger state is associated with 16 first associated report configurations, and N equals 16. The first information indicates the applicability of each of the 16 first associated report configurations.

[0249] The applicability of the first associated report configuration is related to the applicability of the first report configuration and the applicability of the first resource set. In other words, the applicability of the first associated report configuration can be determined based on its associated first report configuration and first resource set.

[0250] Scenario 1: If the first report configuration and the first resource set are applicable, the first report configuration applies.

[0251] For example, the first associated report configuration #1 is associated with the first report configuration #1, the first report configuration #1 is associated with the first resource set list #1, and the first associated report configuration #1 also includes resourcesForChannel #1, which can be associated with the first resource set #1 in the first resource set list #. The first report configuration #1 is applicable when both the first report configuration #1 and the first resource set #1 are applicable.

[0252] Scenario 2: If either the first report configuration or the first resource set is not applicable, the first associated report configuration is not applicable.

[0253] For example, the first associated report configuration #2 is associated with the first report configuration #2, the first report configuration #2 is associated with the first resource set list #2, and the first associated report configuration #2 also includes resourcesForChannel #2, which can be associated with the first resource set #2 in the first resource set list #. The first report configuration #2 is not applicable when it is not applicable or when the first resource set #2 is not applicable.

[0254] The applicability of the first report configuration includes two scenarios: the first report configuration is applicable and the first report configuration is not applicable.

[0255] The first report configuration is applicable in the following situations: The applicability of the first report configuration is "applicable," which can also be referred to as "terminal-side support for the first report configuration." There are two ways to determine the applicability of the first report configuration.

[0256] Method 1: If all the configuration information in the first report configuration is applicable, the first report configuration is applicable.

[0257] The report configuration defines how the terminal reports CSI; in other words, it configures the reference signal for calculating CSI. The report configuration includes one or more of the following: report mode (such as RI, CQI, PMI, L1-RSRP, etc.), reporting trigger conditions, and measurement object. For example, the first report configuration may include RI; when RI is applicable, the first report configuration is applicable. Or, the first report configuration may include both RI and CQI; when both RI and CQI are applicable, the first report configuration is applicable.

[0258] Method 2: At least one time slot offset in the first report configuration applies, and the first report configuration applies.

[0259] For example, the first report configuration #1 may include 16 time slot offsets. Specifically, the report configuration #1 includes the following time slot offsets: {time slot offset #1, time slot offset #2, time slot offset #3, time slot offset #4, time slot offset #5, time slot offset #6, time slot offset #7, time slot offset #8, time slot offset #9, time slot offset #10, time slot offset #11, time slot offset #12, time slot offset #13, time slot offset #14, time slot offset #15, time slot offset #16}. If any one of these 16 time slot offsets is applicable, then the first report configuration is applicable.

[0260] The first report configuration is not applicable in the following situations: The applicability of the first report configuration is not applicable, which can also be referred to as the terminal side not supporting the first report configuration. Determining that the first report configuration is not applicable can include the following methods: The first report configuration is not applicable when all time slot offsets associated with the first report configuration are not applicable.

[0261] Optionally, the first information may also indicate the applicability of each of the multiple time slot offsets. The applicability of a time slot offset indicates that the terminal device supports that time slot offset. Since the time slot offsets included in the first report configuration may not be fully applicable when the first report configuration is applicable, the first information can further indicate the applicability of each of the multiple time slot offsets. This allows the network side to have a more detailed understanding of the applicability of the measurement configuration to the terminal side.

[0262] The second implementation method is to use the first information to indicate the applicability of the first trigger state list.

[0263] Method 1: The first information indicates whether the first trigger state list is applicable or not.

[0264] Scenario 1: If each of the first trigger states included in the first trigger state list is applicable, the first trigger state list is applicable. In this case, the first information indicates that the first trigger state list is applicable.

[0265] For example, if the first trigger state list includes 16 trigger states, and 5 of these are first trigger states (i.e., the first trigger state list includes 5 first trigger states, and N equals 5), then when all 5 first trigger states are applicable, or in other words, the terminal supports these 5 first trigger states, the first information indicates that the first trigger state list is applicable.

[0266] For example, when the first trigger state list includes 16 trigger states, and all 16 trigger states are first trigger states (i.e., the first trigger state list includes 16 first trigger states, N equals 16), and these 16 first trigger states include reporting states, or in other words, the terminal side supports these 16 first trigger states, then the first information indicates that the first trigger state list is applicable.

[0267] Scenario 2: If one of the first trigger states included in the first trigger state list is not applicable, the first trigger state list is not applicable. In this case, the first information indicates that the first trigger state list is not applicable.

[0268] For example, if the first trigger state list includes 16 trigger states, of which 5 are first trigger states (i.e., the first trigger state list includes 5 first trigger states, and N equals 5), and one of these 5 first trigger states is inapplicable, or in other words, at least one of these 5 first trigger states is inapplicable on the terminal side, then the first information indicates that the first trigger state list is inapplicable.

[0269] For example, if the first trigger state list includes 16 trigger states, where all 16 are first trigger states (i.e., the first trigger state list includes 16 first trigger states, and N equals 16), and one of these 16 first trigger states is inapplicable, or in other words, at least one of these 16 first trigger states is inapplicable on the terminal side, then the first information indicates that the first trigger state list is inapplicable.

[0270] Method 2: The first information indicates the applicability of each of the multiple first trigger states included in the first trigger state list.

[0271] Specifically, for example, when the first trigger state list includes 16 trigger states, of which 5 are first trigger states, that is, the first trigger state list includes 5 first trigger states, and N equals 5. The first information indicates the applicability of each of the 5 first trigger states.

[0272] For example, when the first trigger state list includes 16 trigger states, where all 16 trigger states are first trigger states, that is, the first trigger state list includes 16 first trigger states, and N equals 16. The first information indicates the applicability of each of the 16 first trigger states.

[0273] Method 3: The first information indicates whether the first trigger state list is applicable or not, and indicates the applicability of each first trigger state in the first trigger state list.

[0274] Specifically, in scenario two of method one, the first information indicates that the first trigger state list is not applicable, and at the same time, it can further indicate the applicability of each trigger state under the first trigger state list, so that the network side can know a more specific applicability situation.

[0275] Method 4: The first information indicates the applicability of each first associated report configuration associated with each first trigger state in the first trigger state list.

[0276] Specifically, for example, the first trigger state list #4 includes 16 trigger states, of which 2 are first trigger states, meaning the first trigger state list includes 2 first trigger states, and N equals 2. These 2 first trigger states are denoted as first trigger state #1 and first trigger state #2. For example, first trigger state #1 is associated with 2 first associated report configurations, and first trigger state #2 is associated with 3 first report configurations. In this example, the first information can indicate the applicability of the 2 first associated report configurations associated with first trigger state #1 and the applicability of the 3 first report configurations associated with first trigger state #2.

[0277] It should be understood that the above implementation methods one to four are merely examples. The applicability of the first information indicating the first trigger state list can be set to finer granularity according to the actual situation. For example, it can only indicate whether the first trigger state list is applicable or not, or it can further indicate the applicability of each trigger state in the first trigger state list. Alternatively, the granularity can be further increased, which is not limited in this application.

[0278] Optionally, prior to S510, method 500 further includes the network side sending a UECapabilityEnquiry message to the terminal side, and correspondingly, the terminal side receiving the UECapabilityEnquiry message. The UECapabilityEnquiry message is used to instruct the terminal side to report whether it supports AI or ML functions. The terminal side sends a UECapabilityInformation message to the network side, and correspondingly, the network side receives the UECapabilityInformation message. The UECapabilityInformation message can indicate the functions supported by the terminal side.

[0279] Optionally, following S520, method 500 further includes the network side sending a measurement configuration to the terminal side, and correspondingly, the terminal side receiving the measurement configuration. A description of the measurement configuration can be found in S510. This step is required in the following situations.

[0280] In the first scenario, if the configuration applicability indicated by the first information in S520 cannot meet the requirements, for example, if the applicability of the first trigger status list in S520 is not applicable, the measurement configuration can be re-performed.

[0281] In the second scenario, when the capabilities of the terminal side change, the network side can reconfigure the measurement.

[0282] Optionally, method 500 further includes the network side sending DCI information to the terminal side, and correspondingly, the terminal side receiving the DCI information. The DCI information may include a CSI request and / or a time domain resource assignment. This DCI information can be used to determine the triggering state. If the triggering state of the DCI trigger includes multiple CSI report configurations, the maximum time slot offset in the report configuration can be determined through the time domain resource assignment field in the DCI information. Furthermore, the time slot offset for the physical uplink shared channel (PUSCH) sent from the terminal side to the network side can be determined.

[0283] The above, in conjunction with Figure 6 and Method 500, describes how the network side sends the measurement configuration to the terminal side, and the terminal side provides feedback on the applicability of the trigger state, enabling the network side to know the applicability of the measurement configuration to the terminal side. The following, in conjunction with Figure 7, describes the complete CSI report process based on the applicability inquiry method provided by Method 500.

[0284] Figure 7 is a schematic flowchart of a communication method provided in an embodiment of this application. The method 700 shown in Figure 7 relates to an interaction method between the network side and the terminal side, and includes the following steps.

[0285] Optionally, in S701, the network side sends a UECapabilityEnquiry message to the terminal side, and the terminal side receives the UECapabilityEnquiry message accordingly. The UECapabilityEnquiry message is used to instruct the terminal side to report whether it supports AI or ML functions.

[0286] Optionally, in S702, the terminal sends a UE Capability Information message to the network side, and the network side receives the UE Capability Information message accordingly. The UE Capability Information message can indicate the functions supported by the terminal.

[0287] S710: The network side sends the measurement configuration, and the terminal side receives the measurement configuration accordingly.

[0288] S720, the terminal side sends first information, and correspondingly, the network side receives the first information, wherein the first information indicates the suitability of the measurement configuration.

[0289] Optionally, in S730, the network side sends the measurement configuration, and correspondingly, the terminal side receives the measurement configuration. Examples of scenarios for performing this step are as follows: First, if the configuration applicability indicated by the first information in S520 cannot meet the requirements, for example, if the applicability of the first trigger state list in S720 is inapplicable, the measurement configuration can be re-performed. Second, when the capabilities of the terminal side change, the network side can re-perform the measurement configuration by executing S550.

[0290] Optionally, in S740, the terminal side sends first information, and correspondingly, the network side receives the first information, wherein the first information indicates the suitability of the measurement configuration in S730.

[0291] Optionally, in S750, the network side sends DCI information to the terminal side, and the terminal side receives the DCI information accordingly. The DCI information may include a CSI request and / or a time domain resource assignment. This DCI information can be used to determine the triggering state. If the triggering state of the DCI trigger includes multiple CSI report configurations, the maximum time slot offset in the report configuration can be determined through the time domain resource assignment field in the DCI information. Furthermore, the time slot offset for the physical uplink shared channel (PUSCH) sent from the terminal side to the network side can be determined.

[0292] Optionally, method 700 also includes reporting a CSI report on the terminal side based on the trigger status and slot offset indicated by S750.

[0293] For details not covered in Method 700, please refer to Method 500; they will not be repeated here.

[0294] Method 500 above describes how the network side sends measurement configurations to the terminal side. This measurement configuration, by querying the applicability of AI-related configurations (e.g., AI-related trigger states, AI-related resource sets), allows the terminal side to inform the network side of the applicability of the trigger states, or more granular configurations (e.g., the applicability of associated report configurations related to trigger states). Method 700 demonstrates the complete CSI reporting process.

[0295] The following describes, using method 800, how the network side sends a first query parameter to the terminal side. This first query parameter is an information element in the report configuration or an information element of the configuration associated with the report configuration. The terminal side provides feedback to the network side on the applicability of this first query parameter, enabling the network side to obtain the terminal side's applicability to the parameter and thus configure the measurement configuration for the terminal side.

[0296] Figure 8 is a schematic flowchart of another communication method provided in an embodiment of this application. The method 800 shown in Figure 8 involves the interaction between the network side and the terminal side. Method 800 includes S810 and S820. Optionally, the method further includes S830.

[0297] S810, the network side sends the first query parameter, and correspondingly, the terminal side receives the first query parameter.

[0298] The first query parameter can be one or more reason-related parameter sets used for adaptation. For example, it can be an IE in CSI-ReportConfig or an IE referenced by CSI-ReportConfig that selects inference-related parameters.

[0299] The first query parameter is related to at least one of the following: a first resource set list, R first resource sets in the first resource set list, a first time slot offset list, or a first time slot offset in the first time slot offset list, where R is a positive integer.

[0300] For an introduction to the first resource set list, the first resource set, the first time slot offset list, and the first time slot offset, please refer to Method 500; it will not be repeated here.

[0301] Among them, the R first resource set identifiers include R AI-related resource sets in the first resource set list.

[0302] In the first scenario, all resource sets in the first resource set list are AI-related; in other words, all resource sets in the first resource set list are first resource sets. For example, the first resource set list can include 16 first resource sets. Specifically, resource set list #1 includes the following resource sets: {First Resource Set #1, First Resource Set #2, First Resource Set #3, First Resource Set #4, First Resource Set #5, First Resource Set #6, First Resource Set #7, First Resource Set #8, First Resource Set #9, First Resource Set #10, First Resource Set #11, First Resource Set #12, First Resource Set #13, First Resource Set #14, First Resource Set #15, First Resource Set #16}.

[0303] In the second scenario, some resource sets in the first resource set are related to AI. In other words, the list of first resource sets includes at least one first resource set. For example, the list of first resource sets may include 5 first resource sets, or it may include 16 resource sets. Specifically, resource set list #2 includes the following resource sets: {First Resource Set #1, First Resource Set #2, First Resource Set #3, First Resource Set #4, First Resource Set #5, Resource Set #6, Resource Set #7, Resource Set #8, Resource Set #9, Resource Set #10, Resource Set #11, Resource Set #12, Resource Set #13, Resource Set #14, Resource Set #15, Resource Set #16}.

[0304] The network side sends a first query parameter to inquire about the applicability of the first query parameter to the terminal side. In this embodiment, the network side only queries the applicability of the parameter set related to AI. Specifically, the first query parameter may include second indication information, which is used to indicate that the first resource set is related to AI.

[0305] The second indication information can be provided in two ways. The first way is to place the L first resource sets related to AI in the first L positions of the first resource set sequence, with the first information indicating the value of L. The second way is to assign an index to each resource set, with the second indication information indicating the index of the first resource set related to AI in the first resource set list. If the first resource set list includes M resource sets, where L are first resource sets, and both M and L are positive integers, with M greater than or equal to L. For example, M could be 16 and L could be 5.

[0306] The first method sets the L AI-related configurations in the first L positions of the sequence, and the second indication information indicates the value of L. For example, resource set list #2 includes resource sets: {first resource set #1, first resource set #2, first resource set #3, first resource set #4, first resource set #5, resource set #6, resource set #7, resource set #8, resource set #9, resource set #10, resource set #11, resource set #12, resource set #13, resource set #14, resource set #15, resource set #16}, where first resource set #1, first resource set #2, first resource set #3, first resource set #4, and first resource set #5 are AI-related, while resource sets #6, #7, #8, #9, #10, #11, #12, #13, #14, #15, and #16 are not used for AI-related operations and can be understood as not being AI-related.

[0307] It should be understood that L can be indicated by the second indication information, that is, L can be indicated by the network side. In addition, L can also be predefined or configured, without limitation.

[0308] The second approach is to set an index for each resource set, with the second indication information pointing to the index of the first resource set related to AI in the first resource set list. For example, resource set list #3 includes the following resource sets: {first resource set #1, resource set #2, first resource set #3, resource set #4, first resource set #5, resource set #6, first resource set #7, resource set #8, first resource set #9, resource set #10, resource set #11, resource set #12, resource set #13, resource set #14, resource set #15, resource set #16}. Among these, first resource sets #1, #3, #5, #7, and #9 are related to AI, while resource sets #2, #4, #6, #8, #10, #11, #12, #13, #14, #15, and #16 are not used for AI-related operations and can be understood as not being related to AI. In this approach, the resource set indexed {1,3,5,7,9} is AI-related, while the remaining resource sets are not AI-related.

[0309] The index can be implemented using a subset list, which indicates which resource set identifiers (IDs) in the first resource set list are AI-related resource sets.

[0310] The following describes several ways to implement the first query parameter.

[0311] In one implementation, the first query parameter may include a first resource set list.

[0312] In another implementation, the first query parameter may include a first time slot offset list.

[0313] In another implementation, the first query parameters may include a first resource set list and a first time slot list.

[0314] It should be understood that the above is only an example. The first query parameter may also include information elements in other report configurations or information elements referenced by the report configuration. The information elements referenced by the report configuration can be understood as information elements in other configurations associated with the report configuration, such as resource sets in the resource set list associated with the report configuration.

[0315] S820, the terminal sends second information, and the network receives the second information accordingly. The second information indicates the applicability of the first query parameter. The applicability of the first query parameter indicates whether the terminal supports the first query parameter.

[0316] The applicability of the first query parameter can include two cases. The first case is the applicability of one or more parameters included in the first query parameter. The second case is that the applicability of the first query parameter is either applicable or not applicable. These will be described separately below.

[0317] In the first case, the applicability of the first query parameter refers to the applicability of one or more parameters included in the first query parameter. This first case includes several implementation methods, which will be described below.

[0318] In the first implementation, the first query parameter includes a first resource set list, and the applicability of the first query parameter is the applicability of the first resource set list.

[0319] Specifically, if one of the R first resource sets is not applicable, the list of first resource sets is not applicable, and the second information indicates that the list of first resource sets in the first query parameters is not applicable.

[0320] When each of the R first resource sets is applicable, the list of first resource sets applies, and the second information indicates that the list of first resource sets in the first query parameter applies.

[0321] In the second implementation, the first query parameter includes a list of first resource sets, and the applicability of the first query parameter is the applicability of R first resource sets in the list of first resource sets. The second information indicates the applicability of each first resource set in the R first resource sets.

[0322] In the third implementation, the first query parameter includes a first time slot offset list, and the applicability of the first query parameter is the applicability of the first time slot offset list.

[0323] Specifically, if one of the R first time slot offsets is not applicable, the first time slot offset list is not applicable, and the second information indicates that the first time slot offset list in the first query parameter is not applicable.

[0324] If each of the R first time slot offsets is applicable, the first time slot offset list is applicable, and the second information indicates that the first time slot offset list in the first query parameter is applicable. Alternatively, if one of the R first time slot offsets is applicable, the first time slot offset list is applicable, and the second information indicates that the first time slot offset list in the first query parameter is applicable.

[0325] The fourth implementation method includes a first query parameter that includes a first time slot offset list. The applicability of the first query parameter is the applicability of R first time slot offsets in the first time slot offset list. The second information indicates the applicability of each of the R first time slot offsets.

[0326] In the fifth implementation, the first query parameters include a first resource set list and a first time slot offset list. The applicability of the first query parameters is the applicability of the first resource set list and the first time slot offset list. The second information indicates the applicability of the first resource set list and the first time slot offset list in the first query parameters.

[0327] In the sixth implementation, the first query parameter includes a first resource set list and a first time slot offset list. The applicability of the first query parameter is the applicability of each first resource set in the first resource set list and the applicability of each first time slot offset in the first time slot offset list.

[0328] In the second scenario, the applicability of the first query parameter is either applicable or inapplicable. These will be discussed in detail below.

[0329] If the first query parameter is related to the first resource set list and the first resource set list is applicable, the second information indicates that the first query parameter is applicable;

[0330] If the first query parameter is related to the first resource set list, and the first resource set list is not applicable, the second information indicates that the first query parameter is not applicable;

[0331] If the first query parameter is related to the first time slot offset list and the first time slot offset list is applicable, the second information indicates that the first query parameter is applicable;

[0332] If the first query parameter is related to the first time slot offset list, and the first time slot offset list is not applicable, the second information indicates that the first query parameter is not applicable;

[0333] When the first query parameter is related to the first time slot offset list and the first resource set list, and both the first resource set list and the first time slot offset list are applicable, the second information indicates that the first query parameter is applicable.

[0334] If the first query parameter is related to the first time slot offset list and the first resource set list, and the first resource set list or the first time slot offset list is not applicable, the second information indicates that the first query parameter is not applicable.

[0335] Optionally, method 800 may also include S830, whereby the network side sends a measurement configuration and the terminal side receives the measurement configuration accordingly.

[0336] The measurement configuration can be referred to in Method 500, and will not be repeated here. Unlike Method 500, the measurement configuration can be determined based on the second information fed back by S820. In one implementation, the network side can prioritize configuring the configuration that is applicable based on the applicability feedback in the second information.

[0337] Optionally, prior to method S810, method 800 further includes the network side sending a terminal capability query message to the terminal side, and correspondingly, the terminal side receiving the terminal capability query message. The terminal capability query message is used to instruct the terminal side to report whether it supports AI or ML functions. The terminal side sends a terminal capability information message to the network side, and correspondingly, the network side receives the terminal capability information message. The terminal capability information message may indicate the functions supported by the terminal side.

[0338] The above describes method 800, which introduces how the network side sends a first query parameter to the terminal side. This first query parameter inquires about the applicability of AI-related resource sets in information elements of the report configuration or information elements of the configuration associated with the report configuration. The terminal side then feeds back the applicability of parameter sets of different fine granularities to the network side, enabling the network side to know the applicability of the parameter sets to the terminal side. This facilitates the network side in configuring measurement configurations for the terminal side. The complete CSI report process based on the applicability query method provided by method 800 is described below with reference to Figure 9.

[0339] Figure 9 is a schematic flowchart of another communication method provided in an embodiment of this application. The method 900 shown in Figure 9 relates to an interaction method between the network side and the terminal side, and includes the following steps.

[0340] Optionally, in S901, the network side sends a terminal capability inquiry (e.g., UECapabilityEnquiry) message to the terminal side, and correspondingly, the terminal side receives the terminal capability inquiry message. The terminal capability inquiry message is used to instruct the terminal side to report whether it supports AI or ML functions.

[0341] Optionally, in S902, the terminal sends a terminal capability information (e.g., UECapabilityInformation) message to the network side, and the network side receives the terminal capability information message accordingly. The terminal capability information message can indicate the functions supported by the terminal.

[0342] S910, the network side sends the first query parameter, and correspondingly, the terminal side receives the first query parameter.

[0343] S920, the terminal sends second information, and the network receives the second information accordingly. The second information is used to indicate the applicability of the first query parameters.

[0344] Optionally, in the S930, the network side sends the measurement configuration, and correspondingly, the terminal side receives the measurement configuration.

[0345] Alternatively, in S940, the terminal side sends first information, and the network side receives the first information accordingly. The first information indicates the suitability of the measurement configuration. For details, please refer to method 500.

[0346] Optionally, in S950, the network side sends DCI information to the terminal side, and the terminal side receives the DCI information accordingly. The DCI information may include a CSI request and / or a time domain resource assignment. This DCI information can be used to determine the triggering state. If the triggering state of the DCI trigger includes multiple CSI report configurations, the maximum time slot offset in the report configuration can be determined through the time domain resource assignment field in the DCI information. Furthermore, the time slot offset for the physical uplink shared channel (PUSCH) sent from the terminal side to the network side can be determined.

[0347] Optionally, method 900 also includes reporting a CSI report on the terminal side based on the trigger status and slot offset indicated by S950.

[0348] The methods described above, 500 and 700, illustrate how the network side sends a measurement configuration and queries the terminal side about its suitability for that configuration, thereby completing a CSI report. Methods 800 and 900 illustrate how the network side sends a first query parameter and queries the terminal side about its suitability for relevant parameters of the report configuration, thereby completing a CSI report.

[0349] Figure 10 is a schematic block diagram of a communication device provided in an embodiment of this application. The device 1000 shown in Figure 10 may include a processing module 1010 and a communication module 1020.

[0350] In one possible design, device 1000 can be used to implement the communication method implemented by the terminal side in any of the embodiments shown in Figures 5 to 9. For example, processing module 1010 is used to implement the model download or inference steps performed by the terminal side in each method embodiment; communication module 1020 is used to implement the sending and / or receiving steps performed by the terminal side in each method embodiment.

[0351] For example, the communication module 1020 can be used to: receive a measurement configuration, the measurement configuration being associated with a first trigger state list, the first trigger state list including multiple first trigger states, the first trigger state being associated with N first associated report configurations, the first associated report configuration indicating the association between the first report configuration and a first resource set, where N is a positive integer; or it can be used to send first information, the first information indicating the applicability of the first trigger state, or the first information indicating the applicability of the first trigger state list, the applicability of the first trigger state being associated with the N first associated report configurations.

[0352] A more detailed description of the processing module 1010 and the communication module 1020 can be obtained directly from the relevant descriptions in the method embodiments shown in Figures 5 to 9, and will not be repeated here.

[0353] In another possible design, device 1000 can be used to implement the communication method implemented by the network side in any of the embodiments shown in Figures 5 to 9. For example, processing module 1010 is used to implement the inference task executed by the network side in each method embodiment; communication module 1020 is used to implement the sending and / or receiving steps executed by the network side in each method embodiment.

[0354] For example, the communication module 1020 is used to send a measurement configuration, which is associated with a first trigger state list. The first trigger state list includes multiple first trigger states, and each first trigger state is associated with N first associated report configurations. The first associated report configurations indicate the association between the first report configurations and a first resource set, where N is a positive integer. Alternatively, it can be used to receive first information, which indicates the applicability of the first trigger state, or the first information indicates the applicability of the first trigger state list, and the applicability of the first trigger state is associated with the N first associated report configurations.

[0355] A more detailed description of the processing module 1010 and the communication module 1020 can be obtained directly from the relevant descriptions in the method embodiments shown in Figures 5 to 9, and will not be repeated here.

[0356] It should be noted that the communication module can also be called a transceiver module, transceiver unit, transceiver, transceiver device, or transceiver apparatus, etc. The processing module can also be called a processor, processing board, processing unit, or processing apparatus, etc. Optionally, the communication module is used to perform the sending and receiving operations of the terminal-side device or network-side device in the above method. The device in the communication module that implements the receiving function can be considered as the receiving module, and the device in the communication module that implements the sending function can be considered as the sending module; that is, the communication module can include both a receiving module and a sending module.

[0357] It should also be noted that, in one possible design, the aforementioned processing module and / or communication module can be implemented through virtual modules. For example, the processing module can be implemented through software functional units or virtual devices, and the communication module can be implemented through software functions or virtual devices. In another possible design, the processing module or communication module can also be implemented through physical devices. For example, if the device is implemented using a chip / chip circuit, the communication module can be an input / output circuit and / or a communication interface, performing input operations (corresponding to the aforementioned receiving operation) and output operations (corresponding to the aforementioned sending operation); the processing module can be an integrated processor, a microprocessor, or an integrated circuit.

[0358] The module division in this embodiment is illustrative and represents only one logical functional division; in actual implementation, other division methods may be used. Furthermore, the functional modules in the various examples of this embodiment can be integrated into a single processor, exist as separate physical entities, or be integrated into a single module. The integrated modules described above can be implemented in hardware or as software functional modules.

[0359] Figure 11 is a schematic diagram of another communication device provided in an embodiment of this application. As shown in Figure 11, the device 1100 includes a processing circuit 1110 and a communication circuit 1120. The processing circuit 1110 and the communication circuit 1120 are coupled to each other.

[0360] It can be understood that the processing circuit 1110 can be one or more processors, or it can be all or part of the processing functions of one or more processors.

[0361] Understandably, the communication circuit 1120 can be a transceiver or an input / output interface.

[0362] Optionally, the device 1100 may further include a memory 1130 for storing instructions executed by the processing circuit 1110, or storing input data required for the running instructions of the processing circuit 1110, or storing data generated after the running instructions of the processing circuit 1110.

[0363] It is understood that the memory 1130 may be located outside the processing circuit 1110 or inside the processing circuit 1110.

[0364] As an example, the processing circuit 1110 is used to implement the functions of the processing module 1110, and the communication circuit 1120 is used to implement the functions of the communication module 1120.

[0365] As an example, device 1100 can be a communication device or a chip used in a communication device.

[0366] When device 1100 is a communication device, the communication circuit can be a transceiver; when device 1100 is a chip, the communication circuit can be an input / output circuit, a bus, pins, or other types of communication interfaces, wherein the input circuit in the input / output circuit can be used for receiving, and the output interface can be used for transmitting.

[0367] It is understood that the processor in the embodiments of this application may be one or more of the following devices, or all or part of the circuitry of the following devices for processing functions: a central processing unit (CPU), a processor for AI, or other general-purpose processors, digital signal processors (DSPs), field-programmable gate arrays (FPGAs), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. A general-purpose processor may be a microprocessor or any conventional processor.

[0368] For example, the processor used for AI can be one or more of the following: graphics processing unit (GPU), neural processing unit (NPU), tensor processing unit (TPU), and data processing unit (DPU).

[0369] For example, one possible implementation of a processor for AI could be the AI ​​processor 1200 shown in Figure 12. Figure 12 is a schematic diagram of the structure of an AI processor provided in an embodiment of this application.

[0370] As shown in Figure 12, the AI ​​processor 1200 may include one or more of the following: an AI core, a digital vision pre-processing (DVPP) module, a task scheduler (TS), an L3 cache, an AI CPU, a control CPU, an L2 cache, a universal serial bus (USB) interface, a network interface card (NIC), a peripheral component interconnect express (PCIe) interface (PCIe is a high-speed serial computer expansion bus standard), a double data rate (DDR) / high bandwidth memory (HBM) interface, a general purpose input / output (GPIO) / inter-integrated circuit (I2C) bus, etc. It is understood that the specific meanings of these terms are well known to those skilled in the art and will not be elaborated upon here.

[0371] This application also provides a computer program product that, when run on a processor, can implement the communication method executed by the terminal side or the communication method executed by the network side in the above method embodiments.

[0372] This application also provides a computer-readable storage medium containing computer instructions that, when executed on a processor, can implement the communication method executed by the terminal side or the communication method executed by the network side in the above method embodiments.

[0373] This application also provides a communication system, including the aforementioned terminal side and network side. The terminal side can be used to implement the communication method implemented by the terminal side in the above method embodiments, and the network side can be used to implement the communication method implemented by the network side in the above method embodiments.

[0374] It is understood that the processor in the embodiments of this application may be any of the following devices or all or part of the circuitry used for processing functions: a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSPs), field-programmable gate arrays (FPGAs), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. A general-purpose processor may be a microprocessor or any conventional processor.

[0375] The terms “unit”, “module”, etc., used in this specification may be used to refer to computer-related entities, hardware, firmware, combinations of hardware and software, software, or software in execution.

[0376] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0377] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0378] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0379] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0380] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0381] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0382] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0383] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0384] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0385] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A communication method, characterized in that, include: Receive measurement configuration, the measurement configuration is associated with a first trigger state list, the first trigger state list includes multiple first trigger states, the first trigger state includes N first associated report configurations, the first associated report configuration indicates the association relationship between the first report configuration and the first resource set, where N is a positive integer; Send a first message indicating the applicability of the first trigger state, or the first message indicating the applicability of the first trigger state list, the applicability of the first trigger state being related to the N first associated report configurations.

2. A communication method characterized by comprising: include: Send a measurement configuration, which is associated with a first trigger state list. The first trigger state list includes multiple first trigger states, and each first trigger state includes N first associated report configurations. The first associated report configurations indicate the association between the first report configurations and the first resource set, where N is a positive integer. Receive first information, which indicates the applicability of the first trigger state, or the first information indicates the applicability of the first trigger state list, the applicability of the first trigger state being related to the N first associated report configurations.

3. The method according to claim 1 or 2, characterized in that, The applicability of the first triggering state includes: The first triggering state applies when all N first associated report configurations are applicable; or, If one of the N first associated report configurations is not applicable, the first trigger state is not applicable.

4. The method according to any one of claims 1 to 3, characterized in that, The first information, indicating the applicability of the first triggering state, further includes: The first information indicates the applicability of each of the N first associated report configurations included in the first trigger state.

5. The method according to claim 4, characterized in that, The applicability of the first associated report configuration includes: The first associated report configuration applies when both the first report configuration and the first resource set are applicable; or... The first associated report configuration is not applicable if either the first report configuration or the first resource set is not applicable.

6. The method according to claim 5, characterized in that, The first report configuration includes multiple first time slot offsets, and the first report configuration applies to, including: All configuration information in the first report configuration is applicable, the first report configuration is applicable, and the configuration information includes the plurality of first time slot offsets; or, At least one of the first time slot offsets in the first report configuration applies, and the first report configuration applies; or, The multiple first time slot offsets mentioned in the first report configuration are not applicable, and the first report configuration is not applicable.

7. The method according to claim 6, characterized in that, The first information also indicates the applicability of each of the plurality of first time slot offsets.

8. The method according to any one of claims 1 to 7, characterized in that, The applicability of the first trigger state list includes: The first trigger state list applies when all first trigger states included in the first trigger state list are applicable; or... If there is one first trigger state that is not applicable among all the first trigger states included in the first trigger state list, then the first trigger state list is not applicable.

9. The method according to any one of claims 1 to 8, characterized in that, The first information indicates the applicability of the first trigger state list, and also includes: The first information indicates the applicability of each of the first trigger states in the first trigger state list; or, The first information indicates the applicability of each of the first associated report configurations included in each of the first trigger states in the first trigger state list.

10. The method according to any one of claims 1 to 9, characterized in that, At least one of the following is related to artificial intelligence (AI): The first trigger state list, the first trigger state, the first associated report configuration, the resource set list associated with the first report configuration, the first resource set, or the first time slot offset, wherein the first report configuration includes the first time slot offset.

11. The method according to claim 10, characterized in that, The first trigger state is included in the first W first trigger states in the first trigger state list, and / or the first resource set is included in the first Z first resource sets in the resource set list associated with the first report configuration, where W and Z are both positive integers.

12. The method according to claim 10, characterized in that, The measurement configuration also includes first indication information, which indicates one or more of the following related to AI: the first trigger state list, the first trigger state, the first associated report configuration, the resource set list associated with the first report configuration, the first resource set, or the first time slot offset.

13. The method according to any one of claims 1 to 12, characterized in that, The first triggering state is the Channel State Information (CSI) aperiodic triggering state.

14. A communication method, characterized in that, include: Receive a first query parameter, which is related to at least one of the following: a first resource set list, R first resource sets in the first resource set list, a first time slot offset list, or a first time slot offset in the first time slot offset list, where R is a positive integer; Send a second message indicating the applicability of the first query parameters.

15. A communication method, characterized in that, include: Send a first query parameter, which is related to at least one of the following: a first resource set list, R first resource sets in the first resource set list, a first time slot offset list, or a first time slot offset in the first time slot offset list, where R is a positive integer; Receive a second message, which indicates the applicability of the first query parameters.

16. The method according to claim 14 or 15, characterized in that, The applicability of the first query parameter includes one or more of the following: The applicability of the first resource set list; The applicability of each of the R first resource sets; The applicability of the first time slot offset list; The applicability of each first time slot offset in the first time slot offset list.

17. The method according to claim 16, characterized in that, The applicability of the first resource set list includes: If one of the R first resource sets is not applicable, the list of first resource sets is not applicable; or, The list of first resource sets applies when each of the R first resource sets is applicable.

18. The method according to claim 16 or 17, characterized in that, The applicability of the first time slot offset list includes: If there is a case in the first time slot offset list where the first time slot offset is not applicable, then the first time slot offset list is not applicable; or... The first time slot offset list applies when each of the first time slot offsets in the first time slot offset list applies.

19. The method according to any one of claims 14 to 18, characterized in that, The applicability of the first query parameter includes one or more of the following: The first query parameter applies when it is related to the first resource set list and the first resource set list is applicable. If the first query parameter is related to the first resource set list, but the first resource set list is not applicable, then the first query parameter is not applicable. When the first query parameter is related to the first time slot offset list and the first time slot offset list is applicable, the first query parameter is applicable; If the first query parameter is related to the first time slot offset list, but the first time slot offset list is not applicable, then the first query parameter is not applicable. The first query parameter is applicable when it is related to the first time slot offset list and the first resource set list, and both the first resource set list and the first time slot offset list are applicable. If the first query parameter is related to the first time slot offset list and the first resource set list, and the first resource set list or the first time slot offset list is not applicable, then the first query parameter is not applicable.

20. The method according to any one of claims 14 to 19, characterized in that, The R first resource sets are located in the first R of the resource set list, or each of the R first resource sets is indicated as AI-related.

21. A communication device, characterized in that, Includes modules or units for performing the method according to any one of claims 1 to 20.

22. A communication device, characterized in that, Includes a processor configured to cause the communication device to perform the method of any one of claims 1 to 20.

23. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program or instructions that, when executed on a communication device, cause the communication device to perform the method as described in any one of claims 1 to 20.

24. A computer program product, characterized in that, The computer program product includes a computer program or instructions that, when executed on a communication device, cause the communication device to perform the method as described in any one of claims 1 to 20.

25. A system, characterized in that, It includes means for implementing the method of any one of claims 1, 3 to 13 and means for implementing the method of any one of claims 2 to 13, or means for implementing the method of any one of claims 14, 16 to 20 and means for implementing the method of any one of claims 15 to 20.

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