Communication method and apparatus

Abstract

Embodiments of the present application provide a communication method and apparatus. The method comprises: a first network element receives a first request from a second network element, wherein the first request is used for requesting the first network element to participate in a first federated learning task; the first network element acquires first information, wherein the first information is used for indicating that the second network element can provide to the first network element a global model corresponding to the first federated learning task; and the first network element sends a first response of the first request to the second network element on the basis of the first information, wherein the first response is used for indicating that the first network element determines to participate in the first federated learning task. In this way, whether the first network element (i.e., a client) has the permission to acquire the global model can be determined, and on the basis of whether the global model can be acquired, the first network element can decide whether to participate in the first federated learning task, thereby ensuring that the first network element can effectively participate in the federated learning task, and improving the user satisfaction of the client.

Description

Communication method and device

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application claims priority to the Chinese patent application filed with the State Intellectual Property Office of the People's Republic of China on January 11, 2024, with application number 202410048517.1 and application name "A Communication Method and Device", the entire contents of which are incorporated by reference into this application. Technical Field

[0003] The present application relates to the field of communications, and in particular to a communication method and device. Background Art

[0004] In the core network, a network data analytics function (NWDAF) network element (hereinafter referred to as NWDAF network element or NWDAF) can be a decentralized physical device that holds local data, and multiple NWDAFs can perform federated learning (FL).

[0005] Before starting each federated learning task, the server NWDAF can send a request to multiple client NWDAFs to participate in the federated learning task. After the server NWDAF receives a response from at least one client NWDAF agreeing to participate in the federated learning task, the server NWDAF can select at least one client NWDAF from the client NWDAFs that agree to participate in the federated learning task to form a federated learning group corresponding to the federated learning task. The federated learning group includes a server NWDAF and at least one client NWDAF. Furthermore, the server NWDAF and client NWDAF in the federated learning group can perform multiple rounds of iterative training based on the initial model (without exchanging local data) to obtain the global model corresponding to the federated learning task.

[0006] After multiple rounds of iterative training, the server NWDAF obtains the global model and sends it to one or more client NWDAFs. However, during the global model acquisition process, the client NWDAF remains passive. Therefore, after participating in a federated learning task, a client NWDAF may not be able to obtain the corresponding global model. When a client NWDAF participates in a federated learning task but cannot obtain the global model, the user experience is poor and commercial interests are damaged. Summary of the Invention

[0007] The embodiments of the present application provide a communication method and apparatus for clarifying the client's authority to obtain a global model, ensuring that the client effectively participates in federated learning tasks, and improving the client's user satisfaction.

[0008] In a first aspect, the present application provides a communication method, which is applied to a first network element, or a component (such as a processor, chip, chip system, circuit, or other, etc.) in the first network element, or a software module. Taking the application of the method to the first network element as an example, the method may include: the first network element receiving a first request from a second network element, the first request being used to request the first network element to participate in a first federated learning task; the first network element obtaining first information, the first information being used to indicate that the second network element can provide the first network element with a global model corresponding to the first federated learning task; and the first network element sending a first response to the first request to the second network element based on the first information, the first response being used to indicate that the first network element determines to participate in the first federated learning task.

[0009] By adopting this method, the first network element (i.e., the client) can clearly determine whether it has the authority to obtain the global model. The first network element can decide whether to participate in the first federated learning task based on whether it can obtain the global model, thereby ensuring that the first network element can effectively participate in the federated learning task and improve the user satisfaction of the client.

[0010] In one possible design, the first information includes at least one network element identifier, including the identifier of the first network element; or, the first information includes at least one analysis identifier, including the analysis identifier corresponding to the first federated learning task; or, the first information includes at least one interoperability identifier, including the interoperability identifier corresponding to the first network element. In this way, the first information can indicate the authority of devices of different granularities to obtain the global model, thereby improving the flexibility of the first information.

[0011] In one possible design, the process of obtaining the first information includes: the first network element sending a second request to the NRF network element, the second request being used to query whether the second network element can provide the first network element with the global model corresponding to the first federated learning task; and the first network element receiving the first information from the NRF network element. In this way, the first network element can obtain the first information through the NRF network element.

[0012] In one possible design, the first request may include the first information. In this way, the first network element can directly obtain the first information through the first request, saving signaling overhead.

[0013] In one possible design, the first network element may also receive model information from the second network element, where the model information is used to obtain a global model corresponding to the first federated learning task.

[0014] In this way, the second network element can actively send model information to the first network element, and correspondingly, the first network element can receive the model information, thereby improving the user satisfaction of the client corresponding to the first network element.

[0015] In one possible design, before the first network element receives the model information from the second network element, the first network element may also send a first address to the second network element, where the first address is used to receive the model information.

[0016] In this way, the second network element can send the model information to the first network element through the first address, and the first network element can receive the model information through the first address.

[0017] In one possible design, the first network element may also send a third request to the second network element, where the third request is used to request model information, and the model information is used to obtain the global model corresponding to the first federated learning task; the first network element receives a second response to the third request from the second network element, where the second response includes the model information, or the second response includes indication information for indicating that the model acquisition failed.

[0018] In this way, after receiving the third request from the first network element for obtaining model information, the second network element can send a second response corresponding to the third request to the first network element, and the second response includes model information, thereby improving the flexibility of the first network element in obtaining model information.

[0019] In one possible design, the third request includes identification information corresponding to the first federated learning task, and the second response is determined based on the identification information. Thus, the identification information corresponding to the first federated learning task is carried in the third request, and this identification information can be used as an index for the second network element to query the global model, so that the second network element can accurately send the model information of the global model of the first federated learning task to the first network element. Furthermore, the identification information corresponding to the first federated learning task is carried in the third request, and this identification information can be used as a verification value for the second network element to verify the first network element, thereby preventing network elements unrelated to the first federated learning task from obtaining the model information of the global model corresponding to the first federated learning task, thereby improving communication security.

[0020] In one possible design, the first request may include identification information; and / or the first network element may also receive identification information from the second network element. In this way, the first network element can obtain the aforementioned identification information through multiple channels, thereby improving flexibility.

[0021] In one possible design, the identification information includes at least one of the following: a model identification of an initial model corresponding to the first federated learning task; a model identification of a model in any round of iterative training corresponding to the first federated learning task; a model identification of a global model corresponding to the first federated learning task; or a task identification of the first federated learning task.

[0022] In this way, the identification information can be the model identification of the model or the task identification of the federated learning task, which improves flexibility.

[0023] In one possible design, the first network element may also send second information to the NRF network element, where the second information is used to indicate that the first network element needs to obtain a global model corresponding to the federated learning task in which the first network element participates.

[0024] In this way, the NRF network element can obtain the second information from the first network element, so that the second network element can obtain the second information through the NRF network element, and then the second network element can select the network element (such as the first network element) participating in the federated learning task, thereby improving the effectiveness of the client's participation in the federated learning task.

[0025] In a second aspect, the present application provides a communication method, which is applied to a second network element, or a component (such as a processor, chip, chip system, circuit, or other, etc.) in the second network element, or a software module. Taking the application of this method to the second network element as an example, the method includes: the second network element sends a first request to the first network element, the first request is used to request the first network element to participate in a first federated learning task; the second network element sends first information to the first network element, the first information is used to indicate that the second network element can provide the first network element with a global model corresponding to the first federated learning task; the second network element receives a first response from the first network element, the first response is response information to the first request, and the first response is used to indicate that the first network element determines to participate in the first federated learning task; the first response is determined based on the first information.

[0026] In one possible design, the first information includes at least one network element identifier, at least one network element identifier includes the identifier of the first network element; or, the first information includes at least one analysis identifier, at least one analysis identifier includes the analysis identifier corresponding to the first federated learning task; or, the first information includes at least one interoperability identifier, at least one interoperability identifier includes the interoperability identifier corresponding to the first network element.

[0027] In one possible design, the second network element may further send the first information to the NRF network element so that the first network element obtains the first information from the NRF network element. This may also be understood as the second network element sending the first information to the first network element via the NRF network element.

[0028] In one possible design, the first request includes the first information. In this way, the second network element can send the first information to the first network element through the first request.

[0029] In one possible design, the second network element may also send model information to the first network element, where the model information is used to obtain a global model corresponding to the first federated learning task.

[0030] In one possible design, before the second network element sends the model information to the first network element, the second network element may also receive a first address from the first network element, where the first address is used by the first network element to receive the model information.

[0031] In one possible design, the second network element can also receive a third request from the first network element, where the third request is used to request model information, and the model information is used to obtain the global model corresponding to the first federated learning task; the second network element sends a second response to the third request to the first network element; the second response includes the model information, or the second response includes indication information for indicating that the model acquisition failed.

[0032] In one possible design, the process of the second network element sending the second response to the third request to the first network element includes: when the third request includes identification information corresponding to the first federated learning task, the second network element sends the second response to the first network element. In this way, the second network element can determine whether the first network element has the authority to obtain the global model corresponding to the first federated learning task based on whether the third request includes the identification information corresponding to the first federated learning task, and thus determine whether to send the second response to the first network element, thereby improving the accuracy of communication; in other words, only when the second network element determines that the first network element has the authority to obtain the global model based on the third request, will the second network element send the second response to the first network element, thereby improving the accuracy of communication.

[0033] In one possible design, the first request includes identification information; and / or the second network element sends identification information to the first network element.

[0034] In one possible design, the identification information includes at least one of the following: a model identification of an initial model corresponding to the first federated learning task; a model identification of a model in any round of iterative training corresponding to the first federated learning task; a model identification of a global model corresponding to the first federated learning task; or a task identification of the first federated learning task.

[0035] In one possible design, before the second network element sends the first request to the first network element, the second network element may send a fourth request to the NRF network element, where the fourth request is used to query the first network element whether it needs to obtain the global model corresponding to the federated learning task in which the first network element participates; the second network element receives a third response to the fourth request from the NRF network element, where the third response is used to indicate that the first network element needs to obtain the global model corresponding to the federated learning task in which the first network element participates. In this way, the second network element can obtain the second information of the first network element through the NRF network element, and then the second network element can determine whether to select the first network element to participate in the federated learning task based on the second information, thereby improving the effectiveness of the client's participation in the federated learning task.

[0036] In a third aspect, the present application provides a communication method, which is applied to an NRF network element, or a component in the NRF network element (such as a processor, chip, chip system, circuit, or other, etc.), or a software module. Taking the application of this method to the NRF network element as an example, the method includes: the NRF network element receives a second request from a first network element, the second request is used to query whether the second network element can provide the first network element with a global model corresponding to a first federated learning task; the NRF network element sends first information to the first network element, the first information is used to indicate that the second network element can provide the first network element with a global model corresponding to the first federated learning task.

[0037] In one possible design, the NRF network element may also receive first information from the second network element.

[0038] In one possible design, the NRF network element can also receive a fourth request from the second network element, where the fourth request is used to query whether the first network element needs to obtain the global model corresponding to the federated learning task in which the first network element participates; the NRF network element sends a third response to the fourth request to the second network element, where the third response is used to indicate that the first network element needs to obtain the global model corresponding to the federated learning task in which the first network element participates.

[0039] In one possible design, the NRF network element may also receive second information from the first network element, where the second information is used to indicate that the first network element needs to obtain a global model corresponding to the federated learning task in which the first network element participates.

[0040] In a fourth aspect, the present application provides a communication method, which is applied to a first network element, or a component (such as a processor, chip, chip system, circuit, or other, etc.) in the first network element, or a software module. Taking the application of this method to the first network element as an example, the method may include: the first network element receiving a first request from a second network element, the first request being used to request the first network element to participate in a first federated learning task; the first network element sending a first response to the first request to the second network element, the first response being used to indicate that the first network element determines to participate in the first federated learning task or refuses to participate in the first federated learning task, and the first response is further used to indicate that the first network element needs to obtain a global model corresponding to the federated learning task in which the first network element participates.

[0041] Optionally, the first response may include one or more of the following: first indication information or a model acquisition address. The first indication information is used to indicate that the first network element needs to obtain the global model corresponding to the first federated learning task; the model acquisition address is used to indicate an address at which the first network element receives model information.

[0042] Using this method, the first network element (i.e., the client) can send a response to the second network element to indicate that the first network element needs to obtain the global model corresponding to the federated learning task in which the first network element participates, so that the second network element can clarify whether the first network element needs to obtain the global model.

[0043] In a fifth aspect, the present application further provides a communication device. The communication device can execute the methods described in the first, second, third, or fourth aspects, or the solutions in each possible design. The communication device can be a chip or circuit capable of executing the functions corresponding to the above methods, or a device including the chip or circuit.

[0044] In one possible design, the communication device includes a communication unit for receiving and / or sending data; the communication device also includes a processing unit for implementing the method in any one of the possible designs described in the first, second, third, or fourth aspects. The aforementioned functions can be implemented by hardware or by hardware executing corresponding software. The hardware or software includes one or more units corresponding to the aforementioned functions.

[0045] In a sixth aspect, the present application further provides a communication device. The communication device can execute the method described in the first, second, third, or fourth aspects above, or the solutions in each possible design. The communication device includes: a processor. When the processor executes instructions, the communication device or a device equipped with the communication device executes the method described in any possible design described in the first, second, third, or fourth aspects above.

[0046] Optionally, the communication device may further include a memory for storing computer-executable program code, and the program agent may include the aforementioned instructions. The memory may be located inside or outside the communication device, which is not limited in this application. The memory may be coupled to the processor.

[0047] The communication device may further include a communication interface. Optionally, if the communication device is a chip or a circuit, the communication interface may be an input / output interface of the chip, such as an input / output pin.

[0048] In the seventh aspect, the present application provides a communication system, which includes at least one of the following: a first network element that executes the method of the first aspect or a first network element that executes the method of the fourth aspect, a second network element that executes the method of the second aspect, and an NRF network element that executes the method of the third aspect.

[0049] In an eighth aspect, the present application provides a computer-readable storage medium, which stores a computer program. When the computer program runs on a computer, the computer executes a method in any possible design shown in the first, second, third or fourth aspects above.

[0050] In the ninth aspect, the present application provides a computer program product, in which a computer-readable storage medium stores computer-executable instructions. When the computer-executable instructions are called by a computer, the computer executes a method in any possible design shown in the first, second, third or fourth aspects above.

[0051] In a tenth aspect, the present application provides a chip, comprising a processor for executing the method in any one of the possible designs shown in the first, second, third, or fourth aspects above. Optionally, the chip may further include a communication interface for inputting and / or outputting signaling or data. Optionally, the chip may further include a memory for storing the aforementioned computer program; the processor is coupled to the memory, and the processor can read the computer program stored in the memory to execute the method in any one of the possible designs shown in the first, second, third, or fourth aspects above.

[0052] In addition, the technical effects brought about by the second to tenth aspects can be found in the description of each possible solution in the first aspect above, and will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] FIG1 is a schematic diagram of the architecture of a communication system provided in an embodiment of the present application;

[0054] FIG2 is a flow chart of a communication method provided in an embodiment of the present application;

[0055] FIG3 is a flow chart of another communication method provided in an embodiment of the present application;

[0056] FIG4 is an example diagram of a communication method provided in an embodiment of the present application;

[0057] FIG5 is an example diagram of another communication method provided in an embodiment of the present application;

[0058] FIG6 is an example diagram of another communication method provided in an embodiment of the present application;

[0059] FIG7 is a schematic structural diagram of a communication device provided in an embodiment of the present application;

[0060] FIG8 is a schematic structural diagram of another communication device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0061] In order to make the purpose, technical solutions and beneficial effects of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0062] In the description of this application, unless otherwise specified, “ / ” means or, for example, A / B can mean A or B; “and / or” in this application is merely a description of the association relationship of associated objects, indicating that three relationships can exist, for example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. In addition, in the description of this application, “at least one” means one or more items, and “multiple items” means two or more items. In the description of this application, words such as “first” and “second” are only used for the purpose of distinguishing the description, and cannot be understood as indicating or implying relative importance, nor can they be understood as indicating or implying order.

[0063] The embodiments of the present application can be applied to various communication systems, such as: global system for mobile communications (GSM) system, code division multiple access (CDMA) system, wideband code division multiple access (WCDMA) system, general packet radio service (GPRS), long term evolution (LTE) system, LTE frequency division duplex (FDD) system, LTE time division duplex (TDD), universal mobile telecommunication system (UMTS), world-wide interoperability for microwave access (WIMAX) communication system, fifth generation (5G) system or new radio (NR), or applied to future communication systems or other similar communication systems.

[0064] Figure 1 is a schematic diagram of the architecture of a communication system. The architecture of the communication system shown in Figure 1 may include terminal devices, access network devices, and core network devices. The terminal devices access the data network (DN) through the access network devices and the core network devices. Among them, the core network devices include multiple network functions (NFs) or network elements. The core network devices may also be referred to as core network network elements. For example, the core network devices may include some or all of the following network elements (or core network elements): unified data management (UDM) network element, unified data repository (UDR) network element, application function (AF) network element, policy control function (PCF) network element, access and mobility management function (AMF) network element, session management function (SMF) network element, user plane function (UPF) network element, network data analytics function (NWDAF) network element, network repository function (NRF) network element (not shown in the figure), etc.

[0065] It should be understood that the present application does not limit the number of network elements included in the communication system. For example, the communication system in Figure 1 may include multiple NWDAF network elements.

[0066] Terminal devices can be user equipment (UE), mobile stations, mobile terminals, etc. Terminal devices can be widely used in various scenarios, such as device-to-device (D2D), vehicle-to-everything (V2X) communication, machine-type communication (MTC), the Internet of Things (IoT), virtual reality, augmented reality, industrial control, autonomous driving, telemedicine, smart grids, smart furniture, smart offices, smart wearables, smart transportation, and smart cities. Terminal devices can be mobile phones, tablets, computers with wireless transceiver capabilities, wearable devices, vehicles, urban air vehicles (such as drones and helicopters), ships, robots, robotic arms, smart home devices, etc.

[0067] The access network device may be a radio access network (RAN) device. For example: a base station, an evolved NodeB (eNodeB), a transmission reception point (TRP), a next generation NodeB (gNB) in a 5G mobile communication system, a next generation base station in a sixth generation (6G) mobile communication system, a base station in a future mobile communication system, or an access node in a wireless fidelity (WiFi) system, etc.; it may also be a module or unit that performs part of the functions of a base station, for example, a centralized unit (CU) or a distributed unit (DU). The radio access network device may be a macro base station, a micro base station or an indoor station, a relay node or a donor node, etc. The embodiments of the present application do not limit the specific technology and specific device form adopted by the radio access network device.

[0068] Access network equipment and terminal devices can be fixed or mobile. They can be deployed on land, including indoors or outdoors, handheld or vehicle-mounted; on water; or in the air on aircraft, balloons, and satellites. The embodiments of this application do not limit the application scenarios of access network equipment and terminal devices.

[0069] The following is a brief introduction to some core network equipment:

[0070] The AMF network element, referred to as AMF, performs functions such as mobility management and access authentication / authorization. In addition, the AMF is responsible for communicating user policies between terminal devices and the PCF.

[0071] The SMF network element, referred to as SMF, includes functions such as session management, execution of control policies issued by PCF, selection of UPF, and allocation of Internet Protocol (IP) addresses for terminal devices.

[0072] The UPF network element, referred to as UPF, serves as the interface with the data network and includes functions such as user plane data forwarding, session / flow-level billing statistics, and bandwidth limitation.

[0073] UDM network element, referred to as UDM, includes functions such as executing and managing contract data and user access authorization.

[0074] The UDR network element, referred to as UDR, includes the access functions of executing contract data, policy data, application data and other types of data.

[0075] NEF network element, referred to as NEF, is used to support the opening of capabilities and events.

[0076] The AF network element, abbreviated as AF, conveys the application side's requirements to the network side, such as quality of service (QoS) requirements or user status event subscriptions. The AF can be a third-party functional entity or an application server deployed by the operator.

[0077] The PCF network element, referred to as PCF, includes policy control functions such as session and service flow level billing, QoS bandwidth guarantee and mobility management, and terminal device policy decision-making.

[0078] NRF network elements, or NRF for short, can be used to provide network element discovery capabilities. Based on requests from other network elements, they provide network element information corresponding to the network element type. NRF network elements also provide network element management services, such as network element registration, update, and deregistration, as well as network element status subscription and push notification.

[0079] NWDAF network element, referred to as NWDAF, is mainly used to collect data (including one or more of terminal device data, access network device data, core network network element data and third-party application device data), wherein these data can be the terminal device, access network device, core network network element or third-party application device data itself, or the terminal device on the access network device, the core network network element or the third-party application device. Then, data analysis is performed based on the collected data, and the data analysis results are output for use by the network, network management equipment and application execution policy decision-making. NWDAF can use machine learning models for data analysis. In an embodiment of the present application, an NWDAF can be a separate network element, or it can be set up together with other network elements, for example, NWDAF is set up in a PCF network element or an AMF network element.

[0080] In Release 17 of the 3rd Generation Partnership Project (3GPP), the training and inference functions of NWDAF are split. An NWDAF can support only the model training function, only the data inference function, or both the model training and data inference functions.

[0081] The following examples introduce two NWDAFs that support different functions.

[0082] In this application, the model training function network element may be an NWDAF supporting the model training function, which may also be referred to as a training NWDAF, or an NWDAF supporting a model training logical function (MTLF), referred to as MTLF. For example, the MTLF may perform model training based on the acquired data to obtain a trained model.

[0083] The NWDAF may be an NWDAF supporting a data reasoning function, which may also be called a reasoning NWDAF, or an NWDAF supporting an analytics logical function (AnLF), which may be referred to as AnLF.

[0084] For example, AnLF can request a model from MTLF through a model subscription (MLModelProvision_Subscribe) service or message. The model can be obtained by MTLF based on model-related data training. Furthermore, AnLF can input input data into the trained model to obtain analysis results or inference data. It can be understood that MTLF can be understood as a NWDAF that at least supports model training functions. As a possible implementation method, MTLF can also support data reasoning functions. AnLF can be understood as a NWDAF that at least supports data reasoning functions. As a possible implementation method, AnLF can also support model training functions.

[0085] In the embodiments of the present application, AnLF and MTLF are used as examples for illustration, but they do not constitute a limitation on NAWDF.

[0086] It can be understood that the above network elements are examples of one implementation method, and this application does not exclude the existence of network elements or devices with the above network element functions in 6G or newer wireless communication systems that have other names or other forms.

[0087] It is understood that the above-mentioned network element or function can be a network element in a hardware device, a software function running on dedicated hardware, or a virtualized function instantiated on a platform (e.g., a cloud platform). As a possible implementation method, the above-mentioned network element or function can be implemented by a single device, or can be implemented by multiple devices together, or can be a functional module within a single device, which is not specifically limited in the embodiments of the present application.

[0088] In Figure 1, Nudr, Npcf, Namf, Nudm, Nsmf, Naf, and Nnwdaf are service-oriented interfaces provided by the UDR, PCF, AMF, UDM, SMF, AF, and NWDAF, respectively, and are used to invoke corresponding service-oriented operations. N1, N2, N3, N4, and N6 are interface serial numbers, and their meanings are as follows:

[0089] 1) N1: The interface between the AMF network element and the terminal device, which can be used to transmit non-access stratum (NAS) signaling (such as QoS rules from the AMF network element) to the terminal device.

[0090] 2) N2: The interface between the AMF network element and the access network equipment, which can be used to transmit radio bearer control information from the core network side to the access network equipment.

[0091] 3) N3: The interface between the access network equipment and the UPF network element, mainly used to transmit uplink and downlink user plane data between the access network equipment and the UPF network element.

[0092] 4) N4: The interface between the SMF network element and the UPF network element, which can be used to transmit information between the control plane and the user plane, including controlling the issuance of forwarding rules, QoS rules, traffic statistics rules, etc. for the user plane and reporting information on the user plane.

[0093] 5) N6: Interface between UPF network element and DN, used to transmit uplink and downlink user data flows between UP network element F and DN.

[0094] The following is an explanation of the basic technical concepts involved in this application:

[0095] 1. Analysis ID: used to identify the analysis service (or analysis service, referred to as service). In the embodiment of the present application, the aforementioned service is related to the data model, that is, the data model can be used to execute the service. In other words, the analysis ID is related to the data model, that is, the data model is used to execute the service corresponding to the analysis ID. The data model can also be called a machine learning model or a training model, that is, a model generated by training using data.

[0096] The following example illustrates the analysis identifier. MTLF is associated with the analysis identifier, that is, the model support provided by MTLF is used to execute the service corresponding to the analysis identifier. Exemplarily, MTLF can be associated with one or more analysis identifiers. It can be understood that the MTLF can provide a model of the service corresponding to each of the one or more analysis identifiers. For example, MTLF1 is associated with analysis identifier 1 and analysis identifier 2, that is, MTLF1 corresponds to analysis identifier 1 and analysis identifier 2, then MTLF1 can provide a model of the service corresponding to analysis identifier 1, and a model of the service corresponding to analysis identifier 2.

[0097] 2. Vendor ID: This field identifies a device manufacturer. A vendor ID can correspond to one or more network elements (NFs), such as NWDAFs, including MTLFs. For example, if MTLF1 and MTLF2 correspond to vendor ID 1, they belong to the same vendor, whose vendor ID is vendor ID 1.

[0098] For NF, the manufacturer ID corresponds to the manufacturer of the network element. It can also be understood as network element information (NF information), which identifies the vendor information of the network element.

[0099] 3. Interoperability indicator: This identifies a list of NWDAF (e.g., MTLF or AnLF) providers (or suppliers, manufacturers) that can access models from each other. The interoperability indicator can also be called an interoperability indicator, a machine learning (ML) model interoperability indicator, or a model interoperability indicator.

[0100] For example, the interoperability identifier includes one or more vendor identifiers (e.g., a vendor list or a vendor identifier list), or the interoperability identifier is associated with the one or more vendor identifiers. Assuming that the MTLF has an interoperability identifier, and the interoperability identifier corresponds to a first vendor identifier list, the vendors in the first vendor identifier list are allowed to obtain models from the MTLF; or, the vendors in the first vendor identifier list are allowed to retrieve or use models provided by the MTLF; or, the vendors in the first vendor identifier list are able to obtain models from the MTLF; or, the vendors in the first vendor identifier list are able to retrieve or use models provided by the MTLF; or, the interoperability identifier also indicates that the MTLF supports the vendor requesting the model provided by the MTLF for the NWDAF of the vendors in the first vendor identifier list. For another example, the interoperability identifier can also correspond to the MTLF, or to the analysis identifier, or to the analysis identifier of the MLTF; in other words, the interoperability identifier is related to the MTLF, or the interoperability identifier is related to the analysis identifier.

[0101] Optionally, a MTLF may have one or more interoperability identifiers. If a MTLF has multiple interoperability identifiers, the multiple interoperability identifiers correspond to different analysis identifiers respectively. For example, assuming that the NWDAF network element (taking MTLF NF ID 1 as an example) corresponds to analysis identifier 1 and analysis identifier 2, the MTLF to which MTLF NF ID 1 belongs has interoperability identifier 1 and interoperability identifier 2, interoperability identifier 1 corresponds to analysis identifier 1, and interoperability identifier 2 corresponds to analysis identifier 2; for further example, if the MTLF to which MTLF NF ID 1 belongs and the MTLF to which MTLF NF ID 2 belongs both belong to the list of manufacturers supporting interoperability, the MTLF to which MTLF NF ID 2 belongs can have interoperability identifier 1 and interoperability identifier 2, wherein interoperability identifier 1 corresponds to analysis identifier 1, and / or, interoperability identifier 2 corresponds to analysis identifier 2, that is, MTLFs of the same manufacturer can have the same interoperability identifier for the same analysis identifier. In addition, if the MTLF to which MTLF NF ID 1 belongs and the MTLF to which MTLF NF ID 2 belongs do not belong to the same list of vendors supporting interoperability, the MTLF to which MTLF NF ID 2 belongs may have an interoperability identifier 3 and an interoperability identifier 4, wherein the interoperability identifier 3 corresponds to the analysis identifier 1, and / or the interoperability identifier 4 corresponds to the analysis identifier 2, that is, the MTLFs of the same vendor may have different interoperability identifiers for the same analysis identifier.

[0102] Exemplarily, analysis identifier 1 is associated with model 1, i.e., model 1 is used to execute the service corresponding to analysis identifier 1, and analysis identifier 1 is associated with interoperability identifier 1, i.e., model 1 is associated with interoperability identifier 1. Assume that interoperability identifier 1 includes the identifier of manufacturer 1 and the identifier of manufacturer 2, i.e., model 1 can be provided to manufacturer 1 and manufacturer 2 for use. Alternatively, it can be understood that if the manufacturer of the NWDAF is manufacturer 1 or manufacturer 2, then the NWDAF can use model 1.

[0103] In order to clarify the client's authority to obtain the global model, ensure that the client effectively participates in the federated learning task, and improve the user satisfaction of the client, an embodiment of the present application provides a communication method. The communication method can be implemented in the communication system shown in Figure 1 above. The communication method involves a first network element, a second network element, and an NRF network element; the first network element and the second network element can be the NWDAF network element shown in Figure 1 above, or other network elements, which is not limited in this application. For example, the first network element can be a client network element, and the second network element can be a server network element.

[0104] The following describes the communication method provided by the embodiment of the present application in conjunction with the accompanying drawings. FIG2 shows a communication method provided by the embodiment of the present application, which may include the following steps:

[0105] S201: A second network element sends a first request to a first network element; in response, the first network element receives the first request from the second network element. The first request is used to request the first network element to participate in a first federated learning task.

[0106] Optionally, the first request may include identification information corresponding to the first federated learning task.

[0107] Optionally, the first federated learning task can be replaced by other names such as the first federated learning, the first federated learning function, the first federated learning process, or the first federated learning activity.

[0108] Optionally, participation can be replaced by joining. In the embodiment of the present application, requesting participation in the first federated learning task can be understood as: requesting an entity (or network element or device or node, etc.) (such as the first network element) that has the ability to participate in the first federated learning task to participate in the first federated learning task. In other words, in the embodiment of the present application, requesting the first network element to participate in the first federated learning task can be understood as: requesting the first network element to determine that the first network element has the ability to participate in the first federated learning task. In other words, in the embodiment of the present application, requesting the first network element to participate in the first federated learning task can be understood as: requesting the first network element to agree to participate in (or join) the first federated learning task.

[0109] S202: The first network element obtains first information.

[0110] Optionally, the first information is used to indicate that the second network element is capable of providing the first network element with a global model corresponding to the first federated learning task. It should be understood that "the second network element is capable of providing the first network element with a global model corresponding to the first federated learning task" includes but is not limited to indicating any of the following situations: the second network element is capable of proactively sending the global model corresponding to the first federated learning task to the first network element; the second network element is capable of sending the global model corresponding to the first federated learning task to the first network element after receiving a request to obtain the global model; the second network element is capable of authorizing the first network element to obtain the global model corresponding to the first federated learning task; or the first network element has the authority to obtain the global model corresponding to the first federated learning task.

[0111] In the embodiment of the present application, the global model corresponding to the federated learning task refers to the model generated after the client network element and the server network element jointly execute the federated learning task.

[0112] In some examples, the first information may also indicate the authority of devices of different granularities (eg, multiple network elements including the first network element) to obtain the global model.

[0113] The first information may include at least one network element identifier, including the identifier of the first network element; or the first information may include at least one analysis identifier, including the analysis identifier corresponding to the first federated learning task; or the first information may include at least one interoperability identifier, including the interoperability identifier corresponding to the first network element. It should be understood that the first information includes but is not limited to identifiers of the aforementioned several granularities.

[0114] In this way, the first information can indicate the authority of devices of different granularities to obtain the global model, which can improve the flexibility of the first information. For example, when the first information includes at least one network element identifier, the first information is indication information at the network element granularity, that is, the first information indicates that the second network element can provide the global model corresponding to the first federated learning task to the network element corresponding to the at least one network element identifier. For another example, when the first information includes at least one analysis identifier, the first information is indication information at the analysis identifier granularity, that is, the first information indicates that the second network element can provide the global model corresponding to the first federated learning task to the network element corresponding to the at least one analysis identifier. For another example, when the first information includes at least one interoperability identifier, the first information is indication information at the interoperability identifier granularity, and the interoperability identifier includes at least one vendor identifier, then the first information indicates that the second network element can provide the global model corresponding to the first federated learning task to the network element belonging to the vendor corresponding to the vendor identifier.

[0115] In one possible design, as shown in FIG3 , the implementation manner in which the first network element obtains the first information includes but is not limited to manner A1 and manner A2:

[0116] Method A1 (including S202-a1):

[0117] S202 - a1 : The second network element sends first information to the first network element. Correspondingly, the first network element receives the first information from the second network element.

[0118] Optionally, after receiving the first information from the second network element, the first network element may further send a confirmation message of the first information to the second network element.

[0119] Optionally, the first information may be included in the first request in S201. It should be understood that S201 and S202-a1 may be the same step; that is, when approach A1 is adopted, S201 and S202 may be combined into one step. Based on this, when the first request includes the first information, the first network element may parse the first request to obtain the first information after executing S201.

[0120] Optionally, the first information may also be carried in other messages sent by the second network element to the first network element.

[0121] Method A2 (including at least one of the following steps: S202-b1, S202-b2, S202-b3): the second network element may send the first information to the first network element through the NRF network element.

[0122] S202-b2: The first network element sends a second request to the NRF network element; accordingly, the NRF network element receives the second request from the first network element; the second request is used to query whether the second network element can provide the first network element with a global model corresponding to the first federated learning task. In some examples, the second request in S202-b2 may be a network element discovery request of the network element discovery process of the first network element, and the network element discovery request is used to request to obtain a network element configuration file (NF profile) (including one or more configuration policies) of at least one network element (including the second network element), and one or more configuration policies in the NF profile may include the aforementioned "query whether the second network element can provide the first network element with a global model corresponding to the first federated learning task". The "network element discovery process" in the embodiments of the present application can refer to the traditional technical solutions in the field and will not be repeated here.

[0123] S202-b3: The NRF network element sends first information to the first network element; accordingly, the first network element receives the first information from the NRF network element. In some examples, the first information in S202-b3 may be included in a network element discovery response of the network element discovery process, or the first information in S202-b3 may be the network element discovery response of the network element discovery process; wherein the network element discovery response is used to send the NF profile of the second network element.

[0124] In this way, by using the aforementioned S202-b2 and S202-b3, the first network element can obtain the first information through the NRF network element. For example, the first network element can obtain the first information through the network element discovery process.

[0125] Optionally, before executing S202-b2, the second network element may further execute S202-b1.

[0126] S202-b1: The second network element sends the first information to the NRF network element, so that the first network element obtains the first information from the NRF network element. Correspondingly, the NRF network element receives the first information from the second network element. The NRF network element can also store the first information. In some examples, S202-b1 can be implemented in the network element registration process of the second network element. In other words, the first information can be carried in the network element registration request of the second network element. The "network element registration process" in the embodiment of the present application can refer to the traditional technical solutions in the field and will not be repeated here.

[0127] In this way, the NRF network element can obtain the first information from the second network element, so as to provide it to the first network element subsequently.

[0128] S203: The first network element sends a first response to the first request to the second network element based on the first information; accordingly, the second network element receives the first response from the first network element. The first response is used to indicate that the first network element has confirmed to participate in the first federated learning task.

[0129] Using the methods shown in S201 to S203 above, the first network element (i.e., the client) can determine whether it has permission to obtain the global model, or whether it will obtain the global model. The first network element can decide whether to participate in the first federated learning task based on whether the global model can be obtained, thereby ensuring that the first network element can effectively participate in the federated learning task and improving user satisfaction of the client.

[0130] In one possible example, after the first network element receives a first request from the second network element, when the first network element needs to obtain the global model corresponding to the first federated learning task and the first network element has not obtained the first information, the first network element sends a response to the second network element indicating a refusal to participate in the first federated learning task.

[0131] In one possible example, when the first network element does not need to obtain the global model corresponding to the first federated learning task, regardless of whether the first network element obtains the first information, the first network element may send a first response to the second network element to instruct the first network element to determine to participate in the first federated learning task. In other words, after executing S201, the first network element may send the first response to the second network element to instruct the first network element to determine to participate in the first federated learning task without executing S202.

[0132] In another possible example, when the first network element needs to obtain the global model corresponding to the first federated learning task, the first network element may not obtain the first information, that is, not execute S202. In this example scenario, the first network element may not send the first response to the first request to the second network element based on the first information. In other words, after executing S201, the first network element may send the first response to the first request to the second network element. In the aforementioned example scenario, the first response may also be used to indicate that the first network element needs to obtain the global model corresponding to the federated learning task in which the first network element participates. In this way, the first network element (i.e., the client) may send the first response to the second network element indicating that the first network element needs to obtain the global model corresponding to the federated learning task in which the first network element participates, so that the second network element can determine whether the first network element needs to obtain the global model. Furthermore, the first network element (i.e., the client) may obtain the global model corresponding to the first federated learning task (e.g., by executing steps S205-c1 to S205-c2, or by executing steps S205-d1 to S205-d2).

[0133] Optionally, the first response includes one or more of the following: first indication information or a model acquisition address. The first indication information is used to indicate that the first network element needs to obtain model information corresponding to the first federated learning task. Alternatively, the first indication information is used to indicate that the first network element requests to obtain model information corresponding to the first federated learning task. The model acquisition address is used to indicate an address from which the first network element obtains the model information corresponding to the first federated learning task.

[0134] In some examples, the first network element and the second network element may agree in advance on the following information through standard preconfiguration or negotiation: the first network element agrees to participate in the first federated learning task, which means that the first network element needs to obtain the global model corresponding to the first federated learning task.

[0135] In the scenario of the aforementioned example, the first response may also be used to indicate that the first network element needs to obtain the global model corresponding to the federated learning task in which the first network element participates.

[0136] In the absence of logical conflicts, the above examples can be cross-referenced and combined into new embodiments, and this application does not limit them.

[0137] In one possible design, as shown in FIG3 , after executing S203 or any of the foregoing examples (not shown in the figure), the first network element and the second network element may further execute S204: the first network element and the second network element execute a first federated learning task (the first federated learning task includes one or more rounds of training). Optionally, the second network element may further send a task identifier of the first federated learning task and / or a model identifier of a global model corresponding to the first federated learning task to the first network element.

[0138] Illustratively, during the first round of training, the second network element may send an initial model to the first network element; the second network element may also send a model identifier of the initial model to the first network element.

[0139] Furthermore, during any subsequent round of training, the second network element may send the process model to the first network element; the second network element may also send a model identifier of the process model to the first network element.

[0140] In one possible design, as shown in FIG3 , the first network element and the second network element may further perform steps S205-c1 to S205-c2, or the first network element and the second network element may further perform steps S205-d1 to S205-d2. That is, after the first network element and the second network element complete the first federated learning task (e.g., perform one or more rounds of training), the first network element may obtain model information; the two methods for the first network element to obtain model information include method B1 and method B2. The model information may be a global model, or the model information may be parameter information of the global model, or the model information may be information required to obtain the global model.

[0141] Method B1 (including at least one of the following steps: S205-c1, S205-c2):

[0142] S205-c2: The second network element may send model information to the first network element; correspondingly, the first network element receives the model information from the second network element, and the model information is used to obtain a global model corresponding to the first federated learning task.

[0143] In some embodiments, the second network element may send model information to all network elements participating in the first federated learning task; or, the second network element may send model information to all network elements participating in the last round of training in the first federated learning task.

[0144] In this way, the first network element can obtain the model information using the method B1, that is, the second network element can actively send the model information to the first network element.

[0145] Optionally, before the second network element sends the model information to the first network element, the first network element may further execute S205 - c1 .

[0146] S205-c1: The first network element may also send a first address to the second network element; accordingly, the second network element receives the first address from the first network element. The first address is used to receive model information. In some examples, the first address in S205-c1 may be included in the confirmation message sent by the first network element to the second network element in the aforementioned method A1.

[0147] In this way, the second network element can send the model information to the first network element through the first address. For example, the second network element can store the model information in the storage space corresponding to the first address, and the second network element can obtain the model information through the storage space corresponding to the first location.

[0148] Method B2 (including S205-d1 and S205-d2):

[0149] S205-d1: The first network element may send a third request to the second network element; correspondingly, the second network element receives the third request from the first network element. The third request is used to request to obtain model information.

[0150] S205-d2: The second network element may send a second response to the third request to the first network element; accordingly, the first network element receives the second response to the third request from the second network element, wherein the second response includes model information, or the second response includes indication information indicating a model acquisition failure.

[0151] In this way, the first network element can use method B2 to obtain model information, that is, the first network element can send a third request for obtaining model information to the second network element, so that the second network element sends a second response corresponding to the third request to the first network element, and the second response includes model information, thereby improving the flexibility of the first network element in obtaining model information.

[0152] In some examples, when executing S204, the first network element may exit the first federated learning task midway due to internal reasons, that is, the first network element does not fully participate in the process of executing the first federated learning task in S204. At this time, the second network element may not actively send model information to the first network element. The first network element can obtain the model information by sending a third request to the second network element. Assuming that the first federated learning task is in an unfinished state when the second network element receives the third request, the second network element can send a second response to the first network element. The second response includes indication information of the model acquisition failure. The second response may also include the time when the error occurred, the waiting time (that is, the time interval between receiving the first request and sending the second response) and the cause of the error (for example, "the first federated learning task is in an unfinished state at the current moment" or "the global model is not generated at the current moment").

[0153] Optionally, the third request may include identification information corresponding to the first federated learning task. In this case, the second response may be determined based on the aforementioned identification information.

[0154] In some examples, when the third request includes identification information corresponding to the first federated learning task, the second network element sends a second response to the first network element. Conversely, when the third request received by the second network element does not include identification information corresponding to the first federated learning task, the second network element may not send the aforementioned second response to the first network element, or the second response may include indication information indicating a model acquisition failure.

[0155] The identification information may include at least one of the following: the model identification of the initial model corresponding to the first federated learning task; the model identification of the model in any round of iterative training corresponding to the first federated learning task; the model identification of the global model corresponding to the first federated learning task; or the task identification of the first federated learning task.

[0156] It should be understood that the second network element may perform multiple federated learning tasks and may therefore store global models corresponding to multiple federated learning tasks. In the aforementioned method B2, the third request carries identification information corresponding to the first federated learning task. This identification information can be used as an index for the second network element to query the global model, so that the second network element can accurately send model information of the global model of the first federated learning task to the first network element, thereby improving communication accuracy. In addition, the third request carries identification information corresponding to the first federated learning task. This identification information can be used as a verification value for the second network element to verify the first network element, thereby preventing network elements unrelated to the first federated learning task from obtaining model information of the global model corresponding to the first federated learning task, thereby improving communication security.

[0157] Optionally, the first network element may obtain the identification information in a manner including but not limited to manner C1 and manner C2:

[0158] Mode C1: When the first request includes identification information, the first network element may parse the first request to obtain the identification information after executing S201.

[0159] Method C2: The second network element sends identification information to the first network element; accordingly, the first network element may also receive identification information from the second network element. For example, during the process of the first network element and the second network element performing the first federated learning task, the first network element and the second network element perform the actions in the aforementioned method C2.

[0160] In one possible design, as shown in FIG3 , the first network element may further perform the following steps (including S200 - e1):

[0161] S200-e1: The first network element may further send second information to the NRF network element; accordingly, the NRF network element receives the second information from the first network element. The second information is used to indicate that the first network element needs to obtain the global model corresponding to some or all federated learning tasks in which the first network element participates. The NRF network element may further store the second information.

[0162] In some embodiments, the second information may also indicate that the first network element needs permission for the global model corresponding to the federated learning task initiated by devices of different granularities (e.g., multiple network elements including the second network element). For example, the second information may be used to indicate that the first network element needs to obtain the global model corresponding to the federated learning task initiated by the network element corresponding to a certain (or multiple) network element identifier; for another example, the second information may be used to indicate that the first network element needs to obtain the global model corresponding to a certain (or multiple) analysis identifier; for another example, the second information may be used to indicate that the first network element needs to obtain the global model corresponding to the federated learning task initiated by the network element belonging to a certain (or multiple) interoperability identifier.

[0163] In this way, the second information can indicate the authority of the global model corresponding to the federated learning tasks initiated by devices of different granularities, which can improve the flexibility of the second information.

[0164] It should be noted that the execution order of the aforementioned S200-e1 can be performed before the aforementioned S201. In some examples, S200-e1 can be implemented during the network element registration process of the first network element. In other words, the second information can be included in the network element registration request of the first network element. Alternatively, the aforementioned S200-e1 can be performed at any step from S201 to S205-d2, or after S205-d2. In this way, the NRF network element can obtain the second information from the first network element.

[0165] Optionally, before executing S201, the second network element may further obtain the second information through the following steps (S200-e2 and S200-e3).

[0166] S200-e2: The second network element may also send a fourth request to the NRF network element; accordingly, the NRF network element receives the fourth request from the second network element. The fourth request is used to query the first network element whether it needs to obtain the global model corresponding to the federated learning task in which the first network element participates. In some examples, the fourth request in S200-e2 may be a network element discovery request of the network element discovery process of the second network element, which may be used to request the NF profile (including one or more configuration policies) of at least one network element (including the first network element), and the one or more configuration policies may include the aforementioned "query whether the first network element needs to obtain the global model corresponding to the federated learning task in which the first network element participates".

[0167] S200-e3: The NRF network element sends a third response to the fourth request to the second network element; accordingly, the second network element can also receive a third response to the fourth request from the NRF network element, and the third response is used to indicate that the first network element needs to obtain the global model corresponding to the federated learning task in which the first network element participates. For example, the third response may include the second information, or the second network element may determine the second information based on the third response. In some examples, the third response in S200-e3 may be carried in the network element discovery response of the network element discovery process, or the third response in S200-e3 is the network element discovery response of the network element discovery process; wherein, the network element discovery response is used to send the NF profile of the first network element.

[0168] In this way, by using the aforementioned S200-e2 and S200-e3, the second network element can obtain the second information through the NRF network element. By using the same method, the second network element can obtain the second information corresponding to multiple client network elements through the NRF network element.

[0169] In some examples, the second network element may select some client network elements from the aforementioned multiple client network elements based on the obtained permission requirements of the multiple client network elements (whether it is necessary to obtain the permission requirements of the global model corresponding to the federated learning task in which the network element participates), and send a request to participate in the federated learning task to these client network elements to improve the effectiveness of the client network elements' participation in the federated learning task. The second network element may select the client network elements in a manner that: when the second network element is able to provide the client network element with the global model corresponding to the federated learning task, the second network element may select some client network elements that have the permission requirements to obtain the global model; when the second network element is unable to provide the client network element with the global model corresponding to the federated learning task, the second network element may select some client network elements that do not have the permission requirements to obtain the global model.

[0170] Based on the communication method shown in S201 to S205-d2 above, as shown in Figures 4, 5, and 6, this application provides the following three possible examples of communication methods. In the example of the communication method, the network elements performing the federated learning task include: a server network element, client network element 1 and client network element 2, and an NRF network element.

[0171] Example 1

[0172] Through S401-a1 to S401-a3, the network element registration process of the server network element is executed. This process can refer to the above-mentioned S202-b1 to S202-b3.

[0173] S401-a1: The server network element sends a network element registration request of the server network element to the NRF network element; the network element registration request includes the configuration policy of the server network element. The configuration policy can be used to indicate the network element authorized to obtain the global model, that is, the configuration policy can be used to indicate that at least one client network element has the authority to obtain the global model. The configuration policy of the server network element can refer to the aforementioned description of the first information. In some examples, the network element registration request initiated by the server network element may include the NF profile of the server network element, and the NF profile may include the aforementioned configuration policy.

[0174] Assuming that the server network element is able to provide a global model corresponding to a federated learning task to at least one client network element, the configuration policy may include an identifier corresponding to the at least one client network element. For example, the configuration policy includes an identifier of at least one client network element, an analysis identifier corresponding to at least one federated learning task, or an interoperability identifier corresponding to at least one client network element.

[0175] S401-a2: The NRF network element stores the configuration policy of the server network element.

[0176] S401 - a3 : The NRF network element sends a network element registration response of the server network element to the server network element.

[0177] Through S402-b1 to S402-b3, the network element registration process of the client network element 1 is executed. This process can refer to the aforementioned S200-e1 to S200-e3.

[0178] S402-b1: Client network element 1 sends a network element registration request of client network element 1 to the NRF network element; the network element registration request includes the configuration policy of the client network element. The configuration policy is used to indicate that the client network element 1 needs to obtain the global model corresponding to the federated learning task in which the client network element 1 participates. The configuration policy of the client network element 1 can refer to the aforementioned description of the second information. In some examples, the network element registration request initiated by the client network element 1 can include the NF profile of the client network element 1, and each NF profile can include the aforementioned configuration policy.

[0179] S402-b2: The NRF network element stores the configuration policy of the client network element 1.

[0180] S402 - b3 : The NRF network element sends a network element registration response of the client network element 1 to the client network element 1 .

[0181] Optionally, the network element registration process (not shown in the figure) of the client network element 2 (or other client network elements) can be executed through actions similar to S402-b1 to S402-b3.

[0182] S403: The server network element may select at least one client network (eg, including client network element 1) according to the configuration policy of the plurality of client network elements, so that the at least one client network element participates in the federated learning task A.

[0183] For example, assuming that the configuration policy of the server network element indicates that the client network elements with the authority to obtain the global model corresponding to the federated learning task include client network element 1 (or client network element 2), the client network elements selected by the server network element may include client network element 1 (or client network element 2).

[0184] For another example, suppose that the configuration policy of the server network element indicates that the client network elements with the authority to obtain the global model corresponding to the federated learning task do not include client network element 1 and client network element 2, the configuration policy of client network element 1 indicates that client network element 1 needs to obtain the global model corresponding to the federated learning task in which client network element 1 participates, and the configuration policy of client network element 2 indicates that client network element 2 does not need to obtain the global model corresponding to the federated learning task in which client network element 2 participates (or the configuration policy of client network element 2 does not indicate that client network element 2 needs to obtain the global model corresponding to the federated learning task in which client network element 2 participates), then the client network elements selected by the server network element include client network element 1 and do not include client network element 2.

[0185] Optionally, before executing S403, the server network element may further obtain the configuration policies of the aforementioned multiple client network elements through a network element discovery process (not shown in the figure). The method for the server network element to obtain the configuration policies of the multiple client network elements through the network element discovery process can be referred to above S200-e2 and S200-e3, and will not be repeated here. Alternatively, before executing S403, the server network element may further pre-store the configuration policies of the multiple client network elements.

[0186] Through S404 - c1 to S404 - c3 , it is determined whether the client network element 1 participates in the federated learning task A. This process may refer to the aforementioned S201 and S203 .

[0187] S404 - c1 : The server network element sends a request to client network element 1 to participate in federated learning task A.

[0188] S404-c2: Client network element 1 determines a response (agreement or refusal) to participate in federated learning task A based on the configuration policy of the server network element. It should be understood that S404-c2 can refer to the process of determining the first response in S203 above. The configuration policy may include the first information in the aforementioned communication method, or the configuration policy may be the first information in the aforementioned communication method.

[0189] For example, assuming that the configuration policy of client network element 1 indicates that client network element 1 does not need to obtain the global model corresponding to the federated learning task in which client network element 1 participates (or the configuration policy of client network element 1 does not indicate that client network element 1 needs to obtain the global model corresponding to the federated learning task in which client network element 1 participates), then client network element 1 determines a response to indicate consent to participate in federated learning task A.

[0190] For another example, assuming that the configuration policy of client network element 1 indicates that client network element 1 needs to obtain the global model corresponding to the federated learning task in which client network element 1 participates, and the configuration policy of the server indicates that client network element 1 has the authority to obtain the global model, then client network element 1 determines a response indicating agreement to participate in federated learning task A; conversely, assuming that the configuration policy of client network element 1 indicates that client network element 1 needs to obtain the global model corresponding to the federated learning task in which client network element 1 participates, and the configuration policy of the server indicates that client network element 1 does not have the authority to obtain the global model, then client network element 1 determines a response indicating refusal to participate in federated learning task A.

[0191] Before executing S404-c2, client network element 1 may also obtain the configuration policy of the aforementioned server network element through a network element discovery process (not shown in the figure). The method by which client network element 1 may obtain the configuration policy of the aforementioned server network element through the network element discovery process can be referred to S202-b2 and S202-b3 in the aforementioned method A2. Alternatively, before executing S404-c2, the client network element may also pre-store the configuration policy of the aforementioned server network element.

[0192] S404-c3: Client network element 1 sends a response to participate in federated learning task A to the server network element.

[0193] Optionally, through actions similar to S404-c1 to S404-c3, the server network element can determine whether other client network elements in at least one client network element selected in S403 participate in federated learning task A (not shown in the figure), thereby determining at least one client network element participating in federated learning task A.

[0194] Through S405 - d1 and S405 - d2 , the model training is iteratively performed, that is, the federated learning task A is performed. This process can refer to the aforementioned S204 .

[0195] S405-d1: The server network element sends a model training message to the client network element 1. In the first iteration, the model training message includes the initial model and the model identifier corresponding to the initial model; in subsequent iterations, the model training message includes the process model and the model identifier of the process model.

[0196] S405-d2: The client network element 1 sends a training feedback message to the server network element.

[0197] It should be understood that the process model in S405 - d1 is generated based on the training feedback information of at least one client network element in the previous round of training.

[0198] Optionally, through actions similar to S405-d1 and S405-d2, the server network element and at least one client network element can iteratively perform multiple rounds of model training to determine the global model corresponding to the federated learning task A.

[0199] During the aforementioned iterative model training process, some client network elements (such as client network element 1) can participate in the federated learning task A throughout the entire process, while some client network elements (such as client network element 2) may exit the federated learning task A midway due to internal reasons.

[0200] S406: The server network element saves model information of the global model obtained after multiple rounds of iterative training.

[0201] Through S407-e1 (or S407-f1 and S407-f2), the client network element 1 obtains the model information. This process can refer to the aforementioned S205-c1 to S205-c2, or refer to the aforementioned S205-d1 to S205-d2.

[0202] S407-e1: The server network element sends the model information to the client network element 1. This process can refer to the above-mentioned method B1.

[0203] Optionally, the server network element may also send model information to other client network elements participating in the federated learning task A (not shown in the figure).

[0204] S407-f1: Client network element 1 sends a global model request to the server network element. The global model request may include the model identifier of the initial model and / or the model identifier of the process model in S405-d1. This process may refer to S205-d1 in the aforementioned method B2.

[0205] S407-f2: The server network element sends the model information to the client network element 1. This process can refer to S205-d2 in the above-mentioned method B2.

[0206] For example, assuming that the server network element determines that the aforementioned global model request does not include the model identifier of the initial model and does not include the model identifier of the process model, the server network element does not execute S407-f2, or the server network element sends an indication message to the client network element 1 to indicate that the global model acquisition failed.

[0207] Optionally, other client network elements (eg, client network element 2) may obtain the aforementioned model information (not shown in the figure) through actions similar to S407-f1 and S407-f2.

[0208] Example 2

[0209] Through S501-a1 to S501-a3, the network element registration process of the server network element is executed. This process can refer to the above-mentioned S401-a1 to S401-a3.

[0210] Through S502-b1 to S502-b3, the network element registration process for client network element 1 is executed. This process can refer to the aforementioned S402-b1 to S402-b3. Optionally, the server network element and client network element 2 (or other client network elements) can also execute the network element registration process for client network element 2 (or other client network elements) through actions similar to S502-b1 to S502-b3 (not shown in the figure).

[0211] S503: The server network element may select at least one client network (eg, including client network element 1) according to the configuration policies of the plurality of client network elements. This process may refer to the aforementioned S403.

[0212] Through S504-c1 to S504-c3, it is determined whether client network element 1 participates in federated learning task A. This process can refer to the aforementioned S404-c1 to S404-c3. Optionally, through actions similar to S504-c1 to S504-c3, the server network element can determine whether other client network elements among the at least one client network element selected in S503 participate in federated learning task A (not shown in the figure), thereby determining at least one client network element participating in federated learning task A.

[0213] Through S505-d1 and S505-d2, model training is iteratively performed, i.e., federated learning task A is executed. This process can refer to the aforementioned S405-d1 and S405-d2. Optionally, the server network element and at least one client network element can iteratively perform multiple rounds of model training through actions similar to S505-d1 and S505-d2, thereby determining the global model corresponding to federated learning task A.

[0214] S505-d1 includes: the server network element sending a model training message to client network element 1; S505-d1 differs from S405-d1 in Example 1 in that, in each iteration, the model training message may include the model identifier of the global model corresponding to federated learning task A. Optionally, in the first iteration, the model training message may further include an initial model and a model identifier corresponding to the initial model; in subsequent iterations, the model training message may further include a process model and a model identifier of the process model.

[0215] S506: The server network element saves the model information of the global model obtained after multiple rounds of iterative training. This process can refer to the aforementioned S406.

[0216] Client network element 1 obtains the model information through S507-e1 (or S507-f1 and S507-f2). This process can refer to the aforementioned S407-e1 (or S407-f1 and S407-f2). Optionally, other client network elements (e.g., client network element 2) can obtain the aforementioned model information through actions similar to S507-e1 (or S507-f1 and S507-f2) (not shown in the figure).

[0217] S507-f2 includes: the server network element sending the model information to the client network element 1. For example, S507-f2 differs from S407-f2 in Example 1 in that, assuming that the server network element determines that the global model request does not include the model identifier of the global model, the server network element does not execute S507-f2, or the server network element sends indication information to the client network element 1 indicating that the global model acquisition failed.

[0218] Example 3

[0219] Through S601-a1 to S601-a3, the network element registration process of the server network element is executed. This process can refer to the above-mentioned S401-a1 to S401-a3.

[0220] Through S602-b1 to S602-b3, the network element registration process for client network element 1 is executed. This process can refer to the aforementioned S402-b1 to S402-b3. Optionally, the server network element and client network element 2 (or other client network elements) can also execute the network element registration process for client network element 2 (or other client network elements) through actions similar to S602-b1 to S602-b3 (not shown in the figure).

[0221] S603: The server network element may select at least one client network (eg, including client network element 1) according to the configuration policies of the plurality of client network elements. This process may refer to the aforementioned S403.

[0222] Through S604-c1 to S604-c3, it is determined whether client network element 1 participates in federated learning task A. This process can refer to the aforementioned S404-c1 to S404-c3. Optionally, through actions similar to S604-c1 to S604-c3, the server network element can also determine whether other client network elements among the at least one client network element selected in S603 participate in federated learning task A (not shown in the figure), thereby determining at least one client network element participating in federated learning task A.

[0223] Among them, S604-c3 includes: client network element 1 sends a response to the server network element to participate in federated learning A. S604-c3 is different from S404-c3 in Example 1 and S504-c3 in Example 2 in that the response to participate in federated learning A can include a global model receiving address.

[0224] Through S605-d1 and S605-d2, model training is iteratively performed, that is, federated learning task A is executed. This process can refer to S405-d1 and S405-d2 in the aforementioned example 1, or refer to S505-d1 and S505-d2 in the aforementioned example 2. Optionally, the server network element and at least one client network element can iteratively perform multiple rounds of model training through actions similar to S605-d1 and S605-d2, thereby determining the global model corresponding to federated learning task A.

[0225] S605-d2 includes: client network element 1 sends a training feedback message to the server network element. S605-d2 is different from S405-d2 in Example 1 and S505-d2 in Example 2 in that the training feedback message may include a global model receiving address.

[0226] S606: The server network element saves the model information of the global model obtained after multiple rounds of iterative training. This process can refer to the aforementioned S406.

[0227] In step S607-e1, the client network element 1 obtains the model information. This process can refer to the aforementioned step S407-e1. Optionally, the server network element can also send the model information to other client network elements participating in the federated learning task A (not shown in the figure).

[0228] Among them, S607-e1 includes: the server network element sends model information to the client network element 1. S607-e1 differs from S407-e1 in Example 1 and S507-e1 in Example 2 in that when the "response to participating in federated learning A" in S604-c3 or the "training feedback message" in S605-d2 carries a global model receiving address, the server network element can send the model information to the global model receiving address, thereby achieving the purpose of the server network element sending the model information to the client network element 1.

[0229] In the various embodiments of the present application, unless otherwise specified or there is a logical conflict, the terms and / or descriptions between different embodiments are consistent and can be referenced by each other. The technical features in different embodiments can be combined to form new embodiments according to their inherent logical relationships.

[0230] The method provided in the embodiment of the present application is introduced above in conjunction with the accompanying drawings. The communication device provided in the embodiment of the present application is introduced below in conjunction with the accompanying drawings.

[0231] Based on the same technical concept, this application also provides a communication device for implementing the communication methods provided in the above embodiments. Referring to FIG. 7 , the communication device 700 includes a communication unit 701 and a processing unit 702 . The communication unit 701 is configured to receive and / or transmit data; the processing unit 702 is configured to implement the steps of the communication method shown in FIG. 2 or FIG. 3 .

[0232] In one possible example, when the communication device 700 is used to implement the functions of the first network element shown in FIG. 2 or FIG. 3 , the communication unit 701 is configured to: receive a first request from a second network element, the first request being used to request the communication device 700 to participate in a first federated learning task; the communication unit 701 is further configured to: obtain first information, the first information being used to indicate that the second network element can provide the communication device 700 with a global model corresponding to the first federated learning task; and the processing unit 702 is configured to perform the following steps through the communication unit 701: based on the first information, control the communication unit 701 to send a first response to the first request to the second network element, the first response being used to indicate that the communication device 700 determines to participate in the first federated learning task. The processing unit 702 can be configured to control the sending and receiving operations of the communication unit 701.

[0233] In one possible design, the first information includes at least one network element identifier, at least one network element identifier includes the identifier of the communication device 700; or, the first information includes at least one analysis identifier, at least one analysis identifier includes the analysis identifier corresponding to the first federated learning task; or, the first information includes at least one interoperability identifier, at least one interoperability identifier includes the interoperability identifier corresponding to the communication device 700.

[0234] In one possible design, the communication unit 701 can also be used to: send a second request to the NRF network element, the second request being used to query whether the second network element can provide the communication device 700 with a global model corresponding to the first federated learning task; and receive first information from the NRF network element.

[0235] In one possible design, the first request includes first information.

[0236] In one possible design, the communication unit 701 is further used to: receive model information from the second network element, where the model information is used to obtain a global model corresponding to the first federated learning task.

[0237] In one possible design, the communication unit 701 is further used to: before receiving the model information from the second network element, send a first address to the second network element, where the first address is used to receive the model information.

[0238] In one possible design, the communication unit 701 is also used to: send a third request to the second network element, the third request is used to request to obtain model information, and the model information is used to obtain the global model corresponding to the first federated learning task; the communication unit 701 is also used to: receive a second response to the third request from the second network element, the second response includes model information, or the second response includes indication information for indicating that the model acquisition failed.

[0239] In one possible design, the third request includes identification information corresponding to the first federated learning task, and the second response is determined based on the identification information.

[0240] In one possible design, the first request includes identification information; and / or, the communication unit 701 is further used to: receive identification information from the second network element.

[0241] In one possible design, the identification information includes at least one of the following: a model identification of an initial model corresponding to the first federated learning task; a model identification of a model in any round of iterative training corresponding to the first federated learning task; a model identification of a global model corresponding to the first federated learning task; or a task identification of the first federated learning task.

[0242] In one possible design, the communication unit 701 is further used to: send second information to the NRF network element, where the second information is used to indicate that the communication device 700 needs to obtain a global model corresponding to the federated learning task in which the communication device 700 participates.

[0243] In one possible example, when the communication device 700 is used to implement the function of the second network element shown in Figure 2 or Figure 3 above, the communication unit 701 is used to: send a first request to the first network element, the first request is used to request the first network element to participate in the first federated learning task; the communication unit 701 is also used to: send first information to the first network element, the first information is used to indicate that the communication device 700 can provide the first network element with a global model corresponding to the first federated learning task; the communication unit 701 is also used to: receive a first response from the first network element, the first response is response information to the first request, the first response is used to indicate that the first network element has determined to participate in the first federated learning task; the first response is determined based on the first information. The processing unit 702 can be used to control the sending and receiving operations of the communication unit 701.

[0244] In one possible design, the first information includes at least one network element identifier, at least one network element identifier includes the identifier of the first network element; or, the first information includes at least one analysis identifier, at least one analysis identifier includes the analysis identifier corresponding to the first federated learning task; or, the first information includes at least one interoperability identifier, at least one interoperability identifier includes the interoperability identifier corresponding to the first network element.

[0245] In one possible design, the communication unit 701 is further used to: send the first information to the NRF network element, so that the first network element obtains the first information from the NRF network element.

[0246] In one possible design, the first request includes first information.

[0247] In one possible design, the communication unit 701 is further used to: send model information to the first network element, where the model information is used to obtain a global model corresponding to the first federated learning task.

[0248] In one possible design, the communication unit 701 is further used to: before sending the model information to the first network element, receive a first address from the first network element, where the first address is used by the first network element to receive the model information.

[0249] In one possible design, the communication unit 701 is also used to: receive a third request from the first network element, the third request is used to request to obtain model information, and the model information is used to obtain the global model corresponding to the first federated learning task; the communication unit 701 is also used to: send a second response to the third request to the first network element; the second response includes the model information, or the second response includes indication information for indicating that the model acquisition failed.

[0250] In one possible design, the communication unit 701 can also be used to: when the third request includes identification information corresponding to the first federated learning task, send a second response to the first network element.

[0251] In one possible design, the first request includes identification information; and / or, the communication unit 701 is further used to: send identification information to the first network element.

[0252] In one possible design, the identification information includes at least one of the following: a model identification of an initial model corresponding to the first federated learning task; a model identification of a model in any round of iterative training corresponding to the first federated learning task; a model identification of a global model corresponding to the first federated learning task; or a task identification of the first federated learning task.

[0253] In one possible design, the communication unit 701 is also used to: send a fourth request to the NRF network element before sending the first request to the first network element, the fourth request being used to query whether the first network element needs to obtain the global model corresponding to the federated learning task in which the first network element participates; and receive a third response to the fourth request from the NRF network element, the third response being used to indicate that the first network element needs to obtain the global model corresponding to the federated learning task in which the first network element participates.

[0254] In one possible example, when the communication device 700 is used to implement the functions of the NRF network element shown in Figure 2 or Figure 3 above, the communication unit 701 is used to: receive a second request from a first network element, the second request being used to query whether the second network element can provide the first network element with a global model corresponding to the first federated learning task; the communication unit 701 is further used to: send first information to the first network element, the first information being used to indicate that the second network element can provide the first network element with a global model corresponding to the first federated learning task. The processing unit 702 can be used to control the sending and receiving operations of the communication unit 701.

[0255] In one possible design, the communication unit 701 is further used to: receive first information from the second network element.

[0256] In one possible design, the communication unit 701 is also used to: receive a fourth request from the second network element, the fourth request being used to query whether the first network element needs to obtain the global model corresponding to the federated learning task in which the first network element participates; the communication unit 701 is also used to: send a third response to the fourth request to the second network element, the third response being used to indicate that the first network element needs to obtain the global model corresponding to the federated learning task in which the first network element participates.

[0257] In one possible design, the communication unit 701 is further used to: receive second information from the first network element, where the second information is used to indicate that the first network element needs to obtain a global model corresponding to the federated learning task in which the first network element participates.

[0258] Based on the same technical concept, the embodiment of the present application also provides another communication device 800, which can implement the communication method provided in the above embodiment. Referring to Figure 8, the communication device 800 includes a processor 801. Optionally, the communication device 800 also includes a memory 802 and / or a communication interface 803. The memory can be placed inside the communication device or outside the communication device, which is not limited in this application. Among them, the communication interface 803, the processor 801 and the memory 802 are interconnected. Exemplarily, the communication device 800 can be the first network element, the second network element or the NRF network element shown in the embodiment of the present application.

[0259] Optionally, the communication interface 803, the processor 801, and the memory 802 are interconnected via a bus 804. The bus 804 may be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus. The bus may be classified as an address bus, a data bus, a control bus, etc. For ease of illustration, FIG8 shows only one thick line, but this does not mean that there is only one bus or only one type of bus.

[0260] The communication interface 803 is used to receive and / or send signals to achieve communication with other devices other than the communication device.

[0261] The processor 801 can be used to execute any of the communication methods described in Figures 2 to 6 above. The communication methods can be described in the above embodiments and will not be described in detail here. The processor 801 can be a central processing unit (CPU), a network processor (NP), or a combination of a CPU and an NP. The processor 801 can further include a hardware chip. The hardware chip can be an application-specific integrated circuit (ASIC), a programmable logic device (PLD), or a combination thereof. The PLD can be a complex programmable logic device (CPLD), a field-programmable gate array (FPGA), a generic array logic (GAL), or any combination thereof. When implementing the above functions, the processor 801 can be implemented through hardware, or it can also execute corresponding software implementations through hardware.

[0262] The memory 802 is used to store program instructions, etc. Specifically, the program instructions may include program code, which includes computer operating instructions. The memory 802 may include random access memory (RAM) or non-volatile memory (non-volatile memory), such as at least one disk storage device. The processor 801 executes the program instructions stored in the memory 802 to implement the above functions, thereby implementing the methods provided in the above embodiments.

[0263] Based on the same technical concept, an embodiment of the present application further provides a computer program, which, when executed on a computer, enables the computer to execute the method provided in the above embodiment.

[0264] Based on the same technical concept, an embodiment of the present application further provides a computer-readable storage medium, which stores a computer program. When the computer program runs on a computer, the computer executes the method provided in the above embodiment.

[0265] The storage medium may be any available medium that can be accessed by a computer. By way of example and not limitation, computer-readable media may include RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage media or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and can be accessed by a computer.

[0266] Based on the same technical concept, an embodiment of the present application further provides a chip, which is used to read a computer program stored in a memory to implement the method provided in the above embodiment.

[0267] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0268] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the present application. It should be understood that each flow and / or box in the flow chart and / or block diagram, as well as the combination of the flow chart and / or box in the flow chart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device produce a device for implementing the functions specified in one or more flow charts and / or one or more boxes in the block diagram.

[0269] These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce a product including an instruction device that implements the functions specified in one or more processes in the flowchart and / or one or more boxes in the block diagram.

[0270] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, so that the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one or more processes in the flowchart and / or one or more boxes in the block diagram.

[0271] Obviously, those skilled in the art may make various changes and modifications to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is intended to include these modifications and variations.

Claims

1. A communication method, applied to a first network element, characterized in that The method includes: Receiving a first request from a second network element, where the first request is used to request the first network element to participate in a first federated learning task; Obtaining first information, where the first information is used to indicate that the second network element can provide the global model corresponding to the first federated learning task to the first network element; According to the first information, sending a first response to the first request to the second network element, where the first response is used to indicate that the first network element determines to participate in the first federated learning task.

2. The method according to claim 1, wherein: The first information includes at least one network element identifier, and the at least one network element identifier includes the identifier of the first network element; or The first information includes at least one analysis identifier, and the at least one analysis identifier includes the analysis identifier corresponding to the first federated learning task; or The first information includes at least one interoperability identifier, and the at least one interoperability identifier includes the interoperability identifier corresponding to the first network element.

3. The method according to claim 1 or 2, characterized in that The obtaining the first information includes: Sending a second request to a Network Repository Function (NRF) network element, where the second request is used to query whether the second network element can provide the global model corresponding to the first federated learning task to the first network element; Receiving the first information from the NRF network element.

4. The method according to claim 1 or 2, wherein: The first request includes the first information.

5. The method according to any one of claims 1-4, characterized in that, The method further includes: Receiving model information from the second network element, where the model information is used to obtain the global model corresponding to the first federated learning task.

6. The method according to claim 5, wherein Before receiving the model information from the second network element, it further includes: Sending a first address to the second network element, where the first address is used to receive the model information.

7. The method according to any one of claims 1-4, characterized in that, The method further includes: Sending a third request to the second network element, where the third request is used to request to obtain model information, and the model information is used to obtain the global model corresponding to the first federated learning task; Receiving a second response to the third request from the second network element, where the second response includes the model information, or the second response includes indication information for indicating that model acquisition fails.

8. The method according to claim 7, wherein: The third request includes identification information corresponding to the first federated learning task, and the second response is determined according to the identification information.

9. The method according to claim 8, wherein: The first request includes the identification information; and / or The method further includes: receiving the identification information from the second network element.

10. The method according to claim 8 or 9, characterized in that The identification information includes at least one of the following: The model identifier of the initial model corresponding to the first federated learning task; The model identifier of the model in any round of iterative training process corresponding to the first federated learning task; The model identifier of the global model corresponding to the first federated learning task; or The task identifier of the first federated learning task.

11. The method according to any one of claims 1-10, characterized in that, The method further includes: Sending second information to the NRF network element, where the second information is used to indicate that the first network element needs to obtain the global model corresponding to the federated learning task participated by the first network element.

12. A communication method, applied to a second network element, characterized in that, The method includes: Sending a first request to a first network element, where the first request is used to request the first network element to participate in a first federated learning task; Sending first information to the first network element, where the first information is used to indicate that a second network element can provide a global model corresponding to the first federated learning task to the first network element; Receiving a first response from the first network element, where the first response is a response message of the first request, and the first response is used to indicate that the first network element determines to participate in the first federated learning task; the first response is determined according to the first information.

13. The method according to claim 12, wherein The first information includes at least one network element identifier, and the at least one network element identifier includes an identifier of the first network element; or The first information includes at least one analysis identifier, and the at least one analysis identifier includes an analysis identifier corresponding to the first federated learning task; or The first information includes at least one interoperability identifier, and the at least one interoperability identifier includes an interoperability identifier corresponding to the first network element.

14. The method according to claim 12 or 13, characterized in that, The method further includes: Sending the first information to a Network Repository Function (NRF) network element.

15. The method according to claim 12 or 13, wherein The first request includes the first information.

16. The method according to any one of claims 12 - 15, characterized in that, The method further includes: Sending model information to the first network element, where the model information is used to obtain a global model corresponding to the first federated learning task.

17. The method according to claim 16, wherein Before sending the model information to the first network element, it further includes: Receiving a first address from the first network element, where the first address is used for the first network element to receive the model information.

18. The method according to any one of claims 12-15, characterized in that, The method further includes: Receiving a third request from the first network element, where the third request is used to request to obtain model information, and the model information is used to obtain a global model corresponding to the first federated learning task; Sending a second response to the third request of the first network element; the second response includes the model information, or the second response includes indication information for indicating that model acquisition fails.

19. The method according to claim 18, wherein Sending the second response to the third request of the first network element includes: When the third request includes identification information corresponding to the first federated learning task, sending the second response to the first network element.

20. The method according to claim 19, wherein The first request includes the identification information; and / or The method further includes: sending the identification information to the first network element.

21. The method according to claim 19 or 20, characterized in that, The identification information includes at least one of the following: A model identifier of an initial model corresponding to the first federated learning task; A model identifier of a model in any round of iterative training process corresponding to the first federated learning task; A model identifier of a global model corresponding to the first federated learning task; or A task identifier of the first federated learning task.

22. The method according to any one of claims 12-21, characterized in that, Before sending the first request to the first network element, it further includes: Sending a fourth request to a Network Repository Function (NRF) network element, where the fourth request is used to query whether the first network element needs to obtain a global model corresponding to a federated learning task participated by the first network element. Receive a third response to the fourth request from the NRF network element, where the third response is used to indicate that the first network element needs to obtain the global model corresponding to the federated learning task participated in by the first network element.

23. A communication method, applied to a Network Repository Function (NRF) network element, is characterized in that, The method includes: Receive a second request from a first network element, where the second request is used to query whether a second network element can provide the global model corresponding to a first federated learning task to the first network element; Send first information to the first network element, where the first information is used to indicate that the second network element can provide the global model corresponding to the first federated learning task to the first network element.

24. The method according to claim 23, wherein The method further includes: Receive the first information from the second network element.

25. The method according to claim 23 or 24, characterized in that, The method further includes: Receive a fourth request from the second network element, where the fourth request is used to query whether the first network element needs to obtain the global model corresponding to the federated learning task participated in by the first network element; Send a third response to the fourth request to the second network element, where the third response is used to indicate that the first network element needs to obtain the global model corresponding to the federated learning task participated in by the first network element.

26. The method according to any one of claims 23 to 25, characterized in that The method further includes: Receive second information from the first network element, where the second information is used to indicate that the first network element needs to obtain the global model corresponding to the federated learning task participated in by the first network element.

27. A communication method, applied to a first network element, characterized in that The method includes: Receive a first request from a second network element, where the first request is used to request the first network element to participate in a first federated learning task; Send a first response to the first request to the second network element, where the first response is used to indicate that the first network element determines to participate in the first federated learning task or refuses to participate in the first federated learning task, and the first response is further used to indicate that the first network element needs to obtain the global model corresponding to the federated learning task participated in by the first network element.

28. The method according to claim 27, wherein The first response includes first indication information and / or a model acquisition address; The first indication information is used to indicate that the first network element needs to obtain the global model corresponding to the first federated learning task; the model acquisition address is used to indicate the address where the first network element receives model information.

29. A communication device, characterized in that, Includes: A communication unit and a processing unit; The communication unit is used to receive and / or send data; The processing unit is used to execute the method according to any one of claims 1-11, or is used to execute the method according to any one of claims 12-22, or is used to execute the method according to any one of claims 23-26, or is used to execute the method according to any one of claims 27-28.

30. A communication device, characterized in that, Includes: At least one processor; The at least one processor is used to execute the method according to any one of claims 1-11, or is used to execute the method according to any one of claims 12-22, or is used to execute the method according to any one of claims 23-26, or is used to execute the method according to any one of claims 27-28.

31. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when called by a computer, cause the computer to be used to execute the method described in any one of claims 1-11, or to execute the method described in any one of claims 12-22, or to execute the method described in any one of claims 23-26, or to execute the method described in any one of claims 27-28.

32. A chip system, characterized in that, Comprising a processor; The processor is configured to execute a computer-executable program, such that a device installed with the chip system is used to execute the method described in any one of claims 1-11, or to execute the method described in any one of claims 12-22, or to execute the method described in any one of claims 23-26, or to execute the method described in any one of claims 27-28.

33. A communication system, characterized in that, The communication system includes a first network element, a second network element, and a third network element; The first network element is configured to execute the method described in any one of claims 1-11; The second network element is configured to execute the method described in any one of claims 12-22; The third network element is configured to execute the method described in any one of claims 23-26.

34. A computer program product, characterized in that, The computer program product stores a computer program or instructions, which, when executed by a communication device, cause the computer to execute the method described in any one of claims 1-11, or cause the computer to execute the method described in any one of claims 12-22, or cause the computer to execute the method described in any one of claims 23-26, or cause the computer to execute the method described in any one of claims 27-28.

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