Communication method and device

Abstract

Provided are a communication method and device, the method comprising: a first analysis function network element receiving an analysis context transfer request from a second analysis function network element, the first analysis function network element sending an analysis context to the second analysis function network element, the analysis context comprising an identifier of a first model and an identifier of a model training function network element. By adopting the method, the analysis context obtained by the second analysis function network element comprises the identifier of the first model and the identifier of the model training function network element instead of directly obtaining the first information; the second analysis function network element can obtain the first information from the model training function network element according to the identifier of the first model and the information of the model training function network element, so that the second analysis function network element can obtain the model used by the first analysis function network element, and the safety of model obtaining can be improved.

Description

Technical Field

[0001] The present application relates to the field of communications, and in particular to a communication method and device. Background Art

[0002] Due to internal (e.g. load balancing, graceful shutdown) or external triggers (e.g. user equipment (UE) mobility), a service consuming network element may transfer one or more analytics subscriptions from one analytics logical function (AnLF) network element to another AnLF network element, i.e. from a source AnLF network element to a target AnLF network element.

[0003] Currently, the service consumption network element or the source AnLF network element needs to use the network element discovery process to discover the target AnLF network element, so as to transfer the analysis context of the analysis subscription that needs to be transferred from the source AnLF network element to the target AnLF network element. After the target AnLF network element obtains the analysis context, the target AnLF network element hopes to continue to provide services to the service consumption network element using the model used by the source AnLF network element. How to enable the target AnLF network element to continue to provide services to the service consumption network element using the model used by the source AnLF network element is a problem worthy of attention. Summary of the invention

[0004] The embodiments of the present application provide a communication method and apparatus to solve the problem that a source AnLF network element notifies a target AnLF that a model used by the source AnLF network element has a potential security risk.

[0005] In a first aspect, the present application provides a communication method, which can be performed by a first analysis function network element or a module (such as a chip) in the first analysis function network element. The method includes: the first analysis function network element receives an analysis context transfer request from a second analysis function network element; the first analysis function network element sends an analysis context to the second analysis function network element, and the analysis context includes an identifier of a first model and an identifier of a model training function network element.

[0006] By adopting the above method, the analysis context provided by the first analysis function network element to the second analysis function network element includes the identifier of the first model and the identifier of the model training function network element, rather than directly including the first information, which can improve the security of model acquisition.

[0007] In a possible implementation, the first analysis function network element receives first information from the model training function network element, where the first information is associated with the first model.

[0008] In a possible implementation, the first information includes an identifier of the model training function network element.

[0009] The model training function network element provides first information to the first analysis function network element, and the first information is associated with the first model.

[0010] The model training function network element is a producer of the model associated with the first information. The model training function network element authorizes the first analysis function network element to obtain the model associated with the first information. The first information includes an identifier of a first model, and the model associated with the first information is the first model.

[0011] The first information is information related to the first model. Exemplarily, the first information includes the network element identifier of the producer of the model, that is, the identifier of the network element with the model training function, or the network element identifier of the network element providing the information related to the first model. The first information may also include the address of the model, for example, a URL, etc.

[0012] In one possible implementation, before the first analysis function network element receives an analysis context transfer request from the second analysis function network element, the first analysis function network element uses the first model to provide services corresponding to the analysis identifier; the first analysis function network element sends an analysis subscription transfer request to the second analysis function network element, and the analysis subscription transfer request includes the analysis identifier.

[0013] In one possible implementation, the analysis context transfer request includes the identifier of the manufacturer of the second analysis function network element; before the first analysis function network element sends the analysis context to the second analysis function network element, the first analysis function network element obtains a first interoperability identifier, and the first interoperability identifier is the interoperability identifier corresponding to the analysis identifier of the model training function network element, or the first interoperability identifier is the interoperability identifier of the model training function network element; the first analysis function network element determines that the first interoperability identifier includes the identifier of the manufacturer of the second analysis function network element.

[0014] The above design can be used to determine whether the first interoperability identifier includes the identifier of the manufacturer of the second analysis function network element.

[0015] In a possible implementation, the first analysis function network element obtains the first interoperability identifier from the model training function network element or the network storage function network element.

[0016] In one possible implementation, before the first analysis function network element receives an analysis context transfer request from the second analysis function network element, the first analysis function network element sends a model request message to the model training function network element, and the model request message includes the analysis identifier; the first analysis function network element receives the identifier of the first model from the model training function network element.

[0017] In a possible implementation, before the first analysis function network element sends the analysis context to the second analysis function network element, the first analysis function network element sends a first request message to the model training function network element, and the first request message is used to request the model training function network element to agree that the first analysis function network element provides the second analysis function network element with the identifier of the first model; the first analysis function network element receives a first response message from the model training function network element, and the first response message indicates that the first analysis function network element agrees to provide the second analysis function network element with the identifier of the first model.

[0018] The above design can be used to request the model training function network element to authorize the first analysis function network element to provide the identification of the first model to the second analysis function network element.

[0019] In a second aspect, the present application provides a communication method, which can be executed by a second analysis function network element or a module (such as a chip) in the second analysis function network element. The method includes: the second analysis function network element sends an analysis context transfer request to the first analysis function network element; the second analysis function network element receives an analysis context from the first analysis function network element, the analysis context includes an identifier of a first model, and an identifier of a model training function network element; the second analysis function network element sends the identifier of the first model to the model training function network element; the second analysis function network element receives first information from the model training function network element, and the first information is associated with the first model.

[0020] Using the above method, the analysis context obtained by the second analysis function network element includes the identifier of the first model and the identifier of the model training function network element, instead of obtaining the first information directly from the first analysis function network element. The second analysis function network element can obtain the first information from the model training function network element based on the identifier of the first model and the identifier of the model training function network element, so that the second analysis function network element can obtain the model used by the first analysis function network element and improve the security of model acquisition.

[0021] In a possible implementation, the first information includes an identifier of the model training function network element.

[0022] In a possible implementation, the analysis context transfer request includes an identifier of a manufacturer of the second analysis function network element.

[0023] In one possible implementation, before the second analysis function network element sends an analysis context transfer request to the first analysis function network element, the second analysis function network element receives an analysis subscription transfer request from the first analysis function network element, and the analysis subscription transfer request includes analysis subscription information; the second analysis function network element determines the first analysis function network element based on the analysis subscription information.

[0024] In one possible implementation, before the second analysis function network element sends an analysis context transfer request to the first analysis function network element, the second analysis function network element receives an analysis subscription request from a service consumption network element; the analysis subscription request includes analysis subscription information; the second analysis function network element determines the first analysis function network element based on the analysis subscription information.

[0025] In a third aspect, the present application provides a communication method, which can be executed by a model training function network element or a module (such as a chip) in the model training function network element. The method includes: the model training function network element receives an identifier of a first model from a second analysis function network element; the model training function network element determines first information based on the identifier of the first model, and the first information is associated with the first model; the model training function network element sends the first information to the second analysis function network element.

[0026] By adopting the above method, when the model training function network element determines that the second analysis function network element obtains the identification of the first model, the model training function network element provides the first information to the second analysis function network element, and the security of model acquisition can be improved.

[0027] In a possible implementation, before the model training function network element receives the identifier of the first model from the second analysis function network element, the model training function network element receives a first request message from the first analysis function network element, and the first request message is used to request the model training function network element to agree that the first analysis function network element provides the identifier of the first model to the second analysis function network element; the model training function network element sends a first response message to the first analysis function network element, and the first response message indicates that it agrees that the first analysis function network element provides the identifier of the first model to the second analysis function network element.

[0028] By adopting the above design, the model training functional network element can authorize the first analysis functional network element to provide the identification of the first model to the second analysis functional network element.

[0029] In a possible implementation, the model training function network element receives a model request message from the first analysis function network element, and the model request message includes an analysis identifier; the model training function network element sends the identifier of the first model to the first analysis function network element, and the first model is used to provide a service corresponding to the analysis identifier.

[0030] In one possible implementation, before the model training function network element receives the identifier of the first model from the second analysis function network element, the model training function network element sends a first interoperability identifier to the first analysis function network element, where the first interoperability identifier is the interoperability identifier corresponding to the analysis identifier of the model training function network element, or the first interoperability identifier is the interoperability identifier of the model training function network element.

[0031] In a possible implementation, before the model training function network element receives the identifier of the first model from the second analysis function network element, the model training function network element sends first information to the first analysis function network element, where the first information is associated with the first model.

[0032] In a possible implementation, the first information includes an identifier of the model training function network element.

[0033] In a fourth aspect, the present application provides a communication method, which can be executed by a first analysis function network element or a module (such as a chip) in the first analysis function network element. The method includes: the first analysis function network element receives an analysis context transfer request from a second analysis function network element; the first analysis function network element sends an analysis context to the second analysis function network element, and the analysis context includes an association identifier and an identifier of a model training function network element.

[0034] By adopting the above method, the analysis context provided by the first analysis function network element to the second analysis function network element includes the association identifier and the identifier of the model training function network element, rather than directly including the first information, which can improve the security of model acquisition.

[0035] In a possible implementation, the association identifier corresponds to the first information, the model training function network element is used to provide the first information, and the first information is associated with the first model.

[0036] In a possible implementation, the first analysis function network element sends a model request message to the model training function network element, and the model request message includes an analysis identifier; the first analysis function network element receives the identifier of the first model and the association identifier from the model training function network element, and the first model is used to provide the service corresponding to the analysis identifier.

[0037] With the above design, the first analysis function network element can use the existing subscription association identifier as the association identifier.

[0038] In a possible implementation, after the first analysis function network element receives an analysis context transfer request from the second analysis function network element, the first analysis function network element sends a third request message to the model training function network element, and the third request message includes the identifier of the first model; the third request message is used to request the model training function network element to generate an identifier associated with the first information; the first analysis function network element receives a third response message from the model training function network element, and the third response message includes the associated identifier.

[0039] With the above design, the first analysis function network element can request the model training function network element to generate an identifier associated with the first information as an associated identifier. Alternatively, it can also be described as the first analysis function network element can request the model training function network element to generate an identifier associated with the first model as an associated identifier.

[0040] In one possible implementation, before the first analysis function network element receives an analysis context transfer request from the second analysis function network element, the first analysis function network element uses the first model to provide services corresponding to the analysis identifier; the first analysis function network element sends an analysis subscription transfer request to the second analysis function network element, and the analysis subscription transfer request includes the analysis identifier.

[0041] In one possible implementation, the analysis context transfer request includes the identifier of the manufacturer of the second analysis function network element; before the first analysis function network element sends the analysis context to the second analysis function network element, the first analysis function network element obtains a first interoperability identifier, and the first interoperability identifier is the interoperability identifier corresponding to the analysis identifier of the model training function network element, or the first interoperability identifier is the interoperability identifier of the model training function network element; the first analysis function network element determines that the first interoperability identifier includes the identifier of the manufacturer of the second analysis function network element.

[0042] In a possible implementation, the first analysis function network element obtains the first interoperability identifier from the model training function network element or the network storage function network element.

[0043] In a fifth aspect, the present application provides a communication method, which can be executed by a second analysis function network element or a module (such as a chip) in the second analysis function network element. The method includes: the second analysis function network element sends an analysis context transfer request to the first analysis function network element; the second analysis function network element receives the analysis context from the first analysis function network element, the analysis context includes an association identifier and an identifier of a model training function network element; the second analysis function network element sends the association identifier to the model training function network element; the second analysis function network element receives the first information from the model training function network element, and the first information is associated with the first model.

[0044] By adopting the above method, the analysis context obtained by the second analysis function network element includes the association identifier and the identifier of the model training function network element, instead of directly obtaining the first information from the first analysis function network element, the second analysis function network element can obtain the first information from the model training function network element based on the association identifier and the identifier of the model training function network element, so that the second analysis function network element can obtain the model used by the first analysis function network element and the security of model acquisition can be improved.

[0045] In a possible implementation, the first association identifier corresponds to the first information, and the model training function network element is used to provide the first information.

[0046] In one possible implementation, before the second analysis function network element sends an analysis context transfer request to the first analysis function network element, the second analysis function network element receives an analysis subscription transfer request from the first analysis function network element, and the analysis subscription transfer request includes analysis subscription information; the second analysis function network element determines the first analysis function network element based on the analysis subscription information.

[0047] In one possible implementation, before the second analysis function network element sends an analysis context transfer request to the first analysis function network element, the second analysis function network element receives an analysis subscription request from a service consumption network element; the analysis subscription request includes analysis subscription information; the second analysis function network element determines the first analysis function network element based on the analysis subscription information.

[0048] In a sixth aspect, the present application provides a communication method, which can be executed by a model training function network element or a module (such as a chip) in the model training function network element. The method includes: the model training function network element receives an association identifier from a second analysis function network element; the model training function network element determines first information according to the association identifier, and the first information is associated with the first model; the model training function network element sends the first information to the second analysis function network element.

[0049] By adopting the above method, when the model training function network element determines that the second analysis function network element obtains the association identifier, the model training function network element provides the first information to the second analysis function network element, and the security of model acquisition can be improved.

[0050] In a possible implementation, before the model training function network element receives the association identifier from the second analysis function network element, the model training function network element receives a third request message from the first analysis function network element, and the third request message includes the identifier of the first model; the third request message is used to request the model training function network element to generate an identifier associated with the first information; the model training function network element sends a third response message to the first analysis function network element, and the third response message includes the association identifier.

[0051] In a possible implementation, the model training function network element receives a model request message from the first analysis function network element, and the model request message includes an analysis identifier; the model training function network element sends the identifier of the first model and the association identifier to the first analysis function network element, and the first model is used to provide a service corresponding to the analysis identifier.

[0052] In a possible implementation, the model training function network element also sends a first interoperability identifier to the first analysis function network element, where the first interoperability identifier is the interoperability identifier corresponding to the analysis identifier of the model training function network element, or the first interoperability identifier is the interoperability identifier of the model training function network element.

[0053] In a seventh aspect, the present application provides a communication method, which can be performed by a first analysis function network element or a module (such as a chip) in the first analysis function network element. The method includes: the first analysis function network element receives an analysis context transfer request from a second analysis function network element, wherein the analysis context transfer request includes a model receiving address; the first analysis function network element sends an identifier of a first model and the model receiving address to a model training function network element.

[0054] By adopting the above method, the analysis context provided by the first analysis function network element to the second analysis function network element includes the identifier of the first model and the model receiving address, rather than directly including the first information, which can improve the security of model acquisition.

[0055] In one possible implementation, before the first analysis function network element receives an analysis context transfer request from the second analysis function network element, the first analysis function network element uses the first model to provide services corresponding to the analysis identifier; the first analysis function network element sends an analysis subscription transfer request to the second analysis function network element, and the analysis subscription transfer request includes the analysis identifier.

[0056] In one possible implementation, the analysis context transfer request includes the identifier of the manufacturer of the second analysis function network element; before the first analysis function network element sends the analysis context to the second analysis function network element, the first analysis function network element obtains a first interoperability identifier, and the first interoperability identifier is the interoperability identifier corresponding to the analysis identifier of the model training function network element, or the first interoperability identifier is the interoperability identifier of the model training function network element; the first analysis function network element determines that the first interoperability identifier includes the identifier of the manufacturer of the second analysis function network element.

[0057] In a possible implementation, the first analysis function network element obtains the first interoperability identifier from the model training function network element or the network storage function network element.

[0058] In one possible implementation, before the first analysis function network element receives an analysis context transfer request from the second analysis function network element, the first analysis function network element sends a model request message to the model training function network element, and the model request message includes the analysis identifier; the first analysis function network element receives the identifier of the first model from the model training function network element.

[0059] In an eighth aspect, the present application provides a communication method, which can be performed by a second analysis function network element or a module (such as a chip) in the second analysis function network element. The method includes: the second analysis function network element sends an analysis context transfer request to the first analysis function network element; wherein the analysis context transfer request includes a model receiving address; the second analysis function network element obtains first information according to the model receiving address, and the first information is associated with the first model.

[0060] Using the above method, the second analysis function network element provides the model receiving address to the first analysis function network element, and obtains the first information based on the model receiving address. This allows the second analysis function network element to obtain the model used by the first analysis function network element and improves the security of model acquisition.

[0061] In one possible implementation, before the second analysis function network element sends an analysis context transfer request to the first analysis function network element, the second analysis function network element receives an analysis subscription transfer request from the first analysis function network element, and the analysis subscription transfer request includes analysis subscription information; the second analysis function network element determines the first analysis function network element based on the analysis subscription information.

[0062] In one possible implementation, before the second analysis function network element sends an analysis context transfer request to the first analysis function network element, the second analysis function network element receives an analysis subscription request from a service consumption network element; the analysis subscription request includes analysis subscription information; the second analysis function network element determines the first analysis function network element based on the analysis subscription information.

[0063] In a ninth aspect, the present application provides a communication method, which can be executed by a model training function network element or a module (such as a chip) in the model training function network element. The method includes: the model training function network element receives an identifier of a first model and a model receiving address from a second analysis function network element; the model training function network element determines first information according to the identifier of the first model, and the first information is associated with the first model; the model training function network element provides the first information according to the model receiving address.

[0064] By using the above method, the model training function network element obtains the model receiving address from the first analysis function network element and provides the first information based on the model receiving address, so that the second analysis function network element can obtain the model used by the first analysis function network element and improve the security of model acquisition.

[0065] In a possible implementation, the model training function network element receives a model request message from the first analysis function network element, and the model request message includes an analysis identifier; the model training function network element sends the identifier of the first model to the first analysis function network element, and the first model is used to provide a service corresponding to the analysis identifier.

[0066] In a possible implementation, the model training function network element also sends a first interoperability identifier to the first analysis function network element, where the first interoperability identifier is the interoperability identifier corresponding to the analysis identifier of the model training function network element, or the first interoperability identifier is the interoperability identifier of the model training function network element.

[0067] In the tenth aspect, the present application provides a communication device, which may be a first device, or a module or unit (for example, a chip, or a chip system, or a circuit) in the first device that corresponds one-to-one to the method / operation / step / action described in any one of the first to ninth aspects, or may be capable of being used in combination with the first device.

[0068] In an eleventh aspect, the present application provides a communication device comprising at least one processing element and at least one storage element, wherein the at least one storage element is used to store programs and data, and the at least one processing element is used to read and execute the programs and data stored in the storage element, so that any method described in any one of the above aspects of the present application is implemented.

[0069] In a twelfth aspect, the present application further provides a computer program, which, when executed on a computer, enables the computer to execute any of the methods described in any of the above aspects.

[0070] In the thirteenth aspect, the present application provides a communication device, which includes: an interface circuit and at least one processor; the interface circuit is used to provide the at least one processor with input and / or output of programs or instructions; the at least one processor is used to execute the program or instructions so that the communication device can implement any method described in any of the above aspects.

[0071] In a possible manner, the communication device includes the at least one memory, and the at least one memory is used to store the program or instruction.

[0072] In a fourteenth aspect, the present application provides a computer storage medium storing a software program, which, when read and executed by one or more processors, can implement any of the methods described in any of the above aspects.

[0073] In a fifteenth aspect, the present application provides a computer program product comprising instructions, which, when executed on a computer, enables the computer to execute any of the methods described in any of the above aspects.

[0074] In a sixteenth aspect, the present application provides a chip system, comprising at least one chip and a memory, wherein the at least one chip is used to read and execute a program stored in the memory to implement any of the methods described in any of the above aspects.

[0075] In the seventeenth aspect, the present application provides a communication system, which includes a first analysis function network element, a second analysis function network element and a model training function network element, the first analysis function network element executes the method described in any one of the first, fourth or seventh aspects, the second analysis function network element executes the method described in any one of the second, fifth or eighth aspects, and the model training function network element executes the method described in any one of the third, sixth or ninth aspects.

[0076] In a possible manner, the system further includes a network storage function network element and / or a service consumption network element.

[0077] Based on the implementations provided in the above aspects, the present application can also be further combined to provide more implementations. BRIEF DESCRIPTION OF THE DRAWINGS

[0078] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the background technology, the drawings required for use in the embodiments of the present application or the background technology will be described below.

[0079] Figure 1 This is a schematic diagram of the 5G network architecture based on the service-oriented architecture in this application;

[0080] Figure 2 One of the flow charts for summarizing a communication method in this application;

[0081] Figure 3 A flowchart of a service consumption network element triggering a target AnLF to send an analysis context transfer request to a first AnLF in this application;

[0082] Figure 4 This is a flowchart of a first AnLF triggering a target AnLF to send an analysis context transfer request to the first AnLF in this application;

[0083] Figure 5 This is the second flow chart of an overview of a communication method in this application;

[0084] Figure 6 This is a third flow chart of an overview of a communication method in this application;

[0085] Figure 7 This is a fourth flow chart of an overview of a communication method in this application;

[0086] Figure 8 This is a fifth flow chart of an overview of a communication method in this application;

[0087] Fig. 9 This is a schematic diagram of the structure of a communication device in this application;

[0088] Fig.10 This is a schematic diagram of the structure of another communication device in this application. DETAILED DESCRIPTION

[0089] The specific implementation of the application is described below by way of example in conjunction with the accompanying drawings in the embodiments of the present application. However, the implementation of the present application may also include combining these embodiments without departing from the spirit or scope of the present application, such as adopting other embodiments and making structural changes. Therefore, the detailed description of the following embodiments should not be understood in a restrictive sense. The terms used in the embodiments of the present application are only used to explain the specific embodiments of the present application, and are not intended to limit the present application.

[0090] The embodiments of the present application can be applied to various communication systems, for example: 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), worldwide 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.

[0091] Figure 1 Schematic diagram of 5G network architecture based on service-oriented architecture. Figure 1The 5G network architecture shown may include terminal equipment, access network equipment and core network equipment. The terminal equipment accesses the data network (DN) through the access network equipment and the core network equipment. Among them, the core network equipment includes a variety of network functions (NF) or network elements, for example, including some or all of the following 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 storage function (NRF) network element (not shown in the figure), etc.

[0092] 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 completes 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.

[0093] 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), Internet of Things (IOT), virtual reality, augmented reality, industrial control, autonomous driving, telemedicine, smart grid, smart furniture, smart office, smart wearable, smart transportation, smart city, etc. Terminal devices can be mobile phones, tablet computers, computers with wireless transceiver functions, wearable devices, vehicles, urban air vehicles (such as drones, helicopters, etc.), ships, robots, robotic arms, smart home devices, etc.

[0094] The access network equipment and terminal equipment can be fixed or movable. The access network equipment and terminal equipment can be deployed on land, including indoors or outdoors, handheld or vehicle-mounted; they can also be deployed on the water surface; they can also be deployed on airplanes, balloons and artificial satellites in the air. The embodiments of the present application do not limit the application scenarios of the access network equipment and terminal equipment.

[0095] The following is a brief introduction to some core network equipment:

[0096] AMF network element, referred to as AMF, includes functions such as mobility management, access authentication / authorization, etc. In addition, it is also responsible for transmitting user policies between terminal devices and PCF.

[0097] 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.

[0098] UPF network element, referred to as UPF, is an interface with the data network, including functions such as user plane data forwarding, session / flow-level billing statistics, and bandwidth limitation.

[0099] UDM network element, referred to as UDM, includes functions such as execution management of contract data and user access authorization.

[0100] 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.

[0101] NEF network element, referred to as NEF, is used to support the opening of capabilities and events.

[0102] AF network element, referred to as AF, transmits the requirements of the application side to the network side, such as quality of service (QoS) requirements or user status event subscription, etc. AF can be a third-party functional entity or an application server deployed by an operator.

[0103] 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.

[0104] NRF network element, referred to as NRF, can be used to provide network element discovery function, based on the request of other network elements, provide network element information corresponding to the network element type. NRF network element also provides network element management services, such as network element registration, update, deregistration, network element status subscription and push, etc.

[0105] 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 data of the terminal device on the access network device, the core network network element or the third-party application device, and then perform data analysis based on the collected data, and output the data analysis results 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 jointly set up with other network elements, for example, NWDAF is set up in a PCF network element or an AMF network element.

[0106] In Release 17 of the 3rd Generation Partnership Project (3GPP), the training function and the reasoning function of NWDAF are split. An NWDAF can support only the model training function, or only the data reasoning function, or both the model training function and the data reasoning function.

[0107] In the present application, the model training function network element may be a NWDAF supporting the model training function, which may also be referred to as a training NWDAF, or a NWDAF supporting a model training logical function (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.

[0108] The analysis function network element may be an NWDAF supporting data reasoning function, which may also be referred to as reasoning NWDAF, or an NWDAF supporting analysis logical function (AnLF), referred to as AnLF. For example, AnLF may request a model from MTLF through a model subscription (MLModelProvision_Subscribe) service or message, and the model may be obtained by MTLF according to relevant data of the model training. Furthermore, AnLF may input input data into the trained model to obtain analysis results or reasoning data.

[0109] It is understandable that MTLF can be understood as NWDAF that at least supports model training function. As a possible implementation method, MTLF can also support data reasoning function. AnLF can be understood as NWDAF that at least supports data reasoning function. As a possible implementation method, AnLF can also support model training function.

[0110] It can be understood that the above network elements are examples of one implementation method, and the present application does not exclude the existence of network elements or devices with the above network element functions having other names or other forms in 6G or newer wireless communication systems.

[0111] It is understandable that the above 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 network element or function can be implemented by one device, or by multiple devices together, or can be a functional module in one device, which is not specifically limited in the embodiments of the present application.

[0112] Figure 1 Among them, Nudr, Npcf, Namf, Nudm, Nsmf, Naf, and Nnwdaf are service interfaces provided by the above-mentioned UDR, PCF, AMF, UDM, SMF, AF, and NWDAF respectively, which are used to call corresponding service operations.

[0113] The following is an explanation of the basic technical concepts involved in this application:

[0114] 1. Analysis ID

[0115] The analysis identifier can be used to indicate an analysis business or an analysis service, or service for short. The service is associated with a model, that is, the model can be used to perform the service. Alternatively, the analysis identifier is associated with a model, that is, the model is used to perform the service corresponding to the analysis identifier.

[0116] Or it can also be understood that MTLF is related to 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 related to one or more analysis identifiers. It can be understood that the MTLF can provide a model of the service corresponding to each analysis identifier in one or more analysis identifiers. For example, MTLF1 is related to 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.

[0117] 2. Interoperability indicator

[0118] Exemplarily, the interoperability identifier may correspond to the MTLF, or to the analysis identifier, or to the analysis identifier corresponding to the MLTF. Alternatively, it may be described as that the interoperability identifier is related to the MTLF, or the interoperability identifier is related to the analysis identifier. The interoperability identifier may also be referred to as an interoperability indicator, or a machine learning (ML) model interoperability identifier, or a model interoperability indicator (ML Model interoperability indicator).

[0119] The interoperability identifier includes a list of vendors, or is described as a list of NWDAF providers (or suppliers). The vendors in the vendor list are allowed to retrieve or use the models provided by MTLF. The interoperability identifier also indicates that MTLF supports vendors to request the models provided by MTLF for the NWDAF of the vendors in the vendor list. The interoperability identifier also indicates that the vendors in the vendor list are allowed to obtain models from MTLF. The interoperability identifier also indicates that the MTLF allows the vendors in the vendor list to obtain models from the MTLF.

[0120] The interoperability identifier is a list of MTLF providers, for example, the interoperability identifier represents the manufacturer identifier, or the interoperability identifier is associated with the manufacturer identifier. The interoperability identifier can be associated with the analysis identifier, such as a one-to-one correspondence between the two, indicating that the MTLF allows the corresponding manufacturer or the MTLF included in the manufacturer to obtain the model corresponding to the analysis identifier, and / or, indicating that the MTLF is allowed to interoperate with the AnLF on the model corresponding to the analysis identifier. Optionally, an MTLF may have one or more interoperability identifiers. If there are multiple interoperability identifiers, the multiple interoperability identifiers correspond to different analysis identifiers, respectively. For example, MTLF NF ID 1 corresponds to analysis identifier 1 and analysis identifier 2, wherein 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. Optionally, if the MTLF to which MTLF NF ID 1 belongs and the MTLF to which MTLF NF ID 2 belongs support interoperability, the MTLF to which MTLF NF ID 2 belongs may have interoperability identification 1 and interoperability identification 2, wherein interoperability identification 1 corresponds to analysis identification 1, and / or, interoperability identification 2 corresponds to analysis identification 2, that is, MTLFs of the same manufacturer may have the same interoperability identification for the same analysis identification. In addition, if the MTLF to which MTLF NF ID 1 belongs and the MTLF to which MTLF NF ID 2 belongs belong to different manufacturers, the MTLF to which MTLF NFID 2 belongs may have interoperability identification 3 and interoperability identification 4, wherein interoperability identification 3 corresponds to analysis identification 1, and / or, interoperability identification 4 corresponds to analysis identification 2, that is, MTLFs of the same manufacturer may have different interoperability identifications for the same analysis identification.

[0121] Exemplarily, analysis identifier 1 is related to model 1, that is, model 1 is used to execute the service corresponding to analysis identifier 1, and analysis identifier 1 is related to interoperability identifier 1, that is, model 1 is related to interoperability identifier 1. Assume that interoperability identifier 1 includes the identifier of manufacturer 1 and the identifier of manufacturer 2, that is, model 1 can be provided to manufacturer 1 and manufacturer 2 for use, or it can be understood that if the manufacturer of NWDAF is manufacturer 1 or manufacturer 2, then the NWDAF can use model 1.

[0122] Exemplarily, one MTLF may have one or more interoperability identifiers. If there are multiple interoperability identifiers, the multiple interoperability identifiers may correspond to different analysis identifiers. For example, MTLF1 corresponds to analysis identifier 1 and analysis identifier 2, wherein interoperability identifier 1 corresponds to analysis identifier 1, and interoperability identifier 2 corresponds to analysis identifier 2.

[0123] 3. Model Producer

[0124] The model producer is the entity that produces the model, or the entity that has the right to provide model information to other entities according to the network configuration, and the consumer can obtain the model based on the model information. Model information includes but is not limited to: the uniform resource locator (URL) of the model file, the model itself, etc.

[0125] 4. Manufacturer logo

[0126] The vendor ID of the vendor may also be expressed as network element information, identifying the vendor or manufacturer of the network element. For example, Vendor ID1 identifies the vendor of the NWDAF network element.

[0127] The manufacturer identifier can be used to identify a device manufacturer. A manufacturer identifier can correspond to one or more NWDAF device identifiers. For example, NWDAF NF ID 1 and NWDAF NF ID 2 can both correspond to manufacturer identifier 1, that is, the MTLF to which MTLF NF ID 1 belongs and the MTLF to which MTLF NF ID 2 belongs belong to the same manufacturer, and the manufacturer identifier of the manufacturer is manufacturer identifier 1.

[0128] Currently, according to the authorization process of the model, the transfer or use of the model must be authorized by the model producer. Therefore, the source AnLF network element must obtain authorization from the model producer (i.e., the MTLF network element that produced the model) before passing the model to a third party. If the source AnLF network element directly carries the address of the model to the target AnLF (i.e., the third party) through the analysis context, there is a security risk.

[0129] Based on the above Figure 1 The network system architecture shown and the contents of the above-mentioned related technical introductions provide several possible communication methods in the embodiments of the present application. In the following, the analysis function network element is AnLF and the model training function network element is MTLF as an example for explanation.

[0130] The present application provides a communication method, such as Figure 2 As shown, the method includes:

[0131] Step 200: the second AnLF sends an analysis context transfer request to the first AnLF, and correspondingly, the first AnLF receives the analysis context transfer request from the second AnLF.

[0132] Exemplarily, the first AnLF provides a service corresponding to an analysis identifier for a service consumption network element, and the analysis subscription corresponding to the analysis identifier is associated with an analysis context identifier. If the first AnLF or the service consumption network element determines to select a target AnLF, that is, decides to transfer the analysis subscription from the first AnLF to the target AnLF, the target AnLF is triggered to send an analysis context transfer request to the first AnLF. The following description takes the target AnLF as the second AnLF as an example, and the first AnLF may also be referred to as the source AnLF.

[0133] Exemplarily, the analysis context transfer request includes the analysis context identifier, so that the first AnLF determines that the analysis subscription to be transferred is the analysis subscription associated with the analysis context identifier, and further determines the analysis context corresponding to the analysis context identifier.

[0134] For example, the analysis context identifier may be a subscription correlation ID, or a set of user permanent identifiers (SUPI) and related analysis IDs for UE-related analysis, or an analysis ID for NF-related analysis.

[0135] Step 210: The first AnLF sends the analysis context to the second AnLF, and correspondingly, the second AnLF receives the analysis context from the first AnLF.

[0136] The analysis context includes an identifier of the first model and an identifier of the first MTLF. The first AnLF uses the first model to provide a service corresponding to the analysis identifier for the service consumption network element. The first MTLF corresponding to the identifier of the first MTLF is the producer of the first model. That is, the first AnLF obtains the ML model information from the first MTLF to provide the service corresponding to the analysis identifier. The ML model information can also be referred to as the first information, and the first information is associated with the first model. The first information may include an ML model file address (e.g., a URL or a fully qualified domain name (FQDN), or an analytics data repository functional (ADRF) ID or an ADRF set ID. When the ML model information includes an ADRFID or ADRF set ID, the first information may also include a storage transaction ID. Optionally, the first information may include an identifier of the first model. Optionally, the first information may include an interoperability identifier corresponding to an analysis identifier corresponding to the first model of the MTLF. The first information may also include other content, which is not limited in this application. It is understandable that part of the content included in the first information can be used to obtain the first model, and the first information also includes other content, for example, relevant information used to describe the first model, model accuracy information, model applicable scenario information, etc.

[0137] The first AnLF obtains, from the first MTLF, ML model information of a model used to provide a service corresponding to the analysis identifier.

[0138] Step 220: the second AnLF sends the identifier of the first model to the first MTLF, and correspondingly, the first MTLF receives the identifier of the first model from the second AnLF.

[0139] Exemplarily, the second AnLF sends a model request message to the first MTLF, where the model request message includes an identifier of the first model.

[0140] The model request message may be a model provision subscription (Nnwdaf_MLModelProvision_Subscribe) message.

[0141] Exemplarily, the second AnLF sends the identifier of the first model to the first MTLF corresponding to the identifier of the first MTLF according to the identifier of the first MTLF in the analysis context.

[0142] Step 230: The first MTLF determines the first information according to the identifier of the first model.

[0143] Exemplarily, the first MTLF determines whether the first model can be provided for the second AnLF, for example, by indexing the context in which the first model is used according to the identifier of the first model, and performing analysis and judgment. For example, it is determined whether the area of ​​the first model has changed. If the first MTLF determines to provide the first model for the second AnLF, the first information is determined according to the identifier of the first model. If the first MTLF determines that the first model cannot be provided for the second AnLF, a rejection message can be returned, or a new model can be returned to the second AnLF.

[0144] Step 240: The first MTLF sends the first information to the second AnLF. Correspondingly, the second AnLF receives the first information from the first MTLF.

[0145] For the specific content of the first information, please refer to the relevant description in the above step 210.

[0146] Step 250: The second AnLF obtains the first model according to the first information.

[0147] Exemplarily, the second AnLF may obtain the first model according to the URL in the first information. Alternatively, the second AnLF may send a model acquisition request to the ADRF identified by the ADRFID in the first information, and the ADRF may send the first model to the first AnLF.

[0148] Using the above method, the analysis context obtained by the second AnLF includes the identifier of the first model and the identifier of the first MTLF, instead of directly including the first information. The second AnLF can obtain the first information from the first MTLF based on the identifier of the first model and the identifier of the first MTLF, so that the second AnLF can obtain the model used by the first AnLF network element and the security of model acquisition can be improved.

[0149] The following combination Figure 3 and Figure 4 right Figure 2 In the following, the analysis function network element is AnLF, the model training function network element is MTLF, and the network storage function network element is NRF.

[0150] like Figure 3 As shown, the process in which the service consumption network element determines that a target AnLF needs to be selected and triggers the target AnLF to send an analysis context transfer request to the first AnLF is as follows:

[0151] Step 301: A service consumption network element sends a first analysis subscription message to a first AnLF, wherein the first analysis subscription message includes an analysis identifier.

[0152] Exemplarily, the service consuming network element requests the first AnLF to provide it with the service corresponding to the analysis identifier through the first analysis subscription message. For example, the service consuming network element may be an AMF, an SMF or other core network elements.

[0153] Exemplarily, the analysis subscription message may be Nnwdaf_AnalyticsSubscription_Subscribe.

[0154] Step 302: The first AnLF sends a model request message to the first MTLF, wherein the model request message includes an analysis identifier.

[0155] Exemplarily, the model request message is a model provision subscription (Nnwdaf_MLModelProvision_Subscribe) message.

[0156] In a possible implementation, the first AnLF may obtain the first MTLF through the network element discovery process. Exemplarily, the first AnLF sends an NF discovery message 1 to the NRF. The NF discovery message 1 includes an analysis identifier. For example, the NF discovery message may be Nnrf_NF Discovery. The NF discovery message 1 is used to discover the MTLF, or to discover the NWDAF of the included MTLF. The NRF determines the first MTLF according to the analysis identifier in the NF discovery message 1. The NRF sends an NF discovery response message 1 to the first AnLF. The NF discovery response message 1 includes information about the first MTLF, wherein the information about the first MTLF may include at least one of an identifier of the first MTLF, an analysis identifier, and a first interoperability identifier. The first interoperability identifier is an interoperability identifier corresponding to the analysis identifier of the first MTLF or an interoperability identifier of the first MTLF. For example, the information of the first MTLF is the NF information (profile) of the first MTLF.

[0157] It is understandable that the NRF can determine one or more MTLFs according to the analysis identifier in the NF discovery message 1. At this time, the NF discovery response message 1 can include information of the one or more MTLFs. The first MTLF can be understood as any one of the one or more MTLFs, and the following only takes the first MTLF as an example for explanation.

[0158] Step 303: The first MTLF sends the identifier of the first model to the first AnLF.

[0159] Exemplarily, the first MTLF determines the first model according to the analysis identifier in the model request message. The first model is used to provide a service corresponding to the analysis identifier.

[0160] In a possible implementation, the first MTLF may also send at least one of a subscription correlation ID, the first information, and the first interoperability ID to the first AnLF. For example, the subscription correlation ID is subscription correlation ID 1. For a description of the first information, reference may be made to the above step 210. The above information may be carried by one or more messages, which is not limited in this application.

[0161] It can be understood that the first MTLF is the producer of the model corresponding to the identifier of the first model.

[0162] It can also be understood that the first MTLF is the provider of the model corresponding to the identifier of the first model.

[0163] It can also be understood that the first MTLF is a provider of the first information of the model corresponding to the identifier of the first model.

[0164] It can also be understood that the first MTLF provides the first model and / or information of the first model to the first AnLF.

[0165] It can also be understood that the first MTLF provides the first AnLF with the first model and / or the information of the first model, and the first model and / or the information of the first model are used to provide the analysis service corresponding to the analysis identifier.

[0166] The model subscription association corresponding to the subscription association identifier and the analysis identifier is used to identify the model subscription between the first AnLF and the first MTLF. In addition, the first MTLF stores the corresponding relationship between the subscription association identifier and the first information.

[0167] Step 304: The first AnLF uses the first model to provide the service consuming network element with the service corresponding to the analysis identifier.

[0168] Exemplarily, the first AnLF obtains the first model according to the first information, and uses the first model to provide the service corresponding to the analysis identifier for the service consumption network element. One possible scenario is that the first AnLF obtains the model according to the first information, for example, through the URL of the model in the first information, for example, through the ADRF in the first information, the first AnLF obtains the URL of the first model from the ADRF, and then obtains the first model through the URL. The above situations can all be understood as the first AnLF obtaining the first model from the first MTLF. Alternatively, it can be understood as the first AnLF obtaining information about the first model from the first MTLF.

[0169] It can be understood that the first AnLF obtains the first model from the first MTLF. Alternatively, it can be understood that the first AnLF obtains information of the first model from the first MTLF.

[0170] It can also be understood that the first AnLF obtains information of the first model for analysis from the first MTLF. Alternatively, it can be understood that the first AnLF obtains the first model for analysis from the first MTLF, or alternatively, it can be understood that the first AnLF obtains the first model and / or information of the first model for analyzing the analysis service corresponding to the analysis identifier.

[0171] It can also be understood that the first AnLF obtains the first model from the first MTLF, and uses the first model to provide a service corresponding to the analysis identifier.

[0172] Step 305: The first AnLF sends an analysis context identifier, for example, subscription correlation ID2, to the service consumption network element.

[0173] The analysis subscription association corresponding to the analysis context identifier and the analysis identifier is used to identify the analysis subscription between the first AnLF and the service consumption network element. In addition, the first AnLF stores the corresponding relationship (or association relationship) between the analysis context identifier and at least one of the identifier of the first model, the subscription association identifier, the first information, and the identifier of the first MTLF.

[0174] Step 306: The service consuming network element determines and selects the target AnLF.

[0175] Exemplarily, the service consuming network element may determine to select the target AnLF according to internal logic or external trigger conditions. For example, the service consuming network element starts to request related analysis, or receives a stop subscription request for an existing analysis, and then selects a new AnLF to continue serving it.

[0176] In a possible implementation manner, the service consuming network element may determine the target AnLF through a network element discovery process.

[0177] Exemplarily, the service consumption network element sends an NF discovery message 2 to the NRF. The NF discovery message 2 is used to discover the AnLF, or to discover the NWDAF of the contained AnLF. The NRF determines one or more AnLFs according to the NF discovery message 2. The NRF sends an NF discovery response message 2 to the service consumption network element. The NF discovery response message 2 includes information about the one or more AnLFs. The service consumption network element determines the target AnLF according to the information about the one or more AnLFs. The following is only described by taking the target AnLF as the second AnLF as an example, and the second AnLF is one of the one or more AnLFs.

[0178] Step 307: The service consumption network element sends a second analysis subscription message to the second AnLF, wherein the second analysis subscription message includes an analysis identifier.

[0179] Exemplarily, the second analysis subscription message further includes analysis subscription information, wherein the analysis subscription information includes at least one of an identifier of the first AnLF, a SUPI, analysis filter information of UE-related analysis, and an analysis context identifier.

[0180] Step 308: The second AnLF sends an analysis context transfer request to the first AnLF.

[0181] Exemplarily, the second AnLF determines the first AnLF according to the analysis subscription information, and the analysis context transfer request includes an analysis context identifier.

[0182] Step 309: The first AnLF sends an analysis context to the second AnLF, where the analysis context includes an identifier of the first model and an identifier of the first MTLF.

[0183] Exemplarily, the analysis context identifier has a corresponding relationship with the identifier of the first model and the identifier of the first MTLF, and the first AnLF determines the analysis context corresponding to the analysis context identifier according to the analysis context identifier, and the analysis context includes the identifier of the first model and the identifier of the first MTLF.

[0184] In a possible implementation, before the first AnLF sends the analysis context to the second AnLF, optionally, the analysis context transfer request also includes the identifier of the manufacturer of the second AnLF, and then, the first AnLF can judge whether the identifier of the manufacturer of the second AnLF belongs to the first interoperability identifier according to the first interoperability identifier, or it can be described as judging whether the first interoperability identifier includes the identifier of the manufacturer of the second AnLF, that is, from the above, it can be seen that the first interoperability identifier includes a list of manufacturer identifiers, and the first AnLF judges whether the identifier of the manufacturer of the second AnLF belongs to the list of manufacturer identifiers. Among them, the first AnLF can obtain the first interoperability identifier from the first MTLF (refer to step 303) or from the NRF (refer to step 302). In a possible implementation, before the first AnLF sends the analysis context to the second AnLF, the first AnLF can also send a first request message to the first MTLF, and the first request message is used to request the first MTLF to agree that the first AnLF provides the identifier of the first model for the second AnLF. Then, the first MTLF sends a first response message to the first AnLF, and the first response message indicates whether it agrees that the first AnLF provides the identifier of the first model for the second AnLF. Exemplarily, if the first MTLF agrees that the first AnLF provides the second AnLF with an identifier of the first model, a first response message is sent to the first AnLF, and the first response message indicates that the first AnLF agrees to provide the second AnLF with an identifier of the first model. If the first MTLF disagrees that the first AnLF provides the second AnLF with an identifier of the first model, a first response message is sent to the first AnLF, and the first response message indicates that the first AnLF does not agree to provide the second AnLF with an identifier of the first model. The present application does not limit the specific method of how the first MTLF determines whether to agree that the first AnLF provides the second AnLF with an identifier of the first model.

[0185] The first request message may also be described as an identifier for requesting to allow the first AnLF to provide the second AnLF with the first model, or an identifier for requesting to authorize the first AnLF to provide the second AnLF with the first model.

[0186] Exemplarily, the first request message may include at least one of a subscription association identifier, an identifier of the first model, an identifier of the second AnLF, or an identifier of the manufacturer of the second AnLF. If the first request message includes the identifier of the manufacturer of the second AnLF, the first MTLF may determine whether the identifier of the manufacturer of the second AnLF belongs to the first interoperability identifier, and if the identifier of the manufacturer of the second AnLF belongs to the first interoperability identifier, the first AnLF is allowed to provide the identifier of the first model to the second AnLF, otherwise, the first AnLF is not allowed to provide the identifier of the first model to the second AnLF.

[0187] Step 310: The second AnLF sends the identifier of the first model to the first MTLF.

[0188] Exemplarily, the second AnLF sends a model provision subscription message to the first MTLF, where the model provision subscription includes an identifier of the first model.

[0189] Step 311: The first MTLF determines first information according to the identifier of the first model.

[0190] Step 312: The first MTLF sends first information to the second AnLF.

[0191] Step 313: The second AnLF obtains the first model according to the first information.

[0192] Steps 308 to 313 may refer to the above-mentioned steps 200 to 250 and will not be described in detail here.

[0193] like Figure 4 As shown, the process in which the first AnLF determines to select the target AnLF and triggers the target AnLF to send an analysis context transfer request to the first AnLF is specifically as follows:

[0194] Steps 401 to 405 may refer to the above-mentioned steps 301 to 305 .

[0195] Step 406: The first AnLF determines that a target AnLF needs to be selected.

[0196] For example, if the first AnLF determines that it is in an overload state, or is close to or exceeds the service uptime according to the network element state, or the first AnLF is ready to shut down and stop providing external services, the first AnLF determines to select a target AnLF.

[0197] In a possible implementation manner, the first AnLF may determine the target AnLF through a network element discovery process.

[0198] Exemplarily, the first AnLF sends an NF discovery message 2 to the NRF. The NF discovery message 2 is used to discover the AnLF, or to discover the NWDAF of the included AnLF. The NRF determines one or more AnLFs according to the NF discovery message 2. The NRF sends an NF discovery response message 2 to the first AnLF. The NF discovery response message 2 includes information of one or more AnLFs. The first AnLF determines the target AnLF according to the information of one or more AnLFs. The following is only described by taking the target AnLF as the second AnLF as an example, and the second AnLF is one of the one or more AnLFs.

[0199] Step 407: The first AnLF sends an analysis subscription transfer request to the second AnLF.

[0200] Exemplarily, the analysis subscription transfer request includes analysis subscription information, wherein the analysis subscription information includes at least one of an identifier of the first AnLF, a SUPI, analysis filter information of UE-related analysis, and an analysis context identifier.

[0201] Steps 408 to 413 may refer to the above-mentioned steps 308 to 313 .

[0202] By the above Figure 3 and Figure 4 As shown, the service consumption network element or the first AnLF can determine the selected target AnLF, thereby triggering the target AnLF to send an analysis context transfer request to the first AnLF. The following embodiments are only described by taking the example of the service consumption network element determining the selected target AnLF and then triggering the second AnLF to send an analysis context transfer request to the first AnLF. It can be understood that the following embodiments are also applicable to the scenario in which the first AnLF determines the selected target AnLF and then triggers the second AnLF to send an analysis context transfer request to the first AnLF.

[0203] The present application also provides a communication method, such as Figure 5 As shown, the method includes:

[0204] Steps 501 to 507 refer to the above-mentioned steps 301 to 307 .

[0205] Step 508: The second AnLF sends an analysis context transfer request to the first AnLF.

[0206] Exemplarily, the analysis context transfer request includes an analysis context identifier.

[0207] Step 509: the first AnLF sends a second request message to the first MTLF, where the second request message is used to request the MTLF to agree that the first AnLF provides the first information to the second AnLF.

[0208] The second request message may also be described as being used to request permission for the first AnLF to provide the first information to the second AnLF, or to request authorization for the first AnLF to provide the first information to the second AnLF.

[0209] Alternatively, the second request message may also be described as being used to request the MTLF to agree that the first AnLF provides the first model for the second AnLF, to request permission for the first AnLF to provide the first model for the second AnLF, or to request authorization for the first AnLF to provide the first model for the second AnLF.

[0210] Exemplarily, the analysis context identifier has a corresponding relationship with the identifier of the first model, the identifier of the first MTLF and the first information. The first AnLF determines the identifier of the first model and the identifier of the first MTLF corresponding to the analysis context identifier according to the analysis context identifier, and determines that the analysis context corresponding to the analysis context identifier includes the first information. The first information is associated with the first model. The first information may include an ML model file address (for example, a URL or FQDN), or an ADRFID or ADRF set D. When the ML model information includes an ADRFID or ADRF set ID, the first information may also include a storage transaction identifier. Optionally, the first information may include an identifier of the first model. The first information may also include other content, which is not limited in this application. It can be understood that part of the content included in the first information can be used to obtain the first model, and the first information also includes other content, for example, related information used to describe the first model.

[0211] It can also be understood that the first AnLF does not directly provide the first information to the second AnLF, or it can be understood that before the first AnLF sends the first information to the second AnLF, it needs to obtain permission or authorization from the first MTLF.

[0212] Exemplarily, the second request message may include at least one of a subscription association identifier, an identifier of the first model, an identifier of the second AnLF, or an identifier of a manufacturer of the second AnLF.

[0213] Step 510: The first MTLF sends a second response message to the first AnLF, where the first response message indicates that the first AnLF agrees to provide the first information to the second AnLF.

[0214] Exemplarily, if the first MTLF agrees that the first AnLF provides the first information to the second AnLF, a second response message is sent to the first AnLF, and the second response message indicates that it agrees that the first AnLF provides the first information to the second AnLF. If the first MTLF disagrees that the first AnLF provides the first information to the second AnLF, the second response message indicates that it disagrees that the first AnLF provides the first information to the second AnLF. This application does not limit how the first MTLF determines whether it agrees that the first AnLF provides the first information to the second AnLF. The following is only explained by taking the second response message indicating that it agrees that the first AnLF provides the first information to the second AnLF as an example.

[0215] Step 511: The first AnLF sends an analysis context to the second AnLF, wherein the analysis context includes the first information and / or the model file of the first model.

[0216] Optionally, step 512: the second AnLF obtains the first model according to the first information.

[0217] By adopting the above method, the first MTLF authorizes the first AnLF to provide the first information, and then the analysis context sent by the first AnLF to the second AnLF may include the first information, so that the second AnLF can obtain the model used by the first AnLF network element and the security of model acquisition can be improved.

[0218] The present application also provides a communication method, such as Figure 6 As shown, the method includes:

[0219] Steps 601 to 607 refer to the above-mentioned steps 301 to 307 .

[0220] Step 608: The second AnLF sends an analysis context transfer request to the first AnLF.

[0221] Exemplarily, the analysis context transfer request includes an analysis context identifier.

[0222] Step 609: The first AnLF sends an analysis context to the second AnLF, wherein the analysis context includes an association identifier and an identifier of the first MTLF, wherein the association identifier at this time is a subscription association identifier.

[0223] Exemplarily, the analysis context identifier has a corresponding relationship with the subscription association identifier and the identifier of the first MTLF, and the first AnLF determines the analysis context corresponding to the analysis context identifier according to the analysis context identifier. The analysis context includes the subscription association identifier and the identifier of the first MTLF.

[0224] In combination with the above step 305, it can be known that the first AnLF stores the correspondence between the analysis context identifier and the subscription association identifier, so the subscription association identifier can be determined according to the analysis context identifier.

[0225] Step 610: The second AnLF sends a subscription association identifier to the first MTLF.

[0226] Step 611: The first MTLF determines first information according to the subscription association identifier.

[0227] It can be known from the above step 303 that the first MTLF stores the corresponding relationship between the subscription association identifier and the first information. Therefore, the first MTLF can determine the first information according to the subscription association identifier.

[0228] Step 612: The first MTLF sends the first information to the second AnLF.

[0229] Step 613: The second AnLF obtains the first model according to the first information.

[0230] By adopting the above method, the second AnLF obtains the subscription association identifier and the identifier of the first MTLF by analyzing the context, instead of directly obtaining the first information. The second AnLF can obtain the first information from the first MTLF based on the subscription association identifier and the information of the first MTLF, so that the second AnLF can obtain the model used by the first AnLF network element and the security of model acquisition can be improved.

[0231] The present application also provides a communication method, such as Figure 7 As shown, the method includes:

[0232] Steps 701 to 707 refer to the above-mentioned steps 301 to 307 .

[0233] Step 708: The second AnLF sends an analysis context transfer request to the first AnLF.

[0234] Exemplarily, the analysis context transfer request includes an analysis context identifier.

[0235] Step 709: the first AnLF sends a third request message to the first MTLF, where the third request message includes the identifier of the first model.

[0236] The third request message is used to request the first MTLF to allocate an identifier associated with the first model.

[0237] Exemplarily, the analysis context identifier has a corresponding relationship with the identifier of the first model and the identifier of the first MTLF, and the first AnLF determines the identifier of the first model and the identifier of the first MTLF corresponding to the analysis context identifier according to the analysis context identifier.

[0238] Step 710: The first MTLF sends a third response message to the first AnLF.

[0239] Exemplarily, the first MTLF generates an association identifier for the first information, and saves a corresponding relationship between the association identifier and the first information.

[0240] The third response message includes an association identifier and an identifier of the first MTLF. The association identifier at this time is an association identifier associated with the first information, which can also be called a model association identifier or a model information association identifier. The following is an example of a model association identifier.

[0241] Step 711: The first AnLF sends an analysis context to the second AnLF, wherein the analysis context includes a model association identifier and an identifier of the first MTLF.

[0242] Step 712: The second AnLF sends the model association identifier to the first MTLF.

[0243] Step 713: The first MTLF determines the first information according to the model association identifier.

[0244] It can be known from the above step 710 that the first MTLF stores the corresponding relationship between the model association identifier and the first model, so the first MTLF can determine the first information according to the model association identifier.

[0245] Step 714: The first MTLF sends the first information to the second AnLF.

[0246] Step 715: The second AnLF obtains the first model according to the first information.

[0247] By adopting the above method, the second AnLF obtains the model association identifier and the identifier of the first MTLF by analyzing the context, instead of directly obtaining the first information. The second AnLF can obtain the first information from the first MTLF based on the model association identifier and the information of the first MTLF, so that the second AnLF can obtain the model used by the first AnLF network element and improve the security of model acquisition.

[0248] The present application also provides a communication method, such as Figure 8 As shown, the method includes:

[0249] Steps 801 to 807 refer to the above-mentioned steps 301 to 307 .

[0250] Step 808: The second AnLF sends an analysis context transfer request to the first AnLF.

[0251] Exemplarily, the analysis context transfer request includes an analysis context identifier and a model receiving address.

[0252] Step 809: the first AnLF sends a fourth request message to the first MTLF, where the fourth request message includes a model receiving address and an identifier of the first model.

[0253] Exemplarily, the analysis context identifier has a corresponding relationship with the identifier of the first model and the identifier of the first MTLF, and the first AnLF determines the identifier of the first model and the identifier of the first MTLF corresponding to the analysis context identifier according to the analysis context identifier.

[0254] The fourth request message is used to request the first MTLF to provide the first information according to the model receiving address.

[0255] Step 810: The model training function network element determines first information according to the identifier of the first model.

[0256] Step 811: The first MTLF provides first information according to the model receiving address.

[0257] Step 812: The second analysis function network element obtains the first information according to the model receiving address.

[0258] Step 813: The second analysis function network element obtains the first model according to the first information.

[0259] By adopting the above method, the second AnLF provides a model receiving address, and the first MTLF provides the first information according to the model receiving address, so that the second AnLF can obtain the model used by the first AnLF network element and the security of model acquisition can be improved.

[0260] It is understandable that in order to realize the functions in the above-mentioned embodiments, the first analysis function network element, the model training function network element and the second analysis function network element include hardware structures and / or software modules corresponding to the execution of each function. Those skilled in the art should easily realize that, in combination with the units and method steps of each example described in the embodiments disclosed in this application, the present application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a function is executed in the form of hardware or computer software driving hardware depends on the specific application scenario and design constraints of the technical solution.

[0261] Fig. 9 and Fig.10 A schematic diagram of the structure of possible communication devices provided for embodiments of the present application. These communication devices can be used to implement the functions of the first analysis function network element, the model training function network element or the second analysis function network element in the above method embodiments, and thus can also achieve the beneficial effects possessed by the above method embodiments.

[0262] like Fig. 9 As shown, the communication device 900 includes a processing unit 910 and a transceiver unit 920. The communication device 1000 is used to implement the functions of the first analysis function network element, the model training function network element or the second analysis function network element in the above method embodiment.

[0263] When the communication device 900 is used to implement the function of the first analysis function network element in the above method embodiment:

[0264] The processing unit 910 calls the transceiver unit 920 to execute: receiving an analysis context transfer request from the second analysis function network element; sending an analysis context to the second analysis function network element, wherein the analysis context includes an identifier of the first model and an identifier of the model training function network element.

[0265] In a possible implementation, the transceiver unit 920 is used to receive first information from the model training function network element, where the first information is associated with the first model.

[0266] In a possible implementation, the first information includes an identifier of the model training function network element.

[0267] In one possible implementation, before receiving an analysis context transfer request from a second analysis function network element, the processing unit 910 is used to use the first model to provide a service corresponding to the analysis identifier; the transceiver unit 920 is used to send an analysis subscription transfer request to the second analysis function network element, and the analysis subscription transfer request includes the analysis identifier.

[0268] In one possible implementation, the analysis context transfer request includes the identifier of the manufacturer of the second analysis function network element; before sending the analysis context to the second analysis function network element, the transceiver unit 920 is used to obtain a first interoperability identifier, where the first interoperability identifier is the interoperability identifier corresponding to the analysis identifier of the model training function network element, or the first interoperability identifier is the interoperability identifier of the model training function network element; the processing unit 910 is used to determine that the first interoperability identifier includes the identifier of the manufacturer of the second analysis function network element.

[0269] In a possible implementation, the transceiver unit 920 is used to obtain the first interoperability identifier from the model training function network element or the network storage function network element.

[0270] In one possible implementation, before receiving an analysis context transfer request from a second analysis function network element, the transceiver unit 920 is used to send a model request message to the model training function network element, wherein the model request message includes the analysis identifier; and receive the identifier of the first model from the model training function network element.

[0271] In one possible implementation, before sending the analysis context to the second analysis function network element, the transceiver unit 920 is used to send a first request message to the model training function network element, wherein the first request message is used to request the model training function network element to agree that the first analysis function network element provides the second analysis function network element with the identifier of the first model; and receive a first response message from the model training function network element, wherein the first response message indicates that the first analysis function network element agrees to provide the second analysis function network element with the identifier of the first model.

[0272] When the communication device 900 is used to implement the function of the second analysis function network element in the above method embodiment:

[0273] The processing unit 910 calls the transceiver unit 920 to execute: sending an analysis context transfer request to the first analysis function network element; receiving an analysis context from the first analysis function network element, the analysis context including an identifier of a first model and an identifier of a model training function network element; sending the identifier of the first model to the model training function network element; receiving first information from the model training function network element, the first information being associated with the first model.

[0274] In a possible implementation, the first information includes an identifier of the model training function network element.

[0275] In a possible implementation, the analysis context transfer request includes an identifier of a manufacturer of the second analysis function network element.

[0276] In one possible implementation, before sending an analysis context transfer request to the first analysis function network element, the transceiver unit 920 is used to receive an analysis subscription transfer request from the first analysis function network element, and the analysis subscription transfer request includes analysis subscription information; the second analysis function network element determines the first analysis function network element based on the analysis subscription information.

[0277] In one possible implementation, before the second analysis function network element sends an analysis context transfer request to the first analysis function network element, the second analysis function network element receives an analysis subscription request from a service consumption network element; the analysis subscription request includes analysis subscription information; and the processing unit 910 is used to determine the first analysis function network element based on the analysis subscription information.

[0278] When the communication device 900 is used to implement the function of the model training function network element in the above method embodiment:

[0279] The transceiver unit 920 is used to receive the identifier of the first model from the second analysis function network element; the processing unit 910 is used to determine the first information based on the identifier of the first model, and the first information is associated with the first model; the transceiver unit 920 is used to send the first information to the second analysis function network element.

[0280] In one possible implementation, before receiving the identifier of the first model from the second analysis function network element, the transceiver unit 920 is used to receive a first request message from the first analysis function network element, wherein the first request message is used to request the model training function network element to agree that the first analysis function network element provides the identifier of the first model to the second analysis function network element; and send a first response message to the first analysis function network element, wherein the first response message indicates that the first analysis function network element agrees to provide the identifier of the first model to the second analysis function network element.

[0281] In a possible implementation, the transceiver unit 920 is used to receive a model request message from the first analysis function network element, where the model request message includes an analysis identifier; and send the identifier of the first model to the first analysis function network element, where the first model is used to provide a service corresponding to the analysis identifier.

[0282] In one possible implementation, the transceiver unit 920 is used to send a first interoperability identifier to the first analysis function network element, where the first interoperability identifier is an interoperability identifier corresponding to the analysis identifier of the model training function network element, or the first interoperability identifier is an interoperability identifier of the model training function network element.

[0283] In a possible implementation, the transceiver unit 920 is used to send first information to the first analysis function network element before receiving the identifier of the first model from the second analysis function network element, where the first information is associated with the first model.

[0284] In a possible implementation, the first information includes an identifier of the model training function network element.

[0285] A more detailed description of the processing unit 910 and the transceiver unit 920 can be directly obtained by referring to the relevant description in the above method embodiment, which will not be repeated here.

[0286] like Fig.10 As shown, the communication device 1000 includes a processor 1010 and an interface circuit 1020. The processor 1010 and the interface circuit 1020 are coupled to each other. It is understood that the interface circuit 1020 can be a transceiver or an input-output interface. Optionally, the communication device 1000 may also include a memory 1030 for storing instructions executed by the processor 1010 or storing input data required by the processor 1010 to execute instructions or storing data generated after the processor 1010 executes instructions.

[0287] When the communication device 1000 is used to implement Figure 5 When the method is shown, the processor 1010 is used to implement the functions of the processing unit 910, and the interface circuit 1020 is used to implement the functions of the transceiver unit 920.

[0288] It is understandable that the processor in the embodiments of the present application may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field programmable gate arrays (FPGA) or other programmable logic devices, transistor logic devices, hardware components or any combination thereof. The general-purpose processor may be a microprocessor or any conventional processor.

[0289] In the present application, another example of a device is provided, the notification device includes at least one processor and at least one memory, the at least one processor is coupled to the at least one memory, the at least one memory is used to store instructions, when the instructions are executed by the at least one processor, the communication device executes the method in the above embodiment. Take the communication device including a processor and a memory as an example, Fig.10 As shown, the communication device 1000 includes a processor 1010 and a memory 1030. The processor 1010 and the memory 1030 are coupled, and the memory 1030 stores instructions. When the instructions stored in the memory 1030 are executed by the processor 1010, the communication device 1000 executes the method executed by each network element in the above embodiment.

[0290] The method steps in the embodiments of the present application can be implemented in hardware or in software instructions that can be executed by a processor. The software instructions can be composed of corresponding software modules, and the software modules can be stored in random access memory, flash memory, read-only memory, programmable read-only memory, erasable programmable read-only memory, electrically erasable programmable read-only memory, registers, hard disks, mobile hard disks, CD-ROMs, or any other form of storage medium known in the art. An exemplary storage medium is coupled to the processor so that the processor can read information from the storage medium and write information to the storage medium. The storage medium can also be a component of the processor. The processor and the storage medium can be located in an ASIC. In addition, the ASIC can be located in the above-mentioned network element. The processor and the storage medium can also exist in the above-mentioned network element as discrete components.

[0291] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented by software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer programs or instructions. When the computer program or instruction is loaded and executed on a computer, the process or function described in the embodiment of the present application is executed in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, a network device, a user device or other programmable device. The computer program or instruction may be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer program or instruction may be transmitted from one website site, computer, server or data center to another website site, computer, server or data center by wired or wireless means. The computer-readable storage medium may be any available medium that a computer can access or a data storage device such as a server, data center, etc. that integrates one or more available media. The available medium may be a magnetic medium, for example, a floppy disk, a hard disk, a tape; it may also be an optical medium, for example, a digital video disc; it may also be a semiconductor medium, for example, a solid-state hard disk. The computer-readable storage medium may be a volatile or nonvolatile storage medium, or may include both volatile and nonvolatile types of storage media.

[0292] In the various embodiments of the present application, unless otherwise specified or provided in a logical conflict, the terms and / or descriptions between the different embodiments are consistent and may be referenced to each other, and the technical features in the different embodiments may be combined to form new embodiments according to their inherent logical relationships.

[0293] In the present application, "at least one" means one or more, and "more than one" means two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone, where A and B can be singular or plural. In the text description of the present application, the character " / " generally indicates that the previous and next associated objects are in an "or" relationship; in the formula of the present application, the character " / " indicates that the previous and next associated objects are in a "division" relationship. "Including at least one of A, B and C" can mean: including A; including B; including C; including A and B; including A and C; including B and C; including A, B and C.

[0294] It is understood that the various numbers involved in the embodiments of the present application are only for the convenience of description and are not used to limit the scope of the embodiments of the present application. The size of the sequence number of the above-mentioned processes does not mean the order of execution, and the execution order of each process should be determined by its function and internal logic.

Claims

1. A communication method, characterized in that: The method includes: The first analysis function network element receives an analysis context transfer request from the second analysis function network element; The first analysis function network element sends an analysis context to the second analysis function network element, where the analysis context includes an identifier of the first model and an identifier of the model training function network element.

2. The method according to claim 1, characterized in that Also includes: The first analysis function network element receives first information from the model training function network element, where the first information is associated with the first model.

3. The method according to claim 2, characterized in that The first information includes an identifier of the model training function network element.

4. The method according to any one of claims 1 to 3, characterized in that: Before the first analysis function network element receives the analysis context transfer request from the second analysis function network element, the method further includes: The first analysis function network element provides a service corresponding to the analysis identifier using the first model; The first analysis function network element sends an analysis subscription transfer request to the second analysis function network element, where the analysis subscription transfer request includes the analysis identifier.

5. The method according to claim 4, characterized in that The analysis context transfer request includes an identifier of a manufacturer of the second analysis function network element; Before the first analysis function network element sends the analysis context to the second analysis function network element, the method further includes: The first analysis function network element obtains a first interoperability identifier, where the first interoperability identifier is an interoperability identifier corresponding to the analysis identifier of the model training function network element, or the first interoperability identifier is an interoperability identifier of the model training function network element; The first analysis function network element determines that the first interoperability identifier includes the identifier of the manufacturer of the second analysis function network element.

6. The method according to claim 5, characterized in that The first analysis function network element obtains the first interoperability identifier, including: The first analysis function network element obtains the first interoperability identifier from the model training function network element or the network storage function network element.

7. The method according to any one of claims 4 to 5, characterized in that: Before the first analysis function network element receives the analysis context transfer request from the second analysis function network element, the method further includes: The first analysis function network element sends a model request message to the model training function network element, where the model request message includes the analysis identifier; The first analysis function network element receives an identifier of the first model from the model training function network element.

8. The method according to any one of claims 1 to 7, characterized in that: Before the first analysis function network element sends the analysis context to the second analysis function network element, the method further includes: The first analysis function network element sends a first request message to the model training function network element, where the first request message is used to request the model training function network element to agree that the first analysis function network element provides the second analysis function network element with an identifier of the first model; The first analysis function network element receives a first response message from the model training function network element, and the first response message indicates that the first analysis function network element agrees to provide the identifier of the first model to the second analysis function network element.

9. A communication method, characterized in that: The method includes: The second analysis function network element sends an analysis context transfer request to the first analysis function network element; The second analysis function network element receives an analysis context from the first analysis function network element, where the analysis context includes an identifier of the first model and an identifier of the model training function network element; The second analysis function network element sends the identifier of the first model to the model training function network element; The second analysis function network element receives first information from the model training function network element, where the first information is associated with the first model.

10. The method according to claim 9, characterized in that The first information includes an identifier of the model training function network element.

11. The method according to claim 9 or 10, characterized in that The analysis context transfer request includes an identifier of a manufacturer of the second analysis function network element.

12. The method according to any one of claims 9 to 11, characterized in that: Before the second analysis function network element sends the analysis context transfer request to the first analysis function network element, the method further includes: The second analysis function network element receives an analysis subscription transfer request from the first analysis function network element, wherein the analysis subscription transfer request includes analysis subscription information; The second analysis function network element determines the first analysis function network element according to the analysis subscription information.

13. The method according to any one of claims 9 to 11, characterized in that: Before the second analysis function network element sends the analysis context transfer request to the first analysis function network element, the method further includes: The second analysis function network element receives an analysis subscription request from a service consumption network element; the analysis subscription request includes analysis subscription information; The second analysis function network element determines the first analysis function network element according to the analysis subscription information.

14. A communication method, characterized in that: The method includes: The model training function network element receives the identifier of the first model from the second analysis function network element; The model training function network element determines first information according to the identifier of the first model, where the first information is associated with the first model; The model training function network element sends the first information to the second analysis function network element.

15. The method according to claim 14, characterized in that Before the model training function network element receives the identifier of the first model from the second analysis function network element, the method further includes: The model training function network element receives a first request message from the first analysis function network element, where the first request message is used to request the model training function network element to agree that the first analysis function network element provides the second analysis function network element with an identifier of the first model; The model training function network element sends a first response message to the first analysis function network element, and the first response message indicates that it agrees with the first analysis function network element to provide the identifier of the first model to the second analysis function network element.

16. The method according to claim 14 or 15, characterized in that Also includes: The model training function network element receives a model request message from the first analysis function network element, where the model request message includes an analysis identifier; The model training function network element sends the identifier of the first model to the first analysis function network element, and the first model is used to provide a service corresponding to the analysis identifier.

17. The method according to any one of claims 14 to 16, characterized in that: Before the model training function network element receives the identifier of the first model from the second analysis function network element, the method further includes: The model training function network element sends a first interoperability identifier to the first analysis function network element, where the first interoperability identifier is the interoperability identifier corresponding to the analysis identifier of the model training function network element, or the first interoperability identifier is the interoperability identifier of the model training function network element.

18. The method according to any one of claims 14 to 17, characterized in that: Before the model training function network element receives the identifier of the first model from the second analysis function network element, the method further includes: The model training function network element sends the first information to the first analysis function network element, where the first information is associated with the first model.

19. The method according to any one of claims 14 to 18, characterized in that: The first information includes an identifier of the model training function network element.

20. A communication device, characterized in that: The method comprises a unit or a module for executing the method according to any one of claims 1 to 19.

21. A communication device, characterized in that: The communication device comprises at least one processor; the at least one processor is configured to execute the method according to any one of claims 1 to 19.

22. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a program, and when the program is run on a device, the device is caused to perform the method according to any one of claims 1 to 19.

23. A computer program product, characterized in that The computer program product comprises a program or instructions, and when the program or instructions are executed by a device, the device is caused to perform the method according to any one of claims 1 to 19.

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