Information transmission method and device, terminal and network side equipment

Abstract

The invention discloses an information transmission method and device, a terminal and network side equipment, and belongs to the technical field of communication, and the information transmission method comprises the steps that the terminal receives a first message sent by the network side equipment; wherein the first message comprises related information of an artificial intelligence (AI) model, and the related information of the AI model comprises at least one of the following items: identification information of the AI model; file information of the AI model; attribute information of the AI model; and a download address of the AI model.

Description

Technical Field

[0001] This application belongs to the field of communication technologies, and particularly relates to an information transmission method, apparatus, terminal, and network-side device. Background Art

[0002] Currently, in a mobile communication network, tasks can be executed or services can be provided based on Artificial Intelligence (AI). For example, a terminal can perform Channel State Information (CSI) prediction, positioning, etc. based on a pre-trained AI model. In actual situations, the training and generation of an AI model may be located on the 3rd Generation Partnership Project (3GPP) network side, Over The Top (OTT) server side, etc., while the inference based on the AI model is located on the terminal side. Therefore, it is necessary to transfer the AI model from the training party to the terminal. However, in the prior art, there is no corresponding solution for how the network transfers the AI model to the terminal. Summary of the Invention

[0003] Embodiments of this application provide an information transmission method, apparatus, terminal, and network-side device, capable of providing a way for the network side to transfer an AI model to the terminal.

[0004] In a first aspect, an information transmission method is provided. The method includes:

[0005] The terminal receives a first message sent by a network-side device;

[0006] Wherein, the first message includes information related to an Artificial Intelligence (AI) model, and the information related to the AI model includes at least one of the following:

[0007] Identification information of the AI model;

[0008] File information of the AI model;

[0009] Attribute information of the AI model;

[0010] Download address of the AI model.

[0011] In a second aspect, an information transmission apparatus is provided. The apparatus includes:

[0012] A first receiving module, configured to receive a first message sent by a network-side device;

[0013] Wherein, the first message includes information related to an Artificial Intelligence (AI) model, and the information related to the AI model includes at least one of the following:

[0014] Identification information of the AI model;

[0015] File information of the AI model;

[0016] Attribute information of the AI model;

[0017] Download address of the AI model.

[0018] Thirdly, an information transmission method is provided, and the method includes:

[0019] A first network element sends a first message to a terminal;

[0020] Wherein, the first message includes information related to an artificial intelligence (AI) model, and the information related to the AI model includes at least one of the following:

[0021] Identification information of the AI model;

[0022] File information of the AI model;

[0023] Attribute information of the AI model;

[0024] Download address information of the AI model.

[0025] Fourthly, an information transmission device is provided, and the device includes:

[0026] A second sending module, configured to send a first message to a terminal;

[0027] Wherein, the first message includes information related to an artificial intelligence (AI) model, and the information related to the AI model includes at least one of the following:

[0028] Identification information of the AI model;

[0029] File information of the AI model;

[0030] Attribute information of the AI model;

[0031] Download address information of the AI model.

[0032] Fifthly, an information transmission method is provided, and the method includes:

[0033] A second network element receives a second request message sent by a first network element, wherein the second request message is used to request to obtain an AI model;

[0034] The second network element sends a second response message to the first network element, wherein the second response message includes at least one of the following: an indication of whether to accept the AI model acquisition request, information related to the AI model.

[0035] Sixthly, an information transmission device is provided, and the device includes:

[0036] A fourth receiving module, configured to receive a second request message sent by a first network element, where the second request message is used to request to obtain an AI model.

[0037] A fourth sending module, configured to send a second response message to the first network element, where the second response message includes at least one of the following: an indication of whether to accept the AI model acquisition request, and relevant information of the AI model.

[0038] In a seventh aspect, a terminal is provided, which includes a processor and a memory. The memory stores a program or instruction that can run on the processor. When the program or instruction is executed by the processor, the steps of the method described in the first aspect are implemented.

[0039] In an eighth aspect, a terminal is provided, which includes a processor and a communication interface. The communication interface is configured to receive a first message sent by a network-side device. The first message includes relevant information of an artificial intelligence (AI) model. The relevant information of the AI model includes at least one of the following: identification information of the AI model; file information of the AI model; attribute information of the AI model; download address of the AI model.

[0040] In a ninth aspect, a network-side device is provided, which includes a processor and a memory. The memory stores a program or instruction that can run on the processor. When the program or instruction is executed by the processor, the steps of the method described in the third aspect are implemented.

[0041] In a tenth aspect, a network-side device is provided, which includes a processor and a communication interface. The communication interface is configured to send a first message to a terminal. The first message includes relevant information of an artificial intelligence (AI) model. The relevant information of the AI model includes at least one of the following: identification information of the AI model; file information of the AI model; attribute information of the AI model; download address information of the AI model.

[0042] In an eleventh aspect, a network-side device is provided, which includes a processor and a memory. The memory stores a program or instruction that can run on the processor. When the program or instruction is executed by the processor, the steps of the method described in the fifth aspect are implemented.

[0043] In a twelfth aspect, a network-side device is provided, which includes a processor and a communication interface. The communication interface is configured to receive a second request message sent by a first network element, where the second request message is used to request to obtain an AI model; and send a second response message to the first network element, where the second response message includes at least one of the following: an indication of whether to accept the AI model acquisition request, and relevant information of the AI model.

[0044] In a thirteenth aspect, an information transmission system is provided, including: a terminal and a network-side device. The terminal can be used to execute the steps of the information transmission method described in the first aspect, and the network-side device can be used to execute the steps of the information transmission method described in the third aspect or the information transmission method described in the fifth aspect.

[0045] In a fourteenth aspect, a readable storage medium is provided. Programs or instructions are stored on the readable storage medium, and when the programs or instructions are executed by a processor, the steps of the method described in the first aspect are implemented, or the steps of the method described in the third aspect are implemented, or the steps of the method described in the fifth aspect are implemented.

[0046] In a fifteenth aspect, a chip is provided. The chip includes a processor and a communication interface, and the communication interface is coupled to the processor. The processor is used to run programs or instructions to implement the steps of the method described in the first aspect, or the steps of the method described in the third aspect, or the steps of the method described in the fifth aspect.

[0047] In a sixteenth aspect, a computer program / program product is provided. The computer program / program product is stored in a storage medium, and the computer program / program product is executed by at least one processor to implement the steps of the method described in the first aspect, or the steps of the method described in the third aspect, or the steps of the method described in the fifth aspect.

[0048] In an embodiment of the present application, the terminal receives a first message sent by the network-side device; wherein, the first message includes information related to an artificial intelligence (AI) model, and the information related to the AI model includes at least one of the following: identification information of the AI model; file information of the AI model; attribute information of the AI model; download address of the AI model. That is, in an embodiment of the present application, the network-side passes at least one of the identification information of the AI model, the file information of the AI model, the attribute information of the AI model, and the download address of the AI model to the terminal through the first message, providing a way for the network-side to transfer the AI model to the terminal. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 is a block diagram of a wireless communication system to which an embodiment of the present application can be applied;

[0050] Figure 2a is one of the schematic diagrams of AI positioning provided by an embodiment of the present application;

[0051] Figure 2b is another schematic diagram of AI positioning provided by an embodiment of the present application;

[0052] Figure 2cIt is the third schematic diagram of AI positioning provided by an embodiment of the present application;

[0053] Figure 2d It is the fourth schematic diagram of AI positioning provided by an embodiment of the present application;

[0054] Figure 2e It is the fifth schematic diagram of AI positioning provided by an embodiment of the present application;

[0055] Figure 3 It is the flowchart of a method for information transmission provided by an embodiment of the present application;

[0056] Figure 4 It is the flowchart of another method for information transmission provided by an embodiment of the present application;

[0057] Figure 5 It is the flowchart of yet another method for information transmission provided by an embodiment of the present application;

[0058] Figure 6a It is the flowchart of yet another method for information transmission provided by an embodiment of the present application;

[0059] Figure 6b It is the flowchart of yet another method for information transmission provided by an embodiment of the present application;

[0060] Figure 7 It is the structural diagram of an information transmission device provided by an embodiment of the present application;

[0061] Figure 8 It is the structural diagram of another information transmission device provided by an embodiment of the present application;

[0062] Figure 9 It is the structural diagram of yet another information transmission device provided by an embodiment of the present application;

[0063] Figure 10 It is the structural diagram of a communication device provided by an embodiment of the present application;

[0064] Figure 11 It is the structural diagram of a terminal provided by an embodiment of the present application;

[0065] Figure 12 It is the structural diagram of a network-side device provided by an embodiment of the present application. Detailed implementation manners

[0066] Next, the technical solutions in the embodiments of the present application will be clearly described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art belong to the scope of protection of the present application.

[0067] The terms "first", "second", etc. in this application are used to distinguish similar objects, rather than to describe a specific order or sequence. It should be understood that such terms can be interchanged under appropriate circumstances so that the embodiments of this application can be implemented in an order other than those illustrated or described herein, and the objects distinguished by "first" and "second" are generally of the same type, and do not limit the number of objects. For example, the first object can be one or multiple. In addition, "or" in this application means at least one of the connected objects. For example, "A or B" covers three scenarios, namely, Scenario 1: including A and not including B; Scenario 2: including B and not including A; Scenario 3: including both A and B. The character " / " generally indicates that the associated objects before and after are in an "or" relationship.

[0068] The term "indication" in this application can be either a direct indication (or an explicit indication) or an indirect indication (or an implicit indication). Among them, a direct indication can be understood as that the sender clearly informs the receiver of specific information, operations to be performed, or request results, etc. in the sent indication; an indirect indication can be understood as that the receiver determines the corresponding information based on the indication sent by the sender, or makes a judgment and determines the operations to be performed or request results, etc. according to the judgment result.

[0069] It is worth noting that the technology described in the embodiments of this application is not limited to the Long Term Evolution (LTE) / LTE-Advanced (LTE-A) system, but can also be used in other wireless communication systems, such as Code Division Multiple Access (CDMA), Time Division Multiple Access (TDMA), Frequency Division Multiple Access (FDMA), Orthogonal Frequency Division Multiple Access (OFDMA), Single-carrier Frequency-Division Multiple Access (SC-FDMA), or other systems. The terms "system" and "network" in the embodiments of this application are often used interchangeably, and the described technology can be used not only in the systems and radio technologies mentioned above, but also in other systems and radio technologies. The following description describes the New Radio (NR) system for example purposes, and the NR terms are used in most of the following descriptions, but these technologies can also be applied to systems other than the NR system, such as the 6th generation (6 thGeneration, 6G) communication system.

[0070] Figure 1A block diagram of a wireless communication system to which embodiments of the present application can be applied is shown. The wireless communication system includes a terminal 11 and a network-side device 12. Among them, the terminal 11 can be a mobile phone, a tablet personal computer, a laptop computer, a notebook computer, a personal digital assistant (PDA), a handheld computer, a netbook, an ultra-mobile personal computer (UMPC), a mobile internet device (MID), an augmented reality (AR), a virtual reality (VR) device, a robot, a wearable device, a flight vehicle, a vehicle user equipment (VUE), a shipborne device, a pedestrian user equipment (PUE), a smart home (home devices with wireless communication functions, such as refrigerators, TVs, washing machines, or furniture, etc.), a game console, a personal computer (PC), a teller machine, or a self-service machine, etc. Wearable devices include: smart watches, smart bracelets, smart earphones, smart glasses, smart jewelry (smart bracelets, smart bracelets, smart rings, smart necklaces, smart anklets, smart ankle chains, etc.), smart wristbands, smart clothing, etc. Among them, the vehicle user equipment can also be referred to as a vehicle terminal, a vehicle controller, a vehicle module, a vehicle component, a vehicle chip, or a vehicle unit, etc. It should be noted that the specific type of the terminal 11 is not limited in the embodiments of the present application. The network-side device 12 can include an access network device or a core network device. Among them, the access network device can also be referred to as a radio access network (RAN) device, a radio access network function, or a radio access network unit. The access network device can include a base station, a wireless local area network (WLAN) access point (AP), or a wireless fidelity (WiFi) node, etc.Among them, the base station may be referred to as Node B (NB), Evolved Node B (eNB), the next generation Node B (gNB), New Radio Node B (NR Node B), access point, Relay Base Station (RBS), Serving Base Station (SBS), Base Transceiver Station (BTS), radio base station, radio transceiver, Basic Service Set (BSS), Extended Service Set (ESS), home Node B (HNB), home evolved Node B, Transmission Reception Point (TRP), or some other suitable term in the art. As long as the same technical effect is achieved, the base station is not limited to specific technical terms. It should be noted that in the embodiments of this application, only the base station in the NR system is taken as an example for introduction, and the specific type of the base station is not limited.

[0071] The core network device may include, but is not limited to, at least one of the following: core network node, core network function, Mobility Management Entity (MME), Access and Mobility Management Function (AMF), Session Management Function (SMF), User Plane Function (UPF), Policy Control Function (PCF), Policy and Charging Rules Function (PCRF), Edge Application Server Discovery Function (EASDF), Unified Data Management (UDM), Unified Data Repository (UDR), Home Subscriber Server (HSS), Centralized network configuration (CNC), Network Repository Function (NRF), Network Exposure Function (NEF), Local NEF (L-NEF), Binding Support Function (BSF), Application Function (AF), etc. It should be noted that in the embodiments of this application, only the core network devices in the NR system are taken as examples for introduction, and the specific types of core network devices are not limited.

[0072] For ease of understanding, some content related to the embodiments of this application is described below:

[0073] I. AI positioning

[0074] AI positioning aims to use an AI model to predict measurement information, so as to give the position estimate of the target, which can save a large amount of measurement resources and reduce the computing power consumption. Currently, it includes the following five frameworks:

[0075] Case 1: UE-based positioning using the UE-side model, direct AI / Machine Learning (ML) or AI / ML-assisted positioning, such as Figure 2aAs shown;

[0076] Case 2a: UE-assisted / Location Management Function (LMF) positioning using the UE-side model, AI / ML-assisted positioning, such as Figure 2b As shown;

[0077] Case 2b: UE-assisted / LMF positioning using the LMF-side model, direct AI / ML positioning, such as Figure 2c As shown;

[0078] Case 3a: NG-RAN node-assisted positioning using the gNB-side model, AI / ML-assisted positioning, such as Figure 2d As shown;

[0079] Case 3b: NG-RAN node-assisted positioning using the LMF-side model, direct AI / ML positioning, such as Figure 2e As shown.

[0080] For case 1 and case 2a, the training and generation of the model may occur on the network side or the cloud server (OTT server) side, and the inference occurs on the terminal side. Therefore, the model needs to be sent from the trainer to the terminal.

[0081] For Case 1:

[0082] Model training: OTT server, CN (LMF / NWDAF);

[0083] Model inference: UE side, where the intermediate inference is completed inside the UE, and the AI positioning result is sent to the CN.

[0084] For Case 2a:

[0085] Model training: OTT server, CN (LMF / NWDAF);

[0086] Model inference: UE side, and the AI measurement information is sent to the CN.

[0087] Generally speaking, in the above two cases:

[0088] The terminal obtains the trained AI positioning model from the Core Network (CN) or the OTT server;

[0089] The terminal performs model inference locally to obtain AI measurement information (i.e., case 2a) or directly obtains the AI positioning result (i.e., case 1);

[0090] The terminal reports the positioning intermediate quantity (i.e., AI measurement information, case 2a) or the positioning result (i.e., AI position estimate, case 1) to the CN. The CN determines the final AI position estimate based on the AI measurement quantity or directly uses the position estimate reported by the terminal.

[0091] The following will combine the accompanying drawings and elaborate on the information transmission method provided in the embodiments of the present application through some embodiments and their application scenarios.

[0092] Please refer to Figure 3 , Figure 3 which is a flowchart of an information transmission method provided in the embodiments of the present application. This method can be executed by a terminal. As Figure 3 shown, it includes the following steps:

[0093] Step 301, the terminal receives a first message sent by a network-side device;

[0094] Among them, the first message includes information related to an artificial intelligence (AI) model. The information related to the AI model includes at least one of the following:

[0095] The identification information of the AI model;

[0096] The file information of the AI model;

[0097] The attribute information of the AI model;

[0098] The download address of the AI model.

[0099] In this embodiment, the above network-side devices may include, but are not limited to, at least one of AMF, a network element for managing the target service, a network element for managing the AI model, etc. Exemplarily, if the target service is a positioning service, the above network element for managing the target service may include LMF, the above AI model may be a model related to the positioning service, and the above network element for managing the AI model may include NWDAF, etc.

[0100] The identification information of the above AI model may include, but is not limited to, at least one of the ID of the model, the Analytics ID, the Functionality ID, etc. Among them, the above Analytics ID is used to describe the purpose or scenario of the AI model. For example, AI positioning, UE mobility, etc. It should be noted that the above model ID can be a globally unique identifier or a locally unique identifier. For example, it is unique within a Public Land Mobile Network (PLMN). In this embodiment, since the identification information of the AI model can uniquely identify the AI model globally or locally, the identification information of the AI model can help the terminal perform convenient and fast retrieval. For example, when subsequently using, updating, or deleting the AI model, the network and the terminal only need to use the AI model identification information and do not need to interact with a large amount of model file information.

[0101] The file information of the above AI model may include, but is not limited to, model parameter information, model structure information, etc. In this embodiment, the file information of the AI model is the specific parameters and execution files of the model. The file information of the AI model can be a standardized file (such as exe, xml, etc.) or a non-standardized file supported for installation or use by the terminal, which can help the terminal perform AI inference under various different services and improve service quality.

[0102] The attribute information of the above AI model may include, but is not limited to, attribute parameters such as the usage information of the model (such as model validity period, effective range, etc.), the size of the model, the applicable range of the model, and the generalization information of the model. In this embodiment, the terminal can judge whether it is suitable to use the AI model in certain geographical areas and certain access scenarios and whether the accuracy of the AI model meets the requirements according to the generalization information of the model. In addition, the size of the model (mainly referring to the required storage space, such as 100MB, 1GB) can help the terminal judge which model to download according to its own storage space. For example, when the network does not provide the file information of the above AI model but provides the model download address, the network provides the size of the model to the terminal, and the terminal can judge whether to download a larger or smaller model according to its remaining storage space, so as to balance its own storage space and the AI service experience.

[0103] The download address of the above AI model can be used by the terminal to download the AI model. For example, based on the request method of the application layer Hypertext Transfer Protocol (HTTP), the terminal requests to download the AI model from the device corresponding to the download address of the above AI model, such as the address of the OTT server. For example, it requests to download the file information of the AI model. In practical applications, some models may not be generated by 3GPP training but are provided by a third party (such as an OTT server). In this embodiment, by providing the download address information of the AI model to the terminal, the terminal can choose whether to download the model and select a suitable model for download. In addition, by providing the download address information of the AI model to the terminal, it is also possible to avoid sending the model file to the terminal every time the model is transmitted, thereby achieving the purpose of saving signaling.

[0104] The above first message can be carried in the control plane signaling, that is, the network side device sends the first message to the terminal through the control plane signaling. Exemplarily, the above first message can be carried in a control plane bearer or a container.

[0105] Exemplarily, when the relevant information of the AI model received by the terminal includes the file information of the AI model, the terminal can perform processing such as inference or continued training based on the received file information of the AI model. For example, it can perform positioning based on the file information of the AI model; when the relevant information of the AI model received includes the download address of the AI model, the terminal can download the file information of the AI model based on the download address of the AI model, and then can perform processing such as inference or continued training based on the downloaded file information of the AI model.

[0106] In the embodiment of the present application, the terminal receives a first message sent by the network side device; wherein, the first message includes relevant information of an artificial intelligence AI model, and the relevant information of the AI model includes at least one of the following: identification information of the AI model; file information of the AI model; attribute information of the AI model; download address of the AI model, that is, in the embodiment of the present application, the network side passes at least one of the identification information of the AI model, the file information of the AI model, the attribute information of the AI model, and the download address of the AI model to the terminal through the first message, providing a way for the network side to transfer the AI model to the terminal.

[0107] Optionally, the terminal receiving the first message sent by the network side device includes:

[0108] The terminal receives the first message sent by the network side device through the control plane signaling.

[0109] Exemplarily, the above first message may be carried in a control plane bearer or a container. For example, the above first message may be carried in a control plane container existing in an existing protocol, or the above first request message may be carried in a newly defined or added control plane container.

[0110] In this embodiment, the terminal receives the first message sent by the network side device through control plane signaling. This is beneficial for quickly sending the model to the terminal without the need to establish a new user plane connection, saving some of the overhead of establishing a new user plane connection, and only requiring support for control plane signaling transmission. It is more friendly to some terminals that do not support user plane connections in terms of logical implementation, such as simple Internet of Things (IoT) devices.

[0111] Optionally, before the terminal receives the first message sent by the network side device, the method further includes:

[0112] The terminal sends a first request message to a first network element;

[0113] Wherein, the first request message is used to request to obtain an AI model.

[0114] In this embodiment, the above first network element may include network elements such as AMF and SMF.

[0115] Exemplarily, the above first request message may include at least one of identification information of the AI model, indication information for indicating a request to obtain the AI model, indication information for indicating the transfer of the AI model through the control plane, description information of the AI model, address information of the model storage network element, service type using the model, etc. Among them, the above service type using the model is used to indicate the service to which the requested AI model is applied. For example, services such as positioning and sensing.

[0116] It can be understood that after the first network element receives the first request message, it may send a second request message to a second network element according to the first request message; the first network element may receive the relevant information of the AI model returned by the second network element and send it to the terminal. Among them, the above second network element is a network element that manages the target service, and the AI model is a model related to the target service; or, the second network element is a network element that manages the AI model. For example, if the target service is a positioning service, the above network element that manages the target service may include LMF, the above AI model may be a model related to the positioning service, and the above network element that manages the AI model may include NWDAF.

[0117] In this embodiment, the terminal sends a first request message to the first network element, which facilitates the network side to more accurately and conveniently obtain the relevant information of the required AI model based on the first request message.

[0118] Optionally, the first request message includes at least one of the following: first information, address information of the model storage network element, and service type using the model.

[0119] Wherein, the first information includes at least one of the following:

[0120] First indication information for indicating that the terminal needs to obtain an AI model;

[0121] Second indication information for indicating that the AI model needs to be transmitted through the control plane;

[0122] Identification information of the AI model;

[0123] Description information of the AI model;

[0124] Identification information of the terminal;

[0125] First capability information for indicating that the terminal supports obtaining the AI model through the control plane.

[0126] In this embodiment, the above first indication information is used to indicate a request to obtain an AI model. It should be noted that the above first indication information can be explicit indication information or implicit indication information. For example, when the terminal sends a model request message as the first request message, the message type of the first request message indicates model request, and the network side uses the recognized message type of the first request message as the first indication information, that is, it is understood that the UE is requesting an AI model. The purpose of identifying the first request message through the first indication information in this embodiment, that is, the terminal needs to obtain an AI model, can help the network side identify that the first request message is for requesting a model rather than a model confirmation reply, and can more clearly express the requirements of the terminal.

[0127] The above second indication information is used to indicate the transmission of the AI model through the control plane. It should be noted that when the terminal sends the first request message to the network side through the control plane, optionally, the first request message may carry the second indication information for indicating to the network side to transmit the AI model information through the control plane. In this embodiment, the second indication information indicates the manner in which the terminal hopes to send the relevant information of the AI model to the terminal. Since there are multiple ways of interaction between the terminal and the network, such as APP layer transmission and 3GPP architecture transmission, clearly indicating the use of the user plane to transmit the relevant information of the AI model through the second indication information can prevent the network side from randomly selecting a transmission method for transmission. In addition, using the user plane for transmission can download the large model to the terminal more quickly and improve the model download efficiency.

[0128] The identification information of the above-mentioned AI model may include but is not limited to at least one of the model ID, analysis ID, function ID, etc. In this embodiment, the identification information of the AI ​​model is used to uniquely identify the model globally or locally. The terminal provides the identification information of the AI ​​model to help the network element that manages the AI ​​model (for example, NWDAF) to quickly query the requested AI model. It can also help the network element that manages the target service (for example, LMF) to identify whether it has saved the AI ​​model. This can avoid the above two types of network elements from determining the identification of the AI ​​through the description information of the AI ​​or querying the AI ​​model from other network elements every time, and can optimize the usage process. In addition, the network side and the terminal side can use the identification information of the same AI model. For example, to use, delete and modify a model, you only need to use the model identification information as an index, which also simplifies the subsequent operation and management of the model.

[0129] The identification information of the above-mentioned terminal may include but is not limited to at least one of the terminal (i.e., UE) ID (for example, a user permanent identifier (Subscription Permanent Identifier, SUPI)) and the vendor (Vendor) ID. In this embodiment, the identification information of the above-mentioned terminal is used to identify the identity of the requester, which can help the network side record which users of the model are used. When the model needs to be monitored, updated, or modified later, the user can be found quickly. For example, when the network side needs to delete the model, a deletion request can be sent to the user of the model in a targeted manner instead of broadcasting, which can improve the network side's management efficiency of the model.

[0130] The description information of the above-mentioned AI model may include parameter information for describing the model requirements. In this embodiment, the requirements of a certain AI model are described through the description information of the AI ​​model, which can help the network side quickly identify or determine which model should be used / downloaded to the terminal. In one case, the terminal may not know the identification information of the model. The terminal only knows what its requirements for the model are (for example, what service the model is used for and who the user of the model is). Through the description information of the AI ​​model, the network can know the terminal's requirements for the AI ​​model in more detail, and help the network side select / train to generate a more suitable model from a large number of AI models, rather than randomly issuing a model. This can improve the interaction efficiency between the terminal and the network, as well as the terminal's experience of using the AI ​​model.

[0131] It should be noted that the identification information of the above-mentioned AI model can be understood as the identification information of the AI ​​model requested by the terminal, and the description information of the above-mentioned AI model can be understood as the description information of the AI ​​model requested by the terminal.

[0132] The above model storage network element stores address information (address), for example, LMF address / NWDAF address / OTT server address. Among them, the address information of the above model storage network element can be pre-configured in the terminal, and the first network element can send the first request message to the above model storage network element according to the address information of the above model storage network element. In this embodiment, the address information of the model storage network element can indicate to the network where to obtain the model, which can help the transfer network element or forwarding network element (such as, AMF) of the first request message know which network element the first request message should be forwarded to. In practical applications, as a network element for message transfer (i.e., forwarding network element), it may not know to whom the message can be forwarded. In this embodiment, by providing the address information of the above model storage network element, the request message of the model (i.e., the first request message) can be successfully sent to the target network element (such as, NWDAF, LMF), improving the message forwarding efficiency.

[0133] The above service type using the model is used to indicate the service to which the requested AI model is applied, for example, services such as positioning, communication sensing, etc. In this embodiment, the service type using the model can indicate to the network the service to which the model requested by the terminal is applicable, and the service type using the model can be used by the forwarding network element that forwards the first request message. Exemplarily, if the terminal does not know the address information of the model storage network element and only knows the service for which the requested model is used, such as positioning or communication sensing, after the forwarding network element receives the first request message, it can forward the model request to the corresponding LMF or Sensing Function (SF) according to the service type using the model, which is beneficial to improving the message forwarding efficiency.

[0134] It should be noted that the above service type using the model can be visible to the first network element. Therefore, in the case where the terminal does not provide the address information of the model storage network element, the first network element can judge the purpose of the model requested by the terminal according to the above service type using the model, and then select a suitable network element (LMF, NWDAF or other network elements) to send the second request message.

[0135] The above first capability information is used to indicate that the terminal has the ability to obtain the AI model through the control plane. Through this first capability information, it can help the network side select a suitable model download method. For example, if the terminal does not support downloading the AI model through the control plane, then the network side may not be able to use the control plane connection to download the model. This can allow the network to fully consider and know the device conditions of the terminal regarding model transfer, improving the efficiency of transferring the model. In one scenario, the terminal does not carry the second indication information, so the network can decide to transfer the model to the terminal through the control plane according to the first capability information.

[0136] Optionally, the description information of the AI model includes at least one of the following:

[0137] Service type indication information for indicating the service type that the requested model needs to provide;

[0138] Information about the model usage object;

[0139] The type of model input data, where the type of model input data includes at least one of the type of input data required for model inference and the type of input data required for model training;

[0140] The type of model inference result.

[0141] The above service type indication information is used to indicate the service type that the requested model needs to provide. For example, the requested model is used to provide services such as positioning or sensing. In this embodiment, through the service type indication information, the network element that manages the model can help train the correct model when training the model, or can retrieve more systematically when searching for the model, so as to obtain a model that meets the terminal's requirements. For example, some models are for positioning, some models are suitable for sensing, and some are for image recognition. When the terminal provides the above service type indication information to the network, it can more accurately express the terminal's requirements for the model, avoid the network training / downloading a model with a wrong usage purpose, and thus improve the interaction efficiency between the terminal and the network.

[0142] The above information about the model usage object is used to indicate the objects that can use the model. For example, UE, Programmable Real-time Unit (PRU), gNB, etc. In this embodiment, through the information about the model usage object, the terminal's requirements for the model can be expressed more accurately. For example, in positioning, for the same positioning AI model, some may be for the core network, and some may be for the access network. The generalization effect and accuracy are different for different users. Therefore, clearly indicating the model usage object through the above information about the model usage object can help the network distribute a more accurate model. In addition, considering that the usage effect of the same model on terminals of different terminal manufacturers may be different, and the privacy settings for downloading the model are also different, taking this requirement into account, the terminal can tell the network which terminal device the user is. The more detailed the information about the model test object provided, the clearer the network can know the terminal's requirements, and thus it is beneficial for the network to download a more suitable model to the terminal.

[0143] The type of the input data required for the above model inference can be understood as the type of the input data required for the AI model to perform inference. For example, for an AI model related to positioning, the type of the input data required for the above model inference can be used to indicate positioning-related data. The type of the input data required for the above model training can be understood as the type of the data used for AI model training, such as Channel Impulse Response (CIR) / Power Delay Profile (PDP) / Delay Profile (DP). By providing the type of the above model input data in this embodiment, the requirements of the terminal for the model can be expressed more accurately, which is conducive to the network downloading a more suitable model to the terminal.

[0144] The type of the above model inference result can be understood as the type of the data output by using the AI model for inference. For example, for an AI model related to positioning, the type of the above model inference result can be used to indicate location information or measured intermediate feature information. By providing the type of the above model inference result in this embodiment, the requirements of the terminal for the model can be expressed more accurately, which is conducive to the network downloading a more suitable model to the terminal.

[0145] Optionally, the first information is carried in a model request bearer.

[0146] Exemplarily, the above model request bearer (Container) can be a newly added Container. An optional IE is carried outside the REGISTRATION REQUEST, UL NAS TRANSPORT message to indicate the type of the message in the Container, such as indicating that the message carried in the Container is a model acquisition request, so that the first network element can perform second network element selection and forward the Container to the selected second network element.

[0147] In this embodiment, the above first information is carried in a model request bearer (Container). In this way, after receiving the first request message, the first network element can directly send the model request Container to the second network element.

[0148] Optionally, the terminal sending the first request message to the first network element includes:

[0149] The terminal sends the first request message to the first network element through control plane signaling.

[0150] In this embodiment, the terminal sends a first request message to the first network element through the control plane signaling, so that the existing connection between network elements can be reused, and the first request message can be sent to the network element of the management model by using the network element forwarding mechanism, without establishing / using a user plane connection channel for model transfer, reducing the user plane connection and user plane resource overhead, and lowering the implementation requirements for the terminal / network device.

[0151] Optionally, the method further includes:

[0152] The terminal sends a first response message through the control plane signaling, where the first response message is used to indicate whether the terminal successfully receives the relevant information of the AI model.

[0153] Exemplarily, the above first response message may include indication information on whether the AI model is successfully received, cause information for receiving failure, etc.

[0154] Exemplarily, the above first response message may also be carried in the control plane Container.

[0155] It can be understood that the terminal can send a first response message to the first network element through the control plane signaling, and the first network element forwards the received first response message to the second network element.

[0156] It should be noted that each response message involved in the embodiments of this application may also be referred to as a reply message or a feedback message, etc.

[0157] In this embodiment, the terminal sends a first response message to the first network element through the control plane signaling, which can reuse the existing connection between network elements and send the request message to the network element of the management model by using the network element forwarding mechanism. Here, there is no need to establish / use a user plane connection channel for model transfer, reducing the user plane connection and user plane resource overhead, and lowering the implementation requirements for the terminal / network device. In addition, by sending the first response message to the network side, it is beneficial for the network side to know the reception situation of the terminal for the relevant information of the AI model and ensure the consistency of understanding between the terminal and the network side.

[0158] Optionally, when the first response message is used to indicate that the terminal fails to receive the relevant information of the AI model, the first response message includes first cause information, and the first cause information is used to indicate the reason for the terminal's failure to receive the relevant information of the AI model.

[0159] Exemplarily, the reasons for the terminal's failure to receive the relevant information of the AI model may include at least one of the following: incorrect model format, invalid download address.

[0160] Please refer to Figure 4 , Figure 4It is a flowchart of an information transmission method provided by an embodiment of the present application. This method can be executed by a first network element, such as Figure 4 shown, and includes the following steps:

[0161] Step 401, the first network element sends a first message to the terminal;

[0162] Among them, the first message includes information related to an artificial intelligence (AI) model. The information related to the AI model includes at least one of the following:

[0163] Identification information of the AI model;

[0164] File information of the AI model;

[0165] Attribute information of the AI model;

[0166] Download address information of the AI model.

[0167] In this embodiment, the above-mentioned first network element may include, but is not limited to, at least one of AMF, a network element for managing target services, a network element for managing AI models, etc.

[0168] Optionally, the first network element sending the first message to the terminal includes:

[0169] The first network element sends the first message to the terminal through control plane signaling.

[0170] Optionally, before the first network element sends the first message to the terminal, the method further includes:

[0171] The first network element receives a first request message sent by the terminal, where the first request message is used to request to obtain an AI model;

[0172] The first network element sends a second request message to a second network element, where the second request message is used to request to obtain an AI model, and the second request message is determined according to the first request message;

[0173] The first network element receives a second response message sent by the second network element, where the second response message includes at least one of the following: an indication of whether to accept the AI model acquisition request, the information related to the AI model.

[0174] In this embodiment, the above-mentioned first network element may include network elements such as AMF. The above-mentioned second network element may include a network element for managing target services or a network element for managing AI models, etc., where the AI model is a model related to the target service. For example, if the target service is a positioning service, the above-mentioned network element for managing target services may include LMF, the above-mentioned AI model may be a model related to the positioning service, and the above-mentioned network element for managing AI models may include NWDAF.

[0175] Exemplarily, when the above first request message includes the address information of the above model storage network element, the first network element may send a second request message to the above model storage network element based on the address information of the above model storage network element; when the above first request message does not include the address information of the above model storage network element, the first network element may first select a second network element. For example, if the above first request message includes the service type of the used model, the first network element may judge the purpose of the model requested by the terminal according to the service type of the used model, and then select a suitable network element (LMF, NWDAF or other network element) to send the second request message.

[0176] It can be understood that when the above second response message indicates acceptance of the AI model acquisition request, the above second response message may include relevant information of the AI model. In this case, the first network element sends a first message to the terminal; when the above second response message indicates rejection of the AI model acquisition request, the above second response message may not include the relevant information of the AI model. In this case, the first network element may send a rejection message or a failure message to the terminal, and the rejection message or the failure message may carry second cause information for indicating the reason for rejecting the AI model acquisition request or the failure to acquire the AI model.

[0177] Optionally, the first request message includes at least one of the following: first information, address information of the model storage network element, service type of the used model;

[0178] Wherein, the first information includes at least one of the following:

[0179] First indication information for indicating that the terminal needs to acquire an AI model;

[0180] Second indication information for indicating that the AI model needs to be transmitted through the control plane;

[0181] Identification information of the AI model;

[0182] Description information of the AI model;

[0183] Identification information of the terminal;

[0184] First capability information for indicating that the terminal supports acquiring an AI model through the control plane.

[0185] Optionally, the description information of the AI model includes at least one of the following:

[0186] Service type indication information for indicating the service type that the requested model needs to provide;

[0187] Information about the object using the model;

[0188] The type of model input data, where the type of the model input data includes at least one of the type of input data required for model inference and the type of input data required for model training;

[0189] The type of model inference result.

[0190] Optionally, the second request message may include at least one of the above first information and the service type using the model.

[0191] Optionally, the first information is carried in the model request bearer.

[0192] In this embodiment, the first information is carried in the model request bearer (Container). In this way, after receiving the first request message, the first network element can directly send the model request Container to the second network element, that is, the second request message includes the above model request Container.

[0193] Optionally, the first network element receives the first request message sent by the terminal, including:

[0194] The first network element receives the first request message sent by the terminal through control plane signaling.

[0195] Optionally, before the first network element sends the second request message to the second network element, the method further includes:

[0196] The first network element selects a second network element that supports model transfer.

[0197] Exemplarily, when receiving the first request message, the first network element can, after verifying the UE authorization information according to the first indication information carried in the first request message, select a second network element that supports model transfer and send the second request message to the selected second network element. Exemplarily, the first network element selects a second network element that supports model transfer by querying the NRF, or the first network element locally configures a default second network element.

[0198] Optionally, the first network element selects a second network element that supports model transfer, including:

[0199] The first network element selects a second network element that supports model transfer according to the second information, where the second information includes at least one of the following: the address information of the model storage network element, the service type using the model.

[0200] Exemplarily, when the first request message includes the address information of the model storage network element, the second network element above may be the network element indicated by the address information of the model storage network element; when the first request message includes the service type of using the model, the first network element may, after judging the purpose of the model requested by the terminal according to the service type of using the model, select the second network element accordingly.

[0201] In this embodiment, the first network element selects the second network element that supports model transfer according to the second information, so that the appropriate model storage network element, that is, the second network element, can be selected without seeing the first information, and the model request content of the terminal, such as the first information, is sent to the model storage network element. Because in actual deployment, it is not necessary for the first network element to know the specific content of this first information, and it only needs to transparently transmit / forward it to the corresponding network element, such a design is easier to implement for the device.

[0202] Optionally, the first request message includes the service type of using the model; the first network element selects the second network element that supports model transfer, including:

[0203] The first network element queries the Network Repository Function (NRF) according to the service type of using the model to obtain the identification information or address information of the second network element.

[0204] Exemplarily, the first network element above queries the Network Repository Function (NRF) according to the service type of using the model to query the identification information or address information of the storage network element of the AI model that supports the above service type, and uses this storage network element as the second network element above.

[0205] It should be noted that the implementation manner of this embodiment can refer to Figure 3 the relevant description of the embodiment shown, which will not be elaborated here.

[0206] Please refer to Figure 5 , Figure 5 which is a flowchart of an information transmission method provided by an embodiment of the present application. This method can be executed by the second network element. As Figure 5 shown, it includes the following steps:

[0207] Step 501, the second network element receives a second request message sent by the first network element, where the second request message is used to request to obtain an AI model.

[0208] In this embodiment, the above-mentioned first network element may include network elements such as AMF. The above-mentioned second network element may include, but is not limited to, a network element for managing the target service or a network element for managing the AI model, etc., where the AI model is a model related to the target service. For example, if the target service is a positioning service, the above-mentioned network element for managing the target service may include LMF, the above-mentioned AI model may be a model related to the positioning service, and the above-mentioned network element for managing the AI model may include NWDAF.

[0209] Exemplarily, the above-mentioned second request message may include, but is not limited to, at least one of the first information and the service type using the model; where the first information may include at least one of the following:

[0210] The first indication information, used to indicate that the terminal needs to obtain the AI model;

[0211] The second indication information, used to indicate that the AI model needs to be transmitted through the control plane;

[0212] The identification information of the AI model;

[0213] The description information of the AI model;

[0214] The identification information of the terminal;

[0215] The first capability information, used to indicate that the terminal supports obtaining the AI model through the control plane.

[0216] Optionally, the description information of the AI model includes at least one of the following:

[0217] The service type indication information, used to indicate the service type that the requested model needs to provide;

[0218] The information of the model usage object;

[0219] The type of the model input data, and the type of the model input data includes at least one of the type of the input data required for model inference and the type of the input data required for model training;

[0220] The type of the model inference result.

[0221] Step 502, the second network element sends a second response message to the first network element, where the second response message includes at least one of the following: an indication of whether to accept the AI model acquisition request, and the relevant information of the AI model.

[0222] Exemplarily, when the second network element receives the second request message, if the relevant information of the AI model is stored locally in the second network element, it can directly obtain the relevant information of the AI model stored locally and send it to the terminal via the first network element; if the relevant information of the above AI model is not stored locally in the second network element, the second network element can request the relevant information of the AI model from the storage network element of the relevant information of the AI model and send it to the terminal via the first network element; if the second network element cannot obtain the relevant information of the AI model or does not support the download / use of the above AI model, it can send a second response message to the terminal for instructing to reject the AI model acquisition request. Among them, the above second response message for instructing to reject the AI model acquisition request can also be called a model rejection message. Optionally, the above model rejection message may carry the reason for rejection.

[0223] In some alternative embodiments, the relevant information of the above AI model may be carried in a model response container (Container). Exemplarily, the above model response Container may be a newly added Container.

[0224] It can be understood that when the above second response message indicates acceptance of the AI model acquisition request, the above second response message may include the relevant information of the AI model; when the above second response message indicates rejection of the AI model acquisition request, the above second response message may not include the relevant information of the AI model.

[0225] Optionally, the relevant information of the AI model includes at least one of the following:

[0226] The identification information of the AI model;

[0227] The file information of the AI model;

[0228] The attribute information of the AI model;

[0229] The download address information of the AI model.

[0230] Optionally, the second request message includes first information, where the first information includes at least one of the following:

[0231] First indication information for indicating that the terminal needs to obtain the AI model;

[0232] Second indication information for indicating that the AI model needs to be transmitted through the control plane;

[0233] The identification information of the AI model;

[0234] The description information of the AI model;

[0235] The identification information of the terminal;

[0236] The first capability information is used to indicate that the terminal supports obtaining an AI model through the control plane.

[0237] Optionally, the description information of the AI model includes at least one of the following:

[0238] Service type indication information, which is used to indicate the service type that the requested model needs to provide;

[0239] Information about the object using the model;

[0240] The type of model input data, where the type of model input data includes at least one of the type of input data required for model inference and the type of input data required for model training;

[0241] The type of model inference result.

[0242] Optionally, the first information is carried in the model request bearer.

[0243] Optionally, when the second response message indicates a rejection of the AI model acquisition request, the second response message further includes second reason information, and the second reason information is used to indicate the reason for rejecting the AI model acquisition request.

[0244] Exemplarily, the reasons for rejecting the AI model acquisition request may include but are not limited to at least one of the following: network congestion, the requested model does not exist, unauthorized use of the model, and the model does not meet the requirements.

[0245] Optionally, the second network element is a network element that manages the target service, and the AI model is a model related to the target service; or, the second network element is a network element that manages the AI model.

[0246] Optionally, the second network element is a network element that manages the target service, and the method further includes:

[0247] The second network element sends a third request message to a third network element, where the third network element is a network element that manages the AI model, and the third request message includes the identification information of the AI model, or the third request message includes the identification information of the AI model and the identification information of the terminal;

[0248] The second network element receives a third response message sent by the third network element, where the third response message includes the relevant information of the AI model.

[0249] In this embodiment, the identification information of the above AI model may include, but is not limited to, at least one of the ID of the model, the Analytics ID, the Functionality ID, etc. The identification information of the above terminal may include, but is not limited to, at least one of the terminal (i.e., UE) ID (e.g., SUPI) and the Vendor ID, for the second network element to know the specific consumer.

[0250] The above third network element may be a storage network element of the AI model, for example, NWDAF.

[0251] Exemplarily, the second network element sends a third request message to the third network element; the third network element receives the third request message sent by the second network element, and may obtain the relevant information of the AI model based on the identification information of the AI model included in the third request message, and send it to the second network element.

[0252] It should be noted that the implementation manner of this embodiment can refer to Figure 3 and Figure 4 the relevant descriptions of the embodiments shown, which will not be elaborated here.

[0253] It should also be noted that in various embodiments of the present application, the first request message and the second request message may also be referred to as the model request message, and the above first message and second response message may also be referred to as the model response message or the model delivery message. The above first response message may also be referred to as the model complete message.

[0254] The embodiments of the present application will be described below with reference to examples:

[0255] Example 1: The UE requests to obtain from the LMF, and the LMF distributes the model through the control plane signaling.

[0256] Referring to Figure 6a , the information transmission method provided in this embodiment includes the following steps:

[0257] Step 1, the UE sends a model request message (i.e., the above first request message) to the AMF.

[0258] An optional implementation manner is to encapsulate the relevant information of the AI model such as the model identification information, the terminal identification information, the first capability information, and the model description information in the model request Container.

[0259] Among them, for the relevant content of the above first request message, refer to the relevant description in the foregoing embodiments, which will not be elaborated here.

[0260] Step 2: After the AMF verifies the UE authorization information according to the first indication information of the model request message, it selects an LMF that supports model transfer and executes Step 3.

[0261] In this step, if the address information of the model storage network element is carried in Step 1, the AMF can directly send the model request Container to the corresponding network element; if the address information of the storage network element is not carried, the AMF performs LMF selection and sends the model request Container to the selected LMF. It should be noted that when performing LMF selection, the capabilities of the NRF can be queried to select an LMF that supports model transfer and send a request; for example, if the address information of the storage network element is not carried in Step 1, but the service type using the model is carried, the AMF can send the model request Container to the corresponding service management network element according to the indicated service type. For example, for the communication sensing service, the AMF sends the model request Container to the sensing function locally configured by the AMF, or sends the model request Container after querying the sensing function address through the NRF.

[0262] Step 3: The AMF sends the model request Container to the selected LMF.

[0263] Step 4: If the LMF determines that it needs to obtain the model from the NWDAF, it executes Steps 5 - 6; if the corresponding model is locally saved, it directly executes Step 7.

[0264] If the target model cannot be obtained or the local does not support the distribution / use of the target model, the LMF sends a request to reject the acquisition of the model in Step 7, replies to the UE with a rejection message, and optionally carries the rejection reason.

[0265] Steps 5 - 6: The LMF and the NWDAF interact with the model. The LMF sends a model request message to the NWDAF, carrying the model identification information and the UE ID. The NWDAF replies to the LMF with the model ID, model information (i.e., the file information of the above AI model), model attribute information, and model download address.

[0266] Steps 7 - 8: The LMF sends a model reply Container to the UE through the control plane signaling, carrying the model ID, model information, model attribute information, and model download address.

[0267] An optional implementation is that the above model request Container can be a newly added control plane Container, which carries an optional IE in the registration request or UL NAS TRANSPORT message to indicate the message type within the Container. For example, it indicates that the message type carried in the Container is a model acquisition request, so that the AMF can perform LMF selection according to the above message type, select a suitable LMF, and forward the Container to the LMF.

[0268] If step 4 decides to reject, or no valid model information is received in step 6, the LMF replies with a rejection message or a failure message in step 7. Optionally, the above rejection message or failure message can carry the reason for failure or the reason for rejection.

[0269] In step 9, the UE replies with an ACK to confirm receiving the model information, and this message is transmitted to the LMF through the control plane signaling.

[0270] An optional implementation is similar to the message in step 1 above and is encapsulated inside the Container.

[0271] For steps 1 - 9, an implementation can be to add two new message types. One message type is used to indicate a model download message or a model request message, and the other message type is used to indicate a model download reply message or a model reply message. The above download reply message or model reply message includes two categories. One is successful reception, and the other is reception failure. Optionally, in the case of reception failure, the above download reply message can carry the reason for failure.

[0272] In steps 10 - 13, the NWDAF or LMF updates the model, sends the model update message to the UE via the AMF, and the UE replies with an ACK to confirm receiving the model update message. The messages in this step are transmitted through the control plane signaling. An optional implementation is similar to the message in step 1 above and is encapsulated inside the Container.

[0273] The above model update message can include the updated model ID, the updated model information (i.e., the file information of the above AI model), the updated model attribute information, and the updated model download address.

[0274] It should be noted that the message types in the above steps 10-13 may be different from those in the above steps 1-9. For example, in the above steps 10-13, two new message types are added. One message type is used to indicate the model update message, and the other message type is used to indicate the model update reply message. The above model update reply message includes two categories, one is successful reception, and the other is failed reception. Optionally, in the case of failed reception, the above model update reply message may carry the reason for failure.

[0275] It should be noted that the above steps 4 to 6 and steps 9 to 13 are optional steps.

[0276] Example 2: The UE requests to obtain from the NWDAF, and the NWDAF distributes the model through the control plane signaling.

[0277] The main difference between this Example 2 and Example 1 is that: Refer to Figure 6b In step 3 of, the AMF forwards the model acquisition request to the NWDAF, the AMF directly skips the LMF, and the model is distributed and transmitted between the NWDAF and the UE.

[0278] Refer to Figure 6b , the information transmission method provided in this embodiment includes the following steps:

[0279] Step 1, the UE sends a model request message (i.e., the above first request message) to the AMF.

[0280] An optional implementation method is to encapsulate the relevant information of the AI model such as the model identification information, terminal identification information, first capability information, and model description information in the model request Container.

[0281] Among them, the relevant content of the above first request message refers to the relevant description of the foregoing embodiment, and will not be elaborated here.

[0282] Step 2, after the AMF verifies the UE authorization information according to the first indication information of the model request message, it selects the NWDAF that supports model transfer and executes step 3.

[0283] Step 3, the AMF sends the model request Container to the selected NWDAF.

[0284] Steps 4-5, the NWDAF sends a model reply Container to the UE through the control plane signaling, carrying the model ID, model information, model attribute information, and model download address.

[0285] Among them, this step can be the same as Figure 6aSteps 7-8 are the same or similar. If the NWDAF cannot provide the model requested by the terminal, the NWDAF sends a model transfer failure or model transfer rejection message to the terminal, which will not be elaborated here.

[0286] Step 6: The UE replies with an ACK to confirm receipt of the model information. This message is transmitted to the LMF via control plane signaling.

[0287] An optional implementation is similar to the message in Step 1 above and is encapsulated inside a Container.

[0288] Steps 7-9: The NWDAF updates the model, sends a model update message to the UE via the AMF, and the UE replies with an ACK to confirm receipt of the model update message. The messages in this step are transmitted via control plane signaling. An optional implementation is similar to the message in Step 1 above and is encapsulated inside a Container.

[0289] The above model update message includes the updated model ID, updated model information (model info) (i.e., the file information of the above AI model), updated model attribute information, and updated model download address.

[0290] It should be noted that the above Steps 6 to 9 are optional steps.

[0291] It should be noted that for the information transmission method provided in the embodiments of this application, the execution subject can be an information transmission device, or a control module in the information transmission device for executing the information transmission method. In the embodiments of this application, the information transmission method is executed by the information transmission device as an example to illustrate the information transmission device provided in the embodiments of this application.

[0292] Please refer to Figure 7 , Figure 7 which is the structural diagram of an information transmission device provided in the embodiments of this application. As Figure 7 shown, the information transmission device 700 includes:

[0293] A first receiving module 701, configured to receive a first message sent by a network-side device;

[0294] Among them, the first message includes information related to an artificial intelligence (AI) model. The information related to the AI model includes at least one of the following:

[0295] Identification information of the AI model;

[0296] File information of the AI model;

[0297] Attribute information of the AI model;

[0298] Download address of the AI model.

[0299] Optionally, the first receiving module is specifically configured to:

[0300] Receive a first message sent by a network-side device through control plane signaling.

[0301] Optionally, the apparatus further includes:

[0302] A first sending module, configured to send a first request message to a first network element before receiving the first message sent by the network-side device;

[0303] Wherein, the first request message is used to request to obtain an AI model.

[0304] Optionally, the first request message includes at least one of the following: first information, address information of a model storage network element, service type for using the model;

[0305] Wherein, the first information includes at least one of the following:

[0306] First indication information, used to indicate that the terminal needs to obtain an AI model;

[0307] Second indication information, used to indicate that the AI model needs to be transmitted through the control plane;

[0308] Identification information of the AI model;

[0309] Description information of the AI model;

[0310] Identification information of the terminal;

[0311] First capability information, used to indicate that the terminal supports obtaining an AI model through the control plane.

[0312] Optionally, the description information of the AI model includes at least one of the following:

[0313] Service type indication information, used to indicate the service type that the requested model needs to provide;

[0314] Information about the object using the model;

[0315] Type of model input data, where the type of model input data includes at least one of the type of input data required for model inference and the type of input data required for model training;

[0316] Type of model inference result.

[0317] Optionally, the first information is carried in a model request bearer.

[0318] Optionally, the first sending module is specifically configured to:

[0319] Send a first request message to the first network element through control plane signaling.

[0320] Optionally, the device further includes:

[0321] A target sending module, configured to send a first response message through control plane signaling, where the first response message is used to indicate whether the terminal successfully receives information related to the AI model.

[0322] Optionally, when the first response message is used to indicate that the terminal fails to receive information related to the AI model, the first response message includes first cause information, and the first cause information is used to indicate the reason why the terminal fails to receive information related to the AI model.

[0323] The information transmission device in the embodiments of the present application may be an electronic device, such as an electronic device with an operating system, or a component in an electronic device, such as an integrated circuit or a chip. The electronic device may be a terminal or other devices other than the terminal. Exemplarily, the terminal may include, but is not limited to, the types of the above-listed terminal 11, and other devices may be a server, a Network Attached Storage (NAS), etc., which are not specifically limited in the embodiments of the present application.

[0324] The information transmission device provided in the embodiments of the present application can implement Figure 3 each process implemented by the method embodiments and achieve the same technical effects. To avoid repetition, it will not be elaborated here.

[0325] Please refer to Figure 8 , Figure 8 which is a structural diagram of an information transmission device provided in the embodiments of the present application. As Figure 8 shown, the information transmission device 800 includes:

[0326] A second sending module 801, configured to send a first message to the terminal;

[0327] Wherein, the first message includes information related to an artificial intelligence (AI) model, and the information related to the AI model includes at least one of the following:

[0328] The identification information of the AI model;

[0329] The file information of the AI model;

[0330] The attribute information of the AI model;

[0331] The download address information of the AI model.

[0332] Optionally, the second sending module is specifically configured to:

[0333] Send a first message to the terminal through control plane signaling.

[0334] Optionally, the device further includes:

[0335] A second receiving module, configured to receive a first request message sent by the terminal before sending the first message to the terminal, where the first request message is used to request to obtain an AI model;

[0336] A third sending module, configured to send a second request message to a second network element, where the second request message is used to request to obtain an AI model, and the second request message is determined according to the first request message;

[0337] A third receiving module, configured to receive a second response message sent by the second network element, where the second response message includes at least one of the following: an indication of whether to accept the AI model acquisition request, and related information of the AI model.

[0338] Optionally, the first request message includes at least one of the following: first information, address information of a model storage network element, and service type for using the model;

[0339] Wherein, the first information includes at least one of the following:

[0340] First indication information, used to indicate that the terminal needs to obtain an AI model;

[0341] Second indication information, used to indicate that the AI model needs to be transmitted through the control plane;

[0342] Identification information of the AI model;

[0343] Description information of the AI model;

[0344] Identification information of the terminal;

[0345] First capability information, used to indicate that the terminal supports obtaining an AI model through the control plane.

[0346] Optionally, the description information of the AI model includes at least one of the following:

[0347] Service type indication information, used to indicate the service type that the requested model needs to provide;

[0348] Information about the object using the model;

[0349] Type of model input data, where the type of model input data includes at least one of the type of input data required for model inference and the type of input data required for model training;

[0350] Type of model inference result.

[0351] Optionally, the first information is carried in a model request bearer.

[0352] Optionally, the second receiving module is specifically configured to:

[0353] Receive the first request message sent by the terminal through control plane signaling.

[0354] Optionally, the apparatus further includes:

[0355] A selection module, configured to select a second network element that supports model transfer before sending a second request message to the second network element.

[0356] Optionally, the selection module is specifically configured to:

[0357] Select a second network element that supports model transfer according to second information, where the second information includes at least one of the following: address information of a model storage network element, service type using the model.

[0358] Optionally, the first request message includes a service type using the model; the selection module is specifically configured to:

[0359] Query the Network Repository Function (NRF) according to the service type using the model to obtain identification information or address information of the second network element.

[0360] Optionally, the second network element is a network element that manages a target service, and the AI model is a model related to the target service; or, the second network element is a network element that manages the AI model.

[0361] The information transmission apparatus in the embodiments of the present application may be an electronic device, such as an electronic device with an operating system, or a component in an electronic device, such as an integrated circuit or a chip. The electronic device may be a network-side device or other devices other than network-side devices. Exemplarily, the network-side device may include, but is not limited to, the types of network-side devices 12 listed above, and other devices may be servers, Network Attached Storage (NAS), etc., which are not specifically limited in the embodiments of the present application.

[0362] The information transmission apparatus provided in the embodiments of the present application can implement Figure 4 each process implemented by the method embodiments and achieve the same technical effects. To avoid repetition, details are not described here again.

[0363] Please refer to Figure 9 , Figure 9 which is a structural diagram of an information transmission apparatus provided in the embodiments of the present application. As Figure 9 shown, the information transmission apparatus 900 includes:

[0364] The fourth receiving module 901 is configured to receive a second request message sent by a first network element, where the second request message is used to request to obtain an AI model;

[0365] The fourth sending module 902 is configured to send a second response message to the first network element, where the second response message includes at least one of the following: an indication of whether to accept the AI model acquisition request, and relevant information of the AI model.

[0366] Optionally, the relevant information of the AI model includes at least one of the following:

[0367] The identification information of the AI model;

[0368] The file information of the AI model;

[0369] The attribute information of the AI model;

[0370] The download address information of the AI model.

[0371] Optionally, the second request message includes first information, where the first information includes at least one of the following:

[0372] The first indication information, which is used to indicate that the terminal needs to obtain an AI model;

[0373] The second indication information, which is used to indicate that the AI model needs to be transmitted through the control plane;

[0374] The identification information of the AI model;

[0375] The description information of the AI model;

[0376] The identification information of the terminal;

[0377] The first capability information, which is used to indicate that the terminal supports obtaining an AI model through the control plane.

[0378] Optionally, the description information of the AI model includes at least one of the following:

[0379] The service type indication information, which is used to indicate the service type that the requested model needs to provide;

[0380] The information of the model usage object;

[0381] The type of the model input data, and the type of the model input data includes at least one of the type of the input data required for model inference and the type of the input data required for model training;

[0382] The type of the model inference result.

[0383] Optionally, the first information is carried in a model request bearer.

[0384] Optionally, when the second response message indicates a rejection of the AI model acquisition request, the second response message further includes second reason information for indicating the reason for rejecting the AI model acquisition request.

[0385] Optionally, the second network element is a network element that manages the target service, and the AI model is a model related to the target service; or, the second network element is a network element that manages the AI model.

[0386] Optionally, the second network element is a network element that manages the target service, and the apparatus further includes:

[0387] A fifth sending module, configured to send a third request message to a third network element, where the third network element is a network element that manages the AI model, and the third request message includes identification information of the AI model, or the third request message includes identification information of the AI model and identification information of the terminal;

[0388] A fifth receiving module, configured to receive a third response message sent by the third network element, where the third response message includes relevant information of the AI model.

[0389] The information transmission apparatus in the embodiments of the present application may be an electronic device, such as an electronic device with an operating system, or a component in an electronic device, such as an integrated circuit or a chip. The electronic device may be a network-side device or other devices other than network-side devices. Exemplarily, the network-side device may include, but is not limited to, the types of network-side devices 12 listed above, and other devices may be a server, a Network Attached Storage (NAS), etc., which are not specifically limited in the embodiments of the present application.

[0390] The information transmission apparatus provided in the embodiments of the present application can implement Figure 5 each process implemented by the method embodiments and achieve the same technical effects. To avoid repetition, details are not described here again.

[0391] Optionally, as Figure 10 shown, the embodiments of the present application further provide a communication device 1000, including a processor 1001 and a memory 1002. A program or instruction that can run on the processor 1001 is stored on the memory 1002. For example, when the communication device 1000 is a terminal, when the program or instruction is executed by the processor 1001, each step of the above information transmission method embodiment is implemented, and the same technical effects can be achieved. When the communication device 1000 is a network-side device, when the program or instruction is executed by the processor 1001, each step of the above information transmission method embodiment is implemented, and the same technical effects can be achieved. To avoid repetition, details are not described here again.

[0392] An embodiment of the present application further provides a terminal, including a processor and a communication interface, where the communication interface is configured to receive a first message sent by a network-side device; wherein, the first message includes information related to an artificial intelligence (AI) model, and the information related to the AI model includes at least one of the following: identification information of the AI model; file information of the AI model; attribute information of the AI model; download address of the AI model. This terminal embodiment corresponds to the above terminal-side method embodiment, and each implementation process and implementation manner of the above method embodiment can be applied to this terminal embodiment and can achieve the same technical effect. Specifically, Figure 11 FIG. is a schematic hardware structure diagram of a terminal according to an embodiment of the present application.

[0393] The terminal 1100 includes, but is not limited to, at least some components such as a radio frequency unit 1101, a network module 1102, an audio output unit 1103, an input unit 1104, a sensor 1105, a display unit 1106, a user input unit 1107, an interface unit 1108, a memory 1109, and a processor 1110.

[0394] Those skilled in the art can understand that the terminal 1100 may further include a power supply (such as a battery) for supplying power to each component, and the power supply can be logically connected to the processor 1110 through a power management system, so as to implement functions such as management of charging, discharging, and power consumption management through the power management system. Figure 11 The terminal structure shown in does not constitute a limitation on the terminal. The terminal may include more or fewer components than shown in the figure, or combine certain components, or have different component arrangements, which will not be elaborated here.

[0395] It should be understood that in the embodiment of the present application, the input unit 1104 may include a graphics processing unit (GPU) 11041 and a microphone 11042. The graphics processor 11041 processes image data of a static picture or video obtained by an image capture device (such as a camera) in a video capture mode or an image capture mode. The display unit 1106 may include a display panel 11061, and the display panel 11061 may be configured in the form of a liquid crystal display, an organic light-emitting diode, etc. The user input unit 1107 includes at least one of a touch panel 11071 and other input devices 11072. The touch panel 11071 is also called a touch screen. The touch panel 11071 may include two parts: a touch detection device and a touch controller. The other input devices 11072 may include, but are not limited to, a physical keyboard, function keys (such as volume control keys, power on / off keys, etc.), a trackball, a mouse, and a joystick, which will not be elaborated here.

[0396] In an embodiment of the present application, after receiving downlink data from a network-side device, the radio frequency unit 1101 can transmit it to the processor 1110 for processing; in addition, the radio frequency unit 1101 can send uplink data to the network-side device. Generally, the radio frequency unit 1101 includes, but is not limited to, an antenna, an amplifier, a transceiver, a coupler, a low-noise amplifier, a duplexer, etc.

[0397] The memory 1109 can be used to store software programs or instructions and various data. The memory 1109 mainly includes a first storage area for storing programs or instructions and a second storage area for storing data. Among them, the first storage area can store an operating system, applications or instructions required for at least one function (such as a sound playback function, an image playback function, etc.). In addition, the memory 1109 can include a volatile memory or a non-volatile memory. Among them, the non-volatile memory can be a read-only memory (ROM), a programmable ROM (PROM), an erasable programmable ROM (EPROM), an electrically erasable programmable ROM (EEPROM), or a flash memory. The volatile memory can be a random access memory (RAM), a static RAM (SRAM), a dynamic RAM (DRAM), a synchronous DRAM (SDRAM), a double data rate SDRAM (DDR SDRAM), an enhanced SDRAM (ESDRAM), a synch link DRAM (SLDRAM), and a direct rambus RAM (DRRAM). The memory 1109 in the embodiment of the present application includes, but is not limited to, these and any other suitable types of memories.

[0398] The processor 1110 can include one or more processing units; optionally, the processor 1110 integrates an application processor and a modem processor. Among them, the application processor mainly processes operations related to the operating system, user interface, and applications, etc., and the modem processor mainly processes wireless communication signals, such as a baseband processor. It can be understood that the above-mentioned modem processor may not be integrated into the processor 1110.

[0399] Among them, the radio frequency unit 1101 is used to receive a first message sent by a network-side device; wherein, the first message includes information related to an artificial intelligence (AI) model, and the information related to the AI model includes at least one of the following: identification information of the AI model; file information of the AI model; attribute information of the AI model; download address of the AI model.

[0400] It can be understood that the implementation processes of the various implementation manners mentioned in this embodiment can refer to the relevant descriptions of the foregoing method embodiments and achieve the same or corresponding technical effects. To avoid repetition, they will not be elaborated here.

[0401] This application embodiment also provides a network-side device, including a processor and a communication interface, where the communication interface is used to send a first message to a terminal; wherein, the first message includes information related to an artificial intelligence (AI) model, and the information related to the AI model includes at least one of the following: identification information of the AI model; file information of the AI model; attribute information of the AI model; download address information of the AI model. This network-side device embodiment corresponds to the above-mentioned network-side device method embodiment. The various implementation processes and implementation manners of the above method embodiment can all be applied to this network-side device embodiment and can achieve the same technical effects.

[0402] Specifically, this application embodiment also provides a network-side device. As Figure 12 shown, the network-side device 1200 includes: a processor 1201, a network interface 1202, and a memory 1203. Among them, the network interface 1202 is, for example, a common public radio interface (CPRI).

[0403] Specifically, the network-side device 1200 of this application embodiment further includes: instructions or programs stored on the memory 1203 and executable on the processor 1201. The processor 1201 calls the instructions or programs in the memory 1203 to execute Figure 8 or Figure 9 the methods executed by the modules shown, and achieve the same technical effects. To avoid repetition, they will not be elaborated here.

[0404] This application embodiment also provides a readable storage medium, on which programs or instructions are stored. When the programs or instructions are executed by a processor, the various processes of the above information transmission method embodiment are implemented, and the same technical effects can be achieved. To avoid repetition, they will not be elaborated here.

[0405] Among them, the processor is the processor in the terminal described in the above embodiments. The readable storage medium includes computer-readable storage media, such as computer read-only memory ROM, random access memory RAM, magnetic disks, or optical discs, etc. In some examples, the readable storage medium may be a non-transitory readable storage medium.

[0406] Another embodiment of the present application provides a chip, which includes a processor and a communication interface. The communication interface is coupled to the processor. The processor is configured to run programs or instructions to implement each process of the above information transmission method embodiment, and can achieve the same technical effects. To avoid repetition, it will not be elaborated here.

[0407] It should be understood that the chip mentioned in the embodiments of the present application may also be referred to as a system-on-chip, system chip, chip system, or system-on-chip, etc.

[0408] Another embodiment of the present application provides a computer program / program product. The computer program / program product is stored in a storage medium. The computer program / program product is executed by at least one processor to implement each process of the above information transmission method embodiment, and can achieve the same technical effects. To avoid repetition, it will not be elaborated here.

[0409] Another embodiment of the present application also provides an information transmission system, including: a terminal and a network-side device. The terminal is configured to execute as Figure 3 and each process of the above method embodiments, and the network-side device is configured to execute as Figure 4 and Figure 5 and each process of the above method embodiments, and can achieve the same technical effects. To avoid repetition, it will not be elaborated here.

[0410] It should be noted that in this article, the term "including", "comprising", or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article, or device including a series of elements not only includes those elements, but also includes other elements not explicitly listed, or further includes elements inherent to such process, method, article, or device. Without further limitations, an element defined by the statement "including one..." does not exclude the existence of additional identical elements in the process, method, article, or device including that element. In addition, it should be pointed out that the methods and devices in the embodiments of the present application are not limited to performing functions in the order shown or discussed. They may also include performing functions in a substantially simultaneous manner or in the reverse order according to the functions involved. For example, the described methods may be performed in an order different from that described, and various steps may be added, omitted, or combined. Additionally, the features described with reference to certain examples may be combined in other examples.

[0411] Through the description of the above embodiments, those skilled in the art can clearly understand that the above-described example methods can be implemented by means of computer software products plus the necessary general hardware platforms, and of course, they can also be implemented by hardware. The computer software product is stored in a storage medium (such as ROM, RAM, magnetic disk, optical disk, etc.) and includes several instructions for causing a terminal or a network-side device to execute the methods described in various embodiments of the present application.

[0412] The embodiments of the present application have been described above in conjunction with the accompanying drawings. However, the present application is not limited to the above specific embodiments. The above specific embodiments are merely illustrative and not restrictive. Under the inspiration of the present application, those of ordinary skill in the art can also make many forms of embodiments without departing from the purpose of the present application and the scope protected by the claims. These embodiments are all within the protection scope of the present application.

Claims

1. An information transmission method, characterized in that, including: The terminal receives a first message sent by a network-side device; wherein, the first message includes information related to an artificial intelligence (AI) model, and the information related to the AI model includes at least one of the following: identification information of the AI model; file information of the AI model; attribute information of the AI model; download address of the AI model.

2. The method according to claim 1, wherein The terminal receiving the first message sent by the network-side device includes: The terminal receives the first message sent by the network-side device through control plane signaling.

3. The method according to claim 1 or 2, characterized in that, Before the terminal receives the first message sent by the network-side device, the method further includes: The terminal sends a first request message to a first network element; wherein, the first request message is used to request to obtain an AI model.

4. The method according to claim 3, wherein The first request message includes at least one of the following: first information, address information of a model storage network element, service type for using the model; wherein, the first information includes at least one of the following: first indication information for indicating that the terminal needs to obtain an AI model; second indication information for indicating that the AI model needs to be transmitted through the control plane; identification information of the AI model; description information of the AI model; identification information of the terminal; first capability information for indicating that the terminal supports obtaining an AI model through the control plane.

5. The method according to claim 4, wherein The description information of the AI model includes at least one of the following: service type indication information for indicating the service type that the requested model needs to provide; information about the object using the model; type of model input data, and the type of model input data includes at least one of the type of input data required for model inference and the type of input data required for model training; type of model inference result.

6. The method according to claim 4 or 5, characterized in that, The first information is carried in a model request bearer.

7. The method according to any one of claims 3 to 6, characterized in that The terminal sending the first request message to the first network element includes: The terminal sends the first request message to the first network element through control plane signaling.

8. The method according to any one of claims 1 to 7, characterized in that The method further includes: The terminal sends a first response message through control plane signaling, wherein the first response message is used to indicate whether the terminal has successfully received the information related to the AI model.

9. The method according to claim 8, wherein In the case where the first response message is used to indicate that the terminal fails to receive the information related to the AI model, the first response message includes first cause information, and the first cause information is used to indicate the reason for the terminal's failure to receive the information related to the AI model.

10. An information transmission method, characterized in that, including: The first network element sends a first message to the terminal; wherein, the first message includes information related to an artificial intelligence (AI) model, and the information related to the AI model includes at least one of the following: identification information of the AI model; file information of the AI model; attribute information of the AI model; download address information of the AI model.

11. The method according to claim 10, wherein The first network element sending the first message to the terminal includes: The first network element sends the first message to the terminal through control plane signaling.

12. The method according to claim 10 or 11, characterized in that Before the first network element sends the first message to the terminal, the method further includes: The first network element receives the first request message sent by the terminal, wherein the first request message is used to request to obtain an AI model; The first network element sends a second request message to the second network element, where the second request message is used to request to obtain an AI model, and the second request message is determined according to the first request message; The first network element receives a second response message sent by the second network element, where the second response message includes at least one of the following: an indication of whether to accept the AI model acquisition request, and relevant information about the AI model.

13. The method according to claim 12, wherein The first request message includes at least one of the following: first information, the address information of the model storage network element, and the service type using the model; Wherein, the first information includes at least one of the following: First indication information, which is used to indicate that the terminal needs to obtain an AI model; Second indication information, which is used to indicate that the AI model needs to be transmitted through the control plane; The identification information of the AI model; The description information of the AI model; The identification information of the terminal; First capability information, which is used to indicate that the terminal supports obtaining the AI model through the control plane.

14. The method according to claim 13, wherein The description information of the AI model includes at least one of the following: Service type indication information, which is used to indicate the service type that the requested model needs to provide; Information about the object using the model; The type of the model input data, and the type of the model input data includes at least one of the type of the input data required for model inference and the type of the input data required for model training; The type of the model inference result.

15. The method according to claim 13 or 14, characterized in that, The first information is carried in the model request bearer.

16. The method according to any one of claims 12 to 15, characterized in that, The first network element receives a first request message sent by the terminal, including: The first network element receives the first request message sent by the terminal through control plane signaling.

17. The method according to any one of claims 12 to 16, characterized in that Before the first network element sends the second request message to the second network element, the method further includes: The first network element selects a second network element that supports model transmission.

18. The method according to claim 17, characterized in that The first network element selects a second network element that supports model transmission, including: The first network element selects a second network element that supports model transmission according to second information, where the second information includes at least one of the following: the address information of the model storage network element, and the service type using the model.

19. The method according to claim 17, wherein The first request message includes the service type using the model; The first network element selects a second network element that supports model transmission, including: The first network element queries the Network Repository Function (NRF) according to the service type using the model to obtain the identification information or address information of the second network element.

20. The method according to any one of claims 12 to 19, characterized in that The second network element is a network element that manages the target service, and the AI model is a model related to the target service; or, the second network element is a network element that manages the AI model.

21. An information transmission method, characterized in that, Including: The second network element receives a second request message sent by the first network element, where the second request message is used to request to obtain an AI model; The second network element sends a second response message to the first network element, where the second response message includes at least one of the following: an indication of whether to accept the AI model acquisition request, and relevant information about the AI model.

22. The method according to claim 21, wherein The relevant information about the AI model includes at least one of the following: The identification information of the AI model; The file information of the AI model; The attribute information of the AI model; The download address information of the AI model.

23. The method according to claim 21 or 22, characterized in that, The second request message includes first information, where the first information includes at least one of the following: The first indication information is used to indicate that the terminal needs to obtain an AI model; The second indication information is used to indicate that the AI model needs to be transmitted through the control plane; The identification information of the AI model; The description information of the AI model; The identification information of the terminal; The first capability information is used to indicate that the terminal supports obtaining the AI model through the control plane.

24. The method according to claim 23, wherein The description information of the AI model includes at least one of the following: The service type indication information is used to indicate the service type that the requested model needs to provide; The information of the model usage object; The type of the model input data, and the type of the model input data includes at least one of the type of the input data required for model inference and the type of the input data required for model training; The type of the model inference result.

25. The method according to claim 23 or 24, characterized in that, The first information is carried in the model request bearer.

26. The method according to any one of claims 21 to 25, characterized in that In the case where the second response message indicates a rejection of the AI model acquisition request, the second response message further includes second cause information, and the second cause information is used to indicate the reason for rejecting the AI model acquisition request.

27. The method according to any one of claims 21 to 26, characterized in that, The second network element is a network element that manages the target service, and the AI model is a model related to the target service; or, the second network element is a network element that manages the AI model.

28. The method according to claim 27, wherein The second network element is a network element that manages the target service, and the method further includes: The second network element sends a third request message to a third network element, where the third network element is a network element that manages the AI model, and the third request message includes the identification information of the AI model, or the third request message includes the identification information of the AI model and the identification information of the terminal; The second network element receives a third response message sent by the third network element, where the third response message includes the related information of the AI model.

29. An information transmission device, characterized in that, Applied to the terminal, it includes: The first receiving module is used to receive the first message sent by the network-side device; Wherein, the first message includes the related information of the artificial intelligence (AI) model, and the related information of the AI model includes at least one of the following: The identification information of the AI model; The file information of the AI model; The attribute information of the AI model; The download address of the AI model.

30. The device according to claim 29, wherein The first receiving module is specifically used for: Receiving the first message sent by the network-side device through the control plane signaling.

31. The device according to claim 29 or 30, characterized in that, The device further includes: The first sending module is used to send a first request message to a first network element before receiving the first message sent by the network-side device; Wherein, the first request message is used to request to obtain the AI model.

32. An information transmission device, characterized in that, Applied to the first network element, it includes: The second sending module is used to send a first message to the terminal; Wherein, the first message includes the related information of the artificial intelligence (AI) model, and the related information of the AI model includes at least one of the following: The identification information of the AI model; The file information of the AI model; The attribute information of the AI model; The download address information of the AI model.

33. The device according to claim 32, characterized in that, The second sending module is specifically used for: Sending the first message to the terminal through the control plane signaling.

34. The device according to claim 32 or 33, characterized in that, The device further includes: The second receiving module is used to receive the first request message sent by the terminal before sending the first message to the terminal, where the first request message is used to request to obtain the AI model; A third sending module, configured to send a second request message to a second network element, where the second request message is used to request to obtain an AI model, and the second request message is determined according to the first request message; A third receiving module, configured to receive a second response message sent by the second network element, where the second response message includes at least one of the following: an indication of whether to accept the AI model acquisition request, and related information of the AI model.

35. An information transmission device, characterized in that, Applied to a second network element, including: A fourth receiving module, configured to receive a second request message sent by a first network element, where the second request message is used to request to obtain an AI model; A fourth sending module, configured to send a second response message to the first network element, where the second response message includes at least one of the following: an indication of whether to accept the AI model acquisition request, and related information of the AI model.

36. A terminal, characterized in that, Comprising a processor and a memory, where the memory stores a program or instruction that can run on the processor, and when the program or instruction is executed by the processor, the steps of the information transmission method according to any one of claims 1 to 9 are implemented.

37. A network-side device, characterized in that, Comprising a processor and a memory, where the memory stores a program or instruction that can run on the processor, and when the program or instruction is executed by the processor, the steps of the information transmission method according to any one of claims 10 to 20 are implemented.

38. A network-side device, characterized in that, Comprising a processor and a memory, where the memory stores a program or instruction that can run on the processor, and when the program or instruction is executed by the processor, the steps of the information transmission method according to any one of claims 21 to 28 are implemented.

39. A readable storage medium, characterized in that, A program or instruction is stored on the readable storage medium, and when the program or instruction is executed by a processor, the steps of the information transmission method according to any one of claims 1 to 9 are implemented, or the steps of the information transmission method according to any one of claims 10 to 20 are implemented, or the steps of the information transmission method according to any one of claims 21 to 28 are implemented.

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