An AI model registration method / device / equipment and storage medium

Abstract

The present disclosure provides an AI model registration method / apparatus / device / storage medium, which belongs to the technical field of communication. A terminal device sends AI model information corresponding to an AI model deployed by the terminal device to a network side device. Therefore, the present disclosure provides an AI model registration method, so that the AI model deployed by the terminal device is registered on the network side device, so that the network side device knows the model information of the AI model deployed by the terminal device, and then facilitates the network side device to subsequently manage or monitor the AI model deployed on the terminal device.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the technical field of communication, and particularly relates to a registration method / apparatus / device of an AI model and a storage medium. BACKGROUND

[0002] With the continuous development of AI (Artificial Intelligent) technology, AI models are widely applied in multiple fields. Among them, an AI model trained through a terminal device or an external server of the terminal device is deployed on the terminal device. In the related art, the terminal device needs to register the AI model to a network side device, so that the network side device knows the AI model information of the terminal device, thereby facilitating the network side device to manage or monitor the AI model deployed on the terminal device.

[0003] Therefore, there is an urgent need for a registration method of an AI model. SUMMARY

[0004] The registration method / apparatus / device of an AI model and the storage medium provided by the present disclosure are used for the registration of an AI model.

[0005] In a first aspect, an embodiment of the present disclosure provides a registration method of an AI model, applied to a terminal device, and the method comprises the following steps.

[0006] sending, to a network side device, AI model information corresponding to an AI model deployed by the terminal device.

[0007] In a second aspect, an embodiment of the present disclosure provides a registration method of an AI model, applied to a network side device, and the method comprises the following steps.

[0008] receiving, by the network side device, AI model information corresponding to an AI model deployed by a terminal device, the AI model information being sent by the terminal device.

[0009] In a third aspect, an embodiment of the present disclosure provides a communication apparatus, configured in a terminal device, comprising:

[0010] a sending module, configured to send, to a network side device, AI model information corresponding to an AI model deployed by the terminal device.

[0011] In a fourth aspect, an embodiment of the present disclosure provides a communication apparatus, configured in a network side device, comprising:

[0012] a receiving module, configured to receive AI model information corresponding to an AI model deployed by a terminal device, the AI model information being sent by the terminal device.

[0013] In a fifth aspect, the embodiments of the present disclosure provide a communication device, which comprises a processor, and the processor executes a method in the first aspect when invoking a computer program in a memory.

[0014] In a sixth aspect, the embodiments of the present disclosure provide a communication device, which comprises a processor, and the processor executes a method in the second aspect when invoking a computer program in a memory.

[0015] In a seventh aspect, the embodiments of the present disclosure provide a communication device, which comprises a processor and a memory, and the memory stores a computer program; the processor executes the computer program stored in the memory, so that the communication device executes the method in the first aspect.

[0016] In an eighth aspect, the embodiments of the present disclosure provide a communication device, which comprises a processor and a memory, and the memory stores a computer program; the processor executes the computer program stored in the memory, so that the communication device executes the method in the second aspect.

[0017] In a ninth aspect, the embodiments of the present disclosure provide a communication device, which comprises a processor and an interface circuit, the interface circuit is configured to receive code instructions and transmit the code instructions to the processor, and the processor is configured to execute the code instructions, so that the device executes the method in the first aspect.

[0018] In a tenth aspect, the embodiments of the present disclosure provide a communication device, which comprises a processor and an interface circuit, the interface circuit is configured to receive code instructions and transmit the code instructions to the processor, and the processor is configured to execute the code instructions, so that the device executes the method in the second aspect.

[0019] In an eleventh aspect, the embodiments of the present disclosure provide a communication system, which comprises the communication device in the third aspect to the communication device in the fourth aspect, or the communication device in the fifth aspect to the communication device in the sixth aspect, or the communication device in the seventh aspect to the communication device in the eighth aspect, or the communication device in the ninth aspect to the communication device in the tenth aspect.

[0020] In a twelfth aspect, the embodiments of the present disclosure provide a computer readable storage medium, which is configured to store instructions for the network device, and the instructions are configured to make the terminal device execute the method in any one of the first aspect to the third aspect when the instructions are executed.

[0021] In a thirteenth aspect, the embodiments of the present disclosure further provide a computer program product comprising a computer program, and the computer program product is configured to make a computer execute the method in any one of the first aspect to the second aspect when the computer program product is executed on the computer.

[0022] In a fourteenth aspect, the present disclosure provides a chip system, which includes at least one processor and an interface for supporting network devices to implement functions involved in the method of any one of the first aspect to the second aspect, such as determining or processing at least one of the data and information involved in the above method. In a possible design, the chip system further includes a memory, and the memory is configured to store computer programs and data necessary for the source secondary node. The chip system can be composed of a chip, or can include a chip and other discrete devices.

[0023] In a fifteenth aspect, the present disclosure provides a computer program which, when running on a computer, causes the computer to perform the method of any one of the first aspect to the second aspect. BRIEF DESCRIPTION OF DRAWINGS

[0024] The above and / or additional aspects and advantages of the present application will become apparent and more readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings, in which:

[0025] Figure 1 A schematic diagram of an architecture of a communication system provided by an embodiment of the present disclosure is shown in FIG. 1.

[0026] Figure 2 A schematic diagram of a registration method of an AI model provided by another embodiment of the present disclosure is shown in FIG. 2.

[0027] Figure 3 A schematic diagram of a registration method of an AI model provided by another embodiment of the present disclosure is shown in FIG. 2.

[0028] Figure 4a A schematic diagram of a registration method of an AI model provided by another embodiment of the present disclosure is shown in FIG. 2.

[0029] Figure 4b A schematic diagram of a registration method of an AI model provided by another embodiment of the present disclosure is shown in FIG. 2.

[0030] Figure 5 A schematic diagram of a registration method of an AI model provided by another embodiment of the present disclosure is shown in FIG. 2.

[0031] Figure 6 A schematic diagram of a registration method of an AI model provided by another embodiment of the present disclosure is shown in FIG. 2.

[0032] Figure 7 A schematic diagram of a registration method of an AI model provided by another embodiment of the present disclosure is shown in FIG. 2.

[0033] Figure 8 A schematic diagram of a registration method of an AI model provided by another embodiment of the present disclosure is shown in FIG. 2.

[0034] Figure 9 A flowchart of a registration method of an AI model according to another embodiment of the present disclosure;

[0035] Figure 10 A flowchart of a registration method of an AI model according to another embodiment of the present disclosure;

[0036] Figure 11a A flowchart of a registration method of an AI model according to another embodiment of the present disclosure;

[0037] Figure 11b A flowchart of a registration method of an AI model according to another embodiment of the present disclosure;

[0038] Figure 12 A structural diagram of a communication device according to an embodiment of the present disclosure;

[0039] Figure 13 A structural diagram of a communication device according to another embodiment of the present disclosure;

[0040] Figure 14 A block diagram of a user equipment according to an embodiment of the present disclosure;

[0041] Figure 15 A block diagram of a network side equipment according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0042] The exemplary embodiments will be described in detail herein with reference to the attached drawings. The following description is made with reference to the accompanying drawings in which like reference numerals refer to like elements, and the use of the same reference numerals in different drawings indicates similar or like elements unless otherwise indicated. The following exemplary embodiments described are not representative of all embodiments consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with some aspects of the present disclosure as detailed in the appended claims.

[0043] The terminology used in the present disclosure is for the purpose of describing particular embodiments only and is not intended to be limiting of the present disclosure. As used in the present disclosure and the appended claims, the singular forms "a," "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will also be understood that the term "and / or" as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items.

[0044] It should be understood that although the terms first, second, third, etc., may be used to describe various information in embodiments of this disclosure, such information should not be limited to these terms. These terms are only used to distinguish information of the same type from one another. For example, first information may also be referred to as second information without departing from the scope of embodiments of this disclosure, and similarly, second information may also be referred to as first information. Depending on the context, the words “if” and “suppose” as used herein may be interpreted as “when”, “when”, or “in response to a determination”.

[0045] Embodiments of this disclosure are described in detail below, examples of which are illustrated in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this disclosure, and should not be construed as limiting this disclosure.

[0046] To facilitate understanding, the terminology used in this application will be introduced first.

[0047] 1. Artificial Intelligence (AI)

[0048] AI is a new technical science that studies and develops theories, methods, technologies, and application systems for simulating, extending, and expanding human intelligence.

[0049] The various network elements / functions involved in the embodiments of this disclosure can be either independent hardware devices or functions implemented by computer code within hardware devices. This disclosure does not limit them.

[0050] Please see Figure 1 , Figure 1 This is a schematic diagram of the architecture of a communication system provided in an embodiment of the present disclosure. The communication system may include, but is not limited to, a network device and a terminal device. Figure 1 The number and form of devices shown are for illustrative purposes only and do not constitute a limitation on the embodiments of this disclosure. In actual applications, two or more network devices and two or more terminal devices may be included. Figure 1 The communication system shown is an example including a network device 11 and a terminal device 12.

[0051] It should be noted that the technical solutions of this disclosure can be applied to various communication systems. For example, Long Term Evolution (LTE) systems, 5th Generation (5G) mobile communication systems, 5G New Radio (NR) systems, or other future new mobile communication systems.

[0052] The network device 11 in the embodiments of the present disclosure is an entity for transmitting or receiving signals on the network side. For example, the network device 11 can be an evolved NodeB (eNB), a transmission reception point (TRP), a next generation NodeB (gNB) in an NR system, a base station in other future mobile communication systems, or an access node in a wireless fidelity (WiFi) system, and the like. The embodiments of the present disclosure do not limit the specific technology and specific device form adopted by the network device. The network device provided by the embodiments of the present disclosure can be composed of a central unit (CU) and a distributed unit (DU), wherein the CU can also be referred to as a control unit (control unit). The CU-DU structure can split the protocol layer of the network device, for example, the base station, and the functions of part of the protocol layer are controlled by the CU, and the functions of the remaining part or all of the protocol layer are distributed in the DU and controlled by the CU.

[0053] The terminal device 12 in the embodiments of the present disclosure is an entity for receiving or transmitting signals on the user side, such as a mobile phone. The terminal device can also be referred to as a terminal, a user equipment (UE), a mobile station (MS), a mobile terminal (MT), and the like. The terminal device can be a car, a smart car, a mobile phone, a wearable device, a tablet computer (Pad), a computer with wireless transceiver function, a virtual reality (VR) terminal device, an augmented reality (AR) terminal device, a wireless terminal device in industrial control, a wireless terminal device in self-driving, a wireless terminal device in remote medical surgery, a wireless terminal device in smart grid, a wireless terminal device in transportation safety, a wireless terminal device in smart city, a wireless terminal device in smart home, and the like. The embodiments of the present disclosure do not limit the specific technology and specific device form adopted by the terminal device.

[0054] It can be understood that the communication system described in the embodiments of the present disclosure is for more clearly illustrating the technical solutions of the embodiments of the present disclosure, and does not constitute a limitation on the technical solutions provided by the embodiments of the present disclosure. Those skilled in the art can know that, with the evolution of system architecture and the appearance of new business scenarios, the technical solutions provided by the embodiments of the present disclosure are also applicable to similar technical problems.

[0055] The method and apparatus for registering an AI model and the storage medium provided by the embodiments of the present disclosure are described in detail below with reference to the accompanying drawings.

[0056] Figure 2 The flowchart of the method for registering an AI model provided by another embodiment of the present disclosure, wherein the method is executed by a terminal device, is as shown in Figure 2 The method for registering an AI model can include the following steps:

[0057] Step 201: sending AI model information corresponding to an AI model deployed by a terminal device to a network side device.

[0058] In one embodiment of the present disclosure, the AI model information described above can include an identifier corresponding to the AI model.

[0059] Specifically, in one embodiment of the present disclosure, at least one AI model can be predefined, each predefined AI model has a corresponding predefined model identifier, different AI models can correspond to different AI model information, the terminal device can send the identifier corresponding to the deployed AI model to the network side device, so that the network side device can determine the corresponding predefined AI model through the received AI model identifier, and determine the corresponding AI model information based on the predefined AI model, thereby completing the registration of the AI model deployed by the terminal device on the network side device. In one embodiment of the present disclosure, the model identifier corresponding to the AI model described above can be generated by the terminal device. For example, the terminal server and the network side device can negotiate to predefine a series of AI models or predefine a series of AI models based on a protocol standard, and assign a model identifier to each AI model, and the terminal reports the AI model information by reporting the model identifier. In some embodiments, in response to the terminal sending the model information of the AI model of the terminal device to the network side device, the network device can assign a model ID (Identity Document, serial number) to the AI model reported by the terminal device. In some embodiments, the terminal device also reports a model identifier of an AI model to the network side device, at this time the network side device can not assign a model ID to the AI model, or can assign another model ID to the AI model.

[0060] In an embodiment of the present disclosure, the at least one AI model can be predefined by the terminal device and the network-side device. In another embodiment of the present disclosure, the at least one AI model can be predefined based on a protocol standard.

[0061] In an embodiment of the present disclosure, the model information of the predefined AI model can include at least one of the following information:

[0062] function information of the AI model;

[0063] application range information of the AI model;

[0064] input or output information of the AI model;

[0065] performance information that can be achieved by the AI model;

[0066] structure information of the AI model.

[0067] It should be noted that, in an embodiment of the present disclosure, the network-side device can be a base station or a core network node.

[0068] In summary, in the AI model registration method provided by the embodiments of the present disclosure, the terminal device sends AI model information corresponding to the AI model deployed by the terminal device to the network-side device. That is, the terminal device sends the AI model information corresponding to the AI model deployed by the terminal device to the network-side device, thereby completing the registration of the AI model deployed by the terminal device on the network-side device, so that the network-side device knows the model information of the AI model deployed by the terminal device, and then facilitates the network-side device to subsequently manage or monitor the AI model deployed on the terminal device.

[0069] Figure 3 FIG. 1 shows a flowchart of an AI model registration method provided by another embodiment of the present disclosure, which is executed by a terminal device. As shown in FIG. 1, the AI model registration method can include the following steps: Figure 3

[0070] Step 301: sending description information of an AI model to a network-side device.

[0071] In an embodiment of the present disclosure, the description information of the AI model can include at least one of the following information:

[0072] function information of the AI model;

[0073] application range information of the AI model;

[0074] input or output information of the AI model;

[0075] ​Performance information that can be achieved by the AI model;

[0076] Structure information of the AI model.

[0077] In an embodiment of the present disclosure, the terminal device can send the description information of the AI model to the network side device, so that the terminal device completes the registration of the AI model deployed by the terminal device on the network side device, so that the network side device knows the model information of the AI model deployed by the terminal device, and further so that the network side device subsequently manages or monitors the AI model deployed on the terminal device.

[0078] In summary, in the AI model registration method provided by the embodiments of the present disclosure, the terminal device sends the AI model information corresponding to the AI model deployed by the terminal device to the network side device. That is, in the present disclosure, the terminal device sends the AI model information corresponding to the AI model deployed by the terminal device to the network side device, so that the terminal device completes the registration of the AI model deployed by the terminal device on the network side device, so that the network side device knows the model information of the AI model deployed by the terminal device, and further facilitates the network side device to subsequently manage or monitor the AI model deployed on the terminal device.

[0079] Figure 4a FIG. 1 shows a flowchart of an AI model registration method provided by another embodiment of the present disclosure, which is performed by a terminal device. As shown in FIG. 1, the AI model registration method can include the following steps: Figure 4a

[0080] Step 401a, in response to the terminal device deploying an AI model, the terminal device actively reports the AI model information corresponding to the deployed AI model to the network side device.

[0081] In an embodiment of the present disclosure, if the terminal device deploys an AI model, the terminal device can actively send the AI model information corresponding to the AI model deployed by the terminal device to the network side device, so that the terminal device completes the registration of the AI model deployed by the terminal device on the network side device, so that the network side device knows the AI model information of the AI model deployed by the terminal device.

[0082] For detailed introduction of the AI model information, reference can be made to the related introduction in the above embodiments, which will not be repeated here.

[0083] ​In summary, in the AI model registration method provided by the embodiments of the present disclosure, the terminal device sends AI model information corresponding to the AI model deployed by the terminal device to the network side device. That is, the terminal device completes the registration of the AI model deployed by the terminal device on the network side device by sending the AI model information corresponding to the AI model deployed by the terminal device to the network side device, so that the network side device knows the model information of the AI model deployed by the terminal device, and then facilitates the network side device to subsequently manage or monitor the AI model deployed on the terminal device.

[0084] Figure 4b A flowchart of an AI model registration method provided by another embodiment of the present disclosure is shown in FIG. 8. The method is performed by a terminal device. As shown in FIG. 8, the AI model registration method can include the following steps: Figure 4b

[0085] Step 401b, receiving the reporting message sent by the network side device.

[0086] Step 402b, reporting the AI model information corresponding to the deployed AI model to the network side device.

[0087] In one embodiment of the present disclosure, in response to the terminal device receiving the reporting message sent by the network side device, the terminal device reports the AI model information corresponding to the deployed AI model to the network side device.

[0088] Specifically, in one embodiment of the present disclosure, if the terminal device receives the reporting message sent by the network side device, the terminal device reports the AI model information corresponding to the AI model deployed by the terminal device to the network side device, so that the terminal device completes the registration of the AI model deployed by the terminal device on the network side device, so that the network side device knows the AI model information of the AI model deployed by the terminal device, and then facilitates the network side device to subsequently manage or monitor the AI model deployed on the terminal device.

[0089] For detailed introduction of the AI model information, reference can be made to the related introduction in the above embodiments, which will not be repeated here.

[0090] In summary, in the AI model registration method provided by the embodiments of the present disclosure, the terminal device sends AI model information corresponding to the AI model deployed by the terminal device to the network side device. That is, the terminal device completes the registration of the AI model deployed by the terminal device on the network side device by sending the AI model information corresponding to the AI model deployed by the terminal device to the network side device, so that the network side device knows the model information of the AI model deployed by the terminal device, and then facilitates the network side device to subsequently manage or monitor the AI model deployed on the terminal device. ​

[0091] Figure 5 A flowchart of a registration method of an AI model provided for another embodiment of the present disclosure, which is executed by a terminal device, is shown in FIG. 5. As shown in FIG. 5, the registration method of the AI model can include the following steps: Figure 5

[0092] Step 501: receiving AI operations supported by a network-side device sent by the network-side device.

[0093] In an embodiment of the present disclosure, the AI operations supported by the network-side device received by the terminal device sent by the network-side device include AI-based CSI (Channel State Information) enhancement and AI-based beam management.

[0094] Step 502: determining to report AI models corresponding to the AI operations supported by the network-side device to the network-side device according to the AI operations supported by the network-side device.

[0095] In an embodiment of the present disclosure, after the terminal device receives the AI operations supported by the network-side device sent by the network-side device through step 501, the terminal device can determine AI models supporting the AI operations in the AI models deployed by the terminal device according to the AI operations supported by the network-side device, and report AI model information of the AI models corresponding to the AI operations to the network-side device.

[0096] In an embodiment of the present disclosure, if the AI operations supported by the network-side device received by the terminal device sent by the network-side device include AI-based CSI enhancement and AI-based beam management, the terminal device reports AI model information corresponding to AI models supporting AI-based CSI and AI-based beam management in the AI models deployed by the terminal device to the network-side device.

[0097] For details of other contents of the embodiments, reference can be made to the related descriptions in the above embodiments, which will not be repeated here.

[0098] In summary, in the registration method of the AI model provided in the embodiments of the present disclosure, the terminal device sends AI model information corresponding to the AI models deployed by the terminal device to the network-side device. That is, the terminal device sends the AI model information corresponding to the AI models deployed by the terminal device to the network-side device, thereby completing the registration of the AI models deployed by the terminal device on the network-side device, so that the network-side device knows the model information of the AI models deployed by the terminal device, and further facilitates the network-side device to manage or monitor the AI models deployed on the terminal device in the future.

[0099] ​Figure 6 A flowchart of an AI model registration method provided by another embodiment of the present disclosure is shown in FIG. 7. The method is performed by a terminal device, and can include the following steps: Figure 6 As shown in FIG. 7, the AI model registration method can include the following steps:

[0100] Step 601: Receive a model identifier allocated by a network-side device according to AI model information.

[0101] In one embodiment of the present disclosure, when the terminal device sends AI model information corresponding to an AI model deployed by the terminal device to the network-side device, the terminal device can receive a model identifier allocated by the network-side device according to the AI model information. In one embodiment of the present disclosure, the model identifier can be a model ID.

[0102] In one embodiment of the present disclosure, when the terminal device sends AI model information corresponding to an AI model deployed by the terminal device to the network-side device, the terminal device can receive a model identifier allocated by the network-side device according to the AI model information. In one embodiment of the present disclosure, the model identifier can be a model ID.

[0103] For details of other contents of the embodiments, please refer to the relevant descriptions in the above embodiments, which will not be repeated here.

[0104] In summary, in the AI model registration method provided by the embodiments of the present disclosure, the terminal device sends AI model information corresponding to an AI model deployed by the terminal device to the network-side device. That is, the terminal device sends AI model information corresponding to an AI model deployed by the terminal device to the network-side device, thereby completing the registration of the AI model deployed by the terminal device on the network-side device, so that the network-side device knows the model information of the AI model deployed by the terminal device, and then facilitates the network-side device to manage or monitor the AI model deployed on the terminal device.

[0105] Figure 7 A flowchart of an AI model registration method provided by another embodiment of the present disclosure is shown in FIG. 7. The method is performed by a terminal device, and can include the following steps: Figure 7 As shown in FIG. 7, the AI model registration method can include the following steps:

[0106] Step 701: Receive AI model information corresponding to an AI model deployed by a terminal device, which is sent by the terminal device.

[0107] In one embodiment of the present disclosure, the AI model information can include an identifier corresponding to the AI model.

[0108] Specifically, in one embodiment of the present disclosure, at least one AI model can be predefined, each predefined AI model has a corresponding predefined model identifier, different AI models can correspond to different AI model information, and the network side device can determine the corresponding predefined AI model by receiving the identifier corresponding to the AI model deployed by the terminal device, and determine the corresponding AI model information based on the predefined AI model, thereby completing the registration of the AI model deployed by the terminal device on the network side device. Wherein, in one embodiment of the present disclosure, the identifier corresponding to the AI model can be generated by the terminal device.

[0109] Wherein, in one embodiment of the present disclosure, at least one AI model can be predefined by the terminal device and the network side device. In another embodiment of the present disclosure, at least one AI model can be predefined based on a protocol standard.

[0110] In addition, in one embodiment of the present disclosure, the model information of the predefined AI model can include at least one of the following information:

[0111] Function information of the AI model;

[0112] Application range information of the AI model;

[0113] Input or output information of the AI model;

[0114] Performance information that can be achieved by the AI model;

[0115] Structure information of the AI model.

[0116] It should be noted that, in one embodiment of the present disclosure, the network side device can be a base station or a core network node.

[0117] For detailed introduction of other contents in the present embodiment, please refer to the relevant introduction in the above-mentioned embodiments, which will not be repeated here.

[0118] In summary, in the AI model registration method provided by the embodiments of the present disclosure, the network side device receives the AI model information corresponding to the AI model deployed by the terminal device. That is, the terminal device completes the registration of the AI model deployed by the terminal device on the network side device by sending the AI model information corresponding to the AI model deployed by the terminal device to the network side device, so that the network side device knows the model information of the AI model deployed by the terminal device, and then facilitates the network side device to manage or monitor the AI model deployed on the terminal device in the future.

[0119] Figure 8A flowchart of a registration method of an AI model provided by an embodiment of the present disclosure is shown in FIG. 8. The method is performed by a network-side device. As shown in FIG. 8, the registration method of the AI model can include the following steps: Figure 8

[0120] Step 801: Receive description information of an AI model sent by a terminal device.

[0121] In an embodiment of the present disclosure, the description information of the AI model can include at least one of the following:

[0122] function information of the AI model;

[0123] application range information of the AI model;

[0124] input or output information of the AI model;

[0125] performance information that can be achieved by the AI model;

[0126] structure information of the AI model.

[0127] In an embodiment of the present disclosure, the network-side device can know the model information of the AI model deployed by the terminal device by receiving the description information of the AI model sent by the terminal device, thereby facilitating the network-side device to subsequently manage or monitor the AI model deployed on the terminal device.

[0128] For details of other contents in the present embodiment, reference can be made to the relevant descriptions in the above embodiments, which will not be repeated here.

[0129] In summary, in the registration method of the AI model provided by the embodiments of the present disclosure, the network-side device receives AI model information corresponding to an AI model deployed by a terminal device sent by the terminal device. That is, in the present disclosure, the terminal device completes the registration of the AI model deployed by the terminal device on the network-side device by sending AI model information corresponding to the AI model deployed by the terminal device to the network-side device, so that the network-side device knows the model information of the AI model deployed by the terminal device, and then facilitates the network-side device to subsequently manage or monitor the AI model deployed on the terminal device.

[0130] Figure 9 A flowchart of a registration method of an AI model provided by another embodiment of the present disclosure is shown in FIG. 9. The method is performed by a network-side device. As shown in FIG. 9, the registration method of the AI model can include the following steps: Figure 9

[0131] Step 901: Send a reporting message to a terminal device, the reporting message being used to instruct the terminal device to report AI model information corresponding to an AI model. ​​

[0132] Among one embodiment of the present disclosure, the network-side device can indicate the terminal device to report the AI model information corresponding to the AI model by sending a reporting message to the terminal device. When the terminal device receives the reporting message sent by the network-side device, the terminal device sends the AI model information corresponding to the AI model deployed by the terminal device to the network-side device, thereby completing the registration of the AI model deployed by the terminal device on the network-side device, so that the network-side device knows the model information of the AI model deployed by the terminal device, and then facilitates the network-side device to subsequently manage or monitor the AI model deployed on the terminal device.

[0133] For details of other contents in the present embodiment, please refer to the relevant description in the above embodiments, which will not be repeated here.

[0134] In summary, in the AI model registration method provided by the embodiments of the present disclosure, the network-side device receives the AI model information corresponding to the AI model deployed by the terminal device sent by the terminal device. That is, the terminal device sends the AI model information corresponding to the AI model deployed by the terminal device to the network-side device, thereby completing the registration of the AI model deployed by the terminal device on the network-side device, so that the network-side device knows the model information of the AI model deployed by the terminal device, and then facilitates the network-side device to subsequently manage or monitor the AI model deployed on the terminal device.

[0135] Figure 10 For another embodiment of the present disclosure, a flowchart of an AI model registration method is provided, which is executed by a network-side device. As shown in Figure 10 The AI model registration method can include the following steps:

[0136] Step 1001, sending the AI operation supported by the network-side device to the terminal device.

[0137] For example, in one embodiment of the present disclosure, the AI operation supported by the network-side device and sent by the network-side device to the terminal device includes AI-based CSI (Channel State Information) enhancement and AI-based beam management.

[0138] In addition, in one embodiment of the present disclosure, the AI model reported by the terminal device to the network-side device is generated according to the AI operation supported by the network-side device.

[0139] Specifically, in one embodiment of the present disclosure, after the network-side device sends the AI operation supported by the network-side device to the terminal device, the terminal device can determine the AI model supporting the AI operation in the AI model deployed by the terminal device according to the AI operation supported by the network-side device, and report the AI model information of the AI model corresponding to the AI operation to the network-side device.

[0140] For details of other contents in the present embodiment, reference can be made to the related descriptions in the above embodiments, which will not be repeated here.

[0141] In summary, in the AI model registration method provided by the embodiments of the present disclosure, the network-side device receives the AI model information corresponding to the AI model deployed by the terminal device sent by the terminal device. That is, the terminal device completes the registration of the AI model deployed by the terminal device on the network-side device by sending the AI model information corresponding to the AI model deployed by the terminal device to the network-side device, so that the network-side device knows the model information of the AI model deployed by the terminal device, and then facilitates the network-side device to manage or monitor the AI model deployed on the terminal device in the future.

[0142] Figure 11a For another embodiment of the present disclosure, a flowchart of an AI model registration method is provided, which is executed by a network-side device. As shown in Figure 11a The AI model registration method can include the following steps:

[0143] Step 1101a, sending a model identifier allocated according to the AI model information to the terminal device.

[0144] In one embodiment of the present disclosure, when the terminal device sends the AI model information corresponding to the AI model deployed by the terminal device to the network-side device, the network-side device can allocate a model identifier to the AI model according to the AI model information of the AI model sent by the terminal device. In one embodiment of the present disclosure, the above-mentioned model identifier can be a model ID.

[0145] In one embodiment of the present disclosure, when the terminal device sends the AI model information corresponding to the AI model deployed by the terminal device to the network-side device, the network-side device can not allocate a model identifier to the AI model, or the network-side device allocates another different model identifier to the AI model for distinction.

[0146] For details of other contents in the present embodiment, reference can be made to the related descriptions in the above embodiments, which will not be repeated here.

[0147] To sum up, in the AI model registration method provided by the embodiments of the present disclosure, the network side device receives the AI model information corresponding to the AI model deployed by the terminal device sent by the terminal device. That is, the terminal device completes the registration of the AI model deployed by the terminal device on the network side device by sending the AI model information corresponding to the AI model deployed by the terminal device to the network side device, so that the network side device knows the model information of the AI model deployed by the terminal device, and then facilitates the network side device to subsequently manage or monitor the AI model deployed on the terminal device.

[0148] Figure 11b A flowchart of an AI model registration method provided by another embodiment of the present disclosure is shown in FIG. 11b. The method is executed by a network side device. As shown in FIG. 11b, the AI model registration method can include the following steps: Figure 11b

[0149] Step 1101b: When the terminal device performs cell switching, the target base station acquires the AI model information of the AI model supported by the terminal device.

[0150] In an embodiment of the present disclosure, if the terminal device has completed the registration of the AI model on the network side device, when the terminal device performs cell switching, the target base station corresponding to the target cell to which the terminal device switches needs to acquire the AI model information of the AI model supported by the terminal device, so as to complete the registration of the AI model deployed by the terminal device on the target base station, thereby not needing to complete the registration by interacting with the target base station again.

[0151] In addition, in an embodiment of the present disclosure, when the network side device on which the terminal device completes the registration of the AI model is different, the method of acquiring the AI model information of the AI model supported by the terminal device by the target base station is also different.

[0152] Specifically, in an embodiment of the present disclosure, if the terminal device completes the registration of the AI model on the source base station corresponding to the source cell, when the terminal device performs cell switching, the source base station can send the AI model information of the AI model deployed by the terminal device to the target base station corresponding to the target cell of the terminal device, and the method of acquiring the AI model information of the AI model supported by the terminal device by the target base station can include: the target base station receives the AI model information of the AI model supported by the terminal device sent by the source base station.

[0153] In addition, in another embodiment of the present disclosure, if the terminal device completes the registration of the AI model on the core network node, when the terminal device performs cell switching, the method of acquiring the AI model information of the AI model supported by the terminal device by the target base station can include: the target base station acquires the AI model information of the AI model supported by the terminal device from the core network node. ​

[0154] For details of other contents in this embodiment, please refer to the relevant description in the above embodiments, which will not be repeated here.

[0155] In summary, in the AI model registration method provided by the embodiments of the present disclosure, the network side device receives the AI model information corresponding to the AI model deployed by the terminal device sent by the terminal device. That is, in the present disclosure, the terminal device completes the registration of the AI model deployed by the terminal device on the network side device by sending the AI model information corresponding to the AI model deployed by the terminal device to the network side device, so that the network side device knows the model information of the AI model deployed by the terminal device, and then facilitates the network side device to subsequently manage or monitor the AI model deployed on the terminal device.

[0156] Figure 12 For a structure schematic diagram of a communication device provided by an embodiment of the present disclosure, as shown in Figure 12 The device can include:

[0157] The sending module 1201 is configured to send the AI model information corresponding to the AI model deployed by the terminal device to the network side device.

[0158] In summary, in the communication device provided by the embodiments of the present disclosure, the terminal device sends the AI model information corresponding to the AI model deployed by the terminal device to the network side device. That is, in the present disclosure, the terminal device completes the registration of the AI model deployed by the terminal device on the network side device by sending the AI model information corresponding to the AI model deployed by the terminal device to the network side device, so that the network side device knows the model information of the AI model deployed by the terminal device, and then facilitates the network side device to subsequently manage or monitor the AI model deployed on the terminal device.

[0159] Optionally, in an embodiment of the present disclosure, the AI model information includes an identifier corresponding to the AI model.

[0160] Optionally, in an embodiment of the present disclosure, at least one AI model is predefined, each predefined AI model has a corresponding predefined model identifier, and the model information of the predefined AI model includes at least one of at least the following information:

[0161] function information of the AI model;

[0162] application range information of the AI model;

[0163] input or output information of the AI model;

[0164] performance information that the AI model can achieve;

[0165] structure information of the AI model.

[0166] Optionally, in an embodiment of the present disclosure, the identifier corresponding to the AI model is generated by the terminal device.

[0167] Optionally, in an embodiment of the present disclosure, the apparatus is further configured to:

[0168] send, to the network-side device, description information of the AI model, wherein the description information of the AI model comprises at least one of the following:

[0169] function information of the AI model;

[0170] application range information of the AI model;

[0171] input or output information of the AI model;

[0172] performance information that can be achieved by the AI model;

[0173] structure information of the AI model.

[0174] Optionally, in an embodiment of the present disclosure, in response to the terminal device deploying the AI model, the terminal device actively reports, to the network-side device, AI model information corresponding to the deployed AI model.

[0175] Optionally, in an embodiment of the present disclosure, in response to receiving the reporting message sent by the network-side device, the terminal device reports, to the network-side device, AI model information corresponding to the deployed AI model.

[0176] Optionally, in an embodiment of the present disclosure, the apparatus is further configured to:

[0177] receive AI operations supported by the network-side device sent by the network-side device;

[0178] determine, according to the AI operations supported by the network-side device, to report, to the network-side device, AI models corresponding to the AI operations supported by the network-side device.

[0179] Optionally, in an embodiment of the present disclosure, the apparatus is further configured to:

[0180] receive a model identifier allocated by the network-side device according to the AI model information.

[0181] Figure 13 A structural schematic diagram of a communication apparatus provided by another embodiment of the present disclosure is shown in FIG. 13. Figure 13 As shown in FIG. 13, the apparatus can include:

[0182] a receiving module 1301 configured to receive AI model information corresponding to an AI model deployed by a terminal device sent by the terminal device.

[0183] In summary, in the communication apparatus provided in the embodiments of the present disclosure, the network-side device receives AI model information corresponding to an AI model deployed by a terminal device, that is, the terminal device sends the AI model information corresponding to the AI model deployed by the terminal device to the network-side device, thereby completing the registration of the AI model deployed by the terminal device on the network-side device, so that the network-side device knows the model information of the AI model deployed by the terminal device, and then facilitates the subsequent management or monitoring of the AI model deployed on the terminal device by the network-side device.

[0184] Optionally, in an embodiment of the present disclosure, the AI model information includes an identifier corresponding to the AI model.

[0185] Optionally, in an embodiment of the present disclosure, at least one AI model is predefined, each predefined AI model has a corresponding predefined model identifier, and the model information of the predefined AI model includes at least one of the following information:

[0186] function information of the AI model;

[0187] application range information of the AI model;

[0188] input or output information of the AI model;

[0189] performance information that can be achieved by the AI model;

[0190] structure information of the AI model.

[0191] Optionally, in an embodiment of the present disclosure, the apparatus is further configured to:

[0192] receive description information of the AI model sent by the terminal device, wherein the description information of the AI model includes at least one of the following information:

[0193] function information of the AI model;

[0194] application range information of the AI model;

[0195] input or output information of the AI model;

[0196] performance information that can be achieved by the AI model;

[0197] structure information of the AI model.

[0198] Optionally, in an embodiment of the present disclosure, the apparatus is further configured to:

[0199] send a reporting message to the terminal device, wherein the reporting message is used to instruct the terminal device to report AI model information corresponding to the AI model.

[0200] Optionally, in an embodiment of the present disclosure, the apparatus is further configured to:

[0201] transmit, to the terminal device, AI operations supported by the network-side device, wherein the AI model reported by the terminal device is generated according to the AI operations supported by the network-side device.

[0202] Optionally, in an embodiment of the present disclosure, the apparatus is further configured to:

[0203] transmit, to the terminal device, a model identifier allocated according to the AI model information.

[0204] Optionally, in an embodiment of the present disclosure, the apparatus is further configured to:

[0205] When the terminal device performs cell switching, the target base station acquires AI model information of an AI model supported by the terminal device.

[0206] Optionally, in an embodiment of the present disclosure, the apparatus is further configured to:

[0207] The target base station receives AI model information of an AI model supported by the terminal device transmitted by the source base station.

[0208] Optionally, in an embodiment of the present disclosure, the apparatus is further configured to:

[0209] The target base station acquires AI model information of an AI model supported by the terminal device from a core network node.

[0210] See Figure 14 , Figure 14 is a structural schematic diagram of a communication apparatus 1400 provided by an embodiment of the present disclosure. The communication apparatus 1400 can be a network device, a terminal device, a chip, a chip system, or a processor supporting the implementation of the network device or the terminal device, and the like. The apparatus can be used to implement the methods described in the above method embodiments, and specific reference can be made to the descriptions in the above method embodiments.

[0211] The communication apparatus 1400 can include one or more processors 1401. The processor 1401 can be a general-purpose processor or a special-purpose processor, etc. For example, it can be a baseband processor or a central processing unit. The baseband processor can be used to process communication protocols and communication data, and the central processing unit can be used to control the communication apparatus (such as a base station, a baseband chip, a terminal device, a terminal device chip, a DU or a CU, etc.), execute a computer program, and process data of the computer program.

[0212] Optionally, the communication device 1400 may further include one or more memories 1402, on which a computer program 1404 may be stored. The processor 1401 executes the computer program 1404 to cause the communication device 1400 to perform the method described in the above method embodiments. Optionally, the memory 1402 may also store data. The communication device 1400 and the memory 1402 may be provided separately or integrated together.

[0213] Optionally, the communication device 1400 may also include a transceiver 1405 and an antenna 1406. The transceiver 1405 may be referred to as a transceiver unit, transceiver, or transceiver circuit, etc., and is used to implement the transmission and reception functions. The transceiver 1405 may include a receiver and a transmitter. The receiver may be referred to as a receiver or receiving circuit, etc., and is used to implement the receiving function; the transmitter may be referred to as a transmitter or transmitting circuit, etc., and is used to implement the transmitting function.

[0214] Optionally, the communication device 1400 may further include one or more interface circuits 1407. The interface circuits 1407 are used to receive code instructions and transmit them to the processor 1401. The processor 1401 executes the code instructions to cause the communication device 1400 to perform the methods described in the above method embodiments.

[0215] Communication device 1400 is a terminal device: transceiver 1405 is used to perform... Figure 3 Steps 301-302 in Figure 3; Steps 401 to 402 in Figure 4; Figure 5 Steps 501 to 503 in the process; Figure 6 Steps 601a to 603a in a; Figure 6 Steps 601b to 602b in step b. Processor 1401 is used to execute... Figure 2 Step 201 in the middle; Figure 3 Steps 303-304 in Figure 4; Step 403 in Figure 4; Figure 5 Steps 504 and 505 in the text; Figure 6 Step 604a in a; Figure 6 Step 603b in b; Figure 7 Steps 701-702 in the text.

[0216] Communication device 1400 is a network device: transceiver 1405 is used to perform... Figure 11a Step 1102a in the process. Processor 1401 is used to execute Figure 8 Step 801 in the middle; Figure 9 Steps 901 to 904 in the process; Figure 10 Steps 1001 to 1005 in the process; Figure 11a Step 1101a in the middle; Figure 11bSteps 1101b and 1102b in the process.

[0217] In one implementation, the processor 1401 may include a transceiver for implementing receive and transmit functions. For example, the transceiver may be a transceiver circuit, an interface, or an interface circuit. The transceiver circuit, interface, or interface circuit for implementing receive and transmit functions may be separate or integrated. The aforementioned transceiver circuit, interface, or interface circuit can be used for reading and writing code / data, or it can be used for transmitting or relaying signals.

[0218] In one implementation, processor 1401 may store computer program 1403, which runs on processor 1401 and causes communication device 1400 to perform the methods described in the above method embodiments. Computer program 1403 may be embedded in processor 1401; in this case, processor 1401 may be implemented in hardware.

[0219] In one implementation, the communication device 1400 may include circuitry capable of performing the functions of transmitting, receiving, or communicating as described in the foregoing method embodiments. The processor and transceiver described in this application can be implemented on integrated circuits (ICs), analog ICs, radio frequency integrated circuits (RFICs), mixed-signal ICs, application-specific integrated circuits (ASICs), printed circuit boards (PCBs), electronic devices, etc. The processor and transceiver can also be manufactured using various IC process technologies, such as complementary metal-oxide semiconductors (CMOS), n-metal-oxide-semiconductor (NMOS), positive-channel metal-oxide semiconductors (PMOS), bipolar junction transistors (BJTs), bipolar CMOS (BiCMOS), silicon-germanium (SiGe), gallium arsenide (GaAs), etc.

[0220] The communication device described in the above embodiments may be a network device or a terminal device, but the scope of the communication device described in this application is not limited thereto, and the structure of the communication device may vary. Figure 14 The communication device may be a standalone device or part of a larger device. For example, the communication device may be:

[0221] (1) Independent integrated circuit IC, or chip, or chip system or subsystem;

[0222] (2) A collection of one or more ICs, optionally including storage components for storing data and computer programs;

[0223] (3) ASIC, such as modem;

[0224] (4) Modules that can be embedded in other devices;

[0225] (5) Receivers, terminal equipment, smart terminal equipment, cellular phones, wireless equipment, handheld devices, mobile units, vehicle-mounted equipment, network equipment, cloud equipment, artificial intelligence equipment, etc.

[0226] (6) Others, etc.

[0227] For cases where the communication device can be a chip or a chip system, please refer to [link / reference]. Figure 15 The diagram shows the structure of the chip. Figure 15 The chip shown includes a processor 1501 and an interface 1502. There can be one or more processors 1501, and multiple interfaces 1502.

[0228] Optionally, the chip also includes a memory 1503, which is used to store necessary computer programs and data.

[0229] Those skilled in the art will also understand that the various illustrative logical blocks and steps listed in the embodiments of this application can be implemented by electronic hardware, computer software, or a combination of both. Whether such functionality is implemented through hardware or software depends on the specific application and the overall system design requirements. Those skilled in the art can implement the described functionality using various methods for each specific application, but such implementation should not be construed as exceeding the scope of protection of the embodiments of this application.

[0230] This application also provides a readable storage medium having instructions stored thereon that, when executed by a computer, implement the functions of any of the above method embodiments.

[0231] This application also provides a computer program product that, when executed by a computer, implements the functions of any of the above method embodiments.

[0232] In the above embodiments, all or part of the embodiments can be implemented by software, hardware, firmware or any combination thereof. When implemented by software, all or part of the embodiments can be implemented in the form of a computer program product. The computer program product includes one or more computer programs. When the computer programs are loaded on a computer and executed, all or part of the processes or functions described in the embodiments of the present application are generated. The computer can be a general purpose computer, a special purpose computer, a computer network, or other programmable devices. The computer programs can be stored in a computer readable storage medium or transferred from one computer readable storage medium to another computer readable storage medium, for example, the computer programs can be transferred from one website, computer, server or data center to another website, computer, server or data center through wired (such as coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (such as infrared, wireless, microwave, etc.) mode. The computer readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server, data center, etc. integrated with one or more available media. The available media can be magnetic media (such as floppy disk, hard disk, magnetic tape), optical media (such as high-density digital video disc (digital video disc, DVD)), or semiconductor media (such as solid state disk (solid state disk, SSD)) and the like.

[0233] Those of ordinary skill in the art can understand that the first, second, and the like various numerical designations involved in the present application are only for the convenience of description and do not limit the scope of the embodiments of the present application, nor indicate the order of precedence.

[0234] At least one of the present application can also be described as one or more, and the plurality can be two, three, four or more, which is not limited in the present application. In the embodiments of the present application, for a technical feature, the technical features in the technical feature are distinguished by "first", "second", "third", "A", "B", "C" and "D". There is no order or size order between the technical features described by "first", "second", "third", "A", "B", "C" and "D".

[0235] The correspondence relationship shown in each table in the present application can be configured or predefined. The values of the information in each table are merely examples, and other values can be configured, and the present application is not limited thereto. When configuring the correspondence relationship of the information and each parameter, it is not necessarily required to configure all the correspondence relationships shown in each table. For example, the correspondence relationship shown in some rows in the table in the present application can also not be configured. For another example, the above tables can be appropriately deformed, for example, split, merged, and the like. The names of the parameters shown in the titles of the above tables can also use other names understandable by the communication device, and the values or representation manners of the parameters can also use other values or representation manners understandable by the communication device. The above tables can also use other data structures when implemented, for example, an array, a queue, a container, a stack, a linear table, a pointer, a linked list, a tree, a graph, a structure, a class, a heap, a hash table, or the like.

[0236] The predefinition in the present application can be understood as defining, predefining, storing, pre-storing, pre-negotiating, pre-configuring, solidifying, or pre-burning.

[0237] Those skilled in the art can clearly understand that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be realized by electronic hardware or a combination of computer software and electronic hardware. Whether the functions are realized in hardware or software depends on the specific application and design constraints of the technical solution. A person skilled in the art can use different methods to realize the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0238] Those skilled in the art can clearly understand that, for the convenience and brevity of the description, the specific working processes of the above-described system, device and unit can refer to the corresponding processes in the foregoing method embodiments, which will not be described here.

[0239] The above is merely a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art can easily think of changes or replacements within the technical scope disclosed in the present application, which should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A method for registering an artificial intelligence (AI) model, characterized in that, Applied to a terminal device, the method includes: Send the AI ​​model information corresponding to the AI ​​model deployed on the terminal device to the network-side device; Send the description information of the AI ​​model to the network-side device, wherein the description information of the AI ​​model includes at least one of the following: Functional information of the AI ​​model; Information regarding the application scope of the AI ​​model; The input or output information of the AI ​​model; The performance information that the AI ​​model can achieve; The structural information of the AI ​​model.

2. The method as described in claim 1, characterized in that, The AI ​​model information includes the identifier corresponding to the AI ​​model.

3. The method as described in claim 2, wherein at least one AI model is predefined, each predefined AI model has a corresponding predefined model identifier, and the model information of the predefined AI model includes at least one of the following: Functional information of the AI ​​model; Information regarding the application scope of the AI ​​model; The input or output information of the AI ​​model; The performance information that the AI ​​model can achieve; The structural information of the AI ​​model.

4. The method as described in claim 2, characterized in that, The identifier corresponding to the AI ​​model is generated by the terminal device.

5. The method as described in claim 1, characterized in that, In response to the deployment of an AI model on the terminal device, the terminal device proactively reports the AI ​​model information corresponding to the deployed AI model to the network-side device.

6. The method as described in claim 1, characterized in that, In response to receiving a reporting message from the network-side device, the terminal device reports the AI ​​model information corresponding to the deployed AI model to the network-side device.

7. The method as described in claim 1, characterized in that, Also includes: Receive AI operations supported by the network-side device sent by the network-side device; Based on the AI ​​operations supported by the network-side device, determine the AI ​​model corresponding to the AI ​​operation supported by the network-side device to be reported to the network-side device.

8. The method as described in claim 1 or 7, characterized in that, Also includes: Receive the model identifier assigned by the network-side device based on the AI ​​model information.

9. A method for registering an artificial intelligence (AI) model, characterized in that, Applied to network-side devices, the method includes: Receive AI model information corresponding to the AI ​​model deployed on the terminal device, sent by the terminal device; The terminal device sends a description of the AI ​​model, wherein the description of the AI ​​model includes at least one of the following: Functional information of the AI ​​model; Information regarding the application scope of the AI ​​model; The input or output information of the AI ​​model; The performance information that the AI ​​model can achieve; The structural information of the AI ​​model.

10. The method as described in claim 9, characterized in that, The AI ​​model information includes the identifier corresponding to the AI ​​model.

11. The method of claim 10, wherein at least one AI model is predefined, each predefined AI model has a corresponding predefined model identifier, and the model information of the predefined AI model includes at least one of the following: Functional information of the AI ​​model; Information regarding the application scope of the AI ​​model; The input or output information of the AI ​​model; The performance information that the AI ​​model can achieve; The structural information of the AI ​​model.

12. The method as described in claim 9, characterized in that, Also includes: A reporting message is sent to the terminal device, wherein the reporting message is used to instruct the terminal device to report the AI ​​model information corresponding to the AI ​​model.

13. The method as described in claim 9, characterized in that, Also includes: Send the AI ​​operations supported by the network-side device to the terminal device, wherein the AI ​​model reported by the terminal device is generated based on the AI ​​operations supported by the network-side device.

14. The method as described in claim 9 or 13, characterized in that, Also includes: Send the model identifier assigned based on the AI ​​model information to the terminal device.

15. The method as described in claim 9, characterized in that, Also includes: When the terminal device undergoes cell handover, the target base station obtains the AI ​​model information of the AI ​​model supported by the terminal device.

16. The method as described in claim 15, characterized in that, The target base station obtains AI model information of the AI ​​models supported by the terminal device, including: The target base station receives AI model information of the AI ​​models supported by the terminal device from the source base station.

17. The method as described in claim 15, characterized in that, The target base station obtains AI model information of the AI ​​models supported by the terminal device, including: The target base station obtains the AI ​​model information of the AI ​​models supported by the terminal device from the core network node.

18. A communication device configured in a terminal device, comprising: The sending module is used to send AI model information corresponding to the AI ​​model deployed on the terminal device to the network-side device; Send the description information of the AI ​​model to the network-side device, wherein the description information of the AI ​​model includes at least one of the following: Functional information of the AI ​​model; Information regarding the application scope of the AI ​​model; The input or output information of the AI ​​model; The performance information that the AI ​​model can achieve; The structural information of the AI ​​model.

19. A communication device configured in a network-side device, comprising: A receiving module is configured to receive AI model information corresponding to the AI ​​model deployed on the terminal device, sent by the terminal device; and to receive description information of the AI ​​model sent by the terminal device, wherein the description information of the AI ​​model includes at least one of the following: Functional information of the AI ​​model; Information regarding the application scope of the AI ​​model; The input or output information of the AI ​​model; The performance information that the AI ​​model can achieve; The structural information of the AI ​​model.

20. A communication device, characterized in that, The device includes a processor and a memory, wherein the memory stores a computer program, and the processor executes the computer program stored in the memory to cause the device to perform the method as claimed in any one of claims 1 to 8, or the processor executes the computer program stored in the memory to cause the device to perform the method as claimed in any one of claims 9 to 17.

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