Method, device and equipment for providing service based on artificial intelligence AI and storage medium

Abstract

The invention provides an AI-based service providing method, apparatus and device, and a storage medium, the method comprising: receiving a first request message sent by an AMF network element, the first request message indicating an AI service requested by a terminal device; determining a data allocation result based on the first request message, wherein the data allocation result comprises indication information corresponding to data allocated to the first AI network function network element and at least one second AI network function network element participating in execution of the AI service in data required for completing the AI service; sending the data allocation result to a network function NF network element, and receiving data allocated by the NF network element based on the data allocation result; and determining a first data execution result based on the data allocated by the NF network element, and receiving a second data execution result sent by the second AI network function network element. According to the method disclosed by the invention, the requirement of personalized AI service is met, the provided AI service result is more accurate, the execution efficiency is higher, the overall effectiveness and speed of the AI service are improved, and the problem of fragmentation of an AI application scene is avoided.

Description

Method, device, equipment and storage medium for providing services based on artificial intelligence (AI) Technical Field

[0001] The present disclosure relates to the field of communication technologies, and in particular to methods, devices, equipment, and storage media for providing services based on AI. Background Art

[0002] Because artificial intelligence (AI) technology can help networks achieve a higher level of autonomy and reduce costs and increase efficiency, networks often use AI technology to provide AI services.

[0003] Among the related technologies, the main approach is to provide AI services based on AI technology by optimizing and transforming the traditional network architecture.

[0004] However, the related art methods provide AI services by optimizing and transforming traditional network architectures, lacking a unified technical framework for providing AI services. This has led to fragmented network AI application scenarios and reduced the AI ​​service provision process to a simple overlay on existing network processes. The lack of a universal AI service provision process makes it impossible to meet personalized AI service needs. Furthermore, the related art methods for providing AI services do not segment the types of data required to complete the AI ​​service, nor do they implement categorized management for the AI ​​algorithms required to complete the AI ​​service, resulting in low efficiency and poor convenience.

[0005] Summary of the Invention

[0006] The present disclosure proposes a method, apparatus, device, and storage medium for providing AI-based services to address the technical problems of related technical methods, such as fragmented AI application scenarios, inability to meet personalized AI service needs, low efficiency, and poor convenience.

[0007] In a first aspect, an embodiment of the present disclosure provides a method for providing services based on AI, the method being executed by a second AI network function network element having decision-making capabilities, including:

[0008] Receive a first request message sent by a mobility management function (AMF) network element, where the first request message indicates an AI service requested by a terminal device;

[0009] Determining a data allocation result based on the first request message, the data allocation result including: indication information corresponding to data required to complete the AI ​​service allocated to the first AI network function network element and at least one second AI network function network element participating in executing the AI ​​service;

[0010] Sending the data allocation result to the network function NF network element, and receiving the data allocated by the NF network element based on the data allocation result;

[0011] Determine a first data execution result based on the data allocated by the NF network element, and receive a second data execution result sent by the second AI network function network element.

[0012] This disclosure provides a method for providing AI-based services. A first AI network function element (ANF) with decision-making capabilities receives a first request message from an AMF element, indicating an AI service requested by a terminal device. Furthermore, the first AI network function element determines a data allocation result based on the first request message. The data allocation result includes information indicating which data required to complete the AI ​​service is allocated to the first AI network function element and at least one second AI network function element participating in executing the AI ​​service. The first AI network function element then sends the data allocation result to the NF element and receives data allocated by the NF element based on the data allocation result. Finally, the first AI network function element determines a first data execution result based on the data allocated by the NF element and receives a second data execution result from the second AI network function element. Therefore, the AI ​​service provision method disclosed in this disclosure is not a simple overlay on existing network processes, but rather a complete and universal AI service provision process. Based on this method, the requested AI service can be accurately provided to terminal devices, thereby meeting the needs of personalized AI services. Also, in the method disclosed herein, by grouping the data required to complete the AI ​​service requested by the terminal device and respectively allocating different groups of data to the first AI network function network element and at least one second AI network function network element that participates in executing the AI ​​service, classified management of the AI ​​service is achieved, and fine-grained division of the AI ​​functions is achieved, which will make the subsequent AI service results more accurate. At the same time, in the method disclosed herein, the first AI network function network element and the second AI network function network element determine the data execution results in parallel, thereby improving execution efficiency. In addition, in the present disclosure, the first AI network function network element and multiple second AI network function network elements and other network elements in the core network can constitute a unified technical architecture for providing AI services, thereby avoiding the problem of fragmentation of AI application scenarios.

[0013] Optionally, the method further includes:

[0014] Determine a final service execution result corresponding to the AI ​​service based on the first data execution result and the second data execution result;

[0015] Send the final service execution result corresponding to the AI ​​service to the AMF.

[0016] Optionally, the first request message includes at least one of the following:

[0017] The AI ​​service type corresponding to the AI ​​service requested by the terminal device;

[0018] The AI ​​service identification ID corresponding to the AI ​​service requested by the terminal device.

[0019] Optionally, the method further includes:

[0020] At least one second AI network function network element that participates in executing the AI ​​service is determined from a plurality of second AI network function network elements communicatively connected to the first AI network function network element.

[0021] Optionally, determining at least one second AI network function network element that participates in executing the AI ​​service includes:

[0022] Determine the AI ​​service type corresponding to the AI ​​service;

[0023] Determine the AI ​​algorithms required to complete the AI ​​services;

[0024] Determine the data categories required to complete the AI ​​service;

[0025] Sending a status request message to a second AI network function network element communicatively connected to the first AI network function network element, wherein the status request message is used to request status information related to the AI ​​service execution capability of the second AI network function network element;

[0026] receiving status information sent by the second AI network function network element;

[0027] At least one second AI network function network element that participates in executing the AI ​​service is selected based on at least one of the AI ​​service type, the AI ​​algorithm, the data category, and the status information.

[0028] Optionally, the status information includes at least one of the following:

[0029] Energy status information;

[0030] Communication status information.

[0031] Optionally, the indication information includes at least one of the following:

[0032] Data name;

[0033] Data identification.

[0034] Optionally, determining the data allocation result based on the first request message includes:

[0035] Determine, based on the first request message, indication information corresponding to the data required to complete the AI ​​service, where each indication information is used to indicate a type of data;

[0036] Grouping the indication information to obtain at least one group of indication information;

[0037] Indication information groups are respectively allocated to the first AI network function network element and at least one second AI network function network element participating in executing the AI ​​service to obtain the data allocation result, wherein the indication information group allocated to the first AI network function network element or the at least one second AI network function network element participating in executing the AI ​​service is used to instruct: to allocate the data group indicated by the indication information group corresponding to the first AI network function network element or the second AI network function network element participating in executing the AI ​​service to the first AI network function network element or the second AI network function network element participating in executing the AI ​​service.

[0038] Optionally, grouping the indication information to obtain at least one group of indication information includes:

[0039] The indication information of the data is grouped based on the importance of the data to the AI ​​service and / or the difficulty of processing the data.

[0040] Optionally, the allocating indication information groups to the first AI network function network element and at least one second AI network function network element participating in executing the AI ​​service respectively includes:

[0041] Allocate a specific indication information group to the first AI network function network element, and allocate other indication information groups to at least one second AI network function network element participating in executing the AI ​​service;

[0042] The data corresponding to the specific indication information group is most important to the AI ​​service, and / or the data corresponding to the specific indication information group is most difficult to process.

[0043] Optionally, the method further includes:

[0044] Allocating resource blocks with different weights to at least one second AI network function network element participating in executing the AI ​​service;

[0045] The weight of the resource block allocated to the second AI network function network element is positively correlated with the importance and processing difficulty of the data corresponding to the indication information group allocated to the second AI network function network element for the AI ​​service.

[0046] Optionally, the NF network element includes at least one of the following:

[0047] User Data Register UDR network element;

[0048] Unstructured data storage function UDSF network element.

[0049] Optionally, determining a final service execution result corresponding to the AI ​​service based on the first data execution result and the second data execution result includes:

[0050] Aggregate and structure the first data execution result and the second data execution result to obtain a final service execution result corresponding to the AI ​​service.

[0051] Optionally, the first AI network function network element and at least one second AI network function network element participating in executing the AI ​​service determine the data execution result in parallel.

[0052] In a second aspect, an embodiment of the present disclosure provides a method for providing services based on AI, the method being executed by a second AI network function network element with execution capability, including:

[0053] Receive data allocated by the NF network element, which is the data required to complete the AI ​​service;

[0054] Determine a second data execution result based on the data allocated by the NF network element;

[0055] Send the second data execution result to the first AI network function network element.

[0056] Optionally, the NF network element includes at least one of the following:

[0057] UDR network element;

[0058] UDSF network element.

[0059] Optionally, the method further includes:

[0060] receiving a status request message sent by the first AI network function network element, where the status request message is used to request status information related to the AI ​​service execution capability of the second AI network function network element;

[0061] Send the status information to the first AI network function network element.

[0062] Optionally, the status information includes at least one of the following:

[0063] Energy status information;

[0064] Communication status information.

[0065] Optionally, the method further includes:

[0066] Receive a resource block allocated by the first AI network function network element.

[0067] Optionally, the second AI network function network element, other second AI network function network elements, and the first AI network function network element determine the data execution result in parallel.

[0068] In a third aspect, an embodiment of the present disclosure provides a method for providing services based on AI, the method being executed by a NF network element, including:

[0069] receiving a data allocation result sent by the first AI network function network element, the data allocation result including: indication information corresponding to data required to complete the AI ​​service allocated to the first AI network function network element and at least one second AI network function network element participating in executing the AI ​​service;

[0070] Based on the data allocation result, corresponding data is allocated to the first AI network function network element and at least one second AI network function network element participating in executing the AI ​​service.

[0071] Optionally, the indication information includes at least one of the following:

[0072] Data name;

[0073] Data identification.

[0074] In a fourth aspect, an embodiment of the present disclosure provides a method for providing services based on AI, which is executed by an AMF network element, including:

[0075] receiving a second request message sent by the terminal device, where the second request message indicates an AI service requested by the terminal device;

[0076] Sending a first request message to the first AI network function network element, where the first request message indicates an AI service requested by the terminal device;

[0077] receiving a final service execution result corresponding to the AI ​​service sent by the first AI network function network element;

[0078] Send the final service execution result corresponding to the AI ​​service to the terminal device.

[0079] Optionally, the first request message and the second request message both include at least one of the following:

[0080] The AI ​​service type corresponding to the AI ​​service requested by the terminal device;

[0081] The AI ​​service ID corresponding to the AI ​​service requested by the terminal device.

[0082] Optionally, the method further includes:

[0083] A response message sent by the terminal device is received, where the response message is used to indicate whether the terminal device has successfully received a final service execution result corresponding to the AI ​​service.

[0084] Optionally, the method further includes:

[0085] Receive a feedback result sent by the terminal device, where the feedback result is used to provide feedback on the satisfaction level of the final service execution result.

[0086] In a fifth aspect, an embodiment of the present disclosure provides a method for providing a service based on AI, which is executed by a terminal device and includes:

[0087] Send a second request message to the AMF network element, where the second request message indicates the AI ​​service requested by the terminal device;

[0088] Receive the final service execution result corresponding to the AI ​​service sent by the AMF network element.

[0089] Optionally, the second request message includes at least one of the following:

[0090] The AI ​​service type corresponding to the AI ​​service requested by the terminal device;

[0091] The AI ​​service ID corresponding to the AI ​​service requested by the terminal device.

[0092] Optionally, the method further includes:

[0093] Send a response message to the AMF network element, where the response message is used to indicate whether the terminal device has successfully received the final service execution result corresponding to the AI ​​service.

[0094] Optionally, the method further includes:

[0095] Send a feedback result to the AMF network element, where the feedback result is used to provide feedback on the satisfaction level with the final service execution result.

[0096] In a sixth aspect, an embodiment of the present disclosure provides a communication device, which is configured in a first AI network function network element, including:

[0097] A transceiver module, configured to receive a first request message sent by a mobility management function (AMF) network element, where the first request message indicates an AI service requested by a terminal device;

[0098] a processing module, configured to determine a data allocation result based on the first request message, the data allocation result comprising: indication information corresponding to data required to complete the AI ​​service allocated to the first AI network function network element and at least one second AI network function network element participating in executing the AI ​​service;

[0099] The transceiver module is further configured to send the data allocation result to the NF network element and receive data allocated by the NF network element based on the data allocation result;

[0100] The processing module is further configured to determine a first data execution result based on the data allocated by the NF network element, and receive a second data execution result sent by a second AI network function network element.

[0101] In a seventh aspect, an embodiment of the present disclosure provides a communication device, which is configured in a second AI network function network element, including:

[0102] The transceiver module is used to receive data allocated by the NF network element, which is required to complete the AI ​​service;

[0103] a processing module, configured to determine a second data execution result based on the data allocated by the NF network element;

[0104] The transceiver module is further configured to send the second data execution result to the first AI network function network element.

[0105] In an eighth aspect, an embodiment of the present disclosure provides a communication device, configured in a NF network element, including:

[0106] a transceiver module, configured to receive a data allocation result sent by a first AI network function network element, the data allocation result including: indication information corresponding to data required to complete the AI ​​service allocated to the first AI network function network element and at least one second AI network function network element participating in executing the AI ​​service;

[0107] The transceiver module is further configured to allocate corresponding data to the first AI network function network element and at least one second AI network function network element participating in executing the AI ​​service based on the data allocation result.

[0108] In a ninth aspect, an embodiment of the present disclosure provides a communication device, which is configured in an AMF network element, including:

[0109] a transceiver module, configured to receive a second request message sent by a terminal device, where the second request message indicates an AI service requested by the terminal device;

[0110] The transceiver module is further configured to send a first request message to the first AI network function network element, where the first request message indicates an AI service requested by the terminal device;

[0111] The transceiver module is further configured to receive a final service execution result corresponding to the AI ​​service sent by the first AI network function network element;

[0112] The transceiver module is further configured to send the final service execution result corresponding to the AI ​​service to the terminal device.

[0113] In a tenth aspect, an embodiment of the present disclosure provides a communication apparatus, which is configured in a terminal device and includes:

[0114] A transceiver module, configured to send a second request message to the AMF network element, where the second request message indicates the AI ​​service requested by the terminal device;

[0115] The transceiver module is used to receive the final service execution result corresponding to the AI ​​service sent by the AMF network element.

[0116] In an eleventh aspect, an embodiment of the present disclosure provides a communication device, which includes a processor. When the processor calls a computer program in a memory, the method described in the first aspect is executed.

[0117] In a twelfth aspect, an embodiment of the present disclosure provides a communication device, which includes a processor. When the processor calls a computer program in a memory, it executes the method described in the second aspect.

[0118] In a thirteenth aspect, an embodiment of the present disclosure provides a communication device, which includes a processor. When the processor calls a computer program in a memory, it executes the method described in the third aspect.

[0119] In a fourteenth aspect, an embodiment of the present disclosure provides a communication device, which includes a processor. When the processor calls a computer program in a memory, it executes the method described in the fourth aspect.

[0120] In a fifteenth aspect, an embodiment of the present disclosure provides a communication device, which includes a processor. When the processor calls a computer program in a memory, it executes the method described in the fifth aspect.

[0121] In the sixteenth aspect, an embodiment of the present disclosure provides a communication device, which includes a processor and a memory, in which a computer program is stored; the processor executes the computer program stored in the memory so that the communication device executes the method described in the first aspect above.

[0122] In the seventeenth aspect, an embodiment of the present disclosure provides a communication device, which includes a processor and a memory, in which a computer program is stored; the processor executes the computer program stored in the memory so that the communication device executes the method described in the second aspect above.

[0123] In the eighteenth aspect, an embodiment of the present disclosure provides a communication device, which includes a processor and a memory, in which a computer program is stored; the processor executes the computer program stored in the memory so that the communication device executes the method described in the third aspect above.

[0124] In the nineteenth aspect, an embodiment of the present disclosure provides a communication device, which includes a processor and a memory, in which a computer program is stored; the processor executes the computer program stored in the memory so that the communication device executes the method described in the fourth aspect above.

[0125] In the twentieth aspect, an embodiment of the present disclosure provides a communication device, which includes a processor and a memory, in which a computer program is stored; the processor executes the computer program stored in the memory so that the communication device executes the method described in the fifth aspect above.

[0126] In aspect 21, an embodiment of the present disclosure provides a communication device, which includes a processor and an interface circuit, wherein the interface circuit is used to receive code instructions and transmit them to the processor, and the processor is used to run the code instructions to enable the device to execute the method described in aspect 1 above.

[0127] In aspect 22, an embodiment of the present disclosure provides a communication device, which includes a processor and an interface circuit, wherein the interface circuit is used to receive code instructions and transmit them to the processor, and the processor is used to run the code instructions to enable the device to execute the method described in aspect 2 above.

[0128] In the twenty-third aspect, an embodiment of the present disclosure provides a communication device, which includes a processor and an interface circuit, wherein the interface circuit is used to receive code instructions and transmit them to the processor, and the processor is used to run the code instructions to enable the device to execute the method described in the third aspect above.

[0129] In aspect 24, an embodiment of the present disclosure provides a communication device, which includes a processor and an interface circuit, wherein the interface circuit is used to receive code instructions and transmit them to the processor, and the processor is used to run the code instructions to enable the device to execute the method described in aspect 4 above.

[0130] In aspect 25, an embodiment of the present disclosure provides a communication device, which includes a processor and an interface circuit, wherein the interface circuit is used to receive code instructions and transmit them to the processor, and the processor is used to run the code instructions to enable the device to execute the method described in aspect 5 above.

[0131] In aspect 26, an embodiment of the present disclosure provides a communication system, which includes the communication device described in aspect 6 to the communication device described in aspect 10, or the system includes the communication device described in aspect 11 to the communication device described in aspect 15, or the system includes the communication device described in aspect 16 to the communication device described in aspect 20, or the system includes the communication device described in aspect 21 to the communication device described in aspect 25.

[0132] In aspect 27, an embodiment of the present invention provides a computer-readable storage medium for storing instructions for the above-mentioned network device and / or the above-mentioned terminal device. When the instructions are executed, the network device executes the method described in aspect 1, and / or the terminal device executes the method described in aspect 2, and / or the terminal device executes the method described in aspect 3, and / or the terminal device executes the method described in aspect 4, and / or the terminal device executes the method described in aspect 5.

[0133] In aspect 28, the present disclosure further provides a computer program product comprising a computer program, which, when executed on a computer, enables the computer to execute the method described in any one of aspects 1 to 5 above.

[0134] In the twenty-ninth aspect, the present disclosure provides a chip system, which includes at least one processor and an interface, for supporting a network device to implement the functions involved in the method described in the first aspect, and / or, supporting a terminal device to implement the functions involved in the method described in the second aspect, and / or, supporting a terminal device to implement the functions involved in the method described in the third aspect, and / or, supporting a terminal device to implement the functions involved in the method described in the fourth aspect, and / or, supporting a terminal device to implement the functions involved in the method described in the fifth aspect, for example, determining or processing at least one of the data and information involved in the above methods. In one possible design, the chip system also includes a memory, which is used to store computer programs and data necessary for the source auxiliary node. The chip system can be composed of a chip, or it can include a chip and other discrete devices.

[0135] In aspect 30, the present disclosure provides a computer program which, when executed on a computer, enables the computer to execute the method described in any one of aspects 1 to 5 above.

[0136] In a thirty-first aspect, the present disclosure provides a communication system, including:

[0137] A first network element is configured to receive a second request message sent by a terminal device, where the second request message indicates an AI service requested by the terminal device, and send a first request message, where the first request message indicates the AI ​​service requested by the terminal device;

[0138] a second network element, configured to receive the first request message, determine a data allocation result based on the first request message, the data allocation result comprising: indication information corresponding to data required to complete the AI ​​service allocated to the first AI network function network element and at least one second AI network function network element participating in executing the AI ​​service, and transmit the data allocation result;

[0139] a third network element, configured to receive the data allocation result and allocate data based on the data allocation result;

[0140] The second network element is further configured to receive the data allocated by the third network element based on the data allocation result, and determine the first data execution result;

[0141] at least one fourth network element, configured to receive the data allocated by the third network element based on the data allocation result, determine a second data execution result, and send the second data execution result;

[0142] The second network element is further configured to receive each second data execution result, determine a final service execution result corresponding to the AI ​​service based on the first data execution result and the second data execution result, and send the final service execution result corresponding to the AI ​​service;

[0143] The first network element is further used to receive the final service execution result corresponding to the AI ​​service, and send the final service execution result corresponding to the AI ​​service to the terminal device. BRIEF DESCRIPTION OF THE DRAWINGS

[0144] The above and / or additional aspects and advantages of the present disclosure will become apparent and readily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0145] FIG1a is a schematic diagram of the architecture of a communication system provided by an embodiment of the present disclosure;

[0146] Figure 1b is a schematic diagram of a core network architecture provided by an embodiment of the present disclosure

[0147] FIG2 is a flow chart of a method for providing services based on AI according to another embodiment of the present disclosure;

[0148] FIG3 is a flowchart of a method for providing services based on AI according to another embodiment of the present disclosure;

[0149] FIG4 is a flowchart of a method for providing services based on AI according to another embodiment of the present disclosure;

[0150] FIG5 is a flow chart of a method for providing services based on AI according to another embodiment of the present disclosure;

[0151] FIG6 is a flowchart of a method for providing services based on AI according to another embodiment of the present disclosure;

[0152] FIG7 is a flowchart of a method for providing services based on AI according to another embodiment of the present disclosure;

[0153] FIG8 is a flowchart of a method for providing services based on AI according to another embodiment of the present disclosure;

[0154] FIG9 is a flowchart of a method for providing services based on AI according to another embodiment of the present disclosure;

[0155] FIG10 is a flowchart of a method for providing services based on AI according to another embodiment of the present disclosure;

[0156] FIG11 is a flowchart of a method for providing services based on AI according to another embodiment of the present disclosure;

[0157] FIG12 is a flowchart of a method for providing services based on AI according to another embodiment of the present disclosure;

[0158] FIG13 is a flowchart of a method for providing services based on AI according to another embodiment of the present disclosure;

[0159] FIG14 is a flowchart of a method for providing services based on AI according to another embodiment of the present disclosure;

[0160] FIG15 is a flowchart of a method for providing services based on AI according to another embodiment of the present disclosure;

[0161] FIG16 is a flowchart of a method for providing services based on AI according to another embodiment of the present disclosure;

[0162] FIG17a is a schematic diagram of an interaction flow of a method for providing services based on AI according to another embodiment of the present disclosure;

[0163] FIG17b is a schematic structural diagram of a communication device provided by an embodiment of the present disclosure;

[0164] FIG18 is a schematic structural diagram of a communication device provided by another embodiment of the present disclosure;

[0165] FIG19 is a schematic structural diagram of a communication device provided by another embodiment of the present disclosure;

[0166] FIG20 is a schematic structural diagram of a communication device provided by another embodiment of the present disclosure;

[0167] FIG21 is a schematic structural diagram of a communication device provided by another embodiment of the present disclosure;

[0168] FIG22 is a schematic diagram of the structure of a communication system provided by an embodiment of the present disclosure;

[0169] FIG23 is a block diagram of a communication device provided by one embodiment of the present disclosure;

[0170] FIG24 is a schematic structural diagram of a chip provided in accordance with an embodiment of the present disclosure. DETAILED DESCRIPTION

[0171] Exemplary embodiments will be described in detail herein, with examples illustrated in the accompanying drawings. In the following description, when referring to the drawings, identical numerals in different figures represent identical or similar elements, unless otherwise indicated. The embodiments described in the following exemplary embodiments are not intended to represent all possible implementations consistent with the present disclosure. Rather, they are merely examples of apparatuses and methods consistent with certain aspects of the present disclosure, as detailed in the appended claims.

[0172] The terms used in the embodiments of the present disclosure are for the purpose of describing specific embodiments only and are not intended to limit the embodiments of the present disclosure. The singular forms "a," "an," and "the" used in the embodiments of the present disclosure and the appended claims are also intended to include plural forms unless the context clearly indicates otherwise. It should also be understood that the term "and / or" as used herein refers to and includes any or all possible combinations of one or more associated listed items.

[0173] It should be understood that although the terms first, second, third, etc. may be used to describe various information in the embodiments of the present disclosure, such information should not be limited to these terms. These terms are only used to distinguish information of the same type from each other. For example, without departing from the scope of the embodiments of the present disclosure, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Depending on the context, the words "if" and "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining".

[0174] The embodiments of the present disclosure are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present disclosure, and should not be understood as limiting the present disclosure.

[0175] To facilitate understanding, the terms involved in this application are first introduced.

[0176] 1. Artificial Intelligence (AI)

[0177] AI is a new technical science that studies and develops theories, methods, technologies and application systems for simulating, extending and expanding human intelligence.

[0178] 2. Access and Mobility Management Function (AMF) network element

[0179] The AMF network element performs registration, connection, reachability, and mobility management. It provides a session management message transmission channel between terminal devices and SMF network elements, and provides authentication and authorization functions for terminal device access. It is the access point between terminal devices and the wireless core network control plane.

[0180] In order to better understand the method for determining the side link duration disclosed in an embodiment of the present application, the communication system to which the embodiment of the present application is applicable is first described below.

[0181] Please refer to Figure 1a, which 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 core network device and a terminal device. The number and configuration of devices shown in Figure 1a are for example purposes only and do not constitute a limitation on the embodiments of the present disclosure. In actual applications, two or more core network devices and two or more terminal devices may be included. The communication system shown in Figure 1a includes, for example, a core network device 11 and a terminal device 12.

[0182] It should be noted that the technical solutions of the embodiments of the present disclosure can be applied to various communication systems, such as long-term evolution (LTE) systems, fifth-generation (5G) mobile communication systems, 5G new radio (NR) systems, or other future new mobile communication systems.

[0183] The core network device 11 in the embodiment of the present disclosure is a device deployed in the core network. The function of the core network device 11 is mainly to provide user connection, user management, and service bearer, and to provide an interface to the external network as a bearer network. For example, the core network device in the 5G NR system may include an Access and Mobility Management Function (AMF) network element, a User Plane Function (UPF) network element, and a Session Management Function (SMF) network element.

[0184] Exemplarily, the core network device 11 in the embodiment of the present application may include a location management function network element. Optionally, the location management function network element includes a location server (location server), which may be implemented as any one of the following: LMF (Location Management Function, location management network element), E-SMLC (Enhanced Serving Mobile Location Centre, enhanced serving mobile location center), SUPL (Secure User Plane Location, secure user plane location), SUPL SLP (SUPL Location Platform, secure user plane location platform).

[0185] The terminal device 12 in the embodiment of the present disclosure can be an entity on the user side for receiving or transmitting signals, such as a mobile phone. The terminal device can also be called a terminal device (terminal), user equipment (UE), mobile station (MS), mobile terminal device (MT), etc. The terminal device can be a car with communication function, 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 (industrial control), a wireless terminal device in self-driving, a wireless terminal device in remote medical surgery, a wireless terminal device in smart grid (smart grid), a wireless terminal device in transportation safety (transportation safety), a wireless terminal device in smart city (smart city), a wireless terminal device in smart home (smart home), etc. The embodiment of the present disclosure does not limit the specific technology and specific device form adopted by the terminal device.

[0186] Among them, the core network device 11 and the terminal device 12 can communicate through the base station.

[0187] Also, please refer to Figure 1b, which is a schematic diagram of a core network architecture provided by an embodiment of the present disclosure. Figure 1b includes network elements included in the core network architecture and interfaces used for communication between the network elements.

[0188] The core network architecture abstracts the functions of network elements into multiple services. Compared with the traditional core network architecture, the core network architecture of Figure 1b adds N network elements, namely AI0, AI1, AI2...AIN, wherein AI0 is a decision-making network element, which is used to assign AI tasks to AI1, AI2...AIN network elements, and AI0 can also provide AI functions; and AI1, AI2...AIN network elements are all network elements that provide AI functions based on the decision of AI0. Among them, AI0 can be the first AI network function network element with decision-making capabilities mentioned later in this embodiment, and AI1, AI2...AIN network elements can be the second AI network function network elements with execution capabilities mentioned later in this embodiment. And, the AI0, AI1, AI2...AIN network elements can communicate with other network elements in the network (such as AMF network elements, SMF network elements, etc.).

[0189] It can be understood that the communication system described in the embodiment of the present disclosure is for the purpose of more clearly illustrating the technical solution of the embodiment of the present disclosure, and does not constitute a limitation on the technical solution provided by the embodiment of the present disclosure. Ordinary technicians in this field can know that with the evolution of the system architecture and the emergence of new business scenarios, the technical solution provided by the embodiment of the present disclosure is also applicable to similar technical problems.

[0190] In addition, it should be noted that the method disclosed herein is specifically implemented on the basis of completing the following operations:

[0191] (1) The terminal device has completed the initial registration process and is connected to the network.

[0192] (2) The AI ​​network function network elements (i.e., AI0, AI1, AI2, ... AIN network elements in Figure 1b) have completed registration at the Network Repository Function (NRF) and can be accessed and work normally in the core network architecture.

[0193] (3) The core network has authenticated each AI network function to ensure its secure access.

[0194] (4) AI0 and AI1 / ... / AIN network elements trust each other and transmit real communication information.

[0195] The following describes in detail the method, apparatus, device, and storage medium for providing AI-based services provided by the embodiments of the present disclosure with reference to the accompanying drawings.

[0196] FIG2 is a flow chart of a method for providing services based on AI according to an embodiment of the present disclosure. The method is performed by a first AI network function element with decision-making capabilities. As shown in FIG2 , the method for providing services based on AI may include the following steps:

[0197] Step 201: Receive the first request message sent by the AMF network element.

[0198] In one embodiment of the present disclosure, the first request message indicates an AI service requested by the terminal device. The first request message may include at least one of the following:

[0199] The AI ​​service type (AI Service Type) corresponding to the AI ​​service requested by the terminal device; the AI ​​service type can be video, voice, etc.;

[0200] The AI ​​service identification ID (AI Service ID) corresponding to the AI ​​service requested by the terminal device; the AI ​​service ID is used to uniquely identify the AI ​​service.

[0201] In one embodiment of the present disclosure, the first request message may be sent by the AMF network element to the first AI network function network element after receiving the second request message sent by the terminal device through the base station (such as transparent transmission). The first request message may be a CreateAI0Context_Request message, and the second request message may be an AI Service Establishment Request message.

[0202] Furthermore, it should be noted that, in one embodiment of the present disclosure, the first request message may further include at least one of the following:

[0203] Data Network Name (DNN);

[0204] User information of the terminal device;

[0205] Access typeAccess type;

[0206] The identifier of the terminal device; wherein the representation can be, for example, a Paging Early Indication (PEI), a Generic Public Subscription Identifier (GPSI), etc.

[0207] Step 202: Determine a data allocation result based on the first request message.

[0208] In one embodiment of the present disclosure, the data allocation result includes: indication information corresponding to data required to complete an AI service allocated to a first AI network function element and at least one second AI network function element participating in the AI ​​service execution. In other words, the data allocation result specifically includes: the corresponding allocation relationship between the indication information required to complete the AI ​​service and the first AI network function element and the at least one second AI network function element participating in the AI ​​service execution. Furthermore, the data allocation result implicitly indicates that the data indicated by the indication information corresponding to the first AI network function element is allocated to the first AI network function element, and the data indicated by the indication information corresponding to the second AI network function element is allocated to the second AI network function element. The second AI network function element is specifically a network element capable of executing and providing AI functions but lacks decision-making capabilities. The indication information may be a data name and / or data identifier.

[0209] Furthermore, in one embodiment of the present disclosure, the aforementioned step of "determining a data allocation result based on the first request message" may specifically include: the first AI network function element first determining the specific data required to complete the AI ​​service based on the first request message, and grouping the data required to complete the AI ​​service. Subsequently, the first AI network function element and at least one second AI network function element participating in executing the AI ​​service are each allocated at least one data group, so that the first AI network function element and the at least one second AI network function element participating in executing the AI ​​service can perform corresponding tasks to implement the AI ​​service based on the allocated data groups. However, it should be emphasized that when the first AI network function element determines the specific data required to complete the AI ​​service, it does not determine the specific data. Instead, it indicates the determined data by determining indication information corresponding to the data required to complete the AI ​​service. Furthermore, when grouping the data required to complete the AI ​​service, the first AI network function element does not group the specific data. Instead, it implicitly groups the data by grouping the indication information corresponding to the data. The data indicated by each indication information group is primarily used to complete a portion of the AI ​​service task. Furthermore, when the first AI network function network element allocates at least one data group to the first AI network function network element and the at least one second AI network function network element participating in executing the AI ​​service, the first AI network function network element and the at least one second AI network function network element participating in executing the AI ​​service are not specifically allocated to the first AI network function network element and the at least one second AI network function network element participating in executing the AI ​​service. Instead, a corresponding allocation relationship between the indication information group and the first AI network function network element and the at least one second AI network function network element participating in executing the AI ​​service is determined to implicitly indicate which data are allocated to the first AI network function network element and the at least one second AI network function network element participating in executing the AI ​​service.

[0210] For example, in one embodiment of the present disclosure, it is assumed that the above-mentioned indication information is a data name, and the second AI network function network element participating in the execution of the AI ​​service includes the second AI network function network element #1 and the second AI network function network element #2. Based on this, when the first AI network function network element receives the first request message, it can be determined that the AI ​​service needs to be executed currently, and the first AI network function network element determines based on the first request message that the data names of the data required to complete the AI ​​service include: data name 1, data name 2, data name 3, data name 4...data name 10. At this time, the data names can be grouped to obtain at least one group of data name groups, such as dividing data names 1-3 into data name group 1, dividing data names 4-7 into data name group 2, and dividing data names 8-10 into data name group 3. Afterwards, it can be determined The data allocation result is: data name group 1 is allocated to the first AI network function network element, data name group 2 is allocated to the second AI network function network element #1, and data name group 3 is allocated to the second AI network function network element #2. In this case, the data allocation result implicitly indicates: data with names 1-3 in data name group 1 is allocated to the first AI network function network element, data with names 4-7 in data name group 2 is allocated to the second AI network function network element #1, and data with names 8-10 in data name group 3 is allocated to the second AI network function network element #2.

[0211] Step 203: Send the data allocation result to the Network Function (NF) network element, and receive the data allocated by the NF network element based on the data allocation result.

[0212] In one embodiment of the present disclosure, the NF network element may be a UDR (User Data Repository) network element and / or a UDSF (Unstructured Data Storage Network Function) network element, which respectively store structured data sets and unstructured data sets. Furthermore, the data stored in the UDR network element and the UDSF network element primarily originate from data provided by the terminal device during registration, or data corresponding to the requested AI service provided synchronously to the NF network element when the terminal device requests the AI ​​service.

[0213] Furthermore, in one embodiment of the present disclosure, the first AI network function element sends a data allocation result to the NF element, so that the NF element can allocate corresponding data to the first AI network function element and at least one second AI network function element participating in executing the AI ​​service based on the data allocation result. This enables the first AI network function element and the at least one second AI network function element participating in executing the AI ​​service to perform corresponding tasks based on the data allocated by the NF element to complete the AI ​​service.

[0214] Step 204: Determine a first data execution result based on the data allocated by the NF network element, and receive a second data execution result sent by the second AI network function network element.

[0215] In one embodiment of the present disclosure, the first data execution result may be obtained by training the first AI network function element based on data allocated by the NF element, and the second data execution result may be obtained by training the second AI network function element based on data allocated by the NF element to the second AI network function element.

[0216] As can be seen from steps 202-204 above, in the present disclosure, when the first AI network function element determines that an AI service needs to be executed, it groups the data required to complete the AI ​​service. It then instructs the NF element to distribute the different data groups to the first AI network function element and at least one second AI network function element participating in executing the AI ​​service, respectively. This allows the first AI network function element and the at least one second AI network function element participating in executing the AI ​​service to respectively execute the tasks corresponding to the data based on the distributed data to implement the AI ​​service. As can be seen, in the present disclosure, the first AI network function element and the at least one second AI network function element participating in executing the AI ​​service respectively execute different parts of the AI ​​service, thereby achieving classified management of AI services and fine-grained division of AI functions, which will make the subsequently provided AI service results more accurate.

[0217] Also, it should be noted that, according to an embodiment of the present disclosure, the first AI network function network element and at least one second AI network function network element participating in executing the AI ​​service determine the data execution result in parallel, which is more efficient.

[0218] In addition, in one embodiment of the present disclosure, after obtaining the first data execution result and the second data execution result, the first AI network function network element can provide AI services to the terminal device through the AMF network element based on the first data execution result and the second data execution result.

[0219] In summary, in the AI-based service provision method provided in the embodiments of the present disclosure, a first AI network function element with decision-making capabilities receives a first request message from an AMF element, indicating an AI service requested by a terminal device. Furthermore, the first AI network function element determines a data allocation result based on the first request message. The data allocation result includes information indicating the data required to complete the AI ​​service allocated to the first AI network function element and at least one second AI network function element participating in executing the AI ​​service. The first AI network function element then sends the data allocation result to the NF element and receives data allocated by the NF element based on the data allocation result. Finally, the first AI network function element determines a first data execution result based on the data allocated by the NF element and receives a second data execution result from the second AI network function element. Therefore, the AI ​​service provision method of the present disclosure is not a simple overlay on existing network processes, but rather a complete, universal, and meticulously orchestrated AI service provision process. Based on this method, the requested AI service can be accurately provided to terminal devices, thereby meeting the needs of personalized AI services. Furthermore, in the method disclosed herein, by grouping the data required to complete the AI ​​service requested by the terminal device and respectively allocating different groups of data to the first AI network function network element and at least one second AI network function network element that participates in executing the AI ​​service, classified management of the AI ​​service is achieved, and a fine-grained division of the AI ​​functions is achieved, which will make the subsequent AI service results more accurate. At the same time, in the method disclosed herein, the first AI network function network element and the second AI network function network element determine the data execution results in parallel, thereby improving execution efficiency. Furthermore, in the present disclosure, the first AI network function network element and the second AI network function network element collaborate to execute the AI ​​service, thereby improving the overall effectiveness and speed of the AI ​​service. In addition, in the present disclosure, the first AI network function network element and the multiple second AI network function network elements and other network elements in the core network can constitute a unified technical architecture for providing AI services, thereby avoiding the problem of fragmentation of AI application scenarios.

[0220] FIG3 is a flow chart of a method for providing services based on AI according to an embodiment of the present disclosure. The method is performed by a first AI network function element with decision-making capabilities. As shown in FIG3 , the method for providing services based on AI may include the following steps:

[0221] Step 301: Determine a final service execution result corresponding to the AI ​​service based on the first data execution result and the second data execution result.

[0222] Among them, in one embodiment of the present disclosure, the first AI network function network element can specifically aggregate and structure the first data execution result and the second data execution result to obtain a final service execution result corresponding to the AI ​​service that meets the integrity requirements.

[0223] Step 302: Send the final service execution result corresponding to the AI ​​service to AMF.

[0224] In summary, in the AI-based service provision method provided in the embodiments of the present disclosure, a first AI network function element with decision-making capabilities receives a first request message from an AMF element, indicating an AI service requested by a terminal device. Furthermore, the first AI network function element determines a data allocation result based on the first request message. The data allocation result includes information indicating the data required to complete the AI ​​service allocated to the first AI network function element and at least one second AI network function element participating in executing the AI ​​service. The first AI network function element then sends the data allocation result to the NF element and receives data allocated by the NF element based on the data allocation result. Finally, the first AI network function element determines a first data execution result based on the data allocated by the NF element and receives a second data execution result from the second AI network function element. Therefore, the AI ​​service provision method of the present disclosure is not a simple overlay on existing network processes, but rather a complete, universal, and meticulously orchestrated AI service provision process. Based on this method, the requested AI service can be accurately provided to terminal devices, thereby meeting the needs of personalized AI services. Furthermore, in the method disclosed herein, by grouping the data required to complete the AI ​​service requested by the terminal device and respectively allocating different groups of data to the first AI network function network element and at least one second AI network function network element that participates in executing the AI ​​service, classified management of the AI ​​service is achieved, and a fine-grained division of the AI ​​functions is achieved, which will make the subsequent AI service results more accurate. At the same time, in the method disclosed herein, the first AI network function network element and the second AI network function network element determine the data execution results in parallel, thereby improving execution efficiency. Furthermore, in the present disclosure, the first AI network function network element and the second AI network function network element collaborate to execute the AI ​​service, thereby improving the overall effectiveness and speed of the AI ​​service. In addition, in the present disclosure, the first AI network function network element and the multiple second AI network function network elements and other network elements in the core network can constitute a unified technical architecture for providing AI services, thereby avoiding the problem of fragmentation of AI application scenarios.

[0225] FIG4 is a flow chart of a method for providing services based on AI according to an embodiment of the present disclosure. The method is performed by a first AI network function element with decision-making capabilities. As shown in FIG4 , the method for providing services based on AI may include the following steps:

[0226] Step 401: Determine at least one second AI network function network element that participates in executing an AI service from among multiple second AI network function network elements that are communicatively connected to a first AI network function network element.

[0227] In one embodiment of the present disclosure, the method for determining at least one second AI network function network element participating in executing the AI ​​service may specifically include:

[0228] Step a: Determine the AI ​​service type corresponding to the AI ​​service.

[0229] Specifically, the AI ​​service type corresponding to the AI ​​service may be determined based on the content included in the first request message.

[0230] Step b: Determine the AI ​​algorithm required to complete the AI ​​service.

[0231] Among them, the first AI network function network element can determine the AI ​​service specifically requested by the first request message based on the AI ​​service ID and AI service type in the received first request message, and determine the AI ​​algorithm required to complete the AI ​​service by analyzing the AI ​​service.

[0232] Step c: Determine the data category of the data required to complete the AI ​​service.

[0233] The data categories may include independent and identically distributed (IID) or non-IID.

[0234] Step d: Send a status request message to a second AI network function network element that is communicatively connected to the first AI network function network element, where the status request message is used to request status information related to the AI ​​service execution capability of the second AI network function network element.

[0235] The status information may include energy status information (or power status information) and / or communication status information.

[0236] Step e: Receive status information sent by the second AI network function network element;

[0237] Step f: Select at least one second AI network function network element that participates in executing the AI ​​service based on at least one of the AI ​​service type, the AI ​​algorithm, the data category, and the status information.

[0238] Specifically, in one embodiment of the present disclosure, a second AI network function element whose energy state and / or communication state matches the AI ​​service type, AI algorithm, and data category can be selected to participate in executing the AI ​​service. In another embodiment of the present disclosure, the first few second AI network function elements with better energy state and / or communication state can also be selected to participate in executing the AI ​​service. This can ensure that the second AI network function elements can subsequently complete the AI ​​service with high efficiency and high accuracy, thereby ensuring the efficiency and accuracy of the AI ​​service provision method.

[0239] The number of second AI network function network elements selected to participate in executing the AI ​​service can be determined autonomously by the first AI network function network element based on its implementation, or can be determined based on the specific AI service to be executed, such as determining the number of second AI network function network elements selected to participate in executing the AI ​​service with the goal of "executing the AI ​​service with high efficiency and high precision."

[0240] In summary, in the AI-based service provision method provided in the embodiments of the present disclosure, a first AI network function element with decision-making capabilities receives a first request message from an AMF element, indicating an AI service requested by a terminal device. Furthermore, the first AI network function element determines a data allocation result based on the first request message. The data allocation result includes information indicating the data required to complete the AI ​​service allocated to the first AI network function element and at least one second AI network function element participating in executing the AI ​​service. The first AI network function element then sends the data allocation result to the NF element and receives data allocated by the NF element based on the data allocation result. Finally, the first AI network function element determines a first data execution result based on the data allocated by the NF element and receives a second data execution result from the second AI network function element. Therefore, the AI ​​service provision method of the present disclosure is not a simple overlay on existing network processes, but rather a complete, universal, and meticulously orchestrated AI service provision process. Based on this method, the requested AI service can be accurately provided to terminal devices, thereby meeting the needs of personalized AI services. Furthermore, in the method disclosed herein, by grouping the data required to complete the AI ​​service requested by the terminal device and respectively allocating different groups of data to the first AI network function network element and at least one second AI network function network element that participates in executing the AI ​​service, classified management of the AI ​​service is achieved, and a fine-grained division of the AI ​​functions is achieved, which will make the subsequent AI service results more accurate. At the same time, in the method disclosed herein, the first AI network function network element and the second AI network function network element determine the data execution results in parallel, thereby improving execution efficiency. Furthermore, in the present disclosure, the first AI network function network element and the second AI network function network element collaborate to execute the AI ​​service, thereby improving the overall effectiveness and speed of the AI ​​service. In addition, in the present disclosure, the first AI network function network element and the multiple second AI network function network elements and other network elements in the core network can constitute a unified technical architecture for providing AI services, thereby avoiding the problem of fragmentation of AI application scenarios.

[0241] FIG5 is a flow chart of a method for providing services based on AI according to an embodiment of the present disclosure. The method is performed by a first AI network function element with decision-making capabilities. As shown in FIG5 , the method for providing services based on AI may include the following steps:

[0242] Step 501: Determine, based on the first request message, indication information corresponding to the data required to complete the AI ​​service, where each indication information is used to indicate a type of data.

[0243] In one embodiment of the present disclosure, the indication information may specifically be: a data name and / or a data identifier.

[0244] Furthermore, in one embodiment of the present disclosure, the first AI network function network element may specifically determine the indication information corresponding to the data required to complete the AI ​​service based on the content included in the first request message.

[0245] Step 502: Group the indication information to obtain at least one group of indication information.

[0246] In one embodiment of the present disclosure, the indication information of the data may be grouped based on the importance of the data to the AI ​​service and / or the difficulty of processing the data. For example, the indication information corresponding to data with similar importance and / or processing difficulty to the AI ​​service may be grouped together.

[0247] For example, assume that the first AI network function element determines that the indication information corresponding to the data required to complete the AI ​​service is: indication information #1 for data 1, indication information #2 for data 2, indication information #3 for data 3, and indication information #4 for data 4. If data 1 and data 2 are highly important to the AI ​​service, while data 3 and data 4 are less important, indication information #1 and indication information #2 can be grouped together, while indication information #3 and indication information #4 can be grouped together. Alternatively, if data 2 and data 3 are highly heterogeneous for the AI ​​service, while data 1 and data 4 are less heterogeneous, indicating that data 2 and data 3 are more difficult to process, while data 1 and data 4 are less difficult to process, indication information #2 and indication information #3 can be grouped together, while indication information #1 and indication information #4 can be grouped together.

[0248] Step 503: Allocate indication information groups to the first AI network function element and at least one second AI network function element participating in executing the AI ​​service to obtain a data allocation result.

[0249] The indication information group allocated to the first AI network function network element or at least one second AI network function network element participating in executing the AI ​​service is used to instruct: to allocate the data group indicated by the indication information group corresponding to the first AI network function network element or the second AI network function network element participating in executing the AI ​​service to the first AI network function network element or the second AI network function network element participating in executing the AI ​​service.

[0250] Furthermore, in one embodiment of the present disclosure, the aforementioned method of separately allocating indication information groups to the first AI network function element and at least one second AI network function element participating in executing an AI service may include allocating a specific indication information group to the first AI network function element and allocating other indication information groups to the at least one second AI network function element participating in executing the AI ​​service. In one embodiment of the present disclosure, the data corresponding to the specific indication information group is the most important to the AI ​​service, and / or the data corresponding to the specific indication information group is the most difficult to process. Alternatively, in another embodiment of the present disclosure, the specific indication information group is one of the first few indication information groups whose corresponding data is of greater importance to the AI ​​service, and / or the first few indication information groups whose corresponding data is the most difficult to process.

[0251] In one embodiment of the present disclosure, since the first AI network function network element has strong processing capabilities, by allocating more important and / or more difficult-to-process data required to complete the AI ​​service to the first AI network function network element, the first AI network function network element with stronger processing capabilities can complete the more important and / or more difficult-to-process parts of the AI ​​service, thereby ensuring the efficiency and accuracy of the AI ​​service.

[0252] In summary, in the AI-based service provision method provided in the embodiments of the present disclosure, a first AI network function element with decision-making capabilities receives a first request message from an AMF element, indicating an AI service requested by a terminal device. Furthermore, the first AI network function element determines a data allocation result based on the first request message. The data allocation result includes information indicating the data required to complete the AI ​​service allocated to the first AI network function element and at least one second AI network function element participating in executing the AI ​​service. The first AI network function element then sends the data allocation result to the NF element and receives data allocated by the NF element based on the data allocation result. Finally, the first AI network function element determines a first data execution result based on the data allocated by the NF element and receives a second data execution result from the second AI network function element. Therefore, the AI ​​service provision method of the present disclosure is not a simple overlay on existing network processes, but rather a complete, universal, and meticulously orchestrated AI service provision process. Based on this method, the requested AI service can be accurately provided to terminal devices, thereby meeting the needs of personalized AI services. Furthermore, in the method disclosed herein, by grouping the data required to complete the AI ​​service requested by the terminal device and respectively allocating different groups of data to the first AI network function network element and at least one second AI network function network element that participates in executing the AI ​​service, classified management of the AI ​​service is achieved, and a fine-grained division of the AI ​​functions is achieved, which will make the subsequent AI service results more accurate. At the same time, in the method disclosed herein, the first AI network function network element and the second AI network function network element determine the data execution results in parallel, thereby improving execution efficiency. Furthermore, in the present disclosure, the first AI network function network element and the second AI network function network element collaborate to execute the AI ​​service, thereby improving the overall effectiveness and speed of the AI ​​service. In addition, in the present disclosure, the first AI network function network element and the multiple second AI network function network elements and other network elements in the core network can constitute a unified technical architecture for providing AI services, thereby avoiding the problem of fragmentation of AI application scenarios.

[0253] FIG6 is a flow chart of a method for providing services based on AI according to an embodiment of the present disclosure. The method is performed by a first AI network function element with decision-making capabilities. As shown in FIG6 , the method for providing services based on AI may include the following steps:

[0254] Step 601: Allocate resource blocks with different weights to at least one second AI network function network element that participates in executing an AI service.

[0255] In one embodiment of the present disclosure, the weight of the resource blocks allocated to the second AI network function network element is positively correlated with the importance and processing difficulty of the data corresponding to the indication information group allocated to the second AI network function network element for the AI ​​service. For example, if the data corresponding to the indication information group allocated to the second AI network function network element is more important to the AI ​​service and / or the data corresponding to the indication information group allocated to the second AI network function network element is more difficult to process for the AI ​​service, the second AI network function network element is allocated a resource block with a higher weight.

[0256] It should be noted that the importance and / or processing difficulty of the data corresponding to the indication information group allocated to the second AI network function element for the AI ​​service specifically reflects the processing capability required of the second AI network function element during the AI ​​service completion process. Based on this, by ensuring that the weight of the resource blocks allocated to the second AI network function element is positively correlated with the importance and processing difficulty of the data corresponding to the indication information group allocated to the second AI network function element, the resource blocks allocated to the second AI network function element can be matched to the processing capability required of the second AI network function element during the AI ​​service completion process. This avoids the technical issues of "resource waste due to a large number of resource blocks allocated to the second AI network function element, or low AI service completion efficiency due to a small number of resource blocks allocated to the second AI network function element." This avoids resource waste while ensuring AI service completion efficiency.

[0257] In summary, in the AI-based service provision method provided in the embodiments of the present disclosure, a first AI network function element with decision-making capabilities receives a first request message from an AMF element, indicating an AI service requested by a terminal device. Furthermore, the first AI network function element determines a data allocation result based on the first request message. The data allocation result includes information indicating the data required to complete the AI ​​service allocated to the first AI network function element and at least one second AI network function element participating in executing the AI ​​service. The first AI network function element then sends the data allocation result to the NF element and receives data allocated by the NF element based on the data allocation result. Finally, the first AI network function element determines a first data execution result based on the data allocated by the NF element and receives a second data execution result from the second AI network function element. Therefore, the AI ​​service provision method of the present disclosure is not a simple overlay on existing network processes, but rather a complete and universal AI service provision process. Based on this method, the requested AI service can be accurately provided to the terminal device, thereby meeting the needs of personalized AI services. Also, in the method disclosed herein, by grouping the data required to complete the AI ​​service requested by the terminal device and respectively allocating different groups of data to the first AI network function network element and at least one second AI network function network element that participates in executing the AI ​​service, classified management of the AI ​​service is achieved, and fine-grained division of the AI ​​functions is achieved, which will make the subsequent AI service results more accurate. At the same time, in the method disclosed herein, the first AI network function network element and the second AI network function network element determine the data execution results in parallel, thereby improving execution efficiency. In addition, in the present disclosure, the first AI network function network element and multiple second AI network function network elements and other network elements in the core network can constitute a unified technical architecture for providing AI services, thereby avoiding the problem of fragmentation of AI application scenarios.

[0258] FIG7 is a flow chart of a method for providing an AI-based service according to an embodiment of the present disclosure. The method is executed by a second AI network function element with execution capability. As shown in FIG7 , the method for providing an AI-based service may include the following steps:

[0259] Step 701: Receive data allocated by a NF network element, where the data is required to complete an AI service.

[0260] In one embodiment of the present disclosure, the data received by the second AI network function network element may be allocated to the second AI network function network element by the NF network element based on the data allocation result.

[0261] Step 702: Determine a second data execution result based on the data allocated by the NF network element.

[0262] Step 703: Send the second data execution result to the first AI network function network element.

[0263] In one embodiment of the present disclosure, the second AI network function network element determines the data training result synchronously with the first AI network function network element and other second AI network function network elements.

[0264] In summary, in the AI-based service provision method provided in the embodiments of the present disclosure, a first AI network function element with decision-making capabilities receives a first request message from an AMF element, indicating an AI service requested by a terminal device. Furthermore, the first AI network function element determines a data allocation result based on the first request message. The data allocation result includes information indicating the data required to complete the AI ​​service allocated to the first AI network function element and at least one second AI network function element participating in executing the AI ​​service. The first AI network function element then sends the data allocation result to the NF element and receives data allocated by the NF element based on the data allocation result. Finally, the first AI network function element determines a first data execution result based on the data allocated by the NF element and receives a second data execution result from the second AI network function element. Therefore, the AI ​​service provision method of the present disclosure is not a simple overlay on existing network processes, but rather a complete and universal AI service provision process. Based on this method, the requested AI service can be accurately provided to the terminal device, thereby meeting the needs of personalized AI services. Also, in the method disclosed herein, by grouping the data required to complete the AI ​​service requested by the terminal device and respectively allocating different groups of data to the first AI network function network element and at least one second AI network function network element that participates in executing the AI ​​service, classified management of the AI ​​service is achieved, and fine-grained division of the AI ​​functions is achieved, which will make the subsequent AI service results more accurate. At the same time, in the method disclosed herein, the first AI network function network element and the second AI network function network element determine the data execution results in parallel, thereby improving execution efficiency. In addition, in the present disclosure, the first AI network function network element and multiple second AI network function network elements and other network elements in the core network can constitute a unified technical architecture for providing AI services, thereby avoiding the problem of fragmentation of AI application scenarios.

[0265] FIG8 is a flow chart of a method for providing an AI-based service according to an embodiment of the present disclosure. The method is executed by a second AI network function element with execution capability. As shown in FIG8 , the method for providing an AI-based service may include the following steps:

[0266] Step 801: Receive a status request message sent by a first AI network function network element, where the status request message is used to request status information related to AI service execution capabilities of a second AI network function network element.

[0267] Step 802: Send the status information to the first AI network function network element.

[0268] For a detailed description of steps 801 - 802 , please refer to the above embodiment description.

[0269] In summary, in the AI-based service provision method provided in the embodiments of the present disclosure, a first AI network function element with decision-making capabilities receives a first request message from an AMF element, indicating an AI service requested by a terminal device. Furthermore, the first AI network function element determines a data allocation result based on the first request message. The data allocation result includes information indicating the data required to complete the AI ​​service allocated to the first AI network function element and at least one second AI network function element participating in executing the AI ​​service. The first AI network function element then sends the data allocation result to the NF element and receives data allocated by the NF element based on the data allocation result. Finally, the first AI network function element determines a first data execution result based on the data allocated by the NF element and receives a second data execution result from the second AI network function element. Therefore, the AI ​​service provision method of the present disclosure is not a simple overlay on existing network processes, but rather a complete and universal AI service provision process. Based on this method, the requested AI service can be accurately provided to the terminal device, thereby meeting the needs of personalized AI services. Also, in the method disclosed herein, by grouping the data required to complete the AI ​​service requested by the terminal device and respectively allocating different groups of data to the first AI network function network element and at least one second AI network function network element that participates in executing the AI ​​service, classified management of the AI ​​service is achieved, and fine-grained division of the AI ​​functions is achieved, which will make the subsequent AI service results more accurate. At the same time, in the method disclosed herein, the first AI network function network element and the second AI network function network element determine the data execution results in parallel, thereby improving execution efficiency. In addition, in the present disclosure, the first AI network function network element and multiple second AI network function network elements and other network elements in the core network can constitute a unified technical architecture for providing AI services, thereby avoiding the problem of fragmentation of AI application scenarios.

[0270] FIG9 is a flow chart of a method for providing an AI-based service according to an embodiment of the present disclosure. The method is executed by a second AI network function element with execution capability. As shown in FIG9 , the method for providing an AI-based service may include the following steps:

[0271] Step 901: Receive a resource block allocated by the first AI network function network element.

[0272] For a detailed description of step 901 , please refer to the above embodiment description.

[0273] In summary, in the AI-based service provision method provided in the embodiments of the present disclosure, a first AI network function element with decision-making capabilities receives a first request message from an AMF element, indicating an AI service requested by a terminal device. Furthermore, the first AI network function element determines a data allocation result based on the first request message. The data allocation result includes information indicating the data required to complete the AI ​​service allocated to the first AI network function element and at least one second AI network function element participating in executing the AI ​​service. The first AI network function element then sends the data allocation result to the NF element and receives data allocated by the NF element based on the data allocation result. Finally, the first AI network function element determines a first data execution result based on the data allocated by the NF element and receives a second data execution result from the second AI network function element. Therefore, the AI ​​service provision method of the present disclosure is not a simple overlay on existing network processes, but rather a complete and universal AI service provision process. Based on this method, the requested AI service can be accurately provided to the terminal device, thereby meeting the needs of personalized AI services. Also, in the method disclosed herein, by grouping the data required to complete the AI ​​service requested by the terminal device and respectively allocating different groups of data to the first AI network function network element and at least one second AI network function network element that participates in executing the AI ​​service, classified management of the AI ​​service is achieved, and fine-grained division of the AI ​​functions is achieved, which will make the subsequent AI service results more accurate. At the same time, in the method disclosed herein, the first AI network function network element and the second AI network function network element determine the data execution results in parallel, thereby improving execution efficiency. In addition, in the present disclosure, the first AI network function network element and multiple second AI network function network elements and other network elements in the core network can constitute a unified technical architecture for providing AI services, thereby avoiding the problem of fragmentation of AI application scenarios.

[0274] FIG10 is a flow chart of a method for providing services based on AI according to an embodiment of the present disclosure. The method is executed by a NF network element. As shown in FIG10 , the method for providing services based on AI may include the following steps:

[0275] Step 1001: Receive a data allocation result sent by a first AI network function element. The data allocation result includes: indication information corresponding to data required to complete an AI service allocated to the first AI network function element and at least one second AI network function element participating in executing the AI ​​service.

[0276] For the relevant introduction of step 1001 , reference may be made to the description of the above embodiment.

[0277] Step 1002: Allocate corresponding data to the first AI network function network element and at least one second AI network function network element participating in executing the AI ​​service based on the data allocation result.

[0278] Specifically, in one embodiment of the present disclosure, the NF network element can find the data indicated by each indication information in the data allocation result, and send the data allocation indicated by the indication information corresponding to the first AI network function network element to the first AI network function network element, and send the data allocation indicated by the indication information corresponding to the second AI network function network element to the second AI network function network element.

[0279] It should be noted that, in one embodiment of the present disclosure, the data allocation result may also include user information of the terminal device and / or an identifier of the terminal device. Furthermore, the NF network element may specifically search for data corresponding to the terminal device stored in the NF network element based on the user information and / or identifier of the terminal device, and then search the data corresponding to the terminal device for the data indicated by the various indications in the data allocation result, thereby respectively allocating the corresponding data to the first AI network function network element and the second AI network function network element participating in executing the AI ​​service.

[0280] In summary, in the AI-based service provision method provided in the embodiments of the present disclosure, a first AI network function element with decision-making capabilities receives a first request message from an AMF element, indicating an AI service requested by a terminal device. Furthermore, the first AI network function element determines a data allocation result based on the first request message. The data allocation result includes information indicating the data required to complete the AI ​​service allocated to the first AI network function element and at least one second AI network function element participating in executing the AI ​​service. The first AI network function element then sends the data allocation result to the NF element and receives data allocated by the NF element based on the data allocation result. Finally, the first AI network function element determines a first data execution result based on the data allocated by the NF element and receives a second data execution result from the second AI network function element. Therefore, the AI ​​service provision method of the present disclosure is not a simple overlay on existing network processes, but rather a complete and universal AI service provision process. Based on this method, the requested AI service can be accurately provided to the terminal device, thereby meeting the needs of personalized AI services. Also, in the method disclosed herein, by grouping the data required to complete the AI ​​service requested by the terminal device and respectively allocating different groups of data to the first AI network function network element and at least one second AI network function network element that participates in executing the AI ​​service, classified management of the AI ​​service is achieved, and fine-grained division of the AI ​​functions is achieved, which will make the subsequent AI service results more accurate. At the same time, in the method disclosed herein, the first AI network function network element and the second AI network function network element determine the data execution results in parallel, thereby improving execution efficiency. In addition, in the present disclosure, the first AI network function network element and multiple second AI network function network elements and other network elements in the core network can constitute a unified technical architecture for providing AI services, thereby avoiding the problem of fragmentation of AI application scenarios.

[0281] FIG11 is a flow chart of a method for providing an AI-based service according to an embodiment of the present disclosure. The method is executed by an AMF network element. As shown in FIG11 , the method for providing an AI-based service may include the following steps:

[0282] Step 1101: Receive a second request message sent by a terminal device, where the second request message indicates an AI service requested by the terminal device.

[0283] Step 1102: Send a first request message to the first AI network function network element, where the first request message indicates an AI service requested by the terminal device.

[0284] Step 1103: Receive the final service execution result corresponding to the AI ​​service sent by the first AI network function network element.

[0285] Step 1104: Send the final service execution result corresponding to the AI ​​service to the terminal device.

[0286] In summary, in the AI-based service provision method provided in the embodiments of the present disclosure, a first AI network function element with decision-making capabilities receives a first request message from an AMF element, indicating an AI service requested by a terminal device. Furthermore, the first AI network function element determines a data allocation result based on the first request message. The data allocation result includes information indicating the data required to complete the AI ​​service allocated to the first AI network function element and at least one second AI network function element participating in executing the AI ​​service. The first AI network function element then sends the data allocation result to the NF element and receives data allocated by the NF element based on the data allocation result. Finally, the first AI network function element determines a first data execution result based on the data allocated by the NF element and receives a second data execution result from the second AI network function element. Therefore, the AI ​​service provision method of the present disclosure is not a simple overlay on existing network processes, but rather a complete and universal AI service provision process. Based on this method, the requested AI service can be accurately provided to the terminal device, thereby meeting the needs of personalized AI services. Also, in the method disclosed herein, by grouping the data required to complete the AI ​​service requested by the terminal device and respectively allocating different groups of data to the first AI network function network element and at least one second AI network function network element that participates in executing the AI ​​service, classified management of the AI ​​service is achieved, and fine-grained division of the AI ​​functions is achieved, which will make the subsequent AI service results more accurate. At the same time, in the method disclosed herein, the first AI network function network element and the second AI network function network element determine the data execution results in parallel, thereby improving execution efficiency. In addition, in the present disclosure, the first AI network function network element and multiple second AI network function network elements and other network elements in the core network can constitute a unified technical architecture for providing AI services, thereby avoiding the problem of fragmentation of AI application scenarios.

[0287] FIG12 is a flow chart of a method for providing services based on AI according to an embodiment of the present disclosure. The method is performed by an AMF network element. As shown in FIG12 , the method for providing services based on AI may include the following steps:

[0288] Step 1201: Receive a response message sent by the terminal device, where the response message is used to indicate whether the terminal device has successfully received the final service execution result corresponding to the AI ​​service.

[0289] Among them, in one embodiment of the present disclosure, if the response message indicates that the terminal device has not successfully received the final service execution result, the AMF network element will resend the final service execution result corresponding to the AI ​​service to the terminal device. Thereby, the failure of the transmission of the final service execution result corresponding to the AI ​​service can be prevented, thereby ensuring the successful provision of the AI ​​service.

[0290] In summary, in the AI-based service provision method provided in the embodiments of the present disclosure, a first AI network function element with decision-making capabilities receives a first request message from an AMF element, indicating an AI service requested by a terminal device. Furthermore, the first AI network function element determines a data allocation result based on the first request message. The data allocation result includes information indicating the data required to complete the AI ​​service allocated to the first AI network function element and at least one second AI network function element participating in executing the AI ​​service. The first AI network function element then sends the data allocation result to the NF element and receives data allocated by the NF element based on the data allocation result. Finally, the first AI network function element determines a first data execution result based on the data allocated by the NF element and receives a second data execution result from the second AI network function element. Therefore, the AI ​​service provision method of the present disclosure is not a simple overlay on existing network processes, but rather a complete and universal AI service provision process. Based on this method, the requested AI service can be accurately provided to the terminal device, thereby meeting the needs of personalized AI services. Also, in the method disclosed herein, by grouping the data required to complete the AI ​​service requested by the terminal device and respectively allocating different groups of data to the first AI network function network element and at least one second AI network function network element that participates in executing the AI ​​service, classified management of the AI ​​service is achieved, and fine-grained division of the AI ​​functions is achieved, which will make the subsequent AI service results more accurate. At the same time, in the method disclosed herein, the first AI network function network element and the second AI network function network element determine the data execution results in parallel, thereby improving execution efficiency. In addition, in the present disclosure, the first AI network function network element and multiple second AI network function network elements and other network elements in the core network can constitute a unified technical architecture for providing AI services, thereby avoiding the problem of fragmentation of AI application scenarios.

[0291] FIG13 is a flow chart of a method for providing an AI-based service according to an embodiment of the present disclosure. The method is executed by an AMF network element. As shown in FIG13 , the method for providing an AI-based service may include the following steps:

[0292] Step 1301: Receive a feedback result sent by a terminal device, where the feedback result is used to provide feedback on the satisfaction level with the final service execution result.

[0293] In summary, in the AI-based service provision method provided in the embodiments of the present disclosure, a first AI network function element with decision-making capabilities receives a first request message from an AMF element, indicating an AI service requested by a terminal device. Furthermore, the first AI network function element determines a data allocation result based on the first request message. The data allocation result includes information indicating the data required to complete the AI ​​service allocated to the first AI network function element and at least one second AI network function element participating in executing the AI ​​service. The first AI network function element then sends the data allocation result to the NF element and receives data allocated by the NF element based on the data allocation result. Finally, the first AI network function element determines a first data execution result based on the data allocated by the NF element and receives a second data execution result from the second AI network function element. Therefore, the AI ​​service provision method of the present disclosure is not a simple overlay on existing network processes, but rather a complete and universal AI service provision process. Based on this method, the requested AI service can be accurately provided to the terminal device, thereby meeting the needs of personalized AI services. Also, in the method disclosed herein, by grouping the data required to complete the AI ​​service requested by the terminal device and respectively allocating different groups of data to the first AI network function network element and at least one second AI network function network element that participates in executing the AI ​​service, classified management of the AI ​​service is achieved, and fine-grained division of the AI ​​functions is achieved, which will make the subsequent AI service results more accurate. At the same time, in the method disclosed herein, the first AI network function network element and the second AI network function network element determine the data execution results in parallel, thereby improving execution efficiency. In addition, in the present disclosure, the first AI network function network element and multiple second AI network function network elements and other network elements in the core network can constitute a unified technical architecture for providing AI services, thereby avoiding the problem of fragmentation of AI application scenarios.

[0294] FIG14 is a flow chart of a method for providing services based on AI according to an embodiment of the present disclosure. The method is executed by a terminal device. As shown in FIG14 , the method for providing services based on AI may include the following steps:

[0295] Step 1401: Send a second request message to the AMF network element, where the second request message indicates the AI ​​service requested by the terminal device.

[0296] Step 1402: Receive the final service execution result corresponding to the AI ​​service sent by the AMF network element.

[0297] In summary, in the AI-based service provision method provided in the embodiments of the present disclosure, a first AI network function element with decision-making capabilities receives a first request message from an AMF element, indicating an AI service requested by a terminal device. Furthermore, the first AI network function element determines a data allocation result based on the first request message. The data allocation result includes information indicating the data required to complete the AI ​​service allocated to the first AI network function element and at least one second AI network function element participating in executing the AI ​​service. The first AI network function element then sends the data allocation result to the NF element and receives data allocated by the NF element based on the data allocation result. Finally, the first AI network function element determines a first data execution result based on the data allocated by the NF element and receives a second data execution result from the second AI network function element. Therefore, the AI ​​service provision method of the present disclosure is not a simple overlay on existing network processes, but rather a complete and universal AI service provision process. Based on this method, the requested AI service can be accurately provided to the terminal device, thereby meeting the needs of personalized AI services. Also, in the method disclosed herein, by grouping the data required to complete the AI ​​service requested by the terminal device and respectively allocating different groups of data to the first AI network function network element and at least one second AI network function network element that participates in executing the AI ​​service, classified management of the AI ​​service is achieved, and fine-grained division of the AI ​​functions is achieved, which will make the subsequent AI service results more accurate. At the same time, in the method disclosed herein, the first AI network function network element and the second AI network function network element determine the data execution results in parallel, thereby improving execution efficiency. In addition, in the present disclosure, the first AI network function network element and multiple second AI network function network elements and other network elements in the core network can constitute a unified technical architecture for providing AI services, thereby avoiding the problem of fragmentation of AI application scenarios.

[0298] FIG15 is a flow chart of a method for providing services based on AI according to an embodiment of the present disclosure. The method is executed by a terminal device. As shown in FIG15 , the method for providing services based on AI may include the following steps:

[0299] Step 1501: Send a response message to the AMF network element, which is used to indicate whether the terminal device has successfully received the final service execution result corresponding to the AI ​​service.

[0300] In summary, in the AI-based service provision method provided in the embodiments of the present disclosure, a first AI network function element with decision-making capabilities receives a first request message from an AMF element, indicating an AI service requested by a terminal device. Furthermore, the first AI network function element determines a data allocation result based on the first request message. The data allocation result includes information indicating the data required to complete the AI ​​service allocated to the first AI network function element and at least one second AI network function element participating in executing the AI ​​service. The first AI network function element then sends the data allocation result to the NF element and receives data allocated by the NF element based on the data allocation result. Finally, the first AI network function element determines a first data execution result based on the data allocated by the NF element and receives a second data execution result from the second AI network function element. Therefore, the AI ​​service provision method of the present disclosure is not a simple overlay on existing network processes, but rather a complete and universal AI service provision process. Based on this method, the requested AI service can be accurately provided to the terminal device, thereby meeting the needs of personalized AI services. Also, in the method disclosed herein, by grouping the data required to complete the AI ​​service requested by the terminal device and respectively allocating different groups of data to the first AI network function network element and at least one second AI network function network element that participates in executing the AI ​​service, classified management of the AI ​​service is achieved, and fine-grained division of the AI ​​functions is achieved, which will make the subsequent AI service results more accurate. At the same time, in the method disclosed herein, the first AI network function network element and the second AI network function network element determine the data execution results in parallel, thereby improving execution efficiency. In addition, in the present disclosure, the first AI network function network element and multiple second AI network function network elements and other network elements in the core network can constitute a unified technical architecture for providing AI services, thereby avoiding the problem of fragmentation of AI application scenarios.

[0301] FIG16 is a flow chart of a method for providing services based on AI according to an embodiment of the present disclosure. The method is executed by a terminal device. As shown in FIG16 , the method for providing services based on AI may include the following steps:

[0302] Step 1601: Send feedback results to the AMF network element. The feedback results are used to feedback the satisfaction level with the final service execution results.

[0303] In one embodiment of the present disclosure, the feedback result may be determined based on the user's rating.

[0304] In summary, in the AI-based service provision method provided in the embodiments of the present disclosure, a first AI network function element with decision-making capabilities receives a first request message from an AMF element, indicating an AI service requested by a terminal device. Furthermore, the first AI network function element determines a data allocation result based on the first request message. The data allocation result includes information indicating the data required to complete the AI ​​service allocated to the first AI network function element and at least one second AI network function element participating in executing the AI ​​service. The first AI network function element then sends the data allocation result to the NF element and receives data allocated by the NF element based on the data allocation result. Finally, the first AI network function element determines a first data execution result based on the data allocated by the NF element and receives a second data execution result from the second AI network function element. Therefore, the AI ​​service provision method of the present disclosure is not a simple overlay on existing network processes, but rather a complete and universal AI service provision process. Based on this method, the requested AI service can be accurately provided to the terminal device, thereby meeting the needs of personalized AI services. Also, in the method disclosed herein, by grouping the data required to complete the AI ​​service requested by the terminal device and respectively allocating different groups of data to the first AI network function network element and at least one second AI network function network element that participates in executing the AI ​​service, classified management of the AI ​​service is achieved, and fine-grained division of the AI ​​functions is achieved, which will make the subsequent AI service results more accurate. At the same time, in the method disclosed herein, the first AI network function network element and the second AI network function network element determine the data execution results in parallel, thereby improving execution efficiency. In addition, in the present disclosure, the first AI network function network element and multiple second AI network function network elements and other network elements in the core network can constitute a unified technical architecture for providing AI services, thereby avoiding the problem of fragmentation of AI application scenarios.

[0305] Furthermore, FIG17a is a schematic diagram of an interaction flow of a method for providing services based on AI provided in an embodiment of the present disclosure. As shown in FIG17 , the method includes the following steps:

[0306] 1) The user equipment (UE) (i.e., the aforementioned terminal device) sends an AI Service Establishment Request message (i.e., the aforementioned second request message) to the AMF through the (R)AN.

[0307] The AI ​​Service Establishment Request message includes: DNN, AI Service Type (video, language, etc.), AI Service ID, etc.

[0308] 2) AMF sends a CreateAI0Context_Request message to AIO (i.e., the manager of the AI ​​service, the aforementioned first AI network function network element) to request the provision of AI services.

[0309] The CreateAI0Context_Request message includes: DNN, AI Service Type (video, language, etc.), AI Service ID, User information, Access type, PEI, GPSI and other information.

[0310] 3) AI0 makes decisions based on the received information, analyzing the AI ​​type of the task, the AI ​​algorithm to be used, and the data category (IID / non-IID) to be used, and notifies each AI sub-function to upload its status information (including energy status, communication conditions, etc.).

[0311] 4) The AI ​​sub-function uploads information to AI0.

[0312] 5) AI0 comprehensively determines the information and selects the AI ​​sub-function group to participate in the AI ​​service. Training data is divided into several groups based on reference factors such as importance and heterogeneity. Data with higher importance and greater heterogeneity is processed locally by AI0, while the remaining data is sent to the selected AI sub-function and allocated resource blocks with different weights to achieve the ideal joint training effect. AI0 can then send the data allocation results to the UDR network element and / or UDSF network element (this step is not shown in Figure 17a).

[0313] 6&7) The UDR and UDSF provide structured and unstructured data sets to AI0 and AI sub-functions respectively. The data is distributed according to the grouping set by AI0. The data source is the data stored in these two NFs when the UE registers and makes service requests.

[0314] 8) AI0 and AI sub-functions are trained synchronously and in parallel, and:

[0315] 8(a): Feedback the output result (i.e., the aforementioned second data execution result) to AI0;

[0316] 8(b): AI0 aggregates the local training results (i.e., the aforementioned first data execution results) and the received results and performs structured processing to meet the integrity requirements.

[0317] 9) AI0 transmits the result (i.e., the final service execution result corresponding to the aforementioned AI service) to AMF for output;

[0318] 10) The AMF transparently transmits the output result (i.e., the final service execution result corresponding to the aforementioned AI service) to the UE through the (R)AN.

[0319] 11) The UE responds that it has received the result (i.e. the terminal device sends a response message to the AMF network element) and provides feedback on the result (satisfied or dissatisfied) (i.e. the terminal device sends feedback to the AMF network element).

[0320] 12) The overall process of AI function service is completed and the registration is cancelled.

[0321] FIG17b is a schematic structural diagram of a communication device provided by an embodiment of the present disclosure. As shown in FIG17b , the device may include:

[0322] A transceiver module, configured to receive a first request message sent by a mobility management function (AMF) network element, where the first request message indicates an AI service requested by a terminal device;

[0323] a processing module, configured to determine a data allocation result based on the first request message, the data allocation result comprising: indication information corresponding to data required to complete the AI ​​service allocated to the first AI network function network element and at least one second AI network function network element participating in executing the AI ​​service;

[0324] The transceiver module is further configured to send the data allocation result to the NF network element and receive data allocated by the NF network element based on the data allocation result;

[0325] The processing module is further configured to determine a first data execution result based on the data allocated by the NF network element, and receive a second data execution result sent by a second AI network function network element.

[0326] In summary, in the communication device provided in the embodiments of the present disclosure, a first AI network function element with decision-making capabilities receives a first request message sent by an AMF element, indicating an AI service requested by a terminal device. Furthermore, the first AI network function element determines a data allocation result based on the first request message. The data allocation result includes information indicating the data required to complete the AI ​​service allocated to the first AI network function element and at least one second AI network function element participating in executing the AI ​​service. The first AI network function element then sends the data allocation result to the NF element and receives data allocated by the NF element based on the data allocation result. Finally, the first AI network function element determines a first data execution result based on the data allocated by the NF element and receives a second data execution result sent by the second AI network function element. Therefore, the AI ​​service provision method disclosed in the present disclosure is not a simple overlay on existing network processes, but rather a complete and universal AI service provision process. Based on this method, the requested AI service can be accurately provided to the terminal device, thereby meeting the needs of personalized AI services. Also, in the method disclosed herein, by grouping the data required to complete the AI ​​service requested by the terminal device and respectively allocating different groups of data to the first AI network function network element and at least one second AI network function network element that participates in executing the AI ​​service, classified management of the AI ​​service is achieved, and fine-grained division of the AI ​​functions is achieved, which will make the subsequent AI service results more accurate. At the same time, in the method disclosed herein, the first AI network function network element and the second AI network function network element determine the data execution results in parallel, thereby improving execution efficiency. In addition, in the present disclosure, the first AI network function network element and multiple second AI network function network elements and other network elements in the core network can constitute a unified technical architecture for providing AI services, thereby avoiding the problem of fragmentation of AI application scenarios.

[0327] Optionally, in one embodiment of the present disclosure, the apparatus is further configured to:

[0328] Determine a final service execution result corresponding to the AI ​​service based on the first data execution result and the second data execution result;

[0329] Send the final service execution result corresponding to the AI ​​service to the AMF.

[0330] Optionally, in one embodiment of the present disclosure, the first request message includes at least one of the following:

[0331] The AI ​​service type corresponding to the AI ​​service requested by the terminal device;

[0332] The AI ​​service identification ID corresponding to the AI ​​service requested by the terminal device.

[0333] Optionally, in one embodiment of the present disclosure, the apparatus is further configured to:

[0334] At least one second AI network function network element that participates in executing the AI ​​service is determined from a plurality of second AI network function network elements communicatively connected to the first AI network function network element.

[0335] Optionally, in one embodiment of the present disclosure, the apparatus is further configured to:

[0336] Determine the AI ​​service type corresponding to the AI ​​service;

[0337] Determine the AI ​​algorithms required to complete the AI ​​services;

[0338] Determine the data categories required to complete the AI ​​service;

[0339] Sending a status request message to a second AI network function network element communicatively connected to the first AI network function network element, wherein the status request message is used to request status information related to the AI ​​service execution capability of the second AI network function network element;

[0340] receiving status information sent by the second AI network function network element;

[0341] At least one second AI network function network element that participates in executing the AI ​​service is selected based on at least one of the AI ​​service type, the AI ​​algorithm, the data category, and the status information.

[0342] Optionally, in an embodiment of the present disclosure, the status information includes at least one of the following:

[0343] Energy status information;

[0344] Communication status information.

[0345] Optionally, in an embodiment of the present disclosure, the indication information includes at least one of the following:

[0346] Data name;

[0347] Data identification.

[0348] Optionally, in one embodiment of the present disclosure, the processing module is further configured to:

[0349] Determine, based on the first request message, indication information corresponding to the data required to complete the AI ​​service, where each indication information is used to indicate a type of data;

[0350] Grouping the indication information to obtain at least one group of indication information;

[0351] Indication information groups are respectively allocated to the first AI network function network element and at least one second AI network function network element participating in executing the AI ​​service to obtain the data allocation result, wherein the indication information group allocated to the first AI network function network element or the at least one second AI network function network element participating in executing the AI ​​service is used to instruct: to allocate the data group indicated by the indication information group corresponding to the first AI network function network element or the second AI network function network element participating in executing the AI ​​service to the first AI network function network element or the second AI network function network element participating in executing the AI ​​service.

[0352] Optionally, in one embodiment of the present disclosure, the processing module is further configured to:

[0353] The indication information of the data is grouped based on the importance of the data to the AI ​​service and / or the difficulty of processing the data.

[0354] Optionally, in one embodiment of the present disclosure, the processing module is further configured to:

[0355] Allocate a specific indication information group to the first AI network function network element, and allocate other indication information groups to at least one second AI network function network element participating in executing the AI ​​service;

[0356] The data corresponding to the specific indication information group is most important to the AI ​​service, and / or the data corresponding to the specific indication information group is most difficult to process.

[0357] Optionally, in one embodiment of the present disclosure, the apparatus is further configured to:

[0358] Allocating resource blocks with different weights to at least one second AI network function network element participating in executing the AI ​​service;

[0359] The weight of the resource block allocated to the second AI network function network element is positively correlated with the importance and processing difficulty of the data corresponding to the indication information group allocated to the second AI network function network element for the AI ​​service.

[0360] Optionally, in one embodiment of the present disclosure, the NF network element includes at least one of the following:

[0361] User Data Register UDR network element;

[0362] Unstructured data storage function UDSF network element.

[0363] Optionally, in one embodiment of the present disclosure, the apparatus is further configured to:

[0364] Aggregate and structure the first data execution result and the second data execution result to obtain a final service execution result corresponding to the AI ​​service.

[0365] Optionally, in one embodiment of the present disclosure, the first AI network function network element and at least one second AI network function network element participating in executing the AI ​​service determine the data execution result in parallel.

[0366] FIG18 is a schematic diagram of the structure of a communication device provided by an embodiment of the present disclosure. As shown in FIG18 , the device may include:

[0367] The transceiver module is used to receive data allocated by the NF network element, which is required to complete the AI ​​service;

[0368] a processing module, configured to determine a second data execution result based on the data allocated by the NF network element;

[0369] The transceiver module is further configured to send the second data execution result to the first AI network function network element.

[0370] In summary, in the communication device provided in the embodiments of the present disclosure, a first AI network function element with decision-making capabilities receives a first request message sent by an AMF element, indicating an AI service requested by a terminal device. Furthermore, the first AI network function element determines a data allocation result based on the first request message. The data allocation result includes information indicating the data required to complete the AI ​​service allocated to the first AI network function element and at least one second AI network function element participating in executing the AI ​​service. The first AI network function element then sends the data allocation result to the NF element and receives data allocated by the NF element based on the data allocation result. Finally, the first AI network function element determines a first data execution result based on the data allocated by the NF element and receives a second data execution result sent by the second AI network function element. Therefore, the AI ​​service provision method disclosed in the present disclosure is not a simple overlay on existing network processes, but rather a complete and universal AI service provision process. Based on this method, the requested AI service can be accurately provided to the terminal device, thereby meeting the needs of personalized AI services. Also, in the method disclosed herein, by grouping the data required to complete the AI ​​service requested by the terminal device and respectively allocating different groups of data to the first AI network function network element and at least one second AI network function network element that participates in executing the AI ​​service, classified management of the AI ​​service is achieved, and fine-grained division of the AI ​​functions is achieved, which will make the subsequent AI service results more accurate. At the same time, in the method disclosed herein, the first AI network function network element and the second AI network function network element determine the data execution results in parallel, thereby improving execution efficiency. In addition, in the present disclosure, the first AI network function network element and multiple second AI network function network elements and other network elements in the core network can constitute a unified technical architecture for providing AI services, thereby avoiding the problem of fragmentation of AI application scenarios.

[0371] Optionally, in one embodiment of the present disclosure, the NF network element includes at least one of the following:

[0372] UDR network element;

[0373] UDSF network element.

[0374] Optionally, in one embodiment of the present disclosure, the apparatus is further configured to:

[0375] receiving a status request message sent by the first AI network function network element, where the status request message is used to request status information related to the AI ​​service execution capability of the second AI network function network element;

[0376] Send the status information to the first AI network function network element.

[0377] Optionally, in an embodiment of the present disclosure, the status information includes at least one of the following:

[0378] Energy status information;

[0379] Communication status information.

[0380] Optionally, in one embodiment of the present disclosure, the apparatus is further configured to:

[0381] Receive a resource block allocated by the first AI network function network element.

[0382] Optionally, in one embodiment of the present disclosure, the second AI network function network element, other second AI network function network elements, and the first AI network function network element determine the data execution result in parallel.

[0383] FIG19 is a schematic structural diagram of a communication device provided in an embodiment of the present disclosure. As shown in FIG18 , the device may include:

[0384] a transceiver module, configured to receive a data allocation result sent by a first AI network function network element, the data allocation result including: indication information corresponding to data required to complete the AI ​​service allocated to the first AI network function network element and at least one second AI network function network element participating in executing the AI ​​service;

[0385] The transceiver module is further configured to allocate corresponding data to the first AI network function network element and at least one second AI network function network element participating in executing the AI ​​service based on the data allocation result.

[0386] In summary, in the communication device provided in the embodiments of the present disclosure, a first AI network function element with decision-making capabilities receives a first request message sent by an AMF element, indicating an AI service requested by a terminal device. Furthermore, the first AI network function element determines a data allocation result based on the first request message. The data allocation result includes information indicating the data required to complete the AI ​​service allocated to the first AI network function element and at least one second AI network function element participating in executing the AI ​​service. The first AI network function element then sends the data allocation result to the NF element and receives data allocated by the NF element based on the data allocation result. Finally, the first AI network function element determines a first data execution result based on the data allocated by the NF element and receives a second data execution result sent by the second AI network function element. Therefore, the AI ​​service provision method disclosed in the present disclosure is not a simple overlay on existing network processes, but rather a complete and universal AI service provision process. Based on this method, the requested AI service can be accurately provided to the terminal device, thereby meeting the needs of personalized AI services. Also, in the method disclosed herein, by grouping the data required to complete the AI ​​service requested by the terminal device and respectively allocating different groups of data to the first AI network function network element and at least one second AI network function network element that participates in executing the AI ​​service, classified management of the AI ​​service is achieved, and fine-grained division of the AI ​​functions is achieved, which will make the subsequent AI service results more accurate. At the same time, in the method disclosed herein, the first AI network function network element and the second AI network function network element determine the data execution results in parallel, thereby improving execution efficiency. In addition, in the present disclosure, the first AI network function network element and multiple second AI network function network elements and other network elements in the core network can constitute a unified technical architecture for providing AI services, thereby avoiding the problem of fragmentation of AI application scenarios.

[0387] Optionally, in an embodiment of the present disclosure, the indication information includes at least one of the following:

[0388] Data name;

[0389] Data identification.

[0390] FIG20 is a schematic structural diagram of a communication device provided in an embodiment of the present disclosure. As shown in FIG19 , the device may include:

[0391] a transceiver module, configured to receive a second request message sent by a terminal device, where the second request message indicates an AI service requested by the terminal device;

[0392] The transceiver module is further configured to send a first request message to the first AI network function network element, where the first request message indicates an AI service requested by the terminal device;

[0393] The transceiver module is further configured to receive a final service execution result corresponding to the AI ​​service sent by the first AI network function network element;

[0394] The transceiver module is further configured to send the final service execution result corresponding to the AI ​​service to the terminal device.

[0395] In summary, in the communication device provided in the embodiments of the present disclosure, a first AI network function element with decision-making capabilities receives a first request message sent by an AMF element, indicating an AI service requested by a terminal device. Furthermore, the first AI network function element determines a data allocation result based on the first request message. The data allocation result includes information indicating the data required to complete the AI ​​service allocated to the first AI network function element and at least one second AI network function element participating in executing the AI ​​service. The first AI network function element then sends the data allocation result to the NF element and receives data allocated by the NF element based on the data allocation result. Finally, the first AI network function element determines a first data execution result based on the data allocated by the NF element and receives a second data execution result from the second AI network function element. Therefore, the AI ​​service provision method disclosed in the present disclosure is not a simple overlay on existing network processes, but rather a complete and universal AI service provision process. Based on this method, the requested AI service can be accurately provided to the terminal device, thereby meeting the needs of personalized AI services. Also, in the method disclosed herein, by grouping the data required to complete the AI ​​service requested by the terminal device and respectively allocating different groups of data to the first AI network function network element and at least one second AI network function network element that participates in executing the AI ​​service, classified management of the AI ​​service is achieved, and fine-grained division of the AI ​​functions is achieved, which will make the subsequent AI service results more accurate. At the same time, in the method disclosed herein, the first AI network function network element and the second AI network function network element determine the data execution results in parallel, thereby improving execution efficiency. In addition, in the present disclosure, the first AI network function network element and multiple second AI network function network elements and other network elements in the core network can constitute a unified technical architecture for providing AI services, thereby avoiding the problem of fragmentation of AI application scenarios.

[0396] Optionally, in an embodiment of the present disclosure, the first request message and the second request message each include at least one of the following:

[0397] The AI ​​service type corresponding to the AI ​​service requested by the terminal device;

[0398] The AI ​​service ID corresponding to the AI ​​service requested by the terminal device.

[0399] Optionally, in one embodiment of the present disclosure, the apparatus is further configured to:

[0400] Receive a response message sent by the terminal device, where the response message is used to indicate whether the terminal device has successfully received the final service execution result corresponding to the AI ​​service.

[0401] Optionally, in one embodiment of the present disclosure, the apparatus is further configured to:

[0402] Receive a feedback result sent by the terminal device, where the feedback result is used to provide feedback on the satisfaction level of the final service execution result.

[0403] FIG21 is a schematic structural diagram of a communication device provided in an embodiment of the present disclosure. As shown in FIG20 , the device may include:

[0404] A transceiver module, configured to send a second request message to the AMF network element, where the second request message indicates the AI ​​service requested by the terminal device;

[0405] The transceiver module is used to receive the final service execution result corresponding to the AI ​​service sent by the AMF network element.

[0406] In summary, in the communication device provided in the embodiments of the present disclosure, a first AI network function element with decision-making capabilities receives a first request message sent by an AMF element, indicating an AI service requested by a terminal device. Furthermore, the first AI network function element determines a data allocation result based on the first request message. The data allocation result includes information indicating the data required to complete the AI ​​service allocated to the first AI network function element and at least one second AI network function element participating in executing the AI ​​service. The first AI network function element then sends the data allocation result to the NF element and receives data allocated by the NF element based on the data allocation result. Finally, the first AI network function element determines a first data execution result based on the data allocated by the NF element and receives a second data execution result sent by the second AI network function element. Therefore, the AI ​​service provision method disclosed in the present disclosure is not a simple overlay on existing network processes, but rather a complete and universal AI service provision process. Based on this method, the requested AI service can be accurately provided to the terminal device, thereby meeting the needs of personalized AI services. Also, in the method disclosed herein, by grouping the data required to complete the AI ​​service requested by the terminal device and respectively allocating different groups of data to the first AI network function network element and at least one second AI network function network element that participates in executing the AI ​​service, classified management of the AI ​​service is achieved, and fine-grained division of the AI ​​functions is achieved, which will make the subsequent AI service results more accurate. At the same time, in the method disclosed herein, the first AI network function network element and the second AI network function network element determine the data execution results in parallel, thereby improving execution efficiency. In addition, in the present disclosure, the first AI network function network element and multiple second AI network function network elements and other network elements in the core network can constitute a unified technical architecture for providing AI services, thereby avoiding the problem of fragmentation of AI application scenarios.

[0407] Optionally, in an embodiment of the present disclosure, the second request message includes at least one of the following:

[0408] The AI ​​service type corresponding to the AI ​​service requested by the terminal device;

[0409] The AI ​​service ID corresponding to the AI ​​service requested by the terminal device.

[0410] Optionally, in one embodiment of the present disclosure, the apparatus is further configured to:

[0411] Send a response message to the AMF network element, where the response message is used to indicate whether the terminal device has successfully received the final service execution result corresponding to the AI ​​service.

[0412] Optionally, in one embodiment of the present disclosure, the apparatus is further configured to:

[0413] Send a feedback result to the AMF network element, where the feedback result is used to provide feedback on the satisfaction level with the final service execution result.

[0414] FIG22 is a schematic diagram of the structure of a communication system provided by an embodiment of the present disclosure. As shown in FIG21 , the system may include:

[0415] The first network element (i.e., the aforementioned AMF network element) is configured to receive a second request message sent by a terminal device, where the second request message indicates the AI ​​service requested by the terminal device, and send a first request message, where the first request message indicates the AI ​​service requested by the terminal device;

[0416] The second network element (i.e., the aforementioned first AI network function network element) is configured to receive the first request message, determine a data allocation result based on the first request message, the data allocation result including: indication information corresponding to data required to complete the AI ​​service allocated to the first AI network function network element and at least one second AI network function network element participating in executing the AI ​​service, and transmit the data allocation result;

[0417] a third network element (i.e., the aforementioned NF network element), configured to receive the data allocation result and allocate data based on the data allocation result;

[0418] The second network element is further configured to receive the data allocated by the third network element based on the data allocation result, and determine the first data execution result;

[0419] At least one fourth network element (i.e., the aforementioned second AI network function network element), configured to receive the data allocated by the third network element based on the data allocation result, determine a second data execution result, and send the second data execution result;

[0420] The second network element is further configured to receive each second data execution result, determine a final service execution result corresponding to the AI ​​service based on the first data execution result and the second data execution result, and send the final service execution result corresponding to the AI ​​service;

[0421] The first network element is further used to receive the final service execution result corresponding to the AI ​​service, and send the final service execution result corresponding to the AI ​​service to the terminal device.

[0422] In summary, in the communication system provided by the embodiments of the present disclosure, a first AI network function element with decision-making capabilities receives a first request message sent by an AMF element, indicating an AI service requested by a terminal device. Furthermore, the first AI network function element determines a data allocation result based on the first request message. The data allocation result includes information indicating the data required to complete the AI ​​service allocated to the first AI network function element and at least one second AI network function element participating in executing the AI ​​service. The first AI network function element then sends the data allocation result to the NF element and receives data allocated by the NF element based on the data allocation result. Finally, the first AI network function element determines a first data execution result based on the data allocated by the NF element and receives a second data execution result sent by the second AI network function element. Therefore, the AI ​​service provision method disclosed in the present disclosure is not a simple overlay on existing network processes, but rather a complete and universal AI service provision process. Based on this method, the requested AI service can be accurately provided to the terminal device, thereby meeting the needs of personalized AI services. Also, in the method disclosed herein, by grouping the data required to complete the AI ​​service requested by the terminal device and respectively allocating different groups of data to the first AI network function network element and at least one second AI network function network element that participates in executing the AI ​​service, classified management of the AI ​​service is achieved, and fine-grained division of the AI ​​functions is achieved, which will make the subsequent AI service results more accurate. At the same time, in the method disclosed herein, the first AI network function network element and the second AI network function network element determine the data execution results in parallel, thereby improving execution efficiency. In addition, in the present disclosure, the first AI network function network element and multiple second AI network function network elements and other network elements in the core network can constitute a unified technical architecture for providing AI services, thereby avoiding the problem of fragmentation of AI application scenarios.

[0423] Please refer to Figure 23, which is a schematic diagram of the structure of a communication device 2300 provided in an embodiment of the present application. Communication device 2300 can be a network device or a terminal device, or a chip, chip system, or processor that supports the network device to implement the above method. It can also be a chip, chip system, or processor that supports the terminal device to implement the above method. This device can be used to implement the method described in the above method embodiment. For details, please refer to the description of the above method embodiment.

[0424] The communication device 2300 may include one or more processors 2301. The processor 2301 may be a general-purpose processor or a dedicated processor. For example, it may be a baseband processor or a central processing unit. The baseband processor may be used to process communication protocols and communication data, and the central processing unit may be used to control the communication device (e.g., a base station, a baseband chip, a terminal device, a terminal device chip, a DU or CU, etc.), execute computer programs, and process computer program data.

[0425] Optionally, the communication device 2300 may further include one or more memories 2302, on which a computer program 2304 may be stored. The processor 2301 executes the computer program 2304 to cause the communication device 2300 to perform the method described in the above method embodiment. Optionally, the memory 2302 may also store data. The communication device 2300 and the memory 2302 may be provided separately or integrated together.

[0426] Optionally, the communication device 2300 may further include a transceiver 2305 and an antenna 2306. The transceiver 2305 may be referred to as a transceiver unit, a transceiver, or a transceiver circuit, and is configured to implement transceiver functions. The transceiver 2305 may include a receiver and a transmitter. The receiver may be referred to as a receiver or a receiving circuit, and is configured to implement a receiving function; the transmitter may be referred to as a transmitter or a transmitting circuit, and is configured to implement a transmitting function.

[0427] Optionally, the communication device 2300 may further include one or more interface circuits 2307. The interface circuit 2307 is configured to receive code instructions and transmit the instructions to the processor 2301. The processor 2301 executes the code instructions to enable the communication device 2300 to perform the method described in the above method embodiment.

[0428] In one implementation, the processor 2301 may include a transceiver for implementing receiving and transmitting 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 the receiving and transmitting functions may be separate or integrated. The transceiver circuit, interface, or interface circuit may be used for reading and writing code / data, or may be used for transmitting or delivering signals.

[0429] In one implementation, processor 2301 may store a computer program 2303. Computer program 2303, when executed on processor 2301, enables communication device 2300 to perform the method described in the above method embodiment. Computer program 2303 may be embedded in processor 2301, in which case processor 2301 may be implemented by hardware.

[0430] In one implementation, the communication device 2300 may include a circuit that can implement the functions of sending, receiving, or communicating in the aforementioned method embodiments. The processor and transceiver described in this application can be implemented on an integrated circuit (IC), an analog IC, a radio frequency integrated circuit RFIC, a mixed signal IC, an application specific integrated circuit (ASIC), a printed circuit board (PCB), an electronic device, etc. The processor and transceiver can also be manufactured using various IC process technologies, such as complementary metal oxide semiconductor (CMOS), N-type metal oxide semiconductor (nMetal-oxide-semiconductor, NMOS), P-type metal oxide semiconductor (positive channel metal oxide semiconductor, PMOS), bipolar junction transistor (bipolar junction transistor, BJT), bipolar CMOS (BiCMOS), silicon germanium (SiGe), gallium arsenide (GaAs), etc.

[0431] 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 not be limited to FIG23. The communication device may be an independent device or may be part of a larger device. For example, the communication device may be:

[0432] (1) An independent integrated circuit (IC), or chip, or chip system or subsystem;

[0433] (2) a collection of one or more ICs, optionally including a storage component for storing data and computer programs;

[0434] (3) ASIC, such as modem;

[0435] (4) Modules that can be embedded in other devices;

[0436] (5) Receivers, terminal devices, intelligent terminal devices, cellular phones, wireless devices, handheld devices, mobile units, vehicle-mounted devices, network devices, cloud devices, artificial intelligence devices, etc.;

[0437] (6)Others, etc.

[0438] If the communication device can be a chip or a chip system, please refer to the structural diagram of the chip shown in Figure 24. The chip shown in Figure 24 includes a processor 2401 and an interface 2402. The number of processors 2401 can be one or more, and the number of interfaces 2402 can be multiple.

[0439] Optionally, the chip further includes a memory 2403, which is used to store necessary computer programs and data.

[0440] Those skilled in the art will also appreciate that the various illustrative logical blocks and steps listed in the embodiments of the present application can be implemented by electronic hardware, computer software, or a combination of both. Whether such functions are implemented by hardware or software depends on the specific application and the design requirements of the entire system. Those skilled in the art may use various methods to implement the described functions for each specific application, but such implementation should not be construed as exceeding the scope of protection of the embodiments of the present application.

[0441] The present application also provides a readable storage medium having instructions stored thereon, which implement the functions of any of the above method embodiments when executed by a computer.

[0442] The present application also provides a computer program product, which implements the functions of any of the above method embodiments when executed by a computer.

[0443] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer programs. When the computer program is loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer program can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer program can be transmitted from one website, computer, server or data center to another website, computer, server or data center via a wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) method. 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 or data center that includes one or more available media integrated. The available medium may be a magnetic medium (eg, a floppy disk, a hard disk, a magnetic tape), an optical medium (eg, a high-density digital video disc (DVD)), or a semiconductor medium (eg, a solid state disk (SSD)).

[0444] Those skilled in the art will understand that the various numerical numbers such as first and second involved in this application are only for the convenience of description and are not used to limit the scope of the embodiments of this application, and also indicate the order of precedence.

[0445] In this application, at least one can also be described as one or more, and multiple can be two, three, four or more, which is not limited in this application. In the embodiments of this application, for a technical feature, the technical features in the technical feature are distinguished by "first", "second", "third", "A", "B", "C" and "D", and there is no order of precedence or size between the technical features described by "first", "second", "third", "A", "B", "C" and "D".

[0446] The correspondences shown in the tables in this application can be configured or predefined. The values ​​of the information in each table are examples only and can be configured to other values, which are not limited by this application. When configuring the correspondence between information and parameters, it is not necessarily required to configure all the correspondences shown in each table. For example, in the tables in this application, the correspondences shown in certain rows may not be configured. For another example, appropriate deformation adjustments can be made based on the above tables, such as splitting, merging, etc. The names of the parameters shown in the titles of the above tables can also use other names that can be understood by the communication device, and the values ​​or representations of the parameters can also use other values ​​or representations that can be understood by the communication device. When implementing the above tables, other data structures can also be used, such as arrays, queues, containers, stacks, linear lists, pointers, linked lists, trees, graphs, structures, classes, heaps, hash tables or hash tables, etc.

[0447] The predefined in this application may be understood as defined, predefined, stored, pre-stored, pre-negotiated, pre-configured, solidified, or pre-burned.

[0448] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0449] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0450] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

Claims

1. A method for providing services based on artificial intelligence (AI), characterized in that: Executed by the first AI network function element with decision-making capabilities, including: Receive a first request message sent by a mobility management function (AMF) network element, where the first request message indicates an AI service requested by a terminal device; Determining a data allocation result based on the first request message, the data allocation result including: indication information corresponding to data required to complete the AI ​​service allocated to the first AI network function network element and at least one second AI network function network element participating in executing the AI ​​service; Sending the data allocation result to the network function NF network element, and receiving the data allocated by the NF network element based on the data allocation result; Determine a first data execution result based on the data allocated by the NF network element, and receive a second data execution result sent by the second AI network function network element.

2. The method according to claim 1, wherein The method further comprises: Determine a final service execution result corresponding to the AI ​​service based on the first data execution result and the second data execution result; Send the final service execution result corresponding to the AI ​​service to the AMF.

3. The method according to claim 1, wherein The first request message includes at least one of the following: The AI ​​service type corresponding to the AI ​​service requested by the terminal device; The AI ​​service identification ID corresponding to the AI ​​service requested by the terminal device.

4. The method according to claim 1, wherein The method further comprises: At least one second AI network function network element that participates in executing the AI ​​service is determined from a plurality of second AI network function network elements communicatively connected to the first AI network function network element.

5. The method according to claim 4, wherein The determining of at least one second AI network function network element participating in executing the AI ​​service includes: Determine the AI ​​service type corresponding to the AI ​​service; Determine the AI ​​algorithms required to complete the AI ​​services; Determine the data categories required to complete the AI ​​service; Sending a status request message to a second AI network function network element communicatively connected to the first AI network function network element, wherein the status request message is used to request status information related to the AI ​​service execution capability of the second AI network function network element; receiving status information sent by the second AI network function network element; At least one second AI network function network element that participates in executing the AI ​​service is selected based on at least one of the AI ​​service type, the AI ​​algorithm, the data category, and the status information.

6. The method according to claim 5, wherein The status information includes at least one of the following: Energy status information; Communication status information.

7. The method according to claim 1, wherein The indication information includes at least one of the following: Data name; Data identification.

8. The method according to claim 1 or 5, wherein: The determining the data allocation result based on the first request message includes: Determine, based on the first request message, indication information corresponding to the data required to complete the AI ​​service, where each indication information is used to indicate a type of data; Grouping the indication information to obtain at least one group of indication information; Indication information groups are respectively allocated to the first AI network function network element and at least one second AI network function network element participating in executing the AI ​​service to obtain the data allocation result, wherein the indication information group allocated to the first AI network function network element or the at least one second AI network function network element participating in executing the AI ​​service is used to instruct: to allocate the data group indicated by the indication information group corresponding to the first AI network function network element or the second AI network function network element participating in executing the AI ​​service to the first AI network function network element or the second AI network function network element participating in executing the AI ​​service.

9. The method according to claim 8, wherein The grouping the indication information to obtain at least one group of indication information includes: The indication information of the data is grouped based on the importance of the data to the AI ​​service and / or the difficulty of processing the data.

10. The method according to claim 8, wherein The method of respectively allocating an indication information group to the first AI network function network element and at least one second AI network function network element participating in executing the AI ​​service includes: Allocate a specific indication information group to the first AI network function network element, and allocate other indication information groups to at least one second AI network function network element participating in executing the AI ​​service; The data corresponding to the specific indication information group is most important to the AI ​​service, and / or the data corresponding to the specific indication information group is most difficult to process.

11. The method according to claim 9, wherein The method further comprises: Allocating resource blocks with different weights to at least one second AI network function network element participating in executing the AI ​​service; The weight of the resource block allocated to the second AI network function network element is positively correlated with the importance and processing difficulty of the data corresponding to the indication information group allocated to the second AI network function network element for the AI ​​service.

12. The method according to claim 1, wherein The NF network element includes at least one of the following: User Data Register UDR network element; Unstructured data storage function UDSF network element.

13. The method according to claim 2, wherein The determining a final service execution result corresponding to the AI ​​service based on the first data execution result and the second data execution result includes: Aggregate and structure the first data execution result and the second data execution result to obtain a final service execution result corresponding to the AI ​​service.

14. The method according to claim 1, wherein The first AI network function network element and at least one second AI network function network element participating in executing the AI ​​service determine the data execution result in parallel.

15. A method for providing services based on AI, characterized in that: Executed by a second AI network function element with execution capabilities, including: Receive data allocated by the NF network element, which is required to complete the AI ​​service; Determine a second data execution result based on the data allocated by the NF network element; Send the second data execution result to the first AI network function network element.

16. The method according to claim 15, wherein The NF network element includes at least one of the following: UDR network element; UDSF network element.

17. The method according to claim 15, wherein The method further comprises: receiving a status request message sent by the first AI network function network element, where the status request message is used to request status information related to the AI ​​service execution capability of the second AI network function network element; Send the status information to the first AI network function network element.

18. The method according to claim 17, wherein The status information includes at least one of the following: Energy status information; Communication status information.

19. The method according to claim 15, wherein The method further comprises: Receive a resource block allocated by the first AI network function network element.

20. The method of claim 15, wherein: The second AI network function network element, other second AI network function network elements, and the first AI network function network element determine the data execution result in parallel.

21. A method for providing services based on AI, characterized in that: Executed by NFs, including: receiving a data allocation result sent by the first AI network function network element, the data allocation result including: indication information corresponding to data required to complete the AI ​​service allocated to the first AI network function network element and at least one second AI network function network element participating in executing the AI ​​service; Based on the data allocation result, corresponding data is allocated to the first AI network function network element and at least one second AI network function network element participating in executing the AI ​​service.

22. The method according to claim 21, wherein The indication information includes at least one of the following: Data name; Data identification.

23. A method for providing services based on AI, characterized in that: Executed by the AMF network element, including: receiving a second request message sent by the terminal device, where the second request message indicates an AI service requested by the terminal device; Sending a first request message to the first AI network function network element, where the first request message indicates an AI service requested by the terminal device; receiving a final service execution result corresponding to the AI ​​service sent by the first AI network function network element; Send the final service execution result corresponding to the AI ​​service to the terminal device.

24. The method according to claim 23, wherein The first request message and the second request message each include at least one of the following: The AI ​​service type corresponding to the AI ​​service requested by the terminal device; The AI ​​service ID corresponding to the AI ​​service requested by the terminal device.

25. The method of claim 23, wherein: The method further comprises: Receive a response message sent by the terminal device, where the response message is used to indicate whether the terminal device has successfully received the final service execution result corresponding to the AI ​​service.

26. The method of claim 23, wherein: The method further comprises: Receive a feedback result sent by the terminal device, where the feedback result is used to provide feedback on the satisfaction level of the final service execution result.

27. A method for providing services based on AI, characterized in that: Executed by the terminal device, including: Send a second request message to the AMF network element, where the second request message indicates the AI ​​service requested by the terminal device; Receive the final service execution result corresponding to the AI ​​service sent by the AMF network element.

28. The method of claim 27, wherein: The second request message includes at least one of the following: The AI ​​service type corresponding to the AI ​​service requested by the terminal device; The AI ​​service ID corresponding to the AI ​​service requested by the terminal device.

29. The method of claim 28, wherein The method further comprises: Send a response message to the AMF network element, where the response message is used to indicate whether the terminal device has successfully received the final service execution result corresponding to the AI ​​service.

30. The method of claim 27, wherein: The method further comprises: Send a feedback result to the AMF network element, where the feedback result is used to provide feedback on the satisfaction level with the final service execution result.

31. A communication device, characterized in that: The device is configured in a first AI network function network element with decision-making capability, including: A transceiver module, configured to receive a first request message sent by a mobility management function (AMF) network element, where the first request message indicates an AI service requested by a terminal device; a processing module, configured to determine a data allocation result based on the first request message, the data allocation result comprising: indication information corresponding to data required to complete the AI ​​service allocated to the first AI network function network element and at least one second AI network function network element participating in executing the AI ​​service; The transceiver module is further configured to send the data allocation result to the NF network element and receive data allocated by the NF network element based on the data allocation result; The processing module is further configured to determine a first data execution result based on the data allocated by the NF network element, and receive a second data execution result sent by a second AI network function network element.

32. A communication device, characterized in that: The device is configured to be executed in a second AI network function network element having execution capability, including: The transceiver module is used to receive data allocated by the NF network element, which is required to complete the AI ​​service; a processing module, configured to determine a second data execution result based on the data allocated by the NF network element; The transceiver module is further configured to send the second data execution result to the first AI network function network element.

33. A communication device, characterized in that: The device is configured in a NF network element and includes: a transceiver module, configured to receive a data allocation result sent by a first AI network function network element, the data allocation result including: indication information corresponding to data required to complete the AI ​​service allocated to the first AI network function network element and at least one second AI network function network element participating in executing the AI ​​service; The transceiver module is further configured to allocate corresponding data to the first AI network function network element and at least one second AI network function network element participating in executing the AI ​​service based on the data allocation result.

34. A communication device, characterized in that: The device is configured in the AMF network element and includes: a transceiver module, configured to receive a second request message sent by a terminal device, where the second request message indicates an AI service requested by the terminal device; The transceiver module is further configured to send a first request message to the first AI network function network element, where the first request message indicates an AI service requested by the terminal device; The transceiver module is further configured to receive a final service execution result corresponding to the AI ​​service sent by the first AI network function network element; The transceiver module is further configured to send the final service execution result corresponding to the AI ​​service to the terminal device.

35. A communication device, characterized in that: The device is configured in a terminal device and includes: A transceiver module, configured to send a second request message to the AMF network element, where the second request message indicates the AI ​​service requested by the terminal device; The transceiver module is used to receive the final service execution result corresponding to the AI ​​service sent by the AMF network element.

36. A communication device, characterized in that The device includes a processor and a memory, wherein a computer program is stored in the memory, and the processor executes the computer program stored in the memory so that the device performs the method according to any one of claims 1 to 14, or the processor executes the computer program stored in the memory so that the device performs the method according to claims 15 to 20, or the processor executes the computer program stored in the memory so that the device performs the method according to claims 21 to 22, or the processor executes the computer program stored in the memory so that the device performs the method according to claims 23 to 26, or the processor executes the computer program stored in the memory so that the device performs the method according to claims 27 to 30.

37. A communication device, characterized in that: include: processor and interface circuitry, wherein The interface circuit is used to receive code instructions and transmit them to the processor; The processor is configured to run the code instructions to execute the method according to any one of claims 1 to 14, or to run the code instructions to execute the method according to claims 15 to 20, or to run the code instructions to execute the method according to claims 21 to 22, or to run the code instructions to execute the method according to claims 23 to 26, or to run the code instructions to execute the method according to claims 27 to 30.

38. A communication system, characterized in that: The system comprises: A first network element is configured to receive a second request message sent by a terminal device, where the second request message indicates an AI service requested by the terminal device, and send a first request message, where the first request message indicates the AI ​​service requested by the terminal device; a second network element, configured to receive the first request message, determine a data allocation result based on the first request message, the data allocation result comprising: indication information corresponding to data required to complete the AI ​​service allocated to the first AI network function network element and at least one second AI network function network element participating in executing the AI ​​service, and transmit the data allocation result; a third network element, configured to receive the data allocation result and allocate data based on the data allocation result; The second network element is further configured to receive the data allocated by the third network element based on the data allocation result, and determine the first data execution result; at least one fourth network element, configured to receive the data allocated by the third network element based on the data allocation result, determine a second data execution result, and send the second data execution result; The second network element is further configured to receive each second data execution result, determine a final service execution result corresponding to the AI ​​service based on the first data execution result and the second data execution result, and send the final service execution result corresponding to the AI ​​service; The first network element is further used to receive the final service execution result corresponding to the AI ​​service, and send the final service execution result corresponding to the AI ​​service to the terminal device.

39. A computer-readable storage medium storing instructions, which, when executed, cause the method according to any one of claims 1 to 14 to be implemented, or when executed, cause the method according to claims 15 to 20 to be implemented, or when executed, cause the method according to claims 21 to 22 to be implemented, or when executed, cause the method according to claims 23 to 26 to be implemented, or when executed, cause the method according to claims 27 to 30 to be implemented.

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