Method, apparatus, device and medium for describing capability of mobile communication system

Abstract

The application discloses a capability description method, device and equipment of a mobile communication system and a medium, and relates to the field of mobile communication. The method comprises: describing the capability of the mobile communication system by using an intelligent dimension and a target dimension; wherein the target dimension comprises at least one of a performance dimension and a flexibility dimension. The application can describe the relationship among the AI function, the user plane function and the control plane function in a systematic, complete and visual manner by introducing the intelligent dimension to describe the capability of the mobile communication system in the case of introducing the AI function in the mobile communication network, and can provide a clear quantitative and qualitative description method to conduct in-depth research on the mobile communication system with the AI function.

Description

Technical Field

[0001] This application relates to the field of mobile communications, and in particular to a capability description method, apparatus, device, and medium for use in mobile communication systems. Background Technology

[0002] 5G systems use User Plane (UP) and Control Plane (CP) functions to describe the capabilities of mobile communication systems.

[0003] The UP (Up) function dimension defines various functions from the physical layer to the core network. The purpose of the UP function is to achieve powerful mobile communication network performance, which is ultimately reflected in data transmission rate, reliability, and latency. The CP (Content Provider) function dimension defines the response methods under factors such as terminal mobility, terminal and network capabilities, with the main purpose of maintaining normal data transmission capabilities.

[0004] However, the above description method is not applicable to the capability description of 6G systems and systems that evolve from 6G systems. Summary of the Invention

[0005] This application provides a method, apparatus, terminal, and medium for describing the capabilities of mobile communication systems, which can provide a better description of mobile communication systems that incorporate artificial intelligence (AI) functions. The technical solution is as follows.

[0006] According to one aspect of this application, a method for describing the capabilities of a mobile communication system is provided, the method comprising:

[0007] The capabilities of the mobile communication system are described using both intelligent and target dimensions.

[0008] The target dimension includes at least one of the performance dimension and the flexibility dimension.

[0009] According to another aspect of this application, a method for optimizing AI functions is provided, the method comprising:

[0010] The application server interacts with the AI ​​cube of the mobile communication system to optimize the AI ​​function empowerment using the data obtained from the interaction. The AI ​​cube includes an orthogonal AI plane, an AI-enabled user plane, and an AI-enabled control plane.

[0011] The AI ​​plane is used to provide AI functions, the AI-enabled user plane is used to provide user plane functions based on the AI ​​functions, and the AI-enabled control plane is used to provide control plane functions based on the AI ​​functions.

[0012] According to another aspect of this application, a capability description apparatus for a mobile communication system is provided, the apparatus comprising:

[0013] The description module is used to describe the capabilities of the mobile communication system using intelligent and target dimensions.

[0014] The target dimension includes at least one of the performance dimension and the flexibility dimension.

[0015] According to another aspect of this application, an AI function optimization apparatus is provided, the apparatus comprising:

[0016] An interaction module is used to interact with the AI ​​cube of the mobile communication system to optimize the AI ​​function empowerment using the data obtained from the interaction. The AI ​​cube includes an AI plane, an AI-enabled user plane, and an AI-enabled control plane that are orthogonal to each other.

[0017] The AI ​​plane is used to provide AI functions, the AI-enabled user plane is used to provide user plane functions based on the AI ​​functions, and the AI-enabled control plane is used to provide control plane functions based on the AI ​​functions.

[0018] According to one aspect of this application, a network element device is provided, the network element device comprising: a processor; a transceiver connected to the processor; and a memory for storing executable instructions of the processor; wherein the processor is configured to load and execute the executable instructions to implement the capability description method of the mobile communication system as described above.

[0019] According to one aspect of this application, an application server is provided, the application server comprising: a processor; a transceiver connected to the processor; and a memory for storing executable instructions of the processor; wherein the processor is configured to load and execute the executable instructions to implement an optimized method for AI functions as described above.

[0020] According to one aspect of this application, a computer-readable storage medium is provided that stores executable instructions, which are loaded and executed by a processor to implement the capability description method or AI function optimization method of the mobile communication system as described above.

[0021] According to one aspect of this application, a computer program product or computer program is provided, the computer program product or computer program including computer instructions stored in a computer-readable storage medium, a processor of a computer device reading the computer instructions from the computer-readable storage medium, the processor executing the computer instructions, causing the computer device to perform the capability description method of the mobile communication system or the optimization method of AI function described in the above aspect.

[0022] According to one aspect of this application, a chip is provided, the chip including programmable logic circuitry or a program, the chip being used to implement the capability description method of a mobile communication system or the optimization method of AI functions as described above.

[0023] The technical solutions provided in this application have at least the following beneficial effects:

[0024] By introducing an intelligent dimension to describe the capabilities of mobile communication systems, we can systematically, completely, and vividly describe the relationship between AI functions, user plane functions, and control plane functions when AI functions are introduced into mobile communication networks. This provides a clear quantitative and qualitative descriptive method for in-depth research on mobile communication systems that incorporate AI. Attached Figure Description

[0025] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0026] Figure 1 This is a schematic diagram of a mobile communication system provided in an exemplary embodiment of this application;

[0027] Figure 2 This is a flowchart of a capability description method for a mobile communication system provided in an exemplary embodiment of this application;

[0028] Figure 3 This is a schematic diagram of an AI cube provided in an exemplary embodiment of this application;

[0029] Figure 4 This is a flowchart of a capability description method for a mobile communication system provided in an exemplary embodiment of this application;

[0030] Figure 5 This is a schematic diagram of a user plane provided in an exemplary embodiment of this application;

[0031] Figure 6This is a schematic diagram of a control plane provided in an exemplary embodiment of this application;

[0032] Figure 7 This is a schematic diagram of an AI cube provided in an exemplary embodiment of this application;

[0033] Figure 8 This is a flowchart of an exemplary embodiment of the AI ​​function optimization method provided in this application;

[0034] Figure 9 This is a schematic diagram of an optimization method for AI functionality provided in an exemplary embodiment of this application;

[0035] Figure 10 This is a structural block diagram of a capability description apparatus for a mobile communication system provided in an exemplary embodiment of this application;

[0036] Figure 11 This is a structural block diagram of an AI function optimization device provided in an exemplary embodiment of this application;

[0037] Figure 12 This is a schematic diagram of the structure of a communication device provided in an exemplary embodiment of this application. Detailed Implementation

[0038] To make the objectives, technical solutions, and advantages of this application clearer, the embodiments of this application will be described in further detail below with reference to the accompanying drawings.

[0039] Figure 1 A schematic diagram of the architecture of a mobile communication system provided in an exemplary embodiment of this application is shown. Figure 1 As shown, the system architecture 100 may include: User Equipment (UE), Radio Access Network (RAN), Core Network (CN), and Data Network (DN). Among them, UE, RAN, and CN are the main components of the architecture. Logically, they can be divided into two parts: the user plane and the control plane. The control plane is responsible for the management of the mobile network, and the user plane is responsible for the transmission of service data.

[0040] UE (User Equipment): This is the entry point for mobile users to interact with the network. It provides basic computing and storage capabilities, displays service windows to the user, and accepts user input. The UE will use next-generation air interface technology to establish signal and data connections with the RAN (Radio Network Array), thereby transmitting control signals and service data to the mobile network.

[0041] RAN: Similar to a base station in a traditional network, it is deployed close to the UE (User Equipment) to provide network access for authorized users within the cell coverage area. It can transmit user data using transmission tunnels of different quality levels based on user level and service requirements. The RAN manages its own resources, utilizes them efficiently, and provides access services to the UE on demand, forwarding control signals and user data between the UE and the core network.

[0042] The Network Controller (CN) is responsible for maintaining the subscription data of the mobile network, managing the network elements of the mobile network, and providing the UE with functions such as session management, mobility management, policy management, and security authentication. When the UE attaches, it provides network access authentication; when the UE makes a service request, it allocates network resources for the UE; when the UE moves, it updates network resources for the UE; when the UE is idle, it provides a fast recovery mechanism for the UE; when the UE detaches, it releases network resources for the UE; and when the UE has service data, it provides data routing functions, such as forwarding uplink data to the Network Controller (DN); or receiving downlink data from the UE from the DN, forwarding it to the Ranging RAN, and then sending it to the UE.

[0043] DN: This is the data network that provides business services to users. Generally, the client is located at the UE (User Equipment), and the application server is located in the data network. The data network can be a private network, such as a local area network (LAN), or an external network not controlled by the operator, such as the Internet. It can also be a dedicated network jointly deployed by the operator, such as for configuring Internet Protocol (IP) and IP Multimedia Core Network Subsystem (IMS) services.

[0044] Figure 2 A flowchart illustrating a capability description method for a mobile communication system provided in an exemplary embodiment of this application is shown. This method can be performed by a mobile communication system or a computer device, and the method includes:

[0045] Step 210: Describe the capabilities of the mobile communication system using the intelligence dimension and the target dimension;

[0046] The target dimensions include at least one of performance and flexibility. Intelligence refers to the intelligence of the mobile communication system in terms of artificial intelligence. Performance refers to the performance of the mobile communication system when providing mobile communication services. Flexibility refers to the mobile communication system's ability to withstand various changes while providing mobile communication services.

[0047] Among them, the performance dimension can also be called the user plane dimension, and the flexibility dimension can also be called the control plane dimension.

[0048] This step includes, but is not limited to, at least one of the following three situations:

[0049] • The capabilities of mobile communication systems are described using both intelligence and performance dimensions;

[0050] • The capabilities of mobile communication systems are described using the dimensions of intelligence and flexibility;

[0051] • The capabilities of mobile communication systems are described using the dimensions of intelligence, performance, and flexibility.

[0052] With the advent of AI, user functions in mobile communication systems will be upgraded to AI-powered user functions (AI-powered UP), and control functions in mobile communication systems will be upgraded to AI-powered control functions (AI-powered CP). AI-powered functions are also known as AI optimization or AI-driven functions.

[0053] In an exemplary embodiment, an AI cube can be introduced to describe the capabilities of a mobile communication system. The AI ​​cube includes mutually orthogonal AI planes, an AI-enabled user plane, and an AI-enabled control plane. The AI ​​plane is also known as the AI ​​functional plane.

[0054] Figure 3 An AI cube 30 is shown, which includes: an AI plane, an AI-enabled user plane, and an AI-enabled control plane. Wherein:

[0055] The AI ​​plane is used to provide AI functionality, and it determines the level of intelligence in the user plane and control plane. Optionally, the AI ​​plane is used to describe the upper bound of the intelligence dimension of the mobile communication system. The stronger the capabilities of the AI ​​plane, the higher the level of intelligence it can enable in the user plane or control plane.

[0056] AI-enabled user plane is used to provide user plane functions based on AI capabilities; it can also be called user plane or AI-optimized user plane.

[0057] AI-enabled control plane is used to provide control plane functions based on AI capabilities; it can also be called control plane or AI-optimized control plane.

[0058] With the intelligence, performance, and flexibility dimensions forming mutually orthogonal coordinate axes, the plane defined or determined by the orthogonal intelligence and performance dimensions constitutes the AI-enabled user plane. The plane defined or determined by the orthogonal intelligence and flexibility dimensions constitutes the AI-enabled control plane.

[0059] The AI ​​plane empowers traditional CP and UP dimensions by providing general AI functions, forming an AI-enabled control plane and an AI-enabled user plane.

[0060] The AI ​​plane provides functions such as model storage, data collection, model training, model inference, and model deployment to enable AI services. These functions, as resources, are specifically used to enhance and train suitable AI models for the user plane, and then deploy them to the user plane to form an AI-enabled user plane; and / or, to enhance and train suitable AI models for the control plane, and then deploy them to the control plane to form an AI-enabled control plane.

[0061] Since the three planes are orthogonal to each other and each has its own value boundaries, the AI ​​cube, formed by the AI ​​plane, the AI-enabled control plane, the AI-enabled user plane, and three other parallel planes determined by the value boundaries of the three planes, constitutes the capability range of the mobile communication system. In other words, the space of the AI ​​cube is the capability range of the mobile communication system, and different subnets obtained by on-demand networking in the mobile communication system can all find their corresponding positions within the space of the AI ​​cube.

[0062] In summary, the method provided in this embodiment, by introducing an intelligent dimension to describe the capabilities of a mobile communication system, can systematically, completely, and vividly describe the relationship between AI functions, user plane functions, and control plane functions when AI functions are introduced into a mobile communication network. It can provide a clear quantitative and qualitative descriptive method for in-depth research on mobile communication systems that have introduced AI.

[0063] Figure 4 A flowchart illustrating a capability description method for a mobile communication system provided in an exemplary embodiment of this application is shown. This method can be performed by a mobile communication system or a computer device, and the method includes:

[0064] Indicative, Figure 3 The three coordinate axes in the diagram represent the intelligence dimension, performance dimension, and flexibility dimension. The intelligence dimension corresponds to the AI ​​plane, the performance dimension corresponds to the user plane, and the flexibility dimension corresponds to the control plane. Using these three planes, the capabilities of the mobile communication system can be measured in one of the three dimensions. For example, step 210 may optionally include at least one of the following three steps:

[0065] Step 212: Use AI plane description to describe the AI ​​functions when enabling AI in mobile communication systems;

[0066] In terms of intelligence, the AI ​​plane is used to describe the relevant capabilities required for AI to empower the user plane and / or control plane. Optionally, AI empowerment of the user plane refers to AI optimization of the original functions of the user plane based on AI technology, and AI empowerment of the control plane refers to AI optimization of the original functions of the control plane based on AI technology.

[0067] The AI ​​plane, also known as the AI ​​functional plane, determines the upper limit of the intelligence level of the user plane and control plane. The stronger the AI ​​plane, the higher the level of intelligence it can enable in the CPU / UP. The AI ​​plane is used to provide AI functions. AI functions include at least one of the following:

[0068] • Storage function of AI models;

[0069] • AI model training data collection function;

[0070] • Training function of AI models;

[0071] • The reasoning function of AI models;

[0072] • The function of sending AI models to user plane network elements;

[0073] User plane network elements refer to network elements that provide user plane functions, such as user plane function (UPF) network elements.

[0074] • The function of sending AI models to control plane network elements.

[0075] Control plane network elements refer to network elements that provide control plane functions, such as Session Management Function (SMF) and Policy Control Function (PCF).

[0076] For example, the AI ​​model mentioned above is one or more AI models. The AI ​​model sent to the user plane network element can be the same as or different from the AI ​​model sent to the control plane network element.

[0077] After AI capabilities are used to empower the user plane and / or control plane, the extent to which AI capabilities are enabled in the user plane and / or control plane can be measured using at least one of the following two methods:

[0078] First, the degree of substitution of the AI ​​plane, which indicates the extent to which the AI ​​plane substitutes for different levels of functions in the mobile communication system.

[0079] Generally speaking, the level of intelligence is strongly correlated with the scope of participation in intelligence. In mobile communication systems without AI functionality (i.e., traditional mobile communication systems), functional modules are implemented by user plane network elements and / or control plane network elements. In mobile communication systems with AI functionality, AI is used to replace functional modules at different levels in the traditional mobile communication system; the greater the scope of replacement, the higher the level of intelligence.

[0080] For example, the alternatives, from smallest to largest, include but are not limited to: network parameters, functional modules on a single network element, functional modules on multiple network elements, functional modules on a single protocol layer, functional modules on multiple protocol layers, and end-to-end implementations at the entire system level.

[0081] Second, the operational efficiency of the AI ​​plane under standard measurement conditions;

[0082] Standard measurement conditions (or unit measurement conditions) include at least one of the following: time, frequency, computational load, storage capacity, and energy consumption.

[0083] For example, the value in the intelligence dimension is directly proportional to the operational efficiency of the AI ​​plane when performing AI operations under standard measurement conditions.

[0084] For example, the maximum number of times the AI ​​plane performs AI operations per unit of time; the maximum number of times the AI ​​plane performs AI operations per unit of energy consumption; the maximum number of times the AI ​​plane performs AI operations per unit of frequency and energy consumption; the shortest time for the AI ​​plane to perform AI operations per unit of computational load, and so on.

[0085] When both substitution degree and operational efficiency are considered, the level of intelligence of a mobile communication system (or mobile communication network) can be calculated by weighting the substitution degree and operational efficiency.

[0086] The capability of intelligent dimension = a * degree of substitution + b * operational efficiency.

[0087] For example, weight a + weight b = 1.

[0088] Step 214: Use AI-enabled user plane to describe the AI-enabled status of user plane functions in the mobile communication system.

[0089] When performance is included as a target dimension, the AI-enabled user plane description describes the AI-enabled capabilities of user plane functions in a mobile communication system. This AI-enabled capability is also known as the AI-optimized capability profile.

[0090] For example, a traditional user plane can be empowered or optimized based on AI capabilities to obtain an AI-empowered user plane. In the AI ​​cube, the plane defined by the orthogonal intelligence dimension and performance dimension is the AI-empowered user plane. The AI-empowered user plane functionality includes at least one of the following:

[0091] • Throughput optimization based on AI models;

[0092] Throughput optimization based on AI models includes, but is not limited to: channel estimation based on AI models, noise reduction based on AI models, AI receivers based on AI models, intelligent scheduling based on data features, and priority scheduling based on packet features. Packet features include, but are not limited to: packet periodicity, packet size, and packet importance. Optionally, the data features and packet features are extracted by the AI ​​model.

[0093] • Latency optimization based on AI models;

[0094] For example, data packet scheduling based on data content can reduce data packet transmission latency.

[0095] • Reliability optimization based on AI models.

[0096] For example, resource reservation based on data characteristics ensures the priority of important data packets during transmission.

[0097] With AI empowerment, the user plane can be stretched from a line on a two-dimensional plane along the AI ​​dimension into an AI-enabled user plane, such as... Figure 5 As shown. Step 214 can be performed using at least one of the following two measurement methods:

[0098] First, the communication capabilities of the user plane enabled by AI are described to illustrate the AI-enabled features of the user plane functions in the mobile communication system.

[0099] Communication capabilities include at least one of the following: communication rate, reliability, latency, jitter, and user density.

[0100] Second, the AI-enabled computing power of the user plane is used to describe the AI-enabled functionality of user plane functions in mobile communication systems.

[0101] Service computing power refers to the computing capabilities used to serve business operations. In mobile communication systems that incorporate AI capabilities, the system not only acts as a conduit for data transmission but also provides computing power services to application-layer services. Therefore, the AI-enabled capabilities of user plane functions in a mobile communication system can be assessed through communication capabilities and service computing power.

[0102] When both communication capabilities and service computing power are used simultaneously, the AI-enabled functionality of user plane functions in a mobile communication system (or mobile communication network) can be calculated by using a weighted sum of the communication capabilities and service computing power.

[0103] Performance capability = c * communication capability + d * business computing power.

[0104] For example, weight c + weight d = 1.

[0105] Step 216: Using AI-enabled control plane, describe the AI-enabled status of control plane functions in mobile communication systems.

[0106] With flexibility as a target dimension, the AI-enabled control plane describes the AI-enabled capabilities of the control plane functions in a mobile communication system. This AI-enabled capability is also known as the AI-optimized capability profile.

[0107] For example, a traditional control plane can be empowered or optimized based on AI capabilities to obtain an AI-empowered control plane. In the AI ​​cube, the plane defined by the orthogonal intelligence and flexibility dimensions is the AI-empowered user plane. The AI-empowered control plane functionality includes at least one of the following:

[0108] AI-based mobility enhancement;

[0109] Positioning enhancement based on AI models;

[0110] Quality of Service (QoS) control based on AI models;

[0111] Cell selection based on AI models;

[0112] Cell reselection based on AI models;

[0113] AI-based load balancing.

[0114] With AI empowerment, the control plane can be stretched from a line on a two-dimensional plane along the AI ​​dimension into an AI-enabled control plane, such as... Figure 6 As shown. Step 216 can be measured in the following way:

[0115] • The performance of the control plane of the AI ​​cube under changing conditions is used to describe the flexibility of the mobile communication system.

[0116] Performance under changing conditions includes at least one of the following: the ability to withstand changes in terminal mobility, the execution speed when control policies change, the response speed when network conditions change, and the granularity of control policies when changes occur. These four aspects are used to comprehensively evaluate the flexibility of a mobile communication system. Generally, the higher the flexibility, the smaller the impact of changing conditions on performance.

[0117] Combination Figure 3 It can be seen that after determining the value boundaries (or metrics, values, or capabilities) of the mobile communication system in the dimensions of intelligence, performance, and flexibility, the AI ​​plane, AI-enabled control plane, and AI-enabled user plane of the mobile communication system are also determined. Since the three planes are orthogonal to each other and have their own value boundaries, the AI ​​cube formed by the AI ​​plane, the AI-enabled control plane, the AI-enabled user plane, and three other parallel planes determined by the value boundaries of the three planes constitutes the capability range of the mobile communication system. In other words, the AI ​​plane, the AI-enabled control plane, and the AI-enabled user plane constitute the three orthogonal planes of the AI ​​cube.

[0118] By qualitatively describing the three dimensions of the AI ​​cube, subnets in different scenarios can find their corresponding locations using this qualitatively described AI-Cube. Each subnet is constructed on demand within the capabilities of the mobile communication system. For example... Figure 7 As shown:

[0119] Subnet 1: Factory Production Line (IIoT in a Factory) Network (High Performance, High Flexibility): This network has extremely high requirements for reliability, latency, and speed to ensure precise production on the production line. To maintain reliability, it must be able to immediately trigger redundant path transmission or allocate resources to guarantee the transmission of critical services when speed changes occur. However, this service does not require network analysis or prediction of external conditions or human behavior; it only executes business operations within the factory.

[0120] Subnet 2: Smart Home Network (High Intelligence, High Flexibility): Users' smartphones, smartwatches, TVs, air conditioners, and other smart home devices are flexibly connected and can communicate with each other, but the communication performance requirements are not high. The smart home network needs to predict human behavior and change the network topology accordingly. For example, during a phone call, if a person moves from the office to their car, an AI model can predict the person's behavior and switch the call from the cellular network to the car's Bluetooth to ensure a smooth user experience.

[0121] Subnet 3: Auto-driving network (high performance, high intelligence): Auto-driving places high demands on network transmission latency and computing power. Furthermore, due to the high speed of the vehicle, there are also high requirements for on-demand network topology changes. In addition, high intelligence is required for vehicle trajectory prediction and risk assessment under specific scenario conditions.

[0122] In summary, the method provided in this embodiment describes the capabilities of a mobile communication system by using an AI cube formed by an AI plane, an AI-enabled user plane, and an AI-enabled control plane. This method can systematically, completely, and vividly describe the relationship between AI functions, user plane functions, and control plane functions when AI functions are introduced into a mobile communication network. It provides a clear quantitative and qualitative description method for in-depth research on mobile communication systems that have introduced AI.

[0123] Figure 8 A flowchart illustrating an exemplary embodiment of an AI functionality optimization method provided in this application is shown. This method can be executed by a mobile communication system and an application server, and includes:

[0124] Step 820: The mobile communication system interacts with the application server through the AI ​​cube.

[0125] The AI ​​cube comprises an AI plane, an AI-enabled user plane, and an AI-enabled control plane. The mobile communication system interacts with the application server via the AI ​​cube, or in other words, the application server interacts with the AI ​​cube, so that the AI ​​cube and / or the application server can use the data obtained from this interaction to optimize the AI ​​functionality.

[0126] Reference Figure 9 This step includes, but is not limited to, at least one of the following:

[0127] For AI planes:

[0128] Scenario 1: The mobile communication system provides the first cross-domain data to the application server through the AI ​​plane. The application server receives the first cross-domain data sent by the AI ​​plane and trains the AI ​​model on the application server side based on the first cross-domain data.

[0129] Domains in a mobile communication system include: UE, access network, core network, and data network (application server). Cross-domain data refers to data located in different domains. Due to the domain boundaries and privacy requirements of each domain, the application server cannot directly access data in certain domains. In this embodiment, the AI ​​plane of the mobile communication system provides first cross-domain data to the application server located in the data network, enabling the application server to train its AI model based on the first cross-domain data. Compared to using only application server-side data, this results in a higher-performance AI model.

[0130] Scenario 2: The application server provides the second cross-domain data to the AI ​​plane, and the mobile communication system receives the second cross-domain data sent by the application server through the AI ​​plane; the AI ​​plane trains the AI ​​model on the AI ​​plane side based on the second cross-domain data.

[0131] Similarly, the AI ​​plane cannot directly access data from the application server. After the application server provides the AI ​​plane with second-domain data, the AI ​​plane can train its own AI model based on this second-domain data. Compared to using only data from the AI ​​plane, this results in a higher-performing AI model.

[0132] Among them, at least one of the first cross-domain data and the second cross-domain data can be provided indirectly using encryption methods such as federated learning and homomorphic encryption.

[0133] For AI-enabled user interfaces:

[0134] Scenario 3: The application server provides the service content of data packets to the AI-enabled user plane of the mobile communication system. The mobile communication system obtains the service content of the data packets sent by the application server through the AI-enabled user plane. The AI-enabled user plane performs target operations based on the service content. The target operations include at least one of the following: AI-based user plane function adjustment, AI-based resource scheduling, AI-based service routing, and AI-based resource scheduling.

[0135] The business content includes, but is not limited to: text, images, audio, video, games, instant messaging, and calls. By providing perception capabilities to the user plane through the application server, the user plane can perceive the business content of the data packets provided by the application server in real time. This enables intelligent resource scheduling and intelligent routing based on business content, ensuring optimal data transmission rates, latency, and reliability. Simultaneously, it can fully leverage the computing power of the AI-enabled user plane and application server to process the business content.

[0136] For AI-enabled control plane:

[0137] Scenario 4: The application server provides application information to the AI-enabled control plane, and the mobile communication system obtains the application information provided by the application server through the AI-enabled control plane; the AI-enabled control plane adjusts its functions based on the application information.

[0138] Application information includes, but is not limited to, application data characteristics, application traffic predictions, etc. The control plane obtains application information provided by the application server, and then adjusts its functions based on AI based on this information. For example, the control plane predicts the future behavior of the application server based on the application information, and then performs flexible scheduling based on the prediction results.

[0139] Scenario 5: The mobile communication system provides data collection results to the application server through an AI-enabled control plane. The application server obtains the data collection results provided by the AI-enabled control plane and adjusts the application layer behavior based on the data collection results.

[0140] Data collection results include, but are not limited to: transmission latency, transmission bandwidth, and terminal feedback of data packets that match the application's data characteristics. The application server obtains the data collection results provided by the AI-enabled control plane, and adjusts application-layer behavior based on these results. For example, adjusting the video encoding / decoding bitrate based on transmission latency, and adjusting the switching between video call mode and voice call mode.

[0141] In summary, the method provided in this embodiment enables the opening of capabilities with third-party application servers based on the three planes of the AI ​​cube, and explains the collaborative relationship between the three planes, which can improve the performance of mobile communication networks based on optimized AI functions.

[0142] Figure 10 This application shows a block diagram of a capability description apparatus for a mobile communication system provided in an exemplary embodiment, the apparatus comprising:

[0143] Description module 1020 is used to describe the capabilities of the mobile communication system using intelligent dimensions and target dimensions;

[0144] The target dimension includes at least one of the performance dimension and the flexibility dimension.

[0145] In an optional design of this embodiment, the description module 1020 is used to describe the AI ​​functions of the mobile communication system when it is AI-enabled using an AI plane description.

[0146] When the target dimension includes the performance dimension, the AI-enabled user plane is used to describe the AI-enabled status of the user plane functions in the mobile communication system.

[0147] When the target dimension includes the flexibility dimension, the AI-enabled control plane is used to describe the AI-enabled status of the control plane functions in the mobile communication system.

[0148] In an optional design of this embodiment, the AI ​​plane is a plane perpendicular to the intelligence dimension, the AI-enabled user plane is a plane orthogonal to the intelligence dimension and the performance dimension, and the AI-enabled control plane is a plane orthogonal to the intelligence dimension and the flexibility dimension.

[0149] In an optional design of this embodiment, the metrics for measuring the effectiveness of AI functionality include at least one of the following:

[0150] The degree of substitution of the AI ​​plane is used to indicate the extent to which the AI ​​plane substitutes for different levels of functions in the mobile communication system;

[0151] And / or,

[0152] The operational efficiency of the AI ​​plane under standard measurement conditions; the standard measurement conditions include at least one of time, frequency, computational load, storage load, and energy consumption.

[0153] In an optional design of this embodiment, the AI ​​function includes at least one of the following functions:

[0154] The storage function of AI models;

[0155] The data collection function of the AI ​​model;

[0156] The training function of the AI ​​model;

[0157] The reasoning function of the AI ​​model;

[0158] The function of sending the AI ​​model to the user plane network element;

[0159] The function of sending the AI ​​model to the control plane network element.

[0160] In an optional design of this embodiment, the description module 1020 is used to describe the AI-enabled status of the user plane functions in the mobile communication system using the communication capabilities of the AI-enabled user plane; and / or, to describe the AI-enabled status of the user plane functions in the mobile communication system using the computing power of the AI-enabled user plane.

[0161] In an optional design of this embodiment, the user plane functionality includes at least one of the following:

[0162] Throughput optimization based on AI models;

[0163] Latency optimization based on the AI ​​model;

[0164] Reliability optimization based on the AI ​​model.

[0165] In an optional design of this embodiment, the description module 1020 is used to describe the AI ​​function enabling status of the control plane function in the mobile communication system by using the performance of the control plane of the AI ​​cube under changing conditions.

[0166] The performance under changing conditions includes at least one of the following: the ability to withstand changes in terminal movement speed, the execution speed when the control strategy changes, the response speed when the network state changes, and the fineness of control strategy changes.

[0167] In an optional design of this embodiment, the control plane function includes at least one of the following:

[0168] Mobility enhancement based on AI models;

[0169] Location enhancement based on the AI ​​model;

[0170] QoS control based on the AI ​​model;

[0171] Cell selection based on the AI ​​model;

[0172] Cell reselection based on the AI ​​model;

[0173] Load balancing based on the AI ​​model.

[0174] In an optional design of this embodiment, the AI ​​plane, the AI-enabled user plane, and the AI-enabled control plane constitute three orthogonal planes of the AI ​​cube.

[0175] In an optional design of this embodiment, the device further includes:

[0176] The interaction module 1040 is used to perform data interaction between the AI ​​cube and the application server so that the AI ​​cube and / or the application server can use the data obtained from the interaction to optimize the AI ​​function empowerment.

[0177] In an optional design of this embodiment, the interaction module 1040 is used to provide first cross-domain data to the application server through the AI ​​plane, so that the application server can train the AI ​​model on the application server side based on the first cross-domain data; or, to receive second cross-domain data sent by the application server through the AI ​​plane; and to train the AI ​​model on the AI ​​plane side based on the second cross-domain data.

[0178] In an optional design of this embodiment, the interaction module 1040 is used to obtain the service content of the data packets sent by the application server through the AI-enabled user plane; the AI-enabled user plane performs target operations based on the service content, and the target operations include at least one of: AI-based user plane function adjustment, AI-based resource scheduling, AI-based service routing, and AI-based resource scheduling.

[0179] In an optional design of this embodiment, the interaction module 1040 is used to obtain application information provided by the application server through the AI-enabled control plane; adjust the control plane function based on the application information; or, provide data collection results to the application server through the AI-enabled control plane so that the application server can adjust the application layer behavior based on the data collection results.

[0180] Figure 11 The diagram illustrates a block diagram of an AI function optimization apparatus provided in an exemplary embodiment of this application, the apparatus comprising:

[0181] The interaction module 1120 is used to interact with the AI ​​cube of the mobile communication system to optimize the AI ​​function empowerment using the data obtained from the interaction. The AI ​​cube includes an AI plane, an AI-enabled user plane, and an AI-enabled control plane that are orthogonal to each other.

[0182] The AI ​​plane is used to provide AI functions, the AI-enabled user plane is used to provide user plane functions based on the AI ​​functions, and the AI-enabled control plane is used to provide control plane functions based on the AI ​​functions.

[0183] In an optional design of this application embodiment, the interaction module 1120 is used to obtain first cross-domain data provided by the AI ​​plane through the application server; train the AI ​​model on the application server side based on the first cross-domain data; or send second cross-domain data to the AI ​​plane so that the AI ​​plane trains the AI ​​model on the AI ​​plane side based on the second cross-domain data.

[0184] In an optional design of this application embodiment, the interaction module 1120 is used to send data packet service content to the AI-enabled user plane so that the AI-enabled user plane can perform target operations based on the service content. The target operations include at least one of: AI-based user plane function adjustment, AI-based resource scheduling, AI-based service routing, and AI-based resource scheduling.

[0185] In an optional design of this application embodiment, the interaction module 1120 is used to send application information to the AI-enabled control plane so that the AI-enabled control plane can adjust its functions based on the application information; or, receive data collection results sent by the AI-enabled control plane; and adjust application layer behavior based on the data collection results.

[0186] Figure 12 The diagram shows a schematic of the structure of a communication device (terminal, network element, or application server) provided in an exemplary embodiment of this application. The communication device includes a processor 101, a receiver 102, a transmitter 103, a memory 104, and a bus 105.

[0187] The processor 101 includes one or more processing cores. The processor 101 executes various functional applications and information processing by running software programs and modules.

[0188] The receiver 102 and the transmitter 103 can be implemented as a communication component, which can be a communication chip.

[0189] The memory 104 is connected to the processor 101 via the bus 105.

[0190] The memory 104 can be used to store at least one instruction, and the processor 101 is used to execute the at least one instruction to implement the various steps in the above method embodiments. Specifically, the transmitter 103 is used to perform steps related to transmission; the receiver 104 is used to perform steps related to reception; and the processor 101 is used to perform steps other than transmission and reception.

[0191] Furthermore, the memory 104 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, including but not limited to: magnetic disks or optical disks, electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), static random access memory (SRAM), read-only memory (ROM), magnetic storage, flash memory, and programmable read-only memory (PROM).

[0192] In an exemplary embodiment, a computer-readable storage medium is also provided, which stores at least one instruction, at least one program, code set, or instruction set, wherein the at least one instruction, the at least one program, the code set, or the instruction set is loaded and executed by a processor to implement the capability description method or AI function optimization method of the mobile communication system provided in the above-described method embodiments.

[0193] In an exemplary embodiment, a computer program product or computer program is also provided, which includes computer instructions stored in a computer-readable storage medium. A processor of a communication device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the communication device to perform the capability description method of the mobile communication system or the optimization method of AI function described above.

[0194] Those skilled in the art will understand that all or part of the steps of the above embodiments can be implemented by hardware or by a program instructing related hardware. The program can be stored in a computer-readable storage medium, such as a read-only memory, a disk, or an optical disk.

[0195] The above description is merely an optional embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A method for describing the capabilities of a mobile communication system, characterized in that, The method includes: The capabilities of the mobile communication system are described using both intelligent and target dimensions. The target dimension includes at least one of the performance dimension and the flexibility dimension; The AI ​​plane is used to describe the AI ​​functions when the mobile communication system is AI-enabled. When the target dimension includes the performance dimension, the AI-enabled user plane is used to describe the AI-enabled status of the user plane functions in the mobile communication system. When the target dimension includes the flexibility dimension, the AI-enabled control plane is used to describe the AI-enabled function of the control plane function in the mobile communication system. The AI ​​plane, the AI-enabled user plane, and the AI-enabled control plane constitute the three orthogonal planes of the AI ​​cube. The AI ​​cube, formed by the AI ​​plane, the AI-enabled control plane, the AI-enabled user plane, and three other parallel planes determined by the value boundaries of the three planes, represents the capability range of the mobile communication system.

2. The method according to claim 1, characterized in that, The AI ​​plane is a plane perpendicular to the intelligent dimension; The AI-enabled user plane is a plane orthogonal to the intelligence dimension and the performance dimension. The AI-enabled control plane is a plane defined by the orthogonal dimensions of intelligence and flexibility.

3. The method according to claim 1, characterized in that, The metrics for measuring the effectiveness of AI functionality include at least one of the following: The degree of substitution of the AI ​​plane is used to indicate the extent to which the AI ​​plane substitutes for different levels of functions in the mobile communication system; And / or, The operational efficiency of the AI ​​plane under standard measurement conditions; the standard measurement conditions include at least one of time, frequency, computational load, storage load, and energy consumption.

4. The method according to claim 1, characterized in that, The AI ​​function includes at least one of the following functions: The storage function of AI models; The data collection function of the AI ​​model; The training function of the AI ​​model; The reasoning function of the AI ​​model; The function of sending the AI ​​model to the user plane network element; The function of sending the AI ​​model to the control plane network element.

5. The method according to claim 1, characterized in that, The AI-enabled user plane describes the AI-enabled functionality of the user plane functions in the mobile communication system, including: Using the AI-enabled user plane communication capabilities, describe the AI-enabled functionality of the user plane functions in the mobile communication system; And / or, Using the computing power of the AI-enabled user plane, the AI-enabled functionality of the user plane functions in the mobile communication system is described.

6. The method according to claim 5, characterized in that, The user plane functionality includes at least one of the following: Throughput optimization based on AI models; Latency optimization based on the AI ​​model; Reliability optimization based on the AI ​​model.

7. The method according to claim 1, characterized in that, The AI-enabled control plane describes the AI-enabled functionality of the control plane functions in the mobile communication system, including: The performance of the control plane of the AI ​​cube under changing conditions is used to describe the AI ​​function enablement of the control plane function in the mobile communication system. The performance under changing conditions includes at least one of the following: the ability to withstand changes in terminal movement speed, the execution speed when the control strategy changes, the response speed when the network state changes, and the fineness of control strategy changes.

8. The method according to claim 7, characterized in that, The control plane functions include at least one of the following: Mobility enhancement based on AI models; Location enhancement based on the AI ​​model; QoS control based on the AI ​​model; Cell selection based on the AI ​​model; Cell reselection based on the AI ​​model; Load balancing based on the AI ​​model.

9. The method according to any one of claims 1-8, characterized in that, The AI ​​cube interacts with the application server to optimize the AI ​​functionality using the data obtained from the interaction.

10. The method according to claim 9, characterized in that, The data interaction between the AI ​​cube and the application server includes: The AI ​​plane provides the application server with first cross-domain data so that the application server can train the AI ​​model on the application server side based on the first cross-domain data. or, The AI ​​plane receives second cross-domain data sent by the application server; and trains an AI model on the AI ​​plane side based on the second cross-domain data.

11. The method according to claim 10, characterized in that, The data interaction between the AI ​​cube and the application server includes: The AI-enabled user plane obtains the service content of the data packets sent by the application server; the AI-enabled user plane performs target operations based on the service content, and the target operations include at least one of: AI-based user plane function adjustment, AI-based resource scheduling, AI-based service routing, and AI-based resource scheduling.

12. The method according to claim 10, characterized in that, The data interaction between the AI ​​cube and the application server includes: The AI-enabled control plane acquires application information provided by the application server; based on the application information, it adjusts the AI-based control plane functions. or, The AI-enabled control plane provides data collection results to the application server, enabling the application server to adjust application-layer behavior based on the data collection results.

13. A capability description device for a mobile communication system, characterized in that, The device includes: The description module is used to describe the capabilities of the mobile communication system using intelligent and target dimensions. The target dimension includes at least one of the performance dimension and the flexibility dimension; The description module is used to describe the AI ​​functions of the mobile communication system when AI empowerment is applied using an AI plane; when the target dimension includes a performance dimension, it uses an AI-empowered user plane to describe the AI ​​function empowerment of the user plane functions in the mobile communication system; when the target dimension includes a flexibility dimension, it uses an AI-empowered control plane to describe the AI ​​function empowerment of the control plane functions in the mobile communication system; the AI ​​plane, the AI-empowered user plane, and the AI-empowered control plane constitute three orthogonal planes of an AI cube; the AI ​​cube formed by the AI ​​plane, the AI-empowered control plane, the AI-empowered user plane, and three other parallel planes determined by the value boundaries of the three planes constitutes the capability range of the mobile communication system.

14. The apparatus according to claim 13, characterized in that, The AI ​​plane is a plane perpendicular to the intelligent dimension; The AI-enabled user plane is a plane orthogonal to the intelligence dimension and the performance dimension. The AI-enabled control plane is a plane defined by the orthogonal dimensions of intelligence and flexibility.

15. The apparatus according to claim 13, characterized in that, The metrics for measuring the effectiveness of AI functionality include at least one of the following: The degree of substitution of the AI ​​plane is used to indicate the extent to which the AI ​​plane substitutes for different levels of functions in the mobile communication system; And / or, The operational efficiency of the AI ​​plane under standard measurement conditions; the standard measurement conditions include at least one of time, frequency, computational load, storage load, and energy consumption.

16. The apparatus according to claim 13, characterized in that, The AI ​​function includes at least one of the following functions: The storage function of AI models; The data collection function of the AI ​​model; The training function of the AI ​​model; The reasoning function of the AI ​​model; The function of sending the AI ​​model to the user plane network element; The function of sending the AI ​​model to the control plane network element.

17. The apparatus according to claim 13, characterized in that, The description module is used to describe the AI-enabled status of the user plane functions in the mobile communication system by using the communication capabilities of the AI-enabled user plane; and / or, to describe the AI-enabled status of the user plane functions in the mobile communication system by using the computing power of the AI-enabled user plane.

18. The apparatus according to claim 16, characterized in that, The user plane functionality includes at least one of the following: Throughput optimization based on AI models; Latency optimization based on the AI ​​model; Reliability optimization based on the AI ​​model.

19. The apparatus according to claim 13, characterized in that, The description module is used to describe the AI ​​function enabling status of the control plane function in the mobile communication system by taking the performance of the control plane of the AI ​​cube under changing conditions. The performance under changing conditions includes at least one of the following: the ability to withstand changes in terminal movement speed, the execution speed when the control strategy changes, the response speed when the network state changes, and the fineness of control strategy changes.

20. The apparatus according to claim 19, characterized in that, The control plane functions include at least one of the following: Mobility enhancement based on AI models; Location enhancement based on the AI ​​model; QoS control based on the AI ​​model; Cell selection based on the AI ​​model; Cell reselection based on the AI ​​model; Load balancing based on the AI ​​model.

21. The apparatus according to any one of claims 13 to 20, characterized in that, The device further includes: An interaction module is used to conduct data interaction between the AI ​​cube and the application server, so that the AI ​​cube and / or the application server can use the data obtained from the interaction to optimize the AI ​​function empowerment.

22. The apparatus according to claim 21, characterized in that, The interaction module is used to provide first cross-domain data to the application server through the AI ​​plane, so that the application server can train the AI ​​model on the application server side based on the first cross-domain data; or, to receive second cross-domain data sent by the application server through the AI ​​plane; and to train the AI ​​model on the AI ​​plane side based on the second cross-domain data.

23. The apparatus according to claim 21, characterized in that, The interaction module is used to obtain the service content of the data packets sent by the application server through the AI-enabled user plane; the AI-enabled user plane performs target operations based on the service content, and the target operations include at least one of: AI-based user plane function adjustment, AI-based resource scheduling, AI-based service routing, and AI-based resource scheduling.

24. The apparatus according to claim 21, characterized in that, The interaction module is used to obtain application information provided by the application server through the AI-enabled control plane; adjust the control plane function based on the application information; or provide data collection results to the application server through the AI-enabled control plane so that the application server can adjust the application layer behavior based on the data collection results.

25. A network element device, characterized in that, The network element equipment includes: processor; A transceiver connected to the processor; Memory for storing the executable instructions of the processor; The processor is configured to load and execute the executable instructions to implement the method as described in any one of claims 1 to 12.

26. A computer-readable storage medium, characterized in that, The readable storage medium stores executable instructions that are loaded and executed by a processor to implement the method as described in any one of claims 1 to 12.

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