Processing method, communication equipment and computer readable storage medium

Abstract

The invention provides a processing method, communication equipment and a computer readable storage medium. The processing method comprises the following steps: reporting an available artificial intelligence or machine learning function based on first content; according to the technical scheme of the invention, a mechanism for reporting the available artificial intelligence or machine learning function is perfected, the accuracy of reporting the available artificial intelligence or machine learning function can be improved, reasonable function management of the network equipment is facilitated, and / or the consistency of function configuration of the terminal equipment and the network equipment is kept, and / or the user experience is improved. And thus, an available artificial intelligence or machine learning function can be accelerated to be activated in a radio resource control recovery process.

Description

Technical Field

[0001] The present application relates to the field of communication technology, and in particular to a processing method, a communication device, and a computer-readable storage medium. Background Art

[0002] Artificial Intelligence / Machine Learning (AI / ML) plays an important role in communication network planning, deployment, operation and maintenance management. During the application process, the terminal device needs to report the available AI / ML functions to the network device, and / or the network device needs to obtain the AI / ML functions available to the terminal device so that the network device can perform reasonable function configuration, and / or maintain the consistency of the function configuration between the network device and the terminal device.

[0003] During the process of conceiving and implementing the present application, the inventors discovered that there are at least the following problems: in the existing protocol, the mechanism for reporting available AI / ML functions is imperfect, which may lead to inaccurate reporting of available AI / ML functions, thereby hindering the reasonable function management of network devices, and / or hindering the consistency of function configuration between network devices and terminal devices.

[0004] The preceding description is intended to provide general background information and does not necessarily constitute prior art.

[0005] Technical Solutions

[0006] The main purpose of this application is to provide a processing method, a communication device and a computer-readable storage medium, which aims to improve the mechanism for reporting available AI / ML functions, which can improve the accuracy of reporting available AI / ML functions, thereby helping network devices to perform reasonable function management, and / or, thereby helping to maintain consistency in the function configuration of terminal devices and network devices.

[0007] The present application provides a processing method which can be applied to a terminal device (such as a mobile phone), comprising the steps of:

[0008] S1: Available artificial intelligence or machine learning capabilities based on the first content report.

[0009] Optionally, the terminal device is in a radio resource control inactive state.

[0010] Optionally, available artificial intelligence or machine learning functionality is carried in the radio resource control resumption request signaling.

[0011] Optionally, available artificial intelligence or machine learning functionality is carried in the radio resource control recovery completion signaling.

[0012] Optionally, the method further comprises at least one of the following:

[0013] The first content includes a stored configuration of artificial intelligence or machine learning functions;

[0014] The first content includes the retained artificial intelligence or machine learning function configuration;

[0015] The first content includes the restored artificial intelligence or machine learning function configuration;

[0016] The first content includes updated artificial intelligence or machine learning function configuration.

[0017] Optionally, the method further comprises at least one of the following:

[0018] The retained AI or ML functional configuration is determined by the AI ​​or ML indication;

[0019] The configuration of the restored artificial intelligence or machine learning function is determined by the artificial intelligence or machine learning indication;

[0020] The updated artificial intelligence or machine learning function configuration is configured via radio resource control recovery signaling.

[0021] Optionally, the method further comprises at least one of the following:

[0022] an AI or ML instruction, including at least one of an AI or ML retention instruction, an AI or ML release instruction, and an AI or ML recovery instruction;

[0023] The artificial intelligence or machine learning indication is carried in at least one of the radio resource control reconfiguration signaling, the radio resource control release signaling, and the radio resource control recovery signaling.

[0024] The present application also provides a processing method, which can be applied to a network device (such as a base station), comprising the steps of:

[0025] S2: Receive available artificial intelligence or machine learning functions, where the available artificial intelligence or machine learning functions are reported by the terminal device based on the first content.

[0026] Optionally, the terminal device is in a radio resource control inactive state.

[0027] Optionally, available artificial intelligence or machine learning functionality is carried in the radio resource control resumption request signaling.

[0028] Optionally, available artificial intelligence or machine learning functionality is carried in the radio resource control recovery completion signaling.

[0029] Optionally, the method further comprises at least one of the following:

[0030] The first content includes a stored configuration of artificial intelligence or machine learning functions;

[0031] The first content includes the retained artificial intelligence or machine learning function configuration;

[0032] The first content includes the restored artificial intelligence or machine learning function configuration;

[0033] The first content includes updated artificial intelligence or machine learning function configuration.

[0034] Optionally, the method further comprises at least one of the following:

[0035] The retained AI or ML functional configuration is determined by the AI ​​or ML indication;

[0036] The configuration of the restored artificial intelligence or machine learning function is determined by the artificial intelligence or machine learning indication;

[0037] The updated artificial intelligence or machine learning function configuration is configured via radio resource control recovery signaling.

[0038] Optionally, the method further comprises at least one of the following:

[0039] an AI or ML instruction, including at least one of an AI or ML retention instruction, an AI or ML release instruction, and an AI or ML recovery instruction;

[0040] The artificial intelligence or machine learning indication is carried in at least one of the radio resource control reconfiguration signaling, the radio resource control release signaling, and the radio resource control recovery signaling.

[0041] The present application also provides a communication device, comprising: a memory, a processor, and a processing program stored in the memory and executable on the processor, wherein the processing program implements the steps of any of the processing methods described above when executed by the processor.

[0042] The communication device in this application can be a terminal device (such as a mobile phone) or a network device (such as a base station). The specific reference needs to be clarified based on the context.

[0043] The present application also provides a storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of any of the processing methods described above are implemented.

[0044] The technical solution of the present application improves the mechanism for reporting available artificial intelligence or machine learning functions based on the first content, which can improve the accuracy of reporting available artificial intelligence or machine learning functions, thereby helping network devices to perform reasonable function management, and / or, thereby helping to maintain consistency in the functional configuration of terminal devices and network devices. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] The drawings herein are incorporated into the specification and constitute a part of the specification, illustrate embodiments consistent with the present application, and are used together with the specification to explain the principles of the present application. In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the description of the embodiments are briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor.

[0046] Figure 1 A schematic diagram of the hardware structure of a mobile terminal for implementing various embodiments of the present application;

[0047] Figure 2 A communication network system architecture diagram provided for an embodiment of the present application;

[0048] Figure 3 A schematic diagram of the hardware structure of a controller 140 provided in this application;

[0049] Figure 4 A schematic diagram of the hardware structure of a network node 150 provided in this application;

[0050] Figure 5 is a schematic flow chart of a processing method according to the first embodiment;

[0051] Figure 6 is a schematic diagram of an interaction sequence according to the second embodiment;

[0052] Figure 7 is a schematic flow chart of a processing method according to a third embodiment;

[0053] Figure 8 is a flow chart of a processing method according to a seventh embodiment;

[0054] Fig. 9 A schematic diagram of the structure of the processing device provided in the embodiment of the present application Figure 1 ;

[0055] Fig.10 A schematic diagram of the structure of the processing device provided in the embodiment of the present application Figure 2 ;

[0056] Fig.11A schematic diagram of the structure of a communication device provided in an embodiment of the present application.

[0057] The realization of the purpose, functional features and advantages of this application will be further described in conjunction with the embodiments and with reference to the accompanying drawings. The above-mentioned drawings have shown clear embodiments of this application, which will be described in more detail later. These drawings and textual descriptions are not intended to limit the scope of the concept of this application in any way, but to illustrate the concept of this application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0058] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0059] It should be noted that, in this article, the terms "comprises", "includes" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or device including the element, and / or, components, features, and elements with the same name in different embodiments of the present application may have the same meaning or different meanings, and their specific meanings need to be determined by their explanation in the specific embodiment or further combined with the context of the specific embodiment.

[0060] It should be understood that, although the terms first, second, third, etc. may be used to describe various information in this article, these information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of this article, 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 word "if" as used herein can be interpreted as "at the time of" or "when" or "in response to determination". Furthermore, as used in this article, the singular forms "one", "one" and "the" are intended to also include plural forms, unless there is an opposite indication in the context. It should be further understood that the terms "comprising" and "including" indicate that there are the described features, steps, operations, elements, components, projects, kinds, and / or groups, but do not exclude the existence, occurrence or addition of one or more other features, steps, operations, elements, components, projects, kinds, and / or groups. The terms "or", "and / or", "including at least one of the following" etc. used in this application can be interpreted as inclusive, or mean any one or any combination. For example, “comprising at least one of the following: A, B, C” means “any of the following: A; B; C; A and B; A and C; B and C; A and B and C”, and for another example, “A, B or C” or “A, B and / or C” means “any of the following: A; B; C; A and B; A and C; B and C; A and B and C”. An exception to this definition will only occur when a combination of elements, functions, steps or operations are inherently mutually exclusive in some manner.

[0061] It should be understood that, although the various steps in the flowchart in the embodiment of the present application are displayed in sequence according to the indication of the arrows, these steps are not necessarily performed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and it can be performed in other orders. Moreover, at least a portion of the steps in the figure may include a plurality of sub-steps or a plurality of stages, and these sub-steps or stages are not necessarily performed at the same time, but can be performed at different times, and their execution order is not necessarily performed in sequence, but can be performed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.

[0062] As used herein, the words "if" and "if" may be interpreted as "at the time of" or "when" or "in response to determining" or "in response to detecting", depending on the context. Similarly, the phrases "if it is determined" or "if (stated condition or event) is detected" may be interpreted as "when it is determined" or "in response to determining" or "when detecting (stated condition or event)" or "in response to detecting (stated condition or event)", depending on the context.

[0063] It should be noted that in this article, step codes such as S1 and S2 are used for the purpose of expressing the corresponding content more clearly and concisely, and do not constitute a substantial limitation on the order. When implementing the step, those skilled in the art may execute S2 first and then S1, etc., but these should all be within the scope of protection of this application.

[0064] It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0065] In the subsequent description, the suffixes such as "module", "component" or "unit" used to represent elements are only used to facilitate the description of the present application, and have no specific meanings. Therefore, "module", "component" or "unit" can be used in a mixed manner.

[0066] The communication device in this application can be a terminal device (such as a mobile phone) or a network device (such as a base station). The specific reference needs to be clarified based on the context.

[0067] The terminal device may be implemented in various forms. For example, the terminal device described in this application may include intelligent terminal devices such as mobile phones, tablet computers, laptop computers, PDAs, portable media players (PMPs), navigation devices, wearable devices, smart bracelets, pedometers, etc., as well as fixed terminal devices such as digital TVs and desktop computers.

[0068] The subsequent description will be made by taking a mobile terminal as an example, and those skilled in the art will understand that, in addition to components specifically used for mobile purposes, the construction according to the embodiments of the present application can also be applied to fixed-type terminal devices.

[0069] See also Figure 1 , which is a schematic diagram of the hardware structure of a mobile terminal for implementing various embodiments of the present application, the mobile terminal 100 may include: RF (Radio Frequency, radio frequency) unit 101, WiFi module 102, audio output unit 103, A / V (audio / video) input unit 104, sensor 105, display unit 106, user input unit 107, interface unit 108, memory 109, processor 110, and power supply 111 and other components. Those skilled in the art can understand that Figure 1 The structure of the mobile terminal shown in the figure does not constitute a limitation on the mobile terminal. The mobile terminal may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently.

[0070] Combine the following Figure 1 The following is a detailed introduction to the various components of the mobile terminal:

[0071] The radio frequency unit 101 can be used for receiving and sending signals during information transmission or communication. Specifically, after receiving the downlink information of the base station, it is sent to the processor 110 for processing; in addition, the uplink data is sent to the base station. Generally, the radio frequency unit 101 includes but is not limited to an antenna, at least one amplifier, a transceiver, a coupler, a low noise amplifier, a duplexer, etc. And / or, the radio frequency unit 101 can also communicate with the network and other devices through wireless communication. The above-mentioned wireless communications can use any communication standard or protocol, including but not limited to GSM (Global System of Mobile communication), GPRS (General Packet Radio Service), CDMA2000 (Code Division Multiple Access 2000), WCDMA (Wideband Code Division Multiple Access), TD-SCDMA (Time Division-Synchronous Code Division Multiple Access), FDD-LTE (Frequency Division Duplexing-Long Term Evolution), TDD-LTE (Time Division Duplexing-Long Term Evolution), 5G and 6G, etc.

[0072] WiFi is a short-range wireless transmission technology. Mobile terminals can help users send and receive emails, browse web pages, and access streaming media through WiFi module 102. It provides users with wireless broadband Internet access. Figure 1 The WiFi module 102 is shown, but it is understandable that it is not an essential component of the mobile terminal and can be omitted as needed without changing the essence of the invention.

[0073] The audio output unit 103 can convert the audio data received by the RF unit 101 or the WiFi module 102 or stored in the memory 109 into an audio signal and output it as sound when the mobile terminal 100 is in a call signal reception mode, a talk mode, a recording mode, a voice recognition mode, a broadcast reception mode, etc. Moreover, the audio output unit 103 can also provide audio output related to a specific function performed by the mobile terminal 100 (for example, a call signal reception sound, a message reception sound, etc.). The audio output unit 103 may include a speaker, a buzzer, etc.

[0074] The A / V input unit 104 is used to receive audio or video signals. The A / V input unit 104 may include a graphics processor (GPU) 1041 and a microphone 1042, and the graphics processor 1041 processes the image data of a static picture or video obtained by an image capture device (such as a camera) in a video capture mode or an image capture mode. The processed image frame can be displayed on the display unit 106. The image frame processed by the graphics processor 1041 can be stored in the memory 109 (or other storage medium) or sent via the radio frequency unit 101 or the WiFi module 102. The microphone 1042 can receive sound (audio data) via the microphone 1042 in a telephone call mode, a recording mode, a voice recognition mode, and other operating modes, and can process such sound into audio data. The processed audio (voice) data can be converted into a format output that can be sent to a mobile communication base station via the radio frequency unit 101 in the case of a telephone call mode. The microphone 1042 can implement various types of noise elimination (or suppression) algorithms to eliminate (or suppress) noise or interference generated in the process of receiving and sending audio signals.

[0075] The mobile terminal 100 also includes at least one sensor 105, such as a light sensor, a motion sensor, and other sensors. Optionally, the light sensor includes an ambient light sensor and a proximity sensor. Optionally, the ambient light sensor can adjust the brightness of the display panel 1061 according to the brightness of the ambient light, and the proximity sensor can turn off the display panel 1061 and / or the backlight when the mobile terminal 100 is moved to the ear. As a type of motion sensor, the accelerometer sensor can detect the magnitude of acceleration in all directions (generally three axes), and can detect the magnitude and direction of gravity when stationary. It can be used for applications that identify the posture of the mobile phone (such as horizontal and vertical screen switching, related games, magnetometer posture calibration), vibration recognition related functions (such as pedometer, tapping), etc.; as for other sensors that can be configured on the mobile phone, such as fingerprint sensors, pressure sensors, iris sensors, molecular sensors, gyroscopes, barometers, hygrometers, thermometers, infrared sensors, etc., they will not be repeated here.

[0076] The display unit 106 is used to display information input by the user or information provided to the user. The display unit 106 may include a display panel 1061, which may be configured in the form of a liquid crystal display (LCD), an organic light-emitting diode (OLED), or the like.

[0077] The user input unit 107 can be used to receive input digital or character information, and to generate key signal input related to the user settings and function control of the mobile terminal. Optionally, the user input unit 107 may include a touch panel 1071 and other input devices 1072. The touch panel 1071, also known as a touch screen, can collect the user's touch operation on or near it (such as the user's operation on the touch panel 1071 or near the touch panel 1071 using any suitable object or accessory such as a finger, stylus, etc.), and drive the corresponding connection device according to a pre-set program. The touch panel 1071 may include two parts: a touch detection device and a touch controller. Optionally, the touch detection device detects the user's touch orientation, detects the signal brought by the touch operation, and transmits the signal to the touch controller; the touch controller receives the touch information from the touch detection device, converts it into the touch point coordinates, and then sends it to the processor 110, and can receive and execute the command sent by the processor 110. And / or, the touch panel 1071 can be implemented in various types such as resistive, capacitive, infrared, and surface acoustic wave. In addition to the touch panel 1071, the user input unit 107 may further include other input devices 1072. Optionally, the other input devices 1072 may include, but are not limited to, one or more of a physical keyboard, a function key (such as a volume control key, a switch key, etc.), a trackball, a mouse, a joystick, etc., which are not specifically limited here.

[0078] Optionally, the touch panel 1071 may cover the display panel 1061. When the touch panel 1071 detects a touch operation on or near it, it transmits the information to the processor 110 to determine the type of touch event. Then, the processor 110 provides corresponding visual output on the display panel 1061 according to the type of touch event. Figure 1 In the figure, the touch panel 1071 and the display panel 1061 are used as two independent components to implement the input and output functions of the mobile terminal. However, in some embodiments, the touch panel 1071 and the display panel 1061 can be integrated to implement the input and output functions of the mobile terminal, which is not limited here.

[0079] The interface unit 108 serves as an interface through which at least one external device can be connected to the mobile terminal 100. For example, the external device may include a wired or wireless headset port, an external power supply (or battery charger) port, a wired or wireless data port, a memory card port, a port for connecting a device with an identification module, an audio input / output (I / O) port, a video I / O port, a headphone port, etc. The interface unit 108 may be used to receive input (e.g., data information, power, etc.) from an external device and transmit the received input to one or more elements within the mobile terminal 100 or may be used to transmit data between the mobile terminal 100 and an external device.

[0080] The memory 109 can be used to store software programs and various data. The memory 109 can mainly include a program storage area and a data storage area. Optionally, the program storage area can store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area can store data created according to the use of the mobile phone (such as audio data, a phone book, etc.), etc. And / or, the memory 109 can include a high-speed random access memory, and can also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0081] The processor 110 is the control center of the mobile terminal. It uses various interfaces and lines to connect various parts of the entire mobile terminal. It executes various functions of the mobile terminal and processes data by running or executing software programs and / or modules stored in the memory 109, and calling data stored in the memory 109, so as to monitor the mobile terminal as a whole. The processor 110 may include one or more processing units; preferably, the processor 110 may integrate an application processor and a modem processor. Optionally, the application processor mainly processes the operating system, user interface, and application programs, and the modem processor mainly processes wireless communications. It is understandable that the above-mentioned modem processor may not be integrated into the processor 110.

[0082] The mobile terminal 100 may also include a power supply 111 (such as a battery) for supplying power to various components. Preferably, the power supply 111 may be logically connected to the processor 110 via a power management system, thereby implementing functions such as charging, discharging, and power consumption management through the power management system.

[0083] although Figure 1 Not shown, the mobile terminal 100 may further include a Bluetooth module, etc., which will not be described in detail here.

[0084] In order to facilitate understanding of the embodiments of the present application, the communication network system on which the mobile terminal of the present application is based is described below.

[0085] See also Figure 2 , Figure 2 A communication network system architecture diagram is provided for an embodiment of the present application. The communication network system is a NR (New Radio) system of universal mobile communication technology. The NR system includes a UE (User Equipment) 201, an E-UTRAN (Evolved UMTS Terrestrial Radio Access Network) 202, an EPC (Evolved Packet Core) 203 and an operator's IP service 204, which are connected in sequence.

[0086] Optionally, UE201 may be the above-mentioned terminal device 100, which will not be described in detail here.

[0087] E-UTRAN 202 includes eNodeB 2021 and other eNodeBs 2022 , etc. Optionally, eNodeB 2021 may be connected to other eNodeBs 2022 via a backhaul (eg, an X2 interface), and eNodeB 2021 is connected to EPC 203 , and eNodeB 2021 may provide UE 201 with access to EPC 203 .

[0088] EPC203 may include MME (Mobility Management Entity) 2031, HSS (Home Subsber Server) 2032, other MMEs 2033, SGW (Serving Gate Way) 2034, PGW (PDN Gate Way) 2035 and PCRF (Policy and Charging Rules Function) 2036, etc. Optionally, MME2031 is a control node that processes signaling between UE201 and EPC203, and provides bearer and connection management. HSS2032 is used to provide some registers to manage functions such as home location register (not shown in the figure), and save some user-specific information such as service features and data rates. All user data can be sent through SGW2034, PGW2035 can provide IP address allocation and other functions for UE 201, PCRF2036 is the policy and charging control policy decision point for service data flow and IP bearer resources, which selects and provides available policy and charging control decisions for the policy and charging execution function unit (not shown in the figure).

[0089] The IP service 204 may include the Internet, an intranet, an IMS (IP Multimedia Subsystem) or other IP services.

[0090] Although the above introduction takes the LTE system as an example, those skilled in the art should know that the present application is not only applicable to the LTE system, but also to other wireless communication systems, such as GSM, CDMA2000, WCDMA, TD-SCDMA, 5G and future new network systems (such as 6G), etc., without limitation here.

[0091] Figure 3 The hardware structure diagram of a controller 140 provided in the present application is shown in FIG. The controller 140 includes a memory 1401 and a processor 1402. The memory 1401 is used to store program instructions, and the processor 1402 is used to call the program instructions in the memory 1401 to execute the steps executed by the controller in the first embodiment of the above method. The implementation principle and beneficial effects are similar and will not be described in detail here.

[0092] Optionally, the controller further includes a communication interface 1403, which can be connected to the processor 1402 via a bus 1404. The processor 1402 can control the communication interface 1403 to implement the receiving and sending functions of the controller 140.

[0093] Figure 4 The hardware structure diagram of a network node 150 provided in the present application is shown in FIG. The network node 150 includes: a memory 1501 and a processor 1502, the memory 1501 is used to store program instructions, and the processor 1502 is used to call the program instructions in the memory 1501 to execute the steps performed by the first node in the first embodiment of the above method, and its implementation principle and beneficial effects are similar, which will not be repeated here.

[0094] Optionally, the controller further includes a communication interface 1503, which can be connected to the processor 1502 via a bus 1504. The processor 1502 can control the communication interface 1503 to implement the receiving and sending functions of the network node 150.

[0095] The above-mentioned integrated module implemented in the form of a software function module can be stored in a computer-readable storage medium. The above-mentioned software function module is stored in a storage medium, including a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) or a processor (English: processor) to perform some steps of the methods of various embodiments of the present application.

[0096] 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 instructions. When loading and executing computer program instructions on a computer, the process or function according to 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 devices. Computer instructions can be stored in a storage medium, or transmitted from one storage medium to another storage medium. For example, computer instructions can be transmitted from a website site, computer, server or data center to another website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode. The storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more available media integration. Available media can be magnetic media, (e.g., floppy disk, hard disk, tape), optical media (e.g., DVD), or semiconductor media (e.g., solid state hard disk solid state disk, SSD), etc.

[0097] Based on the above-mentioned mobile terminal hardware structure and communication network system, various embodiments of the present application are proposed.

[0098] Technical terms involved in the embodiments of this application:

[0099] AI / ML: Artificial Intelligence / Machine Learning, artificial intelligence or machine learning;

[0100] BM: Beam Management, beam management;

[0101] LCM: Life Cycle Management, life cycle management;

[0102] RRC: Radio Resource Control, radio resource control;

[0103] UE:User Equipment, terminal equipment;

[0104] NW:NetWork, network equipment;

[0105] CSI: Channel State Information, channel state information;

[0106] DCI: Downlink Control Information, downlink control information;

[0107] MAC CE: Media Access Control Control Element, media access control control element;

[0108] UAI: UE Assistance Information, terminal equipment assistance information;

[0109] MCG: Master Cell Group, main cell group;

[0110] RLF: Radio Link Failure, wireless link failure;

[0111] RACH: Random Access CHannel, random access channel;

[0112] PCell, Primary Cell, primary cell;

[0113] PScell, Primary Secondary cell, primary secondary cell.

[0114] First embodiment

[0115] Reference Figure 5 , Figure 5 The flowchart of the processing method according to the first embodiment is shown. The processing method of the embodiment of the present application can be applied to a terminal device (such as a mobile phone), and includes the following steps:

[0116] S1: Available artificial intelligence or machine learning capabilities based on the first content report.

[0117] Optionally, the terminal device is in a radio resource control inactive state (RRC_INACTIVE).

[0118] Optionally, the first content includes a stored artificial intelligence or machine learning functional configuration.

[0119] Optionally, the first content includes a retained artificial intelligence or machine learning functional configuration.

[0120] Optionally, the retained artificial intelligence or machine learning functional configuration is determined by an artificial intelligence or machine learning indication.

[0121] Optionally, the first content includes a restored artificial intelligence or machine learning functional configuration.

[0122] Optionally, the restored artificial intelligence or machine learning functional configuration is determined by an artificial intelligence or machine learning indication.

[0123] Optionally, the first content includes an updated artificial intelligence or machine learning functional configuration.

[0124] Optionally, the updated artificial intelligence or machine learning functionality is configured via radio resource control recovery signaling configuration.

[0125] Optionally, the artificial intelligence or machine learning indication includes at least one of the following:

[0126] Artificial intelligence or machine learning retention instructions;

[0127] Artificial intelligence or machine learning release instructions;

[0128] Artificial intelligence or machine learning recovery indication.

[0129] Optionally, the artificial intelligence or machine learning indication is carried in at least one of radio resource control reconfiguration signaling, radio resource control release signaling, and radio resource control recovery signaling.

[0130] Optionally, available artificial intelligence or machine learning functionality is carried in the radio resource control resumption request signaling.

[0131] Optionally, available artificial intelligence or machine learning functionality is carried in the radio resource control recovery completion signaling.

[0132] Optionally, the network device performs function configuration and / or function activation based on available artificial intelligence or machine learning functions sent by the terminal device.

[0133] Through the technical solution of this embodiment, specifically by reporting the available artificial intelligence or machine learning function based on the first content, the mechanism for reporting the available artificial intelligence or machine learning function is improved, which can improve the accuracy of reporting the available artificial intelligence or machine learning function, thereby helping the network device to perform reasonable function management, and / or, thereby helping to maintain the consistency of the function configuration of the terminal device and the network device, and / or, thereby helping to accelerate the activation of the available artificial intelligence or machine learning function during the wireless resource control recovery process.

[0134] Second embodiment

[0135] Reference Figure 6 , Figure 6 This is an interaction timing diagram according to the second embodiment. This embodiment discloses a method for a terminal device to interact with a network device for artificial intelligence or machine learning function configuration.

[0136] Optionally, the network device sends a terminal device capability inquiry (UE Capability Enquiry) signaling to the terminal device.

[0137] Optionally, the terminal device capability inquiry signaling is used to obtain capabilities and / or features (Features) supported by the terminal device.

[0138] Optionally, the terminal device sends terminal device capability information (UE Capability Information) signaling to the network device.

[0139] Optionally, the terminal device capability information carries at least one of the following: a frequency band supported by the terminal device, a frequency band combination supported by the terminal device, artificial intelligence or machine learning (AI / ML) capabilities, and a feature supported by the terminal device.

[0140] Optionally, the artificial intelligence or machine learning capabilities include supported functionality and / or supported models.

[0141] Optionally, the network device sends a radio resource control reconfiguration (RRCReconfiguration) signaling to the terminal device.

[0142] Optionally, the radio resource control reconfiguration signaling carries artificial intelligence or machine learning function configuration or other configuration.

[0143] Optionally, the artificial intelligence or machine learning function configuration or other configuration includes at least one of the following: inference configuration, applicable functionality report configuration, training configuration, network device side additional condition, terminal device side additional condition, and associated ID.

[0144] Optionally, artificial intelligence or machine learning function configuration is included in the other configuration information field.

[0145] Optionally, the artificial intelligence or machine learning functional configuration is represented by newly introduced information fields, including: artificial intelligence or machine learning preference configuration (AI / MLPreferenceConfig) and / or available functional preference configuration (ApplicableFunctionalityPreferenceConfig).

[0146] Optionally, the association identifier is configured in the channel state information reporting configuration.

[0147] Optionally, the association identifier is used to associate additional conditions on the network device side.

[0148] Optionally, the available capabilities reporting configuration is not used for inference.

[0149] Optionally, the reasoning configuration is used for artificial intelligence or machine learning reasoning, including: set A (Set A) and / or set B (Set B).

[0150] Optionally, set B is used for measurement and / or inference input.

[0151] Optionally, set A is used for inference output and / or inference result.

[0152] Optionally, the training configuration is used for artificial intelligence or machine learning model training.

[0153] Optionally, the inference configuration, training configuration, additional conditions on the network device side, and additional conditions on the terminal device side include: available function reporting configuration and / or channel state information (CSI, Channel State Information) reporting configuration.

[0154] Optionally, the channel state information reporting configuration includes: at least one of periodic, aperiodic, and semi-persistent.

[0155] Optionally, the radio resource control reconfiguration signaling also carries an artificial intelligence or machine learning indication.

[0156] Optionally, artificial intelligence or machine learning indications are included in the artificial intelligence or machine learning functional configuration.

[0157] Optionally, the artificial intelligence or machine learning indication is used to determine whether to release, retain or restore the artificial intelligence or machine learning function configuration during the wireless resource control recovery process.

[0158] Optionally, the terminal device stores the received artificial intelligence or machine learning function configuration.

[0159] Optionally, the terminal device sends a radio resource control reconfiguration completion (RRCReconfigurationComplete) signaling to the network device.

[0160] Optionally, the radio resource control reconfiguration completion signaling carries available functions.

[0161] Optionally, the available functionality is artificial intelligence or machine learning configuration supported and / or available on the terminal device.

[0162] Optionally, available functions provide artificial intelligence or machine learning configuration for network devices, such as channel state information reporting configuration.

[0163] Optionally, the radio resource control reconfiguration completion signaling is used to report available functions.

[0164] Optionally, when the inference configuration and / or the training configuration includes periodic channel state information reporting, the corresponding periodic channel state information is activated, and / or the corresponding periodic channel state information is deemed to be activated.

[0165] Optionally, when the inference configuration and / or training configuration includes periodic channel state information reporting, and the inference configuration and / or training configuration is an additional condition on the network device side, the corresponding periodic channel state information is activated, and / or the corresponding periodic channel state information is deemed to be activated.

[0166] Optionally, when the inference configuration and / or training configuration includes periodic channel state information reporting, and the inference configuration and / or training configuration is an additional condition on the network device side, the corresponding periodic channel state information is activated, and / or the corresponding periodic channel state information is deemed to be activated.

[0167] Optionally, the network device sends function activation or deactivation control information to the terminal device.

[0168] Optionally, the network device activates channel state information reporting through downlink control information (DCI, Downlink Control Information) and / or a media access control control element (MAC CE, Media Access Control Control Element).

[0169] Optionally, the network device deactivates channel state information reporting through downlink control information and / or control elements of media access control.

[0170] Optionally, the channel state information reporting includes aperiodic and / or semi-static reporting.

[0171] Optionally, channel state information reporting provides artificial intelligence or machine learning configuration for network devices.

[0172] Optionally, the channel state information is used to activate channel state information reporting of the inference configuration and / or training configuration.

[0173] Optionally, the channel state information is used to deactivate channel state information reporting of the inference configuration and / or training configuration.

[0174] Optionally, the terminal device sends terminal device assistance information (UAI, UE Assistance Information) signaling to the network device.

[0175] Optionally, the terminal device auxiliary information carries available functions of the terminal device and / or available functions of status update.

[0176] Optionally, the radio resource control reconfiguration signaling also carries an updated artificial intelligence or machine learning indication.

[0177] Optionally, artificial intelligence or machine learning indications are included in the artificial intelligence or machine learning functional configuration.

[0178] Optionally, the artificial intelligence or machine learning indication is used to determine whether to release, retain or restore the artificial intelligence or machine learning function configuration during the wireless resource control recovery process.

[0179] Optionally, the radio resource control reconfiguration signaling also carries an updated artificial intelligence or machine learning indication.

[0180] Optionally, artificial intelligence or machine learning indications are included in the artificial intelligence or machine learning functional configuration.

[0181] Optionally, the artificial intelligence or machine learning indication is used to determine whether to release or retain or restore the artificial intelligence or machine learning function configuration during the wireless resource control recovery process.

[0182] Optionally, the status update includes: applicable becomes unavailable (non applicable), and / or unavailable becomes available.

[0183] Optionally, the available function provides a channel state information reporting configuration for the network device. Optionally, the channel state information reporting configuration includes: at least one of periodic, aperiodic, and semi-persistent.

[0184] Optionally, the network device sends function activation or deactivation control information to the terminal device.

[0185] Optionally, the network device sends radio resource control reconfiguration signaling to the terminal device.

[0186] Optionally, radio resource control reconfiguration signaling is used to update artificial intelligence or machine learning function configuration.

[0187] Optionally, the terminal device sends a radio resource control reconfiguration completion signaling to the terminal device.

[0188] Optionally, radio resource control reconfiguration completion signaling is used to respond to updating the artificial intelligence or machine learning function configuration.

[0189] Through the technical solution of this embodiment, specifically by carrying artificial intelligence or machine learning indications in wireless resource control reconfiguration signaling, it is used to determine whether to retain, release or restore the artificial intelligence or machine learning function configuration during the wireless resource control recovery process, thereby improving the reporting mechanism of the artificial intelligence or machine learning functions available to the terminal device, thereby supporting the improvement of the memory management efficiency of the terminal device, and / or supporting the improvement of the consistency of the functional configuration of the terminal device and the network device, and / or helping to accelerate the activation of available artificial intelligence or machine learning functions during the wireless resource control recovery process.

[0190] Third embodiment

[0191] Reference Figure 7 , Figure 7 This is an interaction timing diagram shown according to the third embodiment. Based on any of the foregoing embodiments of the present application, this embodiment further discloses a method for a terminal device to report available artificial intelligence or machine learning functions.

[0192] Optionally, the terminal device initiates radio resource control recovery, for details, please refer to protocol TS 38.331v18, 5.3.13.2.

[0193] Optionally, before the terminal device initiates radio resource control recovery, the network device sends a radio resource control release signaling to the terminal device.

[0194] Optionally, the terminal device enters a radio resource control inactive state according to radio resource control release signaling.

[0195] Optionally, the radio resource control release signaling carries an artificial intelligence or machine learning indication.

[0196] Optionally, the terminal device releases or retains the artificial intelligence or machine learning function configuration according to the artificial intelligence or machine learning indication.

[0197] Optionally, the radio resource control release signaling also carries artificial intelligence or machine learning function configuration.

[0198] Optionally, the terminal device stores the artificial intelligence or machine learning function configuration carried by the wireless resource control release signaling.

[0199] Optionally, the terminal device sends a radio resource control resume request (RRC Resume Request) signaling to the network device.

[0200] Optionally, the terminal device sends a wireless resource control recovery request signaling after releasing the artificial intelligence or machine learning function configuration.

[0201] Optionally, the released artificial intelligence or machine learning function configuration is an artificial intelligence or machine learning function configuration carried by the wireless resource control release signaling.

[0202] Optionally, the released artificial intelligence or machine learning function configuration is an artificial intelligence or machine learning function configuration received by the terminal device in the radio resource control connected state (RRC_CONNECTED).

[0203] Optionally, the terminal device sends a radio resource control recovery request signaling after starting radio resource control recovery, for details, refer to protocol TS 38.331v18, 5.3.13.3.

[0204] Optionally, the terminal device is set with available artificial intelligence or machine learning functions, such as applicableAIMLfunctionality, AIMLapplicablefunctionality, UEapplicableAIML.

[0205] Optionally, the terminal device sets available artificial intelligence or machine learning based on stored artificial intelligence or machine learning function configurations and / or applicable functionality of the terminal device.

[0206] Optionally, the stored artificial intelligence or machine learning functional configuration is a reserved or unreleased artificial intelligence or machine learning functional configuration.

[0207] Optionally, the radio resource control recovery request signaling carries available artificial intelligence or machine learning functionality.

[0208] Optionally, the network device sends a radio resource control recovery signaling to the network device, for details, please refer to protocol TS38.331v18, 5.3.13.4.

[0209] Optionally, the terminal device sends a radio resource control recovery completion signaling to the network device. For details, please refer to protocol TS 38.331v18, 5.3.13.4.

[0210] Through the technical solution of this embodiment, specifically by reporting the available artificial intelligence or machine learning function based on the stored artificial intelligence or machine learning function configuration, the mechanism for reporting the available artificial intelligence or machine learning function is improved, which can improve the accuracy of reporting the available artificial intelligence or machine learning function, thereby helping the network device to perform reasonable function management, and / or, thereby helping to maintain the consistency of the function configuration of the terminal device and the network device, and / or, thereby helping to accelerate the activation of the available artificial intelligence or machine learning function during the wireless resource control recovery process.

[0211] Fourth embodiment

[0212] Based on any of the foregoing embodiments of the present application, this embodiment further discloses a method for a terminal device to report available artificial intelligence or machine learning functions.

[0213] Optionally, the terminal device initiates radio resource control recovery, for details, please refer to protocol TS 38.331v18, 5.3.13.2.

[0214] Optionally, the terminal device sends a radio resource control recovery request signaling to the network device, for details, please refer to protocol TS 38.331v18, 5.3.13.3.

[0215] Optionally, the network device sends a radio resource control resume (RRC Resume) signaling to the terminal device.

[0216] Optionally, the terminal device receives radio resource control recovery signaling sent by the network device.

[0217] Optionally, the radio resource control recovery signaling carries an artificial intelligence or machine learning indication.

[0218] Optionally, the terminal device releases, retains or restores the artificial intelligence or machine learning function configuration according to the artificial intelligence or machine learning instructions.

[0219] Optionally, when the wireless resource control recovery signaling carries an artificial intelligence or machine learning indication, the artificial intelligence or machine learning function configuration is released; and / or, when the wireless resource control recovery signaling does not carry an artificial intelligence or machine learning indication, the artificial intelligence or machine learning function configuration is retained or restored.

[0220] Optionally, when the wireless resource control recovery signaling carries an artificial intelligence or machine learning indication, the artificial intelligence or machine learning function configuration is retained or restored; and / or, when the wireless resource control recovery signaling does not carry an artificial intelligence or machine learning indication, the artificial intelligence or machine learning function configuration is released.

[0221] Optionally, the artificial intelligence or machine learning indication may be at least one of a release indication, a retention indication, and a recovery indication, for example: an artificial intelligence or machine learning release indication, an artificial intelligence or machine learning retention indication, an artificial intelligence or machine learning recovery indication.

[0222] Optionally, when the wireless resource control recovery signaling carries an artificial intelligence or machine learning indication, and the artificial intelligence or machine learning indication is a release indication, the artificial intelligence or machine learning function configuration is released.

[0223] Optionally, when the wireless resource control recovery signaling carries an artificial intelligence or machine learning indication, and the artificial intelligence or machine learning indication is a retention indication, the artificial intelligence or machine learning function configuration is retained.

[0224] Optionally, when the wireless resource control recovery signaling carries an artificial intelligence or machine learning indication, and the artificial intelligence or machine learning indication is a recovery indication, the artificial intelligence or machine learning function configuration is restored.

[0225] Optionally, when the wireless resource control recovery signaling does not carry an artificial intelligence or machine learning release indication, the artificial intelligence or machine learning function configuration is retained and / or restored.

[0226] Optionally, when the radio resource control recovery signaling does not carry an artificial intelligence or machine learning retention indication, the artificial intelligence or machine learning function configuration is released.

[0227] Optionally, when the wireless resource control recovery signaling does not carry an artificial intelligence or machine learning recovery indication, the artificial intelligence or machine learning function configuration is released.

[0228] Optionally, if the artificial intelligence or machine learning functionality is configured to release and / or the timer is running, the timer is stopped.

[0229] Optionally, the timer configures an associated timer for the artificial intelligence or machine learning function.

[0230] Optionally, the terminal device is set with available artificial intelligence or machine learning functions, such as applicableAIMLfunctionality, AIMLapplicablefunctionality, UEapplicableAIML.

[0231] Optionally, the terminal device sets the available artificial intelligence or machine learning function according to the retained or restored artificial intelligence or machine learning function configuration, and / or the terminal device sets the available artificial intelligence or machine learning function according to the available functions of the terminal device.

[0232] Optionally, the terminal device sends a radio resource control recovery completion signaling.

[0233] Optionally, the radio resource control recovery completion signaling carries artificial intelligence or machine learning capabilities available to the terminal device.

[0234] Through the technical solution of this embodiment, specifically by reporting the available artificial intelligence or machine learning function based on the retained or restored artificial intelligence or machine learning function configuration, the mechanism for reporting the available artificial intelligence or machine learning function is improved, which can improve the accuracy of reporting the available artificial intelligence or machine learning function, thereby helping the network device to perform reasonable function management, and / or, thereby helping to maintain the consistency of the function configuration of the terminal device and the network device, and / or, thereby helping to accelerate the activation of the available artificial intelligence or machine learning function during the wireless resource control recovery process.

[0235] Fifth embodiment

[0236] Based on any of the foregoing embodiments of the present application, this embodiment further discloses a method for a terminal device to report available artificial intelligence or machine learning functions.

[0237] Optionally, the terminal device initiates radio resource control recovery, for details, please refer to protocol TS 38.331v18, 5.3.13.2.

[0238] Optionally, the terminal device sends a radio resource control recovery request signaling to the network device, for details, please refer to protocol TS 38.331v18, 5.3.13.3.

[0239] Optionally, the network device sends radio resource control recovery signaling to the terminal device.

[0240] Optionally, the radio resource control recovery signaling carries the artificial intelligence or machine learning function configuration or carries an updated artificial intelligence or machine learning function configuration.

[0241] Optionally, the terminal device sends a radio resource control recovery completion signaling to the network device.

[0242] Optionally, the terminal device is set with available artificial intelligence or machine learning functions, such as applicableAIMLfunctionality, AIMLapplicablefunctionality, UEapplicableAIML.

[0243] Optionally, the terminal device configures available artificial intelligence or machine learning based on the configured or updated artificial intelligence or machine learning function configuration settings.

[0244] Optionally, the terminal device sets available artificial intelligence or machine learning functions according to available functions of the terminal device.

[0245] Optionally, the radio resource control recovery completion signaling carries artificial intelligence or machine learning capabilities available to the terminal device.

[0246] Through the technical solution of this embodiment, specifically by reporting the available artificial intelligence or machine learning function based on the configured or updated artificial intelligence or machine learning function configuration, the mechanism for reporting the available artificial intelligence or machine learning function is improved, which can improve the accuracy of reporting the available artificial intelligence or machine learning function, thereby helping the network device to perform reasonable function management, and / or, thereby helping to maintain the consistency of the function configuration between the terminal device and the network device, and / or, thereby helping to accelerate the activation of the available artificial intelligence or machine learning function during the wireless resource control recovery process.

[0247] Sixth embodiment

[0248] Based on any of the foregoing embodiments of the present application, this embodiment further discloses a method for a terminal device to report available artificial intelligence or machine learning functions.

[0249] Optionally, the terminal device initiates radio resource control recovery, for details, please refer to protocol TS 38.331v18, 5.3.13.2.

[0250] Optionally, the terminal device sends a radio resource control recovery request signaling to the network device, for details, please refer to protocol TS 38.331v18, 5.3.13.3.

[0251] Optionally, before the terminal device initiates radio resource control recovery, the network device sends a radio resource control release signaling to the terminal device.

[0252] Optionally, the terminal device enters a radio resource control inactive state according to radio resource control release signaling.

[0253] Optionally, the radio resource control release signaling carries an artificial intelligence or machine learning indication.

[0254] Optionally, the terminal device releases or retains the artificial intelligence or machine learning function configuration according to the artificial intelligence or machine learning indication.

[0255] Optionally, the radio resource control release signaling carries artificial intelligence or machine learning function configuration.

[0256] Optionally, the terminal device stores the artificial intelligence or machine learning function configuration carried by the wireless resource control release signaling.

[0257] Optionally, the terminal device sends a radio resource control resume request (RRC Resume Request) signaling to the network device.

[0258] Optionally, the terminal device sends a wireless resource control recovery request signaling after releasing the artificial intelligence or machine learning function configuration.

[0259] Optionally, the terminal device sends a radio resource control recovery request signaling after starting radio resource control recovery, for details, refer to protocol TS 38.331v18, 5.3.13.3.

[0260] Optionally, the terminal device is set with available artificial intelligence or machine learning functions, such as applicableAIMLfunctionality, AIMLapplicablefunctionality, UEapplicableAIML.

[0261] Optionally, the terminal device sets available artificial intelligence or machine learning based on stored artificial intelligence or machine learning function configurations and / or applicable functionality of the terminal device.

[0262] Optionally, the stored artificial intelligence or machine learning functional configuration is a reserved or unreleased artificial intelligence or machine learning functional configuration.

[0263] Optionally, the network device sends a radio resource control resume (RRC Resume) signaling to the terminal device.

[0264] Optionally, the terminal device receives radio resource control recovery signaling sent by the network device.

[0265] Optionally, the radio resource control recovery signaling carries an artificial intelligence or machine learning indication.

[0266] Optionally, the terminal device releases, retains or restores the artificial intelligence or machine learning function configuration according to the artificial intelligence or machine learning instructions.

[0267] Optionally, when the wireless resource control recovery signaling carries an artificial intelligence or machine learning indication, the artificial intelligence or machine learning function configuration is released; and / or, when the wireless resource control recovery signaling does not carry an artificial intelligence or machine learning indication, the artificial intelligence or machine learning function configuration is retained or restored.

[0268] Optionally, when the wireless resource control recovery signaling carries an artificial intelligence or machine learning indication, the artificial intelligence or machine learning function configuration is retained or restored; and / or, when the wireless resource control recovery signaling does not carry an artificial intelligence or machine learning indication, the artificial intelligence or machine learning function configuration is released.

[0269] Optionally, the artificial intelligence or machine learning indication may be at least one of a release indication, a retention indication, and a recovery indication, for example: an artificial intelligence or machine learning release indication, an artificial intelligence or machine learning retention indication, an artificial intelligence or machine learning recovery indication.

[0270] Optionally, when the wireless resource control recovery signaling carries an artificial intelligence or machine learning indication, and the artificial intelligence or machine learning indication is a release indication, the artificial intelligence or machine learning function configuration is released.

[0271] Optionally, when the wireless resource control recovery signaling carries an artificial intelligence or machine learning indication, and the artificial intelligence or machine learning indication is a retention indication, the artificial intelligence or machine learning function configuration is retained.

[0272] Optionally, when the wireless resource control recovery signaling carries an artificial intelligence or machine learning indication, and the artificial intelligence or machine learning indication is a recovery indication, the artificial intelligence or machine learning function configuration is restored.

[0273] Optionally, when the wireless resource control recovery signaling does not carry an artificial intelligence or machine learning release indication, the artificial intelligence or machine learning function configuration is retained and / or restored.

[0274] Optionally, when the radio resource control recovery signaling does not carry an artificial intelligence or machine learning retention indication, the artificial intelligence or machine learning function configuration is released.

[0275] Optionally, when the wireless resource control recovery signaling does not carry an artificial intelligence or machine learning recovery indication, the artificial intelligence or machine learning function configuration is released.

[0276] Optionally, if the artificial intelligence or machine learning functionality is configured to release and / or the timer is running, the timer is stopped.

[0277] Optionally, the timer configures an associated timer for the artificial intelligence or machine learning function.

[0278] Optionally, the terminal device is set with available artificial intelligence or machine learning functions, such as applicableAIMLfunctionality, AIMLapplicablefunctionality, UEapplicableAIML.

[0279] Optionally, the terminal device sets the available artificial intelligence or machine learning function according to the retained or restored artificial intelligence or machine learning function configuration, and / or the terminal device sets the available artificial intelligence or machine learning function according to the available functions of the terminal device.

[0280] Optionally, the network device sends radio resource control recovery signaling to the terminal device.

[0281] Optionally, the radio resource control recovery signaling carries the artificial intelligence or machine learning function configuration or carries an updated artificial intelligence or machine learning function configuration.

[0282] Optionally, the terminal device sends a radio resource control recovery completion signaling to the network device.

[0283] Optionally, the terminal device is set with available artificial intelligence or machine learning functions, such as applicableAIMLfunctionality, AIMLapplicablefunctionality, UEapplicableAIML.

[0284] Optionally, the terminal device configures available artificial intelligence or machine learning based on the configured or updated artificial intelligence or machine learning function configuration settings.

[0285] Optionally, the terminal device sets available artificial intelligence or machine learning functions according to available functions of the terminal device.

[0286] Optionally, the radio resource control recovery completion signaling carries artificial intelligence or machine learning capabilities available to the terminal device.

[0287] Through the technical solution of this embodiment, specifically by reporting the available artificial intelligence or machine learning function based on the stored, retained, restored or updated artificial intelligence or machine learning function configuration, the available artificial intelligence or machine learning function can be flexibly configured and / or reported, and the mechanism for reporting the available artificial intelligence or machine learning function is improved. The accuracy of reporting the available artificial intelligence or machine learning function can be improved, which in turn helps the network device to perform reasonable function management, and / or, helps to maintain the consistency of the function configuration of the terminal device and the network device, and / or, helps to accelerate the activation of the available artificial intelligence or machine learning function during the wireless resource control recovery process.

[0288] Seventh embodiment

[0289] Reference Figure 8 , Figure 8 FIG. 5 is a flow chart of a processing method according to a seventh embodiment. The method of this embodiment can be applied to a network device (such as a base station), and includes the following steps:

[0290] S2: Receive available artificial intelligence or machine learning functions, where the available artificial intelligence or machine learning functions are reported by the terminal device based on the first content.

[0291] Optionally, the terminal device is in a radio resource control inactive state (RRC_INACTIVE).

[0292] Optionally, the terminal device sends available artificial intelligence or machine learning functions to the network device based on the first content.

[0293] Optionally, the network device receives available artificial intelligence or machine learning functions sent by the terminal device based on the first content.

[0294] Optionally, the first content includes a stored artificial intelligence or machine learning functional configuration.

[0295] Optionally, the first content includes a retained artificial intelligence or machine learning functional configuration.

[0296] Optionally, the retained artificial intelligence or machine learning functional configuration is determined by an artificial intelligence or machine learning indication.

[0297] Optionally, the first content includes a restored artificial intelligence or machine learning functional configuration.

[0298] Optionally, the restored artificial intelligence or machine learning functional configuration is determined by an artificial intelligence or machine learning indication.

[0299] Optionally, the first content includes an updated artificial intelligence or machine learning functional configuration.

[0300] Optionally, the updated artificial intelligence or machine learning functionality is configured via radio resource control recovery signaling configuration.

[0301] Optionally, the artificial intelligence or machine learning indication includes at least one of the following:

[0302] Artificial intelligence or machine learning retention instructions;

[0303] Artificial intelligence or machine learning release instructions;

[0304] Artificial intelligence or machine learning recovery indication.

[0305] Optionally, the artificial intelligence or machine learning indication is carried in at least one of radio resource control reconfiguration signaling, radio resource control release signaling, and radio resource control recovery signaling.

[0306] Optionally, available artificial intelligence or machine learning functionality is carried in the radio resource control resumption request signaling.

[0307] Optionally, available artificial intelligence or machine learning functionality is carried in the radio resource control recovery completion signaling.

[0308] Optionally, the network device performs function configuration and / or function activation based on available artificial intelligence or machine learning functions sent by the terminal device.

[0309] Through the technical solution of this embodiment, the mechanism for reporting the available artificial intelligence or machine learning function is improved by specifically receiving the available artificial intelligence or machine learning function reported by the terminal device based on the first content through the network device, which can improve the accuracy of reporting the available artificial intelligence or machine learning function, thereby helping the network device to perform reasonable function management, and / or, thereby helping to maintain the consistency of the function configuration of the terminal device and the network device, and / or, thereby helping to accelerate the activation of the available artificial intelligence or machine learning function during the wireless resource control recovery process.

[0310] Eighth embodiment

[0311] Reference Fig. 9 , Fig. 9 A schematic diagram of the structure of the processing device provided in the embodiment of the present application Figure 1 , the device may be mounted on or is the terminal device in the above method embodiment, Fig. 9 The processing device shown can be used to perform part or all of the functions of the method embodiments described in the above embodiments, such as Fig. 9 As shown, the processing device 1100 includes:

[0312] The processing module 1101 is used to report available artificial intelligence or machine learning functions based on the first content.

[0313] Optionally, the terminal device is in a radio resource control inactive state.

[0314] Optionally, available artificial intelligence or machine learning functionality is carried in the radio resource control resumption request signaling.

[0315] Optionally, available artificial intelligence or machine learning functionality is carried in the radio resource control recovery completion signaling.

[0316] Optionally, the device further comprises at least one of the following:

[0317] The first content includes a stored configuration of artificial intelligence or machine learning functions;

[0318] The first content includes the retained artificial intelligence or machine learning function configuration;

[0319] The first content includes the restored artificial intelligence or machine learning function configuration;

[0320] The first content includes updated artificial intelligence or machine learning function configuration.

[0321] Optionally, the device further comprises at least one of the following:

[0322] The retained AI or ML functional configuration is determined by the AI ​​or ML indication;

[0323] The configuration of the restored artificial intelligence or machine learning function is determined by the artificial intelligence or machine learning indication;

[0324] The updated artificial intelligence or machine learning function configuration is configured via radio resource control recovery signaling.

[0325] Optionally, the device further comprises at least one of the following:

[0326] an AI or ML instruction, including at least one of an AI or ML retention instruction, an AI or ML release instruction, and an AI or ML recovery instruction;

[0327] The artificial intelligence or machine learning indication is carried in at least one of the radio resource control reconfiguration signaling, the radio resource control release signaling, and the radio resource control recovery signaling.

[0328] The processing device provided in the embodiment of the present application has similar implementation principles and beneficial effects to the technical solutions shown in the above-mentioned corresponding method embodiments, and will not be described in detail here.

[0329] Ninth embodiment

[0330] Reference Fig.10 , Fig.10 A schematic diagram of the structure of the processing device provided in the embodiment of the present application Figure 2 The device may be mounted on or be the network device in the above method embodiment. Fig.10 The processing device shown can be used to perform part or all of the functions of the method embodiments described in the above embodiments, such as Fig.10 As shown, the processing device 1200 includes:

[0331] The receiving module 1201 is used to receive available artificial intelligence or machine learning functions, and the available artificial intelligence or machine learning functions are reported by the terminal device based on the first content.

[0332] Optionally, the terminal device is in a radio resource control inactive state.

[0333] Optionally, available artificial intelligence or machine learning functionality is carried in the radio resource control recovery request signaling.

[0334] Optionally, available artificial intelligence or machine learning functionality is carried in the radio resource control recovery completion signaling.

[0335] Optionally, the device further comprises at least one of the following:

[0336] The first content includes a stored configuration of artificial intelligence or machine learning functions;

[0337] The first content includes the retained artificial intelligence or machine learning function configuration;

[0338] The first content includes the restored artificial intelligence or machine learning function configuration;

[0339] The first content includes updated artificial intelligence or machine learning function configuration.

[0340] Optionally, the device further comprises at least one of the following:

[0341] The retained AI or ML functional configuration is determined by the AI ​​or ML indication;

[0342] The configuration of the restored artificial intelligence or machine learning function is determined by the artificial intelligence or machine learning indication;

[0343] The updated artificial intelligence or machine learning function configuration is configured via radio resource control recovery signaling.

[0344] Optionally, the method further comprises at least one of the following:

[0345] an AI or ML instruction, including at least one of an AI or ML retention instruction, an AI or ML release instruction, and an AI or ML recovery instruction;

[0346] The artificial intelligence or machine learning indication is carried in at least one of the radio resource control reconfiguration signaling, the radio resource control release signaling, and the radio resource control recovery signaling.

[0347] The processing device provided in the embodiment of the present application has similar implementation principles and beneficial effects to the technical solutions shown in the above-mentioned corresponding method embodiments, and will not be described in detail here.

[0348] See also Fig.11 , Fig.11 This is a schematic diagram of the structure of the communication device provided in the embodiment of the present application. Fig.11 As shown, the communication device 160 described in this embodiment can be the terminal device (or a component that can be used for the terminal device) or the network device (or a component that can be used for the network device) mentioned in the above method embodiment. The communication device 160 can be used to implement the method corresponding to the terminal device or the network device described in the above method embodiment, and specifically refer to the description in the above method embodiment.

[0349] The communication device 160 may include one or more processors 161, which may also be referred to as a processing unit, and may implement certain control or processing functions. The processor 161 may be a general-purpose processor or a dedicated processor, etc. For example, it may be a baseband processor or a central processing unit. The baseband processor may be used to process the communication protocol and communication data, and the central processing unit may be used to control the communication device, execute the software program, and process the data of the software program.

[0350] Optionally, the processor 161 may also store instructions 163 or data (eg, intermediate data). Optionally, the instructions 163 may be executed by the processor 161, so that the communication device 160 executes the method corresponding to the terminal device or network device described in the above method embodiment.

[0351] Optionally, the communication device 160 may include a circuit, which can implement the functions of sending or receiving or communicating in the aforementioned method embodiments.

[0352] Optionally, the communication device 160 may include one or more memories 162, on which instructions 164 may be stored. The instructions may be executed on the processor 161, so that the communication device 160 executes the method described in the above method embodiment.

[0353] Optionally, data may also be stored in the memory 162. The processor 161 and the memory 162 may be provided separately or integrated together.

[0354] Optionally, the communication device 160 may further include a transceiver 165 and / or an antenna 166. The processor 161 may be referred to as a processing unit, and controls the communication device 160 (terminal device or core network device or wireless access network device). The transceiver 165 may be referred to as a transceiver unit, a transceiver, a transceiver circuit, or a transceiver, etc., and is used to implement the transceiver function of the communication device 160.

[0355] Optionally, if the communication device 160 is used to implement operations corresponding to the terminal device in the above embodiments, for example, the transceiver 165 and / or the processor 161 can report available artificial intelligence or machine learning functions based on the first content.

[0356] Optionally, the specific implementation process of the processor 161 and the transceiver 165 can refer to the relevant description of the above embodiments, which will not be repeated here.

[0357] Optionally, if the communication device 160 is used to implement operations corresponding to the network devices in the above-mentioned embodiments, for example: the transceiver 165 can receive available artificial intelligence or machine learning functions, and the available artificial intelligence or machine learning functions are reported by the terminal device based on the first content.

[0358] Optionally, the specific implementation process of the processor 161 and the transceiver 165 can refer to the relevant description of the above embodiments, which will not be repeated here.

[0359] The processor 161 and the transceiver 165 described in the present application can be implemented in an IC (Integrated Circuit), an analog integrated circuit, an RFIC (Radio Frequency Integrated Circuit), a mixed signal integrated circuit, an ASIC (Application Specific Integrated Circuit), a PCB (Printed Circuit Board), an electronic device, etc. The processor 161 and the transceiver 165 can also be manufactured using various integrated circuit process technologies, such as CMOS (Complementary Metal Oxide Semiconductor), NMOS (N Metal-Oxide-Semiconductor), PMOS (Positive channel Metal Oxide Semiconductor), BJT (Bipolar Junction Transistor), bipolar CMOS (BiCMOS), silicon germanium (SiGe), gallium arsenide (GaAs), etc. In the present application, the communication device can be a terminal device (such as a mobile phone) or a network device (such as a base station), which needs to be determined according to the context. In addition, the terminal device can be implemented in various forms. For example, the terminal devices described in this application may include mobile terminals such as mobile phones, tablet computers, laptops, PDAs, portable media players (PMPs), navigation devices, wearable devices, smart bracelets, pedometers, etc., as well as fixed terminal devices such as digital TVs and desktop computers.

[0360] Although in the above embodiments, the communication device is described by taking a terminal device or a network device as an example, the scope of the communication device described in the present application is not limited to the above terminal device or network device, and the structure of the communication device may not be limited to the above terminal device or network device. Fig.11 The communication device may be a stand-alone device or may be part of a larger device.

[0361] An embodiment of the present application also provides a communication system, including: a terminal device as in any of the above embodiments; and a network device as in any of the above embodiments.

[0362] An embodiment of the present application also provides a communication device, including a memory and a processor, wherein a processing program is stored in the memory, and when the processing program is executed by the processor, the steps of the processing method in any of the above embodiments are implemented.

[0363] The communication device in this application can be a terminal device (such as a mobile phone) or a network device (such as a base station). The specific reference needs to be clarified based on the context.

[0364] An embodiment of the present application further provides a computer-readable storage medium, on which a processing program is stored. When the processing program is executed by a processor, the steps of the processing method in any of the above embodiments are implemented.

[0365] In the embodiments of the communication device and computer-readable storage medium provided in the embodiments of the present application, all technical features of any of the above-mentioned processing method embodiments may be included, and the expansion and explanation content of the specification are basically the same as those of the embodiments of the above-mentioned methods, and will not be repeated here.

[0366] The present application also provides a computer program product, which includes a computer program code. When the computer program code is run on a computer, the computer executes the methods in the above various possible implementations. The present application also provides a chip, which includes a memory and a processor. The memory is used to store a computer program, and the processor is used to call and run the computer program from the memory, so that a device equipped with the chip executes the methods in the above various possible implementations.

[0367] It can be understood that the above scenarios are only examples and do not constitute a limitation on the application scenarios of the technical solutions provided in the embodiments of the present application. The technical solutions of the present application can also be applied to other scenarios. For example, it is known to those skilled in the art that with the evolution of the system architecture and the emergence of new business scenarios, the technical solutions provided in the embodiments of the present application are also applicable to similar technical problems. The serial numbers of the embodiments of the present application are only for description and do not represent the advantages and disadvantages of the embodiments. The steps in the method of the embodiment of the present application can be adjusted, merged and deleted in sequence according to actual needs. The units in the device of the embodiment of the present application can be merged, divided and deleted according to actual needs. In the present application, for the same or similar terminology, technical solutions and / or application scenario descriptions, they are generally described in detail only when they appear for the first time. When they appear again later, for the sake of brevity, they are generally not repeated. When understanding the content of the technical solutions of the present application, for the same or similar terminology, technical solutions and / or application scenario descriptions that are not described in detail later, reference can be made to the relevant detailed descriptions before. In the present application, the descriptions of each embodiment have their own emphasis. For the parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments. The various technical features of the technical solution of the present application can be arbitrarily combined. In order to make the description concise, not all possible combinations of the various technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of the present application.

[0368] Through the description of the above implementation mode, it can be clearly understood by those skilled in the art that the above-mentioned embodiment method can be implemented by means of software plus the necessary general hardware platform, and of course it can also be implemented by hardware, but in many cases the former is a better implementation mode. Based on such an understanding, the technical solution of the present application is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product is stored in a storage medium (such as ROM / RAM, disk, CD) as above, including several instructions to enable a terminal device (which can be a mobile phone, computer, server, controlled terminal device, or network device, etc.) to execute the method of each embodiment of the present application. 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 instructions. When loading and executing computer program instructions on a computer, the process or function according to 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 devices. Computer instructions can be stored in a storage medium, or transmitted from one storage medium to another storage medium. For example, computer instructions can be transmitted from one website, computer, server or data center to another website, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line) or wireless (e.g., infrared, wireless, microwave, etc.) means. The 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 can be a magnetic medium (e.g., a floppy disk, a storage disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid state storage disk Solid State Disk (SSD)). The above are only preferred embodiments of the present application, and the scope of the patent of the present application is not limited thereto. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the scope of patent protection of the present application.

Claims

1. A processing method, characterized in that: Applied to terminal equipment, including the steps of: S1: Available artificial intelligence or machine learning capabilities based on the first content report.

2. The method according to claim 1, characterized in that Also includes at least one of the following: The terminal device is in a radio resource control inactive state; Available artificial intelligence or machine learning functions are carried in the radio resource control recovery request signaling; Available artificial intelligence or machine learning functions are carried in the radio resource control recovery complete signaling; The first content includes a stored configuration of artificial intelligence or machine learning functions; The first content includes the retained artificial intelligence or machine learning function configuration; The first content includes the restored artificial intelligence or machine learning function configuration; The first content includes updated artificial intelligence or machine learning function configuration.

3. The method according to claim 2, characterized in that Also includes at least one of the following: The retained AI or ML functional configuration is determined by the AI ​​or ML indication; The configuration of the restored artificial intelligence or machine learning function is determined by the artificial intelligence or machine learning indication; The updated artificial intelligence or machine learning function configuration is configured via radio resource control recovery signaling.

4. The method according to claim 3, characterized in that Also includes at least one of the following: an AI or ML instruction, including at least one of an AI or ML retention instruction, an AI or ML release instruction, and an AI or ML recovery instruction; The artificial intelligence or machine learning indication is carried in at least one of the radio resource control reconfiguration signaling, the radio resource control release signaling, and the radio resource control recovery signaling.

5. A processing method, characterized in that: Applied to network equipment, including the steps of: S2: Receive available artificial intelligence or machine learning functions, where the available artificial intelligence or machine learning functions are reported by the terminal device based on the first content.

6. The method according to claim 5, characterized in that Also includes at least one of the following: The terminal device is in a radio resource control inactive state; Available artificial intelligence or machine learning functions are carried in the radio resource control recovery request signaling; Available artificial intelligence or machine learning functions are carried in the radio resource control recovery complete signaling; The first content includes a stored configuration of artificial intelligence or machine learning functions; The first content includes the retained artificial intelligence or machine learning function configuration; The first content includes the restored artificial intelligence or machine learning function configuration; The first content includes updated artificial intelligence or machine learning function configuration.

7. The method according to claim 6, characterized in that Also includes at least one of the following: The retained AI or ML functional configuration is determined by the AI ​​or ML indication; The configuration of the restored artificial intelligence or machine learning function is determined by the artificial intelligence or machine learning indication; The updated artificial intelligence or machine learning function configuration is sent via radio resource control resumption signaling.

8. The method according to claim 7, characterized in that Also includes at least one of the following: an AI or ML instruction, including at least one of an AI or ML retention instruction, an AI or ML release instruction, and an AI or ML recovery instruction; The artificial intelligence or machine learning indication is carried in at least one of the radio resource control reconfiguration signaling, the radio resource control release signaling, and the radio resource control recovery signaling.

9. A communication device, characterized in that: include: A memory, a processor, and a processing program stored in the memory and executable on the processor, wherein the processing program is executed by the processor to implement the steps of the processing method according to claim 1 or 5.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and the computer program is executed by a processor to implement the steps of the processing method according to claim 1 or 5.

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