Method for sending indication information, method for receiving indication information, and terminals, apparatus, system and storage medium

Abstract

The present disclosure relates to a method for sending indication information, a method for receiving indication information, and terminals, an apparatus, a system and a storage medium. The method for receiving indication information comprises: receiving first indication information sent by a network device, the first indication information being used for indicating a terminal behavior of a terminal in managing an AI model or an AI function. In the method of the present disclosure, a terminal receives first indication information to learn of a UE behavior indicated by a network device, so that an adaptive operation can be performed during the process of the terminal managing an AI model or AI function, thereby facilitating an improvement to the rationality of the terminal managing the AI model or AI function when the terminal has reached a consensus with the network device by means of negotiation.

Description

Method, terminal, device, system and storage medium for sending and receiving indication information Technical Field

[0001] The present disclosure relates to the field of communication technologies, and in particular to a method, terminal, device, system, and storage medium for sending and receiving indication information. Background Art

[0002] Artificial intelligence (AI) technology can be applied across a wide range of technological fields. Machine learning algorithms are one of the most important AI implementation methods. Machine learning uses large amounts of training data to generate models that can be used to accurately predict events. In wireless communication networks, AI can be applied for prediction and reasoning, improving communication system performance.

[0003] Summary of the Invention

[0004] In wireless communication systems, the issue of how to manage AI-related models or functions needs to be addressed.

[0005] Embodiments of the present disclosure provide a method, terminal, device, system, and storage medium for sending and receiving indication information.

[0006] In a first aspect, an embodiment of the present disclosure provides a method for receiving indication information, performed by a terminal, the method comprising:

[0007] Receive first indication information sent by a network device, where the first indication information is used to instruct the terminal to manage a terminal behavior of an AI model or an AI function.

[0008] In a second aspect, an embodiment of the present disclosure provides a method for sending indication information, which is performed by a network device, and the method includes:

[0009] Sending first indication information to the terminal, where the first indication information is used to instruct the terminal to manage terminal behavior of the AI ​​model or AI function.

[0010] In a third aspect, an embodiment of the present disclosure provides a terminal, including:

[0011] The transceiver module is used to receive first indication information sent by a network device, where the first indication information is used to instruct the terminal to manage the terminal behavior of the AI ​​model or AI function.

[0012] In a fourth aspect, an embodiment of the present disclosure provides a network device, comprising

[0013] The transceiver module is used to send first indication information to the terminal, where the first indication information is used to instruct the terminal to manage the terminal behavior of the AI ​​model or AI function.

[0014] In a fifth aspect, an embodiment of the present disclosure provides a terminal, including:

[0015] one or more processors;

[0016] The terminal is used to execute the method of the first aspect.

[0017] In a sixth aspect, an embodiment of the present disclosure provides a network device, including:

[0018] one or more processors;

[0019] The network device is used to execute the method of the second aspect.

[0020] In a seventh aspect, an embodiment of the present disclosure provides a communication system, including a terminal and a network device, wherein:

[0021] The terminal is configured to implement the method of the first aspect;

[0022] The network device is configured to implement the method of the second aspect.

[0023] In an eighth aspect, an embodiment of the present disclosure provides a storage medium, wherein the storage medium stores instructions, wherein:

[0024] When the instructions are executed on the communication device, the communication device is caused to execute the method of the first aspect or the second aspect.

[0025] In the embodiment of the present disclosure, the terminal obtains the UE behavior indicated by the network device by receiving the first indication information, so that adaptive operations can be performed during the process of the terminal managing the AI ​​model or AI function, thereby facilitating improving the rationality and effectiveness of the terminal's management of the AI ​​model or AI function in consultation with the network device. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the technical solutions in the embodiments of the present disclosure, the following drawings required for describing the embodiments are introduced. The following drawings are merely some embodiments of the present disclosure and do not impose specific limitations on the protection scope of the present disclosure.

[0027] FIG1 is an exemplary schematic diagram of the architecture of a communication system provided according to an embodiment of the present disclosure;

[0028] 2a to 2b are exemplary interaction diagrams of a method according to an embodiment of the present disclosure;

[0029] 3a to 3d are exemplary flowcharts of a method according to an embodiment of the present disclosure;

[0030] 4a to 4d are exemplary flowcharts of a method according to an embodiment of the present disclosure;

[0031] FIG5a is a schematic structural diagram of a terminal according to an embodiment of the present disclosure;

[0032] FIG5b is a schematic structural diagram of a network device according to an embodiment of the present disclosure;

[0033] FIG6a is a schematic diagram of a communication device according to an embodiment of the present disclosure;

[0034] FIG6 b is a schematic diagram of a communication device according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0035] Embodiments of the present disclosure provide a method, terminal, device, system, and storage medium for sending and receiving indication information.

[0036] In a first aspect, an embodiment of the present disclosure provides a method for receiving indication information, performed by a terminal, the method comprising:

[0037] Receive first indication information sent by a network device, where the first indication information is used to instruct the terminal to manage a terminal behavior of an AI model or an AI function.

[0038] In the above embodiment, the terminal obtains the UE behavior indicated by the network device by receiving the first indication information, so that adaptive operations can be performed during the terminal's AI model or AI function management process, thereby facilitating the improvement of the rationality and effectiveness of the terminal's management of the AI ​​model or AI function in consultation with the network device.

[0039] In conjunction with the embodiments of the first aspect, in some embodiments, the first indication information includes at least one of the following:

[0040] The identifier of at least one AI model;

[0041] The identifier of at least one AI function;

[0042] The identifier of at least one AI application scenario.

[0043] The AI ​​model, the AI ​​function, or the AI ​​application scenario must meet at least one of the following conditions:

[0044] The AI ​​functionality is associated with one or more of the AI ​​models;

[0045] The AI ​​application scenario is associated with one or more AI models;

[0046] The AI ​​application scenario is associated with one or more AI functions.

[0047] In the above embodiment, the terminal can obtain the model identifier, function identifier or scenario identifier indicated by the network device based on the received first indication information, so that the terminal can perform corresponding terminal behavior when managing the model corresponding to the first indication information.

[0048] In combination with the embodiments of the first aspect, in some embodiments, the AI ​​function corresponds to one or more AI models that implement the same function.

[0049] In the above embodiment, the terminal may manage the associated model or function at an appropriate time according to the first indication information based on the association between the AI ​​function and the AI ​​model.

[0050] In conjunction with the embodiments of the first aspect, in some embodiments, the AI ​​application scenario includes at least one of the following:

[0051] beam management;

[0052] Beam measurement;

[0053] Channel state information CSI reporting;

[0054] Terminal positioning;

[0055] Mobility management;

[0056] Radio resource measurement.

[0057] In the above embodiment, in different communication scenarios, the terminal can manage the model or function at an appropriate time based on the first indication information to improve the utilization effect of the model or function.

[0058] In conjunction with the embodiments of the first aspect, in some embodiments, the method further includes:

[0059] When the terminal selects a first AI model or a first AI function, the terminal determines the terminal behavior according to the first AI model or the first AI function and the first indication information; wherein the first AI model is one of multiple AI models supported by the terminal, or the first AI function is one of multiple AI functions supported by the terminal.

[0060] In the above embodiment, the terminal can make a judgment on the selected AI model or function based on the first indication information, and determine the appropriate terminal behavior, so as to negotiate with the network device to determine the appropriate management operation.

[0061] In conjunction with the embodiments of the first aspect, in some embodiments, the terminal determines the terminal behavior according to the first AI model or the first AI function and the first indication information, including:

[0062] When the first AI model or the first AI function matches the identifier in the first indication information, the terminal sends second indication information to the network device; wherein the second indication information is used to indicate: the identifier corresponding to the first AI model or the first AI function, and / or a management operation on the first AI model or the first AI function.

[0063] In the above embodiment, when the AI ​​model or function selected by the terminal matches the first indication information, the terminal may send the second indication information to promptly report the management indication to the network device to facilitate subsequent reasonable management operations.

[0064] In conjunction with the embodiments of the first aspect, in some embodiments, the method further includes:

[0065] The terminal performs the management operation indicated by the second indication information on the first AI model or the first AI function.

[0066] In conjunction with the embodiments of the first aspect, in some embodiments, the terminal determines the terminal behavior according to the first AI model or the first AI function and the first indication information, including:

[0067] When the first AI model or the first AI function matches the identifier in the first indication information, the terminal sends a request message to the network device; wherein the request message is used to indicate the identifier corresponding to the first AI model or the first AI function, and / or the management operation requested by the terminal;

[0068] receiving third indication information sent by the network device, where the third indication information is used to indicate an identifier corresponding to a second AI model or a second AI function that the terminal is allowed to manage, and / or to allow the terminal to perform a management operation on the second AI model or the second AI function;

[0069] The second AI model is the same as or different from the first AI model, or the second AI function is the same as or different from the second AI function.

[0070] In the above embodiment, when the AI ​​model or function selected by the terminal matches the first indication information, the terminal can send a request message to promptly request a management indication from the network device.

[0071] In conjunction with the embodiments of the first aspect, in some embodiments, the method further includes:

[0072] The terminal performs the management operation indicated by the third indication information on the second AI model or the second AI function.

[0073] In the above embodiment, after sending the management request, the terminal may perform a management operation on the model or function according to the third instruction information of the network device, thereby managing the model or function under the instruction of the network device.

[0074] In conjunction with the embodiments of the first aspect, in some embodiments, the management operation includes at least one of the following:

[0075] Enabling AI models or AI functions;

[0076] Disabling AI models or AI functions;

[0077] Switching of AI models or AI functions.

[0078] In the above embodiment, the management of the model or function by the terminal includes enabling, disabling or switching. The terminal can perform appropriate management operations at an appropriate time under the instruction or permission of the network device.

[0079] In conjunction with the embodiments of the first aspect, in some embodiments, the method further includes:

[0080] Sending auxiliary information to the network device, where the auxiliary information includes a correspondence between an AI model, an AI function, and an AI application scenario; or,

[0081] Receive configuration information sent by the network device, where the configuration information includes the corresponding relationship.

[0082] In the above embodiment, the terminal can determine the corresponding relationship by itself and report the corresponding relationship to the network device, or the terminal receives the corresponding relationship configured by the network device, and based on the corresponding relationship, the terminal can perform appropriate processing on the associated model, function or scenario.

[0083] In a second aspect, an embodiment of the present disclosure provides a method for sending indication information, which is performed by a network device, and the method includes:

[0084] Sending first indication information to the terminal, where the first indication information is used to instruct the terminal to manage terminal behavior of the AI ​​model or AI function.

[0085] In the above embodiment, the network device sends a first indication message to indicate the possible UE behaviors to the terminal, so that adaptive operations can be performed during the terminal's management of the AI ​​model or AI function, thereby facilitating the improvement of the rationality and effectiveness of the terminal's management of the AI ​​model or AI function in agreement with the network device.

[0086] In conjunction with the embodiments of the second aspect, in some embodiments, the first indication information includes at least one of the following:

[0087] The identifier of at least one AI model;

[0088] The identifier of at least one AI function;

[0089] The identifier of at least one AI application scenario.

[0090] In conjunction with the embodiments of the second aspect, in some embodiments, the AI ​​model, the AI ​​function, or the AI ​​application scenario satisfies at least one of the following:

[0091] The AI ​​function is associated with one or more of the AI ​​models;

[0092] The AI ​​application scenario is associated with one or more AI models;

[0093] The AI ​​application scenario is associated with one or more AI functions.

[0094] In combination with the embodiments of the second aspect, in some embodiments, the AI ​​function corresponds to one or more AI models that implement the same function.

[0095] In conjunction with the embodiments of the second aspect, in some embodiments, the AI ​​application scenario includes at least one of the following:

[0096] beam management;

[0097] Beam measurement;

[0098] CSI reporting;

[0099] Terminal positioning;

[0100] Mobility management;

[0101] Radio resource measurement.

[0102] In conjunction with the embodiments of the second aspect, in some embodiments, the method further includes:

[0103] receiving second indication information sent by the terminal, where the second indication information is sent when the first AI model or the first AI function matches an identifier in the first indication information; the second indication information is used to indicate: an identifier corresponding to the first AI model or the first AI function, and / or a management operation on the first AI model or the first AI function;

[0104] The first AI model is one of multiple AI models supported by the terminal, or the first AI function is one of multiple AI functions supported by the terminal.

[0105] In conjunction with the embodiments of the second aspect, in some embodiments, the method further includes:

[0106] receiving a request message sent by the terminal, wherein the request message is sent when the first AI model or the first AI function matches the identifier in the first indication information, and the request message is used to indicate the identifier corresponding to the first AI model or the first AI function, and / or the management operation requested by the terminal;

[0107] Sending third indication information to the terminal, where the third indication information is used to indicate an identifier corresponding to a second AI model or a second AI function that the terminal is allowed to manage, and / or allowing the terminal to perform a management operation on the second AI model or the second AI function;

[0108] The second AI model is the same as or different from the first AI model, or the second AI function is the same as or different from the second AI function.

[0109] In conjunction with the embodiments of the second aspect, in some embodiments, the management operation includes at least one of the following:

[0110] Enabling AI models or AI functions;

[0111] Disabling AI models or AI functions;

[0112] Switching of AI models or AI functions.

[0113] In conjunction with the embodiments of the second aspect, in some embodiments, the method further includes:

[0114] receiving auxiliary information sent by the terminal, where the auxiliary information includes a correspondence between an AI model, an AI function, and an AI application scenario; or

[0115] Send configuration information to the terminal, where the configuration information includes the corresponding relationship.

[0116] In a third aspect, an embodiment of the present disclosure provides a terminal, including:

[0117] The transceiver module is used to receive first indication information sent by a network device, where the first indication information is used to instruct the terminal to manage the terminal behavior of the AI ​​model or AI function.

[0118] In a fourth aspect, an embodiment of the present disclosure provides a network device, comprising

[0119] The transceiver module is used to send first indication information to the terminal, where the first indication information is used to instruct the terminal to manage the terminal behavior of the AI ​​model or AI function.

[0120] In a fifth aspect, an embodiment of the present disclosure provides a terminal, including:

[0121] one or more processors;

[0122] The terminal is used to execute the method of the first aspect.

[0123] In a sixth aspect, an embodiment of the present disclosure provides a network device, including:

[0124] one or more processors;

[0125] The network device is used to execute the method of the second aspect.

[0126] In a seventh aspect, an embodiment of the present disclosure provides a communication system, including a terminal and a network device, wherein:

[0127] The terminal is configured to implement the method of the first aspect;

[0128] The network device is configured to implement the method of the second aspect.

[0129] In an eighth aspect, an embodiment of the present disclosure provides a storage medium, wherein the storage medium stores instructions, wherein:

[0130] When the instructions are executed on the communication device, the communication device is caused to execute the method of the first aspect or the second aspect.

[0131] In a ninth aspect, an embodiment of the present disclosure proposes a program product. When the program product is executed by a communication device, the communication device executes the method described in the optional implementation of the first and second aspects.

[0132] In a tenth aspect, an embodiment of the present disclosure proposes a computer program, which, when executed on a computer, enables the computer to execute the method described in the optional implementation of the first and second aspects.

[0133] In an eleventh aspect, an embodiment of the present disclosure provides a chip or a chip system, wherein the chip or chip system includes a processing circuit configured to execute the method described in the optional implementation of the first and second aspects above.

[0134] It is understandable that the above-mentioned terminals, network devices, communication systems, storage media, program products, computer programs, chips, or chip systems are all used to perform the methods proposed in the embodiments of the present disclosure. Therefore, the beneficial effects that can be achieved can refer to the beneficial effects of the corresponding methods and will not be repeated here.

[0135] The embodiments of the present disclosure are not exhaustive and are merely illustrative of some embodiments, and are not intended to be a specific limitation on the scope of protection of the present disclosure. In the absence of contradiction, each step in a certain embodiment can be implemented as an independent embodiment, and the steps can be arbitrarily combined. For example, a solution after removing some steps in a certain embodiment can also be implemented as an independent embodiment, and the order of the steps in a certain embodiment can be arbitrarily exchanged. In addition, the optional implementation methods in a certain embodiment can be arbitrarily combined; in addition, the embodiments can be arbitrarily combined. For example, some or all steps of different embodiments can be arbitrarily combined, and a certain embodiment can be arbitrarily combined with the optional implementation methods of other embodiments.

[0136] In each embodiment of the present disclosure, unless otherwise specified or provided for by logic, the terms and / or descriptions between the embodiments are consistent and can be referenced by each other. The technical features in different embodiments can be combined to form a new embodiment based on their inherent logical relationships.

[0137] The terms used in the embodiments of the present disclosure are only for the purpose of describing specific embodiments and are not intended to limit the present disclosure.

[0138] In the embodiments of the present disclosure, unless otherwise specified, elements expressed in the singular, such as "a", "an", "the", "above", "said", "the", "the", etc., may mean "one and only one", or "one or more", "at least one", etc. For example, when using articles such as "a", "an", "the" in English in translation, the noun following the article may be understood as a singular expression or a plural expression.

[0139] In the embodiments of the present disclosure, “plurality” refers to two or more.

[0140] In some embodiments, the terms "at least one," "one or more," "a plurality of," "multiple," etc. may be used interchangeably.

[0141] In some embodiments, descriptions such as "at least one of A and B," "A and / or B," "A in one case, B in another case," or "in response to one case A, in response to another case B" may include the following technical solutions depending on the situation: in some embodiments, A (A is executed independently of B); in some embodiments, B (B is executed independently of A); in some embodiments, execution is selected from A and B (A and B are selectively executed); and in some embodiments, A and B (both A and B are executed). The above is also applicable when there are more branches such as A, B, and C.

[0142] In some embodiments, "A or B" and other descriptions may include the following technical solutions depending on the situation: in some embodiments, A (A is executed independently of B); in some embodiments, B (B is executed independently of A); in some embodiments, execution is selected from A and B (A and B are selectively executed). The above is also applicable when there are more branches such as A, B, C, etc.

[0143] The prefixes such as "first" and "second" in the embodiments of the present disclosure are only used to distinguish different description objects and do not constitute any restriction on the position, order, priority, quantity or content of the description objects. For the statement of the description object, please refer to the description in the context of the claims or embodiments, and no unnecessary restriction should be constituted due to the use of prefixes. For example, if the description object is a "field", the ordinal number before the "field" in the "first field" and the "second field" does not limit the position or order between the "fields". "First" and "second" do not limit whether the "fields" they modify are in the same message, nor do they limit the order of the "first field" and the "second field". For another example, if the description object is a "level", the ordinal number before the "level" in the "first level" and the "second level" does not limit the priority between the "levels". For another example, the number of description objects is not limited by the ordinal number and can be one or more. Taking "first device" as an example, the number of "devices" can be one or more. In addition, the objects modified by different prefixes can be the same or different. For example, if the description object is "device", then the "first device" and the "second device" can be the same device or different devices, and their types can be the same or different; for another example, if the description object is "information", then the "first information" and the "second information" can be the same information or different information, and their contents can be the same or different.

[0144] In some embodiments, “including A,” “comprising A,” “used to indicate A,” and “carrying A” can be interpreted as directly carrying A or indirectly indicating A.

[0145] In some embodiments, terms such as "in response to...", "in response to determining...", "in the case of...", "at the time of...", "when...", "if...", "if...", etc. can be used interchangeably.

[0146] In some embodiments, terms such as "greater than", "greater than or equal to", "not less than", "more than", "more than or equal to", "not less than", "higher than", "higher than or equal to", "not less than", and "above" can be replaced with each other, and terms such as "less than", "less than or equal to", "not greater than", "less than", "less than or equal to", "not more than", "lower than", "lower than or equal to", "not higher than", and "below" can be replaced with each other.

[0147] In some embodiments, devices and equipment can be interpreted as physical or virtual, and their names are not limited to the names recorded in the embodiments. In some cases, they can also be understood as "equipment", "device", "circuit", "network element", "node", "function", "unit", "section", "system", "network", "chip", "chip system", "entity", "subject", etc.

[0148] In some embodiments, "network" can be interpreted as devices included in the network, such as access network equipment, core network equipment, etc.

[0149] In some embodiments, "access network device (AN device)" may also be referred to as "radio access network device (RAN device)", "base station (BS)", "radio base station", "fixed station", and in some embodiments may also be understood as "node", "access point", "transmission point (TP)", "reception point (RP)", "transmission and / or reception point (TRP)" "panel", "antenna panel", "antenna array", "cell", "macro cell", "small cell", "femto cell", "pico cell", "sector", "cell group", "serving cell", "carrier", "component carrier", "bandwidth part (BWP)", etc.

[0150] In some embodiments, "terminal" or "terminal device" may be referred to as "user equipment (UE)", "user terminal" "mobile station (MS)", "mobile terminal (MT)", subscriber station, mobile unit, subscriber unit, wireless unit, remote unit, mobile device, wireless device, wireless communication device, remote device, mobile subscriber station, access terminal, mobile terminal, wireless terminal, remote terminal, handset, user agent, mobile client, client, etc.

[0151] In some embodiments, obtaining data, information, etc. may comply with the laws and regulations of the country where the data is obtained.

[0152] In some embodiments, data, information, etc. may be obtained with the user's consent.

[0153] In addition, each element, each row, or each column in the table of the embodiment of the present disclosure can be implemented as an independent embodiment, and the combination of any elements, any rows, and any columns can also be implemented as an independent embodiment.

[0154] FIG1 is a schematic diagram showing the architecture of a communication system according to an embodiment of the present disclosure.

[0155] As shown in FIG1 , a communication system 100 includes a terminal 101 and a network device 102 .

[0156] In some embodiments, the terminal 101 includes, for example, a mobile phone, a wearable device, an Internet of Things device, a car with communication function, a smart car, a tablet computer, a computer with wireless transceiver function, a virtual reality (VR) terminal device, an augmented reality (AR) terminal device, a wireless terminal device in industrial control, a wireless terminal device in self-driving, a wireless terminal device in remote medical surgery, a wireless terminal device in a smart grid, a wireless terminal device in transportation safety, a wireless terminal device in a smart city, and at least one of a wireless terminal device in a smart home, but is not limited thereto.

[0157] In some embodiments, when the network device 102 is a network device, the network device may include at least one of an access network device and a core network device.

[0158] In some embodiments, the access network device is, for example, a node or device that accesses a terminal to a wireless network. The access network device may include an evolved NodeB (eNB), a next generation evolved NodeB (ng-eNB), a next generation NodeB (gNB), a node B (NB), a home node B (HNB), a home evolved nodeB (HeNB), a wireless backhaul device, a radio network controller (RNC), a base station controller (BSC), a base transceiver station (BTS), a base band unit (BBU), a mobile switching center, a base station in a 6G communication system, an open base station (Open RAN), a cloud base station (Cloud RAN), a base station in other communication systems, and at least one of an access node in a wireless fidelity (WiFi) system, but is not limited thereto.

[0159] In some embodiments, the technical solution of the present disclosure can be applied to the Open RAN architecture. In this case, the interfaces between or within the access network devices involved in the embodiments of the present disclosure can be transformed into internal interfaces of the Open RAN, and the processes and information interactions between these internal interfaces can be implemented through software or programs.

[0160] In some embodiments, the access network device can be composed of a centralized unit (CU) and a distributed unit (DU), where the CU can also be called a control unit. The CU-DU structure can be used to split the protocol layer of the access network device, with the functions of some protocol layers centrally controlled by the CU, and the functions of the remaining part or all of the protocol layers distributed in the DU, which is centrally controlled by the CU, but is not limited to this.

[0161] In some embodiments, the core network device can be a device including one or more network elements, or it can be multiple devices or device groups, each including all or part of one or more network elements. The network element can be virtual or physical. The core network includes, for example, at least one of the Evolved Packet Core (EPC), the 5G Core Network (5GCN), and the Next Generation Core (NGC). Alternatively, the core network device refers to a network element with a specific function, such as the Access Management Function (AMF), the Service Management Function (SMF), etc.

[0162] It can be understood that the communication system described in the embodiment of the present disclosure is for the purpose of more clearly illustrating the technical solution of the embodiment of the present disclosure, and does not constitute a limitation on the technical solution provided by the embodiment of the present disclosure. Ordinary technicians in this field can know that with the evolution of the system architecture and the emergence of new business scenarios, the technical solution provided by the embodiment of the present disclosure is also applicable to similar technical problems.

[0163] The following embodiments of the present disclosure may be applied to the communication system 100 shown in FIG. 1 , or a part of the main body thereof, but are not limited thereto.

[0164] The entities shown in Figure 1 are examples. The communication system may include all or part of the entities in Figure 1, and may also include other entities outside of Figure 1. The number and form of the entities are arbitrary. The connection relationship between the entities is an example. The entities may be connected or disconnected, and the connection may be in any manner, which may be direct or indirect, and may be wired or wireless.

[0165] The embodiments of the present disclosure can be applied to Long Term Evolution (LTE), LTE-Advanced (LTE-A), LTE-Beyond (LTE-B), SUPER 3G, IMT-Advanced, 4th generation mobile communication system (4G), 5th generation mobile communication system (5G), 5G new radio (NR), future radio access (FRA), new radio access technology (RAT), new radio (NR), new radio access (NX), future generation radio access (FX), Global System for Mobile communications (GSM (registered trademark)), CDMA2000, Ultra Mobile Broadband (UMB), IEEE 802.11 (Wi-Fi (registered trademark)), IEEE 802.16 (WiMAX (registered trademark)), IEEE 802.20, Ultra-WideBand (UWB), Bluetooth (registered trademark), Public Land Mobile Network (PLMN) networks, Device-to-Device (D2D) systems, Machine-to-Machine (M2M) systems, Internet of Things (IoT) systems, Vehicle-to-Everything (V2X), systems utilizing other communication processing methods, and next-generation systems based on and extending these. Furthermore, multiple systems may be combined (for example, a combination of LTE or LTE-A with 5G).

[0166] In the disclosed embodiments, in an AI-based wireless communication system, training the AI ​​model requires collecting a large amount of data, and different application scenarios require different data. Terminal 101 may support multiple AI models or functions, so it is necessary to solve the problem of how Terminal 101 manages AI-related models or functions.

[0167] FIG2a is an interactive diagram illustrating a method for receiving and sending indication information according to an embodiment of the present disclosure. As shown in FIG2a , an embodiment of the present disclosure relates to a method for receiving and sending indication information, the method comprising:

[0168] Step S2101 , the terminal 101 sends auxiliary information to the network device 102 .

[0169] In some embodiments, assistance information includes the correspondence or mapping relationship between AI models, AI functions, and AI application scenarios.

[0170] Optionally, each AI function is associated with one or more AI models, which are used to implement a specific function. In other words, an AI function corresponds to one or more AI models, where the one or more AI models can be used to implement a function or the same function, or one or more AI models that implement the same function are collectively referred to as an AI function.

[0171] Optionally, the AI ​​application scenario is associated with one or more AI models, or the AI ​​application scenario is associated with one or more AI functions. The one or more AI models or AI functions are used in the AI ​​application scenario.

[0172] Optionally, the AI ​​application scenario includes at least one of the following:

[0173] beam management;

[0174] Beam measurement;

[0175] Channel State Information (CSI) reporting;

[0176] Terminal positioning;

[0177] Mobility management;

[0178] Radio resource measurement.

[0179] Optionally, the above AI application scenarios are for illustration only and are not limiting. For example, they may also include mobile communication system processes such as cell switching and wireless resource management.

[0180] During AI-based beam management, terminal 101 can reduce the number of measured beams. Terminal 101 or network device 102 then uses AI inference to determine the optimal beam. Beam prediction in beam management includes spatial and time-domain beam prediction. In spatial beam prediction, terminal 101 measures a small number of beams and predicts the measurement results of other beams. In time-domain beam prediction, terminal 101 predicts future beam measurement results based on historical beam measurement results.

[0181] During AI-based CSI reporting, terminal 101 can perform CSI compression based on an AI model, compress the CSI measurement results using AI, and report the compressed CSI measurement results to network device 102. After receiving the CSI measurement results, network device 102 restores the original CSI measurement results using the AI ​​model. The AI-based CSI reporting process reduces the number of signaling bits required during the reporting process. Network device 102 can also predict future CSI based on historical CSI measurement results reported by terminal 101.

[0182] In the AI-based positioning process, the terminal 101 can predict the precise location based on limited measurement results.

[0183] In the AI-based mobility process, the terminal 101 can predict the handover target cell or mobility event.

[0184] Optionally, for any AI application scenario, during the training phase, the AI ​​model or function needs to be trained using training data from the corresponding scenario. During the use and inference process of the AI ​​model or function, multiple AI models or AI functions may be required for inference and prediction. Therefore, for a terminal 101 that supports multiple AI models or AI functions, it is necessary to effectively manage the AI ​​models or AI functions.

[0185] In some embodiments, the network device 102 receives auxiliary information to obtain the corresponding relationships supported by the terminal 101.

[0186] In some embodiments, step S2101 is applicable to an implementation in which the terminal 101 independently determines the above correspondence relationship. Optionally, step S2101 can be omitted, for example, when the terminal 101 obtains the correspondence relationship through step S2102, step S2101 can be omitted.

[0187] Step S2102 , the network device 102 sends configuration information to the terminal 101 .

[0188] Optionally, the configuration information includes the correspondence between AI models, AI functions and AI application scenarios.

[0189] Optionally, the corresponding relationship can refer to the implementation of step S2102, which will not be repeated here.

[0190] In some embodiments, the network device 102 may send the configuration information via Radio Resource Control (RRC).

[0191] In some embodiments, the terminal 101 receives the above configuration information to obtain the corresponding relationship.

[0192] In some embodiments, step S2102 is applicable to an implementation in which the network device 102 configures the corresponding relationship for the terminal 101. Optionally, step S2102 may be omitted, for example, when the terminal 101 determines the corresponding relationship through step S2101, step S2102 may be omitted.

[0193] Step S2103 , the network device 102 sends first indication information to the terminal 101 .

[0194] Optionally, the first indication information is used to instruct the terminal 101 to manage the terminal behavior of the AI ​​model or AI function.

[0195] For example, the terminal behavior may include the behavior of terminal 101 before deciding to manage the AI ​​model or AI function but performing a specific management operation; or, the terminal behavior may include the operation of terminal 101 after deciding to manage the AI ​​model or AI function, as well as the specific management operation.

[0196] Optionally, the management of the AI ​​model or AI function by the terminal 101 may include the use of the AI ​​model or AI function, or the selection not to use a certain AI model or AI function.

[0197] Optionally, the management operation of the terminal 101 on the AI ​​model or AI function includes one of the following: enabling the AI ​​model or AI function, disabling the AI ​​model or AI function, and switching the AI ​​model or AI function.

[0198] Optionally, enabling an AI model or AI function may be activating the AI ​​model or AI function, and disabling the AI ​​model or AI function may be deactivating the AI ​​model or AI function. For example, after activating an AI model or AI function, terminal 101 may use or apply the AI ​​model or AI function; after deactivating the AI ​​model or AI function, terminal 101 may consider the AI ​​model or AI function to be invalid; when switching an AI model or AI function, terminal 101 may switch from using or applying one AI model or AI function to using or applying another AI model or AI function.

[0199] In some embodiments, when the terminal 101 manages the AI ​​model or AI function in different ways, different terminal behaviors may be determined based on the first indication information.

[0200] Optionally, the method for the terminal 101 to manage the AI ​​model or AI function includes the following two methods: network determination and terminal determination. The terminal behaviors in the two methods are different.

[0201] In one example, the network decision-making method includes the following two methods: First, the network device 102 sends configuration information (configuration), such as relevant configuration for measurement (measurement) or reporting (reporting); the terminal 101 reports auxiliary information to the network device 102, and the auxiliary information may include measurement results (measurements). The network device 102 sends a management instruction (management instruction) to the terminal 101, instructing the terminal 101 to use the AI ​​model or AI function. Second, the network device 102 sends configuration information, such as relevant configuration for measurement or reporting; the terminal 101 can decide how to manage the AI ​​model or function and send a management request (management request) to the network device 102. After receiving the management request, the network device 102 issues a management instruction, and the terminal 101 determines the AI ​​model or AI function to be used according to the management instruction.

[0202] In another example, the terminal 101 may make a decision in one of the following three ways: First, the network device 102 sends configuration information, such as performing measurements and configuring AI management conditions (conditions for event triggering); when the configured AI management conditions are met, the terminal 101 automatically determines the AI ​​model or function to use and reports the management result, or management decision (management decision report), to the network device 102. Second, the network device 102 sends configuration information, such as including a configuration for the terminal 101 to report a management decision, and the terminal 101 independently determines the AI ​​model or AI function to use and then reports the management decision to the network device 102. Third, the terminal 101 independently determines the AI ​​model or function to use and does not report the management decision.

[0203] Optionally, the terminal 101 may perform an appropriate operation or select an appropriate method for AI management based on the first indication information. For example, the first indication information may be used to indicate when the terminal 101 sends a management indication, such as when the terminal 101 sends a management indication in a terminal-determined manner; for another example, the first indication information may be used to indicate when the terminal 101 sends a management request, such as when the terminal 101 sends a management request in a network-determined manner.

[0204] In some embodiments, the first indication information includes at least one of the following:

[0205] The identifier of at least one AI model (model ID);

[0206] At least one AI functional ID;

[0207] The identifier of at least one AI application scenario (situation ID).

[0208] Optionally, the AI ​​model, the AI ​​function, or the AI ​​application scenario satisfies at least one of the following:

[0209] The AI ​​functionality is associated with one or more of the AI ​​models;

[0210] The AI ​​application scenario is associated with one or more of the AI ​​models;

[0211] AI application scenarios are associated with one or more of the AI ​​functions

[0212] Optionally, the correspondence between AI models, AI functions and AI application scenarios can refer to the description in the above embodiments.

[0213] Optionally, each AI model corresponds to an ID, and each AI function also corresponds to a corresponding ID. An AI function can be a collection of AI models used for a specific function.

[0214] Optionally, before the network device 102 sends the first indication information, the terminal 101 may report the AI ​​model or AI function supported by itself through capability information or auxiliary information, so that the network device 102 can know the AI ​​model or AI function supported by the terminal 101. Through the model identification process, the terminal 101 and the network device 102 can reach a unified understanding of the performance and architecture parameters of the model. The terminal 101 can send the metadata of the terminal-side model to the network device 102, and the network device 102 can also send the metadata of the network-side model to the terminal 101. The metadata may include the performance, architecture, parameters and identification of the corresponding model.

[0215] In some embodiments, the terminal 101 receives the first indication information and may perform reasonable operations when applying the model indicated by the first indication information according to the identifier indicated by the first indication information.

[0216] In step S2104 , the terminal 101 selects a first AI model or a first AI function.

[0217] Optionally, the terminal 101 selects the first AI model or the first AI function, which may mean that the terminal decides to manage the first AI model or the first AI function, but has not yet performed a specific management operation.

[0218] Optionally, the first AI model is one of multiple AI models supported by the terminal, or the first AI function is one of multiple AI functions supported by the terminal.

[0219] Optionally, the first AI model and the first AI function may be the same as or different from the AI ​​model or AI function indicated in the first indication information.

[0220] Optionally, based on the description of the foregoing embodiment, after the terminal 101 decides to manage the first AI model or the first AI function, the management method may be a network-determined method or a terminal-determined method.

[0221] Step S2105 , the terminal 101 sends second indication information to the network device 102 .

[0222] Optionally, step S2105 is performed when the first AI model or the first AI function matches the identifier in the first indication information, that is, the first AI model or the first AI function belongs to the AI ​​model or AI function indicated or bound by the first indication information.

[0223] Optionally, step S2105 corresponds to the terminal behavior indicated by the first indication information.

[0224] Optionally, the second indication information is used to indicate: an identifier corresponding to the first AI model or the first AI function, and / or a management operation on the first AI model or the first AI function.

[0225] Optionally, when the terminal 101 supports only one management operation, the terminal 101 may not report the management operation in the second indication information, and the supported management operation will be adopted by default.

[0226] Optionally, the second indication information may also be referred to as a management indication or a management decision. For example, in a terminal decision manner, the terminal 101 may send the second indication information to the network device 102 .

[0227] In some embodiments, the management operation includes at least one of the following:

[0228] Enabling AI models or AI functions;

[0229] Disabling AI models or AI functions;

[0230] Switching of AI models or AI functions.

[0231] Optionally, the second indication information reports the management operation decided or selected by the terminal 101, and / or the identifier of the first AI model or the first AI function.

[0232] Optionally, the network device 102 receives the second indication information to obtain the identifier of the first AI model or first AI function selected by the terminal 101, and / or the management operation determined by the terminal 101 for the first AI model or first AI function.

[0233] In some embodiments, when the first AI model or the first AI function does not match the identifier in the first indication information, such as when it does not belong to the AI ​​model or function indicated by the first indication information, or when the first AI model or the first AI function is different from the model bound to the application scenario in the first indication information, the terminal 101 may not send the second indication information.

[0234] In step S2106 , the terminal 101 performs a management operation on the first AI model or the first AI function.

[0235] Optionally, this step may also be performed before step S2105.

[0236] Optionally, the management operation of the terminal 101 may be based on its own decision, such as the record in the second indication information.

[0237] Optionally, steps S2105 and S2106 correspond to the terminal behavior indicated by the first indication information.

[0238] Optionally, referring to the description of the aforementioned embodiment or the following embodiment, the management operation of the terminal 101 on the first AI model or the first AI function includes but is not limited to at least one of the following: activating or using the first AI model or the first AI function, deactivating the first AI model or the first AI function, and switching the first AI model or the first AI function.

[0239] In some embodiments, the names of information, etc. are not limited to the names described in the embodiments, and terms such as "information", "message", "signal", "signaling", "report", "configuration", "indication", "instruction", "command", "channel", "parameter", "domain", and "field" can be used interchangeably.

[0240] In some embodiments, "obtain", "get", "get", "receive", "transmit", "bidirectional transmission", "send and / or receive" can be interchangeable, and can be interpreted as receiving from other entities, obtaining from protocols, obtaining from higher layers, obtaining by self-processing, autonomous implementation, etc.

[0241] In some embodiments, terms such as "send", "transmit", "report", "download", "transmit", "bidirectional transmission", "send and / or receive" can be used interchangeably.

[0242] In some embodiments, the terms "radio", "wireless", "radio access network (RAN)", "access network (AN)", "RAN-based" and the like may be used interchangeably.

[0243] In some embodiments, terms such as "moment", "time point", "time", and "time position" can be replaced with each other, and terms such as "duration", "period", "time window", "window", and "time" can be replaced with each other.

[0244] In some embodiments, the terms "component carrier (CC)", "cell", "frequency carrier", "carrier frequency" and the like can be used interchangeably.

[0245] In some embodiments, terms such as "certain", "preset", "preset", "setting", "indicated", "a certain", "any", and "first" can be interchangeable. "Specific A", "preset A", "preset A", "setting A", "indicated A", "a certain A", "any A", and "first A" can be interpreted as A pre-specified in a protocol, etc., or as A obtained through setting, configuration, or indication, etc., or as specific A, a certain A, any A, or first A, etc., but not limited to this.

[0246] In some embodiments, the determination or judgment can be performed by a value represented by 1 bit (0 or 1), or by a true or false value (Boolean value) represented by true or false, or by comparison of numerical values ​​(for example, comparison with a predetermined value), but is not limited thereto.

[0247] In some embodiments, "not expecting to receive" can be interpreted as not receiving on time domain resources and / or frequency domain resources, or as not performing subsequent processing on the data after receiving it; "not expecting to send" can be interpreted as not sending, or as sending but not expecting the recipient to respond to the content sent.

[0248] The method involved in the embodiment of the present disclosure may include at least one of steps S2101 to S2106; for example, the method includes step S2103, or the method includes steps S2103 to S2105.

[0249] In some embodiments, at least one of steps S2101 to S2102 is optional, and one or more of these steps may be omitted or replaced in different embodiments.

[0250] In some embodiments, at least one of steps S2104 to S2106 is optional, and one or more of these steps may be omitted or replaced in different embodiments.

[0251] In some embodiments, reference may be made to other optional implementations described before or after the description corresponding to FIG. 2 a .

[0252] FIG2b is an interactive diagram illustrating a method for receiving and sending indication information according to an embodiment of the present disclosure. As shown in FIG2b , an embodiment of the present disclosure relates to a method for receiving and sending indication information, the method comprising:

[0253] Step S2201 : Terminal 101 sends auxiliary information to network device 102 .

[0254] In some embodiments, the implementation of step S2201 can refer to the optional implementation of step S2101 and will not be repeated here.

[0255] Step S2202 , the network device 102 sends configuration information to the terminal 101 .

[0256] In some embodiments, the implementation of step S2202 can refer to the optional implementation of step S2102 and will not be repeated here.

[0257] Step S2203 , the network device 102 sends first indication information to the terminal 101 .

[0258] In some embodiments, the implementation of step S2203 can refer to the optional implementation of step S2103 and will not be repeated here.

[0259] In step S2204, the terminal 101 selects a first AI model or a first AI function.

[0260] In some embodiments, the implementation of step S2204 can refer to the optional implementation of step S2104 and will not be repeated here.

[0261] Step S2205 , the terminal 101 sends a request message to the network device 102 .

[0262] Optionally, step S2205 is performed when the first AI model or the first AI function matches the identifier in the first indication information, that is, the first AI model or the first AI function belongs to the AI ​​model or AI function indicated or bound by the first indication information.

[0263] Optionally, step S2205 corresponds to the terminal behavior indicated by the first indication information.

[0264] Optionally, the request information is used to indicate an identifier corresponding to the first AI model or the first AI function, and / or a management operation requested by the terminal.

[0265] Optionally, when the terminal 101 supports only one management operation, the requested management operation may not be indicated in the request information, and the supported management operation is requested by default.

[0266] Optionally, the management operation requested by the terminal includes at least one of the following: enabling of an AI model or an AI function; disabling of an AI model or an AI function; or switching of an AI model or an AI function.

[0267] Optionally, the request information may also be referred to as a management request. For example, in a network-determined manner, the terminal 101 may send the request information to the network device 102 .

[0268] Optionally, the network device 102 receives the request information to obtain the identifier of the first AI model or first AI function requested to be managed by the terminal 101, and / or the management operation requested by the terminal 101 for the first AI model or first AI function.

[0269] In some embodiments, when the first AI model or the first AI function does not match the identifier in the first indication information, the terminal 101 may not send the request information.

[0270] Step S2206 : The network device 102 sends third indication information to the terminal 101 .

[0271] Optionally, steps S2205 and S2206 correspond to the terminal behavior indicated by the first indication information.

[0272] Optionally, the third indication information is used to indicate an identifier corresponding to the second AI model or second AI function that the terminal is allowed to manage, and / or to allow the terminal to perform management operations on the second AI model or second AI function.

[0273] Optionally, the second AI model is the same as or different from the first AI model, or the second AI function is the same as or different from the second AI function. Optionally, the allowed management operation is the same as or different from the operation requested by terminal 101. For example, network device 102 indicates, through third indication information, an indicator for activating or deactivating the second AI model or the second AI function.

[0274] Optionally, the third indication information may also be called a management indication.

[0275] Optionally, the terminal 101 receives the third indication information and determines the management behavior allowed by the network device 102. In this embodiment, the terminal 101 needs to determine the management model or function to be used based on the management indication. Optionally, the terminal 101 receives the third indication information, which is a terminal behavior determined by the terminal based on the first indication information.

[0276] In step S2207 , the terminal 101 performs a management operation on the second AI model or the second AI function.

[0277] Optionally, the management of the terminal 101 may be performed according to the instructions of the network device 102, such as executing the management operation indicated by the third indication information.

[0278] Optionally, steps S2205 to S2207 correspond to the terminal behavior indicated by the first indication information.

[0279] The method involved in the embodiment of the present disclosure may include at least one of steps S2201 to S2207; for example, the method includes step S2203, or the method includes steps S2203 to S2206.

[0280] In some embodiments, at least one of steps S2201 to S2202 is optional, and one or more of these steps may be omitted or replaced in different embodiments.

[0281] In some embodiments, at least one of steps S2204 to S2207 is optional, and one or more of these steps may be omitted or replaced in different embodiments.

[0282] In some embodiments, reference may be made to other optional implementations described before or after the description corresponding to FIG. 2 b .

[0283] FIG3a is a schematic diagram of a method for receiving and sending indication information according to an embodiment of the present disclosure. As shown in FIG3a, an embodiment of the present disclosure relates to a method for receiving and sending indication information, which is executed by terminal 101 and includes:

[0284] Step S3101, sending auxiliary information.

[0285] In some embodiments, the implementation of step S3101 can refer to the optional implementation of step S2101 and will not be repeated here.

[0286] Step S3102, obtain configuration information.

[0287] In some embodiments, the implementation of step S3102 can refer to the optional implementation of step S2102 and will not be repeated here.

[0288] Optionally, the terminal 101 may obtain configuration information from the network device 102 or other entities.

[0289] Step S3103: Obtain first indication information.

[0290] In some embodiments, the implementation of step S3103 can refer to the optional implementation of step S2103 and will not be repeated here.

[0291] Optionally, the terminal 101 may obtain the first indication information from the network device 102 or other entities.

[0292] In step S3104, when the terminal 101 selects the first AI model or the first AI function, the terminal behavior is determined based on the first indication information.

[0293] In some embodiments, the implementation of step S3104 can refer to the optional implementation of steps S2105 to S2106, which will not be repeated here.

[0294] In some embodiments, the implementation of step S3104 may refer to the optional implementation of steps S2205 to S2207, which will not be repeated here.

[0295] The method involved in the embodiment of the present disclosure may include at least one of steps S3101 to S3104.

[0296] In some embodiments, reference may be made to other optional implementations described before or after the description corresponding to FIG. 3 a .

[0297] FIG3b is a schematic diagram of a method for receiving and sending indication information according to an embodiment of the present disclosure. As shown in FIG3a, an embodiment of the present disclosure relates to a method for receiving and sending indication information, which is executed by terminal 101 and includes:

[0298] Step S3201: Obtain first indication information.

[0299] In some embodiments, the implementation of step S3201 can refer to the optional implementation of step S2103 and will not be repeated here.

[0300] In step S3202, when the terminal 101 selects the first AI model or the first AI function, the terminal 101 sends the second indication information.

[0301] In some embodiments, the implementation of step S3202 can refer to the optional implementation of steps S2104 to S2105, which will not be repeated here.

[0302] In some embodiments, reference may be made to other optional implementations described before or after the description corresponding to FIG. 3 b .

[0303] FIG3c is a schematic diagram of a method for receiving and sending indication information according to an embodiment of the present disclosure. As shown in FIG3c, an embodiment of the present disclosure relates to a method for receiving and sending indication information, which is executed by terminal 101 and includes:

[0304] Step S3301: Obtain first indication information.

[0305] In some embodiments, the implementation of step S3301 can refer to the optional implementation of step S2103 and will not be repeated here.

[0306] In step S3302, when the terminal 101 selects the first AI model or the first AI function, it sends a request message.

[0307] In some embodiments, the implementation of step S3302 can refer to the optional implementation of steps S2204 to S2205, which will not be repeated here.

[0308] Step S3303: Terminal 101 obtains third indication information.

[0309] In some embodiments, the implementation of step S3303 can refer to the optional implementation of step S2206 and will not be repeated here.

[0310] In some embodiments, reference may be made to other optional implementations described before or after the description corresponding to FIG. 3c.

[0311] FIG3 d is a schematic diagram of a method for receiving and sending indication information according to an embodiment of the present disclosure. As shown in FIG3 d , an embodiment of the present disclosure relates to a method for receiving and sending indication information, which is executed by terminal 101 and includes:

[0312] Step S3401: Receive first indication information sent by the network device 102.

[0313] In some embodiments, the implementation of step S3401 can refer to the optional implementation of step S2103 and will not be repeated here.

[0314] In some embodiments, the first indication information includes at least one of the following:

[0315] The identifier of at least one artificial intelligence (AI) model;

[0316] The identifier of at least one AI function;

[0317] The identifier of at least one AI application scenario.

[0318] Optionally, the AI ​​model, the AI ​​function, or the AI ​​application scenario satisfies at least one of the following:

[0319] The AI ​​function is associated with one or more of the AI ​​models;

[0320] The AI ​​application scenario is associated with one or more AI models;

[0321] The AI ​​application scenario is associated with one or more of the AI ​​functions. Optionally, the AI ​​application scenario includes at least one of the following:

[0322] beam management;

[0323] Beam measurement;

[0324] Channel state information CSI reporting;

[0325] Terminal positioning;

[0326] Mobility management;

[0327] Radio resource measurement.

[0328] In some embodiments, the method further comprises:

[0329] When the terminal selects a first AI model or a first AI function, the terminal determines a terminal behavior according to the first AI model or the first AI function and the first indication information; wherein the first AI model is one of multiple AI models supported by the terminal, or the first AI function is one of multiple AI functions supported by the terminal.

[0330] In some embodiments, the terminal determines the terminal behavior according to the first AI model or the first AI function and the first indication information, including:

[0331] When the first AI model or the first AI function matches the identifier in the first indication information, the terminal sends second indication information to the network device; wherein the second indication information is used to indicate: the identifier corresponding to the first AI model or the first AI function, and / or a management operation on the first AI model or the first AI function.

[0332] In some embodiments, the method further comprises:

[0333] The terminal performs the management operation indicated by the second indication information on the first AI model or the first AI function.

[0334] In some embodiments, the terminal determines the terminal behavior according to the first AI model or the first AI function and the first indication information, including:

[0335] When the first AI model or the first AI function matches the identifier in the first indication information, the terminal sends a request message to the network device; wherein the request message is used to indicate the identifier corresponding to the first AI model or the first AI function, and / or the management operation requested by the terminal;

[0336] receiving third indication information sent by the network device, where the third indication information is used to indicate an identifier corresponding to a second AI model or a second AI function that the terminal is allowed to manage, and / or to allow the terminal to perform a management operation on the second AI model or the second AI function;

[0337] The second AI model is the same as or different from the first AI model, or the second AI function is the same as or different from the first AI function.

[0338] In some embodiments, the method further comprises:

[0339] The terminal performs the management operation indicated by the third indication information on the second AI model or the second AI function.

[0340] In some embodiments, the management operation includes at least one of the following:

[0341] Enabling AI models or AI functions;

[0342] Disabling AI models or AI functions;

[0343] Switching of AI models or AI functions.

[0344] In some embodiments, the method further comprises:

[0345] Send auxiliary information to the network device, including the correspondence between AI models, AI functions, and AI application scenarios; or,

[0346] Receive configuration information sent by the network device, where the configuration information includes the corresponding relationship.

[0347] In some embodiments, reference may be made to other optional implementations described before or after the description corresponding to FIG. 3 d .

[0348] FIG4a is a schematic diagram of a method for receiving and sending indication information according to an embodiment of the present disclosure. As shown in FIG4a, an embodiment of the present disclosure relates to a method for receiving and sending indication information, which is executed by a network device 102 and includes:

[0349] Step S4101, obtain auxiliary information.

[0350] In some embodiments, the implementation of step S4101 can refer to the optional implementation of step S2101 and will not be repeated here.

[0351] Step S4102, sending configuration information.

[0352] In some embodiments, the implementation of step S4102 can refer to the optional implementation of step S2102 and will not be repeated here.

[0353] Optionally, the network device 102 may send configuration information to the terminal 101 or other entities.

[0354] Step S4103: Send first indication information.

[0355] In some embodiments, the implementation of step S4103 can refer to the optional implementation of step S2103 and will not be repeated here.

[0356] Optionally, the network device 102 may send first indication information to the terminal 101 or other entities.

[0357] Step S4104 : determining corresponding actions based on different information sent by the terminal 101 .

[0358] In some embodiments, the implementation of step S4104 can refer to the optional implementation of steps S2105 to S2106, which will not be repeated here.

[0359] In some embodiments, the implementation of step S4104 may refer to the optional implementation of steps S2205 to S2207, which will not be repeated here.

[0360] The method involved in the embodiment of the present disclosure may include at least one of steps S4101 to S4104.

[0361] In some embodiments, reference may be made to other optional implementations described before or after the description corresponding to FIG. 4 a .

[0362] FIG4b is a schematic diagram of a method for receiving and sending indication information according to an embodiment of the present disclosure. As shown in FIG4b, an embodiment of the present disclosure relates to a method for receiving and sending indication information, which is performed by a network device 102 and includes:

[0363] Step S4201: Send first indication information.

[0364] In some embodiments, the implementation of step S4201 can refer to the optional implementation of step S2103 and will not be repeated here.

[0365] Step S4202: Receive second indication information.

[0366] In some embodiments, the implementation of step S4202 can refer to the optional implementation of steps S2104 to S2105, which will not be repeated here.

[0367] In some embodiments, reference may be made to other optional implementations described before or after the description corresponding to FIG. 4 b .

[0368] FIG4c is a schematic diagram of a method for receiving and sending indication information according to an embodiment of the present disclosure. As shown in FIG4c, an embodiment of the present disclosure relates to a method for receiving and sending indication information, which is performed by the network device 102 and includes:

[0369] Step S4301: Send first indication information.

[0370] In some embodiments, the implementation of step S4301 can refer to the optional implementation of step S2103 and will not be repeated here.

[0371] Step S4302, receiving request information.

[0372] In some embodiments, the implementation of step S4302 can refer to the optional implementation of steps S2204 to S2205, which will not be repeated here.

[0373] Step S4303: Send third indication information.

[0374] In some embodiments, the implementation of step S4303 can refer to the optional implementation of step S2206 and will not be repeated here.

[0375] In some embodiments, reference may be made to other optional implementations described before or after the description corresponding to FIG. 4c.

[0376] FIG4d is a schematic diagram of a method for receiving and sending indication information according to an embodiment of the present disclosure. As shown in FIG4d , an embodiment of the present disclosure relates to a method for receiving and sending indication information, which is performed by a network device 102 and includes:

[0377] Step S4401: Send first indication information to terminal 101.

[0378] In some embodiments, the implementation of step S4401 can refer to the optional implementation of step S2103 and will not be repeated here.

[0379] In some embodiments, the first indication information includes at least one of the following:

[0380] The identifier of at least one AI model;

[0381] The identifier of at least one AI function;

[0382] The identifier of at least one AI application scenario.

[0383] Optionally, the AI ​​model, the AI ​​function, or the AI ​​application scenario satisfies at least one of the following:

[0384] The AI ​​function is associated with one or more of the AI ​​models;

[0385] The AI ​​application scenario is associated with one or more AI models;

[0386] The AI ​​application scenario is associated with one or more of the AI ​​functions

[0387] Optionally, the AI ​​application scenario includes at least one of the following:

[0388] beam management;

[0389] Beam measurement;

[0390] CSI reporting;

[0391] Terminal positioning;

[0392] Mobility management;

[0393] Radio resource measurement.

[0394] In some embodiments, the method further comprises:

[0395] receiving second indication information sent by the terminal, where the second indication information is sent when the first AI model or the first AI function matches the identifier in the first indication information; the second indication information is used to indicate: the identifier corresponding to the first AI model or the first AI function, and / or a management operation on the first AI model or the first AI function;

[0396] The first AI model is one of multiple AI models supported by the terminal, or the first AI function is one of multiple AI functions supported by the terminal.

[0397] In some embodiments, the method further comprises:

[0398] receiving a request message sent by a terminal, where the request message is sent when the first AI model or the first AI function matches the identifier in the first indication information, and the request message is used to indicate the identifier corresponding to the first AI model or the first AI function, and / or the management operation requested by the terminal;

[0399] Sending third indication information to the terminal, where the third indication information is used to indicate an identifier corresponding to the second AI model or second AI function that the terminal is allowed to manage, and / or allowing the terminal to perform management operations on the second AI model or second AI function;

[0400] The second AI model is the same as or different from the first AI model, or the second AI function is the same as or different from the first AI function.

[0401] In some embodiments, the management operation includes at least one of the following:

[0402] Enabling AI models or AI functions;

[0403] Disabling AI models or AI functions;

[0404] Switching of AI models or AI functions.

[0405] In some embodiments, the method further comprises:

[0406] Receive auxiliary information sent by the terminal, where the auxiliary information includes the correspondence between the AI ​​model, AI function, and AI application scenario; or

[0407] Send configuration information to the terminal, where the configuration information includes the corresponding relationship.

[0408] In some embodiments, reference may be made to other optional implementations described before or after the description corresponding to FIG. 4 d .

[0409] The present disclosure provides an AI management method that enables UE to reasonably manage AI models or functions. To facilitate understanding of the present disclosure, some specific examples are listed below:

[0410] Example 1:

[0411] The UE receives a first indication sent by the network. When the UE decides to manage the first AI model or function, the UE determines how to determine the AI ​​model or function to use according to the first indication.

[0412] Optionally, the UE may correspond to the terminal 101 in the aforementioned embodiment, and the network may correspond to the network device 102 in the aforementioned embodiment.

[0413] Optionally, the first indication may correspond to the first indication information of the aforementioned embodiment.

[0414] As an example, management includes activation, deactivation, switching, etc. of models or functions.

[0415] Example 2:

[0416] Based on Example 1, the first indication may be a model or function identifier.

[0417] Example 3:

[0418] Based on Example 1 or Example 2, if the model is the model determined in the first indication, the UE uses the first model or function and sends a management indication to the network, indicating the first model or function and the management decision.

[0419] As an embodiment, the first indication may indicate one or more model identifiers. The UE determines whether to send the management indication according to whether the managed model matches the indicated model.

[0420] As an embodiment, the first indication may indicate one or more functions or application scenarios, each of which is bound to one or more models. The UE determines whether to send the management indication based on whether the managed model matches the bound model.

[0421] Optionally, the correspondence between the functions and the models may be configured by the network or determined by the UE itself.

[0422] Example 4:

[0423] Based on Example 1 or Example 2, if the model is the model determined in the first indication, the UE sends a management request to the network, where the request indicates the first model or function and the management decision.

[0424] As an embodiment, the first indication may indicate one or more model identifiers. The UE determines whether to send a management request according to whether the managed model matches the indicated model.

[0425] As an embodiment, the first indication may indicate one or more functions or application scenarios, each function or application scenario being bound to one or more models. The UE determines whether to send a management request based on whether the managed model matches the bound model.

[0426] Optionally, the correspondence between the functions and the models may be configured by the network or determined by the UE itself.

[0427] Example 5:

[0428] Based on Example 4, after receiving the management instruction sent by the network, the model or function to be used is determined according to the management instruction.

[0429] As an example, the management instruction includes an activated or deactivated model or function identifier.

[0430] Example 6:

[0431] Based on Example 1, the UE reports the correspondence between the model and the function or application scenario to the network.

[0432] The embodiments of the present disclosure further provide an apparatus for implementing any of the above methods. For example, an apparatus is provided, comprising units or modules for implementing each step performed by a terminal in any of the above methods. For another example, another apparatus is provided, comprising units or modules for implementing each step performed by a network device (e.g., an access network device, a core network function node, a core network device, etc.) in any of the above methods.

[0433] It should be understood that the division of the various units or modules in the above device is merely a division of logical functions. In actual implementation, they may be fully or partially integrated into a physical entity, or they may be physically separated. In addition, the units or modules in the device may be implemented in the form of a processor calling software: for example, the device includes a processor, the processor is connected to a memory, and the memory stores instructions. The processor calls the instructions stored in the memory to implement any of the above methods or implement the functions of the various units or modules of the above device, wherein the processor is, for example, a general-purpose processor, such as a central processing unit (CPU) or a microprocessor, and the memory is a memory within the device or a memory outside the device. Alternatively, the units or modules in the device can be implemented in the form of hardware circuits, and the functions of some or all of the units or modules can be realized by designing the hardware circuits. The above-mentioned hardware circuits can be understood as one or more processors; for example, in one implementation, the above-mentioned hardware circuit is an application-specific integrated circuit (ASIC), which realizes the functions of some or all of the above units or modules by designing the logical relationship of the components in the circuit; for example, in another implementation, the above-mentioned hardware circuit can be realized by a programmable logic device (PLD). Taking a field programmable gate array (FPGA) as an example, it can include a large number of logic gate circuits, and the connection relationship between the logic gate circuits is configured by configuring the configuration file, thereby realizing the functions of some or all of the above units or modules. All units or modules of the above devices can be realized in the form of software called by the processor, or in the form of hardware circuits, or in part by the form of software called by the processor, and the rest by hardware circuits.

[0434] In the embodiments of the present disclosure, the processor is a circuit with signal processing capabilities. In one implementation, the processor can be a circuit with instruction reading and execution capabilities, such as a central processing unit (CPU), a microprocessor, a graphics processing unit (GPU) (which can be understood as a microprocessor), or a digital signal processor (DSP). In another implementation, the processor can implement certain functions through the logical relationship of the hardware circuit. The logical relationship of the above-mentioned hardware circuit is fixed or reconfigurable. For example, the processor is a hardware circuit implemented by an application-specific integrated circuit (ASIC) or a programmable logic device (PLD), such as an FPGA. In a reconfigurable hardware circuit, the process of the processor loading a configuration document and implementing the hardware circuit configuration can be understood as the process of the processor loading instructions to implement the functions of some or all of the above units or modules. In addition, it can also be a hardware circuit designed for artificial intelligence, which can be understood as an ASIC, such as a neural network processing unit (NPU), a tensor processing unit (TPU), a deep learning processing unit (DPU), etc.

[0435] Figure 5a is a schematic diagram of the structure of a terminal according to an embodiment of the present disclosure. As shown in Figure 5a, terminal 5100 may include at least one of a transceiver module 5101 and a processing module 5102. In some embodiments, transceiver module 5101 is configured to receive first indication information sent by a network device, the first indication information being used to instruct the terminal on the terminal's behavior in managing an AI model or AI function.

[0436] Optionally, the transceiver module 5101 is configured to execute at least one of the communication steps of sending and / or receiving performed by the terminal 101 in any of the above methods, which are not described in detail here. Optionally, the processing module 5102 is configured to execute at least one of the other steps performed by the terminal 101 in any of the above methods, which are not described in detail here.

[0437] Figure 5b is a schematic diagram of the structure of a terminal according to an embodiment of the present disclosure. As shown in Figure 5b, network device 5200 may include at least one of a transceiver module 5201 and a processing module 5202. In some embodiments, transceiver module 5201 is configured to send first indication information to the terminal, instructing the terminal on the terminal behavior of managing an AI model or AI function.

[0438] Optionally, the transceiver module 5201 is configured to execute at least one of the communication steps of sending and / or receiving performed by the network device 102 in any of the above methods, which are not described in detail here. Optionally, the processing module 5202 is configured to execute at least one of the other steps performed by the network device 102 in any of the above methods, which are not described in detail here.

[0439] In some embodiments, the transceiver module may include a transmitting module and / or a receiving module, and the transmitting module and the receiving module may be separate or integrated. Optionally, the transceiver module may be interchangeable with the transceiver.

[0440] In some embodiments, the processing module can be a single module or can include multiple submodules. Optionally, the multiple submodules respectively execute all or part of the steps required to be executed by the processing module. Optionally, the processing module can be interchangeable with the processor.

[0441] Figure 6a is a schematic diagram of the structure of a communication device 6100 proposed in an embodiment of the present disclosure. Communication device 6100 can be a network device (e.g., an access network device, a core network device, etc.), a terminal (e.g., a user equipment, etc.), a chip, a chip system, or a processor that supports a network device implementing any of the above methods, or a chip, a chip system, or a processor that supports a terminal implementing any of the above methods. Communication device 6100 can be used to implement the methods described in the above method embodiments. For details, please refer to the description of the above method embodiments.

[0442] As shown in Figure 6a, the communication device 6100 includes one or more processors 6101. The processor 6101 can be a general-purpose processor or a dedicated processor, for example, a baseband processor or a central processing unit. The baseband processor can be used to process the communication protocol and communication data, and the central processing unit can be used to control the communication device (such as a base station, a baseband chip, a terminal device, a terminal device chip, a DU or a CU, etc.), execute programs, and process program data. Optionally, the communication device 6100 is used to perform any of the above methods. Optionally, one or more processors 6101 are used to call instructions to enable the communication device 6100 to perform any of the above methods.

[0443] In some embodiments, the communication device 6100 further includes one or more transceivers 6102. When the communication device 6100 includes one or more transceivers 6102, the transceiver 6102 performs at least one of the communication steps, such as sending and / or receiving, in the above-described method, and the processor 6101 performs at least one of the other steps. In an optional embodiment, the transceiver may include a receiver and / or a transmitter, and the receiver and transmitter may be separate or integrated. Optionally, the terms transceiver, transceiver unit, transceiver, transceiver circuit, interface circuit, and interface may be used interchangeably; the terms transmitter, transmitting unit, transmitter, and transmitting circuit may be used interchangeably; and the terms receiver, receiving unit, receiver, and receiving circuit may be used interchangeably.

[0444] In some embodiments, the communication device 6100 further includes one or more memories 6103 for storing data. Alternatively, all or part of the memories 6103 may be located outside the communication device 6100. In alternative embodiments, the communication device 6100 may include one or more interface circuits 6104. Optionally, the interface circuits 6104 are connected to the memories 6103 and may be configured to receive data from the memories 6103 or other devices, or to send data to the memories 6103 or other devices. For example, the interface circuits 6104 may read data stored in the memories 6103 and send the data to the processor 6101.

[0445] The communication device 6100 described in the above embodiment may be a network device or a terminal, but the scope of the communication device 6100 described in the present disclosure is not limited thereto, and the structure of the communication device 6100 may not be limited by FIG. 6a. The communication device may be an independent device or may be part of a larger device. For example, the communication device may be: 1) an independent integrated circuit IC, or a chip, or a chip system or subsystem; (2) a collection of one or more ICs, optionally, the above IC collection may also include a storage component for storing data or programs; (3) an ASIC, such as a modem; (4) a module that can be embedded in other devices; (5) a receiver, a terminal device, an intelligent terminal device, a cellular phone, a wireless device, a handheld device, a mobile unit, an in-vehicle device, a network device, a cloud device, an artificial intelligence device, etc.; (6) others, etc.

[0446] FIG6b is a schematic diagram of the structure of a chip 6200 according to an embodiment of the present disclosure. If the communication device 6100 can be a chip or a chip system, reference can be made to the schematic diagram of the structure of the chip 6200 shown in FIG6b , but the present disclosure is not limited thereto.

[0447] The chip 6200 includes one or more processors 6201. The chip 6200 is configured to execute any of the above methods.

[0448] In some embodiments, chip 6200 further includes one or more interface circuits 6202. Terms such as interface circuit, interface, and transceiver pins may be used interchangeably. In some embodiments, chip 6200 further includes one or more memories 6203 for storing data. Alternatively, all or part of memory 6203 may be located external to chip 6200. Optionally, interface circuit 6202 is connected to memory 6203 and may be used to receive data from memory 6203 or other devices, or may be used to send data to memory 6203 or other devices. For example, interface circuit 6202 may read data stored in memory 6203 and send the data to processor 6201.

[0449] In some embodiments, the interface circuit 6202 performs at least one of the communication steps, such as sending and / or receiving, in the above-described method. For example, the interface circuit 6202 performing the communication steps, such as sending and / or receiving, in the above-described method means that the interface circuit 6202 performs data exchange between the processor 6201, the chip 6200, the memory 6203, or the transceiver device. In some embodiments, the processor 6201 performs at least one of the other steps.

[0450] The modules and / or devices described in various embodiments, such as virtual devices, physical devices, and chips, can be arbitrarily combined or separated according to circumstances. Optionally, some or all steps can also be performed collaboratively by multiple modules and / or devices, which is not limited here.

[0451] The present disclosure also proposes a storage medium having instructions stored thereon. When the instructions are executed on the communication device 6100, the communication device 6100 executes any of the above methods. Optionally, the storage medium is an electronic storage medium. Optionally, the storage medium is a computer-readable storage medium, but is not limited thereto and may also be a storage medium readable by other devices. Optionally, the storage medium may be a non-transitory storage medium, but is not limited thereto and may also be a temporary storage medium.

[0452] The present disclosure also provides a program product, which, when executed by the communication device 6100, enables the communication device 6100 to perform any of the above methods. Optionally, the program product is a computer program product.

[0453] The present disclosure also proposes a computer program, which, when executed on a computer, causes the computer to perform any one of the above methods. Industrial Applicability

[0454] By receiving the first indication information, the terminal learns the UE behavior indicated by the network device, so that it can perform adaptive operations during the process of the terminal managing the AI ​​model or AI function, thereby improving the rationality of the terminal's management of the AI ​​model or AI function in consultation with the network device.

Claims

1. A method for receiving indication information, executed by a terminal, the method comprising: Receiving first indication information sent by a network device, the first indication information being used to indicate terminal behavior for the terminal to manage an artificial intelligence (AI) model or an AI function.

2. The method according to claim 1, wherein The first indication information includes at least one of the following: Identifiers of at least one AI model; Identifiers of at least one AI function; Identifiers of at least one AI application scenario.

3. The method according to claim 2, wherein, Among the AI model, the AI function, or the AI application scenario, at least one of the following is satisfied: The AI function is associated with one or more of the AI models; The AI application scenario is associated with one or more of the AI models; The AI application scenario is associated with one or more of the AI functions.

4. The method according to claim 2, wherein, The AI application scenario includes at least one of the following: Beam management; Beam measurement; Channel state information (CSI) reporting; Terminal positioning; Mobility management; Wireless resource measurement.

5. The method according to any one of claims 1 to 4, wherein, The method further comprises: When the terminal selects a first AI model or a first AI function, the terminal determines the terminal behavior according to the first AI model or the first AI function and the first indication information; wherein, the first AI model is one of multiple AI models supported by the terminal, or the first AI function is one of multiple AI functions supported by the terminal.

6. The method according to claim 5, wherein, The terminal determining the terminal behavior according to the first AI model or the first AI function and the first indication information includes: When the first AI model or the first AI function matches the identifier in the first indication information, the terminal sends second indication information to the network device; wherein, the second indication information is used to indicate: the identifier corresponding to the first AI model or the first AI function, and / or the management operation on the first AI model or the first AI function.

7. The method according to claim 6, wherein, The method further comprises: The terminal performs the management operation indicated by the second indication information on the first AI model or the first AI function.

8. The method according to claim 5, wherein The terminal determining the terminal behavior according to the first AI model or the first AI function and the first indication information includes: When the first AI model or the first AI function matches the identifier in the first indication information, the terminal sends request information to the network device; wherein, the request information is used to indicate the identifier corresponding to the first AI model or the first AI function, and / or the management operation requested by the terminal; Receiving third indication information sent by the network device, the third indication information being used to indicate the identifier corresponding to a second AI model or a second AI function allowed for the terminal to manage, and / or the management operation allowed for the terminal to perform on the second AI model or the second AI function; Wherein, the second AI model may be the same as or different from the first AI model, or the second AI function may be the same as or different from the first AI function.

9. The method according to claim 8, wherein, The method further comprises: The terminal performs the management operation indicated by the third indication information on the second AI model or the second AI function.

10. The method according to any one of claims 6 to 9, wherein, The management operation includes at least one of the following: Enabling of an AI model or AI function; Disabling of an AI model or AI function; Switching of an AI model or AI function.

11. The method according to any one of claims 1 to 4, wherein, The method further includes: Sending auxiliary information to the network device, where the auxiliary information includes the correspondence between the AI model, the AI function, and the AI application scenario; or, Receiving configuration information sent by the network device, where the configuration information includes the correspondence.

12. A method for sending indication information, which is executed by a network device, and the method includes: Sending first indication information to a terminal, where the first indication information is used to indicate the terminal behavior of the terminal for managing the AI model or AI function.

13. The method according to claim 12, wherein, The first indication information includes at least one of the following: Identifiers of at least one AI model; Identifiers of at least one AI function; Identifiers of at least one AI application scenario.

14. The method according to claim 13, wherein, At least one of the following is satisfied among the AI model, the AI function, or the AI application scenario: The AI function is associated with one or more of the AI models; The AI application scenario is associated with one or more of the AI models; The AI application scenario is associated with one or more of the AI functions.

15. The method according to claim 13, wherein, The AI application scenario includes at least one of the following: Beam management; Beam measurement; CSI reporting; Terminal positioning; Mobility management; Wireless resource measurement.

16. The method according to any one of claims 12 to 15, wherein, The method further includes: Receiving second indication information sent by the terminal, where the second indication information is sent when the first AI model or the first AI function matches the identifier in the first indication information; the second indication information is used to indicate: the identifier corresponding to the first AI model or the first AI function, and / or the management operation for the first AI model or the first AI function; Wherein, the first AI model is one of the multiple AI models supported by the terminal, or the first AI function is one of the multiple AI functions supported by the terminal.

17. The method according to any one of claims 12 to 15, wherein, The method further includes: Receiving request information sent by the terminal, where the request information is sent when the first AI model or the first AI function matches the identifier in the first indication information, and the request information is used to indicate the identifier corresponding to the first AI model or the first AI function, and / or the management operation requested by the terminal; Sending third indication information to the terminal, where the third indication information is used to indicate the identifier corresponding to the second AI model or the second AI function allowed for the terminal to manage, and / or the management operation allowed for the terminal to perform on the second AI model or the second AI function; Wherein, the second AI model is the same as or different from the first AI model, or the second AI function is the same as or different from the second AI function.

18. The method according to any one of claims 16 to 17, wherein, The management operation includes at least one of the following: Enabling of an AI model or AI function; Disabling of an AI model or AI function; Switching of an AI model or AI function.

19. The method according to any one of claims 12 to 15, wherein, The method further includes: Receiving auxiliary information sent by the terminal, where the auxiliary information includes the correspondence between the AI model, the AI function, and the AI application scenario; or, Sending configuration information to the terminal, where the configuration information includes the correspondence.

20. A terminal, comprising: a transceiver module, configured to receive first indication information sent by a network device, where the first indication information is used to indicate terminal behavior for the terminal to manage an AI model or an AI function.

21. A network device, comprising: a transceiver module, configured to send first indication information to a terminal, where the first indication information is used to indicate terminal behavior for the terminal to manage an AI model or an AI function.

22. A terminal, comprising: one or more processors; wherein, the terminal is configured to execute the method according to any one of claims 1 to 11.

23. A network device, comprising: one or more processors; wherein, the network device is configured to execute the method according to any one of claims 12 to 19.

24. A communication system, comprising a terminal and a network device, wherein, the terminal is configured to implement the method according to any one of claims 1 to 11; the network device is configured to implement the method according to any one of claims 12 to 19.

25. A storage medium, storing instructions, wherein, when the instructions run on a communication device, the communication device is caused to execute the method according to any one of claims 1 to 11 or 12 to 19.

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