Processing method and device

Abstract

The embodiment of the invention discloses a processing method and device. The method comprises: a network device receiving first information sent by a terminal, the first information being used for indicating an operation state of the terminal; and according to the running state of the terminal, the network device executes a corresponding artificial intelligence AI operation. By implementing the embodiment of the invention, the network side can be assisted to manage the AI model of the terminal through the terminal local AI operation environment reported by the terminal, so that the performance of the terminal can be prevented from being influenced by the reasons of terminal resource shortage, low power and the like, and the network side can conveniently carry out AI related processing.

Description

A processing method and device thereof Technical Field

[0001] The present disclosure relates to the field of communication technology, and in particular to a processing method and a device thereof. Background Art

[0002] In recent years, artificial intelligence (AI) technology has achieved continuous breakthroughs in numerous fields. The continued development of fields such as intelligent voice and computer vision has not only brought a rich variety of applications to smart terminals, but has also found widespread application in education, transportation, home living, healthcare, retail, security, and other fields. This has brought convenience to people's lives while also promoting industrial upgrading across various industries. AI technology is also rapidly interpenetrating with other disciplines, integrating knowledge from different disciplines while also providing new directions and methods for their development.

[0003] Related technologies incorporate AI into wireless air interfaces, leveraging it to enhance wireless air interface transmission. However, when AI models are deployed on the terminal side, they require storage and computing resources to run them. Running AI models on the terminal also consumes power or releases heat, causing overheating and impacting performance.

[0004] Summary of the Invention

[0005] The embodiments of the present disclosure provide a processing method and a device thereof.

[0006] According to a first aspect of an embodiment of the present disclosure, a processing method is proposed, including:

[0007] The network device receives first information sent by the terminal, where the first information is used to indicate an operating state of the terminal;

[0008] According to the operating status of the terminal, the network device performs corresponding artificial intelligence (AI) operations.

[0009] According to a second aspect of the embodiments of the present disclosure, a processing method is proposed, including:

[0010] The terminal sends first information to the network device, where the first information is used to indicate the operating status of the terminal, wherein the first information is used by the network device to perform corresponding artificial intelligence (AI) operations according to the operating status of the terminal.

[0011] According to a third aspect of an embodiment of the present disclosure, a first communication device is provided, including:

[0012] a transceiver module, configured to receive first information sent by a terminal, where the first information is used to indicate an operating status of the terminal;

[0013] A processing module is used to perform corresponding artificial intelligence (AI) operations according to the operating status of the terminal.

[0014] According to a fourth aspect of an embodiment of the present disclosure, a second communication device is provided, including:

[0015] A transceiver module is used to send first information to a network device, where the first information is used to indicate the operating status of the terminal, wherein the first information is used by the network device to perform corresponding artificial intelligence (AI) operations according to the operating status of the terminal.

[0016] According to a fifth aspect of an embodiment of the present disclosure, a communication system is provided, including:

[0017] A network device configured to perform an optional implementation of the first aspect;

[0018] The terminal is configured to execute the optional implementation of the aforementioned second aspect.

[0019] According to a sixth aspect of an embodiment of the present disclosure, a communication device is provided, including: one or more processors;

[0020] The processor is used to call instructions to enable the communication device to execute the optional implementation of the first and second aspects mentioned above.

[0021] According to a seventh aspect of an embodiment of the present disclosure, a storage medium is proposed, which stores instructions. When the instructions are executed on a communication device, the communication device executes optional implementation methods of the aforementioned first and second aspects.

[0022] According to the technical solution disclosed in the present invention, the terminal local AI operating environment reported by the terminal can assist the network side in managing the terminal's AI model, thereby avoiding the impact of terminal side performance due to terminal resource shortages, low power, etc., thereby facilitating the network side to perform AI-related processing. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] 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.

[0024] FIG1 is a schematic diagram of the architecture of a communication system provided by an embodiment of the present disclosure;

[0025] FIG2A is an interactive schematic diagram illustrating a processing method according to an embodiment of the present disclosure;

[0026] FIG2B is an interactive schematic diagram illustrating a processing method according to an embodiment of the present disclosure;

[0027] FIG2C is an interactive schematic diagram illustrating a processing method according to an embodiment of the present disclosure;

[0028] FIG3A is a schematic flow chart of a processing method according to an embodiment of the present disclosure;

[0029] FIG3B is a flow chart of a processing method according to an embodiment of the present disclosure;

[0030] FIG3C is a flow chart of a processing method according to an embodiment of the present disclosure;

[0031] FIG3D is a schematic flow chart of a processing method according to an embodiment of the present disclosure;

[0032] FIG4A is a schematic flow chart showing a processing method according to an embodiment of the present disclosure;

[0033] FIG5 is an interactive schematic diagram of the processing method proposed in an embodiment of the present disclosure;

[0034] FIG6A is a schematic diagram of the structure of a network device proposed in an embodiment of the present disclosure;

[0035] FIG6B is a schematic structural diagram of a terminal proposed in an embodiment of the present disclosure;

[0036] FIG7A is a schematic structural diagram of a communication device 7100 proposed in an embodiment of the present disclosure;

[0037] FIG7B is a schematic structural diagram of a chip 7200 according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0038] The embodiments of the present disclosure provide a processing method and a device thereof.

[0039] In a first aspect, an embodiment of the present disclosure provides a processing method, including:

[0040] The network device receives first information sent by the terminal, where the first information is used to indicate an operating state of the terminal;

[0041] According to the operating status of the terminal, the network device performs corresponding artificial intelligence (AI) operations.

[0042] In the above embodiment, the terminal local AI operating environment reported by the terminal can assist the network side in managing the terminal's AI model, thereby avoiding the impact of terminal side performance due to terminal resource shortages, low power, etc., thereby facilitating the network side to perform AI-related processing.

[0043] In conjunction with some embodiments of the first aspect, in some embodiments, the operating state includes at least one of the following:

[0044] Computing resource status;

[0045] Storage resource status;

[0046] Battery status;

[0047] Fever state.

[0048] In conjunction with some embodiments of the first aspect, in some embodiments, the first information indicates that a first feature occurs in the operating state of the terminal, and the first feature includes at least one of the following:

[0049] The storage resource is less than or equal to a first storage resource threshold;

[0050] The computing resource is less than or equal to a first computing resource threshold;

[0051] The battery level is less than or equal to a first battery level threshold;

[0052] The terminal is overheated.

[0053] In conjunction with some embodiments of the first aspect, in some embodiments, the network device performing the corresponding artificial intelligence (AI) operation includes at least one of the following:

[0054] The network device pauses or shuts down the transmission of the AI ​​model;

[0055] The network device does not activate the new AI model;

[0056] The network device sends second information to the terminal, where the second information includes first operation cycle configuration information of the AI ​​model, and / or the second information is used to instruct the terminal to perform at least one of the following actions: pausing or disabling reception of the AI ​​model, disabling at least one AI model in the terminal, and disabling the first AI model;

[0057] Among them, the operation cycle included in the first operation cycle configuration information is greater than the first operation cycle, the first operation cycle is the operation cycle associated with the AI ​​model and / or AI function before the network device receives the first information and the first feature indicated by the first information includes overheating of the terminal, and the first AI model is an AI model in the terminal whose computational complexity meets the first condition.

[0058] In conjunction with some embodiments of the first aspect, in some embodiments, the network device performing a corresponding artificial intelligence (AI) operation based on the operating status of the terminal includes:

[0059] The first feature indicated by the first information includes that when the storage resource is less than or equal to a first storage resource threshold, the network device suspends or shuts down the sending of the AI ​​model.

[0060] In conjunction with some embodiments of the first aspect, in some embodiments, the network device performing a corresponding artificial intelligence (AI) operation based on the operating status of the terminal includes:

[0061] The first feature indicated by the first information includes sending second information to the terminal when the computing resource is less than or equal to a first computing resource threshold, and the second information is used to instruct the terminal to shut down at least one AI model in the terminal.

[0062] In conjunction with some embodiments of the first aspect, in some embodiments, the network device performing a corresponding artificial intelligence (AI) operation based on the operating status of the terminal includes:

[0063] The first feature indicated by the first information includes not activating a new AI model when the power level is less than or equal to a first power threshold, and / or sending second information to the terminal; the second information is used to instruct the terminal to turn off the first AI model.

[0064] In conjunction with some embodiments of the first aspect, in some embodiments, the network device performing a corresponding artificial intelligence (AI) operation based on the operating status of the terminal includes:

[0065] The first feature indicated by the first information includes sending second information to the terminal when the terminal is overheated, and the second information includes the first operation cycle configuration information of the AI ​​model.

[0066] In conjunction with some embodiments of the first aspect, in some embodiments, the first information indicates that a second feature occurs in the operating state of the terminal, and the second feature includes at least one of the following:

[0067] The storage resource is greater than or equal to a second storage resource threshold;

[0068] The computing resource is greater than or equal to a second computing resource threshold;

[0069] The battery level is greater than or equal to a second battery level threshold;

[0070] The terminal is not overheating.

[0071] In conjunction with some embodiments of the first aspect, in some embodiments, the network device performing the corresponding artificial intelligence (AI) operation includes at least one of the following:

[0072] The network device enables or reconfigures the sending of the AI ​​model;

[0073] The network device activates the new AI model;

[0074] The network device sends second information to the terminal, where the second information is used to instruct the terminal to perform at least one of the following actions: activating at least one AI model in the terminal, activating the first AI model, and restoring the operation cycle of the AI ​​model to the first operation cycle.

[0075] In conjunction with some embodiments of the first aspect, in some embodiments, processing the artificial intelligence (AI) model and / or AI function of the terminal according to the operating state of the terminal includes:

[0076] The second feature indicated by the first information includes that when the storage resource is greater than or equal to a second storage resource threshold, the network device starts or reconfigures the sending of the AI ​​model.

[0077] In conjunction with some embodiments of the first aspect, in some embodiments, the network device performing a corresponding artificial intelligence (AI) operation based on the operating status of the terminal includes:

[0078] The second feature indicated by the first information includes sending second information to the terminal when the computing resource is greater than or equal to a second computing resource threshold, and the second information is used to instruct the terminal to activate at least one AI model in the terminal.

[0079] In conjunction with some embodiments of the first aspect, in some embodiments, the network device performing a corresponding artificial intelligence (AI) operation based on the operating status of the terminal includes:

[0080] The second feature indicated by the first information includes activating a new AI model when the power level is greater than or equal to a second power level threshold, and / or sending second information to the terminal; the second information is used to instruct the terminal to activate the first AI model.

[0081] In conjunction with some embodiments of the first aspect, in some embodiments, the network device performing a corresponding artificial intelligence (AI) operation based on the operating status of the terminal includes:

[0082] The second feature indicated by the first information includes sending second information to the terminal when the terminal is not overheating, and the second information is used to instruct the terminal to restore the operation cycle of the AI ​​model to the first operation cycle.

[0083] In conjunction with some embodiments of the first aspect, in some embodiments, the operating state includes at least one of the following:

[0084] Not suitable for AI reasoning;

[0085] The need to reduce the number of activated AI models;

[0086] The frequency of AI model execution needs to be reduced;

[0087] The activated AI model can be increased;

[0088] Not suitable for receiving AI model transmissions;

[0089] Suitable for receiving AI model transmissions.

[0090] In conjunction with some embodiments of the first aspect, in some embodiments, the network device performing a corresponding artificial intelligence (AI) operation based on the operating status of the terminal includes:

[0091] When the first information indicates that the AI ​​model activated by the terminal is not suitable for AI reasoning, the AI ​​model activated by the terminal is closed.

[0092] In conjunction with some embodiments of the first aspect, in some embodiments, the network device performing a corresponding artificial intelligence (AI) operation based on the operating status of the terminal includes:

[0093] When the first information indicates that the activated AI model needs to be reduced, second information is sent to the terminal, and the second information instructs the terminal to shut down at least one AI model in the terminal.

[0094] In conjunction with some embodiments of the first aspect, in some embodiments, the network device performing a corresponding artificial intelligence (AI) operation based on the operating status of the terminal includes:

[0095] When the first information indicates that the frequency of execution of the AI ​​model needs to be reduced, second information is sent to the terminal, where the second information includes configuration information of the operation frequency of the AI ​​model.

[0096] In conjunction with some embodiments of the first aspect, in some embodiments, the network device performing a corresponding artificial intelligence (AI) operation based on the operating status of the terminal includes:

[0097] When the first information indicates the AI ​​model that can be added for activation, one or more AI models are activated according to business needs, and / or second information is sent to the terminal, where the second information includes model information of the one or more AI models, and the second information is used by the terminal to activate the one or more AI models.

[0098] In conjunction with some embodiments of the first aspect, in some embodiments, the network device performing a corresponding artificial intelligence (AI) operation based on the operating status of the terminal includes:

[0099] When the first information indicates that it is not suitable to receive the AI ​​model transmission, the network device turns off or suspends the sending of the AI ​​model, and / or sends second information to the terminal, where the second information is used to instruct the terminal to turn off or suspend the reception of the AI ​​model.

[0100] In conjunction with some embodiments of the first aspect, in some embodiments, the network device performing a corresponding artificial intelligence (AI) operation based on the operating status of the terminal includes:

[0101] When the first information indicates that it is suitable to receive the AI ​​model transmission, the network device restarts or reconfigures the sending of the AI ​​model, and / or sends second information to the terminal, where the second information is used to instruct the terminal to start receiving the AI ​​model.

[0102] In a second aspect, the present disclosure provides a processing method, including:

[0103] The terminal sends first information to the network device, where the first information is used to indicate the operating status of the terminal, wherein the first information is used by the network device to perform corresponding artificial intelligence (AI) operations according to the operating status of the terminal.

[0104] In conjunction with some embodiments of the second aspect, in some embodiments, the operating state includes at least one of the following:

[0105] Computing resource status;

[0106] Storage resource status;

[0107] Battery status;

[0108] Fever state.

[0109] In conjunction with some embodiments of the second aspect, in some embodiments, the first information indicates that a first feature occurs in the operating state of the terminal, and the first feature includes at least one of the following:

[0110] The storage resource is less than or equal to a first storage resource threshold;

[0111] The computing resource is less than or equal to a first computing resource threshold;

[0112] The battery level is less than or equal to a first battery level threshold;

[0113] The terminal is overheated.

[0114] In combination with some embodiments of the second aspect, in some embodiments, the first feature indicated by the first information includes that the storage resource is less than or equal to a first storage resource threshold, and the first information is used to instruct the network device to pause or shut down the sending of the AI ​​model.

[0115] In conjunction with some embodiments of the second aspect, in some embodiments, the first feature indicated by the first information includes that the computing resource is less than or equal to a first computing resource threshold, and the method further includes:

[0116] Receive second information sent by the network device, where the second information is used to instruct the terminal to shut down at least one AI model in the terminal.

[0117] In combination with some embodiments of the second aspect, in some embodiments, the first feature indicated by the first information includes that the power is less than or equal to a first power threshold, and the first information is used to instruct the network device not to activate a new AI model, and / or to send second information to the terminal.

[0118] The second information is used to instruct the terminal to shut down a first AI model, where the first AI model is an AI model in the terminal whose computational complexity satisfies a first condition.

[0119] In conjunction with some embodiments of the second aspect, in some embodiments, the first feature indicated by the first information includes overheating of the terminal, and the method further includes:

[0120] Receive second information sent by the network device, where the second information includes first operating cycle configuration information of the AI ​​model, where the operating cycle included in the first operating cycle configuration information is greater than the first operating cycle, where the first operating cycle is the operating cycle associated with the AI ​​model before the network device receives the first information and the first feature indicated by the first information includes overheating of the terminal.

[0121] In conjunction with some embodiments of the second aspect, in some embodiments, the first information indicates that a second feature occurs in the operating state of the terminal, and the second feature includes at least one of the following:

[0122] The storage resource is greater than or equal to a second storage resource threshold;

[0123] The computing resource is greater than or equal to a second computing resource threshold;

[0124] The battery level is greater than or equal to a second battery level threshold;

[0125] The terminal is not overheating.

[0126] In combination with some embodiments of the second aspect, in some embodiments, the second feature indicated by the first information includes that the storage resource is greater than or equal to a second storage resource threshold, and the first information is used to instruct the network device to start or reconfigure the sending of the AI ​​model.

[0127] In conjunction with some embodiments of the second aspect, in some embodiments, the second feature indicated by the first information includes that the computing resource is greater than or equal to a second computing resource threshold, and the method further includes:

[0128] Receive second information sent by the network device, where the second information is used to instruct the terminal to activate at least one AI model in the terminal.

[0129] In conjunction with some embodiments of the second aspect, in some embodiments, the second feature indicated by the first information includes that the power level is greater than or equal to a second power level threshold, and the first information is used to indicate activation of a new AI model and / or sending second information to the terminal;

[0130] The second information is used to instruct the terminal to activate a first AI model, where the first AI model is an AI model in the terminal whose computational complexity satisfies a first condition.

[0131] In conjunction with some embodiments of the second aspect, in some embodiments, the second feature indicated by the first information includes that the terminal is not overheated, and the method further includes:

[0132] Receive second information sent by the network device, where the second information is used to instruct the terminal to restore the operation cycle of the AI ​​model to the first operation cycle.

[0133] In conjunction with some embodiments of the second aspect, in some embodiments, the operating state includes at least one of the following:

[0134] Not suitable for AI reasoning;

[0135] The need to reduce the number of activated AI models;

[0136] The frequency of AI model execution needs to be reduced;

[0137] The activated AI model can be increased;

[0138] Not suitable for receiving AI model transmissions;

[0139] Suitable for receiving AI model transmissions.

[0140] In combination with some embodiments of the second aspect, in some embodiments, the first information indicates that it is not suitable for AI reasoning, and the first information is used to instruct the network device to shut down the AI ​​model that has been activated by the terminal.

[0141] In conjunction with some embodiments of the second aspect, in some embodiments, the first information indicates the AI ​​model that needs to reduce activation, and the method further includes:

[0142] Receive second information sent by the network device, where the second information instructs the terminal to shut down at least one AI model in the terminal.

[0143] In conjunction with some embodiments of the second aspect, in some embodiments, the first information indicates the need to reduce the frequency of execution of the AI ​​model, and the method further includes:

[0144] Receive second information sent by the network device, where the second information includes configuration information of the operation frequency of the AI ​​model.

[0145] In conjunction with some embodiments of the second aspect, in some embodiments, the first information indicates the AI ​​model that can be added and activated, and the first information is used to instruct the network device to activate one or more AI models according to service needs, and / or send second information to the terminal;

[0146] The second information includes model information of the one or more AI models, and the second information is used by the terminal to activate the one or more AI models.

[0147] In conjunction with some embodiments of the second aspect, in some embodiments, the first information indicates that it is not suitable to receive AI model transmission, and the first information is used to instruct the network device to turn off or suspend the transmission of the AI ​​model, and / or send second information to the terminal;

[0148] The second information is used to instruct the terminal to close or suspend reception of the AI ​​model.

[0149] In conjunction with some embodiments of the second aspect, in some embodiments, the first information indicates the suitability for receiving AI model transmission, and the first information is used to instruct the network device to restart or reconfigure the sending of the AI ​​model, and / or to send second information to the terminal;

[0150] The second information is used to instruct the terminal to start receiving the AI ​​model.

[0151] In a third aspect, an embodiment of the present disclosure proposes a network device, comprising at least one of a transceiver module and a processing module; wherein the above-mentioned network device is used to execute the optional implementation method of the first aspect.

[0152] In a fourth aspect, an embodiment of the present disclosure proposes a terminal, comprising at least one of a transceiver module and a processing module; wherein the terminal is used to execute the optional implementation method of the second aspect.

[0153] In a fifth aspect, an embodiment of the present disclosure provides a communication system, including:

[0154] A network device configured as an optional implementation of the first aspect;

[0155] The terminal is configured to execute the optional implementation of the aforementioned second aspect.

[0156] In a sixth aspect, an embodiment of the present disclosure proposes a communication device, comprising: one or more processors; wherein the processor is used to call instructions to enable the communication device to execute the optional implementation method of the aforementioned first aspect.

[0157] In a seventh aspect, an embodiment of the present disclosure proposes a communication device, comprising: one or more processors; wherein the processor is used to call instructions to enable the communication device to execute the optional implementation method of the aforementioned second aspect.

[0158] In an eighth aspect, an embodiment of the present disclosure proposes a storage medium storing instructions. When the instructions are executed on a communication device, the communication device executes optional implementation methods of the aforementioned first and second aspects.

[0159] 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.

[0160] 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.

[0161] 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.

[0162] It is understandable that the above-mentioned network devices, terminals, 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.

[0163] The present disclosure provides processing methods and apparatuses thereof. In some embodiments, the terms processing method, information processing method, and communication method are interchangeable; the terms processing apparatus, information processing apparatus, and communication apparatus are interchangeable; and the terms processing system, information processing system, and communication system are interchangeable.

[0164] 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.

[0165] 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.

[0166] 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.

[0167] 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.

[0168] In the embodiments of the present disclosure, “plurality” refers to two or more.

[0169] In some embodiments, the terms "at least one," "one or more," "a plurality of," "multiple," etc. may be used interchangeably.

[0170] 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.

[0171] 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.

[0172] 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.

[0173] 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.

[0174] In some embodiments, terms such as "time / frequency" and "time / frequency domain" refer to the time domain and / or the frequency domain.

[0175] 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.

[0176] 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.

[0177] 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.

[0178] In some embodiments, "network" can be interpreted as devices included in the network, such as access network equipment, core network equipment, etc.

[0179] 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.

[0180] 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.

[0181] In some embodiments, data, information, etc. may be obtained with the user's consent.

[0182] Figure 1 is a schematic diagram of the architecture of a communication system according to an embodiment of the present disclosure. The communication system may include, but is not limited to, one network device and one terminal. The number and configuration of devices shown in Figure 1 are for example purposes only and do not limit the present disclosure. In actual applications, two or more network devices and two or more terminals may be included. The communication system 100 shown in Figure 1 includes, for example, one network device 101 and one terminal 102.

[0183] In some embodiments, network device 101 and terminal 102 are used to distinguish different description objects. The terminal herein can be an entity on the user side for receiving or transmitting signals, such as a mobile phone. It can also be referred to as a terminal, user equipment (UE), mobile station (MS), mobile terminal (MT), etc. The terminal can be at least one of a car with communication functions, a smart car, a mobile phone, a wearable device, a tablet computer (Pad), a computer with wireless transceiver functions, a virtual reality (VR) terminal, an augmented reality (AR) terminal, a wireless terminal in industrial control, a wireless terminal in self-driving, a wireless terminal in remote medical surgery, a wireless terminal in a smart grid, a wireless terminal in transportation safety, a wireless terminal in a smart city, a wireless terminal in a smart home, etc. The embodiments of the present disclosure do not limit the specific technology and specific device form adopted by the terminal.

[0184] In some embodiments, the network device may be an access network device. In some embodiments, the access network device is, for example, a node or device that connects a terminal device to a wireless network. The access network device may include, but is not limited to, at least one of an evolved NodeB (eNB), a next generation evolved NodeB (ng-eNB), a next generation NodeB (gNB), a NodeB (NB), a home nodeB (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 RAN, a cloud RAN, a base station in other communication systems, and an access node in a Wi-Fi system.

[0185] 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.

[0186] 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.

[0187] 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 proposed in 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 proposed in the embodiment of the present disclosure is also applicable to similar technical problems.

[0188] The following embodiments of the present disclosure may be applied to the communication system 100 shown in FIG1 , or a portion thereof, but are not limited thereto. The entities shown in FIG1 are illustrative only. The communication system may include all or part of the entities shown in FIG1 , or may include other entities outside of FIG1 . The number and form of the entities are arbitrary, and the entities may be physical or virtual. The connection relationships between the entities are illustrative only. The entities may be connected or disconnected, and the connection may be in any manner, including direct or indirect, wired or wireless.

[0189] 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 methods, and next-generation systems based on and extending these methods. Furthermore, multiple systems may be combined (for example, a combination of LTE or LTE-A with 5G).

[0190] It should be noted that the widespread application of fifth-generation (5G) technology has brought about tremendous changes in all aspects of people's lives. According to the vision of the ITU (International Telecommunication Union), 5G will penetrate into all areas of future society and build a comprehensive information ecosystem centered on users. Among them, 5G user experience rates can reach 100Mbit / s to 1Gbit / s, which can support ultimate business experiences such as mobile virtual reality; 5G peak rates can reach 10Gbit / s to 20Gbit / s, and traffic density can reach 10Mbit / s / m 2 , capable of supporting more than a thousand-fold growth in mobile business traffic in the future; the 5G connection density can reach 1 million / m 2 , effectively supporting massive numbers of IoT devices; 5G transmission latency can reach milliseconds, meeting the stringent requirements of the Internet of Vehicles and industrial control; 5G can support mobile speeds of 500 km / h, providing a good user experience in high-speed rail environments. As a representative of new infrastructure, 5G will undoubtedly reshape the future information society.

[0191] In recent years, artificial intelligence (AI) technology has achieved continuous breakthroughs in numerous fields. The continued development of fields such as intelligent voice and computer vision has not only brought a rich variety of applications to smart terminals, but has also found widespread application in education, transportation, home living, healthcare, retail, security, and other fields. This has brought convenience to people's lives while also promoting industrial upgrading across various industries. AI technology is also rapidly interpenetrating with other disciplines, integrating knowledge from different disciplines while also providing new directions and methods for their development.

[0192] Related technologies incorporate AI into wireless air interfaces, leveraging it to enhance wireless air interface transmission technology. In some cases, when AI models are deployed on terminals, they require resources, such as storage and computing resources, to run them. Furthermore, running AI models consumes power or generates heat, causing overheating and impacting performance.

[0193] However, for some AI use cases, the control of AI functions or AI models is on the network side, such as the network side controlling the model's switch. At this time, the network side is not aware of the terminal's running status of the AI ​​model, and therefore may configure AI operations that do not correspond to the terminal's local status. Among them, AI models can refer to programs that can be run on the terminal, and AI functions are abstractions of the functions implemented by AI models. For example, an AI function can correspond to one or more parameters related to the operation of the AI ​​model, and an AI function can correspond to multiple AI models. For example, as long as the corresponding AI model or AI function is running, it is called an AI operation.

[0194] To this end, the present disclosure proposes a processing method and device thereof, which can assist the network side in managing the terminal's AI model through the terminal's local AI operating environment reported by the terminal, thereby avoiding the impact of terminal performance due to terminal resource shortages, low power, etc., thereby facilitating the network side to perform AI-related processing.

[0195] FIG2A is an interactive diagram illustrating a processing method according to an embodiment of the present disclosure. As shown in FIG2A , the processing method according to an embodiment of the present disclosure can be applied to a communication system 100 , and the method includes but is not limited to the following steps.

[0196] Step S2101: Terminal 102 sends first information.

[0197] In some embodiments, the first information may be sent by the terminal 102 to the network device 101. For example, the terminal 102 sends the first information to the network device 101. Optionally, the network device 101 receives the first information. For example, the network device 101 receives the first information sent by the terminal 102.

[0198] In some embodiments, the first information is used to indicate the operating status of the terminal 101. Exemplarily, the first information is used to indicate the operating status of the local side of the terminal 101. Exemplarily, the network device 101 processes the AI ​​model of the terminal 102 according to the operating status of the terminal.

[0199] In some embodiments, the operating state includes at least one of the following: computing resource state; storage resource state; power state; heating state. Exemplarily, the operating state may include the computing resource state. Alternatively, the operating state may include the storage resource state. Alternatively, the operating state may include the power state. Alternatively, the operating state may include the heating state. Alternatively, the operating state may include the computing resource state and the storage resource state. Alternatively, the operating state may include the computing resource state and the power state. Alternatively, the operating state may include the computing resource state and the heating state. Alternatively, the operating state may include the storage resource state and the power state. Alternatively, the operating state may include the storage resource state and the heating state. Alternatively, the operating state may include the power state and the heating state. Alternatively, the operating state may include the computing resource state, the storage resource state, and the power state. Alternatively, the operating state may include the computing resource state, the storage resource state, and the heating state. Alternatively, the operating state may include the computing resource state, the power state, and the heating state. Alternatively, the operating state may include the storage resource state, the power state, and the heating state. Alternatively, the operating state includes the computing resource state, the storage resource state, the power state, and the heating state.

[0200] In some embodiments, the above-mentioned first information is used to indicate that the operating status of the terminal 101 has a first characteristic, and may also be referred to as being used to indicate that the operating status of the terminal 101 has a first characteristic. In some embodiments, the first characteristic may include at least one of the following: storage resources are less than or equal to a first storage resource threshold; computing resources are less than or equal to a first computing resource threshold; power is less than or equal to a first power threshold; terminal overheating. Exemplarily, the first characteristic may include storage resources being less than or equal to a first storage resource threshold. Exemplarily, the first characteristic may include computing resources being less than or equal to a first computing resource threshold. Exemplarily, the first characteristic may include power being less than or equal to a first power threshold. Exemplarily, the first characteristic may include terminal overheating. Exemplarily, the first characteristic may include any combination of the examples given above, which will not be repeated here.

[0201] Exemplarily, the above-mentioned storage resources being less than or equal to the first storage resource threshold may mean that the storage space of terminal 102 is in short supply, for example, the remaining storage space of terminal 102 is less than or equal to a threshold. Exemplarily, the above-mentioned computing resources being less than or equal to the first computing resource threshold may mean that the computing resources (or computing resources) of terminal 102 are insufficient, for example, the memory usage of terminal 102 is greater than or equal to a threshold, indicating that the computing resources of terminal 102 are insufficient. Exemplarily, the above-mentioned power level being less than or equal to the first power level threshold may mean that the remaining power of terminal 102 is less than or equal to a threshold. Exemplarily, the above-mentioned terminal overheating may mean that the temperature of terminal 102 reaches a threshold.

[0202] In some embodiments, the above-mentioned first information can be sent by the terminal 102 to the network device 101 through RRC signaling, or can be sent to the network device 101 through other means. This disclosure does not limit this and will not elaborate on it.

[0203] In step S2102 , the network device 101 performs a corresponding AI operation according to the first feature indicated by the first information.

[0204] In some embodiments, network device 101 receives first information sent by terminal 102 and performs a corresponding AI operation based on the operating state of terminal 102 indicated by the first information, for example, processing an AI model of terminal 102. For example, the first information indicates that the operating state of terminal 102 exhibits a first characteristic, and the network device performs the corresponding AI operation.

[0205] It should be noted that, if the first feature indicated by the first information is different, the AI ​​operation performed by the network device 101 will also be different.

[0206] In some embodiments, the first characteristic indicated by the first information may include one or more of storage resources less than or equal to a first storage resource threshold, computing resources less than or equal to a first computing resource threshold, power less than or equal to a first power threshold, and terminal overheating. Exemplarily, when the first characteristic indicated by the first information includes one or more of storage resources less than or equal to a first storage resource threshold, computing resources less than or equal to a first computing resource threshold, power less than or equal to a first power threshold, and terminal overheating, the network device 101 performs a corresponding artificial intelligence (AI) operation including at least one of the following: the network device suspends or disables the transmission of the AI ​​model; the network device does not activate a new AI model; the network device sends a second message to the terminal, the second message including first operation cycle configuration information for the AI ​​model, and / or the second message is used to instruct the terminal to perform at least one of the following actions: suspending or disabling the reception of the AI ​​model, disabling at least one AI model in the terminal, and disabling the first AI model; wherein the operation cycle included in the first operation cycle configuration information is greater than the first operation cycle, the first operation cycle is the operation cycle associated with the AI ​​model before the network device receives the first information and the first characteristic indicated by the first information includes terminal overheating, and the first AI model is an AI model in the terminal whose computational complexity meets the first condition.

[0207] Exemplarily, the network device 101 suspending or disabling the transmission of the AI ​​model means that if the terminal 102 does not have an AI model, the network device 101 sends the trained AI model to the terminal 102. For example, if the terminal 102 does not have AI model 1 and the terminal 102 wants to use the AI ​​model 1 for corresponding processing, the network device can send the trained AI model 1 to the terminal 102.

[0208] Exemplarily, the first feature indicated by the above-mentioned first information may include one or more of storage resources being less than or equal to a first storage resource threshold, computing resources being less than or equal to a first computing resource threshold, power being less than or equal to a first power threshold, and terminal overheating. In this case, the network device 101 may perform one or more of the following actions: pausing or turning off the sending of the AI ​​model; sending a second message to the terminal 102, turning off or pausing the AI ​​operation through the second message; sending a second message to the terminal 102, reducing the AI-based operation through the second message, for example, configuring a larger AI operation cycle through the second message; switching the AI ​​model.

[0209] In some embodiments, the network device 101 determines that the first feature indicated by the first information includes that the storage resources are less than or equal to the first storage resource threshold, and the network device 101 suspends or shuts down the transmission of the AI ​​model. Exemplarily, the first information sent by the terminal 102 to the network device is used to indicate that the operating state of the terminal 102 has a first feature, and the first feature includes that the storage resources are less than or equal to the first storage resource threshold, indicating that the terminal 102 is currently short of storage resources. The network device 101 can suspend or shut down the transmission of the AI ​​model. Exemplarily, the network device 101 can suspend or shut down the sending of the AI ​​model to the terminal 102, or the network device 101 can suspend or shut down the sending of the AI ​​model to avoid aggravating the problem of storage resource shortage of the terminal 102. For example, there is no AI model 1 on the terminal 102, and the network device can prepare to send the trained AI model 1 to the terminal 102. When the terminal 102 sends the first information to the network device, the first information is used to indicate that the operating status of the terminal 102 has a first feature, and the first feature includes storage resources being less than or equal to a first storage resource threshold, indicating that the terminal 102 currently has a shortage of storage resources, then the network device 101 does not send the trained AI model 1 to the terminal 102.

[0210] In some embodiments, the network device 101 determines that the first feature indicated by the first information includes that the computing resources are less than or equal to the first computing resource threshold, and the network device 101 sends second information to the terminal 102, where the second information is used to instruct the terminal 102 to shut down at least one AI model. Exemplarily, the first information sent by the terminal 102 to the network device indicates that the operating state of the terminal 102 has a first feature, where the first feature includes that the computing resources are less than or equal to the first computing resource threshold, indicating that the terminal 102 currently has insufficient computing resources. In this case, the network device 101 may send second information to the terminal 102, instructing the terminal 102 to shut down at least one AI model in the terminal 102 through the second information, so as to avoid exacerbating the problem of insufficient computing resources of the terminal 102.

[0211] In some embodiments, the network device 101 determines that the first feature indicated by the first information includes that the power level is less than or equal to a first power threshold, the network device 101 does not activate the new AI model, and / or sends second information to the terminal 102; the second information is used to instruct the terminal 102 to turn off the first AI model, and the first AI model is an AI model in the terminal 102 whose computational complexity meets the first condition.

[0212] Exemplarily, the first information sent by terminal 102 to the network device is used to indicate that a first characteristic appears in the operating status of terminal 102, and the first characteristic includes that the power level is less than or equal to a first power threshold, indicating that the current power level of terminal 102 is less than a threshold. Then, network device 101 may not activate a new AI model. Optionally, network device 101 may not activate a new AI model to terminal 102 to avoid aggravating the problem of low power of terminal 102.

[0213] Exemplarily, the first information sent by the terminal 102 to the network device is used to indicate that the operating status of the terminal 102 has a first characteristic, and the first characteristic includes that the power is less than or equal to the first power threshold, indicating that the current power of the terminal 102 is less than a threshold. Then the network device 101 can send a second information to the terminal 102, and instruct the terminal 102 through the second information to shut down the first AI model whose computational complexity meets the first condition. For example, the second information is used to instruct the terminal 102 to shut down the AI ​​model whose computational complexity is higher than a threshold, so as to avoid consuming the terminal power due to the terminal running too many AI models, thereby improving the terminal's battery life.

[0214] Exemplarily, the first information sent by the terminal 102 to the network device is used to indicate that a first feature appears in the operating status of the terminal 102. The first feature includes that the power level is less than or equal to a first power threshold, indicating that the current power level of the terminal 102 is less than or equal to a threshold. Then the network device 101 may not activate a new AI model. Optionally, the network device 101 may not activate a new AI model to the terminal 102. The network device may also send a second message to the terminal 102, instructing the terminal 102 to shut down the first AI model whose computational complexity meets the first condition through the second information. For example, the terminal 102 is instructed to shut down the AI ​​model whose computational complexity is higher than a threshold through the second information, thereby further improving the terminal's battery life.

[0215] In some embodiments, the network device 101 determines that the first feature indicated by the first information includes overheating of the terminal 102, and the network device 101 sends second information to the terminal 102. The second information includes first operating cycle configuration information of the AI ​​model (such as the AI ​​model of the terminal 102). The operating cycle included in the first operating cycle configuration information is greater than the first operating cycle. The first operating cycle is the operating cycle associated with the AI ​​model before the network device 101 receives the first information and the first feature indicated by the first information includes overheating of the terminal 102.

[0216] Exemplarily, terminal 102 sends first information to the network device, where the first information indicates that a first characteristic of the operating status of terminal 102 exists. The first characteristic includes overheating of terminal 102, indicating that the current temperature of terminal 102 has reached a threshold. Network device 101 may then send second information to terminal 102, using the second information to configure a larger AI operation cycle for the AI ​​model of terminal 102. For example, if terminal 102 does not send the first information indicating that the first characteristic includes overheating of terminal 102 to network device 101, the AI ​​operation cycle of the AI ​​model of terminal 102 is M. After terminal 102 sends the first information indicating that the first characteristic includes overheating of terminal 102 to network device 101, network device 102 configures a larger AI operation cycle for the AI ​​model of terminal 102 using the second information, for example, a configured cycle of N, where N is greater than M. This reduces the AI ​​operations of terminal 102, thereby alleviating the problem of overheating of terminal 102.

[0217] In some embodiments, the application cases of the above-mentioned AI model may include but are not limited to at least one of the following: AI-based CSI (Channel State Information) enhancement; AI-based beam management; AI-based positioning. Exemplarily, the terminal 102 may include one or more AI models. For example, when the terminal 102 includes an AI model, the application case of the AI ​​model may be one of AI-based CSI enhancement, AI-based beam management, and AI-based positioning, that is, the AI ​​model may be an AI model for CSI enhancement, or an AI model for beam management, or an AI model for positioning. For another example, when the terminal 102 includes multiple AI models, the application cases of each AI model may be the same or different.

[0218] 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", "field", "symbol", "symbol", "codeword", "codebook", "codeword", "codepoint", "bit", "data", "program", and "chip" can be used interchangeably.

[0219] In some embodiments, terms such as "uplink", "uplink", "physical uplink" can be interchangeable with each other, and terms such as "downlink", "downlink", "physical downlink" can be interchangeable with each other, and terms such as "side", "sidelink", "side communication", "sidelink communication", "direct connection", "direct link", "direct communication", "direct link communication" can be interchangeable with each other.

[0220] 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.

[0221] In some embodiments, terms such as "send", "transmit", "report", "download", "transmit", "bidirectional transmission", "send and / or receive" can be used interchangeably.

[0222] 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.

[0223] 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.

[0224] The method involved in the embodiments of the present disclosure may include at least one of steps S2101 and S2102. For example, step S2101 may be implemented as an independent embodiment, step S2102 may be implemented as an independent embodiment, and step S2101 + step S2102 may be implemented as independent embodiments, but the present invention is not limited thereto.

[0225] In some embodiments, step S2102 is optional, and one or more of these steps may be omitted or replaced in different embodiments.

[0226] In some embodiments, step S2101 is optional, and one or more of these steps may be omitted or replaced in different embodiments.

[0227] In some embodiments, reference may be made to other optional implementations described before or after the description corresponding to FIG. 2A .

[0228] FIG2B is an interactive diagram illustrating a processing method according to an embodiment of the present disclosure. As shown in FIG2B , the processing method according to an embodiment of the present disclosure can be applied to a communication system 100 , and the method includes but is not limited to the following steps.

[0229] Step S2201: Terminal 102 sends first information.

[0230] In some embodiments, the first information may be sent by the terminal 102 to the network device 101. For example, the terminal 102 sends the first information to the network device 101. Optionally, the network device 101 receives the first information. For example, the network device 101 receives the first information sent by the terminal 102.

[0231] In some embodiments, the first information is used to indicate the operating status of terminal 101. Exemplarily, the first information is used to indicate the operating status of the local terminal 101. Exemplarily, network device 101 processes the AI ​​model of terminal 102 according to the operating status of terminal 102 indicated by the first information.

[0232] In some embodiments, the operating state includes at least one of the following: computing resource state; storage resource state; power state; heating state. Exemplarily, the operating state may include the computing resource state. Alternatively, the operating state may include the storage resource state. Alternatively, the operating state may include the power state. Alternatively, the operating state may include the heating state. Alternatively, the operating state may include the computing resource state and the storage resource state. Alternatively, the operating state may include the computing resource state and the power state. Alternatively, the operating state may include the computing resource state and the heating state. Alternatively, the operating state may include the storage resource state and the power state. Alternatively, the operating state may include the storage resource state and the heating state. Alternatively, the operating state may include the power state and the heating state. Alternatively, the operating state may include the computing resource state, the storage resource state, and the power state. Alternatively, the operating state may include the computing resource state, the storage resource state, and the heating state. Alternatively, the operating state may include the computing resource state, the power state, and the heating state. Alternatively, the operating state may include the storage resource state, the power state, and the heating state. Alternatively, the operating state includes the computing resource state, the storage resource state, the power state, and the heating state.

[0233] In some embodiments, the above-mentioned first information is used to indicate that a second feature occurs in the operating state of the terminal 101, and may also be referred to as being used to indicate that a second feature occurs in the operating state of the terminal 101. In some embodiments, the second feature includes at least one of the following: storage resources are greater than or equal to a second storage resource threshold; computing resources are greater than or equal to a second computing resource threshold; power is greater than or equal to a second power threshold; and the terminal is not overheating. Exemplarily, the second feature includes storage resources being greater than or equal to a second storage resource threshold. Exemplarily, the second feature includes computing resources being greater than or equal to a second computing resource threshold. Exemplarily, the second feature includes power being greater than or equal to a second power threshold. Exemplarily, the second feature includes terminal not overheating. Exemplarily, the second feature may include any combination of the examples given above, which will not be repeated here.

[0234] Exemplarily, the above-mentioned storage resources being greater than or equal to the second storage resource threshold may mean that the storage space of terminal 102 is sufficient, for example, the remaining storage space of terminal 102 is greater than or equal to a threshold. Exemplarily, the above-mentioned computing resources being greater than or equal to the second computing resource threshold may mean that the computing resources of terminal 102 are sufficient (or computing resources are sufficient), for example, the memory usage of terminal 102 is less than or equal to a threshold, indicating that the computing resources of terminal 102 are sufficient. Exemplarily, the above-mentioned power level being less than or equal to the first power level threshold may mean that the remaining power of terminal 102 is greater than or equal to a threshold. Exemplarily, the above-mentioned terminal overheating may mean that the temperature of terminal 102 is less than or equal to a threshold.

[0235] In some embodiments, the above-mentioned first information can be sent by the terminal 102 to the network device 101 through RRC signaling, or can be sent to the network device 101 through other means. This disclosure does not limit this and will not elaborate on it.

[0236] Step S2202: The network device 101 performs a corresponding AI operation according to the second feature indicated by the first information.

[0237] In some embodiments, network device 101 receives first information sent by terminal 102 and performs a corresponding AI operation based on the operating state of terminal 102 indicated by the first information, such as processing an AI model of terminal 102. For example, the first information indicates that the operating state of terminal 102 exhibits a second characteristic, and network device 101 performs the corresponding AI operation.

[0238] In some embodiments, the premise that the first information indicates the second characteristic may be that the terminal 102 has previously sent the first information indicating the first characteristic. Exemplarily, if the current operating state of the terminal 102 exhibits the first characteristic, such as one or more of the following: computing resources are less than or equal to the first computing resource threshold, storage resources are less than or equal to the first storage resource threshold, power is less than or equal to the first power threshold, and the terminal is overheated, the terminal 102 sends the first information to the network device 101 to indicate the current operating state of the terminal 102, and the network device 101 performs corresponding processing on the AI ​​model of the terminal 102 based on the first characteristic indicated by the first information; after a period of time, the operating state of the terminal 102 exhibits the second characteristic, such as one or more of the following: computing resources are greater than or equal to the second computing resource threshold, storage resources are greater than or equal to the second storage resource threshold, power is greater than or equal to the second power threshold, and the terminal is not overheated, the terminal 102 may send the first information to the network device 101 to indicate the current operating state of the terminal 102, and the network device 101 performs corresponding processing on the AI ​​model of the terminal 102 based on the second characteristic indicated by the first information.

[0239] It should be noted that, if the second feature indicated by the above-mentioned first information is different, the way in which the network device 101 processes the AI ​​model of the terminal 102 will also be different.

[0240] In some embodiments, the second feature indicated by the first information may include one or more of the following: storage resources are greater than or equal to a second storage resource threshold, computing resources are greater than or equal to a second computing resource threshold, power is greater than or equal to a second power threshold, and the terminal is not overheating. Exemplarily, when the second feature indicated by the first information may include one or more of the following: storage resources are greater than or equal to a second storage resource threshold, computing resources are greater than or equal to a second computing resource threshold, power is greater than or equal to a second power threshold, and the terminal is not overheating, the network device 101 performs a corresponding artificial intelligence (AI) operation including at least one of the following: the network device starts or reconfigures the sending of an AI model; the network device activates a new AI model; the network device sends a second information to the terminal, the second information being used to instruct the terminal to perform at least one of the following actions: activating at least one AI model in the terminal, activating the first AI model, and restoring the operation cycle of the AI ​​model to the first operation cycle.

[0241] Exemplarily, the second feature indicated by the above-mentioned first information may include one or more of the following: storage resources are greater than or equal to a second storage resource threshold, computing resources are greater than or equal to a second computing resource threshold, power is greater than or equal to a second power threshold, and the terminal is not overheating. The network device 101 may perform one or more of the following actions: start or reconfigure the transmission of the AI ​​model; activate the AI ​​function and / or AI model of the terminal 102; increase AI-based operations, exemplarily, increase the operation cycle of the AI ​​model of the terminal 102, and / or increase the number of AI models of the terminal 102, etc.

[0242] In some embodiments, the network device 101 determines that the second feature indicated by the first information includes that the storage resources are greater than or equal to the second storage resource threshold, and the network device 101 starts or reconfigures the transmission of the AI ​​model. Exemplarily, the first information sent by the terminal 102 to the network device is used to indicate that the operating state of the terminal 102 has a second feature, and the second feature includes that the storage resources are greater than or equal to the second storage resource threshold, indicating that the terminal 102 currently has sufficient storage resources. Then, the network device 101 can start or reconfigure the transmission of the AI ​​model. Exemplarily, the network device 101 can start or reconfigure the transmission of the AI ​​model, such as the network device 101 can resend the AI ​​model to the terminal 102.

[0243] Exemplarily, the current operating status of terminal 102 shows a first characteristic, such as the storage resources are less than or equal to the first storage resource threshold, and terminal 102 sends a first message to network device 101 to indicate the current operating status of terminal 102. Network device 101 suspends or shuts down the transmission of the AI ​​model according to the first characteristic indicated by the first information, that is, the network side suspends or shuts down the sending of the AI ​​model, and the terminal correspondingly suspends or shuts down the receiving of the AI ​​model; after a period of time, the operating status of terminal 102 shows a second characteristic, such as the storage resources are greater than or equal to the second storage resource threshold, and terminal 102 can send a first message to network device 101 to indicate the operating status of terminal 102 at this time. Network device 101 can start or reconfigure the sending of the AI ​​model according to the second characteristic indicated by the first information, such as network device 101 can resend the AI ​​model to terminal 102 and start or reconfigure the reception of the AI ​​model of the terminal.

[0244] In some embodiments, network device 101 determines that the second characteristic indicated by the first information includes that the computing resources are greater than or equal to a second computing resource threshold, and network device 101 sends second information to terminal 102, where the second information is used to instruct terminal 102 to activate at least one AI model. Exemplarily, the first information sent by terminal 102 to the network device indicates that the operating status of terminal 102 has the second characteristic, where the first characteristic includes that the computing resources are greater than or equal to the second computing resource threshold, indicating that terminal 102 currently has sufficient computing resources. In this case, network device 101 may send second information to terminal 102, whereby terminal 102 is instructed to activate at least one AI model through the second information.

[0245] In some embodiments, the network device 101 determines that the second feature indicated by the first information includes that the power level is greater than or equal to a second power threshold, and the network device 101 activates a new AI model and / or sends second information to the terminal 102; the second information is used to instruct the terminal 102 to activate the first AI model and / or the first AI function, the first AI model is an AI model in the terminal 102 whose computational complexity meets the first condition, and the first AI function is an AI function in the terminal 102 whose computational complexity meets the first condition.

[0246] Exemplarily, the first information sent by the terminal 102 to the network device is used to indicate that a second feature appears in the operating status of the terminal 102, and the second feature includes a power level greater than or equal to a second power threshold, indicating that the current power level of the terminal 102 is greater than or equal to a threshold. Then, the network device 101 can activate the AI ​​model, such as activating a new AI model. Optionally, the network device 101 can activate a new AI model to the terminal 102.

[0247] Exemplarily, the first information sent by the terminal 102 to the network device is used to indicate that a second feature appears in the operating status of the terminal 102, and the second feature includes that the power level is less than or equal to the first power threshold, indicating that the current power level of the terminal 102 is greater than or equal to a threshold. Then, the network device 101 can send a second message to the terminal 102, and instruct the terminal 102 to activate the first AI model and / or the first AI function whose computational complexity meets the first condition through the second information. For example, the terminal 102 is instructed to activate an AI model whose computational complexity is higher than a threshold through the second information.

[0248] Exemplarily, the first information sent by the terminal 102 to the network device is used to indicate that a second feature appears in the operating status of the terminal 102, and the second feature includes that the power level is greater than or equal to a second power threshold, indicating that the current power level of the terminal 102 is greater than or equal to a threshold. Then the network device 101 can activate the AI ​​model. Optionally, the network device 101 can activate a new AI model to the terminal 102. The network device can also send a second message to the terminal 102, instructing the terminal 102 to activate the first AI model and / or the first AI function whose computational complexity meets the first condition through the second information. For example, the terminal 102 is instructed to activate an AI model whose computational complexity is higher than a threshold through the second information.

[0249] In some embodiments, the network device 101 determines that the second feature indicated by the first information includes that the terminal 102 is not overheating, and the network device 101 sends second information to the terminal 102. The second information is used to indicate that the operating cycle of the AI ​​model of the terminal 102 is restored to the first operating cycle. The first operating cycle is the operating cycle associated with the AI ​​model before the network device 101 receives the first information and the first feature indicated by the first information includes that the terminal 102 is overheating.

[0250] Exemplarily, the first information sent by terminal 102 to the network device is used to indicate that the operating status of terminal 102 has a second characteristic, and the second characteristic includes that terminal 102 is not overheating, indicating that the current temperature of terminal 102 is less than or equal to a threshold. Then, network device 101 can send second information to terminal 102, and through this second information, instruct the operating cycle of the AI ​​model of terminal 102 to restore to the first operating cycle. For example, when terminal 102 does not send the first information indicating that the first feature includes overheating of terminal 102 to network device 101, the AI ​​operation cycle of the AI ​​model of terminal 102 is M. After terminal 102 sends the first information indicating that the first feature includes overheating of terminal 102 to network device 101, network device 102 configures a larger AI operation cycle for the AI ​​model of terminal 102 through the second information, for example, the configured cycle is N, where N is greater than M. After terminal 102 sends the first information indicating that the second feature includes that terminal 102 is not overheating to network device 101, network device 102 configures a smaller AI operation cycle for the AI ​​model of terminal 102 through the second information, such as restoring to the first operation cycle, such as restoring the operation cycle of the AI ​​model of terminal 102 to M.

[0251] In some embodiments, the application cases of the above-mentioned AI model may include but are not limited to at least one of the following: AI-based CSI (Channel State Information) enhancement; AI-based beam management; AI-based positioning. Exemplarily, the terminal 102 may include one or more AI models. For example, when the terminal 102 includes an AI model, the application case of the AI ​​model may be one of AI-based CSI enhancement, AI-based beam management, and AI-based positioning, that is, the AI ​​model may be an AI model for CSI enhancement, or an AI model for beam management, or an AI model for positioning. For another example, when the terminal 102 includes multiple AI models, the application cases of each AI model may be the same or different.

[0252] The method involved in the embodiments of the present disclosure may include at least one of steps S2201 and S2202. For example, step S2201 may be implemented as an independent embodiment, step S2202 may be implemented as an independent embodiment, and step S2201 + step S2202 may be implemented as independent embodiments, but the present invention is not limited thereto.

[0253] In some embodiments, step S2202 is optional, and one or more of these steps may be omitted or replaced in different embodiments.

[0254] In some embodiments, step S2201 is optional, and one or more of these steps may be omitted or replaced in different embodiments.

[0255] In some embodiments, reference may be made to other optional implementations described before or after the description corresponding to FIG. 2B .

[0256] FIG2C is an interactive diagram illustrating a processing method according to an embodiment of the present disclosure. As shown in FIG2C , the processing method according to an embodiment of the present disclosure can be applied to the communication system 100, and the method includes but is not limited to the following steps.

[0257] Step S2301: Terminal 102 sends first information.

[0258] In some embodiments, the first information may be sent by the terminal 102 to the network device 101. For example, the terminal 102 sends the first information to the network device 101. Optionally, the network device 101 receives the first information. For example, the network device 101 receives the first information sent by the terminal 102.

[0259] In some embodiments, the first information is used to indicate the operating status of terminal 101. Exemplarily, the first information is used to indicate the operating status of the local terminal 101. Exemplarily, network device 101 processes the AI ​​model of terminal 102 according to the operating status of terminal 102 indicated by the first information.

[0260] In some embodiments, the above-mentioned operating state includes at least one of the following: unsuitable for AI reasoning; need to reduce the number of activated AI models; need to reduce the frequency of AI model execution; can increase the number of activated AI models; unsuitable for receiving AI model transmission; suitable for receiving AI model transmission. Exemplarily, the above-mentioned operating state may include unsuitable for AI reasoning. Exemplarily, the above-mentioned operating state may include the need to reduce the number of activated AI models. Exemplarily, the above-mentioned operating state may include the need to reduce the frequency of AI model execution. Exemplarily, the above-mentioned operating state may include the possibility of increasing the number of activated AI models. Exemplarily, the above-mentioned operating state may include unsuitable for receiving AI model transmission. Exemplarily, the above-mentioned operating state may include suitable for receiving AI model transmission. Exemplarily, the above-mentioned operating state may include any combination of the above-mentioned examples, which will not be repeated here.

[0261] Exemplarily, the aforementioned "unsuitability for AI reasoning" may refer to the current operating state of terminal 102 being unsuitable for AI reasoning. Exemplarily, the aforementioned need to reduce activation of AI models may refer to the current operating state of terminal 102 requiring reduced activation of AI models. Exemplarily, the aforementioned need to reduce the frequency of AI model execution may refer to the current operating state of terminal 102 requiring reduced execution frequency of AI models, such as reducing AI model operations. Exemplarily, the aforementioned AI models that can be activated more may refer to the current operating state of terminal 102 being suitable for increasing activation of AI models. Exemplarily, the aforementioned "unsuitability for receiving AI model transmission" may refer to the current operating state of terminal 102 being unsuitable for receiving AI model transmission, such as the current operating state of terminal 102 being unsuitable for receiving AI model transmission. Exemplarily, the aforementioned "suitability for receiving AI model transmission" may refer to the current operating state of terminal 102 being suitable for receiving AI model transmission, such as the current operating state of terminal 102 being suitable for receiving AI model transmission from network device 101. Exemplarily, the aforementioned "suitability for receiving AI model transmission" may refer to the current operating state of terminal 102 being suitable for receiving AI model transmission, such as the current operating state of terminal 102 being suitable for receiving AI model transmission from network device 101.

[0262] In some embodiments, the above-mentioned first information can be sent by the terminal 102 to the network device 101 through RRC signaling, or can be sent to the network device 101 through other means. This disclosure does not limit this and will not elaborate on it.

[0263] In step S2302, the network device 101 performs corresponding AI operations according to the operating status of the terminal.

[0264] In some embodiments, the network device 101 receives the first information sent by the terminal 102, and performs a corresponding AI operation according to the operating status of the terminal 102 indicated by the first information, for example, the AI ​​model of the terminal 102 may be processed.

[0265] It should be noted that, if the operating status indicated by the first information is different, the AI ​​operation performed by the network device 101 will also be different.

[0266] In some embodiments, network device 101 determines that the first information indicates that the terminal 102 is not suitable for AI reasoning; network device 101 disables the AI ​​model activated by terminal 102. Exemplarily, if the first information sent by terminal 102 to the network device indicates that terminal 102 is not suitable for AI reasoning, network device 101 may disable the activated AI model, for example, network device 101 may disable all activated AI models.

[0267] In some embodiments, network device 101 determines that first information indicates a need to reduce activated AI models; network device 101 sends second information to terminal 102, where the second information instructs terminal 102 to deactivate at least one AI model in terminal 102. Exemplarily, if terminal 102 sends first information to the network device indicating that terminal 102 needs to reduce activated AI models, network device 101 may instruct terminal 102 to deactivate at least one AI model in terminal 102 via the second information. Specifically, which AI model or models to deactivate can be determined based on business needs, and this disclosure does not limit this.

[0268] In some embodiments, network device 101 determines that first information indicates a need to reduce the frequency of AI model execution; network device 101 sends second information to terminal 102, where the second information includes configuration information for the AI ​​model's operating frequency. Exemplarily, if terminal 102 sends first information to the network device indicating that terminal 102 needs to reduce the frequency of AI model execution, network device 101 may reconfigure the AI ​​model's operating frequency for terminal 102 using the second information, such as configuring a longer AI operation cycle, to reduce the frequency of AI model execution on terminal 102.

[0269] In some embodiments, the network device 101 determines that the first information indicates that an additional AI model can be activated; the network device 101 activates one or more AI models according to business needs, and / or sends second information to the terminal 102, the second information including model information of one or more AI models, and the second information is used by the terminal 102 to activate the one or more AI models. Exemplarily, the first information sent by the terminal 102 to the network device indicates that the terminal 102 can add an activated AI model, then the network device 101 can activate one or more AI models according to business needs, and / or send second information to the terminal 102, the second information including model information of one or more AI models, and the second information is used by the terminal 102 to activate one or more AI models. The terminal 102 receives the second information and activates the corresponding AI model according to the model information in the second information. Exemplarily, the model information may include model parameters and / or model structure, etc., which are not specifically limited in this disclosure.

[0270] In some embodiments, the network device 101 determines that the first information indicates that it is not suitable for receiving the AI ​​model transmission; the network device 101 turns off or suspends the transmission of the AI ​​model, and / or sends second information to the terminal 102, the second information being used to instruct the terminal 102 to turn off or suspend the reception of the AI ​​model. Exemplarily, if the first information sent by the terminal 102 to the network device indicates that the terminal 102 is not suitable for receiving the AI ​​model transmission, the network device 101 may turn off or suspend the transmission of the AI ​​model, and / or send second information to the terminal 102, the second information being used to instruct the terminal 102 to turn off or suspend the reception of the AI ​​model.

[0271] In some embodiments, the network device 101 determines that the first information indicates that the network device is suitable for receiving the AI ​​model transmission; the network device 101 restarts or reconfigures the sending of the AI ​​model, and / or sends second information to the terminal 102, where the second information is used to instruct the terminal 102 to start receiving the AI ​​model. Exemplarily, if the first information sent by the terminal 102 to the network device indicates that the terminal 102 is suitable for receiving the AI ​​model transmission, the network device 101 may restart or reconfigure the sending of the AI ​​model, and / or send second information to the terminal 102, where the second information is used to instruct the terminal 102 to start receiving the AI ​​model.

[0272] In some embodiments, the application cases of the above-mentioned AI model may include but are not limited to at least one of the following: AI-based CSI (Channel State Information) enhancement; AI-based beam management; AI-based positioning. Exemplarily, the terminal 102 may include one or more AI models. For example, when the terminal 102 includes an AI model, the application case of the AI ​​model may be one of AI-based CSI enhancement, AI-based beam management, and AI-based positioning, that is, the AI ​​model may be an AI model for CSI enhancement, or an AI model for beam management, or an AI model for positioning. For another example, when the terminal 102 includes multiple AI models, the application cases of each AI model may be the same or different.

[0273] The method involved in the embodiments of the present disclosure may include at least one of steps S2301 and S2302. For example, step S2301 may be implemented as an independent embodiment, step S2302 may be implemented as an independent embodiment, and step S2301 + step S2302 may be implemented as independent embodiments, but the present invention is not limited thereto.

[0274] In some embodiments, step S2302 is optional, and one or more of these steps may be omitted or replaced in different embodiments.

[0275] In some embodiments, step S2301 is optional, and one or more of these steps may be omitted or replaced in different embodiments.

[0276] In some embodiments, reference may be made to other optional implementations described before or after the description corresponding to FIG. 2C .

[0277] FIG3A is a flow chart of a processing method according to an embodiment of the present disclosure. As shown in FIG3A , the embodiment of the present disclosure relates to a processing method, which can be executed by the network device 101 and may include but is not limited to the following steps.

[0278] Step S3101, receiving first information.

[0279] In some embodiments, the first information may be sent by the terminal 102 to the network device 101. For example, the terminal 102 sends the first information to the network device 101. Optionally, the network device 101 receives the first information. For example, the network device 101 receives the first information sent by the terminal 102.

[0280] In some embodiments, the first information is used to indicate the operating status of terminal 101. Exemplarily, the first information is used to indicate the operating status of the local terminal 101. Exemplarily, network device 101 processes the AI ​​model of terminal 102 according to the operating status of terminal 102 indicated by the first information.

[0281] In some embodiments, the operating state includes at least one of the following: computing resource state; storage resource state; power state; heating state.

[0282] In some embodiments, the first information is used to indicate that the operating state of terminal 101 has a first characteristic, and may also be referred to as indicating that the operating state of terminal 101 has a first characteristic. In some embodiments, the first characteristic may include at least one of the following: storage resources are less than or equal to a first storage resource threshold; computing resources are less than or equal to a first computing resource threshold; power is less than or equal to a first power threshold; or the terminal is overheated.

[0283] The optional implementation of step S3101 can refer to the optional implementation of step S2101 in Figure 2A and other related parts in the embodiment involved in Figure 2A, which will not be repeated here.

[0284] Step S3102: Execute a corresponding AI operation according to the first feature indicated by the first information.

[0285] The optional implementation of step S3102 can refer to the optional implementation of step S2102 in Figure 2A and other related parts in the embodiment involved in Figure 2A, which will not be repeated here.

[0286] FIG3B is a flow chart of a processing method according to an embodiment of the present disclosure. As shown in FIG3B , the embodiment of the present disclosure relates to a processing method, which can be executed by the network device 101 and may include but is not limited to the following steps.

[0287] Step S3201, receiving first information.

[0288] In some embodiments, the first information may be sent by the terminal 102 to the network device 101. For example, the terminal 102 sends the first information to the network device 101. Optionally, the network device 101 receives the first information. For example, the network device 101 receives the first information sent by the terminal 102.

[0289] In some embodiments, the first information is used to indicate the operating status of terminal 101. Exemplarily, the first information is used to indicate the operating status of the local terminal 101. Exemplarily, network device 101 processes the AI ​​model of terminal 102 according to the operating status of terminal 102 indicated by the first information.

[0290] In some embodiments, the operating state includes at least one of the following: computing resource state; storage resource state; power state; heating state.

[0291] In some embodiments, the first information is used to indicate that the operating state of terminal 101 has a second characteristic, and may also be referred to as indicating that the operating state of terminal 101 has a second characteristic. In some embodiments, the second characteristic includes at least one of the following: storage resources are greater than or equal to a second storage resource threshold; computing resources are greater than or equal to a second computing resource threshold; power is greater than or equal to a second power threshold; and the terminal is not overheating.

[0292] The optional implementation of step S3201 can refer to the optional implementation of step S2201 in Figure 2B and other related parts in the embodiment involved in Figure 2B, which will not be repeated here.

[0293] Step S3202: Execute a corresponding AI operation according to the second feature indicated by the first information.

[0294] The optional implementation of step S3202 can refer to the optional implementation of step S2202 in Figure 2B and other related parts in the embodiment involved in Figure 2B, which will not be repeated here.

[0295] FIG3C is a flow chart of a processing method according to an embodiment of the present disclosure. As shown in FIG3C , the embodiment of the present disclosure relates to a processing method, which can be executed by the network device 101 and may include but is not limited to the following steps.

[0296] Step S3301, receiving first information.

[0297] In some embodiments, the first information may be sent by the terminal 102 to the network device 101. For example, the terminal 102 sends the first information to the network device 101. Optionally, the network device 101 receives the first information. For example, the network device 101 receives the first information sent by the terminal 102.

[0298] In some embodiments, the first information is used to indicate the operating status of terminal 101. Exemplarily, the first information is used to indicate the operating status of the local terminal 101. Exemplarily, network device 101 processes the AI ​​model of terminal 102 according to the operating status of terminal 102 indicated by the first information.

[0299] In some embodiments, the above-mentioned operating status includes at least one of the following: not suitable for AI reasoning; the need to reduce the number of activated AI models; the need to reduce the frequency of AI model execution; the ability to increase the number of activated AI models; not suitable for receiving AI model transmission; suitable for receiving AI model transmission.

[0300] The optional implementation of step S3301 can refer to the optional implementation of step S2301 in Figure 2C and other related parts in the embodiment involved in Figure 2C, which will not be repeated here.

[0301] Step S3302: Execute corresponding AI operations according to the operating status of the terminal.

[0302] The optional implementation of step S3302 can refer to the optional implementation of step S2302 in Figure 2C and other related parts in the embodiment involved in Figure 2C, which will not be repeated here.

[0303] FIG3D is a flow chart of a processing method according to an embodiment of the present disclosure. As shown in FIG3C , an embodiment of the present disclosure relates to a processing method, which can be executed by the network device 101 and may include but is not limited to the following steps.

[0304] Step S3401 : Receive first information sent by terminal 102 , where the first information is used to indicate the operating status of terminal 102 .

[0305] Step S3402: Execute corresponding AI operations according to the operating status of the terminal.

[0306] In some embodiments, the operating status includes at least one of the following: computing resource status; storage resource status; power status; and heating status. In one possible implementation, the first information indicates that the operating status of terminal 102 exhibits a first characteristic, where the first characteristic includes at least one of the following: storage resources are less than or equal to a first storage resource threshold; computing resources are less than or equal to a first computing resource threshold; power is less than or equal to a first power threshold; and terminal 102 is overheated.

[0307] Exemplarily, the network device 101 determines that the first characteristic indicated by the first information includes that the storage resources are less than or equal to a first storage resource threshold; the network device 101 suspends or shuts down the transmission of the AI ​​model.

[0308] Exemplarily, the network device 101 determines that the first characteristic indicated by the first information includes that the computing resources are less than or equal to the first computing resource threshold; the network device 101 sends second information to the terminal 102, and the second information is used to instruct the terminal 102 to shut down at least one AI model.

[0309] Exemplarily, the network device 101 determines that the first feature indicated by the first information includes that the power level is less than or equal to the first power threshold; the network device 101 does not activate the new AI model, and / or sends second information to the terminal 102; the second information is used to instruct the terminal 102 to turn off the first AI model, and the first AI model is an AI model in the terminal 102 whose computational complexity meets the first condition.

[0310] Exemplarily, the network device 101 determines that the first characteristic indicated by the first information includes overheating of the terminal 102; the network device 101 sends second information to the terminal 102, the second information includes first operation cycle configuration information of the AI ​​model, the operation cycle included in the first operation cycle configuration information is greater than the first operation cycle, the first operation cycle is the operation cycle associated with the AI ​​model before the network device 101 receives the first information, and the first characteristic indicated by the first information includes the terminal 102 overheating.

[0311] In another possible implementation, the first information indicates that a second characteristic appears in the operating status of the terminal 102, and the second characteristic includes at least one of the following: storage resources are greater than or equal to a second storage resource threshold; computing resources are greater than or equal to a second computing resource threshold; power is greater than or equal to a second power threshold; and the terminal 102 is not overheating.

[0312] Exemplarily, the network device 101 determines that the second characteristic indicated by the first information includes that the storage resources are greater than or equal to a second storage resource threshold; the network device 101 starts or reconfigures the sending of the AI ​​model.

[0313] Exemplarily, the network device 101 determines that the second feature indicated by the first information includes that the computing resources are greater than or equal to the second computing resource threshold; the network device 101 sends second information to the terminal 102, and the second information is used to instruct the terminal 102 to activate at least one AI model.

[0314] Exemplarily, the network device 101 determines that the second feature indicated by the first information includes that the power level is greater than or equal to a second power threshold; the network device 101 activates a new AI model, and / or sends second information to the terminal 102; the second information is used to instruct the terminal 102 to activate the first AI model, and the first AI model is an AI model in the terminal 102 whose computational complexity meets the first condition.

[0315] Exemplarily, the network device 101 determines that the second feature indicated by the first information includes that the terminal 102 is not overheating; the network device 101 sends second information to the terminal 102, and the second information is used to indicate that the operating cycle of the AI ​​model of the terminal 102 is restored to the first operating cycle, and the first operating cycle is when the network device 101 receives the first information, and the first feature indicated by the first information includes the operating cycle associated with the AI ​​model before the terminal 102 overheats.

[0316] In some embodiments, the operating state includes at least one of the following: not suitable for AI reasoning; the need to reduce the number of activated AI models; the need to reduce the frequency of AI model execution; the ability to increase the number of activated AI models; not suitable for receiving AI model transmissions; and suitable for receiving AI model transmissions.

[0317] Exemplarily, the network device 101 determines that the first information indication is not suitable for AI reasoning; the network device 101 shuts down the activated AI model of the terminal 102.

[0318] Exemplarily, the network device 101 determines that the first information indicates that the activated AI model needs to be reduced; the network device 101 sends second information to the terminal 102, and the second information instructs the terminal 102 to turn off at least one AI model.

[0319] Exemplarily, the network device 101 determines that the first information indicates that the frequency of execution of the AI ​​model needs to be reduced; the network device 101 sends second information to the terminal 102, and the second information includes configuration information of the operation frequency of the AI ​​model.

[0320] Exemplarily, the network device 101 determines that the first information indicates that an additional AI model can be activated; the network device 101 activates one or more AI models according to business needs, and / or sends second information to the terminal 102, the second information including model information of one or more AI models, and the second information is used by the terminal 102 to activate one or more AI models.

[0321] Exemplarily, the network device 101 determines that the first information indicates that it is not suitable for receiving the AI ​​model transmission; the network device 101 turns off or suspends the sending of the AI ​​model, and / or sends a second information to the terminal 102, and the second information is used to instruct the terminal 102 to turn off or suspend the reception of the AI ​​model.

[0322] Exemplarily, the network device 101 determines that the first information indicates that it is suitable for receiving the AI ​​model transmission; the network device 101 restarts or reconfigures the sending of the AI ​​model, and / or sends second information to the terminal 102, and the second information is used to instruct the terminal 102 to start receiving the AI ​​model.

[0323] The optional implementation methods of step S3401 and step S3402 can be found in step S2101, step S2202 in Figure 2A, step S2201, step S2202 in Figure 2B, step S2301 and step S2302 in Figure 2C, and other related parts in the embodiments involved in Figures 2A, 2B, and 2C, which will not be repeated here.

[0324] FIG4A is a flow chart of a processing method according to an embodiment of the present disclosure. As shown in FIG4A , the embodiment of the present disclosure relates to a processing method, which can be executed by terminal 102 and may include but is not limited to the following steps.

[0325] Step S4101, sending the first information.

[0326] In some embodiments, the first information may be sent by the terminal 102 to the network device 101. For example, the terminal 102 sends the first information to the network device 101. Optionally, the network device 101 receives the first information. For example, the network device 101 receives the first information sent by the terminal 102.

[0327] In some embodiments, the first information is used to indicate the operating status of terminal 101. Exemplarily, the first information is used to indicate the local operating status of terminal 101. In some embodiments, the first information is used by network device 101 to process the AI ​​model of terminal 102. Exemplarily, network device 101 performs corresponding AI operations based on the operating status of terminal 102 indicated by the received first information.

[0328] In some embodiments, the operating status includes at least one of the following: computing resource status; storage resource status; power status; and heating status. In one possible implementation, the first information indicates that the operating status of terminal 102 exhibits a first characteristic, where the first characteristic includes at least one of the following: storage resources are less than or equal to a first storage resource threshold; computing resources are less than or equal to a first computing resource threshold; power is less than or equal to a first power threshold; and terminal 102 is overheated.

[0329] Exemplarily, the first feature indicated by the first information includes that the storage resources are less than or equal to a first storage resource threshold, and the first information is used to instruct the network device 101 to pause or shut down the transmission of the AI ​​model.

[0330] Exemplarily, the first characteristic indicated by the first information includes that the computing resources are less than or equal to the first computing resource threshold, and the terminal 102 can also receive the second information sent by the network device 101, and the second information is used to instruct the terminal 102 to shut down at least one AI model in the terminal 102.

[0331] Exemplarily, the first feature indicated by the first information includes that the power level is less than or equal to a first power threshold, and the first information is used to instruct the network device 101 not to activate the new AI model, and / or to send second information to the terminal 102, wherein the second information is used to instruct the terminal 102 to turn off the first AI model, and the first AI model is an AI model in the terminal 102 whose computational complexity meets the first condition.

[0332] Exemplarily, the first characteristic indicated by the first information includes overheating of the terminal 102. The terminal 102 can also receive second information sent by the network device 101. The second information includes first operation cycle configuration information of the AI ​​model. The operation cycle included in the first operation cycle configuration information is greater than the first operation cycle. The first operation cycle is the operation cycle associated with the AI ​​model before the network device 101 receives the first information, and the first characteristic indicated by the first information includes the operation cycle before the terminal 102 overheats.

[0333] In one possible implementation, the first information indicates that a second characteristic appears in the operating status of the terminal 102, and the second characteristic includes at least one of the following: storage resources are greater than or equal to a second storage resource threshold; computing resources are greater than or equal to a second computing resource threshold; power is greater than or equal to a second power threshold; and the terminal 102 is not overheating.

[0334] Exemplarily, the second characteristic indicated by the first information includes that the storage resources are greater than or equal to a second storage resource threshold, and the first information is used to instruct the network device 101 to start or reconfigure the transmission of the AI ​​model.

[0335] Exemplarily, the second feature indicated by the first information includes that the computing resources are greater than or equal to the second computing resource threshold, and the terminal 102 can also receive the second information sent by the network device 101, and the second information is used to instruct the terminal 102 to activate at least one AI model in the terminal 102.

[0336] Exemplarily, the second feature indicated by the first information includes a power level greater than or equal to a second power threshold, and the first information is used to indicate activation of a new AI model, and / or sending second information to the terminal 102; wherein, the second information is used to indicate that the terminal 102 activates the first AI model, and the first AI model is an AI model in the terminal 102 whose computational complexity meets the first condition.

[0337] Exemplarily, the second feature indicated by the first information includes that the terminal 102 is not overheating. The terminal 102 can also receive the second information sent by the network device 101. The second information is used to indicate that the operating cycle of the AI ​​model of the terminal 102 is restored to the first operating cycle. The first operating cycle is when the network device 101 receives the first information, and the first feature indicated by the first information includes the operating cycle associated with the AI ​​model before the terminal 102 overheats.

[0338] In some embodiments, the operating state includes at least one of the following: not suitable for AI reasoning; the need to reduce the number of activated AI models; the need to reduce the frequency of AI model execution; the ability to increase the number of activated AI models; not suitable for receiving AI model transmissions; and suitable for receiving AI model transmissions.

[0339] Exemplarily, the first information indicates that it is not suitable for AI reasoning, and the first information is used to instruct the network device 101 to shut down the AI ​​model activated by the terminal 102.

[0340] Exemplarily, the first information indicates that the activated AI models need to be reduced, and the terminal 102 may also receive second information sent by the network device 101, where the second information instructs the terminal 102 to turn off at least one AI model.

[0341] Exemplarily, the first information indicates that the frequency of execution of the AI ​​model needs to be reduced, and the terminal 102 can also receive second information sent by the network device 101, where the second information includes configuration information of the operation frequency of the AI ​​model.

[0342] Exemplarily, the first information indicates that an additional AI model can be activated, and the first information is used to instruct the network device 101 to activate one or more AI models according to business needs, and / or send second information to the terminal 102; wherein the second information includes model information of one or more AI models, and the second information is used by the terminal 102 to activate one or more AI models.

[0343] Exemplarily, the first information indicates that it is not suitable to receive the AI ​​model transmission, and the first information is used to instruct the network device 101 to turn off or suspend the sending of the AI ​​model, and / or send the second information to the terminal 102; wherein, the second information is used to instruct the terminal 102 to turn off or suspend the reception of the AI ​​model.

[0344] Exemplarily, the first information indicates that it is suitable to receive AI model transmission, and the first information is used to instruct the network device 101 to restart or reconfigure the sending of the AI ​​model, and / or send second information to the terminal 102; wherein, the second information is used to instruct the terminal 102 to start receiving the AI ​​model.

[0345] The optional implementation methods of step S4101 can be found in step S2101 and step S2202 of Figure 2A, step S2201 and step S2202 of Figure 2B, step S2301 and step S2302 of Figure 2C, and other related parts in the embodiments involved in Figures 2A, 2B, and 2C, which will not be repeated here.

[0346] Figure 5 is an interactive diagram of a processing method according to an embodiment of the present disclosure. As shown in Figure 5, the method involved in the embodiment of the present disclosure can be applied to a communication system 100, and the method includes but is not limited to the following steps.

[0347] In step S5101, the terminal 102 sends first information to the network device 101, where the first information is used to indicate the operating status of the terminal 102, wherein the first information is used by the network device 101 to process the artificial intelligence AI model of the terminal 102.

[0348] The optional implementation of step S5101 can be found in the optional implementation of step S2101 in Figure 2A, step S2201 in Figure 2B, step S2301 in Figure 2C, and other related parts in the embodiments involved in Figures 2A, 2B, and 2C, which will not be repeated here.

[0349] In step S5102, the network device 101 performs corresponding AI operations according to the operating status of the terminal.

[0350] The optional implementation of step S5102 can refer to the optional implementation of step S2102 in Figure 2A, step S2202 in Figure 2B, step S2302 in Figure 2C, and other related parts in the embodiments involved in Figures 2A, 2B, and 2C, which will not be repeated here.

[0351] In some embodiments, the above method may include the method described in the above embodiments of the network device side, terminal, etc., which will not be repeated here.

[0352] It should be noted that the present disclosure proposes a method for a terminal to report the local AI operating environment, which assists the network side in managing the AI ​​model or AI function of the terminal.

[0353] In some embodiments, the terminal sends a first signaling (also referred to as first information) to the network side, where the first signaling is used to indicate the operating status of the local side of the terminal.

[0354] In some embodiments, the operating status includes any one of computing resources, storage resources, power, and heating status of the terminal.

[0355] In some embodiments, the first signaling indicates that the terminal's local operating state has a first characteristic or a second characteristic. The first characteristic includes at least one of the following: insufficient computing resources, insufficient storage resources, low battery, or terminal overheating. The second characteristic includes at least one of the following: sufficient computing resources, sufficient storage resources, high battery, or terminal not overheating.

[0356] In some embodiments, on the network side, in response to the first signaling indicating the first feature, the network side performs at least one of the following actions: suspending or shutting down the transmission of the AI ​​model; sending a second signaling (also referred to as a second message) to the terminal to shut down, suspend, or reduce AI-based operations, or switch AI functions or AI models. For example, when the first signaling indicates a shortage of terminal storage resources, the transmission of the AI ​​model can be shut down or suspended. When the first signaling indicates a shortage of AI computing resources, the network side can send a signaling to shut down one or more AI functions. For example, when the first signaling indicates that the terminal is overheating, the network can configure a larger AI operation cycle.

[0357] In some embodiments, on the network side, in response to the first signaling indicating the second feature, the network side starts or reconfigures the transmission of the AI ​​model, or activates the AI ​​function / AI model, or adds AI-based operations.

[0358] In some embodiments, the first signaling indicating the second feature is premised on the terminal having sent the first signaling indicating the first feature.

[0359] In some embodiments, the operating status of the local side of the terminal includes at least one of the following: not suitable for AI reasoning, need to reduce the activation of AI models or AI functions, need to reduce the frequency of execution of AI models or AI functions, can activate AI models or AI functions, not suitable for receiving AI model transmission, suitable for receiving AI model transmission.

[0360] In some embodiments, on the network side, in response to the first signaling indication that AI reasoning is not suitable, the network side shuts down all activated AI functions or AI models. In response to the first signaling indication that the number of activated AI models or AI functions needs to be reduced, the network side sends a signaling indication to shut down at least one AI model or AI function. In response to the first signaling indication that the frequency of execution of the AI ​​model or AI function needs to be reduced, the network side reconfigures the frequency of AI-related operations. In response to the first signaling indication that the AI ​​model or AI function can be activated, the network side can activate more AI models or AI functions as needed. In response to the first signaling indication that it is not suitable to receive AI model transmission, the network side shuts down or suspends the reception of the AI ​​model and AI function. In response to the first signaling indication that it is suitable to receive AI model transmission, the network side can restart or reconfigure the transmission of the AI ​​model.

[0361] The embodiments of the present disclosure further provide an apparatus for implementing any of the above methods. For example, an apparatus is provided that includes units or modules for implementing each step performed by a network device in any of the above methods. For another example, another apparatus is provided that includes units or modules for implementing each step performed by a terminal in any of the above methods.

[0362] 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.

[0363] In the embodiments of the present disclosure, the processor is a circuit with information 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.

[0364] Figure 6A is a structural diagram of a network device proposed in an embodiment of the present disclosure. As shown in Figure 6A, the network device 6100 may include: at least one of a transceiver module 6101, a processing module 6102, etc. In some embodiments, the above-mentioned transceiver module is used to receive a first message sent by a terminal, and the first information is used to indicate the operating status of the terminal; the processing module is used to perform a corresponding AI operation according to the operating status of the terminal. Optionally, the above-mentioned transceiver module is used to execute at least one of the communication steps such as sending and / or receiving performed by the network device 101 in any of the above methods, which will not be repeated here. Optionally, the above-mentioned processing module is used to execute at least one of the other steps (such as step S2102, step S2202, step S2302, but not limited to this) performed by the network device 101 in any of the above methods, which will not be repeated here.

[0365] Figure 6B is a structural diagram of the terminal proposed in an embodiment of the present disclosure. As shown in Figure 6B, the terminal 6200 may include: at least one of a transceiver module 6201, a processing module 6202, etc. In some embodiments, the above-mentioned transceiver module is used to send a first information to a network device, and the first information is used to indicate the operating status of the terminal, wherein the first information is used for the network device to perform a corresponding artificial intelligence AI operation according to the operating status of the terminal. Optionally, the above-mentioned transceiver module is used to execute at least one of the communication steps such as sending and / or receiving (for example, step S2101, step S2201, step S2301, but not limited to this) performed by the terminal 6200 in any of the above methods, which will not be repeated here. Optionally, the above-mentioned processing module is used to execute at least one of the other steps performed by the terminal 102 in any of the above methods, which will not be repeated here.

[0366] 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.

[0367] 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.

[0368] Figure 7A is a schematic diagram of the structure of a communication device 7100 proposed in an embodiment of the present disclosure. Communication device 7100 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 to implement any of the above methods, or a chip, a chip system, or a processor that supports a terminal to implement any of the above methods. Communication device 7100 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.

[0369] As shown in Figure 7A, the communication device 7100 includes one or more processors 7101. The processor 7101 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 7100 is used to perform any of the above methods. Optionally, one or more processors 7101 are used to call instructions to enable the communication device 7100 to perform any of the above methods.

[0370] In some embodiments, the communication device 7100 further includes one or more transceivers 7102. When the communication device 7100 includes one or more transceivers 7102, the transceiver 7102 performs at least one of the communication steps such as sending and / or receiving in the above method (e.g., step S2101, step S2201, step S2301, but not limited thereto), and the processor 7101 performs at least one of the other steps (e.g., step S2102, step S2202, step S2302, but not limited thereto). 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 interchangeable, the terms transmitter, transmitting unit, transmitter, and transmitting circuit may be interchangeable, and the terms receiver, receiving unit, receiver, and receiving circuit may be interchangeable.

[0371] In some embodiments, the communication device 7100 further includes one or more memories 7103 for storing data. Alternatively, all or part of the memories 7103 may be located outside the communication device 7100. In alternative embodiments, the communication device 7100 may include one or more interface circuits 7104. Optionally, the interface circuits 7104 are connected to the memory 7102 and may be configured to receive data from the memory 7102 or other devices, or to send data to the memory 7102 or other devices. For example, the interface circuits 7104 may read data stored in the memory 7102 and send the data to the processor 7101.

[0372] The communication device 7100 described in the above embodiment may be a network device or a terminal, but the scope of the communication device 7100 described in the present disclosure is not limited thereto, and the structure of the communication device 7100 may not be limited by FIG. 7A. 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.

[0373] 7B is a schematic diagram of the structure of a chip 7200 proposed in an embodiment of the present disclosure. If the communication device 7100 can be a chip or a chip system, please refer to the schematic diagram of the structure of the chip 7200 shown in FIG7B , but the present disclosure is not limited thereto.

[0374] The chip 7200 includes one or more processors 7201. The chip 7200 is configured to execute any of the above methods.

[0375] In some embodiments, chip 7200 further includes one or more interface circuits 7202. Alternatively, terms such as interface circuit, interface, and transceiver pins may be used interchangeably. In some embodiments, chip 7200 further includes one or more memories 7203 for storing data. Alternatively, all or part of memory 7203 may be located external to chip 7200. Optionally, interface circuit 7202 is connected to memory 7203 and may be used to receive data from memory 7203 or other devices, or may be used to send data to memory 7203 or other devices. For example, interface circuit 7202 may read data stored in memory 7203 and send the data to processor 7201.

[0376] In some embodiments, the interface circuit 7202 performs at least one of the communication steps (e.g., step S2101, step S2201, and step S2301) of the aforementioned method. The interface circuit 7202 performing the communication steps (e.g., step S2101, step S2201, and step S2301) of the aforementioned method, for example, means that the interface circuit 7202 performs data exchange between the processor 7201, chip 7200, memory 7203, or a transceiver device. In some embodiments, the processor 7201 performs at least one of the other steps (e.g., step S2102, step S2202, and step S2302, but not limited thereto).

[0377] The present disclosure also proposes a storage medium having instructions stored thereon. When the instructions are executed on the communication device 7100, the communication device 7100 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.

[0378] The present disclosure also provides a program product, which, when executed by the communication device 7100, enables the communication device 7100 to perform any of the above methods. Optionally, the program product is a computer program product.

[0379] 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.

[0380] In the above embodiments, all or part of the embodiments can be implemented by software, hardware, firmware or any combination thereof. When implemented using software, all or part of the embodiments can be implemented in the form of a computer program product. The computer program product includes one or more computer programs. When the computer program is loaded and executed on a computer, all or part of the processes or functions described in the embodiments of the present disclosure are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer program can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer program can be transmitted from one website, computer, server or data center to another website, computer, server or data center via a wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) method. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that includes one or more available media integrated therein. The available medium may be a magnetic medium (eg, a floppy disk, a hard disk, a magnetic tape), an optical medium (eg, a high-density digital video disc (DVD)), or a semiconductor medium (eg, a solid state disk (SSD)).

[0381] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this disclosure.

[0382] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0383] The above description is merely a specific embodiment of the present disclosure, but the scope of protection of the present disclosure is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this disclosure should be included in the scope of protection of the present disclosure. Therefore, the scope of protection of the present disclosure should be based on the scope of protection of the claims.

Claims

1. A processing method, characterized in that: include: The network device receives first information sent by the terminal, where the first information is used to indicate the operating state of the terminal; According to the operating status of the terminal, the network device performs corresponding artificial intelligence (AI) operations.

2. The method according to claim 1, characterized in that The operating status includes at least one of the following: Computing resource status; Storage resource status; Battery status; Fever state.

3. The method according to claim 2, characterized in that The first information indicates that a first feature occurs in the running state of the terminal, and the first feature includes at least one of the following: The storage resource is less than or equal to the first storage resource threshold; The computing resource is less than or equal to a first computing resource threshold; The power level is less than or equal to a first power level threshold; The terminal is overheated.

4. The method according to claim 3, characterized in that The network device performs corresponding artificial intelligence AI operations including at least one of the following: The network device pauses or shuts down the sending of the AI ​​model; The network device does not activate the new AI model; The network device sends second information to the terminal, where the second information includes first operation cycle configuration information of the AI ​​model, and / or the second information is used to instruct the terminal to perform at least one of the following actions: suspend or turn off reception of the AI ​​model, turn off at least one AI model in the terminal, and turn off the first AI model; Among them, the operation cycle included in the first operation cycle configuration information is greater than the first operation cycle, the first operation cycle is the operation cycle associated with the AI ​​model before the network device receives the first information and the first feature indicated by the first information includes overheating of the terminal, and the first AI model is an AI model in the terminal whose computational complexity meets the first condition.

5. The method according to claim 4, characterized in that According to the running state of the terminal, the network device performs a corresponding artificial intelligence (AI) operation, including: The first feature indicated by the first information includes that when the storage resource is less than or equal to a first storage resource threshold, the network device suspends or shuts down the sending of the AI ​​model.

6. The method according to claim 4, characterized in that According to the running state of the terminal, the network device performs a corresponding artificial intelligence (AI) operation, including: The first feature indicated by the first information includes sending second information to the terminal when the computing resource is less than or equal to a first computing resource threshold, and the second information is used to instruct the terminal to shut down at least one AI model in the terminal.

7. The method according to claim 4, characterized in that According to the running state of the terminal, the network device performs a corresponding artificial intelligence (AI) operation, including: The first feature indicated by the first information includes not activating a new AI model when the power level is less than or equal to a first power threshold, and / or sending second information to the terminal; the second information is used to instruct the terminal to turn off the first AI model.

8. The method according to claim 4, characterized in that According to the running state of the terminal, the network device performs a corresponding artificial intelligence (AI) operation, including: The first feature indicated by the first information includes sending second information to the terminal when the terminal is overheated, and the second information includes the first operation cycle configuration information of the AI ​​model.

9. The method according to claim 2, characterized in that The first information indicates that a second feature occurs in the running state of the terminal, and the second feature includes at least one of the following: The storage resource is greater than or equal to a second storage resource threshold; The computing resource is greater than or equal to a second computing resource threshold; The power level is greater than or equal to a second power level threshold; The terminal is not overheating.

10. The method according to claim 9, characterized in that The network device performs corresponding artificial intelligence AI operations including at least one of the following: The network device starts or reconfigures the sending of the AI ​​model; The network device activates the new AI model; The network device sends second information to the terminal, where the second information is used to instruct the terminal to perform at least one of the following actions: activating at least one AI model in the terminal, activating the first AI model, and restoring the operation cycle of the AI ​​model to the first operation cycle.

11. The method according to claim 10, characterized in that According to the running state of the terminal, the network device performs a corresponding artificial intelligence (AI) operation, including: The second feature indicated by the first information includes that when the storage resource is greater than or equal to a second storage resource threshold, the network device starts or reconfigures the sending of the AI ​​model.

12. The method according to claim 10, characterized in that According to the running state of the terminal, the network device performs a corresponding artificial intelligence (AI) operation, including: The second feature indicated by the first information includes that when the computing resource is greater than or equal to a second computing resource threshold, Send second information, where the second information is used to instruct the terminal to activate at least one AI model in the terminal.

13. The method according to claim 10, characterized in that According to the running state of the terminal, the network device performs a corresponding artificial intelligence (AI) operation, including: The second feature indicated by the first information includes activating a new AI model when the power level is greater than or equal to a second power level threshold, and / or sending second information to the terminal; the second information is used to instruct the terminal to activate the first AI model.

14. The method according to claim 10, characterized in that According to the running state of the terminal, the network device performs a corresponding artificial intelligence (AI) operation, including: The second feature indicated by the first information includes sending second information to the terminal when the terminal is not overheated, and the second information is used to instruct the terminal to restore the operation cycle of the AI ​​model to the first operation cycle.

15. The method according to claim 1, wherein: The operating status includes at least one of the following: Not suitable for AI reasoning; Need to reduce the number of activated AI models; The frequency of AI model execution needs to be reduced; You can add activated AI models; Not suitable for receiving AI model transmissions; Suitable for receiving AI model transmissions.

16. The method according to claim 15, characterized in that According to the running state of the terminal, the network device performs a corresponding artificial intelligence (AI) operation, including: When the first information indicates that the AI ​​model activated by the terminal is closed, it is not suitable for AI reasoning.

17. The method according to claim 15, characterized in that According to the running state of the terminal, the network device performs a corresponding artificial intelligence (AI) operation, including: When the first information indicates that the activated AI model needs to be reduced, second information is sent to the terminal, and the second information instructs the terminal to shut down at least one AI model in the terminal.

18. The method according to claim 15, characterized in that According to the running state of the terminal, the network device performs a corresponding artificial intelligence (AI) operation, including: When the first information indicates that the frequency of execution of the AI ​​model needs to be reduced, second information is sent to the terminal, and the second information includes configuration information of the operation frequency of the AI ​​model.

19. The method according to claim 15, characterized in that According to the running state of the terminal, the network device performs a corresponding artificial intelligence (AI) operation, including: When the first information indicates the AI ​​model that can be added for activation, one or more AI models are activated according to business needs, and / or second information is sent to the terminal, where the second information includes model information of the one or more AI models, and the second information is used by the terminal to activate the one or more AI models.

20. The method of claim 15, wherein: According to the running state of the terminal, the network device performs a corresponding artificial intelligence (AI) operation, including: When the first information indicates that the AI ​​model transmission is not suitable for reception, the network device turns off or suspends the sending of the AI ​​model, and / or sends second information to the terminal, wherein the second information is used to instruct the terminal to turn off or suspend the reception of the AI ​​model.

21. The method of claim 15, wherein: According to the running state of the terminal, the network device performs a corresponding artificial intelligence (AI) operation, including: When the first information indicates that the AI ​​model transmission is suitable for reception, the network device restarts or reconfigures the sending of the AI ​​model, and / or sends second information to the terminal, wherein the second information is used to instruct the terminal to start receiving the AI ​​model.

22. A processing method, characterized in that: include: The terminal sends first information to the network device, where the first information is used to indicate the operating status of the terminal, wherein the first information is used by the network device to perform corresponding artificial intelligence (AI) operations according to the operating status of the terminal.

23. The method of claim 22, wherein: The operating status includes at least one of the following: Computing resource status; Storage resource status; Battery status; Fever state.

24. The method of claim 23, wherein: The first information indicates that a first feature occurs in the running state of the terminal, and the first feature includes at least one of the following: The storage resource is less than or equal to the first storage resource threshold; The computing resource is less than or equal to a first computing resource threshold; The power level is less than or equal to a first power level threshold; The terminal is overheated.

25. The method of claim 24, wherein: The first feature indicated by the first information includes that the storage resource is less than or equal to a first storage resource threshold, and the first information is used to instruct the network device to pause or shut down the sending of the AI ​​model.

26. The method of claim 24, wherein: The first feature indicated by the first information includes that the computing resource is less than or equal to a first computing resource threshold, and the method further includes: Receive second information sent by the network device, where the second information is used to instruct the terminal to shut down at least one AI model in the terminal.

27. The method of claim 24, wherein: The first feature indicated by the first information includes that the power is less than or equal to a first power threshold, and the first information is used to instruct the network device not to activate a new AI model, and / or to send second information to the terminal, The second information is used to instruct the terminal to shut down a first AI model, where the first AI model is an AI model in the terminal whose computational complexity satisfies a first condition.

28. The method of claim 24, wherein: The first feature indicated by the first information includes overheating of the terminal, and the method further includes: Receive second information sent by the network device, the second information includes first operating cycle configuration information of the AI ​​model, the operating cycle included in the first operating cycle configuration information is greater than the first operating cycle, the first operating cycle is the operating cycle associated with the AI ​​model before the network device receives the first information, and the first feature indicated by the first information includes the terminal overheating.

29. The method of claim 23, wherein: The first information indicates that a second feature occurs in the running state of the terminal, and the second feature includes at least one of the following: The storage resource is greater than or equal to a second storage resource threshold; The computing resource is greater than or equal to a second computing resource threshold; The power level is greater than or equal to a second power level threshold; The terminal is not overheating.

30. The method of claim 29, wherein: The second feature indicated by the first information includes that the storage resource is greater than or equal to a second storage resource threshold, and the first information is used to instruct the network device to start or reconfigure the sending of the AI ​​model.

31. The method of claim 29, wherein: The second feature indicated by the first information includes that the computing resource is greater than or equal to a second computing resource threshold, and the method further includes: Receive second information sent by the network device, where the second information is used to instruct the terminal to activate at least one AI model in the terminal.

32. The method of claim 29, wherein: The second feature indicated by the first information includes that the power level is greater than or equal to a second power level threshold, and the first information is used to indicate activation of a new AI model, and / or sending second information to the terminal; The second information is used to instruct the terminal to activate a first AI model, where the first AI model is an AI model in the terminal whose computational complexity satisfies a first condition.

33. The method of claim 29, wherein: The second feature indicated by the first information includes that the terminal is not overheated, and the method further includes: Receive second information sent by the network device, where the second information is used to instruct the terminal to restore the operation cycle of the AI ​​model to the first operation cycle.

34. The method of claim 22, wherein: The operating status includes at least one of the following: Not suitable for AI reasoning; The number of activated AI models and / or AI functions needs to be reduced; The need to reduce the frequency of execution of AI models and / or AI functions; The activated AI models and / or AI functions can be increased; Not suitable for receiving AI model transmissions; Suitable for receiving AI model transmissions.

35. The method of claim 34, wherein: The first information indicates that the terminal is not suitable for AI reasoning, and the first information is used to instruct the network device to shut down the AI ​​model activated by the terminal.

36. The method of claim 34, wherein: The first information indicates the AI ​​model that needs to reduce activation, and the method further includes: Receive second information sent by the network device, where the second information instructs the terminal to shut down at least one AI model in the terminal.

37. The method of claim 34, wherein: The first information indicates the need to reduce the frequency of execution of the AI ​​model, and the method further includes: Receive second information sent by the network device, where the second information includes configuration information of the operation frequency of the AI ​​model.

38. The method of claim 34, wherein: The first information indicates the AI ​​model that can be added and activated, and the first information is used to instruct the network device to activate one or more AI models according to business needs, and / or send second information to the terminal; The second information includes model information of the one or more AI models, and the second information is used by the terminal to activate the one or more AI models.

39. The method of claim 34, wherein: The first information indicates that the AI ​​model transmission is not suitable for reception, and the first information is used to instruct the network device to close or suspend the sending of the AI ​​model, and / or send second information to the terminal; The second information is used to instruct the terminal to close or suspend reception of the AI ​​model.

40. The method of claim 34, wherein: The first information indicates the suitability for receiving AI model transmission, and the first information is used to instruct the network device to restart or reconfigure the sending of the AI ​​model, and / or to send second information to the terminal; The second information is used to instruct the terminal to start receiving the AI ​​model.

41. A first communication device, comprising: A transceiver module, used for receiving first information sent by a terminal, where the first information is used for indicating the running state of the terminal; A processing module is used to perform corresponding artificial intelligence (AI) operations according to the operating status of the terminal.

42. A second communication device, characterized in that: include: A transceiver module is used to send first information to a network device, where the first information is used to indicate the operating status of the terminal, wherein the first information is used by the network device to perform corresponding artificial intelligence (AI) operations according to the operating status of the terminal.

43. A communication device, characterized in that: include: one or more processors; The one or more processors are used to call instructions so that the communication device executes the processing method described in any one of claims 1-21 and 22-40.

44. A storage medium storing instructions, characterized in that: When the instruction is executed on a communication device, the communication device executes the processing method according to any one of claims 1-21 and 22-40.

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