Artificial intelligence management method and communication apparatus

Abstract

The present application relates to the technical field of communications, and provides an artificial intelligence management method and a communication apparatus. The method provides a solution capable of effectively reducing the identification overhead between a terminal device and a network device. Specifically, the method comprises: a terminal device sends a first identifier and a second identifier to a first network device, wherein the first identifier is an identifier configured by a second network device for a first model successfully identified between the second network device and the terminal device, the second identifier is used for identifying a first area, and the first identifier is unique in the first area; and the first network device acquires model information of the first model on the basis of the first identifier and the second identifier, determines whether the first model is available, and sends, to the terminal device, response information used for indicating whether the first model is available. Therefore, a complete identification process can no longer be carried out on a successfully identified model between the terminal device and the first network device, so that the identification overhead between the terminal device and the network device can be effectively reduced.

Description

Artificial intelligence management method and communication device

[0001] This application claims priority to the Chinese patent application filed with the State Intellectual Property Office of China on July 20, 2023, with application number 202310898289.2 and application name “Management Method and Communication Device for Artificial Intelligence”, the entire contents of which are incorporated by reference into this application. Technical Field

[0002] The present application relates to the field of communication technology, and more specifically, to an artificial intelligence management method and communication device. Background Art

[0003] Artificial intelligence (AI) has been widely used in the field of communication technology to improve the communication performance between terminal devices and network devices. In the specific application of AI, the terminal device and the network device will perform model recognition on a certain AI model so that the two can reach a common understanding of the AI ​​model. For example, the terminal device reports to the network device the AI ​​model it supports, the application scenario of the AI ​​model, and the corresponding parameter configuration and other information (this information can also be collectively referred to as model information), and the network device configures a model identifier for the AI ​​model, which is used to identify the AI ​​model.

[0004] However, the current identification process between terminal devices and network devices will result in a large identification overhead. Therefore, how to effectively reduce the identification overhead between terminal devices and network devices is a technical problem that needs to be solved urgently.

[0005] Summary of the Invention

[0006] The present application provides an artificial intelligence management method and communication device, which can effectively reduce the model recognition overhead between terminal devices and network devices.

[0007] In a first aspect, a method for managing artificial intelligence is provided, including: sending a first identifier and a second identifier to a first network device, the first identifier is an identifier configured for a first model and comes from the second network device, the first model is a model successfully identified between the second network device and the terminal device, the second identifier is used to identify a first area, the first identifier is unique within the first area, and the first identifier includes at least one of a model identifier and a function identifier; and receiving response information from the first network device, the response information being used to indicate whether the first model is available.

[0008] The execution subject of the solution described in the first aspect can be a terminal device, or a module or chip used to execute the functions of the terminal device, etc., without limitation. For ease of description, the embodiments of this application are described using a terminal device as an example.

[0009] Specifically, when the terminal device and the first network device identify the first model that has been successfully identified again, the terminal device and the first network device may not exchange complete information for identifying the first model (for example, the type of AI model supported by the terminal device, the application scenario of the AI ​​model, and the corresponding parameter configuration, etc.), but only exchange the first identifier and the second identifier. The first network device can obtain the complete information of the first model based on the first identifier and the second identifier. In this way, the identification overhead between the terminal device and the first network device can be effectively reduced.

[0010] Through the above solution, the identification process between the terminal device and the network device can be simplified, and the identification overhead between the terminal device and the network device can be effectively reduced.

[0011] In a possible implementation, the response information is used to indicate that the first model is available, and the method further includes: receiving a third identifier from the first network device, where the third identifier is an identifier configured by the first network device for the first model.

[0012] In this way, the first network device can configure a new identifier for the model, thereby facilitating the terminal device and the first network device to identify and understand the first model.

[0013] In a possible implementation, the response information is used to indicate that the first model is available, including: the response information includes a third identifier.

[0014] In this way, by issuing a new identifier, the terminal device can determine that the first model is available based on the new identifier.

[0015] In a possible implementation, the response information is used to indicate that the first model is unavailable, and the method further includes: receiving a second model from the first network device and at least one item of information about the second model, wherein the information about the second model is used to activate the second model.

[0016] In this way, the terminal device and the first network device can complete the recognition of the new model.

[0017] In one possible implementation, the response information is used to indicate that the first model is unavailable, and the method further includes: receiving information from the first network device instructing the terminal device to fall back to a non-artificial intelligence AI mode.

[0018] In this way, the indication that the first model is unavailable may be completed.

[0019] In a possible implementation, the response information is used to indicate that the first model is unavailable, and the method further includes: receiving information from the first network device instructing the terminal device to perform a complete identification process.

[0020] In this way, the indication that the first model is unavailable may be completed.

[0021] In a possible implementation, the response information is used to indicate that the first model is unavailable, including: the response information includes the second model and at least one item of information of the second model.

[0022] In this way, the indication that the first model is unavailable may be completed.

[0023] In a possible implementation, the response information is used to indicate that the first model is unavailable, including: the response information includes information instructing the terminal device to fall back to a non-AI mode.

[0024] In this way, the indication that the first model is unavailable may be completed.

[0025] In a possible implementation, the response information is used to indicate that the first model is unavailable, including: the response information instructs the terminal device to perform a complete identification process.

[0026] In this way, the indication that the first model is unavailable may be completed.

[0027] In a possible implementation, the response information includes a first identifier, so as to indicate whether the first model is available.

[0028] In a possible implementation, the method further includes: receiving a first identifier from a second network device.

[0029] In this way, the terminal device can report the first identifier to the first network device.

[0030] In a possible implementation, the method further includes: receiving a second identifier from a second network device.

[0031] In this way, the terminal device can report the second identifier to the first network device.

[0032] In a second aspect, a method for managing artificial intelligence is provided, including: receiving a first identifier and a second identifier from a terminal device, the first identifier being an identifier configured by a first network device for a first model, the first model being a model successfully identified between the first network device and the terminal device, the second identifier being used to identify a first area, the first identifier being unique within the first area, and the first identifier including at least one of a model identifier and a function identifier; obtaining model information of the first model based on the first identifier and the second identifier, and determining whether the first model is available; and sending a response message to the terminal device, the response message being used to indicate whether the first model is available.

[0033] The execution subject of the solution described in the second aspect can be the second network device, or a module or chip used to execute the functions of the second network device, etc., which is not limited to this. For ease of description, the embodiment of this application is described using the second network device as an example.

[0034] Specifically, the second network device can obtain the model information of model 1 according to identifier 1 and identifier 2, and complete the recognition processing of model 1 based on the model information of model 1. The second network device does not need to obtain the model information of model 1 from the terminal device, which can effectively reduce the recognition overhead between the terminal device and the second network device.

[0035] Through the above solution, the identification process between the terminal device and the network device can be simplified, and the identification overhead between the terminal device and the network device can be effectively reduced.

[0036] In a possible implementation, the response information is used to indicate that the first model is available, and the method further includes: sending a third identifier to the terminal device, where the third identifier is used to identify the first model.

[0037] In this way, the second network device can configure a new identifier for the first model, thereby facilitating the terminal device and the second network device to identify and understand the first model.

[0038] In a possible implementation, the response information is used to indicate that the first model is available, including: the response information includes a third identifier.

[0039] In this way, by issuing a new identifier, the terminal device can determine that the first model is available based on the new identifier.

[0040] In one possible implementation, the response information is used to indicate that the first model is unavailable, and the method further includes: sending a second model and at least one item of the second model's information to the terminal device, the second model being different from the first model, and the second model's information being used to activate the second model.

[0041] In this way, the terminal device and the network device can complete the recognition of the new model.

[0042] In one possible implementation, the response information is used to indicate that the first model is unavailable, and the method further includes: instructing the terminal device to fall back to a non-artificial intelligence AI mode.

[0043] In this way, the indication that the first model is unavailable may be completed.

[0044] In a possible implementation, the response information is used to indicate that the first model is unavailable, and the method further includes: instructing the terminal device to perform a complete identification process.

[0045] In this way, the indication that the first model is unavailable may be completed.

[0046] In a possible implementation, the response information is used to indicate that the first model is unavailable, including: the response information includes the second model and at least one item of information of the second model.

[0047] In this way, the indication that the first model is unavailable may be completed.

[0048] In a possible implementation, the response information is used to indicate that the first model is unavailable, including: the response information includes information instructing the terminal device to fall back to a non-AI mode.

[0049] In this way, the indication that the first model is unavailable may be completed.

[0050] In a possible implementation, the response information is used to indicate that the first model is unavailable, including: the response information instructs the terminal device to perform a complete identification process.

[0051] In this way, the indication that the first model is unavailable may be completed.

[0052] In a possible implementation, the response information includes a first identifier.

[0053] In combination with the solutions described in any one of the first aspect and the second aspect, the type of the second identifier includes at least one of the following: a cell identifier, a cell group identifier, a tracking area identifier, a service area identifier, or a time advance group identifier; wherein the type of the first area is associated with the type of the second identifier.

[0054] Exemplarily, the type of the second identifier is a cell identifier, and the first area includes one or more cells; the type of the second identifier is a cell group identifier, and the first area includes one or more cell groups; the type of the second identifier is a tracking area identifier, and the first area includes one or more tracking areas; the type of the second identifier is a service area identifier, and the first area includes one or more service areas; the type of the second identifier is a time advance group identifier, and the first area includes one or more time advance groups; when the type of the second identifier is a tracking area identifier and a service area identifier, the first area includes one or more tracking areas and one or more service areas, etc.

[0055] This allows compatibility with existing standards.

[0056] In combination with the solution described in any one of the first aspect and the second aspect, the area of ​​the first network device belongs to the first area.

[0057] In this way, identification conflict issues can be avoided.

[0058] In combination with the scheme described in any one of the first aspect and the second aspect, the first identifier is carried by at least one of the following messages: a random access message, a radio resource control RRC configuration request message, an RRC configuration completion message, an RRC reconfiguration completion message, an RRC reconstruction request message, or a physical layer message.

[0059] In this way, the above identification process can be completed through specific communication messages.

[0060] In combination with the scheme described in any one of the first aspect and the second aspect, the second identifier is carried by at least one of the following messages: a random access message, a radio resource control RRC configuration request message, an RRC configuration completion message, an RRC reconfiguration completion message, an RRC reconstruction request message, or a physical layer message.

[0061] In this way, the above identification process can be completed through specific communication messages.

[0062] In combination with the solution described in any one of the first aspect and the second aspect, the first network device manages the first cell, which is the current resident cell of the terminal device, and the second network device manages the second cell, which is the source cell of the terminal device.

[0063] In this way, when the terminal device switches to a new cell, the terminal device and the network device corresponding to the newly switched cell can be identified through the above solution, which can effectively reduce the identification overhead between the terminal device and the network device.

[0064] On the third aspect, a method for managing artificial intelligence is provided, including: receiving model information of a first model from a first network device, the first model being a model successfully identified between the first network device and a terminal device; performing identification processing on the first model according to the model information of the first model, and determining whether the first model is available; and sending indication information to the terminal device, the indication information being used to indicate whether the first model is available.

[0065] In one possible implementation, the first network device manages a first cell, which is the source cell of the terminal device; the second network device manages a second cell, which is the current resident cell of the terminal device.

[0066] The execution subject of the solution described in the third aspect can be the second network device, or a module or chip used to execute the functions of the second network device, etc., which is not limited to this. For ease of description, the embodiment of this application is described using the second network device as an example.

[0067] Specifically, the second network device can obtain the model information of the first model from the first network device and complete the recognition of the first model based on the model information of the first model. The second network device may not obtain the model information of the first model from the terminal device, which can effectively reduce the recognition overhead between the terminal device and the second network device.

[0068] Through the above solution, the identification process between the terminal device and the network device can be simplified, and the identification overhead between the terminal device and the network device can be effectively reduced.

[0069] In a possible implementation, the indication information is used to indicate that the first model is available, and the method further includes: sending a first identifier to the terminal device, where the first identifier is used to identify the first model.

[0070] In this way, the second network device can configure an identifier for the first model, thereby facilitating the terminal device and the second network device to identify and understand the first model.

[0071] In a possible implementation, the first identifier is unique within the first area. In other words, the area of ​​the second network device belongs to the first area.

[0072] In this way, identification conflict issues can be avoided.

[0073] In one possible implementation, the first identifier is carried in at least one of the following messages: a random access message, a radio resource control (RRC) configuration request message, an RRC configuration complete message, an RRC reconfiguration complete message, an RRC reconstruction request message, or a physical layer message.

[0074] In this way, the above identification process can be completed through specific communication messages.

[0075] In one possible implementation, the indication information is used to indicate that the first model is unavailable, and the method further includes: sending a second model and at least one item of the second model's information to the terminal device, the second model is different from the first model, and the second model's information is used to activate the second model.

[0076] In this way, the terminal device and the second network device can complete the recognition of the new model.

[0077] In a fourth aspect, a method for managing artificial intelligence is provided, comprising: sending indication information to a network device, the indication information being used to indicate that a first model has been updated, the first model being a model successfully identified between the network device and the terminal device.

[0078] The execution subject of the solution described in the fourth aspect may be a terminal device, or a module or chip for executing the functions of the terminal device, etc., which is not limited to this. For ease of description, the embodiments of this application are described using a terminal device as an example.

[0079] Specifically, the terminal device can use the indication information to let the network device know that a successfully recognized model has been updated, thereby effectively reducing the recognition overhead between the terminal device and the network device. In addition, this can also avoid the terminal device and the network device from having to re-perform the complete recognition process for the updated model.

[0080] In a possible implementation, the method further includes: receiving response information from the network device, the response information including an identifier of the network device configured for the updated first model, or the response information is used to indicate an identifier for continuing to use the first model.

[0081] In this way, the network device can feed back to the terminal device that it has sensed that the first model has been updated.

[0082] In a fifth aspect, a method for managing artificial intelligence is provided, comprising: receiving indication information from a terminal device, the indication information being used to indicate that a first model has been updated, and the first model is a model successfully identified between the terminal device and the network device; sending response information to the terminal device based on the indication information, the response information including an identifier configured by the network device for the updated first model, or the response information being used to indicate an identifier for continuing to use the first model.

[0083] The execution subject of the solution described in the fifth aspect may be a network device, or a module or chip for executing the network device function, etc., without limitation. For ease of description, the embodiments of the present application are described using a network device as an example.

[0084] Through the above technical solution, the network device can sense that the model that has been successfully identified has been updated, and indicate to the terminal device that it has sensed that the first model has been updated.

[0085] In combination with the solution described in any one of the fourth aspect and the fifth aspect, a possible implementation method is that the indication information includes any one of the following: information on the performance of the updated first model, or an identifier of the first model.

[0086] In this way, the network device can be aware that the first model has been updated.

[0087] In a sixth aspect, a method for managing artificial intelligence is provided, comprising: receiving indication information from a network device, the indication information being used to indicate the cancellation of an identification of at least one model; canceling the identification of the at least one model according to the indication information; wherein each model in the at least one model is a model that is successfully identified between the network device and the terminal device.

[0088] The execution subject of the solution described in the sixth aspect may be a terminal device, or a module or chip for executing the functions of the terminal device, etc., which is not limited to this. For ease of description, the embodiments of this application are described using a terminal device as an example.

[0089] Specifically, the terminal device deregisters the identification of at least one model according to the instruction of the network device. In this way, the bit length of the model identification can be effectively reduced, which is conducive to reducing the identification overhead between the terminal device and the network device.

[0090] In a possible implementation, before receiving the instruction information from the network device, the method further includes: sending request information to the network device, where the request information is used to request to deregister the identification of at least one model.

[0091] In this way, the terminal device can proactively request to cancel the identification of some models.

[0092] In a possible implementation, the method further includes: sending response information to the network device, where the response information is used to indicate whether the indication information is successfully received.

[0093] In this way, the network device can determine whether the terminal device has successfully received the indication information.

[0094] In the seventh aspect, a method for managing artificial intelligence is provided, comprising: sending an indication message to a terminal device, the indication message being used to indicate the cancellation of an identification of at least one model, each of the at least one model being a model successfully identified between the terminal device and the network device.

[0095] In a possible implementation, the method further includes: receiving request information from the terminal device, where the request information is used to request cancellation of the identification of the at least one model.

[0096] In a possible implementation, the method further includes: receiving response information from the terminal device, where the response information is used to indicate whether the indication information is successfully received.

[0097] In combination with the solution described in any one of the sixth and seventh aspects, a possible implementation method is that the indication information includes at least one of the following items: an identifier of each model in the at least one model, and model information of each model in the at least one model.

[0098] In combination with the solution described in any one of the sixth and seventh aspects, a possible implementation method is that the request information includes at least one of the following items: an identifier of each model in the at least one model, and model information of each model in the at least one model.

[0099] In the eighth aspect, a method for managing artificial intelligence is provided, including: receiving a first model configuration message and a first wireless resource control configuration information from a network device, the first model configuration information is used to activate the first model, and the first wireless resource control configuration information is used to configure the first wireless resource control configuration; when there is a conflict between the first model configuration information and the first wireless resource control configuration information, determining whether to ignore the first model configuration information or the first wireless resource control configuration information based on the priority of the first model configuration information and the priority of the first wireless resource control configuration information.

[0100] The execution subject of the solution described in the eighth aspect may be a terminal device, or a module or chip for executing the functions of the terminal device, etc., which is not limited to this. For ease of description, the embodiments of this application are described using a terminal device as an example.

[0101] Through the above scheme, the terminal device can determine whether to ignore the first model configuration information or the first wireless resource control configuration information based on the priority of the first model configuration information and the priority of the first wireless resource control configuration information. In this way, the conflict problem between the first model configuration information and the first wireless resource control configuration information can be solved.

[0102] A possible implementation method is to determine whether to ignore the first model configuration information or the first wireless resource control configuration information based on the priority of the first model configuration information and the priority of the first wireless resource control configuration information, including: determining whether to ignore the first model configuration information or the first wireless resource control information based on the priority of the signaling used to carry the first model configuration information and the priority of the signaling used to carry the first wireless resource control configuration information.

[0103] In this way, the terminal device can handle the conflict between the first model configuration information and the first wireless resource control configuration information according to the priority between the signaling used to carry the first model configuration information and the signaling used to carry the first wireless resource control configuration information.

[0104] In a possible implementation, when the priority of the signaling used to carry the first model configuration information is higher than the priority of the signaling used to carry the first radio resource control configuration information, the method includes: determining to ignore the first radio resource control configuration information.

[0105] In a possible implementation, when the priority of the signaling used to carry the first radio resource control configuration information is higher than the priority of the signaling used to carry the first model configuration information, the method includes: determining to ignore the first model configuration information.

[0106] In a ninth aspect, a communication device is provided, which may be a terminal device, or a device in a terminal device (for example, a chip (also known as a chip system), or a circuit), or a device that can be used in conjunction with a terminal device.

[0107] In one possible implementation, the communication device includes a module or unit corresponding to each of the methods / operations / steps / actions described in any one of the first aspects. The module or unit may be a hardware circuit, software, or a combination of hardware circuit and software.

[0108] In the tenth aspect, a communication device is provided, which may be a network device, or a device in a network device (for example, a chip (also known as a chip system), or a circuit), or a device that can be used in conjunction with a terminal device.

[0109] In one possible implementation, the communication device may include a module or unit corresponding to each of the methods / operations / steps / actions described in any one of the second aspects. The module or unit may be a hardware circuit, software, or a combination of hardware circuit and software.

[0110] In the eleventh aspect, a communication device is provided, which may be a network device, or a device in a network device (for example, a chip (also known as a chip system), or a circuit), or a device that can be used in conjunction with a terminal device.

[0111] In one possible implementation, the communication device may include a module or unit corresponding to each of the methods / operations / steps / actions described in any one of the third aspects. The module or unit may be a hardware circuit, software, or a combination of hardware circuit and software.

[0112] In the twelfth aspect, a communication device is provided, which may be a terminal device, or a device in the terminal device (for example, a chip (also known as a chip system) or a circuit), or a device that can be used in conjunction with the terminal device.

[0113] In one possible implementation, the communication device includes a module or unit corresponding to each of the methods / operations / steps / actions described in any one of the fourth aspects. The module or unit may be a hardware circuit, software, or a combination of hardware circuit and software.

[0114] In the thirteenth aspect, a communication device is provided, which may be a network device, or a device in a network device (for example, a chip (also known as a chip system), or a circuit), or a device that can be used in conjunction with a network device.

[0115] In one possible implementation, the communication device may include a module or unit corresponding to each of the methods / operations / steps / actions described in the fifth aspect. The module or unit may be a hardware circuit, software, or a combination of hardware circuit and software.

[0116] In the fourteenth aspect, a communication device is provided, which may be a terminal device, or a device in the terminal device (for example, a chip (also known as a chip system) or a circuit), or a device that can be used in conjunction with the terminal device.

[0117] In one possible implementation, the communication device may include a module or unit corresponding to each of the methods / operations / steps / actions described in the sixth aspect. The module or unit may be a hardware circuit, software, or a combination of hardware circuit and software.

[0118] In the fifteenth aspect, a communication device is provided, which may be a network device, or a device in a network device (for example, a chip (also known as a chip system), or a circuit), or a device that can be used in conjunction with a network device.

[0119] In one possible implementation, the communication device may include a module or unit corresponding to each of the methods / operations / steps / actions described in the seventh aspect. The module or unit may be a hardware circuit, software, or a combination of hardware circuit and software.

[0120] In the sixteenth aspect, a communication device is provided, which may be a terminal device, or a device in the terminal device (for example, a chip (also known as a chip system) or a circuit), or a device that can be used in conjunction with the terminal device.

[0121] In one possible implementation, the communication device may include a module or unit corresponding to each of the methods / operations / steps / actions described in the eighth aspect. The module or unit may be a hardware circuit, software, or a combination of hardware circuit and software.

[0122] In the seventeenth aspect, a communication device is provided, comprising a processor, wherein the processor is used to, by executing a computer program or instruction, or by a logic circuit, enable the communication device to execute the method described in the first aspect and any possibility of the first aspect; or enable the communication device to execute the method described in the second aspect and any possibility of the second aspect; or enable the communication device to execute the method described in the third aspect and any possibility of the third aspect; or enable the communication device to execute the method described in the fourth aspect and any possibility of the fourth aspect; or enable the communication device to execute the method described in the fifth aspect and any possibility of the fifth aspect; or enable the communication device to execute the method described in the sixth aspect and any possibility of the sixth aspect; or enable the communication device to execute the method described in the seventh aspect and any possibility of the seventh aspect; or enable the communication device to execute the method described in the eighth aspect and any possibility of the eighth aspect.

[0123] In a possible implementation, the communication device further includes a memory for storing the computer program or instruction.

[0124] In a possible implementation, the communication device further includes a communication interface, which is used to input and / or output signals.

[0125] In aspect 18, a communication device is provided, comprising a logic circuit and an input / output interface, the input / output interface being used to input and / or output signals, the logic circuit being used to execute the method described in aspect 1 and any possibility of the first aspect; or, the logic circuit being used to execute the method described in aspect 2 and any possibility of the second aspect; or, the logic circuit being used to execute the method described in aspect 3 and any possibility of the third aspect; or, the logic circuit being used to execute the method described in aspect 4 and any possibility of the fourth aspect; or, the logic circuit being used to execute the method described in aspect 5 and any possibility of the fifth aspect; or, the logic circuit being used to execute the method described in aspect 6 and any possibility of the sixth aspect; or, the logic circuit being used to execute the method described in aspect 7 and any possibility of the seventh aspect; or, the logic circuit being used to execute the method described in aspect 8 and any possibility of the eighth aspect.

[0126] In the nineteenth aspect, a computer-readable storage medium is provided, on which a computer program or instruction is stored. When the computer program or the instruction is run on a computer, the method described in the first aspect and any possibility of the first aspect is executed; or the method described in the second aspect and any possibility of the second aspect is executed; or the method described in the third aspect and any possibility of the third aspect is executed; or the method described in the fourth aspect and any possibility of the fourth aspect is executed; or the method described in the fifth aspect and any possibility of the fifth aspect is executed; or the method described in the sixth aspect and any possibility of the sixth aspect is executed; or the method described in the seventh aspect and any possibility of the seventh aspect is executed; or the method described in the eighth aspect and any possibility of the eighth aspect is executed.

[0127] In aspect 20, a computer program product is provided, comprising instructions, which, when run on a computer, cause the method described in aspect 1 and any possibility of aspect 1 to be executed; or cause the method described in aspect 2 and any possibility of aspect 2 to be executed; or cause the method described in aspect 3 and any possibility of aspect 3 to be executed; or cause the method described in aspect 4 and any possibility of aspect 4 to be executed; or cause the method described in aspect 5 and any possibility of aspect 5 to be executed; or cause the method described in aspect 6 and any possibility of aspect 6 to be executed; or cause the method described in aspect 7 and any possibility of aspect 7 to be executed; or cause the method described in aspect 8 and any possibility of aspect 8 to be executed.

[0128] The description of the beneficial effects of the ninth to twentieth aspects may correspond to the description of the beneficial effects of the first to eighth aspects. BRIEF DESCRIPTION OF THE DRAWINGS

[0129] FIG1 is a schematic diagram of an application framework 100 in a communication system according to an embodiment of the present application.

[0130] FIG2 is a schematic diagram of an application framework 200 in a communication system according to an embodiment of the present application.

[0131] FIG3 is a schematic diagram of a communication system 300 applicable to an embodiment of the present application.

[0132] FIG4 is a schematic diagram of a communication system 400 applicable to an embodiment of the present application.

[0133] FIG5 is a schematic diagram of the interactive process of an artificial intelligence management method 500 according to an embodiment of the present application.

[0134] FIG6 is a schematic diagram of the interactive flow of an artificial intelligence management method 600 according to an embodiment of the present application.

[0135] FIG7 is a schematic diagram of the interactive process of an artificial intelligence management method 700 according to an embodiment of the present application.

[0136] FIG8 is a schematic diagram of the interactive process of an artificial intelligence management method 800 according to an embodiment of the present application.

[0137] FIG9 is a schematic diagram of the interactive process of an artificial intelligence management method 900 according to an embodiment of the present application.

[0138] FIG10 is a schematic block diagram of a communication device 1000 according to an embodiment of the present application.

[0139] FIG11 is a schematic block diagram of a communication device 1100 according to an embodiment of the present application. DETAILED DESCRIPTION

[0140] In order to facilitate understanding of the embodiments of the present application, the following points are first explained.

[0141] 1. In this application, unless otherwise specified, "plurality" means two or more.

[0142] 2. In each embodiment of the present application, unless otherwise specified or there is a logical conflict, the terms and / or descriptions between different 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 internal logical relationships.

[0143] 3. The various numerical numbers involved in this application are only used for the convenience of description and are not used to limit the scope of protection of this application. The size of the serial numbers involved in this application does not mean the order of execution. The order of execution of each process should be determined by its function and internal logic. For example, the terms "first", "second", "third", "fourth" and other various terminology labels (if any) in the specification and claims and drawings of this application are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. Among them, the data used in this way can be interchangeable where appropriate, so that the embodiments described here can be implemented in an order other than what is illustrated or described here.

[0144] At the same time, any embodiment or design described in this application as "exemplary" or "for example" should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary" or "for example" is intended to present the relevant concepts in a concrete manner to facilitate understanding.

[0145] 4. The terms "comprise" and "have" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or apparatus that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such process, method, product or apparatus.

[0146] 5. In this application, "used to indicate" can be understood as "enabling," and "enabling" can include direct enabling and indirect enabling. When describing that certain information is used to enable A, it can include that the information directly enables A or indirectly enables A, and does not necessarily mean that the information contains A.

[0147] The information enabled by the information is called information to be enabled. In the specific implementation process, there are many ways to enable the enabled information, such as but not limited to, directly enabling the information to be enabled, such as the information to be enabled itself or the index of the information to be enabled. The information to be enabled can also be indirectly enabled by enabling other information, wherein there is an association between the other information and the information to be enabled. It is also possible to enable only a part of the information to be enabled, while the other parts of the information to be enabled are known or agreed in advance. For example, it is also possible to enable specific information with the help of the arrangement order of each piece of information agreed in advance (such as specified in the protocol), thereby reducing the enabling overhead to a certain extent. At the same time, it is also possible to identify the common parts of each piece of information and enable them uniformly to reduce the enabling overhead caused by enabling the same information separately.

[0148] 6. In this application, "pre-configuration" may include pre-definition, such as protocol definition. "Pre-definition" may be implemented by pre-storing corresponding codes, tables, or other methods that can be used to indicate relevant information in a device (e.g., including each network element). This application does not limit the specific implementation method.

[0149] 7. "Storage" or "saving" as used in this application may refer to storage in one or more memories. The one or more memories may be provided separately or integrated into an encoder or decoder, a processor, or a communication device. The one or more memories may also be provided in part separately and in part integrated into a decoder, processor, or communication device. The type of memory may be any form of storage medium and is not limited thereto.

[0150] 8. The “protocol” referred to in this application may refer to a standard protocol in the field of communications, for example, it may include the fourth generation (4G) network, the fifth generation (5G) network protocol, the new radio (NR) protocol, the 5.5G network protocol, the sixth generation (6G) network protocol and related protocols used in future communication systems. This application does not limit this.

[0151] 9. The arrows or boxes indicated by dotted lines in the schematic diagrams in the accompanying drawings of this application specification represent optional steps or optional modules.

[0152] 10. In this application, unless otherwise specified, “ / ” indicates that the objects associated with each other are in an “or” relationship. For example, A / B can mean A or B. “And / or” in this application is merely a description of the association relationship between associated objects, indicating that three relationships may exist. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. A and B can be singular or plural.

[0153] First, a communication system to which the embodiments of the present application are applicable is described.

[0154] The technical solutions provided in this application can be applied to various communication systems, such as: fifth generation (5G) or new radio (NR) systems, long term evolution (LTE) systems, LTE frequency division duplex (FDD) systems, LTE time division duplex (TDD) systems, wireless local area networks (WLAN) systems, satellite communication systems, future communication systems, such as sixth generation (6G) mobile communication systems, or a fusion system of multiple systems. The technical solutions provided in this application can also be applied to device to device (D2D) communication, vehicle-to-everything (V2X) communication, machine to machine (M2M) communication, machine type communication (MTC), and Internet of Things (IoT) communication systems or other communication systems.

[0155] A network element in a communication system can send a signal to another network element or receive a signal from another network element. The signal may include information, signaling, or data, etc. The network element can also be replaced by an entity, a network entity, a device, a communication device, a communication module, a node, a communication node, etc. The embodiment of the present application is described using a network element as an example. For example, a communication system may include at least one terminal device and at least one network device. The network device can send a downlink signal to the terminal device, and / or the terminal device can send an uplink signal to the network device. It is understandable that the terminal device in the embodiment of the present application can be replaced by the first network element, and the network device can be replaced by the second network element, and the two perform the corresponding communication method in the embodiment of the present application.

[0156] In an embodiment of the present application, the terminal device may also be referred to as user equipment (UE), access terminal, user unit, user station, mobile station, mobile station, remote station, remote terminal, mobile device, user terminal, terminal, wireless communication device, user agent or user device.

[0157] The terminal device may be a device that provides voice / data, such as a handheld device or vehicle-mounted device with a wireless connection function. At present, some examples of terminals are: mobile phones, tablet computers, laptop computers, PDAs, mobile internet devices (MIDs), wearable devices, virtual reality (VR) devices, augmented reality (AR) devices, wireless terminals in industrial control, wireless terminals in self-driving, wireless terminals in remote medical surgery, wireless terminals in smart grids, wireless terminals in transportation safety, wireless terminals in smart cities, wireless terminals in smart homes, cellular phones, cordless phones, session initiation protocol (SIP) phones, wireless local loop (WLL) stations, personal digital assistants (PDAs), handheld devices with wireless communication capabilities, computing devices or other processing devices connected to wireless modems, wearable devices, terminal devices in 5G networks or future evolved public land mobile communication networks (PLMNs). The terminal equipment in the network (PLMN), etc., is not limited to this in the embodiments of the present application.

[0158] As an example and not a limitation, in the embodiments of the present application, the terminal device may also be a wearable device. Wearable devices may also be called wearable smart devices, which are a general term for wearable devices that are intelligently designed and developed using wearable technology for daily wear, such as glasses, gloves, watches, clothing, and shoes. A wearable device is a portable device that is worn directly on the body or integrated into the user's clothes or accessories. Wearable devices are not only hardware devices, but also achieve powerful functions through software support, data interaction, and cloud interaction. Broadly speaking, wearable smart devices include those that are fully functional, large in size, and can achieve complete or partial functions without relying on smartphones, such as smart watches or smart glasses, as well as those that only focus on a certain type of application function and need to be used in conjunction with other devices such as smartphones, such as various smart bracelets and smart jewelry for vital sign monitoring.

[0159] In the embodiments of the present application, the device for realizing the function of the terminal device can be a terminal device, or a device capable of supporting the terminal device to realize the function, such as a chip system, which can be installed in the terminal device or used in combination with the terminal device. In the embodiments of the present application, the chip system can be composed of a chip, or it can include a chip and other discrete devices. In the embodiments of the present application, only the terminal device is used as an example for description, and the embodiments of the present application are not limited to the solutions of the embodiments of the present application.

[0160] The network device in the embodiments of the present application may be a device for communicating with a terminal device, and may also be referred to as an access network device or a radio access network device. For example, the network device may be a base station. The network device in the embodiments of the present application may refer to a radio access network (RAN) node (or device) that connects a terminal device to a wireless network. A base station may broadly cover various names as follows, or replace the following names, such as: NodeB, evolved NodeB (eNB), next generation NodeB (gNB), relay station, access point, transmitting and receiving point (TRP), transmitting point (TP), master station, secondary station, multi-standard radio (motor slide retainer, MSR) node, home base station, network controller, access node, wireless node, access point (AP), transmission node, transceiver node, baseband unit (BBU), remote radio unit (RRU), active antenna unit (AAU), remote radio head (RRH), central unit (CU), distributed unit (DU), radio unit (RU), positioning node, etc. A base station may be a macro base station, a micro base station, a relay node, a donor node, or the like, or a combination thereof. The base station may also refer to a communication module, modem or chip that is set in the aforementioned equipment or device. The base station may also be a mobile switching center and a device that performs the base station function in D2D, V2X, and M2M communications, a network side device in a 6G network, a device that performs the base station function in future communication systems, etc. The base station can support networks with the same or different access technologies. Optionally, the RAN node may also be a server, a wearable device, a vehicle or an on-board device, etc. For example, the access network device in the vehicle to everything (V2X) technology may be a road side unit (RSU). The embodiments of the present application do not limit the specific technology and specific device form adopted by the network equipment.

[0161] Base stations can be fixed or mobile. For example, a helicopter or drone can be configured to act as a mobile base station, and one or more cells can move based on the location of the mobile base station. In other examples, a helicopter or drone can be configured to act as a device that communicates with another base station.

[0162] In some deployments, the network devices mentioned in the embodiments of the present application may include a CU, a DU, or both a CU and a DU, or a control plane CU node (central unit-control plane (CU-CP)), a user plane CU node (central unit-user plane (CU-UP)), and a DU node. For example, the network devices may include a gNB-CU-CP, a gNB-CU-UP, and a gNB-DU.

[0163] In some deployments, multiple RAN nodes collaborate to assist terminals in achieving wireless access, with different RAN nodes implementing portions of the base station's functionality. For example, a RAN node can be a CU, DU, CU-CP, CU-UP, or RU. The CU and DU can be separate or included in the same network element, such as the BBU. The RU can be included in a radio frequency device or radio unit, such as an RRU, AAU, or RRH.

[0164] The RAN node may support one or more types of fronthaul interfaces, with different fronthaul interfaces corresponding to DUs and RUs with different functions. If the fronthaul interface between the DU and the RU is a common public radio interface (CPRI), the DU is configured to implement one or more baseband functions, and the RU is configured to implement one or more radio frequency functions. If the fronthaul interface between the DU and the RU is another type of interface, relative to the CPRI, some of the downlink and / or uplink baseband functions, such as precoding, digital beamforming (BF), or one or more of inverse fast Fourier transform (IFFT) / cyclic prefix (CP) for downlink, are moved from the DU to the RU for implementation; and for uplink, one or more of digital beamforming (BF), or fast Fourier transform (FFT) / cyclic prefix (CP) removal, are moved from the DU to the RU for implementation. In one possible implementation, the interface may be an enhanced common public radio interface (eCPRI). In the eCPRI architecture, the division between the DU and RU is different, corresponding to different types (category, Cat) of eCPRI, such as eCPRI Cat A, B, C, D, E, and F.

[0165] Taking eCPRI Cat A as an example, for downlink transmission, based on layer mapping, the DU is configured to implement layer mapping and one or more functions preceding it (i.e., one or more of coding, rate matching, scrambling, modulation, and layer mapping), while other functions after layer mapping (e.g., RE mapping, BF, or one or more of IFFT / CP) are moved to the RU for implementation. For uplink transmission, based on de-RE mapping, the DU is configured to implement de-mapping and one or more functions preceding it (i.e., one or more of decoding, de-rate matching, descrambling, demodulation, inverse discrete Fourier transform (IDFT), channel equalization, and de-RE mapping), while other functions after de-mapping (e.g., one or more of digital BF or fast Fourier transform (FFT) / CP removal) are moved to the RU for implementation. It is understood that for the functional description of the DU and RU corresponding to various types of eCPRI, please refer to the eCPRI protocol and will not be repeated here.

[0166] In one possible design, the processing unit for implementing baseband functions in the BBU is called a baseband high layer (BBH) unit, and the processing unit for implementing baseband functions in the RRU / AAU / RRH is called a baseband low layer (BBL) unit.

[0167] In different systems, CU (or CU-CP and CU-UP), DU or RU may also have different names, but those skilled in the art can understand their meanings. For example, in the ORAN system, CU may also be called O-CU (Open CU), DU may also be called O-DU, CU-CP may also be called O-CU-CP, CU-UP may also be called O-CU-UP, and RU may also be called O-RU. Any unit of CU (or CU-CP, CU-UP), DU and RU in this application can be implemented by a software module, a hardware module, or a combination of a software module and a hardware module.

[0168] In the embodiments of the present application, the device for implementing the functions of the network device can be a network device; it can also be a device that can support the network device to implement the functions, such as a chip system, a hardware circuit, a software module, or a hardware circuit and a software module. The device can be installed in the network device or used in conjunction with the network device. In the embodiments of the present application, only the device for implementing the functions of the network device is used as an example to illustrate, and does not constitute a limitation on the solutions of the embodiments of the present application.

[0169] The network device and / or terminal device can be deployed on land, including indoors or outdoors, handheld or vehicle-mounted; it can also be deployed on the water surface; it can also be deployed on aircraft, balloons and satellites in the air. The embodiments of this application do not limit the scenarios in which the network device and the terminal device are located. In addition, the terminal device and the network device can be hardware devices, or they can be software functions running on dedicated hardware, software functions running on general-purpose hardware, such as virtualization functions instantiated on a platform (e.g., a cloud platform), or entities including dedicated or general-purpose hardware devices and software functions. This application does not limit the specific forms of the terminal device and the network device.

[0170] In wireless communication networks, such as mobile communication networks, the services supported by the networks are becoming increasingly diverse, and therefore the demands that need to be met are becoming increasingly diverse. For example, the network needs to be able to support ultra-high speeds, ultra-low latency, and / or ultra-large connections. This feature makes network planning, network configuration, and / or resource scheduling increasingly complex. In addition, as network functionality becomes increasingly powerful, such as supporting higher spectrum, supporting high-order multiple input multiple output (MIMO) technology, supporting beamforming, and / or supporting new technologies such as beam management, network energy saving has become a hot research topic. These new demands, new scenarios, and new features have brought unprecedented challenges to network planning, operation and maintenance, and efficient operation. To meet this challenge, artificial intelligence technology can be introduced into wireless communication networks to achieve network intelligence.

[0171] In order to support AI technology in wireless networks, AI nodes may also be introduced into the network.

[0172] Optionally, the AI ​​node can be deployed in one or more of the following locations in the communication system: access network equipment, terminal equipment, or core network equipment. Alternatively, the AI ​​node can be deployed separately, for example, in a location other than any of the above devices, such as a host or cloud server in an over-the-top (OTT) system. The AI ​​node can communicate with other devices in the communication system, such as one or more of the following: network equipment, terminal equipment, or core network elements.

[0173] It is understood that the embodiments of the present application do not limit the number of AI nodes. For example, when there are multiple AI nodes, the multiple AI nodes can be divided based on function, such as different AI nodes are responsible for different functions.

[0174] It is also understood that AI nodes can be independent devices, or integrated into the same device to implement different functions, or can be network elements in hardware devices, or can be software functions running on dedicated hardware, or can be virtualized functions instantiated on a platform (e.g., a cloud platform). This application does not limit the specific form of AI nodes. Among them, AI nodes can be AI network elements or AI modules.

[0175] Figure 1 is a schematic diagram of an application framework 100 in a communication system of an embodiment of the present application. As shown in Figure 1, network elements in the communication system are connected through interfaces (e.g., NG, Xn) or air interfaces. One or more AI modules are provided in these network element nodes, such as core network equipment, access network nodes (RAN nodes), terminals, or one or more devices in operation administration and maintenance (OAM) (for clarity, only one is shown in Figure 1). The access network node can be a separate RAN node, or it can include multiple RAN nodes, for example, including CU and DU. One or more AI modules can also be provided in the CU and / or DU. Optionally, the CU can also be split into CU-CP and CU-UP. One or more AI models are provided in the CU-CP and / or CU-UP.

[0176] The AI ​​module is used to implement the corresponding AI function. The AI ​​modules deployed in different network elements may be the same or different. The model of the AI ​​module can implement different functions according to different parameter configurations. The model of the AI ​​module can be configured based on one or more of the following parameters: structural parameters (such as the number of neural network layers, the width of the neural network, the connection relationship between layers, the weight of the neuron, the activation function of the neuron, or at least one of the bias in the activation function), input parameters (such as the type of input parameters and / or the dimension of the input parameters), or output parameters (such as the type of output parameters and / or the dimension of the output parameters). Among them, the bias in the activation function can also be called the bias of the neural network.

[0177] An AI module can have one or more models. A model can infer an output, which includes one or more parameters. The learning, training, or inference processes of different models can be deployed on different nodes or devices, or on the same node or device.

[0178] Figure 2 is a schematic diagram of an application framework 200 in a communication system according to an embodiment of the present application. As shown in Figure 2, the communication system includes a RAN intelligent controller (RIC). For example, the RIC may be the AI ​​modules 117 and 118 shown in Figure 1, which are used to implement AI-related functions. The RIC includes a near-real-time RIC (near-real time RIC, near-RT RIC) and a non-real-time RIC (non-real time RIC, non-RT RIC). The non-real-time RIC mainly processes non-real-time information, such as data that is not sensitive to latency, and the latency of the data may be in the order of seconds. The real-time RIC mainly processes near-real-time information, such as data that is relatively sensitive to latency, and the latency of the data may be in the order of tens of milliseconds.

[0179] Near real-time RIC is used for model training and reasoning. For example, it is used to train an AI model and use the AI ​​model for reasoning. Near real-time RIC can obtain network-side and / or terminal-side information from RAN nodes (e.g., CU, CU-CP, CU-UP, DU, and / or RU) and / or terminals. This information can be used as training data or reasoning data. Optionally, near real-time RIC can deliver the reasoning results to the RAN node and / or terminal. Optionally, the reasoning results can be exchanged between the CU and DU, and / or between the DU and RU. For example, the near real-time RIC delivers the reasoning results to the DU, and the DU sends it to the RU.

[0180] Non-real-time RIC is also used for model training and reasoning. For example, it is used to train AI models and use the models for reasoning. Non-real-time RIC can obtain network-side and / or terminal-side information from RAN nodes (such as CU, CU-CP, CU-UP, DU and / or RU) and / or terminals. This information can be used as training data or reasoning data, and the reasoning results can be submitted to the RAN node and / or terminal. Optionally, the reasoning results can be exchanged between the CU and DU, and / or between the DU and RU. For example, the non-real-time RIC submits the reasoning results to the DU, and the DU sends it to the RU.

[0181] The near-real-time RIC and non-real-time RIC can also be set up as separate network elements. Optionally, the near-real-time RIC and non-real-time RIC can also be part of other devices. For example, the near-real-time RIC is set up in a RAN node (e.g., a CU or DU), while the non-real-time RIC is set up in an OAM, a cloud server, a core network device, or other network devices.

[0182] Figure 3 is a schematic diagram of a communication system 300 applicable to an embodiment of the present application. As shown in Figure 3, communication system 300 may include at least one network device, such as network device 110; communication system 100 may also include at least one terminal device, such as terminal device 120 and terminal device 130. Network device 110 and terminal devices (such as terminal device 120 and terminal device 130) can communicate via wireless links. Communication devices in the communication system, such as network device 110 and terminal device 120, can communicate using multi-antenna technology.

[0183] Figure 4 is a schematic diagram of a communication system 400 applicable to an embodiment of the present application. Compared to communication system 300, communication system 400 also includes an AI network element 140. AI network element 140 is used to perform AI-related operations, such as building a training data set or training an AI model.

[0184] In one possible implementation, the network device 110 may send data related to the training of the AI ​​model to the AI ​​network element 140, which constructs a training data set and trains the AI ​​model. For example, the data related to the training of the AI ​​model may include data reported by the terminal device. The AI ​​network element 140 may send the results of the operations related to the AI ​​model to the network device 110, and forward them to the terminal device through the network device 110. For example, the results of the operations related to the AI ​​model may include at least one of the following: an AI model that has completed training, an evaluation result or a test result of the model, etc. Exemplarily, a portion of the trained AI model may be deployed on the network device 110, and another portion may be deployed on the terminal device. Alternatively, the trained AI model may be deployed on the network device 110. Alternatively, the trained AI model may be deployed on the terminal device.

[0185] It should be understood that Figure 4 illustrates only the example of a direct connection between AI network element 140 and network device 110. In other scenarios, AI network element 140 may also be connected to a terminal device. Alternatively, AI network element 140 may be connected to both network device 110 and a terminal device simultaneously. Alternatively, AI network element 140 may be connected to network device 110 through a third-party network element. This embodiment of the present application does not limit the connection relationship between the AI ​​network element and other network elements.

[0186] The AI ​​network element 140 may also be provided as a module in a network device and / or a terminal device, for example, in the network device 110 or the terminal device shown in FIG3 .

[0187] It should be noted that Figures 3 and 4 are simplified schematic diagrams for ease of understanding. For example, the communication system may further include other devices, such as wireless relay devices and / or wireless backhaul devices, which are not shown in Figures 3 and 4. In actual applications, the communication system may include multiple network devices (such as network device 110 and network device 150 (not shown in Figure 3)), and may also include multiple terminal devices. The embodiments of the present application do not limit the number of network devices and terminal devices included in the communication system.

[0188] Next, some technical concepts involved in this application are briefly described.

[0189] AI Model: An AI model is an algorithm or computer program that implements AI functionality. It represents the mapping between the model's input and output. AI models can be neural networks, linear regression models, decision tree models, support vector machines (SVMs), Bayesian networks, Q-learning models, or other machine learning (ML) models.

[0190] Two-end model: A two-end model can also be called a bilateral model, collaborative model, dual model, or two-side model. A two-end model is a model composed of multiple sub-models. The sub-models must match each other. These sub-models can be deployed on different nodes.

[0191] The AI ​​model in the embodiment of the present application can be a dual-end model or a single-end model, which can be deployed on terminal devices and / or network devices.

[0192] Model application: Use the trained model to solve practical problems.

[0193] AI function: It does not specifically refer to a specific AI model, but refers to a class of AI models with the same function. For example, AI functions can be channel state information (CSI) feedback, CSI prediction, beam prediction, positioning, channel estimation, etc., that is, AI functions can correspond to multiple AI models.

[0194] It is understood that the implementation of an AI model or AI function can be hardware circuitry, software, or a combination of software and hardware, without limitation. Non-limiting examples of software include: program code, program, subroutine, instruction, instruction set, code, code segment, software module, application, or software application.

[0195] AI model recognition: is a process / method that enables the terminal device and the network device to reach a consensus on the identified AI model. Generally, the terminal device 120 needs to register the AI ​​model with the network device 110, that is, the terminal device 120 informs the network device 110 that the terminal device 120 has an AI model, as well as the function, application scenario, corresponding parameter configuration and other information of the AI ​​model. The network device 110 can then configure a model identifier for the AI ​​model. In this way, the terminal device 120 and the network device 110 have a consistent understanding of the AI ​​model referred to by the model identifier (which can be called successful recognition). Alternatively, the network device 110 sends an AI model to the terminal device 120, as well as information indicating the identifier, function, application scenario, corresponding parameter configuration and other information of the AI ​​model. In the subsequent AI model management process, the terminal device 120 and the network device 110 can use the model identifier to indicate the AI ​​model corresponding to the model identifier.

[0196] AI function identification: is a process / method that enables the terminal device and the network device to reach a consensus on the identified AI function. Generally, the terminal device 120 needs to report to the network device 110 the AI ​​functions supported by the terminal device 120, as well as the application scenarios, corresponding configurations and other information of the AI ​​functions. The network device 110 can also configure a function identifier for the AI ​​function, or identify the AI ​​function through the application scenarios and / or corresponding configuration information of the AI ​​function. In this way, the terminal device 120 and the network device 110 have a consistent understanding of the AI ​​function referred to by the function identifier (which can be called successful identification). In the subsequent management process of the AI ​​function, the terminal device 120 and the network device 110 can use the function identifier to indicate the AI ​​function corresponding to the function identifier.

[0197] It should be noted that in the embodiments of the present application, indications include direct indications (also known as explicit indications) and implicit indications. Direct indication of information A refers to including information A; implicit indication of information A refers to indicating information A through the correspondence between information A and information B and the direct indication of information B. The correspondence between information A and information B can be predefined, pre-stored, pre-burned, or pre-configured.

[0198] It should be noted that in the embodiments of the present application, information C is used to determine information D, which includes information D being determined solely based on information C, as well as information D being determined based on information C and other information. Furthermore, information C can also be used to determine information D indirectly, for example, where information D is determined based on information E, and information E is determined based on information C.

[0199] In addition, in each embodiment of the present application, "network element A (which may be device A) sends information A to network element B (which may be device B)" can be understood as the destination end of the information A or the intermediate network element in the transmission path between the destination end and the network element B, which may include directly or indirectly sending information to network element B. "Network element B receives information A from network element A" can be understood as the source end of the information A or the intermediate network element in the transmission path between the source end and the network element A, which may include directly or indirectly receiving information from network element A. The information may be processed as necessary between the source end and the destination end of the information transmission, such as format changes, etc., but the destination end can understand the valid information from the source end. Similar expressions in this application can be understood similarly and will not be elaborated here.

[0200] Currently, the identification process between a terminal device and a network device (regardless of whether it is an AI model identification process or an AI function identification process, collectively referred to as the identification process) results in a large identification overhead. For example, the terminal device and the network device corresponding to cell 1 perform an identification process on model 1 (regardless of whether it is an AI model or an AI function, collectively referred to as model 1), and model 1 is a successfully identified model. When the terminal device switches from cell 1 to cell 2, the terminal device still needs to perform a complete identification process on model 1 again with the network device corresponding to cell 2, which increases the identification overhead. For another example, after the terminal device updates the successfully identified model 1, the terminal device still needs to perform a complete identification process on the updated model 1 with the network device corresponding to cell 1, which increases the identification overhead. For another example, the terminal device and the network device corresponding to cell 1 perform an identification process on multiple models, and all of the multiple models are successfully identified models. The network device needs to configure an identifier for each of the multiple models. When the terminal device subsequently no longer uses some of the multiple models, if the terminal device and the network device corresponding to cell 1 continue to perform the identification process on other models, the bit length of the model identifier will become increasingly longer, which also increases the identification overhead.

[0201] In view of the above problems, the present application provides an artificial intelligence management method and communication device that can effectively reduce the identification overhead between terminal devices and network devices.

[0202] It should be uniformly explained that the embodiments provided in this application can be used to solve the above-mentioned technical problems, but for the convenience of description and understanding, each embodiment will be described separately in combination with different scenarios below.

[0203] Next, the artificial intelligence management method of the embodiment of the present application is described.

[0204] When the terminal device 120 is in cell 1 (such as the second cell) (cell 1 is the source cell of the terminal device 120), the terminal device 120 and the network device 110 corresponding to cell 1 perform an identification process for model 1, and model 1 is a successfully identified model. When the terminal device switches to cell 2 (such as the first cell) (cell 2 is the current resident cell of the terminal device 120), the terminal device 120 can perform an identification process for model 1 with the network device 150 corresponding to cell 2 through the method shown in Figure 5, which can effectively reduce the identification overhead between the terminal device 120 and the network device 150. For details, please refer to Figure 5.

[0205] Figure 5 is a schematic diagram of the interactive flow of the artificial intelligence management method 500 of an embodiment of the present application. Method 500 can be executed by the terminal device 120, the network device 110 and the network device 150, or by a module and / or device (for example, a chip or integrated circuit, etc.) with corresponding functions installed in the terminal device 120, the network device 110 and the network device 150. It may also be completed by an AI entity or AI module, such as RIC, which is not limited to this. The following description will be made using the terminal device 120, the network device 110 and the network device 150 as an example. Method 200 includes:

[0206] S510, the terminal device 120 sends identification 1 (such as the first identification) and identification 2 (such as the second identification) to the network device 150. Identification 1 is an identification configured for model 1 (such as the first model) and comes from the network device 110. Model 1 is a model successfully identified between the network device 110 and the terminal device 120. Identification 2 is used to identify area 1 (such as the first area). Identification 1 is unique within area 1. It can be understood that in the embodiments of the present application, "area" can be replaced with "range" or "usage scope". Identification 1 or the first identification can also be replaced with "local identification". Identification 2 or the second identification can be replaced with "area identification".

[0207] Accordingly, the network device 150 receives the identifier 1 and the identifier 2 .

[0208] Specifically, the terminal device 120 and the network device 110 can perform an identification process for model 1. The specific content of the identification process can be found in the aforementioned description of AI model identification or AI function identification, which will not be repeated here. After completing the identification process for model 1, the network device 110 configures an identifier 1 for model 1 to identify model 1.

[0209] In one example, when model 1 is a model trained by the terminal device 120, the identification process of model 1 between the terminal device 120 and the network device 110 is as follows: the terminal device 120 reports at least one of the following information to the network device 110: functional information / characteristic information of model 1, that is, what function model 1 is used to implement, such as one or more of CSI feedback or CSI prediction or beam prediction or positioning; application scenario / condition of model 1, that is, under what circumstances model 1 can be used, for example, one or more of indoor, outdoor, urban, suburban and other scenarios, or radio resource control (RRC) configurations supported by model 1, such as one or more of antenna, bandwidth, beam set, etc.; performance of model 1, such as generalized cosine similarity (GCS), square generalized cosine similarity (SGCS), minimum mean square error (MSE), normalized mean square error (NMSE), throughput, spectrum efficiency, transmission rate, block error rate (BER), and so on. One or more of the following: data rate, assumed BLER, hybrid automatic repeat request (HARQ) confirmation / non-confirmation (HARQ ACK / NACK), signal to interference plus noise ratio (SINR), reference signal received power (RSRP), etc. The above information (which may also include information not mentioned, etc.) can be collectively referred to as model information of model 1. In other words, when model 1 is a model trained by the terminal device 120, when the terminal device 120 and the network device 110 perform the identification process for model 1, the terminal device 120 reports the model information of model 1 to the network device 110, so that the network device 110 and the terminal device 120 have a consistent understanding of model 1. Furthermore, the network device 110 configures identifier 1 for model 1.

[0210] In another example, when Model 1 is a model trained by network device 110, the recognition process for Model 1 between terminal device 120 and network device 110 is as follows: network device 110 sends model information of Model 1 to terminal device 120, and sends Model 1 to terminal device 120. In this way, terminal device 120 and network device 110 can have a consistent understanding of Model 1. Furthermore, network device 110 configures identifier 1 for Model 1.

[0211] The above-mentioned “Model 1 is a model successfully identified between the network device 110 and the terminal device 120” can be: the terminal device 120 and the network device 110 have a consistent understanding of Model 1, which can indicate that Model 1 is a model successfully identified between the network device 110 and the terminal device 120; it can also be: the network device 110 configures identification 1 for Model 1, which can also indicate that Model 1 is a model successfully identified between the network device 110 and the terminal device 120.

[0212] The aforementioned "successfully identified model" may also mean that model 1 is available to terminal device 120 and network device 110, i.e., terminal device 120 can perform communication tasks based on model 1, such as performing CSI feedback tasks or CSI prediction tasks based on model 1. Alternatively, model 1 may be used within the service range corresponding to network device 110 (e.g., cell 1).

[0213] In one possible implementation, model 1 is at least one of an AI model and an AI function, that is, model 1 can be an AI model, an AI function, or an AI function and an AI model. Accordingly, in one possible implementation, identifier 1 includes at least one of a model identifier and a function identifier, that is, identifier 1 includes a model identifier, or identifier 1 includes a function identifier, or identifier 1 includes both a model identifier (used to refer to a certain AI model, so that the terminal device and the network device can determine the same AI model through the model identifier) ​​and a function identifier (used to refer to a certain AI function, so that the terminal device and the network device can determine the same AI function through the model identifier). When identifier 1 includes a model identifier, model 1 is an AI model; when identifier 1 includes a function identifier, model 1 is an AI function; when identifier 1 includes a model identifier and a function identifier, model 1 is both an AI model and an AI function.

[0214] In S510, the identifier 2 may be from the network device 110 or determined by the terminal device 120. When the identifier 2 is from the network device 110, the network device 110 may send the identifier 2 to the terminal device 120. The identifier 2 is used to identify the area 1 in which the network device 110 is located, thereby facilitating the network device 150 to determine the location of the network device 110 configured with the identifier 1 for the model 1. For example, the network device 110 may send the identifier 2 to the terminal devices in area 1 via broadcast information. When the identifier 2 is determined by the terminal device 120, the terminal device 120 may determine the identifier 2 based on the following parameters. For example, the terminal device 120 may determine its own cell identifier by measuring synchronization signals, such as a primary synchronization signal and a secondary synchronization signal, and thereby determine the identifier 2.

[0215] In a possible implementation, the type of identifier 2 includes at least one of the following: a cell identifier, a cell group identifier, a tracking area identifier, a service area identifier, or a time advance group identifier.

[0216] When the type of identifier 2 is a cell identifier, identifier 2 can be a cell global identifier (CGI), a base station identifier (gNB ID), or a physical cell identifier (PCI). When the type of identifier 2 is a tracking area identifier, identifier 2 can be a tracking area identifier (TAI) or a tracking area code (TAC). When the type of identifier 2 is a service area identifier, identifier 2 can be a service area identifier (SAI). When the type of identifier 2 is a timing advance group identifier, identifier 2 can be a timing advance group identifier (TAGI). The above-mentioned cell group identifier is used to identify a cell group including at least two cells. In addition, the present application does not limit the combination method between the types of identifier 2. For example, the type of identifier 2 can include a tracking area identifier and a service area identifier, etc. At the same time, there is an association between the type of area 1 and the type of identifier 2, or in other words, the type of area 1 is the same as the type of identifier 2.

[0217] Exemplarily, if the type of identifier 2 is a cell identifier, area 1 includes one or more cells. If the type of identifier 2 is a cell group identifier, area 1 includes one or more cell groups. If the type of identifier 2 is a tracking area identifier, area 1 includes one or more tracking areas. If the type of identifier 2 is a service area identifier, area 1 includes one or more service areas. If the type of identifier 2 is a timing advance group identifier, area 1 includes one or more timing advance groups. If the type of identifier 2 is a tracking area identifier and a service area identifier, area 1 includes one or more tracking areas and one or more service areas, etc.

[0218] In one possible implementation, area 1 includes multiple network devices, including network device 110. Area 1 may also be a valid identification area for identifier 1, that is, the terminal devices and network devices in area 1 have the same understanding of model 1 indicated by identifier 1.

[0219] In one possible implementation, the identifier 1 is unique within the area 1. This avoids the identifier conflict problem.

[0220] S520 : The network device 150 obtains model information of the model 1 according to the identifier 1 and the identifier 2 , and determines whether the model 1 is available.

[0221] Specifically, network device 150 determines region 1 based on identifier 2. If the region of network device 150 does not belong to region 1, network device 150 may interact with network devices within region 1 to obtain model information for model 1. For example, network device 150 may interact with one or more network devices within region 1 to determine network device 110 configured with identifier 1 for model 1, and obtain model information for model 1 from network device 110, or obtain model information for model 1 from a network device within region 1 that stores such information. If network device 150 belongs to region 1, network device 150 may determine whether it stores model information for model 1. If not, it may obtain model information for model 1 from other network devices within region 1.

[0222] Alternatively, in another possible implementation, regardless of whether the area of ​​network device 150 belongs to area 1, network device 150 can obtain model information of model 1 from a third-party device based on identifier 1 and identifier 2. For example, network device 150 obtains model information of model 1 from a third-party device that stores model information of area 1.

[0223] Furthermore, the network device 150 may determine whether model 1 is available, that is, the network device 150 determines whether model 1 is available in cell 2. In one example, if model 1 is a model trained by the terminal device 120, the network device 150 may determine whether the RRC configuration supported by model 1 can be configured, or may determine whether the scenario corresponding to cell 2 belongs to the scenario used by model 1. In another example, if model 1 is a bilateral model (i.e., a model jointly determined by the network device 110 and the terminal device 120), the network device 150 may determine whether there is a network-side model that can be paired with model 1.

[0224] S530 : The network device 150 sends response information 1 to the terminal device 120 . The response information 1 is used to indicate whether the model 1 is available.

[0225] Accordingly, the terminal device 120 receives the response information 1 and determines whether the model 1 is available based on the response information 1. Furthermore, the terminal device 120 determines whether the network device 150 successfully identifies the model 1 based on the response information 1.

[0226] To sum up, when the terminal device 120 and the network device 150 re-identify the model 1 that has been successfully identified, the terminal device 120 and the network device 150 may not interact again to identify the complete information of model 1 (the model information of model 1), but only interact with identification 1 and identification 2. The network device 150 can obtain the complete information of model 1 based on identification 1 and identification 2. In this way, the identification overhead between the terminal device 120 and the network device 150 can be effectively reduced.

[0227] Through the above solution, the identification process between the terminal device and the network device can be simplified, and the identification overhead between the terminal device and the network device can be effectively reduced.

[0228] In one possible implementation, method 500 may further include:

[0229] S530a: The network device 150 sends an identifier 3 to the terminal device 120.

[0230] Correspondingly, the terminal device 120 receives identification 3.

[0231] Specifically, when network device 150 determines that model 1 is available and that a new identifier can be used for model 1, network device 150 may send identifier 3 configured by network device 150 for model 1 to terminal device 120. In subsequent operations, terminal device 120 and network device 150 may use identifier 3 to refer to model 1. In this way, network device 150 can configure a new identifier for model 1, thereby facilitating identification and understanding of model 1 by terminal device 120 and network device 150.

[0232] In one possible implementation, the network device 150 may also be configured with an identifier 4 for identifying area 2, and the network device 150 is located in area 2 (area 2 may be the same as area 1). When the terminal device 120 subsequently identifies model 1 (i.e., when switching from cell 2 to cell 3, the terminal device 120 and the network device corresponding to cell 3 identify model 1 again), the terminal device 120 may report identifiers 1 and 2 to other network devices (such as the network device corresponding to cell 3), or may report identifiers 3 and 4, without limitation.

[0233] In one possible implementation, when network device 150 determines that model 1 is available and that model 1 can use a new identifier, response information 1 may include identifier allocation information, which indicates that model 1 is available and may also be used to configure identifier 3. In other words, response information 1 may include identifier 3. When response information 1 includes identifier 3, terminal device 120 may confirm that network device 150 has successfully identified model 1 and that model 1 uses identifier 3.

[0234] In one possible implementation, when network device 150 determines that model 1 is usable and that identifier 1 of model 1 does not need to be changed, response message 1 is confirmation information, used to confirm that model 1 was successfully identified (or that model 1 is usable), and can also be used to indicate that identifier 1 can continue to be used. In subsequent operations, terminal device 120 and network device 150 can continue to use identifier 1 to refer to model 1.

[0235] In a possible implementation, the response information 1 may include an acknowledgment (ACK) message or an identifier 1. When the response information 1 includes the identifier 1, the terminal device 120 confirms that the network device 150 has successfully identified the model 1.

[0236] In a possible implementation, the network device 150 may also directly activate the model 1 through the identifier 1 without sending the response information 1 to the terminal device 120 .

[0237] In one possible implementation, method 500 may further include:

[0238] S530b: The network device 150 sends at least one of the model 2 and the information of the model 2 to the terminal device 120.

[0239] Accordingly, the terminal device 120 receives at least one of the model 2 and the information of the model 2.

[0240] Specifically, when network device 150 determines that model 1 is unavailable, network device 150 sends model 2 and at least one of model 2 information to terminal device 120. If model 2 is already configured on terminal device 120, the model 2 information may be activation information for model 2, which is used to activate model 2. In this way, the new model can be recognized between terminal device 120 and network device 150.

[0241] Specifically, when the network device 150 determines that model 1 is unavailable, the response information 1 sent by the network device 150 to the terminal device 120 may include model 2 and at least one of the information of model 2, which can be used to indicate that the network device 150 failed to successfully identify model 1 or that model 1 is unavailable.

[0242] In one possible implementation, when the network device 150 determines that model 1 is unavailable, the network device 150 may instruct the terminal device 120 through response information 1 to perform the complete recognition process of model 1, or the network device 150 may instruct the terminal device 120 through response information 1 to fall back to the non-AI mode.

[0243] As a possible implementation, the response information 1 may include information instructing the terminal device 120 to fallback to the non-AI mode, or the response information 1 may include information instructing the terminal device 120 to perform a complete recognition process; or the response information 1 includes at least one of the information of model 2 and the information of model 2. Thus, the terminal device 120 may determine that model 1 is unavailable based on the above information.

[0244] It should be noted that the network device 150 determines that model 1 is unavailable, which may be: the network device 150 does not have an RRC configuration matching model 1, or the network device 150 determines that the scenario corresponding to cell 2 is not suitable for the application scenario of model 1, etc., or when model 1 belongs to a dual-end model, the network device 150 does not have a network-side model matching model 1.

[0245] In the above content, there may be more than one group of identifier 1 and identifier 2 reported by the terminal device 120 to the network device 150, that is, there is more than one model for the terminal device 120 to perform recognition. For example, 1 identifier 2 and N identifiers 1 are used to recognize N models, and M (<N) identifiers 2 and N identifiers 1 are used to recognize N models. Correspondingly, the response information 1 may be used to indicate at least one of the following: which models can be used, which models cannot be used; which models need to replace identifier 1 (i.e., the local identifier); the updated identifier 1 (i.e., the local identifier), the models for which the network device 150 does not obtain model information, which models are recognized successfully, and which models are recognized failed, etc.

[0246] In method 500, identifier 1 and identifier 2 are carried in at least one of the following messages: random access messages, such as message 1 (message 1, Msg1), message 3 (message 3, Msg3), message A (message A, MsgA); RRC connection establishment / reestablishment / reconfiguration related information, such as RRC configuration request (RRCSetupRequest) message, RRC configuration complete (RRCSetupComplete) message, RRC reconfiguration complete (RRCReconfigurationComplete) message, RRC reestablishment request message, RRC reestablishment complete (RRCReestablishmentComplete) message; other RRC messages; physical layer messages, such as uplink control message (uplink control information, UCI); MAC layer messages, such as MAC CE. Identifier 1 and identifier 2 may be carried in the same message or different messages.

[0247] It should be noted that this application supports response information 1 being used only to indicate whether model 1 is available and does not carry other information. This application also supports response information 1 carrying other information, and can use this other information to indicate whether model 1 is available. For example, response information 1 includes identifier 3, which is used to indicate that model 1 is available; for another example, response information 1 includes model 2 and at least one of model 2's information, and at least one of model 2 and model 2's information is used to indicate that model 1 is unavailable, etc.

[0248] In addition, method 500 mainly focuses on describing the solution process of initiating identification by the terminal device, and the content of initiating identification by the network device will be described below in conjunction with Figure 6.

[0249] Figure 6 is a schematic diagram of the interactive flow of the artificial intelligence management method 600 of an embodiment of the present application. Method 600 can be executed by the terminal device 120, the network device 110, and the network device 150, or by a module and / or device (for example, a chip or integrated circuit, etc.) with corresponding functions installed in the terminal device 120, the network device 110, and the network device 150. It may also be completed by an AI entity or AI module, such as RIC, which is not limited to this. The following description will be made using the terminal device 120, the network device 110, and the network device 150 as an example. Method 600 includes:

[0250] S610 : The network device 110 sends the model information of the model 1 to the network device 150 .

[0251] Accordingly, the network device 150 receives the model information of the model 1 .

[0252] Specifically, when the terminal device 120 switches to the network device 150, or when the network device 110 plans to switch the terminal device 130 to the network device 150, or when the network device 150 requests the model information of the model 1 from the network device 110, the network device 110 sends the model information of the model 1 to the network device 150.

[0253] S620: The network device 150 identifies the model 1 according to the model information of the model 1, and determines whether the model 1 is available.

[0254] For the description of S620, please refer to the description of S520, which will not be repeated here.

[0255] S630: The network device 150 sends indication information 1 to the terminal device 120. The indication information 1 is used to indicate whether the model 1 is available.

[0256] Correspondingly, the terminal device 120 receives the indication information 1 and determines whether the model 1 is available according to the indication information 1 .

[0257] For the description of S630, please refer to the description of S530, which will not be repeated here.

[0258] Specifically, the network device 150 may obtain the model information of the model 1 from the network device 110, and complete the recognition of the model 1 based on the model information of the model 1. The network device 150 may not obtain the model information of the model 1 from the terminal device 130, which can effectively reduce the recognition overhead between the terminal device 120 and the network device 150.

[0259] Through the above solution, the identification process between the terminal device and the network device can be simplified, and the identification overhead between the terminal device and the network device can be effectively reduced.

[0260] In one possible implementation, method 600 may further include:

[0261] S630a: The network device 110 sends an identifier 5 to the terminal device 120.

[0262] Accordingly, terminal device 120 receives identifier 5 from network device 110. Identifier 5 is used to identify model 1. For a description of identifier 5, refer to the description of identifier 1 above and will not be repeated here. In this way, network device 150 can configure an identifier for model 1, thereby facilitating identification and understanding of model 1 by terminal device 120 and network device 150.

[0263] In one possible implementation, method 600 may further include:

[0264] S630b: The network device 110 sends the model 2 and at least one of the information of the model 2 to the terminal device 120.

[0265] For the description of S630b, please refer to the description of S530b, which will not be repeated here. In this way, the terminal device 120 and the network device 150 can complete the recognition of the new model.

[0266] After the terminal device 120 updates the successfully recognized model 1, the terminal device 120 and the network device 110 perform the complete recognition process again for the updated model 1, which increases the recognition overhead. Therefore, the terminal device 120 can recognize the updated model 1 with the network device 110 using the method shown in Figure 7, thereby effectively reducing the recognition overhead between the terminal device 120 and the network device 110. For details, please refer to Figure 7.

[0267] Figure 7 is a schematic diagram of the interaction flow of the artificial intelligence management method 700 according to an embodiment of the present application. Method 700 can be executed by the terminal device 120 and the network device 110, or by modules and / or devices (e.g., chips or integrated circuits) with corresponding functions installed in the terminal device 120 and the network device 110. It may also be completed by an AI entity or AI module, such as RIC, without limitation. The following description will be made using the terminal device 120 and the network device 110 as an example. Method 700 includes:

[0268] Optionally, in S710 , the terminal device 120 and the network device 110 perform an identification process for model 1 .

[0269] For the description of S710, please refer to the description of S510 above, which will not be repeated here.

[0270] S720: The terminal device 120 sends indication information 2 to the network device 110. The indication information 2 is used to indicate that the model 1 has been updated.

[0271] Correspondingly, the network device 110 receives the indication information 2 and determines, according to the indication information 2, that the model 1 has been updated.

[0272] After terminal device 120 updates the successfully identified Model 1, that is, after the structure and / or parameters of Model 1 change, terminal device 120 and network device 110 re-identify Model 1. The purpose of re-identification is to allow network device 110 to perceive that Model 1 has been updated. If network device 110 does not perceive that Model 1 has been updated, it may be unable to determine whether deteriorating network performance is caused by Model 1.

[0273] In one possible implementation, the indication information 2 may include any one of the following: an identifier of model 1, information on the performance of the updated model 1 (which is used to indicate the performance of the model 1 after the update), or information on changes in the model information of model 1 due to the model update. When the indication information 2 includes the identifier of model 1, the network device 110 determines that the model 1 has been updated based on the identifier of model 1. When the indication information 2 includes information on the performance of the updated model 1, the network device 110 determines that the model 1 has been updated based on the information on the performance of the updated model 1. The information on the performance of the updated model 1 may also indicate changes in the performance of the updated model 1 compared to the model 1 before the update. The network device updates the corresponding model information of the model 1 stored in itself based on the received model information of the model 1. For other model information of the model 1 not sent by the terminal device, it is assumed that no changes have been made.

[0274] S730 : The network device 110 sends a response message 2 to the terminal device 120 . The response message 2 includes an identifier configured by the network device 110 for the updated model 1 , or the response message 2 is an identifier indicating that the model 1 is to be used.

[0275] Specifically, the network device 110 may reconfigure a new identifier for the updated model 1, or the network device 110 may determine to continue using the identifier of the model 1. In this way, the network device 110 may feedback to the terminal device 120 that it has sensed that the first model has been updated.

[0276] It can be understood that the method shown in FIG. 7 can be combined with the method shown in FIG. 5 or FIG. 6 , or can be independent of the method shown in FIG. 5 or FIG. 6 .

[0277] In summary, the above technical solution allows the terminal device to let the network device know that a successfully recognized model has been updated, effectively reducing the recognition overhead between the terminal device and the network device. This also avoids the need for the terminal device and the network device to re-perform the complete recognition process for the updated model.

[0278] It should be noted that method 700 is described using the interaction between terminal device 120 and network device 110 as an example. However, network device 110 may also be network device 150, and the behaviors of the two are substantially the same. For ease of description, the interaction process between terminal device 120 and network device 150 as shown in method 700 will not be further described below.

[0279] When multiple models are identified between the terminal device 120 and the network device 110, the network device 110 can configure an identifier for each successfully identified model. If the terminal device 120 no longer uses some of the successfully identified models during subsequent use, these models will affect the bit length of the identifiers of subsequent successfully identified models, thereby increasing the identification overhead between the terminal device and the network device. Therefore, the terminal device 120 can effectively reduce the identification overhead by using the method shown in Figure 8. For details, please refer to Figure 8.

[0280] Figure 8 is a schematic diagram of the interaction flow of the artificial intelligence management method 800 according to an embodiment of the present application. The method 800 can be executed by the terminal device 120 and the network device 110, or by a module and / or device (e.g., a chip or integrated circuit, etc.) with corresponding functions installed in the terminal device 120 and the network device 110. It may also be completed by an AI entity or AI module, such as RIC, without limitation. The following description will be made using the terminal device 120 and the network device 110 as an example. The method 800 includes:

[0281] S810: The network device 110 sends indication information 3 to the terminal device 120, where the indication information 3 is used to indicate the cancellation of an identification of at least one model.

[0282] Correspondingly, the terminal device 120 receives indication information 3.

[0283] S820. The terminal device 120 cancels the identification of the at least one model according to the instruction information 3.

[0284] Specifically, the terminal device 120 cancels the identification of at least one model according to the instruction of the network device 110. In this way, the bit length of the model identification can be effectively reduced, which is conducive to reducing the identification overhead between the terminal device and the network device.

[0285] In one possible implementation, the indication information 3 includes an identifier of each model in the at least one model, or the indication information 3 includes model information of each model in the at least one model. In this way, the terminal device 120 can cancel the identifier of the at least one model according to the content included in the indication information 3.

[0286] It is understood that indication information 3 can take effect at time n+k, where time n is the time when terminal device 120 receives indication information 3. Time n can be the first or last OFDM symbol, time slot, subframe, or frame in which terminal device 120 receives indication information 3, and k is a predefined or preconfigured time offset. After indication information 3 takes effect, the identifier of the deregistered model is no longer used for its corresponding indication original model.

[0287] In one possible implementation, method 800 may further include:

[0288] S810a: The terminal device 120 sends a request message 1 to the network device 110, where the request message 1 is used to request to deregister the at least one model.

[0289] Accordingly, the network device 110 receives the request information 1 and can determine the indication information 3 according to the request information 1. In this way, the terminal device 120 can proactively propose to cancel the identification of some models.

[0290] Specifically, the request information 1 may include the identifier of each model in the at least one model, or the request information 1 may include the model information of each model in the at least one model. The model information of each model is associated with the model identifier. This facilitates the network device 110 in determining which model identifiers need to be deregistered.

[0291] In one possible implementation, method 800 may further include:

[0292] S820a. The terminal device 120 sends response information 2 to the network device 110. The response information 2 is used to indicate whether the indication information 3 is successfully received.

[0293] Accordingly, network device 110 receives response information 2 and determines, based on response information 2, whether terminal device 120 has successfully received indication information 3. This allows network device 110 to determine whether terminal device 120 has successfully received indication information 3. It should be noted that method 800 is described using the interaction between terminal device 120 and network device 110 as an example. However, network device 110 may also be network device 150, and the behaviors of the two are substantially the same. For ease of description, the following description will not further detail the interaction between terminal device 120 and network device 150 as shown in method 800.

[0294] It is understandable that the method shown in FIG. 8 may be combined with at least one of the methods shown in FIG. 5 or FIG. 6 or the method shown in FIG. 7 , or may be independent of at least one of the methods shown in FIG. 5 to FIG. 7 .

[0295] In addition, the content described in Figures 5 to 8 is about how to reduce the identification overhead between the terminal device and the network device. However, after the model identification is completed between the terminal device and the network device, there may be a conflict between the model and the RRC configuration. Specifically, each model will have an RRC configuration that can be matched, for example, the antenna port supports 32 ports, the bandwidth supports 10MHz, the feedback bit supports 100 bits, etc. Since model activation and RRC configuration are two independent configurations, it is possible that the activated model does not match the RRC configuration. The terminal device 120 can deal with the situation where the activated model does not match the RRC configuration by the method shown in Figure 9, and please refer to Figure 9 for details. It can be understood that the method shown in Figure 9 can be combined with at least one of the methods shown in Figures 5 to 8, or it can be independent of at least one of the methods shown in Figures 5 to 8.

[0296] Figure 9 is a schematic diagram of the interaction flow of the artificial intelligence management method 900 according to an embodiment of the present application. The method 900 can be executed by the terminal device 120 and the network device 110, or by a module and / or device (e.g., a chip or integrated circuit, etc.) with corresponding functions installed in the terminal device 120 and the network device 110. It may also be completed by an AI entity or AI module, such as RIC, without limitation. The following description will be made using the terminal device 120 and the network device 110 as an example. The method 900 includes:

[0297] S910. The network device 110 sends model configuration information 1 and RRC configuration information 1 to the terminal device 120.

[0298] Accordingly, the terminal device 120 receives model configuration information 1 and RRC configuration information 1. Model configuration information 1 is used to activate model 3, and RRC configuration information 1 is used to configure RRC configuration 1.

[0299] S920. When there is a conflict between model configuration information 1 and RRC configuration information 1, the terminal device 120 determines whether to ignore model configuration information 1 or RRC configuration information 1 based on the priority of model configuration information 1 and the priority of RRC configuration information 1.

[0300] Specifically, the conflict between model configuration information 1 and RRC configuration information 1 may be: there is a mismatch between model 3 used to activate by model configuration information 1 and RRC configuration 1 used to configure by RRC configuration information 1, that is, RRC configuration 1 cannot be applied to model 3, or model 3 cannot support RRC configuration 1. When the priority of model configuration information 1 is higher than the priority of RRC configuration information 1, the terminal device 120 determines to ignore RRC configuration information 1 and use RRC configuration 2 that matches model 3 (RRC configuration 2 has been configured on the terminal device 120 side). When the priority of RRC configuration information 1 is higher than the priority of model configuration information 1, the terminal device 120 determines to ignore model configuration information 1 and continue to use the previous model, or the previous non-AI mode, or fall back to the non-AI mode.

[0301] In one possible implementation, the priority of the signaling used to carry the model configuration information 1 is higher than the priority of the signaling used to carry the RRC configuration information 1. Specifically, the terminal device 120 can make a selection based on whether the priority of the signaling used to carry the model configuration information 1 is higher than the priority of the signaling used to carry the RRC configuration information 1. For example, when the priority of the signaling used to carry the model configuration information 1 is higher than the priority of the signaling used to carry the RRC configuration information 1, the terminal device 120 determines to ignore the RRC configuration information 1. In this way, the terminal device can handle the conflict between the first model configuration information and the first wireless resource control configuration information based on the priority between the signaling used to carry the first model configuration information and the signaling used to carry the first wireless resource control configuration information.

[0302] In one possible implementation, the priority of the signaling used to carry RRC configuration information 1 is higher than the priority of the signaling used to carry model configuration information 1. Specifically, the terminal device 120 can make a selection based on whether the priority of the signaling used to carry model configuration information 1 is higher than the priority of the signaling used to carry RRC configuration information 1. For example, when the priority of the signaling used to carry RRC configuration information 1 is higher than the priority of the signaling used to carry model configuration information 1, the terminal device 120 determines to ignore model configuration information 1. In this way, the terminal device can handle the conflict between the first model configuration information and the first wireless resource control configuration information based on the priority between the signaling used to carry the first model configuration information and the signaling used to carry the first wireless resource control configuration information.

[0303] A possible implementation method supported by the present application is that the priority of the signaling received later may be higher than the priority of the signaling received earlier. When the reception time of RRC configuration information 1 is after the reception time of model configuration information 1, the terminal device 120 determines to ignore the model configuration information 1; when the reception time of RRC configuration information 1 is before the reception time of model configuration information 1, the terminal device 120 determines to ignore RRC configuration information 1.

[0304] In one possible implementation, the present application further supports the provision of a higher priority for signaling received earlier than for signaling received later. When the reception time of RRC configuration information 1 is before the reception time of model configuration information 1, the terminal device 120 determines to ignore model configuration information 1; when the reception time of RRC configuration information 1 is after the reception time of model configuration information 1, the terminal device 120 determines to ignore model configuration information 1.

[0305] The terminal device 120 may also report to the network device 110 that the model configuration information 1 conflicts with the RRC configuration information 1. In this way, the network device 110 may process the conflict.

[0306] Through the above scheme, the terminal device can determine whether to ignore the model configuration information or the RRC configuration information based on the priority of the model configuration information 1 and the priority of the RRC configuration information 1. In this way, the terminal device can resolve the conflict problem between the model configuration information 1 and the RRC configuration information 1.

[0307] It should be noted that method 900 is described using the interaction between terminal device 120 and network device 110 as an example. However, network device 110 may also be network device 150, and the behaviors of the two are substantially the same. For ease of description, the interaction process between terminal device 120 and network device 150 as shown in method 900 will not be further described below.

[0308] It should also be noted that in the above scheme, this application supports the mutual combination between the embodiments, for example, the combination between the method shown in Figure 5 and the method shown in Figure 9, the combination between the method shown in Figure 5 and the method shown in Figure 7, etc., without limitation.

[0309] Finally, the device embodiment of the embodiment of the present application is introduced.

[0310] To implement the various functions of the methods provided herein, both terminal devices and network devices may include hardware structures and / or software modules, with the aforementioned functions implemented in the form of hardware structures, software modules, or a combination of hardware structures and software modules. Whether a particular function is implemented in the form of hardware structures, software modules, or a combination of hardware structures and software modules depends on the specific application and design constraints of the technical solution.

[0311] Figure 10 is a schematic block diagram of a communication device 1000 according to an embodiment of the present application. The communication device 1000 includes a processor 1010 and a communication interface 1020, which may be interconnected via a bus 1030. The communication device 1000 may be a network device 110 or a network device 150, or a terminal device 120.

[0312] Optionally, the communication device 1000 may further include a memory 1040. The memory 1040 includes, but is not limited to, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), or portable read-only memory (CD-ROM), and is used for related instructions and data.

[0313] The processor 1010 may be one or more central processing units (CPUs). In the case where the processor 1010 is a CPU, the CPU may be a single-core CPU or a multi-core CPU. The processor 1010 may be a signal processor, a chip, or other integrated circuit that can implement the method of the present application, or a portion of the circuitry used for processing functions in the aforementioned processor, chip, or integrated circuit. In addition, the communication interface 1020 may also be an input / output interface, which is used for inputting or outputting signals or data, or may be an input / output circuit.

[0314] When the communication apparatus 1000 is a terminal device 120 , illustratively, the processor 1010 is configured to perform the following operations: sending identification 1 and identification 2 to the network device 150 ; receiving response information 1 from the network device 150 , and the like.

[0315] When the communication device 1000 is a network device 150, illustratively, the processor 1010 is used to perform the following operations: receive identification 1 and identification 2 from the terminal device 120; obtain model information of model 1 based on identification 1 and identification 2; send response information 1 to the terminal device 120, etc.

[0316] When the communication apparatus 1000 is the network device 110 , illustratively, the processor 1010 is configured to perform the following operations: sending identification 1 and identification 2 to the terminal device 120 .

[0317] When the communication device 1000 is the network device 110, the network device 150 or the terminal device 120, it will be responsible for executing the methods or steps related to the network device 110, the network device 150 or the terminal device 120 in the above method embodiments.

[0318] It is understood that when the communication device 1000 is a terminal device 120, a network device 110, or a network device 150, the communication interface 1020 may also be referred to as a transceiver. The above description is merely exemplary. For details, please refer to the contents of the above method embodiments. The implementation of each operation in Figure 10 may also correspond to the corresponding description of the method embodiments shown in Figures 5 to 9.

[0319] Figure 11 is a schematic block diagram of a communication device 1100 according to an embodiment of the present application. Communication device 1100 may be a network device 110, a network device 150, or a terminal device 120, or may be a chip or module within network device 110, a network device 150, or a terminal device 120, configured to implement the methods described in the above embodiments. Communication device 1100 includes a transceiver unit 1110. The following provides an exemplary description of transceiver unit 1110.

[0320] The transceiver unit 1110 may include a transmitting unit and a receiving unit. The transmitting unit is configured to execute a transmitting operation of the communication device, and the receiving unit is configured to execute a receiving operation of the communication device. For ease of description, this embodiment of the application combines the transmitting unit and the receiving unit into a single transceiver unit. This is described here as a unified description and will not be repeated later.

[0321] When the communication apparatus 1100 is the terminal device 120, illustratively, the transceiver unit 1110 is configured to send the identifier 1 and the identifier 2 to the network device 150. The transceiver unit 1110 is further configured to receive response information 1 from the network device 150, etc.

[0322] Optionally, the communication apparatus 1100 may further include a processing unit 1120 configured to execute the content of the terminal device 120 involving processing, coordination, and other steps. For example, the processing unit 1120 is configured to perform an identification process of the model 1 with the network device 110 .

[0323] When the communication device 1100 is a network device 110, illustratively, the transceiver unit 1110 is used to send identification 1 and identification 2 to the terminal device.

[0324] Optionally, the communication device 1100 may further include a processing unit 1120 configured to execute the content of the steps involving processing and coordination of the network device 110. For example, the processing unit 1120 is configured to perform the recognition process of the model 1 with the terminal device 120.

[0325] When the communication device 1100 is the network device 110 , the network device 150 , or the terminal device 120 , it will be responsible for executing the methods or steps related to the network device 110 , the network device 150 , or the terminal device 120 in the aforementioned method embodiments.

[0326] Optionally, the communication device 1100 further includes a storage unit 1130, which is used to store a program or code for executing the aforementioned method.

[0327] The device embodiments shown in Figures 10 and 11 are used to implement the contents described in Figures 5 to 9. The specific execution steps and methods of the devices shown in Figures 10 and 11 can refer to the contents described in the above method embodiments.

[0328] The present application also provides a chip, including a processor, for calling and executing instructions stored in a memory from the memory, so that a communication device equipped with the chip executes the methods in the above examples.

[0329] The present application also provides another chip, comprising: an input interface, an output interface, and a processor, wherein the input interface, the output interface, and the processor are connected via an internal connection path, and the processor is configured to execute code in a memory. When the code is executed, the processor is configured to execute the methods in the above examples. Optionally, the chip also includes a memory, which is configured to store computer programs or code.

[0330] The present application also provides a processor for coupling with a memory, and for executing the methods and functions involving a network device or a terminal device in any of the above embodiments.

[0331] In another embodiment of the present application, a computer program product including instructions is provided. When the computer program product is run on a computer, the method of the above embodiment is implemented.

[0332] The present application also provides a computer program. When the computer program is executed in a computer, the method of the aforementioned embodiment is implemented.

[0333] In another embodiment of the present application, a computer-readable storage medium is provided, which stores a computer program. When the computer program is executed by a computer, the method described in the above embodiment is implemented.

[0334] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0335] 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.

[0336] In the several embodiments provided in this application, the disclosed systems, devices, and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0337] Units described as separate components may or may not be physically separate, and components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0338] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0339] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiment of the present application, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the various embodiments of the present application. The aforementioned storage medium includes various media that can store program codes, such as a USB flash drive, a mobile hard disk, a ROM, a RAM, a magnetic disk, or an optical disk.

[0340] The above is only a specific implementation of the embodiment of the present application, but the scope of protection of the embodiment of the present application is not limited to this. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed in the embodiment of the present application, and they should be included in the scope of protection of the embodiment of the present application. Therefore, the scope of protection of the embodiment of the present application should be based on the scope of protection of the claims.

Claims

1. An artificial intelligence management method, characterized in that: include: Sending a first identifier and a second identifier to a first network device, where the first identifier is an identifier configured for a first model and comes from a second network device, the first model is a model successfully identified between the second network device and a terminal device, the second identifier is used to identify a first area, the first identifier is unique within the first area, and the first identifier includes at least one of a model identifier and a function identifier; Response information is received from the first network device, where the response information is used to indicate whether the first model is available.

2. The method according to claim 1, characterized in that The response information is used to indicate that the first model is available, and the method further includes: receiving a third identifier from the first network device, where the third identifier is an identifier configured by the first network device for the first model; or, The response information is used to indicate that the first model is available, and includes: The response information includes the third identifier.

3. The method according to claim 1, characterized in that The response information is used to indicate that the first model is unavailable, and the method further includes: receiving at least one of a second model and second model information from the first network device, wherein the second model information is used to activate the second model; or, receiving information from the first network device indicating to fall back to a non-artificial intelligence AI mode; or, receiving information from the first network device instructing to complete the identification process; or, The response information is used to indicate that the first model is unavailable, and includes one of the following: The response information includes at least one of the second model and the information of the second model; or, The response information includes information indicating that the terminal device falls back to the non-AI mode; or, The response information indicates information that the terminal device performs a complete identification process.

4. The method according to any one of claims 1 to 3, characterized in that The response information includes the first identifier.

5. The method according to any one of claims 1 to 4, characterized in that The type of the second identifier includes at least one of the following: A cell identifier, a cell group identifier, a tracking area identifier, a service area identifier, or a time advance group identifier; The type of the first area is associated with the type of the second identifier.

6. The method according to any one of claims 1 to 5, characterized in that The area of ​​the second network device belongs to the first area.

7. The method according to any one of claims 1 to 6, characterized in that The method further comprises: Receive the first identifier from the second network device.

8. The method according to claim 7, characterized in that The first identifier is carried in at least one of the following messages: Random access message, radio resource control RRC configuration request message, RRC configuration complete message, RRC reconfiguration complete message, RRC reconstruction request message, or physical layer message.

9. The method according to any one of claims 1 to 8, characterized in that The method further comprises: The second identifier is received from the second network device.

10. The method according to claim 9, characterized in that The second identifier is carried in at least one of the following messages: Random access message, radio resource control RRC configuration request message, RRC configuration complete message, RRC reconfiguration complete message, RRC reconstruction request message, or physical layer message.

11. The method according to any one of claims 1 to 10, characterized in that The first network device manages a first cell, where the first cell is a current resident cell of the terminal device. The second network device manages a second cell, and the second cell is a source cell of the terminal device.

12. An artificial intelligence management method, characterized in that: The method is performed by a second network device or a chip used for the second network device, and includes: receiving a first identifier and a second identifier from a terminal device, wherein the first identifier is an identifier configured by a first network device for a first model, the first model is a model successfully identified between the first network device and the terminal device, the second identifier is used to identify a first area, the first identifier is unique within the first area, and the first identifier includes at least one of a model identifier and a function identifier; Acquire model information of the first model according to the first identifier and the second identifier, and determine whether the first model is available; Sending response information to the terminal device, where the response information is used to indicate whether the first model is available.

13. The method according to claim 12, characterized in that The response information is used to indicate that the first model is available, and the method further includes: Sending a third identifier to the terminal device, where the third identifier is an identifier configured by the second network device for the first model; or, The response information is used to indicate that the first model is available, and includes: The response information includes the third identifier.

14. The method according to claim 12, characterized in that The response information is used to indicate that the first model is unavailable, and the method further includes: sending a second model or at least one of information of a second model to the terminal device, where the second model is different from the first model, and the information of the second model is used to activate the second model; or, Instructing the terminal device to return to a non-AI mode; or, instructing the terminal device to perform a complete identification process; or, The response information is used to indicate that the first model is unavailable, and includes: The response information includes at least one of the second model and the information of the second model; or, The response information includes information indicating that the terminal device falls back to a non-AI mode; or, The response information instructs the terminal device to perform a complete identification process.

15. The method according to any one of claims 12 to 14, characterized in that The response information includes the first identifier.

16. The method according to any one of claims 12 to 15, characterized in that The type of the second identifier includes at least one of the following: A cell identifier, a cell group identifier, a tracking area identifier, a service area identifier, or a time advance group identifier; The type of the first area is associated with the type of the second identifier.

17. The method according to any one of claims 12 to 16, characterized in that The area of ​​the first network device belongs to the first area.

18. The method according to any one of claims 12 to 17, characterized in that The first identifier is carried in at least one of the following messages: Random access message, radio resource control RRC configuration request message, RRC configuration complete message, RRC reconfiguration complete message, RRC reconstruction request message, or physical layer message.

19. The method according to any one of claims 12 to 18, characterized in that The second identifier is carried in at least one of the following messages: Random access message, radio resource control RRC configuration request message, RRC configuration complete message, RRC reconfiguration complete message, RRC reconstruction request message, or physical layer message.

20. The method according to any one of claims 12 to 19, characterized in that The second network device manages a first cell, where the first cell is a current resident cell of the terminal device. The first network device manages a second cell, and the second cell is a source cell of the terminal device.

21. A method for managing artificial intelligence, characterized in that: The method is performed by a second network device or a chip used for the second network device, and includes: Receiving model information of a first model from a first network device, where the first model is a model successfully identified between the first network device and a terminal device; Performing identification processing on the first model according to the model information of the first model, and determining whether the first model is available; Sending indication information to the terminal device, where the indication information is used to indicate whether the first model is available.

22. The method according to claim 21, characterized in that The indication information is used to indicate that the first model is available, and the method further includes: A first identifier is sent to the terminal device, where the first identifier is used to identify the first model.

23. The method according to claim 22, characterized in that The first identifier is unique in the first area, and the area of ​​the second network device belongs to the first area.

24. The method according to claim 22 or 23, characterized in that The first identifier is carried in at least one of the following messages: Random access message, radio resource control RRC configuration request message, RRC configuration complete message, RRC reconfiguration complete message, RRC reconstruction request message, or physical layer message.

25. The method according to claim 21, characterized in that The indication information is used to indicate that the first model is unavailable, and the method further includes: A second model and at least one of the information of the second model are sent to the terminal device, where the second model is different from the first model, and the information of the second model is used to activate the second model.

26. An artificial intelligence management method, characterized in that: The method is executed by a terminal device or a chip used for a terminal device, and includes: An indication message is sent to the network device, where the indication message is used to indicate that the first model has been updated, and the first model is a model successfully identified between the network device and the terminal device.

27. The method according to claim 26, characterized in that The method further comprises: Receive response information from the network device, where the response information includes an identifier configured by the network device for the updated first model, or the response information is an identifier used to indicate that the first model is continued to be used.

28. The method according to claim 26 or 27, characterized in that The instruction information includes any one of the following: Information about the performance of the first model after update, or an identifier of the first model.

29. An artificial intelligence management method, characterized in that: The method is performed by a network device or a chip used for a network device, and includes: Receiving indication information from a terminal device, the indication information is used to indicate that a first model has been updated, the first model being a model successfully identified between the terminal device and the network device; According to the indication information, response information is sent to the terminal device, the response information includes an identifier configured by the network device for the updated first model, or the response information is used to indicate an identifier for continuing to use the first model.

30. The method according to claim 29, characterized in that The instruction information includes any one of the following: Information about the performance of the first model after update, or an identifier of the first model.

31. A method for managing artificial intelligence, characterized in that: The method is executed by a terminal device or a chip used for a terminal device, and includes: Receiving instruction information from a network device, wherein the instruction information is used to instruct to cancel the identification of at least one model; According to the indication information, the identification of the at least one model is cancelled; wherein each model of the at least one model is a model successfully identified between the network device and the terminal device.

32. The method according to claim 31, characterized in that Before receiving the indication information from the network device, the method further includes: Sending request information to the network device, wherein the request information is used to request to deregister the identification of the at least one model.

33. The method according to claim 32, characterized in that The request information includes at least one of the following: The identifier of each model in the at least one model, or the model information of each model in the at least one model.

34. The method according to any one of claims 31 to 33, characterized in that The indication information includes at least one of the following: The identifier of each model in the at least one model, or the model information of each model in the at least one model.

35. The method according to any one of claims 31 to 34, characterized in that The method further comprises: Sending response information to the network device, where the response information is used to indicate whether the indication information is successfully received.

36. An artificial intelligence management method, characterized in that: The method is performed by a network device or a chip used for a network device, and includes: Indication information is sent to a terminal device, where the indication information is used to indicate the cancellation of an identification of at least one model, each of the at least one model being a model successfully identified between the terminal device and the network device.

37. The method according to claim 36, characterized in that The method further comprises: Receive request information from the terminal device, where the request information is used to request to cancel the identification of the at least one model.

38. The method according to claim 36 or 37, characterized in that The method further comprises: Receive response information from the terminal device, where the response information is used to indicate whether the indication information is successfully received.

39. The method according to claim 37 or 38, characterized in that The request information includes at least one of the following: The identifier of each model in the at least one model, or the model information of each model in the at least one model.

40. The method according to any one of claims 36 to 39, characterized in that The indication information includes at least one of the following: The identifier of each model in the at least one model, or the model information of each model in the at least one model.

41. An artificial intelligence management method, characterized in that: The method is executed by a terminal device or a chip used for a terminal device, and includes: Receiving a first model configuration message and first radio resource control configuration information from a network device, wherein the first model configuration information is used to activate the first model, and the first radio resource control configuration information is used to configure the first radio resource control configuration; When there is a conflict between the first model configuration information and the first wireless resource control configuration information, it is determined whether to ignore the first model configuration information or the first wireless resource control configuration information according to the priority between the first model configuration information and the first wireless resource control configuration information.

42. The method according to claim 41, characterized in that The determining, according to the priority of the first model configuration information and the priority of the first radio resource control configuration information, to ignore the first model configuration information or the first radio resource control configuration information comprises: Determine whether to ignore the first model configuration information or the first wireless resource control information based on the priority of the signaling used to carry the first model configuration information and the priority of the signaling used to carry the first wireless resource control configuration information.

43. The method according to claim 42, characterized in that When the priority of the signaling used to carry the first model configuration information is higher than the priority of the signaling used to carry the first radio resource control configuration information, the method includes: Determine to ignore the first radio resource control configuration information.

44. The method according to claim 42, characterized in that When the priority of the signaling used to carry the first radio resource control configuration information is higher than the priority of the signaling used to carry the first model configuration information, the method includes: Determine to ignore the first model configuration information.

45. A communication device, characterized in that: comprising a processor, the processor being configured to: By executing computer programs or instructions, or by logic circuits, enabling the communication device to perform the method according to any one of claims 1 to 11; or, enabling the communication device to perform the method according to any one of claims 12 to 20; or, causing the communication device to perform the method according to any one of claims 21 to 25; or, causing the communication device to perform the method according to any one of claims 26 to 28; or, causing the communication device to perform the method according to any one of claims 29 to 30; or, causing the communication device to execute the method according to any one of claims 31 to 35; or, causing the communication device to perform the method according to any one of claims 36 to 40; or, The communication device is enabled to perform the method according to any one of claims 41 to 44.

46. ​​The device according to claim 45, characterized in that The communication device further comprises a memory for storing the computer program or instructions.

47. The device according to claim 45 or 46, characterized in that The communication device further comprises a communication interface, and the communication interface is used for inputting and / or outputting signals.

48. A communication device, characterized in that: It comprises a processing circuit and an input-output interface, wherein the input-output interface is used to input and / or output signals, and the processing circuit is used to execute the method according to any one of claims 1 to 44.

49. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program or instructions, and when the computer program or the instructions are run on a computer, the method according to any one of claims 1 to 44 is executed.

50. A computer program product, characterized in that The invention comprises instructions which, when executed on a computer, cause the method according to any one of claims 1 to 44 to be performed.

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