Communication method, first network element, second network element, and communication system

Abstract

The present disclosure relates to a communication method, a first network element, a second network element, and a communication system. The communication method comprises: a first network element sending first information to a second network element, wherein the first information comprises artificial intelligence (AI) function information running on a terminal. The embodiments of the present disclosure can realize the coordination between a terminal, a core network device and a base station device for an AI model deployed at the terminal or for AI functions.

Description

Communication method, first network element, second network element and communication system Technical Field

[0001] The present disclosure relates to the field of communication technologies, and in particular to a communication method, a first network element, a second network element, and a communication system. Background Art

[0002] Artificial Intelligence (AI) is gradually being applied in the communications field, for example, in 5G New Radio (NR) communications scenarios and even in 6G communications scenarios.

[0003] Summary of the Invention

[0004] To ensure stable communications, coordination is required between terminals, core network devices, and access network devices regarding the AI ​​models deployed on terminals or the use of AI functions.

[0005] The embodiments of the present disclosure provide a communication method, a first network element, a second network element, and a communication system.

[0006] According to a first aspect of an embodiment of the present disclosure, a communication method is proposed, comprising: a first network element sending first information to a second network element, wherein the first information includes artificial intelligence (AI) function information running on a terminal.

[0007] According to a second aspect of an embodiment of the present disclosure, a communication method is proposed, the method including: a second network element receiving first information, the first information being sent by a first network element, the first information including artificial intelligence (AI) function information running on a terminal.

[0008] According to a third aspect of an embodiment of the present disclosure, a communication method is proposed, comprising: a first network element sending first information to a second network element, wherein the first information includes artificial intelligence (AI) function information running on a terminal; and the second network element receiving the first information.

[0009] According to a fourth aspect of an embodiment of the present disclosure, a first network element is proposed, comprising: a transceiver module, configured to send first information to a second network element, wherein the first information includes artificial intelligence (AI) function information running on a terminal.

[0010] According to the fifth aspect of an embodiment of the present disclosure, a second network element is proposed, including: a transceiver module for receiving first information, wherein the first information is sent by the first network element, and the first information includes artificial intelligence AI function information running on the terminal.

[0011] According to a sixth aspect of an embodiment of the present disclosure, a first network element is proposed, comprising: one or more processors; wherein the processor is used to execute the communication method of the first aspect.

[0012] According to a seventh aspect of an embodiment of the present disclosure, a second network element is proposed, comprising: one or more processors; wherein the processor is used to execute the communication method of the second aspect.

[0013] According to an eighth aspect of an embodiment of the present disclosure, a communication system is provided, including a terminal and a network device, wherein the terminal is configured to implement the communication method of the first aspect, and the network device is configured to implement the communication method of the second aspect.

[0014] According to a ninth aspect of an embodiment of the present disclosure, a storage medium is provided, wherein the storage medium stores instructions. When the instructions are executed on a communication device, the communication device executes the communication method of any one of the first and second aspects.

[0015] Through the embodiments of the present disclosure, coordination between the terminal, core network equipment and access network equipment for the AI ​​model deployed in the terminal, or between AI functions can be achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions in the embodiments of the present disclosure, the following drawings required for describing the embodiments are introduced. The following drawings are merely some embodiments of the present disclosure and do not impose specific limitations on the protection scope of the present disclosure.

[0017] FIG1 is a schematic diagram showing the architecture of a communication system according to an embodiment of the present disclosure.

[0018] FIG2A is an interactive schematic diagram illustrating a communication method according to an embodiment of the present disclosure.

[0019] FIG2B is an interactive schematic diagram of a communication method corresponding to situation -A) according to an embodiment of the present disclosure.

[0020] FIG2C is an interactive schematic diagram of a communication method corresponding to situation -B) according to an embodiment of the present disclosure.

[0021] FIG2D is an interactive schematic diagram of a communication method corresponding to situation -C) according to an embodiment of the present disclosure.

[0022] FIG2E is an interactive schematic diagram of a communication method corresponding to situation -D) according to an embodiment of the present disclosure.

[0023] FIG3 is a flow chart of a communication method according to an embodiment of the present disclosure.

[0024] FIG4A is a flow chart showing a communication method according to an embodiment of the present disclosure.

[0025] FIG4B is a flow chart illustrating a communication method according to an embodiment of the present disclosure.

[0026] FIG5 is an interactive diagram illustrating a communication method according to an embodiment of the present disclosure.

[0027] FIG6A is a schematic structural diagram of a first network element proposed in an embodiment of the present disclosure.

[0028] FIG6B is a schematic structural diagram of a second network element proposed in an embodiment of the present disclosure.

[0029] FIG7A is a schematic structural diagram of a communication device proposed in an embodiment of the present disclosure.

[0030] FIG7B is a schematic diagram of the structure of the chip proposed in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0031] The embodiments of the present disclosure provide a communication method, a first network element, a second network element, and a communication system.

[0032] In a first aspect, an embodiment of the present disclosure proposes that a first network element sends first information to a second network element, where the first information includes artificial intelligence (AI) function information running on the terminal.

[0033] In the above embodiment, the first information is sent to the second network element through the first network element, and the AI ​​function information of the terminal is sent to the second network element, so that the second network element can coordinate the AI ​​model or AI function based on the first information, thereby ensuring the stability of the communication process.

[0034] In combination with some embodiments of the first aspect, in some embodiments, the AI ​​function information is configured by a third network element.

[0035] In combination with some embodiments of the first aspect, in some embodiments, the first network element is the terminal, the second network element is a core network device, and the third network element is an access network device.

[0036] In the above embodiment, it is clarified that the terminal reports the AI ​​function information configured by the access network device to the core network device.

[0037] In combination with some embodiments of the first aspect, in some embodiments, the first information includes at least one of the following: an AI function for channel state information CSI prediction configured by the third network element; an AI function for channel state information CSI compression configured by the third network element; an AI function for beam management configured by the third network element; a first AI function configured by the third network element, the first AI function being an AI function configured by the third network element, excluding the AI ​​function for CSI prediction, the AI ​​function for CSI compression, and the AI ​​function for beam management; the running time of the AI ​​function; the AI ​​function The start time at which the AI ​​function can be run; the end time of the AI ​​function operation; the computing power that can be used for CSI prediction; the computing power that can be used for CSI compression; the computing power that can be used for beam management; the computing power that can be used for the first AI function configured by the third network element; the computing power that can be used for the AI ​​function configured by the second network element; the number of AI functions configured by the second network element that can be run simultaneously by the first network element; the number of AI models configured by the second network element that can be run simultaneously by the first network element; the AI ​​functions configured by the second network element that can be run simultaneously by the first network element; the AI ​​models configured by the second network element that can be run simultaneously by the first network element.

[0038] In the above embodiment, it is clarified that the first network element is the terminal, the second network element is the core network device, and the third network element is the access network device. When the AI ​​function information is configured by the third network element, the specific content of the first information is included. This enables AI function reporting in this case, and further enables the core network device to coordinate AI functions or AI models based on the reported AI functions, thereby ensuring stable communication.

[0039] In combination with some embodiments of the first aspect, in some embodiments, the first information is carried by at least one of the following: a long-term positioning protocol LPP; a sidelink positioning protocol SLPP.

[0040] In the above embodiment, by reusing the existing protocol to send the first information, information transmission resources can be saved compared to specifying a new communication protocol for sending.

[0041] In combination with some embodiments of the first aspect, in some embodiments, the first network element is the terminal, the second network element is an access network device, and the third network element is a core network device.

[0042] In the above embodiment, it is clarified that the terminal reports the AI ​​function information configured by the core network device to the access network device.

[0043] In combination with some embodiments of the first aspect, in some embodiments, the first information includes at least one of the following: the AI ​​function for positioning configured by the third network element; the second AI function, the second AI function being the AI ​​function other than the AI ​​function for positioning among the AI ​​functions configured by the third network element; the running time of the AI ​​function; the start time of the AI ​​function running; the end time of the AI ​​function running; the computing power that can be used for the AI ​​positioning configured by the third network element; the computing power that can be used for the second AI function configured by the third network element; the computing power that can be used for CSI prediction; the computing power that can be used for CSI compression; the computing power that can be used for beam management; the computing power that can be used for the AI ​​function configured by the second network element; the number of AI functions configured by the second network element that can be run simultaneously by the first network element; the number of AI models configured by the second network element that can be run simultaneously by the first network element; the AI ​​function configured by the second network element that can be run simultaneously by the first network element; the AI ​​model configured by the second network element that can be run simultaneously by the first network element.

[0044] In the above embodiment, the first network element is the terminal, the second network element is the access network device, and the third network element is the core network device. When the AI ​​function information is configured by the third network element, the specific content of the first information is included. This enables AI function reporting in this case, and further enables the access network device to coordinate the AI ​​function or AI model based on the reported AI function, thereby ensuring stable communication.

[0045] In combination with some embodiments of the first aspect, in some embodiments, the first information is carried in radio resource control RRC signaling.

[0046] In the above embodiment, by reusing the existing protocol to send the first information, information transmission resources can be saved compared to specifying a new communication protocol for sending.

[0047] In combination with some embodiments of the first aspect, in some embodiments, the first network element is an access network device, and the second network element is a core network device.

[0048] In the above embodiment, it is clarified that the access network device reports to the core network device the information about the AI ​​function configured by the access network device for the terminal.

[0049] In combination with some embodiments of the first aspect, in some embodiments, the first information includes at least one of the following: an AI function for CSI prediction configured by the access network device for the terminal; an AI function for CSI compression configured by the access network device for the terminal; an AI function for beam management configured by the access network device for the terminal; a third AI function, wherein the third function is an AI function configured for the terminal among the AI ​​functions configured by the access network device, except the AI ​​function for CSI prediction, the AI ​​function for CSI compression, and the AI ​​function for beam management; the computing capability of the terminal that can be used for the AI ​​positioning-based configuration of the core network device; the computing capability of the terminal that can be used for the AI ​​function configured by the core network device; the computing capability of the terminal for the AI ​​function configured by the access network device; the running time of the AI ​​function of the terminal; the start time of the running of the AI ​​function of the terminal; and the end time of the running of the AI ​​function of the terminal.

[0050] In the above embodiment, when the access network device reports information about the AI ​​function configured by the access network device for the terminal to the core network device, the specific content of the first information is included. This enables AI function reporting in this case, and further enables the core network device to coordinate AI functions or AI models based on the reported AI functions, thereby ensuring stable communication.

[0051] In combination with some embodiments of the first aspect, in some embodiments, the first network element is a core network device, and the second network element is an access network device.

[0052] In the above embodiment, it is clarified that the core network device reports to the access network device the information about the AI ​​function configured by the core network device for the terminal.

[0053] In combination with some embodiments of the first aspect, in some embodiments, the first information includes at least one of the following: an AI function for positioning configured by the core network device for the terminal; a fourth AI function, the fourth AI function being an AI function configured by the core network device for the terminal, other than the AI ​​function for positioning; the computing power of the terminal for positioning; the computing power of the terminal for the AI ​​function configured by the core network device; the computing power of the terminal that can be used for the AI ​​function configured by the access network device; the running time of the AI ​​function of the terminal; the start time of the running of the AI ​​function of the terminal; and the end time of the running of the AI ​​function of the terminal.

[0054] In the above embodiment, when the core network device reports information about the AI ​​function configured by the core network device for the terminal to the access network device, the specific content of the first information is included. This enables AI function reporting in this case, and further enables the access network device to coordinate AI functions or AI models based on the reported AI functions, thereby ensuring stable communication.

[0055] In a second aspect, an embodiment of the present disclosure proposes a communication method, including: a second network element receives first information, the first information is sent by a first network element, and the first information includes artificial intelligence (AI) function information running on a terminal.

[0056] In combination with some embodiments of the second aspect, in some embodiments, the AI ​​function information is configured by a third network element.

[0057] In combination with some embodiments of the second aspect, in some embodiments, the first network element is the terminal, the second network element is a core network device, and the third network element is an access network device.

[0058] In combination with some embodiments of the second aspect, in some embodiments, the first information includes at least one of the following: an AI function for channel state information CSI prediction configured by the third network element; an AI function for channel state information CSI compression configured by the third network element; an AI function for beam management configured by the third network element; a first AI function configured by the third network element, the first AI function being an AI function configured by the third network element, excluding the AI ​​function for CSI prediction, the AI ​​function for CSI compression, and the AI ​​function for beam management; the running time of the AI ​​function; the AI ​​function The start time at which the AI ​​function can be run; the end time of the AI ​​function operation; the computing power that can be used for CSI prediction; the computing power that can be used for CSI compression; the computing power that can be used for beam management; the computing power that can be used for the first AI function configured by the third network element; the computing power that can be used for the AI ​​function configured by the second network element; the number of AI functions configured by the second network element that can be run simultaneously by the first network element; the number of AI models configured by the second network element that can be run simultaneously by the first network element; the AI ​​functions configured by the second network element that can be run simultaneously by the first network element; the AI ​​models configured by the second network element that can be run simultaneously by the first network element.

[0059] In combination with some embodiments of the second aspect, in some embodiments, the first information is carried by at least one of the following: a long-term positioning protocol LPP; a sidelink positioning protocol SLPP.

[0060] In combination with some embodiments of the second aspect, in some embodiments, the first network element is the terminal, the second network element is an access network device, and the third network element is a core network device.

[0061] In combination with some embodiments of the second aspect, in some embodiments, the first information includes at least one of the following: the AI ​​function for positioning configured by the third network element; the second AI function, the second AI function being the AI ​​function other than the AI ​​function for positioning among the AI ​​functions configured by the third network element; the running time of the AI ​​function; the start time of the AI ​​function running; the end time of the AI ​​function running; the computing power that can be used for the AI ​​positioning configured by the third network element; the computing power that can be used for the second AI function configured by the third network element; the computing power that can be used for CSI prediction; the computing power that can be used for CSI compression; the computing power that can be used for beam management; the computing power that can be used for the AI ​​function configured by the second network element; the number of AI functions configured by the second network element that can be run simultaneously by the first network element; the number of AI models configured by the second network element that can be run simultaneously by the first network element; the AI ​​function configured by the second network element that can be run simultaneously by the first network element; the AI ​​model configured by the second network element that can be run simultaneously by the first network element.

[0062] In combination with some embodiments of the second aspect, in some embodiments, the first information is carried in radio resource control RRC signaling.

[0063] In combination with some embodiments of the second aspect, in some embodiments, the first network element is an access network device, and the second network element is a core network device.

[0064] In conjunction with some embodiments of the second aspect, in some embodiments, the first information includes at least one of the following:

[0065] the AI ​​function for CSI prediction configured by the access network device for the terminal; the AI ​​function for CSI compression configured by the access network device for the terminal; the AI ​​function for beam management configured by the access network device for the terminal; a third function, wherein the third function is an AI function configured for the terminal, except the AI ​​function for CSI prediction, the AI ​​function for CSI compression and the AI ​​function for beam management among the AI ​​functions configured by the access network device; the computing capacity of the terminal that can be used for the AI ​​function configured by the core network device; the computing capacity of the terminal that can be used for the AI ​​function configured by the core network device; the computing capacity of the terminal for the AI ​​function configured by the access network device; the running time of the AI ​​function of the terminal; the start time of the running of the AI ​​function of the terminal; and the end time of the running of the AI ​​function of the terminal.

[0066] In combination with some embodiments of the second aspect, in some embodiments, the first network element is a core network device, and the second network element is an access network device.

[0067] In combination with some embodiments of the second aspect, in some embodiments, the first information includes at least one of the following: an AI function for positioning configured by the core network device for the terminal; a fourth AI function, the fourth AI function being an AI function configured by the core network device for the terminal, other than the AI ​​function for positioning; the computing power of the terminal for positioning; the computing power of the terminal for the AI ​​function configured by the core network device; the computing power of the terminal that can be used for the AI ​​function configured by the access network device; the running time of the AI ​​function of the terminal; the start time of the running of the AI ​​function of the terminal; and the end time of the running of the AI ​​function of the terminal.

[0068] In a third aspect, an embodiment of the present disclosure proposes a communication method, which includes: a first network element sends first information to a second network element, wherein the first information includes artificial intelligence (AI) function information running on the terminal; and the second network element receives the first information.

[0069] In a fourth aspect, an embodiment of the present disclosure proposes a first network element, comprising: a transceiver module, configured to send first information to a second network element, wherein the first information includes artificial intelligence (AI) function information running on the terminal.

[0070] In combination with some embodiments of the fourth aspect, in some embodiments, the AI ​​function information is configured by a third network element.

[0071] In combination with some embodiments of the fourth aspect, in some embodiments, the first network element is the terminal, the second network element is a core network device, and the third network element is an access network device.

[0072] In combination with some embodiments of the fourth aspect, in some embodiments, the first network element is the terminal, the second network element is a core network device, and the third network element is an access network device.

[0073] In combination with some embodiments of the fourth aspect, in some embodiments, the first information includes at least one of the following: an AI function for channel state information CSI prediction configured by the third network element; an AI function for channel state information CSI compression configured by the third network element; an AI function for beam management configured by the third network element; a first AI function configured by the third network element, the first AI function being an AI function configured by the third network element, excluding the AI ​​function for CSI prediction, the AI ​​function for CSI compression, and the AI ​​function for beam management; the running time of the AI ​​function; the AI ​​function The start time at which the AI ​​function can be run; the end time of the AI ​​function operation; the computing power that can be used for CSI prediction; the computing power that can be used for CSI compression; the computing power that can be used for beam management; the computing power that can be used for the first AI function configured by the third network element; the computing power that can be used for the AI ​​function configured by the second network element; the number of AI functions configured by the second network element that can be run simultaneously by the first network element; the number of AI models configured by the second network element that can be run simultaneously by the first network element; the AI ​​functions configured by the second network element that can be run simultaneously by the first network element; the AI ​​models configured by the second network element that can be run simultaneously by the first network element.

[0074] In combination with some embodiments of the fourth aspect, in some embodiments, the first information is carried by at least one of the following: a long-term positioning protocol LPP; a sidelink positioning protocol SLPP.

[0075] In conjunction with some embodiments of the fourth aspect, in some embodiments, the first network element is the terminal, the second network element is an access network device, and the third network element is a core network device. The first network element is the terminal, the second network element is a core network device, and the third network element is an access network device.

[0076] In combination with some embodiments of the fourth aspect, in some embodiments, the first information includes at least one of the following: the AI ​​function for positioning configured by the third network element; the second AI function, the second AI function being the AI ​​function other than the AI ​​function for positioning among the AI ​​functions configured by the third network element; the running time of the AI ​​function; the start time of the AI ​​function running; the end time of the AI ​​function running; the computing power for AI positioning configured by the third network element; the computing power for the second AI function configured by the third network element; the computing power that can be used for CSI prediction; the computing power that can be used for CSI compression; the computing power that can be used for beam management; the computing power that can be used for the AI ​​function configured by the second network element; the number of AI functions configured by the second network element that can be run simultaneously by the first network element; the number of AI models configured by the second network element that can be run simultaneously by the first network element; the AI ​​function configured by the second network element that can be run simultaneously by the first network element; the AI ​​model configured by the second network element that can be run simultaneously by the first network element.

[0077] In conjunction with some embodiments of the fourth aspect, in some embodiments, the first information is carried in a radio resource control RRC signaling

[0078] In combination with some embodiments of the fourth aspect, in some embodiments, the first network element is an access network device, and the second network element is a core network device.

[0079] In combination with some embodiments of the fourth aspect, in some embodiments, the first information includes at least one of the following: an AI function for CSI prediction configured by the access network device for the terminal; an AI function for CSI compression configured by the access network device for the terminal; an AI function for beam management configured by the access network device for the terminal; a third AI function, wherein the third function is an AI function configured for the terminal among the AI ​​functions configured by the access network device, except the AI ​​function for CSI prediction, the AI ​​function for CSI compression, and the AI ​​function for beam management; the computing capability of the terminal that can be used for the AI ​​positioning-based configuration of the core network device; the computing capability of the terminal that can be used for the AI ​​function configured by the core network device; the computing capability of the terminal that is used for the AI ​​function configured by the access network device; the running time of the AI ​​function of the terminal; the start time of the running of the AI ​​function of the terminal; and the end time of the running of the AI ​​function of the terminal.

[0080] In combination with some embodiments of the fourth aspect, in some embodiments, the first network element is a core network device, and the second network element is an access network device.

[0081] In combination with some embodiments of the fourth aspect, in some embodiments, the first information includes at least one of the following: an AI function for positioning configured by the core network device for the terminal; a fourth AI function, the fourth AI function being an AI function configured by the core network device for the terminal, other than the AI ​​function for positioning; the computing power of the terminal for positioning; the computing power of the terminal for the AI ​​function configured by the core network device; the computing power of the terminal that can be used for the AI ​​function configured by the access network device; the running time of the AI ​​function of the terminal; the start time of the running of the AI ​​function of the terminal; and the end time of the running of the AI ​​function of the terminal.

[0082] In a fifth aspect, an embodiment of the present disclosure proposes a second network element, comprising: a transceiver module for receiving first information, wherein the first information is sent by the first network element, and the first information includes artificial intelligence AI function information running on the terminal.

[0083] In combination with some embodiments of the fifth aspect, in some embodiments, the AI ​​function information is configured by a third network element.

[0084] In combination with some embodiments of the fifth aspect, in some embodiments, the first network element is the terminal, the second network element is a core network device, and the third network element is an access network device.

[0085] In combination with some embodiments of the fifth aspect, in some embodiments, the first information includes at least one of the following: an AI function for channel state information CSI prediction configured by the third network element; an AI function for channel state information CSI compression configured by the third network element; an AI function for beam management configured by the third network element; a first AI function configured by the third network element, the first AI function being an AI function configured by the third network element, excluding the AI ​​function for CSI prediction, the AI ​​function for CSI compression, and the AI ​​function for beam management; the running time of the AI ​​function; the AI ​​function The start time at which the AI ​​function can be run; the end time of the AI ​​function operation; the computing power that can be used for CSI prediction; the computing power that can be used for CSI compression; the computing power that can be used for beam management; the computing power that can be used for the first AI function configured by the third network element; the computing power that can be used for the AI ​​function configured by the second network element; the number of AI functions configured by the second network element that can be run simultaneously by the first network element; the number of AI models configured by the second network element that can be run simultaneously by the first network element; the AI ​​functions configured by the second network element that can be run simultaneously by the first network element; the AI ​​models configured by the second network element that can be run simultaneously by the first network element.

[0086] In combination with some embodiments of the fifth aspect, in some embodiments, the first information is carried by at least one of the following: a long-term positioning protocol LPP; a sidelink positioning protocol SLPP.

[0087] In combination with some embodiments of the fifth aspect, in some embodiments, the first network element is an access network device, and the second network element is a core network device.

[0088] In combination with some embodiments of the fifth aspect, in some embodiments, the first information includes at least one of the following: the AI ​​function for positioning configured by the third network element; the second AI function, the second AI function being the AI ​​function other than the AI ​​function for positioning among the AI ​​functions configured by the third network element; the running time of the AI ​​function; the start time of the AI ​​function running; the end time of the AI ​​function running; the computing power that can be used for the AI ​​positioning configured by the third network element; the computing power that can be used for the second AI function configured by the third network element; the computing power that can be used for CSI prediction; the computing power that can be used for CSI compression; the computing power that can be used for beam management; the computing power that can be used for the AI ​​function configured by the second network element; the number of AI functions configured by the second network element that can be run simultaneously by the first network element; the number of AI models configured by the second network element that can be run simultaneously by the first network element; the AI ​​function configured by the second network element that can be run simultaneously by the first network element; the AI ​​model configured by the second network element that can be run simultaneously by the first network element.

[0089] In combination with some embodiments of the fifth aspect, in some embodiments, the first information is carried in radio resource control RRC signaling.

[0090] In combination with some embodiments of the fifth aspect, in some embodiments, the first network element is a core network device, and the second network element is an access network device.

[0091] In combination with some embodiments of the fifth aspect, in some embodiments, the first information includes at least one of the following: an AI function for positioning configured by the core network device for the terminal; a fourth AI function, the fourth AI function being an AI function configured by the core network device for the terminal, other than the AI ​​function for positioning; the computing power of the terminal for positioning; the computing power of the terminal for the AI ​​function configured by the core network device; the computing power of the terminal that can be used for the AI ​​function configured by the access network device; the running time of the AI ​​function of the terminal; the start time of the running of the AI ​​function of the terminal; and the end time of the running of the AI ​​function of the terminal.

[0092] In a sixth aspect, an embodiment of the present disclosure proposes a first network element, comprising: one or more processors; wherein the processor is used to execute the communication method of the first aspect.

[0093] In a seventh aspect, the present disclosure implements a second network element, comprising: one or more processors; wherein the processor is used to execute the communication method of the second aspect.

[0094] In an eighth aspect, the present disclosure implements a communication system, comprising a first network element and a second network element, wherein the first network element is configured to implement the communication method of the first aspect, and the second network element is configured to implement the communication method of the second aspect.

[0095] In a ninth aspect, the present disclosure implements a storage medium, which stores instructions. When the instructions are executed on a communication device, the communication device executes the communication method of any one of the first and second aspects.

[0096] The present disclosure provides a communication method, a first network element, a second network element, and a communication system. In some embodiments, the terms "communication method" and "data processing method" and "information processing method" are interchangeable; the terms "data processing device" and "information processing device" and "communication device" are interchangeable; and the terms "information processing system" and "communication system" are interchangeable.

[0097] The embodiments of the present disclosure are not exhaustive and are merely illustrative of some embodiments, and are not intended to be a specific limitation on the scope of protection of the present disclosure. In the absence of contradiction, each step in a certain embodiment can be implemented as an independent embodiment, and the steps can be arbitrarily combined. For example, a solution after removing some steps in a certain embodiment can also be implemented as an independent embodiment, and the order of the steps in a certain embodiment can be arbitrarily exchanged. In addition, the optional implementation methods in a certain embodiment can be arbitrarily combined; in addition, the embodiments can be arbitrarily combined. For example, some or all steps of different embodiments can be arbitrarily combined, and a certain embodiment can be arbitrarily combined with the optional implementation methods of other embodiments.

[0098] In each embodiment of the present disclosure, unless otherwise specified or provided for by logic, the terms and / or descriptions between the embodiments are consistent and can be referenced by each other. The technical features in different embodiments can be combined to form a new embodiment based on their inherent logical relationships.

[0099] The terms used in the embodiments of the present disclosure are only for the purpose of describing specific embodiments and are not intended to limit the present disclosure.

[0100] In the embodiments of the present disclosure, unless otherwise specified, elements expressed in the singular, such as "a", "an", "the", "above", "said", "the", "the", etc., may mean "one and only one", or "one or more", "at least one", etc. For example, when using articles such as "a", "an", "the" in English in translation, the noun following the article may be understood as a singular expression or a plural expression.

[0101] In the embodiments of the present disclosure, “plurality” refers to two or more.

[0102] In some embodiments, the terms "at least one," "one or more," "a plurality of," "multiple," etc. may be used interchangeably.

[0103] In some embodiments, descriptions such as "at least one of A and B," "A and / or B," "A in one case, B in another case," or "in response to one case A, in response to another case B" may include the following technical solutions depending on the situation: in some embodiments, A (A is executed independently of B); in some embodiments, B (B is executed independently of A); in some embodiments, execution is selected from A and B (A and B are selectively executed); and in some embodiments, A and B (both A and B are executed). The above is also applicable when there are more branches such as A, B, and C.

[0104] In some embodiments, "A or B" and other descriptions may include the following technical solutions depending on the situation: in some embodiments, A (A is executed independently of B); in some embodiments, B (B is executed independently of A); in some embodiments, execution is selected from A and B (A and B are selectively executed). The above is also applicable when there are more branches such as A, B, C, etc.

[0105] The prefixes such as "first" and "second" in the embodiments of the present disclosure are only used to distinguish different description objects and do not constitute any restriction on the position, order, priority, quantity or content of the description objects. For the statement of the description object, please refer to the description in the context of the claims or embodiments, and no unnecessary restriction should be constituted due to the use of prefixes. For example, if the description object is a "field", the ordinal number before the "field" in the "first field" and the "second field" does not limit the position or order between the "fields". "First" and "second" do not limit whether the "fields" they modify are in the same message, nor do they limit the order of the "first field" and the "second field". For another example, if the description object is a "level", the ordinal number before the "level" in the "first level" and the "second level" does not limit the priority between the "levels". For another example, the number of description objects is not limited by the ordinal number and can be one or more. Taking "first device" as an example, the number of "devices" can be one or more. In addition, the objects modified by different prefixes can be the same or different. For example, if the description object is "device", then the "first device" and the "second device" can be the same device or different devices, and their types can be the same or different; for another example, if the description object is "information", then the "first information" and the "second information" can be the same information or different information, and their contents can be the same or different.

[0106] In some embodiments, “including A,” “comprising A,” “used to indicate A,” and “carrying A” can be interpreted as directly carrying A or indirectly indicating A.

[0107] In some embodiments, terms such as "time / frequency" and "time / frequency domain" refer to the time domain and / or the frequency domain.

[0108] In some embodiments, terms such as "in response to...", "in response to determining...", "in the case of...", "at the time of...", "when...", "if...", "if...", etc. can be used interchangeably.

[0109] In some embodiments, terms such as "greater than", "greater than or equal to", "not less than", "more than", "more than or equal to", "not less than", "higher than", "higher than or equal to", "not less than", and "above" can be replaced with each other, and terms such as "less than", "less than or equal to", "not greater than", "less than", "less than or equal to", "not more than", "lower than", "lower than or equal to", "not higher than", and "below" can be replaced with each other.

[0110] In some embodiments, devices, etc. can be interpreted as physical or virtual, and their names are not limited to the names recorded in the embodiments. Terms such as "device", "equipment", "device", "circuit", "network element", "node", "function", "unit", "section", "system", "network", "chip", "chip system", "entity", and "subject" can be used interchangeably.

[0111] In some embodiments, "network" can be interpreted as devices included in the network (eg, access network equipment, core network equipment, etc.).

[0112] In some embodiments, the terms "access network device (AN device)", "radio access network device (RAN device)", "base station (BS)", "radio base station" "fixed station", "node", "access point", "transmission point (TP)", "reception point (RP)", "transmission / reception point (TRP)" "panel", "antenna panel", "antenna array", "cell", "macro cell", "small cell", "femto cell", "pico cell", "sector", "cell group", "serving cell", "carrier", "component carrier", "bandwidth part (BWP)" and the like may be used interchangeably.

[0113] In some embodiments, the terms "terminal", "terminal device", "user equipment (UE)", "user terminal", "mobile station (MS)", "mobile terminal (MT)", subscriber station, mobile unit, subscriber unit, wireless unit, remote unit, mobile device, wireless device, wireless communication device, remote device, mobile subscriber station, access terminal, mobile terminal, wireless terminal, remote terminal, handset, user agent, mobile client, client, etc. can be used interchangeably.

[0114] In some embodiments, the access network device, the core network device, or the network device can be replaced by a terminal. For example, the various embodiments of the present disclosure can also be applied to a structure in which the communication between the access network device, the core network device, or the network device and the terminal is replaced by communication between multiple terminals (for example, device-to-device (D2D), vehicle-to-everything (V2X), etc.). In this case, it is also possible to set the structure in which the terminal has all or part of the functions of the access network device. In addition, terms such as "uplink" and "downlink" can also be replaced by terms corresponding to communication between terminals (for example, "side"). For example, uplink channels, downlink channels, etc. can be replaced by side channels, and uplinks, downlinks, etc. can be replaced by side links.

[0115] In some embodiments, the terminal may be replaced by an access network device, a core network device, or a network device. In this case, the access network device, the core network device, or the network device may have a structure that has all or part of the functions of the terminal.

[0116] In some embodiments, obtaining data, information, etc. may comply with the laws and regulations of the country where the data is obtained.

[0117] In some embodiments, data, information, etc. may be obtained with the user's consent.

[0118] In addition, each element, each row, or each column in the table of the embodiment of the present disclosure can be implemented as an independent embodiment, and the combination of any elements, any rows, and any columns can also be implemented as an independent embodiment.

[0119] FIG1 is a schematic diagram showing the architecture of a communication system according to an embodiment of the present disclosure.

[0120] As shown in FIG1 , a communication system 100 includes a first network element (node) 101 and a second network element (node) 102 .

[0121] In some embodiments, the first network element 101 may be, for example, any one of a terminal, a core network device, or an access network device.

[0122] In some embodiments, the second network element 102 may be, for example, any one of a terminal, a core network device, or an access network device.

[0123] In some embodiments, the communication system 100 may further include a third network element 103, which is used to configure AI function information.

[0124] In some embodiments, the third network element 103 in the communication system 100 may be omitted.

[0125] In some embodiments, the terminal includes, for example, a mobile phone, a wearable device, an Internet of Things device, a car with communication function, a smart car, a tablet computer, a computer with wireless transceiver function, a virtual reality (VR) terminal device, an augmented reality (AR) terminal device, a wireless terminal device in industrial control, a wireless terminal device in self-driving, a wireless terminal device in remote medical surgery, a wireless terminal device in a smart grid, a wireless terminal device in transportation safety, a wireless terminal device in a smart city, and at least one of a wireless terminal device in a smart home, but is not limited thereto.

[0126] In some embodiments, the access network device is, for example, a node or device that accesses a terminal to a wireless network. The access network device may include an evolved NodeB (eNB), a next generation evolved NodeB (ng-eNB), a next generation NodeB (gNB), a node B (NB), a home node B (HNB), a home evolved nodeB (HeNB), a wireless backhaul device, a radio network controller (RNC), a base station controller (BSC), a base transceiver station (BTS), a base band unit (BBU), a mobile switching center, a base station in a 6G communication system, an open base station (Open RAN), a cloud base station (Cloud RAN), a base station in other communication systems, and at least one of an access node in a Wi-Fi system, but is not limited thereto.

[0127] In some embodiments, the technical solution of the present disclosure can be applied to the Open RAN architecture. In this case, the interfaces between or within the access network devices involved in the embodiments of the present disclosure can be transformed into internal interfaces of the Open RAN, and the processes and information interactions between these internal interfaces can be implemented through software or programs.

[0128] In some embodiments, the access network device can be composed of a centralized unit (CU) and a distributed unit (DU), where the CU can also be called a control unit. The CU-DU structure can be used to split the protocol layer of the access network device, with the functions of some protocol layers centrally controlled by the CU, and the functions of the remaining part or all of the protocol layers distributed in the DU, which is centrally controlled by the CU, but is not limited to this.

[0129] In some embodiments, the core network device may be a single device including a first network element, a second network element, etc., or may be a plurality of devices or a group of devices, each including all or part of the first network element, the second network element, etc. The network element may be virtual or physical. The core network may include, for example, at least one of an evolved packet core (EPC), a 5G core network (5GCN), and a next generation core (NGC).

[0130] It can be understood that the communication system described in the embodiment of the present disclosure is for the purpose of more clearly illustrating the technical solution of the embodiment of the present disclosure, and does not constitute a limitation on the technical solution proposed in the embodiment of the present disclosure. Ordinary technicians in this field can know that with the evolution of the system architecture and the emergence of new business scenarios, the technical solution proposed in the embodiment of the present disclosure is also applicable to similar technical problems.

[0131] The following embodiments of the present disclosure may be applied to the communication system 100 shown in FIG1 , or a portion thereof, but are not limited thereto. The entities shown in FIG1 are illustrative only. The communication system may include all or part of the entities shown in FIG1 , or may include other entities outside of FIG1 . The number and form of the entities are arbitrary, and the entities may be physical or virtual. The connection relationships between the entities are illustrative only. The entities may be connected or disconnected, and the connection may be in any manner, including direct or indirect, wired or wireless.

[0132] The embodiments of the present disclosure can be applied to Long Term Evolution (LTE), LTE-Advanced (LTE-A), LTE-Beyond (LTE-B), SUPER 3G, IMT-Advanced, 4th generation mobile communication system (4G), 5th generation mobile communication system (5G), 5G new radio (NR), future radio access (FRA), new radio access technology (RAT), new radio (NR), new radio access (NX), future generation radio access (FX), Global System for Mobile communications (GSM (registered trademark)), CDMA2000, Ultra Mobile Broadband (UMB), IEEE 802.11 (Wi-Fi (registered trademark)), IEEE 802.16 (WiMAX (registered trademark)), IEEE 802.20, Ultra-WideBand (UWB), Bluetooth (registered trademark), Public Land Mobile Network (PLMN) networks, Device-to-Device (D2D) systems, Machine-to-Machine (M2M) systems, Internet of Things (IoT) systems, Vehicle-to-Everything (V2X), systems utilizing other communication methods, and next-generation systems based on and extending these methods. Furthermore, multiple systems may be combined (for example, a combination of LTE or LTE-A with 5G).

[0133] In some embodiments, artificial intelligence (AI) is gradually being applied in the communications field. For example, in 5G New Radio (NR) communication scenarios, and even in 6G communication scenarios. For example, in 5G or 6G communication scenarios, positioning based on AI or machine learning (ML) can be implemented. In other words, AI functions are applied to terminal positioning, and AI technology is used to achieve direct or indirect positioning of the terminal.

[0134] It is understandable that for these AI or ML-based functions, some AI models or AI functions are managed by access network equipment. For example, the access network equipment determines to use AI or ML-based beam management, and the access network equipment determines to estimate and predict the channel state information (CSI) based on AI or ML.

[0135] Some AI- or ML-based functions are managed by core network devices. For example, AI-based positioning functions can be managed by the Location Management Function (LMF).

[0136] Based on this, during communication, a terminal may use different AI models from different nodes in the same time period. For example, a terminal may simultaneously use the AI-based positioning function configured on the core network equipment and the AI-based CSI prediction function configured on the access network equipment. In this case, the AI ​​models or AI functions used by the terminal need to be coordinated.

[0137] FIG2A is an interactive diagram of a communication method according to an embodiment of the present disclosure. As shown in FIG2A , the embodiment of the present disclosure relates to a communication method, and the method includes:

[0138] Step S2101: The first network element 101 sends first information to the second network element 102.

[0139] In some embodiments, the second network element 102 obtains the first information.

[0140] In some embodiments, the second network element 102 receives first information from the first network element 101 .

[0141] In some embodiments, terms such as "send", "transmit", "report", "download", "transmit", "bidirectional transmission", "send and / or receive" can be used interchangeably.

[0142] In some embodiments, "obtain", "get", "get", "receive", "transmit", "bidirectional transmission", "send and / or receive" can be interchangeable, and can be interpreted as receiving from other entities, obtaining from protocols, obtaining from higher layers, obtaining by self-processing, autonomous implementation, etc.

[0143] In some embodiments, the names of information, etc. are not limited to the names described in the embodiments, and terms such as "information", "message", "signal", "signaling", "report", "configuration", "indication", "instruction", "command", "channel", "parameter", "domain", "field", "symbol", "symbol", "codeword", "codebook", "codeword", "codepoint", "bit", "data", "program", and "chip" can be used interchangeably.

[0144] In some embodiments, the first network element 101 may be any one of the following: a terminal, an access network device, or a core network device.

[0145] In some embodiments, the second network element 102 may be any one of the following: a terminal, an access network device, or a core network device.

[0146] In some embodiments, the first information includes information about artificial intelligence (AI) running on the terminal.

[0147] In some embodiments, "AI model", "artificial intelligence model", "machine learning (ML) model", "ML model", AI function, and ML function can be replaced with each other.

[0148] In some embodiments, the AI ​​functionality includes an AI model.

[0149] In some embodiments, the AI ​​function information is configured by a third network element.

[0150] Optionally, the third network element may be an access network device or a core network device.

[0151] Optionally, the AI ​​function information may not be configured by the third network element. In the case where the AI ​​function information is not configured by the third network element, the third network element is omitted.

[0152] In some embodiments, the access network device includes, for example, a new radio node (NR Node B, gNB).

[0153] In some embodiments, the core network device includes, for example, a module in the core network device for implementing a positioning management function, such as a positioning management function (LMF) module, or an access and mobility management function (AMF) module.

[0154] It is understandable that, in the case where the first network element and the second network element are different types of execution entities, the content corresponding to the first information is different.

[0155] In some embodiments, the first network element sends first information to the second network element, where the first information includes information about the AI ​​function running on the terminal, generally including the following situations:

[0156] -A) AI function information is configured by a third network element, where the first network element is a terminal, the second network element is a core network device, and the third network element is an access network device.

[0157] -B) AI function information is configured by a third network element, where the first network element is a terminal, the second network element is an access network device, and the third network element is a core network device.

[0158] -C) The first network element is an access network device, and the second network element is a core network device.

[0159] -D) The first network element is a core network device, and the second network element is an access network device.

[0160] It is understandable that, for case -C) and case -D), the AI ​​function information is not configured by the third network element. Therefore, for case -C) and case -D), the third network element is omitted.

[0161] Step S2102: The second network element 102 communicates based on the first information.

[0162] In some embodiments, the second network element 102 performs corresponding communication processing based on the first information of any situation sent by the first network element 101.

[0163] In some embodiments, the second network element 102 determines the AI ​​function that the second network element configures or manages for the terminal based on the first information sent by the first network element 101.

[0164] The communication method involved in the embodiments of the present disclosure may include at least one of steps S2101 and S2102. For example, step S2101 may be implemented as an independent embodiment, step S2102 may be implemented as an independent embodiment, and step S2101 + step S2102 may be implemented as independent embodiments, but the present invention is not limited thereto.

[0165] In some embodiments, steps S2101 and S2102 may be executed in an interchanged order or simultaneously.

[0166] In some embodiments, step S2102 is optional, and one or more of these steps may be omitted or replaced in different embodiments.

[0167] In some embodiments, reference may be made to other optional implementations described before or after the description corresponding to FIG. 2A .

[0168] In some embodiments, FIG2B is an interactive schematic diagram of a communication method corresponding to case -A) according to an embodiment of the present disclosure. As shown in FIG2B , a communication method in case -A) is disclosed, where the first network element is a terminal, and the second network element is a core network device. The method includes:

[0169] In step S2201, the terminal sends first information to the core network device.

[0170] The optional implementation of step S2201 can refer to the optional implementation of step S2101 in Figure 2A and other related parts in the embodiment involved in Figure 2A, which will not be repeated here.

[0171] For -A) situation, the first information includes at least one of the following: AI function configured by the third network element, AI function processing time, AI function computing power, the ability of AI functions and / or AI models that can run simultaneously, the number of AI functions that can run simultaneously and / or the number of AI models that can run simultaneously.

[0172] In some embodiments, the AI ​​function configured by the third network element includes at least one of the following: an AI function configured by the third network element for channel state information (CSI) CSI prediction, an AI function configured by the third network element for CSI compression, an AI function configured by the third network element for beam management, and a first AI function configured by the third network element.

[0173] Optionally, the first AI function is an AI function configured in the third network element, except for the AI ​​function for CSI prediction, or the AI ​​function for CSI compression and the AI ​​function for beam management.

[0174] It can be understood that when the third network element is an access network device, the AI ​​function configured by the third network element can also be understood as including at least one of the following: an AI function configured by the access network device for CSI prediction, an AI function configured by the access network device for CSI compression, an AI function configured by the access network device for beam management, and a first AI function configured by the access network device.

[0175] It can be understood that by reporting the above information, the core network device can configure appropriate AI functions for the terminal after learning the AI ​​functions configured for the terminal by the access network device.

[0176] In some embodiments, the AI ​​function processing time includes at least one of the following: the running time of the AI ​​function, the start time of the AI ​​function running, or the end time of the AI ​​function running.

[0177] It can be understood that by reporting the above information, the core network device can determine the processing time of the AI ​​function configured in the access network currently running the terminal, and then the core network device can configure the appropriate AI function for the terminal according to the processing time of the AI ​​function. For example, considering the limited terminal capabilities, the core network device can configure the AI ​​function for the terminal after the terminal finishes running the AI ​​function configured by the access network device, such as AI-based positioning.

[0178] In some embodiments, the AI ​​function computing capability includes at least one of the following: computing capability that can be used for CSI management, computing capability that can be used for beam management, computing capability for the first AI function configured for a third network element, or computing capability for the AI ​​function configured for a second network element.

[0179] Optionally, the computing capability that can be used for CSI management includes: computing capability that can be used for CSI prediction, and / or computing capability that can be used for CSI compression.

[0180] Optionally, the AI ​​function configured by the second network element includes, for example: an AI positioning function.

[0181] Optionally, the computing capability of the AI ​​function that can be used for the second network element configuration includes, for example, computing capability based on AI positioning that can be used for the second network element configuration.

[0182] Optionally, in some embodiments, the AI ​​function computing capability includes at least one of the following: computing capability that can be used for CSI prediction, computing capability that can be used for CSI compression, computing capability that can be used for beam management, computing capability that can be used for the first AI function configured for access network equipment, or computing capability that can be used for AI positioning-based configuration for core network equipment.

[0183] It can be understood that by reporting the above information, the core network device can determine the computing capability of the AI ​​function configured by the access network device running on the terminal, and then the core network device can configure the appropriate AI function for the terminal according to the computing capability of the AI ​​function. For example, based on the computing capability of the terminal, the core network device can configure an AI function that matches its computing capability for the terminal, or a combination of AI functions. For example, the computing capability of the terminal can only support the computing capability for CSI prediction, then the core network device matches it with the AI ​​function for CSI prediction based on its computing capability. For another example, if the computing capability of the terminal can support the computing capability for CSI prediction and the computing capability for CSI compression, then the core network device matches it with the AI ​​function for CSI prediction and / or the AI ​​function for CSI compression based on its computing capability.

[0184] In some embodiments, the capabilities of AI functions and / or AI models that can run simultaneously include at least one of the following: an AI function configured by a second network element that can be run simultaneously by a first network element, or an AI model configured by a second network element that can be run simultaneously by the first network element.

[0185] It is understood that the AI ​​functions or AI models mentioned above are all models that meet the terminal's applicable conditions. The ability to run simultaneously can be understood as the ability to run which AI functions and AI models simultaneously based on the terminal's own capabilities, or which AI functions and AI models can run simultaneously.

[0186] Optionally, since the first network element is a terminal and the second network element is a core network device, the aforementioned capability of concurrently running AI functions and / or AI models can be understood to include at least one of the following: AI functions configured for the core network that can be concurrently run by the terminal, or AI models configured for the core network that can be concurrently run by the terminal.

[0187] It can be understood that by reporting the above information, the core network device can determine the access network device running on the terminal and configure the ability of the AI ​​function and / or AI model to run simultaneously, and then the core network device can configure the appropriate AI function and / or AI model for the terminal according to the capability. For example, based on the capability of the terminal, the core network device can configure the terminal with an AI function or AI model that matches its ability to run simultaneously. For example, the terminal supports the simultaneous running of an AI model for CSI prediction and an AI model for CSI compression. Based on the capability of the terminal, the core network device can configure the terminal with an AI model for CSI prediction and / or an AI model for CSI compression.

[0188] For another example, the terminal supports the simultaneous operation of the AI ​​function for beam management and the AI ​​function for positioning. Based on this capability of the terminal, the core network device can configure the AI ​​function for beam management and / or the AI ​​function for positioning for the terminal. For another example, the terminal supports the simultaneous operation of the AI ​​function for beam management and the AI ​​function for positioning. When the core network device configures the AI ​​function for beam management and / or the AI ​​function for positioning for the terminal, the terminal can support the simultaneous operation of the above functions. When the core network device configures the following functions for the terminal at the same time: the AI ​​function for beam management, the AI ​​function for positioning, and the AI ​​function for CSI prediction, the terminal can simultaneously operate the AI ​​function for beam management and the AI ​​function for positioning, but cannot simultaneously operate the AI ​​function for beam management, the AI ​​function for positioning, and the AI ​​function for CSI prediction.

[0189] In some embodiments, the number of AI functions that can be run simultaneously and / or the number of AI models that can be run simultaneously include at least one of the following: the number of AI functions configured by the second network element that can be run simultaneously by the first network element, or the number of AI models configured by the second network element that can be run simultaneously by the first network element.

[0190] Optionally, since the first network element is a terminal and the second network element is a core network device, the aforementioned capability of simultaneously running AI functions and / or AI models can be understood to include at least one of the following: the number of AI functions configured for the core network that the terminal can simultaneously run, or the number of AI models configured for the core network that the terminal can simultaneously run.

[0191] It is understood that the AI ​​functions or AI models mentioned above are all models that meet the terminal's applicable conditions. The number of AI functions that can be run simultaneously can be understood as the maximum number of AI functions that can be run simultaneously, the maximum number of AI models that can be run simultaneously, and the maximum number of AI functions and AI models that can be run simultaneously based on the terminal's own capabilities.

[0192] It can be understood that by reporting the above information, the core network device can determine the number of AI functions running at the same time as the configuration of the access network device running by the terminal, and / or the number of AI models that can be run simultaneously. The core network device can then configure the terminal with an appropriate number of AI functions and / or AI models based on this capability. For example, based on the capability of the terminal, the core network device can configure the terminal with AI functions or AI models that match the number of AI functions running simultaneously. For example, the terminal can simultaneously run N AI functions configured by the LMF (N is an integer greater than or equal to 1), and the LMF configures M AI functions for the terminal based on the capability of the terminal (M is an integer greater than or equal to 1 and less than or equal to N).

[0193] For another example, the terminal is capable of simultaneously running N AI models configured by LMF. Based on this capability of the terminal, LMF configures M AI models for the terminal.

[0194] Based on this, in some embodiments, the first information can be understood to include at least one of the following:

[0195] The AI ​​function for CSI prediction configured by the third network element, the AI ​​function for CSI compression configured by the third network element, the AI ​​function for beam management configured by the third network element, the first AI function configured by the third network element, the running time of the AI ​​function, the start time of the AI ​​function running, the end time of the AI ​​function running, the computing power for CSI prediction, the computing power for CSI compression, the computing power for beam management, the computing power for the first AI function configured by the third network element, the computing power that can be used for the AI ​​function configured by the second network element, the number of AI functions configured by the second network element that can be run simultaneously by the first network element, the number of AI models configured by the second network element that can be run simultaneously by the first network element, the AI ​​function configured by the second network element that can be run simultaneously by the first network element, or the AI ​​model configured by the second network element that can be run simultaneously by the first network element.

[0196] In some embodiments, the first information is carried by at least one of the following: sending the first information to the LMF based on the Long Term Evolution Positioning Protocol (LPP), and / or based on the Sidelink Positioning Protocol (SLPP).

[0197] In some embodiments, terms such as "uplink", "uplink", "physical uplink" can be interchangeable with each other, and terms such as "downlink", "downlink", "physical downlink" can be interchangeable with each other, and terms such as "side", "sidelink", "side communication", "sidelink communication", "direct connection", "direct link", "direct communication", "direct link communication" can be interchangeable with each other.

[0198] In some embodiments, for the -B) situation, the first information includes at least one of the following: a second AI function, AI function processing time, AI function computing power, the ability of AI functions and / or AI models that can be run simultaneously, or the number of AI functions that can be run simultaneously and / or the number of AI models that can be run simultaneously.

[0199] In some embodiments, the second AI function is an AI function configured in the third network element, excluding the AI ​​function for positioning.

[0200] In step S2202, the core network device communicates based on the first information.

[0201] In some embodiments, the core network device communicates based on the AI ​​function configured by the access network device included in the first information.

[0202] Exemplarily, after learning about the AI ​​function configured by the access network device for the terminal, the core network device configures a matching AI function for the terminal, thereby enabling communication of the terminal.

[0203] It can be understood that for the core network device to configure the AI ​​function that matches the terminal configuration based on the AI ​​function configured by the access network device, the relevant exemplary instructions can be found in step S2101 and the relevant description in step S2201, and will not be repeated here.

[0204] In some embodiments, the core network device communicates based on the AI ​​function processing time included in the first information.

[0205] Exemplarily, the core network device configures a matching AI function for the terminal based on the processing time of the AI ​​function configured by the access network device for the terminal, thereby enabling communication of the terminal.

[0206] It is understandable that for the core network device to configure the terminal with a matching AI function based on the processing time of the AI ​​function, relevant exemplary instructions can be found in step S2101 and the relevant description in step S2201, which will not be repeated here.

[0207] In some embodiments, the core network device communicates based on the AI ​​function computing capability included in the first information.

[0208] Exemplarily, the core network device matches the corresponding AI function for the terminal according to the computing power of the AI ​​function configured by the access network device running on the terminal, thereby realizing communication of the terminal.

[0209] It can be understood that for the core network device to configure the terminal with matching AI functions based on the AI ​​function computing capability, relevant exemplary instructions can be found in step S2101 and the relevant description in step S2201, and will not be repeated here.

[0210] In some embodiments, the core network device communicates based on the capabilities of the AI ​​functions and / or AI models running simultaneously included in the first information.

[0211] Exemplarily, the core network device configures matching AI functions and / or AI models for the terminal based on the ability of the access network device running the terminal to run AI functions and / or AI models at the same time, thereby achieving communication.

[0212] It can be understood that the core network device configures matching AI functions for the terminal based on the AI ​​functions running simultaneously and / or the capabilities of the AI ​​model. For relevant exemplary explanations, please refer to the relevant descriptions in step S2101 and step S2201, and they will not be repeated here.

[0213] In some embodiments, the core network device communicates based on the number of AI functions that can be run simultaneously and / or the number of AI models that can be run simultaneously included in the first information.

[0214] Exemplarily, the core network device configures matching AI functions and / or AI models for the terminal based on the number of AI functions that can run simultaneously and / or the number of AI models that can run simultaneously configured by the access network device on which the terminal runs.

[0215] It can be understood that for the core network device to configure matching AI functions and / or AI models for the terminal based on the number of AI functions that the terminal can run simultaneously and / or the number of AI models that can run simultaneously, the relevant exemplary instructions can be found in step S2101 and the relevant description in step S2201, and they will not be repeated here.

[0216] The optional implementation of step S2202 can refer to the optional implementation of step S2102 in Figure 2A and other related parts in the embodiment involved in Figure 2A, which will not be repeated here.

[0217] The communication method involved in the embodiments of the present disclosure may include at least one of steps S2201 and S2202. For example, step S2201 may be implemented as an independent embodiment, step S2202 may be implemented as an independent embodiment, and step S2201 + step S2202 may be implemented as independent embodiments, but the present invention is not limited thereto.

[0218] In some embodiments, steps S2201 and S2202 may be performed in an interchangeable order or simultaneously.

[0219] In some embodiments, step S2202 is optional, and one or more of these steps may be omitted or replaced in different embodiments.

[0220] In some embodiments, FIG2C is an interactive schematic diagram of a communication method corresponding to case -B) according to an embodiment of the present disclosure. As shown in FIG2C , a communication method in case -B) is disclosed, where the first network element is a terminal, and the second network element is an access network device. The method includes:

[0221] In step S2301, the terminal sends first information to the access network device.

[0222] The optional implementation of step S2301 can refer to the optional implementation of step S2101 in Figure 2A and other related parts in the embodiment involved in Figure 2A, which will not be repeated here.

[0223] It can be understood that in the -B) case, the second network element is an access network device, the third network element is a core network device, and the second function can be understood as the AI ​​function configured in the core network device, except for the AI ​​function used for positioning.

[0224] In some embodiments, the AI ​​function processing time includes at least one of the following: the running time of the AI ​​function, the start time of the AI ​​function running, or the end time of the AI ​​function running.

[0225] It can be understood that by reporting the above information, the access network device configures a matching AI function for the terminal after learning the AI ​​function configured for the terminal by the core network device.

[0226] In some embodiments, the AI ​​function computing capability includes at least one of the following: computing capability for AI positioning configured by a third network element, computing capability for a second AI function configured by a third network element, computing capability that can be used for CSI management, computing capability that can be used for beam management, or computing capability for an AI function configured by a second network element.

[0227] In some embodiments, the computing power used for CSI management includes, for example, computing power that can be used for CSI prediction and / or computing power that can be used for CSI compression.

[0228] It can be understood that in the -B) case, the second network element is an access network device, the third network element is a core network device, and the AI ​​function computing capability includes at least one of the following: computing capability for AI positioning configured for core network devices, computing capability for the second AI function configured for core network devices, computing capability that can be used for CSI management, computing capability that can be used for beam management, or computing capability for AI functions configured for access network devices.

[0229] It can be understood that by reporting the above information, the access network device configures a matching AI function for the terminal based on the AI ​​function computing capability when it learns the AI ​​function computing capability configured by the core network device for the terminal. For example, based on the computing capability of the terminal, the access network device can configure an AI function that matches its computing capability for the terminal, or a combination of AI functions. For example, if the computing capability of the terminal can only support the computing capability for CSI prediction, the access network device will match it with the AI ​​function for CSI prediction based on its computing capability. For another example, if the computing capability of the terminal can support the computing capability for CSI prediction and the computing capability for CSI compression, the access network device will match it with the AI ​​function for CSI prediction and / or the AI ​​function for CSI compression based on its computing capability.

[0230] In some embodiments, the capabilities of AI functions and / or AI models that can be run simultaneously include at least one of the following: an AI function configured by the second network element that can be run simultaneously by the first network element, or an AI model configured by the second network element that can be run simultaneously by the first network element.

[0231] It is understood that the AI ​​functions or AI models mentioned above are all models that meet the terminal's applicable conditions. The ability to run simultaneously can be understood as the ability to run which AI functions and AI models simultaneously based on the terminal's own capabilities, or which AI functions and AI models can run simultaneously.

[0232] Optionally, since the first network element is a terminal and the second network element is an access network device, the aforementioned capability of concurrently running AI functions and / or AI models can be understood to include at least one of the following: AI functions configured for the access network that can be concurrently run by the terminal, or AI models configured for the access network that can be concurrently run by the terminal.

[0233] Optionally, the AI ​​function configured by the second network element includes, for example: an AI positioning function.

[0234] For example, the terminal can simultaneously run the AI-based positioning capability and the AI-based beam management capability configured by the access network device, but cannot simultaneously run the AI-based CSI prediction capability. In other words, it can be explained that the terminal can simultaneously run the AI-based beam management function and the AI-based CSI prediction function.

[0235] Optionally, since the first network element is a terminal and the second network element is an access network device, the aforementioned capability of simultaneously running AI functions and / or AI models can be understood to include at least one of the following: the number of AI functions configured for the core network that the terminal can simultaneously run, or the number of AI models configured for the core network that the terminal can simultaneously run.

[0236] It can be understood that by reporting the above information, the access network device can determine the ability of the core network device running the terminal to configure the AI ​​function and / or AI model to run simultaneously, and then the access network device can configure the appropriate AI function and / or AI model for the terminal based on this capability. For example, based on the capability of the terminal, the access network device can configure the terminal with an AI function or AI model that matches its ability to run simultaneously. For example, the terminal supports the simultaneous running of an AI model for CSI prediction and an AI model for CSI compression. Based on this capability of the terminal, the access network device can configure the terminal with an AI model for CSI prediction and / or an AI model for CSI compression.

[0237] For another example, the terminal supports the simultaneous operation of the AI ​​function for beam management and the AI ​​function for positioning. Based on this capability of the terminal, the access network device can configure the AI ​​function for beam management and / or the AI ​​function for positioning for the terminal. For another example, the terminal supports the simultaneous operation of the AI ​​function for beam management and the AI ​​function for positioning. When the access network device configures the AI ​​function for beam management and / or the AI ​​function for positioning for the terminal, the terminal can support the simultaneous operation of the above functions. When the access network device configures the following functions for the terminal at the same time: the AI ​​function for beam management, the AI ​​function for positioning, and the AI ​​function for CSI prediction, the terminal can simultaneously operate the AI ​​function for beam management and the AI ​​function for positioning, but cannot simultaneously operate the AI ​​function for beam management, the AI ​​function for positioning, and the AI ​​function for CSI prediction.

[0238] In some embodiments, the number of AI functions that can be run simultaneously and / or the number of AI models that can be run simultaneously include at least one of the following: the number of AI functions configured by the second network element that can be run simultaneously by the first network element, or the number of AI models configured by the second network element that can be run simultaneously by the first network element.

[0239] It is understood that the AI ​​functions or AI models mentioned above are all models that meet the terminal's applicable conditions. The number of AI functions that can be run simultaneously can be understood as the maximum number of AI functions that can be run simultaneously, the maximum number of AI models that can be run simultaneously, and the maximum number of AI functions and AI models that can be run simultaneously based on the terminal's own capabilities.

[0240] It can be understood that by reporting the above information, the access network device can determine the number of AI functions running at the same time as the core network device configuration running by the terminal, and / or the number of AI models that can be run simultaneously. The access network device can then configure the appropriate number of AI functions and / or AI models for the terminal based on this capability. For example, based on the capability of the terminal, the access network device can configure the terminal with AI functions or AI models that match the number of AI functions running simultaneously. For example, the terminal can simultaneously run N AI functions configured by LMF (N is an integer greater than or equal to 1), and the access network device configures M AI functions for the terminal based on the capability of the terminal (M is an integer greater than or equal to 1 and less than or equal to N).

[0241] For another example, the terminal can simultaneously run N AI models configured by LMF. Based on this capability of the terminal, the access network device configures M AI models for the terminal.

[0242] Based on this, in some embodiments, the first information can be understood to include at least one of the following:

[0243] The second AI function, the running time of the AI ​​function, the start time of the AI ​​function running, the end time of the AI ​​function running, the computing power for the AI ​​positioning configured by the third network element, the computing power for the second AI function configured by the third network element, the computing power that can be used for CSI management, the computing power that can be used for beam management, the computing power for the second AI function configured by the second network element, the number of AI functions configured by the second network element that can be run simultaneously by the first network element, the number of AI models configured by the second network element that can be run simultaneously by the first network element, the AI ​​function of the second network element configured by the first network element that can be run simultaneously, and the AI ​​model of the second network element configured by the first network element that can be run simultaneously.

[0244] In some embodiments, the first information is carried in Radio Resource Control (RRC) signaling.

[0245] In step S2302, the access network device communicates based on the first information.

[0246] In some embodiments, the access network device communicates based on the AI ​​function configured by the core network device included in the first information.

[0247] Exemplarily, after learning about the AI ​​function configured for the terminal by the core network device, the access network device configures a matching AI function for the terminal, thereby enabling communication of the terminal.

[0248] It can be understood that for the access network device to configure the AI ​​function that matches the terminal configuration based on the AI ​​function configured by the core network device, the relevant exemplary instructions can be found in step S2101 and the relevant description in step S2301, and will not be repeated here.

[0249] In some embodiments, the access network device communicates based on the AI ​​function computing capability included in the first information.

[0250] Exemplarily, the access network device matches the corresponding AI function for the terminal according to the computing power of the AI ​​function configured by the core network device on which the terminal runs, thereby enabling communication of the terminal.

[0251] It is understandable that for the access network device to configure the terminal with matching AI functions based on the AI ​​function computing capability, relevant exemplary instructions can be found in step S2101 and the relevant description in step S2301, and will not be repeated here.

[0252] In some embodiments, the access network device communicates based on the capabilities of the AI ​​functions and / or AI models running simultaneously included in the first information.

[0253] Exemplarily, the access network device configures matching AI functions and / or AI models for the terminal based on the ability of the core network device running the terminal to run AI functions and / or AI models at the same time, thereby achieving communication.

[0254] It can be understood that the access network device configures matching AI functions for the terminal based on the AI ​​functions running simultaneously and / or the capabilities of the AI ​​model. For relevant exemplary instructions, please refer to step S2101 and the relevant description in step S2301, which will not be repeated here.

[0255] In some embodiments, the access network device communicates based on the number of AI functions that can be run simultaneously and / or the number of AI models that can be run simultaneously included in the first information.

[0256] Exemplarily, the access network device configures matching AI functions and / or AI models for the terminal based on the number of AI functions that can run simultaneously and / or the number of AI models that can run simultaneously configured by the core network device on which the terminal runs.

[0257] It can be understood that for the access network device to configure matching AI functions and / or AI models for the terminal based on the number of AI functions that the terminal can run simultaneously and / or the number of AI models that can run simultaneously, the relevant exemplary instructions can be found in step S2101 and the relevant description in step S2301, and they will not be repeated here.

[0258] The optional implementation of step S2302 can refer to the optional implementation of step S2102 in Figure 2A and other related parts in the embodiment involved in Figure 2A, which will not be repeated here.

[0259] The communication method involved in the embodiments of the present disclosure may include at least one of steps S2301 and S2302. For example, step S2101 may be implemented as an independent embodiment, step S2302 may be implemented as an independent embodiment, and step S2301 + step S2302 may be implemented as independent embodiments, but the present invention is not limited thereto.

[0260] In some embodiments, steps S2301 and S2302 may be executed in an interchanged order or simultaneously.

[0261] In some embodiments, step S2302 is optional, and one or more of these steps may be omitted or replaced in different embodiments.

[0262] In some embodiments, FIG2D is an interactive schematic diagram of a communication method corresponding to case -C) according to an embodiment of the present disclosure. As shown in FIG2D , a communication method in case -C) is disclosed, where the first network element is a terminal, and the second network element is an access network device. The method includes:

[0263] In step S2401, the access network device sends first information to the core network device.

[0264] The optional implementation of step S2401 can refer to the optional implementation of step S2101 in Figure 2A and other related parts in the embodiment involved in Figure 2A, which will not be repeated here.

[0265] In some embodiments, for the -C) situation, the first information includes at least one of the following: the AI ​​function configured by the access network device for the terminal, the third AI function, the AI ​​function computing capacity that the terminal can use for the core network device configuration, the AI ​​function computing capacity that the terminal can use for the access network device configuration, or the AI ​​function processing time of the terminal.

[0266] In some embodiments, the third AI function is an AI function configured in the third network element, excluding the AI ​​function for positioning.

[0267] It can be understood that in the -C) case, the first network element is an access network device, the second network element is a core network device, and the third AI function can be understood as the AI ​​function configured in the core network device, except for the AI ​​function used for positioning.

[0268] In some embodiments, the third function is an AI function configured for the terminal among the AI ​​functions configured in the access network device, except for the AI ​​function for CSI prediction, the AI ​​function for CSI compression, and the AI ​​function for beam management.

[0269] In some embodiments, the AI ​​function configured by the access network device for the terminal includes at least one of the following: an AI function configured by the access network device for CSI prediction for the terminal, an AI function configured by the access network device for CSI compression for the terminal, or an AI function configured by the access network device for beam management for the terminal.

[0270] It can be understood that by reporting the above information, the core network device can configure matching AI functions for the terminal after learning the AI ​​functions configured for the terminal by the access network device.

[0271] In some embodiments, the AI ​​function processing time includes at least one of the following: the running time of the AI ​​function, the start time of the AI ​​function running, or the end time of the AI ​​function running.

[0272] It can be understood that by reporting the above information, the core network device can determine the processing time of the AI ​​function configured in the access network currently running the terminal, and then the core network device can configure the appropriate AI function for the terminal according to the processing time of the AI ​​function. For example, considering the limited terminal capabilities, the core network device can configure the AI ​​function for the terminal after the terminal finishes running the AI ​​function configured by the access network device, such as AI-based positioning.

[0273] It can be understood that by reporting the AI ​​function computing capability of the terminal configured by the access network device for the terminal, which can be used for the core network device configuration, the core network device can configure a matching AI function for the terminal based on this capability.

[0274] It can be understood that by reporting the computing power of the AI ​​function that the terminal configured by the access network device can use for the AI ​​function configured by the access network device, the core network device can adjust the AI ​​function configured by the access network device for the terminal based on this capability.

[0275] Based on this, in some embodiments, the first information can be understood to include at least one of the following:

[0276] The AI ​​function for CSI prediction configured by the access network device for the terminal, the AI ​​function for CSI compression configured by the access network device for the terminal, the AI ​​function for beam management configured by the access network device for the terminal, the third function, the computing capability of the terminal for AI positioning-based configuration of the core network device, the computing capability of the terminal for the AI ​​function configured by the core network device, the computing capability of the terminal for the AI ​​function configured by the access network device, the running time of the AI ​​function of the terminal, the start time of the running of the AI ​​function of the terminal, and the end time of the running of the AI ​​function of the terminal.

[0277] In step S2402, the core network device communicates based on the first information.

[0278] In some embodiments, the core network device communicates based on the AI ​​function configured by the access network device included in the first information.

[0279] Exemplarily, after learning about the AI ​​function configured by the access network device for the terminal, the core network device configures a matching AI function for the terminal, thereby enabling communication of the terminal.

[0280] It can be understood that for the core network device to configure the AI ​​function that matches the terminal configuration based on the AI ​​function configured by the access network device, relevant exemplary instructions can be found in step S2101 and the relevant description in step S2401, and will not be repeated here.

[0281] In some embodiments, the core network device communicates based on the AI ​​function processing time included in the first information.

[0282] Exemplarily, the core network device configures a matching AI function for the terminal based on the processing time of the AI ​​function configured by the access network device for the terminal, thereby enabling communication of the terminal.

[0283] It is understandable that for the core network device to configure the terminal with a matching AI function based on the processing time of the AI ​​function, relevant exemplary instructions can be found in step S2101 and the relevant description in step S2401, and will not be repeated here.

[0284] In some embodiments, the core network device communicates based on the AI ​​function computing capability included in the first information.

[0285] Exemplarily, the core network device matches the corresponding AI function for the terminal according to the computing power of the AI ​​function configured by the access network device running on the terminal, thereby realizing communication of the terminal.

[0286] It is understandable that for the core network device to configure the terminal with a matching AI function based on the AI ​​function computing capability, the relevant exemplary description can be found in step S2101 and the relevant description in step S2401, which will not be repeated here. The optional implementation of step S2402 can be found in the optional implementation of step S2102 in Figure 2A, and other related parts of the embodiment involved in Figure 2A, which will not be repeated here.

[0287] The communication method involved in the embodiments of the present disclosure may include at least one of steps S2401 and S2402. For example, step S2401 may be implemented as an independent embodiment, step S2402 may be implemented as an independent embodiment, and step S2401 + step S2402 may be implemented as independent embodiments, but the present invention is not limited thereto.

[0288] In some embodiments, steps S2401 and S2402 may be executed in an interchanged order or simultaneously.

[0289] In some embodiments, step S2402 is optional, and one or more of these steps may be omitted or replaced in different embodiments.

[0290] In some embodiments, FIG2E is an interactive schematic diagram of a communication method corresponding to case -D) according to an embodiment of the present disclosure. As shown in FIG2E , a communication method in case -D) is disclosed, where the first network element is a core network device, and the second network element is an access network device. The method includes:

[0291] In step S2501, the core network device sends first information to the access network device.

[0292] The optional implementation of step S2501 can refer to the optional implementation of step S2101 in Figure 2A and other related parts in the embodiment involved in Figure 2A, which will not be repeated here.

[0293] In some embodiments, for case -D), the first information includes at least one of the following:

[0294] The AI ​​function for positioning configured by the core network device for the terminal, the fourth AI function, the computing power of the terminal for positioning, the computing power of the terminal for the AI ​​function configured by the core network device, the computing power of the terminal that can be used for the AI ​​function configured by the access network device, and the AI ​​function processing time.

[0295] In some embodiments, the fourth AI function is an AI function configured by the core network device for the terminal, except for the AI ​​function used for positioning.

[0296] It can be understood that by reporting the above information, the access network device can configure the matching AI function for the terminal after learning the AI ​​function configured for the terminal by the core network device.

[0297] In some embodiments, the AI ​​function processing time includes at least one of the following: the running time of the AI ​​function, the start time of the AI ​​function running, or the end time of the AI ​​function running.

[0298] It can be understood that by reporting the above information, the access network device can determine the processing time of the AI ​​function configured in the core network currently running the terminal, and then the access network device can configure the appropriate AI function for the terminal according to the processing time of the AI ​​function. For example, considering the limited terminal capabilities, the access network device can configure the AI ​​function for the terminal after the terminal ends the operation of the AI ​​function configured by the core network device, such as AI-based positioning.

[0299] In some embodiments, terms such as "certain", "preset", "preset", "setting", "indicated", "a certain", "any", and "first" can be interchangeable. "Specific A", "preset A", "preset A", "setting A", "indicated A", "a certain A", "any A", and "first A" can be interpreted as A pre-specified in a protocol, etc., or as A obtained through setting, configuration, or indication, etc., or as specific A, a certain A, any A, or first A, etc., but not limited to this.

[0300] In some embodiments, the terms "radio", "wireless", "radio access network (RAN)", "access network (AN)", "RAN-based" and the like may be used interchangeably.

[0301] In some embodiments, terms such as "synchronization signal (SS)", "synchronization signal block (SSB)", "reference signal (RS)", "pilot", and "pilot signal" can be used interchangeably.

[0302] In some embodiments, terms such as "moment", "time point", "time", and "time position" can be replaced with each other, and terms such as "duration", "period", "time window", "window", and "time" can be replaced with each other.

[0303] In step S2502, the access network device communicates based on the first information.

[0304] In some embodiments, the access network device communicates based on the AI ​​function configured by the core network device included in the first information.

[0305] Exemplarily, after learning about the AI ​​function configured for the terminal by the core network device, the access network device configures a matching AI function for the terminal, thereby enabling communication of the terminal.

[0306] It can be understood that for the access network device to configure the AI ​​function that matches the terminal configuration based on the AI ​​function configured by the core network device, the relevant exemplary instructions can be found in step S2101 and the relevant description in step S2501, and will not be repeated here.

[0307] In some embodiments, the access network device communicates based on the AI ​​function computing capability included in the first information.

[0308] Exemplarily, the access network device matches the corresponding AI function for the terminal according to the computing power of the AI ​​function configured by the core network device on which the terminal runs, thereby enabling communication of the terminal.

[0309] It is understandable that for the access network device to configure the terminal with matching AI functions based on the AI ​​function computing capability, relevant exemplary instructions can be found in step S2101 and the relevant description in step S2501, and will not be repeated here.

[0310] In some embodiments, the access network device communicates based on the AI ​​function processing time included in the first information.

[0311] Exemplarily, the access network device configures a matching AI function for the terminal based on the processing time of the AI ​​function configured by the core network device for the terminal, thereby enabling communication of the terminal.

[0312] It is understandable that for the access network device to configure the terminal with a matching AI function based on the processing time of the AI ​​function, relevant exemplary instructions can be found in step S2101 and the relevant description in step S2501, which will not be repeated here.

[0313] The optional implementation of step S2502 can refer to the optional implementation of step S2102 in Figure 2A and other related parts in the embodiment involved in Figure 2A, which will not be repeated here.

[0314] The communication method involved in the embodiments of the present disclosure may include at least one of steps S2501 and S2502. For example, step S2501 may be implemented as an independent embodiment, step S2502 may be implemented as an independent embodiment, and step S2501 + step S2502 may be implemented as independent embodiments, but the present invention is not limited thereto.

[0315] In some embodiments, steps S2501 and S2502 may be executed in an interchanged order or simultaneously.

[0316] In some embodiments, step S2502 is optional, and one or more of these steps may be omitted or replaced in different embodiments.

[0317] FIG3 is a flow chart of a communication method according to an embodiment of the present disclosure. As shown in FIG3 , the embodiment of the present disclosure relates to a communication method, which includes:

[0318] Step S3101, sending the first information.

[0319] For the optional implementation of step S3101, please refer to the optional implementation of step S2101 in Figure 2A, the optional implementation of step S2201 in Figure 2B, the optional implementation of step S2301 in Figure 2C, the optional implementation of step S2401 in Figure 2D, the optional implementation of step S2501 in Figure 2E and other related parts in the embodiments involved in Figures 2A, 2B, 2C, 2D and 2E, which will not be repeated here.

[0320] In some embodiments, the first information includes artificial intelligence (AI) function information running on the terminal.

[0321] In some embodiments, the AI ​​function information is configured by a third network element.

[0322] In some embodiments, the first network element is a terminal, the second network element is a core network device, and the third network element is an access network device.

[0323] In some embodiments, the AI ​​function information is configured by a third network element, and when the first network element is a terminal, the second network element is a core network device, and the third network element is an access network device, the first information includes at least one of the following: an AI function for CSI prediction configured by the third network element; an AI function for CSI compression configured by the third network element; an AI function for beam management configured by the third network element; a first AI function configured by the third network element, where the first AI function is an AI function configured by the third network element, excluding the AI ​​function for CSI prediction, the AI ​​function for CSI compression, and the AI ​​function for beam management; operation of the AI ​​function The running time; the starting time of the AI ​​function operation; the ending time of the AI ​​function operation; the computing power that can be used for CSI prediction; the computing power that can be used for CSI compression; the computing power that can be used for beam management; the computing power that can be used for the first AI function configured in the third network element; the computing power that can be used for the AI ​​function configured in the second network element; the number of AI functions configured in the second network element that can be run simultaneously by the first network element; the number of AI models configured in the second network element that can be run simultaneously by the first network element; the AI ​​functions configured in the second network element that can be run simultaneously by the first network element; the AI ​​models configured in the second network element that can be run simultaneously by the first network element.

[0324] In some embodiments, the AI ​​function information is configured by a third network element, the first network element is a terminal, the second network element is a core network device, and the third network element is an access network device, and the first information is carried on at least one of the following: LPP, or SLPP.

[0325] In some embodiments, the first network element is the terminal, the second network element is an access network device, and the third network element is a core network device.

[0326] In some embodiments, the AI ​​function information is configured by a third network element, and when the first network element is a terminal, the second network element is an access network device, and the third network element is a core network device, the first information includes at least one of the following: an AI function for positioning configured by the third network element; a second AI function, where the second AI function is an AI function other than the AI ​​function for positioning among the AI ​​functions configured by the third network element; the running time of the AI ​​function; the start time of the AI ​​function running; the end time of the AI ​​function running; the computing power that can be used for AI positioning configured by the third network element; the computing power that can be used for the second AI function configured by the third network element; the computing power that can be used for CSI prediction; the computing power that can be used for CSI compression; the computing power that can be used for beam management; the computing power that can be used for the AI ​​function configured by the second network element; the number of AI functions configured by the second network element that can be run simultaneously by the first network element; the number of AI models configured by the second network element that can be run simultaneously by the first network element; the AI ​​function configured by the second network element that can be run simultaneously by the first network element; the AI ​​model configured by the second network element that can be run simultaneously by the first network element.

[0327] In some embodiments, the first information is carried in radio resource control RRC signaling.

[0328] In some embodiments, the first network element is an access network device, and the second network element is a core network device.

[0329] In some embodiments, when the first network element is an access network device and the second network element is a core network device, the first information includes at least one of the following: an AI function for CSI prediction configured by the access network device for the terminal; an AI function for CSI compression configured by the access network device for the terminal; an AI function for beam management configured by the access network device for the terminal; a third AI function, where the third function is an AI function configured for the terminal among the AI ​​functions configured by the access network device, except for the AI ​​function for CSI prediction, the AI ​​function for CSI compression, and the AI ​​function for beam management; the computing capacity of the terminal that can be used for AI positioning-based configuration of the core network device; the computing capacity of the terminal that can be used for the AI ​​function configured by the core network device; the computing capacity of the terminal for the AI ​​function configured by the access network device; the running time of the terminal's AI function; the start time of the terminal's AI function running; and the end time of the terminal's AI function running.

[0330] In some embodiments, the first network element is a core network device, and the second network element is an access network device.

[0331] In some embodiments, when the first network element is a core network device and the second network element is an access network device, the first information includes at least one of the following: an AI function for positioning configured by the core network device for the terminal; a fourth AI function, where the fourth AI function is an AI function other than the AI ​​function for positioning among the AI ​​functions configured by the core network device for the terminal; the computing power of the terminal for positioning; the computing power of the terminal for the AI ​​function configured by the core network device; the computing power of the terminal that can be used for the AI ​​function configured by the access network device; the running time of the terminal's AI function; the start time of the terminal's AI function running; and the end time of the terminal's AI function running.

[0332] Step S3102: communicate based on the first information.

[0333] For the optional implementation of step S3102, please refer to the optional implementation of step S2102 in Figure 2A, the optional implementation of step S2202 in Figure 2B, the optional implementation of step S2302 in Figure 2C, the optional implementation of step S2402 in Figure 2D, the optional implementation of step S2502 in Figure 2E and other related parts in the embodiments involved in Figures 2A, 2B, 2C, 2D and 2E, which will not be repeated here.

[0334] The communication method involved in the embodiments of the present disclosure may include at least one of steps S3101 and S3102. For example, step S3101 may be implemented as an independent embodiment, step S3102 may be implemented as an independent embodiment, and step S3101 + step S3102 may be implemented as independent embodiments, but the present disclosure is not limited thereto.

[0335] In some embodiments, steps S3101 and S3102 may be executed in an interchanged order or simultaneously.

[0336] In some embodiments, step S3102 is optional, and one or more of these steps may be omitted or replaced in different embodiments.

[0337] FIG4A is a flow chart of a communication method according to an embodiment of the present disclosure. As shown in FIG4A , the embodiment of the present disclosure relates to a communication method, and the method includes:

[0338] Step S4101, obtain first information.

[0339] In some embodiments, the second network element 102 receives the first information sent by the first network element 101, but is not limited thereto and may also receive the first information sent by other entities.

[0340] In some embodiments, the second network element 102 obtains first information specified by the protocol.

[0341] In some embodiments, the second network element 102 obtains the first information from an upper layer(s).

[0342] In some embodiments, the second network element 102 performs processing to obtain the first information.

[0343] In some embodiments, step S3101 is omitted, and the second network element 102 autonomously implements the function indicated by the first information, or the above function is default or by default.

[0344] For the optional implementation of step S4101, please refer to the optional implementation of step S2101 in Figure 2A, the optional implementation of step S2201 in Figure 2B, the optional implementation of step S2301 in Figure 2C, the optional implementation of step S2401 in Figure 2D, the optional implementation of step S2501 in Figure 2E, the optional implementation of step S3101 in Figure 3 and other related parts in the embodiments involved in Figures 2A, 2B, 2C, 2D, 2E and 3, which will not be repeated here.

[0345] Step S4102: communicate based on the first information.

[0346] The optional implementation method of step S4102 can refer to the optional implementation method of step S2102 in Figure 2A, the optional implementation method of step S2201 in Figure 2B, the optional implementation method of step S2301 in Figure 2C, the optional implementation method of step S2401 in Figure 2D, the optional implementation method of step S2501 in Figure 2E and other related parts in the embodiments involved in Figures 2A, 2B, 2C, 2D and 2E, which will not be repeated here.

[0347] The communication method involved in the embodiments of the present disclosure may include at least one of steps S4101 and S4102. For example, step S4101 may be implemented as an independent embodiment, step S4102 may be implemented as an independent embodiment, and step S4101 + step S4102 may be implemented as independent embodiments, but the present invention is not limited thereto.

[0348] In some embodiments, steps S4101 and S4102 may be executed in an interchanged order or simultaneously.

[0349] In some embodiments, step S4102 is optional, and one or more of these steps may be omitted or replaced in different embodiments.

[0350] FIG4B is a flow chart of a communication method according to an embodiment of the present disclosure. As shown in FIG4B , the embodiment of the present disclosure relates to a communication method, and the method includes:

[0351] Step S4201, receiving first information.

[0352] For the optional implementation of step S4201, please refer to the optional implementation of step S2101 in Figure 2A, the optional implementation of step S2201 in Figure 2B, the optional implementation of step S2301 in Figure 2C, the optional implementation of step S2401 in Figure 2D, the optional implementation of step S2501 in Figure 2E, the optional implementation of step S3101 in Figure 3 and other related parts in the embodiments involved in Figures 2A, 2B, 2C, 2D, 2E and 3, which will not be repeated here.

[0353] In some embodiments, the first information is sent by the first network element, and the first information includes AI function information running on the terminal.

[0354] In some embodiments, the AI ​​function information is configured by a third network element.

[0355] In some embodiments, the first network element is a terminal, the second network element is a core network device, and the third network element is an access network device.

[0356] In some embodiments, the AI ​​function information is configured by a third network element, and when the first network element is a terminal, the second network element is a core network device, and the third network element is an access network device, the first information includes at least one of the following: an AI function for channel state information CSI prediction configured by the third network element; an AI function for channel state information CSI compression configured by the third network element; an AI function for beam management configured by the third network element; a first AI function configured by the third network element, where the first AI function is an AI function configured by the third network element, except for the AI ​​function for CSI prediction, the AI ​​function for CSI compression, and the AI ​​function for beam management. ; The running time of the AI ​​function; The start time of the AI ​​function running; The end time of the AI ​​function running; The computing power that can be used for CSI prediction; The computing power that can be used for CSI compression; The computing power that can be used for beam management; The computing power that can be used for the first AI function configured in the third network element; The computing power that can be used for the AI ​​function configured in the second network element; The number of AI functions configured in the second network element that can be run simultaneously by the first network element; The number of AI models configured in the second network element that can be run simultaneously by the first network element; The AI ​​functions configured in the second network element that can be run simultaneously by the first network element; The AI ​​models configured in the second network element that can be run simultaneously by the first network element.

[0357] In some embodiments, the AI ​​function information is configured by a third network element, the first network element is a terminal, the second network element is a core network device, and the third network element is an access network device, and the first information is carried on at least one of the following: LPP, or SLPP.

[0358] In some embodiments, the first network element is a terminal, the second network element is an access network device, and the third network element is a core network device.

[0359] In some embodiments, the AI ​​function information is configured by a third network element, and when the first network element is a terminal, the second network element is an access network device, and the third network element is a core network device, the first information includes at least one of the following: an AI function for positioning configured by the third network element; a second AI function, where the second AI function is an AI function other than the AI ​​function for positioning among the AI ​​functions configured by the third network element; the running time of the AI ​​function; the start time of the AI ​​function running; the end time of the AI ​​function running; the computing power that can be used for AI positioning configured by the third network element; the computing power that can be used for the second AI function configured by the third network element; the computing power that can be used for CSI prediction; the computing power that can be used for CSI compression; the computing power that can be used for beam management; the computing power that can be used for the AI ​​function configured by the second network element; the number of AI functions configured by the second network element that can be run simultaneously by the first network element; the number of AI models configured by the second network element that can be run simultaneously by the first network element; the AI ​​function configured by the second network element that can be run simultaneously by the first network element; the AI ​​model configured by the second network element that can be run simultaneously by the first network element.

[0360] In some embodiments, the AI ​​function information is configured by a third network element, the first network element is a terminal, the second network element is an access network device, and the third network element is a core network device, and the first information is carried in the radio resource control RRC signaling.

[0361] In some embodiments, the first network element is an access network device, and the second network element is a core network device.

[0362] In some embodiments, the AI ​​function information is configured by a third network element, and when the first network element is an access network device and the second network element is a core network device, the first information includes at least one of the following: the AI ​​function for CSI prediction configured by the access network device for the terminal; the AI ​​function for CSI compression configured by the access network device for the terminal; the AI ​​function for beam management configured by the access network device for the terminal; the third function, which is the AI ​​function configured for the terminal among the AI ​​functions configured by the access network device, except the AI ​​function for CSI prediction, the AI ​​function for CSI compression and the AI ​​function for beam management; the computing capacity of the terminal that can be used for the AI ​​positioning-based configuration of the core network device; the computing capacity of the terminal that can be used for the AI ​​function configured by the core network device; the computing capacity of the terminal for the AI ​​function configured by the access network device; the running time of the terminal's AI function; the start time of the terminal's AI function operation; and the end time of the terminal's AI function operation.

[0363] In some embodiments, the first network element is a core network device, and the second network element is an access network device.

[0364] In some embodiments, AI function information is configured by a third network element, the first network element is a core network device, the second network element is an access network device, the core network device configures the terminal with an AI function for positioning; a fourth AI function, the fourth AI function is the AI ​​function configured by the core network device for the terminal, except for the AI ​​function for positioning; the computing power of the terminal for positioning; the computing power of the terminal for the AI ​​function configured by the core network device; the computing power of the terminal that can be used for the AI ​​function configured by the access network device; the running time of the terminal's AI function; the start time of the terminal's AI function running; the end time of the terminal's AI function running.

[0365] Figure 5 is an interactive diagram of a communication method according to an embodiment of the present disclosure. As shown in Figure 5, the embodiment of the present disclosure relates to a communication method, which includes:

[0366] Step S5101: The first network element 101 sends first information to the second network element 102.

[0367] The optional implementation of step S5101 can be found in step S2101 of Figure 2A, step S3101 of Figure 3, step S4101 of Figure 4A, step S4201 of Figure 4B, and other related parts in the embodiments involved in Figures 2A, 3, 4A and 4B, which will not be repeated here.

[0368] In some embodiments, the first information includes artificial intelligence (AI) function information running on the terminal.

[0369] In some embodiments, the above method may include the method described in the above embodiments of the communication system side, terminal side, network device side, etc., which will not be repeated here.

[0370] In some embodiments, a communication method is proposed to enable a terminal to coordinate between different AI functions and / or AI models from access network devices and core network devices.

[0371] In some embodiments, coordinating the AI ​​model or AI function used by the terminal includes at least one of the following situations:

[0372] -A) The terminal provides information to the core network device indicating the AI ​​functions managed by other access network devices running on the terminal.

[0373] -B) The terminal provides information to the access network device indicating the AI ​​functions managed by other core network devices running on the terminal.

[0374] -C) The access network device provides information to the core network device indicating the AI ​​functions managed by other access network devices running on the terminal.

[0375] -D) The core network device provides information to the access network device indicating the AI ​​function (such as positioning) running on the terminal.

[0376] It should be noted that the terminal mentioned in the embodiments of the present disclosure can be written as "UE", the access network device mentioned can be written as "gNB", and the core network device mentioned can be "LMF" or "CN".

[0377] In some embodiments, for the -A) situation, the information includes at least one of the following: information on the operation of the AI ​​function, time information on the operation of the AI ​​function, floating-point number information, the number of AI functions for positioning that can be run simultaneously, the number of AI models for positioning that can be run simultaneously, applicable AI models, or applicable AI functions.

[0378] Optionally, the information on the operation of the AI ​​function includes at least one of the following: a function for CSI prediction, a function for beam management, or other AI functions for access network device management.

[0379] It can be understood that other AI functions managed by access network devices can be understood as AI functions managed by access network devices other than the above-mentioned functions.

[0380] Optionally, the time information of the AI ​​function running includes at least one of the following: the running time of the AI ​​function, the start time of the AI ​​function, or the stop time of the AI ​​function.

[0381] Optionally, the floating-point information includes at least one of the following: floating-point information for CSI prediction, floating-point information for beam management, floating-point information for positioning, or floating-point information of other AI functions managed by access network devices.

[0382] Optionally, the number of AI functions for positioning that can be run simultaneously can be understood as the maximum number of AI functions that can be applied by the terminal based on the capabilities of the terminal and managed via the core network device.

[0383] Optionally, the number of AI models for positioning that can be run simultaneously can be understood as the maximum number of AI models that can be applied by the terminal based on the capabilities of the terminal and managed via the core network device.

[0384] In some embodiments, information may be sent to the core network device via LPP or SLPP, for example, providing capabilities via LPP or requesting assistance data based on LPP.

[0385] In some embodiments, for the -B) situation, the information includes at least one of the following: information on the execution of the AI ​​function, time information on the execution of the AI ​​function, floating-point number information, the number of AI functions for positioning that can be executed simultaneously, the number of AI models for positioning that can be executed simultaneously, applicable AI models, or applicable AI functions.

[0386] Optionally, the information on the operation of the AI ​​function includes at least one of the following: a function for CSI prediction, a function for beam management, or other AI functions for core network device management.

[0387] It can be understood that other AI functions managed by core network devices can be understood as AI functions managed by core network devices other than the above-mentioned functions.

[0388] Optionally, the time information of the AI ​​function running includes at least one of the following: the running time of the AI ​​function, the start time of the AI ​​function, or the stop time of the AI ​​function.

[0389] Optionally, the floating-point information includes at least one of the following: floating-point information for CSI prediction, floating-point information for beam management, floating-point information for positioning, or floating-point information of other AI functions managed by access network devices.

[0390] Optionally, the number of AI functions for positioning that can be run simultaneously can be understood as the maximum number of AI functions that can be applied by the terminal based on the capabilities of the terminal and managed via the access network device.

[0391] Optionally, the number of AI models for positioning that can be run simultaneously can be understood as the maximum number of AI models that can be applied by the terminal based on the capabilities of the terminal and managed via the access network device.

[0392] Optionally, the information may be sent via RRC signaling, for example, via UAI.

[0393] In some embodiments, for -C), the information includes at least one of the following:

[0394] Function used for CSI prediction, function used for beam management, other AI functions managed by access network equipment, floating-point numbers used for positioning, floating-point numbers used for AI functions managed by access network equipment, running time of AI functions, start time of AI functions, or stop time of AI functions.

[0395] In some embodiments, for -D), the information includes at least one of the following:

[0396] Functions used for CSI prediction, functions used for beam management, other AI functions managed by core network devices, floating-point numbers used for positioning, floating-point numbers used for AI functions managed by access network devices, running time of AI functions, start time of AI functions, or stop time of AI functions.

[0397] In the embodiments of the present disclosure, some or all of the steps and their optional implementations may be arbitrarily combined with some or all of the steps in other embodiments, or may be arbitrarily combined with the optional implementations of other embodiments.

[0398] The embodiments of the present disclosure further provide an apparatus for implementing any of the above methods. For example, an apparatus is provided, comprising units or modules for implementing each step performed by a terminal in any of the above methods. For another example, another apparatus is provided, comprising units or modules for implementing each step performed by a network device (e.g., an access network device, a core network function node, a core network device, etc.) in any of the above methods.

[0399] It should be understood that the division of the various units or modules in the above device is merely a division of logical functions. In actual implementation, they may be fully or partially integrated into a physical entity, or they may be physically separated. In addition, the units or modules in the device may be implemented in the form of a processor calling software: for example, the device includes a processor, the processor is connected to a memory, and the memory stores instructions. The processor calls the instructions stored in the memory to implement any of the above methods or implement the functions of the various units or modules of the above device, wherein the processor is, for example, a general-purpose processor, such as a central processing unit (CPU) or a microprocessor, and the memory is a memory within the device or a memory outside the device. Alternatively, the units or modules in the device can be implemented in the form of hardware circuits, and the functions of some or all of the units or modules can be realized by designing the hardware circuits. The above-mentioned hardware circuits can be understood as one or more processors; for example, in one implementation, the above-mentioned hardware circuit is an application-specific integrated circuit (ASIC), which realizes the functions of some or all of the above units or modules by designing the logical relationship of the components in the circuit; for example, in another implementation, the above-mentioned hardware circuit can be realized by a programmable logic device (PLD). Taking a field programmable gate array (FPGA) as an example, it can include a large number of logic gate circuits, and the connection relationship between the logic gate circuits is configured by configuring the configuration file, thereby realizing the functions of some or all of the above units or modules. All units or modules of the above devices can be realized in the form of software called by the processor, or in the form of hardware circuits, or in part by the form of software called by the processor, and the rest by hardware circuits.

[0400] In the embodiments of the present disclosure, the processor is a circuit with signal processing capabilities. In one implementation, the processor can be a circuit with instruction reading and execution capabilities, such as a central processing unit (CPU), a microprocessor, a graphics processing unit (GPU) (which can be understood as a microprocessor), or a digital signal processor (DSP). In another implementation, the processor can implement certain functions through the logical relationship of the hardware circuit. The logical relationship of the above-mentioned hardware circuit is fixed or reconfigurable. For example, the processor is a hardware circuit implemented by an application-specific integrated circuit (ASIC) or a programmable logic device (PLD), such as an FPGA. In a reconfigurable hardware circuit, the process of the processor loading a configuration document and implementing the hardware circuit configuration can be understood as the process of the processor loading instructions to implement the functions of some or all of the above units or modules. In addition, it can also be a hardware circuit designed for artificial intelligence, which can be understood as an ASIC, such as a neural network processing unit (NPU), a tensor processing unit (TPU), a deep learning processing unit (DPU), etc.

[0401] Figure 6A is a schematic diagram of the structure of the first network element proposed in an embodiment of the present disclosure. As shown in Figure 6A, the first network element 6100 may include: a transceiver module 6101 and a processing module 6102. In some embodiments, the above-mentioned transceiver module 6101 is used to send first information to the second network element, wherein the first information includes artificial intelligence AI function information running on the terminal. Optionally, the above-mentioned transceiver module 6101 is used to perform at least one of the communication steps such as sending and / or receiving (for example, step S2101, but not limited to this) performed by the first network element 101 in any of the above methods, which will not be repeated here.

[0402] In some embodiments, the processing module 6102 is configured to communicate based on the first information. Optionally, the processing module 6102 is configured to execute at least one of the processing steps (such as step S2102, but not limited thereto) executed by the second network element 102 in any of the above methods, which will not be described in detail here.

[0403] Figure 6B is a structural diagram of the second network element proposed in an embodiment of the present disclosure. As shown in Figure 6B, the second network element 6200 may include: a transceiver module 6201. In some embodiments, the above-mentioned transceiver module 6201 is used to receive first information from the first network element, wherein the first information is sent by the first network element, and the first information includes artificial intelligence AI function information running on the terminal. Optionally, the above-mentioned transceiver module 6201 is used to perform at least one of the communication steps such as sending and / or receiving (for example, step S2101, but not limited to this) performed by the second network element 102 in any of the above methods, which will not be repeated here.

[0404] In some embodiments, the processing module 6202 is configured to communicate based on the first information, wherein the first information is sent by the first network element and includes information about the artificial intelligence (AI) function running on the terminal. Optionally, the processing module 6202 is configured to execute at least one of the processing steps (such as step S2102, but not limited thereto) performed by the second network element 102 in any of the above methods, which will not be further described here.

[0405] In some embodiments, the transceiver module may include a transmitting module and / or a receiving module, and the transmitting module and the receiving module may be separate or integrated. Optionally, the transceiver module may be interchangeable with the transceiver.

[0406] In some embodiments, the processing module can be a single module or can include multiple submodules. Optionally, the multiple submodules respectively execute all or part of the steps required to be executed by the processing module. Optionally, the processing module can be interchangeable with the processor.

[0407] Figure 7A is a schematic diagram of the structure of a communication device 7100 proposed in an embodiment of the present disclosure. Communication device 7100 can be a network device (e.g., an access network device, a core network device, etc.), a terminal (e.g., a user equipment, etc.), a chip, a chip system, or a processor that supports a network device to implement any of the above methods, or a chip, a chip system, or a processor that supports a terminal to implement any of the above methods. Communication device 7100 can be used to implement the methods described in the above method embodiments. For details, please refer to the description of the above method embodiments.

[0408] As shown in Figure 7A, the communication device 7100 includes one or more processors 7101. The processor 7101 can be a general-purpose processor or a dedicated processor, for example, a baseband processor or a central processing unit. The baseband processor can be used to process the communication protocol and communication data, and the central processing unit can be used to control the communication device (such as a base station, a baseband chip, a terminal device, a terminal device chip, a DU or a CU, etc.), execute programs, and process program data. Optionally, the communication device 7100 is used to perform any of the above methods. Optionally, one or more processors 7101 are used to call instructions to enable the communication device 7100 to perform any of the above methods.

[0409] In some embodiments, the communication device 7100 further includes one or more transceivers 7102. When the communication device 7100 includes one or more transceivers 7102, the transceiver 7102 performs at least one of the communication steps such as sending and / or receiving in the above method (for example, step S2101, but not limited thereto), and the processor 7101 performs at least one of the other steps (for example, step S2102, but not limited thereto). In an optional embodiment, the transceiver may include a receiver and / or a transmitter, and the receiver and transmitter may be separate or integrated. Optionally, the terms transceiver, transceiver unit, transceiver, transceiver circuit, interface circuit, and interface may be interchangeable, the terms transmitter, transmitting unit, transmitter, and transmitting circuit may be interchangeable, and the terms receiver, receiving unit, receiver, and receiving circuit may be interchangeable.

[0410] In some embodiments, the communication device 7100 further includes one or more memories 7103 for storing data. Alternatively, all or part of the memories 7103 may be located outside the communication device 7100. In alternative embodiments, the communication device 7100 may include one or more interface circuits 7104. Optionally, the interface circuits 7104 are connected to the memories 7103 and may be configured to receive data from the memories 7103 or other devices, or to send data to the memories 7103 or other devices. For example, the interface circuits 7104 may read data stored in the memories 7103 and send the data to the processor 7101.

[0411] The communication device 7100 described in the above embodiment may be a network device or a terminal, but the scope of the communication device 7100 described in the present disclosure is not limited thereto, and the structure of the communication device 7100 may not be limited by FIG. 7A. The communication device may be an independent device or may be part of a larger device. For example, the communication device may be: 1) an independent integrated circuit IC, or a chip, or a chip system or subsystem; (2) a collection of one or more ICs, optionally, the above IC collection may also include a storage component for storing data or programs; (3) an ASIC, such as a modem; (4) a module that can be embedded in other devices; (5) a receiver, a terminal device, an intelligent terminal device, a cellular phone, a wireless device, a handheld device, a mobile unit, an in-vehicle device, a network device, a cloud device, an artificial intelligence device, etc.; (6) others, etc.

[0412] 7B is a schematic diagram of the structure of a chip 7200 proposed in an embodiment of the present disclosure. If the communication device 7100 can be a chip or a chip system, please refer to the schematic diagram of the structure of the chip 7200 shown in FIG7B , but the present disclosure is not limited thereto.

[0413] The chip 7200 includes one or more processors 7201. The chip 7200 is configured to execute any of the above methods.

[0414] In some embodiments, chip 7200 further includes one or more interface circuits 7202. Alternatively, terms such as interface circuit, interface, and transceiver pins may be used interchangeably. In some embodiments, chip 7200 further includes one or more memories 7203 for storing data. Alternatively, all or part of memory 7203 may be located external to chip 7200. Optionally, interface circuit 7202 is connected to memory 7203 and may be used to receive data from memory 7203 or other devices, or may be used to send data to memory 7203 or other devices. For example, interface circuit 7202 may read data stored in memory 7203 and send the data to processor 7201.

[0415] In some embodiments, the interface circuit 7202 performs at least one of the communication steps (e.g., but not limited to, step S2101) in the above method, such as sending and / or receiving. For example, the interface circuit 7202 performs the communication steps (e.g., sending and / or receiving) in the above method, which means that the interface circuit 7202 performs data exchange between the processor 7201, the chip 7200, the memory 7203, or the transceiver device. In some embodiments, the processor 7201 performs at least one of the other steps (e.g., but not limited to, step S2102).

[0416] The modules and / or devices described in various embodiments, such as virtual devices, physical devices, and chips, can be arbitrarily combined or separated according to circumstances. Optionally, some or all steps can also be performed collaboratively by multiple modules and / or devices, which is not limited here.

[0417] The present disclosure also proposes a storage medium having instructions stored thereon. When the instructions are executed on the communication device 7100, the communication device 7100 executes any of the above methods. Optionally, the storage medium is an electronic storage medium. Optionally, the storage medium is a computer-readable storage medium, but is not limited thereto and may also be a storage medium readable by other devices. Optionally, the storage medium may be a non-transitory storage medium, but is not limited thereto and may also be a temporary storage medium.

[0418] The present disclosure also provides a program product, which, when executed by the communication device 7100, enables the communication device 7100 to perform any of the above methods. Optionally, the program product is a computer program product.

[0419] The present disclosure also proposes a computer program, which, when executed on a computer, causes the computer to perform any one of the above methods.

Claims

1. A communication method, characterized in that, The method includes: A first network element sends first information to a second network element, where the first information includes artificial intelligence (AI) function information of a terminal.

2. The method according to claim 1, wherein The AI function information is configured by a third network element.

3. The method according to claim 1 or 2, characterized in that, The first network element is the terminal, the second network element is a core network device, and the third network element is an access network device.

4. The method according to any one of claims 1 to 3, characterized in that The first information includes at least one of the following: The AI function configured by the third network element for channel state information (CSI) prediction; The AI function configured by the third network element for CSI compression; The AI function configured by the third network element for beam management; The first AI function configured by the third network element, where the first AI function is an AI function configured by the third network element other than the AI function for CSI prediction, the AI function for CSI compression, and the AI function for beam management; The running time of the AI function; The start time of the AI function running; The end time of the AI function running; The computing power available for CSI prediction; The computing power available for CSI compression; The computing power available for beam management; The computing power available for the first AI function configured by the third network element; The computing power available for the AI function configured by the second network element; The number of AI functions configured by the second network element that the first network element can run simultaneously; The number of AI models configured by the second network element that the first network element can run simultaneously; The AI functions configured by the second network element that the first network element can run simultaneously; The AI models configured by the second network element that the first network element can run simultaneously.

5. The method according to any one of claims 3 to 4, characterized in that The first information is carried on at least one of the following: Long-Term Proximity (LPP) protocol; Sidelink Positioning Protocol (SLPP).

6. The method according to claim 1 or 2, characterized in that, The first network element is the terminal, the second network element is an access network device, and the third network element is a core network device.

7. The method according to claim 6, characterized in that, The first information includes at least one of the following: The AI function configured by the third network element for positioning; The second AI function, where the second AI function is an AI function configured by the third network element other than the AI function for positioning; The running time of the AI function; The start time of the AI function running; The end time of the AI function running; The computing power available for AI positioning configured by the third network element; The computing power available for the second AI function configured by the third network element; The computing power available for CSI prediction; The computing power available for CSI compression; The computing power available for beam management; The computing power available for the AI function configured by the second network element; The number of AI functions configured by the second network element that the first network element can run simultaneously; The number of AI models configured by the second network element that the first network element can run simultaneously; The AI functions configured by the second network element that the first network element can run simultaneously; The AI models configured by the second network element that the first network element can run simultaneously.

8. The method according to claim 7, wherein The first information is carried on radio resource control (RRC) signaling.

9. The method according to claim 1, wherein The first network element is an access network device, and the second network element is a core network device.

10. The method according to claim 9, wherein The first information includes at least one of the following: The AI function for CSI prediction configured by the access network device for the terminal; The AI function for CSI compression configured by the access network device for the terminal; The AI function for beam management configured by the access network device for the terminal; A third AI function, which is an AI function configured by the access network device for the terminal other than the AI function for CSI prediction, the AI function for CSI compression, and the AI function for beam management among the AI functions configured by the access network device for the terminal; The computing power of the terminal that can be used for the AI-based positioning configured by the core network device; The computing power of the terminal that can be used for the AI function configured by the core network device; The computing power of the terminal for the AI function configured by the access network device; The running time of the AI function of the terminal; The start time of the operation of the AI function of the terminal; The end time of the operation of the AI function of the terminal.

11. The method according to claim 1, wherein The first network element is a core network device, and the second network element is an access network device.

12. The method according to claim 11, wherein The first information includes at least one of the following: The AI function for positioning configured by the core network device for the terminal; A fourth AI function, which is an AI function configured by the core network device for the terminal other than the AI function for positioning; The computing power of the terminal for positioning; The computing power of the terminal for the AI function configured by the core network device; The computing power of the terminal that can be used for the AI function configured by the access network device; The running time of the AI function of the terminal; The start time of the operation of the AI function of the terminal; The end time of the operation of the AI function of the terminal.

13. A communication method, characterized in that, The method includes: The second network element receives the first information, which is sent by the first network element, and the first information includes the artificial intelligence (AI) function information of the terminal operation.

14. The method according to claim 13, characterized in that, The AI function information is configured by the third network element.

15. The method according to claim 13 or 14, characterized in that, The first network element is the terminal, the second network element is the core network device, and the third network element is the access network device.

16. The method according to any one of claims 13 to 15, characterized in that, The first information includes at least one of the following: The AI function for channel state information (CSI) prediction configured by the third network element; The AI function for CSI compression configured by the third network element; The AI function for beam management configured by the third network element; The first AI function configured by the third network element, which is an AI function configured by the third network element other than the AI function for CSI prediction, the AI function for CSI compression, and the AI function for beam management; The running time of the AI function; The start time of the operation of the AI function; The end time of the operation of the AI function; The computing power that can be used for CSI prediction; The computing power that can be used for CSI compression; The computing power that can be used for beam management; The computing power that can be used for the first AI function configured by the third network element; The computing power that can be used for the AI function configured by the second network element; The number of AI functions configured on the second network element that can be run simultaneously by the first network element; The number of AI models configured by the second network element that can be run simultaneously by the first network element; The first network element can simultaneously run an AI function configured by the second network element; The first network element can simultaneously run an AI model configured by the second network element.

17. The method according to any one of claims 15 to 16, characterized in that The first information is carried by at least one of the following: Long-term positioning protocol LPP; Sidelink Positioning Protocol SLPP.

18. The method according to claim 13 or 14, characterized in that, The first network element is the terminal, the second network element is an access network device, and the third network element is a core network device.

19. The method according to claim 18, wherein The first information includes at least one of the following: an AI function for positioning configured by the third network element; a second AI function, where the second AI function is an AI function configured by the third network element, excluding the AI ​​function for positioning; The operating time of AI functions; The start time of the AI ​​function operation; The termination time of the AI ​​function operation; The computing capability of AI positioning configured by the third network element; The computing capability of the second AI function configured by the third network element; Computing power that can be used for CSI prediction; Computational power that can be used for CSI compression; Computing power that can be used for beam management; The computing power capable of being used for the AI ​​function configured by the second network element; The number of AI functions configured in the second network element that can be simultaneously run by the first network element; The number of AI models configured by the second network element that can be run simultaneously by the first network element; The first network element can simultaneously run an AI function configured by the second network element; The first network element is capable of simultaneously running an AI model configured by the second network element.

20. The method according to claim 19, wherein The first information is carried in radio resource control RRC signaling.

21. The method according to claim 13, wherein The first network element is an access network device, and the second network element is a core network device.

22. The method according to claim 21, wherein The first information includes at least one of the following: an AI function for CSI prediction configured by the access network device for the terminal; an AI function for CSI compression configured by the access network device for the terminal; an AI function for beam management configured by the access network device for the terminal; a third function, where the third function is an AI function configured for the terminal among the AI ​​functions configured by the access network device, except the AI ​​function for CSI prediction, the AI ​​function for CSI compression, and the AI ​​function for beam management; The terminal can be used for AI positioning-based computing capabilities configured by the core network device; The computing capability of the terminal that can be used for the AI ​​function configured by the core network device; The computing capability of the terminal for the AI ​​function configured by the access network device; The running time of the AI ​​function of the terminal; The start time of the AI ​​function operation of the terminal; The termination time of the AI ​​function operation of the terminal.

23. The method according to claim 13, wherein The first network element is a core network device, and the second network element is an access network device.

24. The method according to claim 23, wherein The first information includes at least one of the following: an AI function for positioning configured by the core network device for the terminal; The fourth AI function, which is the AI function configured by the core network device for the terminal and excludes the AI function for positioning among the AI functions configured for the terminal; The computing power of the terminal for positioning; The computing power of the terminal for the AI function configured by the core network device; The computing power of the terminal that can be used for the AI function configured by the access network device; The running time of the AI function of the terminal; The start time of the operation of the AI function of the terminal; The end time of the operation of the AI function of the terminal.

25. A communication method, characterized in that, The method includes: A first network element sends first information to a second network element, where the first information includes information about the artificial intelligence (AI) function running on the terminal; The second network element receives the first information.

26. A first network element, characterized in that, It includes: A transceiver module for sending first information to the second network element, where the first information includes information about the artificial intelligence (AI) function running on the terminal.

27. A second network element, characterized in that, It includes: A transceiver module for receiving the first information, where the first information is sent by the first network element and includes information about the artificial intelligence (AI) function running on the terminal.

28. A first network element, characterized in that, It includes: One or more processors; Wherein, the processor is used to execute the communication method according to any one of claims 1 to 12.

29. A second network element, characterized in that, It includes: One or more processors; Wherein, the processor is used to execute the communication method according to any one of claims 12 to 24.

30. A communication system, characterized in that, It includes a first network element and a second network element, where the first network element is configured to implement the communication method according to any one of claims 1 to 12, and the second network element is configured to implement the communication method according to any one of claims 13 to 24.

31. A storage medium, the storage medium stores instructions, characterized in that, When the instruction runs on the communication device, it causes the communication device to execute the communication method according to any one of claims 1 to 12 or 13 to 24.

Images