Communication method and related apparatus

Abstract

The present application provides a communication method and a related apparatus. AI capability information of a communication unit can be conveyed to indicate that the communication unit supports provision of measurement data for an AI positioning model, thereby helping network elements deploying the AI positioning model to efficiently acquire the measurement data for the AI positioning model from the communication unit, and accordingly improving the utilization efficiency of the AI positioning method. The communication unit may be a terminal device, a radio access device, an LMF, or the like.

Description

Communication method and related apparatus

[0001] This application claims priority to the Chinese patent application No. CN202411101443.X, filed on August 9, 2024, and entitled "Communication method and related apparatus", the content of which is incorporated herein by reference in its entirety. TECHNICAL FIELD

[0002] The present application relates to the field of communication technology, in particular to a communication method and related apparatus. BACKGROUND

[0003] With the rapid development of wireless communication technology, the function and application scenarios of base stations as the core components of the network are also expanding. In recent years, the technology of using base stations for environmental perception has gradually attracted attention. This technology is based on the interaction between the base station and the surrounding environment, and through the collection and analysis of signals received by the base station, it realizes the perception and monitoring of the surrounding environment. When using base stations for environmental perception, if there are multiple perception targets in the environment, in the case of introducing terminal device assisted perception, the terminal device needs to send perception reference signals through multiple beams, so as to realize the perception of targets in multiple beam directions.

[0004] However, when using base stations for environmental perception, in the case that the perception reference signal resources of the base station are limited, artificial intelligence (AI) positioning can be used to improve positioning accuracy. However, how to efficiently use the AI positioning method is a problem to be solved. SUMMARY

[0005] The measurement data required by the AI positioning model and the measurement data required by the existing positioning method are generally different, but not all providers of measurement data support providing measurement data for AI positioning models, which restricts the use efficiency of AI positioning methods.

[0006] The embodiments of the present application provide a communication method and related apparatus, which can pass AI capability information of a communication unit to indicate that the communication unit supports providing measurement data for an AI positioning model, so as to facilitate the network element deploying the AI positioning model to more efficiently obtain the measurement data for the AI positioning model from the communication unit, thereby improving the use efficiency of the AI positioning method.

[0007] The following describes a communication method provided by the first aspect of the application. The method can be executed by a first communication unit. The first communication unit can be a provider of measurement data for positioning or a communication unit that performs signal measurement to obtain the measurement data, for example, the first communication unit can be a terminal device or a wireless access device. The measurement data for positioning provided by the first communication unit can include measurement data for an AI positioning model.

[0008] The first communication unit can be a device or apparatus with a chip, or a device or apparatus integrated with a circuit, or a chip, chip system, module, or control unit in the foregoing devices or apparatus, which are not limited in the present application. The chip can be a modem chip, also known as a baseband chip, or a system on chip (SoC) chip or system in package (SIP) chip containing a modem core. It should be noted that in the present application, when referring to the first communication unit, it can refer to the first communication unit itself, or a chip, functional module, or integrated circuit in the first communication unit that completes the method provided by the present application, which is not limited in the present application. Similarly, in the present application, when referring to the terminal device, it can refer to the terminal device itself, or a chip, functional module, or integrated circuit in the terminal device that completes the method provided by the present application, which is not limited in the present application. Similarly, in the present application, when referring to the wireless access device, it can refer to the wireless access device itself, or a chip, functional module, or integrated circuit in the wireless access device that completes the method provided by the present application, which is not limited in the present application.

[0009] In the first aspect and possible implementation manners thereof, the method executed by the first communication unit is described as an example. The method can include: the first communication unit sending first information, the first information including AI capability information of the first communication unit, the AI capability information of the first communication unit being used to indicate that the first communication unit supports providing measurement data for an AI positioning model. The first communication unit sends its own AI capability information to other network elements, which can inform other network elements that it supports providing measurement data for an AI positioning model, thereby facilitating network elements deploying AI positioning models to more efficiently obtain measurement data for AI positioning models from the first communication unit, and further improving the use efficiency of AI positioning methods.

[0010] In a possible implementation manner of the first aspect, the first communication unit can send the first information to a second communication unit, and the AI positioning model is deployed on the second communication unit. In this way, the second communication unit can more efficiently determine that the first communication unit supports providing the measurement data for the AI model, thereby improving the use efficiency of the AI positioning method.

[0011] The application does not limit that the first communication unit directly sends its AI capability information to the second communication unit. For example, the first communication unit can forward its AI capability information to the second communication unit through another network element. The second communication unit can provide positioning services for the first communication unit, and / or the AI positioning model can be deployed on the second communication unit, and / or the second communication unit can process the AI positioning model, and / or the second communication unit can perform AI positioning based on the AI positioning model. The second communication unit can be a location management function (LMF).

[0012] In a possible implementation manner of the first aspect, after the first communication unit sends the first information, the first communication unit can further receive second information sent by the second communication unit, and the second information is used to indicate that the first communication unit provides the measurement data.

[0013] In a possible implementation manner of the first aspect, before the first communication unit sends the first information, the first communication unit can further receive third information sent by the second communication unit, and the third information is used to request AI capability information of the first communication unit.

[0014] Optionally, the third information is further used to indicate a type of the requested AI capability, for example, used to indicate a capability of the first communication unit to collect AI measurement data of a target type.

[0015] In a possible implementation manner of the first aspect, the first information is sent to the second communication unit based on information of the second communication unit configured in the first communication unit.

[0016] The communication method provided in the second aspect of the present application is described below. The method can be executed by a second communication unit. The second communication unit can be a communication unit for obtaining measurement data for an AI positioning model from a first communication unit. For example, the second communication unit can provide positioning services for the first communication unit, and / or the AI positioning model can be deployed on the second communication unit, and / or the second communication unit can process the AI positioning model, and / or the second communication unit can perform AI positioning based on the AI positioning model. The first communication unit can be understood with reference to the first communication unit in the communication method provided in the first aspect. For example, the second communication unit can be an LMF.

[0017] The second communication unit can be a device or apparatus with a chip, or a device or apparatus integrated with a circuit, or a chip, a chip system, a module, or a control unit in the foregoing devices or apparatus, which are not limited in the present application. The chip can be a modem chip, also known as a baseband chip, or a system on chip (SoC) chip or a system in package (SIP) chip containing a modem core. It should be noted that, in the present application, when referring to the second communication unit, it can refer to the second communication unit itself, or a chip, a functional module, or an integrated circuit in the second communication unit that completes the method provided in the present application, which is not limited in the present application. Similarly, in the present application, when referring to the LMF, it can refer to the LMF itself, or a chip, a functional module, or an integrated circuit in the LMF that completes the method provided in the present application, which is not limited in the present application.

[0018] In the second aspect and possible implementation manners thereof, the method executed by the second communication unit is described as an example. The method comprises: receiving, by the second communication unit, first information, wherein the first information comprises artificial intelligence (AI) capability information of a first communication unit, and the AI capability information of the first communication unit is used to indicate that the first communication unit supports providing measurement data for an AI positioning model, and the AI positioning model is deployed on the second communication unit. After receiving the first information by the second communication unit, second information can also be sent to the first communication unit, wherein the second information is used to instruct the first communication unit to provide the measurement data.

[0019] Based on the second aspect, in a possible implementation manner, before receiving the first information, the second communication unit also sends third information to the first communication unit, wherein the third information is used to request the AI capability information of the first communication unit.

[0020] Optionally, the third information is also used to indicate the type of the requested AI capability, for example, to indicate the capability of the first communication unit to collect AI measurement data of a target type.

[0021] In a possible implementation manner of the second aspect, the first information is sent by a third communication unit, wherein the third communication unit is configured to store the subscription information of the first communication unit, and the subscription information of the first communication unit comprises the AI capability information of the first communication unit; and before the second communication unit receives the first information sent by the third communication unit, the fourth information can be further sent to the third communication unit, and the fourth information is used to request the subscription information of the first communication unit.

[0022] In a possible implementation manner of the second aspect, the first information is sent by a fourth communication unit, and the fourth communication unit is configured to train the AI positioning model, and the first information is used to instruct the second communication unit to provide the measurement data obtained from the first communication unit.

[0023] In a possible implementation manner of the second aspect, the second communication unit further sends the measurement data obtained from the first communication unit to the fourth communication unit.

[0024] One or more information appearing in the present application can be replaced by other names (for example, message or packet or signaling, etc.).

[0025] In a possible implementation manner of the second aspect, the first information is sent by a fifth communication unit, and the first information is used to instruct the second communication unit to perform positioning based on the AI positioning model and the measurement data obtained from the first communication unit.

[0026] In a possible implementation manner of the second aspect, the second communication unit further sends the positioning result to the fifth communication unit.

[0027] In a possible implementation manner of the second aspect, the second communication unit further sends fifth information to a sixth communication unit, the fifth information comprises the AI capability information of the second communication unit, and the AI capability information of the second communication unit is used to instruct that the second communication unit supports providing the measurement data, and the sixth communication unit is configured to store the AI capability information of the second communication unit.

[0028] In a possible implementation manner of the first aspect or the second aspect, the first communication unit is a terminal device, and the measurement data supported to be provided by the terminal device comprises measurement data of downlink data sent by a radio access device.

[0029] In a possible implementation of the first aspect or the second aspect, the first communication unit is a wireless access device, and the measurement data supported by the wireless access device to provide includes measurement data of uplink data transmitted by the terminal device.

[0030] In a possible implementation of the first aspect or the second aspect, the AI capability information of the first communication unit is further used to indicate a type of the measurement data supported by the first communication unit to provide.

[0031] In a possible implementation of the first aspect or the second aspect, the type of the measurement data indicated by the AI capability information of the first communication unit includes channel impulse response (CIR) and / or channel power delay profile (PDP).

[0032] The communication method provided in the third aspect of the present application is described below. The method can be executed by a second communication unit. The second communication unit can be an AI training data consumer and / or an AI inference result consumer. In the present application, the AI training data consumer refers to a communication unit used to request the first communication unit to provide training data of an AI model, and the AI inference result consumer refers to a communication unit used to request the first communication unit to provide an AI positioning result. The first communication unit can be understood with reference to the second communication unit in the communication method provided in the second aspect. For example, in the communication method provided in the third aspect, the first communication unit can be an LMF. The AI training data consumer and the AI inference result consumer can be collectively referred to as an AI consumer. The present application does not limit the types of the AI training data consumer and the AI inference result consumer. For example, the AI training data consumer can be a model training logical function (MTLF) or a network data analytics function (NWDAF), and the AI inference result consumer can include at least one of an AMF, an SMF, a PCF, an MTLF, and an NWDAF.

[0033] The second communication unit can be a device or apparatus with a chip, or a device or apparatus integrated with a circuit, or a chip, a chip system, a module, or a control unit in the foregoing devices or apparatuses, without limitation. The chip can be a modem chip, also known as a baseband chip, or a system on chip (SoC) chip or a system in package (SIP) chip containing a modem core. It should be noted that, in the present application, the second communication unit can refer to the second communication unit itself, or a chip, a functional module, or an integrated circuit in the second communication unit that implements the method provided in the present application, without limitation. Similarly, in the present application, the MTLF can refer to the MTLF itself, or a chip, a functional module, or an integrated circuit in the MTLF that implements the method provided in the present application, without limitation. Similarly, in the present application, the AMF can refer to the AMF itself, or a chip, a functional module, or an integrated circuit in the AMF that implements the method provided in the present application, without limitation.

[0034] In a third aspect and possible implementation manners thereof, the method is performed by the second communication unit is taken as an example for description. The method comprises: the second communication unit sends first information, the first information comprising a first information element, the first information element being used to indicate that a communication unit supporting providing measurement data for an artificial intelligence (AI) positioning model is discovered; and the second communication unit receives second information, the second information comprising information of a first communication unit, the first communication unit supporting providing the measurement data. The second communication unit can discover an LMF capable of providing measurement data for an AI model by sending the first information and receiving the second information, which is advantageous to avoid a problem that the second communication unit (for example, an MTLF or an AMF) discovers an LMF, but the LMF cannot collect AI measurement data from a UE / gNB, so that the LMF can determine which UE / gNB supports providing AI measurement data when collecting AI measurement data, enabling normal AI measurement data collection, completing or assisting in completing an AI positioning model training / inference process based on AI measurement data.

[0035] According to the third aspect, in a possible implementation manner, the first information further comprises a second information element, the second information element being used to indicate a first area, a service area of the first communication unit containing the first area.

[0036] The service area of the first communication unit can refer to an area in which the first communication unit supports providing positioning services, for example, a service area of an LMF refers to an area in which the LMF supports providing positioning services, or in other words, the LMF supports positioning a UE in the service area.

[0037] In a possible implementation manner of the third aspect, the first region is determined according to a region of interest of the AI positioning model.

[0038] In a possible implementation manner of the third aspect, the method further includes: sending third information to the first communication unit based on information of the first communication unit, the third information being used to instruct to provide the measurement data; and receiving the measurement data provided by the first communication unit, the received measurement data being used to process the AI positioning model.

[0039] In the present application, the measurement data can include measurement data of a signal, and can also include a label (for example, a positioning result or a position of a terminal device) corresponding to the measurement data of the signal.

[0040] In a possible implementation manner of the third aspect, the first region is determined according to a position of a terminal device or a cell of the terminal device.

[0041] In a possible implementation manner of the third aspect, the method further includes: sending fourth information to the first communication unit based on information of the first communication unit, the fourth information being used to instruct the first communication unit to process the position of the terminal device based on the AI positioning model.

[0042] The communication method provided in the fourth aspect of the present application is introduced below. The method can be executed by a fourth communication unit. The fourth communication unit can be understood as the second communication unit in the communication method provided in the third aspect. The fourth communication unit can be a communication unit used to request the second communication unit to provide training data of an AI model, and / or used to request the second communication unit to provide an AI positioning result. The second communication unit can be understood with reference to the second communication unit in the communication method provided in the second aspect. For example, in the communication method provided in the third aspect, the second communication unit can be an LMF. As introduced in the communication method provided in the third aspect, the fourth communication unit can be an AI training data consumer (for example, an MTLF) or an AI inference result consumer (for example, an AMF). With the evolution of network elements, the MTLF can also be an AI inference result consumer, that is, to use an AI positioning model for positioning.

[0043] In a fourth aspect and possible implementation manners thereof, the method is performed by a fourth communication unit. The method comprises: receiving, by the fourth communication unit, first information, the first information comprising artificial intelligence (AI) capability information of a first communication unit, the AI capability information of the first communication unit being used to indicate that the first communication unit supports providing measurement data for an AI positioning model, the first communication unit being served by a second communication unit; and then sending, by the fourth communication unit, second information to the second communication unit, the second information being used to instruct the second communication unit to provide the measurement data, or sending third information to the second communication unit, the third information being used to instruct the second communication unit to perform positioning based on the AI positioning model and the measurement data. The first communication unit can be understood with reference to the first communication unit in the first aspect. The fourth communication unit (for example, an AMF or an MTLF) screens a terminal device or a wireless access device that can provide AI measurement data based on AI capability information in subscription information of the terminal device / wireless access device, thereby avoiding a problem that the fourth communication unit directly requests the AI measurement data of the terminal device or the wireless access device from the second communication unit (for example, an LMF) but the terminal device or the wireless access device cannot provide the AI measurement data.

[0044] In a possible implementation manner based on the fourth aspect, the first information further comprises information of the second communication unit.

[0045] In a possible implementation manner based on the fourth aspect, the first information is sent by a third communication unit, the third communication unit being used to save subscription information of the first communication unit, the subscription information of the first communication unit comprising the AI capability information of the first communication unit. Before receiving the first information, the third communication unit can further send fourth information to the third communication unit, the fourth information being used to request the subscription information of the first communication unit. By storing the AI capability information that the terminal device or the wireless access device can provide AI measurement data as the subscription information of the terminal device or the wireless access device to the third communication unit (for example, a UDM), the fourth communication unit can first screen the terminal device or the wireless access device that supports providing AI measurement data, so that the fourth communication unit can directly request the AI measurement data of the terminal device or the wireless access device from the second communication unit that serves the terminal device or the wireless access device.

[0046] The communication apparatus provided in the fifth aspect of the present application is described below. The communication apparatus can be the first communication unit in the communication method of the first aspect or be deployed in the first communication unit.

[0047] The communication apparatus can comprise a sending module configured to send first information, the first information comprising artificial intelligence (AI) capability information of a first communication unit, the AI capability information of the first communication unit being used to indicate that the first communication unit supports providing measurement data for an AI positioning model.

[0048] Based on the fifth aspect, in a possible implementation, the sending module is specifically configured to send the first information to a second communication unit on which the AI positioning model is deployed.

[0049] Based on the fifth aspect, in a possible implementation, the communication apparatus can further comprise a receiving module configured to receive second information sent by the second communication unit after the sending module sends the first information, the second information being used to indicate that the first communication unit provides the measurement data.

[0050] Based on the fifth aspect, in a possible implementation, the receiving module is further configured to receive third information sent by the second communication unit before the sending module sends the first information, the third information being used to request AI capability information of the first communication unit.

[0051] Based on the fifth aspect, in a possible implementation, the first information is sent to the second communication unit based on information of the second communication unit configured in the first communication unit.

[0052] The communication apparatus provided in the sixth aspect of the present application is described below. The communication apparatus can be the second communication unit in the communication method of the second aspect or be deployed in the second communication unit. The communication apparatus can comprise a receiving module. The receiving module is configured to receive first information, the first information comprising artificial intelligence (AI) capability information of a first communication unit, the AI capability information of the first communication unit being used to indicate that the first communication unit supports providing measurement data for an AI positioning model, the AI positioning model being deployed in the second communication unit.

[0053] The communication apparatus can further comprise a sending module configured to send second information to the first communication unit after the receiving module receives the first information, the second information being used to indicate that the first communication unit provides the measurement data.

[0054] Based on the sixth aspect, in a possible implementation, the first information is sent by the first communication unit.

[0055] Based on the sixth aspect, in a possible implementation, the sending module is further configured to send third information to the first communication unit before the receiving module receives the first information, the third information being used to request AI capability information of the first communication unit.

[0056] In a possible implementation manner of the sixth aspect, the first information is sent by a third communication unit, where the third communication unit is configured to store subscription information of the first communication unit, and the subscription information of the first communication unit includes AI capability information of the first communication unit, and the sending module is further configured to send fourth information to the third communication unit before the receiving module receives the first information sent by the third communication unit, where the fourth information is used to request the subscription information of the first communication unit.

[0057] In a possible implementation manner of the sixth aspect, the first information is sent by a fourth communication unit, where the fourth communication unit is configured to train the AI positioning model, and the first information is used to instruct the second communication unit to provide the measurement data obtained from the first communication unit.

[0058] In a possible implementation manner of the sixth aspect, the first information is sent by a fifth communication unit, and the first information is used to instruct the second communication unit to perform positioning based on the AI positioning model and the measurement data obtained from the first communication unit.

[0059] In a possible implementation manner of the sixth aspect, the sending module is further configured to send fifth information to a sixth communication unit, where the fifth information includes AI capability information of the second communication unit, the AI capability information of the second communication unit is used to instruct the second communication unit to support providing the measurement data, and the sixth communication unit is configured to store the AI capability information of the second communication unit.

[0060] In a possible implementation manner of the fifth aspect or the sixth aspect, the first communication unit is a terminal device, and the measurement data supported to be provided by the terminal device includes measurement data of downlink data sent by a radio access device.

[0061] In a possible implementation manner of the fifth aspect or the sixth aspect, the first communication unit is a radio access device, and the measurement data supported to be provided by the radio access device includes measurement data of uplink data sent by a terminal device.

[0062] In a possible implementation manner of the fifth aspect or the sixth aspect, the AI capability information of the first communication unit is further used to instruct a type of the measurement data supported to be provided by the first communication unit.

[0063] In a possible implementation manner of the fifth aspect or the sixth aspect, the type of the measurement data instructed by the AI capability information of the first communication unit includes channel impulse response (CIR) and / or channel power delay profile (PDP).

[0064] The communication apparatus provided in the seventh aspect of the present application is introduced as follows. The communication apparatus can be the second communication unit in the communication method provided in the third aspect or be deployed in the second communication unit. The communication apparatus can include a sending module configured to send first information, the first information including a first information unit configured to indicate that a communication unit supporting providing measurement data for an artificial intelligence (AI) positioning model is discovered. The communication apparatus can further include a receiving module configured to receive second information, the second information including information of a first communication unit, the first communication unit supporting providing the measurement data.

[0065] In a possible implementation manner based on the seventh aspect, the first information further includes a second information unit configured to indicate a first area, a service area of the first communication unit containing the first area.

[0066] In a possible implementation manner based on the seventh aspect, the first area is determined according to a region of interest of the AI positioning model.

[0067] In a possible implementation manner based on the seventh aspect, the sending module is further configured to send, to the first communication unit, third information based on the information of the first communication unit, the third information being configured to indicate that the measurement data is provided, and the receiving module is further configured to receive the measurement data provided by the first communication unit, the received measurement data being used for processing the AI positioning model.

[0068] In a possible implementation manner based on the seventh aspect, the first area is determined according to a location of a terminal device or a cell of the terminal device.

[0069] In a possible implementation manner based on the seventh aspect, the sending module is further configured to send, to the first communication unit, fourth information based on the information of the first communication unit, the fourth information being configured to indicate that the first communication unit processes the location of the terminal device based on the AI positioning model.

[0070] The communication apparatus provided in the eighth aspect of the present application is introduced as follows. The communication apparatus can be a second communication unit in the communication method provided in the fourth aspect or be deployed in the second communication unit. The communication apparatus can include a receiving module configured to receive first information, wherein the first information includes artificial intelligence (AI) capability information of a first communication unit, the AI capability information of the first communication unit is used to indicate that the first communication unit supports providing measurement data for an AI positioning model, and the first communication unit is served by the second communication unit. The communication apparatus can further include a sending module configured to send second information to the second communication unit, wherein the second information is used to instruct the second communication unit to provide the measurement data, or send third information to the second communication unit, wherein the third information is used to instruct the second communication unit to perform positioning based on the AI positioning model and the measurement data.

[0071] According to the eighth aspect, in a possible implementation, the first information further includes information of the second communication unit.

[0072] According to the eighth aspect, in a possible implementation, the first information is sent by a third communication unit, the third communication unit is used to save subscription information of the first communication unit, the subscription information of the first communication unit includes the AI capability information of the first communication unit, and the sending module is further configured to send fourth information to the third communication unit before the receiving module receives the first information, wherein the fourth information is used to request the subscription information of the first communication unit.

[0073] The ninth aspect of the present application provides a communication apparatus, which includes a processor and a memory. The memory stores computer programs or computer instructions. The processor is configured to invoke and run the computer programs or computer instructions stored in the memory, so that the processor implements any one of the implementation manners in any one of the first aspect to the fourth aspect.

[0074] Optionally, the communication apparatus further includes a transceiver, and the processor is configured to control the transceiver to transceive signals or information.

[0075] The tenth aspect of the present application provides a communication apparatus, which includes a processor and an interface circuit. The processor is configured to communicate with other apparatuses through the interface circuit and perform the method described in any one of the first aspect to the fourth aspect. The processor includes one or more.

[0076] The eleventh aspect of the present application provides a communication device, comprising a processor connected with a memory, and used to invoke a program stored in the memory to execute the method in any one of the first aspect to the fourth aspect. The memory can be located in the communication device or outside the communication device. The processor comprises one or more processors.

[0077] In an implementation, at least one of the first communication unit, the second communication unit, the third communication unit, the fourth communication unit, the fifth communication unit and the sixth communication unit can be a chip or a chip system.

[0078] The twelfth aspect of the present application provides a computer program product comprising computer instructions, which, when executed on a computer, cause the computer to perform any one of the implementations of any one of the first aspect to the fourth aspect.

[0079] The thirteenth aspect of the present application provides a computer-readable storage medium comprising computer instructions, which, when executed on a computer, cause the computer to perform any one of the implementations of any one of the first aspect to the fourth aspect.

[0080] The fourteenth aspect of the present application provides a chip (device) comprising a processor, which is used to invoke a computer program or computer instructions in a memory to cause the processor to perform any one of the implementations of any one of the first aspect to the fourth aspect.

[0081] Optionally, the processor is coupled with the memory through an interface.

[0082] The fifteenth aspect of the present application provides a communication system, comprising at least one of the execution subject of the communication method provided in the first aspect, the execution subject of the communication method provided in the second aspect, the execution subject of the communication method provided in the third aspect and the execution subject of the communication method provided in the fourth aspect.

[0083] According to the above technical solution, the AI capability information of the communication unit is transmitted to indicate that the communication unit supports providing measurement data for the AI positioning model, so that the network element deploying the AI positioning model can more efficiently obtain the measurement data for the AI positioning model from the communication unit, thereby improving the use efficiency of the AI positioning method. BRIEF DESCRIPTION OF DRAWINGS

[0084] FIG. 1 schematically shows an application scenario of utilizing a base station for sensing;

[0085] FIG. 2 schematically shows an application scenario of utilizing a terminal device to assist a base station for sensing;

[0086] FIG. 3-1 and FIG. 3-2 respectively show a schematic diagram of a communication system according to an embodiment of the present application;

[0087] FIG. 3-3 shows a schematic diagram of a 5G network architecture based on service interface;

[0088] FIG. 4-1 and FIG. 4-2 respectively show a downlink positioning scenario and an uplink positioning scenario;

[0089] FIG. 5, FIG. 6-1, FIG. 6-2, FIG. 7 to FIG. 14 respectively show a possible flow of a communication method provided by the present application;

[0090] FIG. 15 shows a schematic diagram of a simplified structure of a UE;

[0091] FIG. 16 shows a schematic diagram of a simplified structure of a base station. DETAILED DESCRIPTION

[0092] First, some terms in the embodiments of the present application are explained to facilitate understanding by those skilled in the art.

[0093] (1) Configuration and pre-configuration: In the present application, configuration and pre-configuration will be used together. Configuration refers to that a network device such as a base station or a server sends some parameter configuration information or parameter values to a terminal through a message or signaling, so that the terminal determines the communication parameters or transmission resources according to the values or information. Pre-configuration is similar to configuration, which can be a way that a network device such as a base station or a server sends parameter information or values to a terminal through a communication link or carrier; or a way that the corresponding parameters or parameter values are defined in the standard, or the related parameters or values are set in the terminal device in advance, which is not limited in the present application. Further, these values and parameters can be changed or updated.

[0094] (2) In the present application, "for indicating" can include for directly indicating and for indirectly indicating. When describing that an indication information is for indicating A, it can be understood as that the indication information carries A, directly indicates A or indirectly indicates A.

[0095] In the present application, the information indicated by the indication information is referred to as to-be-indicated information. In the specific implementation process, there are many ways to indicate the to-be-indicated information, for example, it can be realized by a direct indication manner, such as indicating by the to-be-indicated information itself or the index of the to-be-indicated information. It can also be realized by an indirect indication manner by indicating other information, wherein the to-be-indicated information and the other information have an association relationship. It can also only indicate a part of the to-be-indicated information, and the other part of the to-be-indicated information is known or agreed in advance. For example, the indication of specific information can also be realized by means of the arrangement order of each information agreed in advance (for example, the protocol stipulates), thereby reducing the indication overhead to a certain extent.

[0096] The to-be-indicated information can be sent as a whole, or can be sent separately into multiple sub-information, and the sending period and / or sending time of the sub-information can be the same or different. The specific sending method is not limited in the present application. The sending period and / or sending time of the sub-information can be predefined, for example, predefined according to the protocol, or configured by the transmitting end device to the receiving end device by sending configuration information. The configuration information may, for example, but not limited to, include one or a combination of at least two of RRC signaling, medium access control (MAC) layer signaling and physical layer signaling. The MAC layer signaling may, for example, include a medium access control control element (MAC CE); the physical layer signaling may, for example, include downlink control information (DCI).

[0097] (3) The terms "system" and "network" in the embodiments of the present application can be used interchangeably. "At least one" means one or more, and "multiple" means two or more. The "and / or" describes the association relationship of the associated objects, which means that there can be three relationships, for example, A and / or B, which can represent the cases of A alone, A and B together, and B alone, wherein A and B can be singular or plural. The character " / " generally represents an "or" relationship between the front and rear associated objects. "At least one of the following" or similar expressions means any combination of these items, including any combination of single item or multiple items. For example, "at least one of A, B and C" includes A, B, C, AB, AC, BC or ABC. In addition, unless otherwise specified, the ordinal numbers "first", "second", etc. mentioned in the embodiments of the present application are used to distinguish multiple objects, and are not used to limit the order, time sequence, priority or importance of the multiple objects.

[0098] (4) In the embodiments of the present application, “sending” and “receiving” represent the direction of signal transmission. In the present application, entity A sending information to entity B can mean that A directly sends to B, or A indirectly sends to B through other entities. Similarly, entity B receiving information from entity A can mean that entity B directly receives the information sent by entity A, or that entity B indirectly receives the information sent by entity A through other entities. Here, entity A and B can be RAN nodes or terminals, or modules inside RAN nodes or terminals. The sending and receiving of information can be the exchange of information between RAN nodes and terminals, for example, the exchange of information between a base station and a terminal; the sending and receiving of information can also be the exchange of information between two RAN nodes, for example, the exchange of information between a CU and a DU; the sending and receiving of information can also be the exchange of information between different modules inside one device, for example, the exchange of information between a terminal chip and other modules of the terminal, or the exchange of information between a base station chip and other modules of the base station. “Sending” can also be understood as the “output” of the chip interface, and “receiving” can also be understood as the “input” of the chip interface.

[0099] (5) In the embodiments of the present application, artificial intelligence (AI) can enable machines to have human intelligence, for example, enabling machines to apply computer hardware and software to simulate certain intelligent behaviors of humans. To achieve artificial intelligence, a machine learning method can be used. In the machine learning method, the machine learns (or trains) a model using training data. The model represents the mapping between the input and the output. The learned model can be used for inference (or prediction), i.e., the model can be used to predict the output corresponding to a given input. The output can also be referred to as an inference result (or prediction result).

[0100] (6) Routing ID: used to identify the serving LMF of the UE, and is information of the serving LMF locally configured by the UE. Hereinafter, the routing ID is referred to as the first identifier of the LMF.

[0101] (7) Correlation ID: used to identify the serving LMF of the UE. Hereinafter, the correlation ID is referred to as the second identifier of the LMF. The second identifier of the LMF has a similar function to the first identifier of the LMF, and the difference is that the first identifier of the LMF is used for identification between the AMF and the UE, and the second identifier of the LMF is used for identification between the LMF and the AMF.

[0102] (8) Positioning Reference Signal (PRS) is a downlink reference signal introduced in 3GPP R16 version, which is used for downlink positioning technology. In DL-TDOA (Downlink Time Difference Of Arrival) positioning, the downlink time difference of arrival between two groups of TRPs is measured based on the downlink PRS signal to determine the position information of the UE; in Multi-RTT (Multi-Round Trip Time) positioning, the round trip time between two groups of TRPs is measured based on the uplink positioning SRS signal and the downlink PRS signal to determine the position information of the UE; in DL-AoD positioning, the downlink departure angle AoD of multiple TRPs is measured based on the downlink PRS signal to determine the position information of the UE.

[0103] (9) Sounding Reference Signal (SRS) is a reference pilot signal of the uplink wireless environment, which does not need to be accompanied by any physical channel, and is mainly used for uplink state information measurement by the base station in wireless resource scheduling and wireless link adaptation.

[0104] Next, the full name of some English abbreviations in the present application is described.

[0105] Reference to "one embodiment" or "some embodiments" or "one implementation" or "some implementations" etc. described in the present application means that the particular feature, structure or characteristic described in connection with the embodiment is included in one or more embodiments of the present application. Therefore, the statements "in one embodiment", "in some embodiments", "in other some embodiments", "in further some embodiments" etc. appearing in different places in the specification are not necessarily all referring to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized. The terms "include", "contain", "have" and their variants mean "including but not limited to", unless otherwise specifically emphasized.

[0106] In the description of the present application, unless otherwise specified, " / " means "or", for example, A / B can mean A or B. "And / or" herein is only a description of the association relationship of the associated objects, which means that there can be three relationships, for example, A and / or B, which can mean: A exists alone, A and B exist together, and B exists alone. In addition, "at least one" means one or more, and "multiple" means two or more. "At least one of the following" or the like means any combination of the items, including any combination of single or multiple items. For example, at least one of a, b, or c can mean a, b, c, a and b, a and c, b and c, or a and b and c. Where a, b, c can be single or multiple.

[0107] With the rapid development of wireless communication technology, base stations as the core components of the network, their functions and application scenarios are also expanding. In recent years, the technology of using base stations for environmental perception has gradually attracted attention. This technology is based on the interaction between the base station and the surrounding environment, by collecting and analyzing the signals received by the base station, to achieve the perception and monitoring of the surrounding environment.

[0108] In the field of environmental perception, traditional methods usually rely on specialized sensors and devices, such as cameras, radars, or infrared detectors, etc. However, these methods have some problems, such as high cost, difficult deployment, affected by weather conditions, etc. In contrast, using base stations for environmental perception has many advantages.

[0109] Base stations have a wide coverage range. As the infrastructure of wireless communication networks, base stations usually cover the entire city or a specific area. This means that using base stations for environmental perception can achieve real-time monitoring of large areas, providing valuable data support for urban planning, traffic management, disaster warning, etc. Secondly, base stations have the characteristics of continuous online. Base stations need to provide communication services for users 24 hours a day, so they are always in working condition. This makes it possible to use base stations for environmental perception to achieve real-time, continuous data collection and analysis, and timely discovery and processing of environmental problems. In addition, using base stations for environmental perception can also reduce costs. Since base stations have been widely deployed in cities, there is no need to install a large number of additional sensors and devices. Only by upgrading and modifying the existing base stations, the perception and monitoring of the surrounding environment can be achieved. This not only saves a lot of investment costs, but also avoids repeated construction and resource waste.

[0110] There is a problem of limited coverage range when sensing by a base station. The base station can only effectively sense and detect strong reflection targets in the visible area. As shown in FIG. 1, for the base station, the sensing area is divided into a line-of-sight (LOS) area and a non-line-of-sight (NLOS) area. Due to the obstruction of obstacles, the target in the NLOS area cannot be effectively sensed. For the NLOS area, a terminal device can be introduced to assist the base station in sensing. For example, as shown in FIG. 2, the terminal device assists the base station to implement sensing of the environment. Specifically, the base station sends a sensing reference signal, which is reflected by a reflector and then reflected by a cylinder to the terminal device. The terminal device can measure the sensing reference signal to obtain a sensing measurement result. The reflector and the cylinder can be considered as sensing targets. If there are multiple sensing targets to be detected, different beams need to be used to send the sensing reference signal, so as to improve the detection accuracy of the sensing targets.

[0111] The following describes a communication system to which the present application is applicable. The present application is still applicable to other communication systems, and the present application is not limited in particular.

[0112] FIG. 3-1 is a schematic diagram of a communication system according to an embodiment of the present application. Referring to FIG. 3-1, the communication system includes a terminal device 301, a next generation Node B (gNB) 302, a next generation evolved Node B (ng-eNB) 303, an access and mobility management function (AMF) 304, a location management function (LMF) 305, and a sensing management function (SMF) 306.

[0113] The terminal device 301 communicates with an access network device (such as the gNB 302 or the ng-eNB 303 in FIG. 3-1) through a Uu interface. The ng-eNB 303 is an access network device in a LTE communication system, and the gNB 302 is an access network device in a new radio (NR) communication system. In the communication system, the access network devices communicate with each other through an Xn interface, and the access network devices and the AMF 304 communicate through an NG-C interface. The AMF 304 and the LMF 305 communicate through an NL1 interface. The AMF 304 is equivalent to a router for communication between the access network device and the LMF 305. The LMF 305 is a network element, module or component in a new radio (NR) core network that provides positioning functions for a terminal device. The LMF 305 is used for positioning calculation of the location of the terminal device. The SMF 306 can store an environmental map and can implement environmental map reconstruction. The SMF 306 interacts with the LMF 305 to exchange environmental and measurement information.

[0114] In the communication system shown in FIG. 3-1, the LMF 305 and the SMF 306 are two network elements deployed separately. In actual applications, the LMF 305 and the SMF 306 can also be deployed or integrated together, that is, the LMF 305 and the SMF 306 are the same network element. The specific application is not limited. For example, as shown in FIG. 3-2, the LMF 305 and the SMF 306 are deployed or integrated together to become a network element that provides sensing and positioning functions.

[0115] FIGS. 3-1 and 3-2 only show an example in which the communication system includes two access network devices of gNB and ng-eNB. In actual applications, the communication system can include at least one access network device, and the specific application is not limited.

[0116] In the communication systems shown in FIGS. 3-1 and 3-2, the LMF is the name of the current communication system. In future communication systems, the name of the LMF may change with the evolution of the communication system. For example, the LMF can also be called a positioning device, a positioning center, a positioning server, a positioning management device, or a positioning management function device. The specific application does not limit the name of the LMF. In the current communication system or the future communication system, as long as other functional network elements with similar functions to the LMF have other names, the LMF in the embodiments of the application can be understood, and the information sending method and the information receiving method provided by the embodiments of the application are applicable.

[0117] In this application, the name of the SMF in the communication system shown in FIG. 3-1 and FIG. 3-2 respectively may change as the communication system evolves. As long as other functional network elements with similar functions to the SMF have other names, they can be understood as the SMF of this application and are applicable to the method provided in this application. For example, the SMF can also be a communication awareness function, a positioning management function, an awareness management function entity, an awareness function network element, an awareness network element, an awareness server, a positioning server, or other names, and the name of the SMF is not limited in this application. The following embodiments mainly use the description of the SMF to introduce the execution operation of the functional network element.

[0118] FIG. 3-3 schematically shows a 5G network architecture based on a service interface. This application does not limit the specific structure of the 5G network. For example, the 5G network can include more or fewer network elements, and one or more network elements in FIG. 3-3 can be replaced by other network elements. This application does not limit the functions of the network elements in FIG. 3-3. The name and / or function of the network element may change as the communication system evolves.

[0119] The technical solutions of this application can be applied to a 3rd generation partnership project (3GPP) related cellular communication system. For example, a fourth generation (4G) communication system, a 5G communication system, a communication system after the fifth generation communication system. For example, a sixth generation communication system. For example, the fourth generation communication system can include a long term evolution (LTE) communication system. The fifth generation communication system can include a new radio (NR) communication system. The technical solutions of this application can also be applied to a wireless fidelity (WiFi) system, a communication system supporting multiple wireless technology fusion, a device-to-device (D2D) system, or a V2X communication system.

[0120] The terminal device, the access network device, the awareness management function, and the positioning management function related in this application are introduced as follows.

[0121] A terminal device, also referred to as a user equipment (UE), a mobile station (MS), a mobile terminal (MT), a fixed wireless access (FWA), a customer premise equipment (CPE), etc. A terminal device is a device including a wireless communication function (providing voice / data connectivity to a user). For example, a handheld device having a wireless connection function, a vehicle-mounted device, an MTC terminal, etc. Currently, a terminal device can include a mobile phone, a tablet computer, a notebook computer, a palm computer, a mobile internet device (MID), a wearable device, a virtual reality (VR) device, an augmented reality (AR) device, a wireless terminal in industrial control, a wireless terminal in self driving (e.g., a drone, a vehicle), a wireless terminal in remote medical surgery, a wireless terminal in a smart grid, a wireless terminal in transportation safety, a wireless terminal in a smart city, or a wireless terminal in a smart home, etc. For example, a wireless terminal in self driving can be a drone, a helicopter, or an airplane, etc. For example, a wireless terminal in vehicle networking can be a vehicle-mounted device, a whole-vehicle device, a vehicle-mounted module, a vehicle, or a ship, etc. A wireless terminal in industrial control can be a camera, a robot, or a mechanical arm, etc. A wireless terminal in a smart home can be a television, an air conditioner, a sweeping machine, a sound box, or a set-top box, etc. A terminal device can also be a device or a module with a corresponding communication function accessing the above-illustrated communication system. A terminal device is usually provided with a communication module, a circuit or a chip for performing a corresponding communication function, and is also configured with program instructions for performing a corresponding communication function. Hereinafter, the terminal device is taken as an example of UE.

[0122] It should be noted that the UE can be a device or apparatus with a chip, or a device or apparatus integrated with a circuit, or a chip, a chip system, a module or a control unit in the above-illustrated device or apparatus, which is not limited in the present application. It should be noted that in the present application, when referring to the UE, it can refer to the UE itself, or a chip, a functional module or an integrated circuit in the UE for completing the method provided in the present application, which is not limited in the present application.

[0123] An access network device is a kind of device deployed in a wireless access network to provide wireless communication function for a UE. The access network device can access the UE to a radio access network (RAN) node of a wireless network, which can also be referred to as a wireless access device, an access network device, a RAN entity, an access node, a network node, or a communication device, etc.

[0124] Specifically, the access network device can be an access network device for a 3GPP related cellular system. For example, a 4G communication system, or a 5G communication system. The access network device can also be an access network device in an open access network (open RAN, O-RAN or ORAN) or a cloud radio access network (CRAN). Alternatively, the access network device can also be an access network device in a communication system obtained by fusing two or more of the above communication systems.

[0125] The access network device includes, but is not limited to, an evolved Node B (eNB), an RNC, a Node B (NB), a base station controller (BSC), a base transceiver station (BTS), a home base station (for example, a home evolved Node B, or home Node B, HNB), a baseband unit (BBU), an access point (AP) in a wireless fidelity (WiFi) system, a macro base station, a micro base station, a wireless relay node, a donor node, a wireless controller in a CRAN scenario, a wireless backhaul node, a transmission point (TP), or a transmission and reception point (TRP), and the like, and can also be an access network device in a 5G mobile communication system. For example, a next generation Node B (gNB) in an NR system, a TRP, a TP, or one or a group (including multiple antenna panels) of antenna panels of a base station in a 5G mobile communication system; or the access network device can also be a network node constituting a gNB or a transmission point. For example, a centralized unit (CU), a distributed unit (DU), a centralized unit control plane (CU-CP), a centralized unit user plane (CU-UP), or a radio unit (RU), and the like. The CU and the DU can be separately arranged or can be included in the same network element, for example, a BBU. The RU can be included in a radio frequency device or a radio frequency unit. For example, in a remote radio unit (RRU), an active antenna unit (AAU), or a remote radio head (RRH). Or the access network device can also be a server, a wearable device, a vehicle or a vehicle-mounted device, and the like. For example, the access network device in V2X technology can be a road side unit (RSU). It should be understood that the above-mentioned TRP can be a device or module located at the network side of the above-mentioned communication system and having corresponding communication functions. The TRP is usually provided with a communication module, circuit, or chip for performing corresponding communication functions. The TRP is also configured with program instructions for corresponding communication functions.

[0126] It should be noted that the CU (or CU-CP and CU-UP), DU or RU can also have different names in different systems, but those skilled in the art can understand their meanings. For example, in an open radio access network (ORAN) system, the CU can also be referred to as an open centralized unit (O-CU) or an open CU, the DU can also be referred to as an open distributed unit (O-DU), the CU-CP can also be referred to as an open centralized unit control plane (O-CU-CP), the CU-UP can also be referred to as an open centralized unit user plane (O-CU-UP), and the RU can also be referred to as an open radio unit (O-RU). The specific application is not limited. Any one of the CU, CU-CP, CU-UP, DU and RU in the present application can be realized by a software module, a hardware module, or a combination of a software module and a hardware module.

[0127] Optionally, for network elements in the ORAN system, each network element can implement the protocol layer functions shown in Table 1 below.

[0128] Table 1

[0129] It should be noted that in the ORAN system, the access network device in the present application can be one or more network elements in Table 1 above.

[0130] The architecture of the CU and the DU of the access network device will be introduced below. The access network device includes at least one CU and at least one DU. Optionally, the access network device also includes at least one RU.

[0131] The following is introduced by taking an access network device including one CU and one DU as an example. The CU has part of the function of the core network, and the CU can include a CU-CP and a CU-UP. The CU and the DU can be configured according to the protocol layer function of the wireless network they implement. For example, the CU is configured to implement the function of the packet data convergence protocol (PDCP) layer and the protocol layer above (for example, the function of the RRC layer and / or the SDAP layer). The DU is configured to implement the function of the protocol layer below the PDCP layer (for example, the function of the RLC layer, the MAC layer, and / or the physical (PHY) layer). For another example, the CU is configured to implement the function of the protocol layer above the PDCP layer (for example, the function of the RRC layer and / or the SDAP layer), and the DU is configured to implement the function of the protocol layer below the PDCP layer (for example, the function of the RLC layer, the MAC layer, and / or the PHY layer, etc.).

[0132] When the CU includes the CU-CP and the CU-UP, the CU-CP is used to implement the control plane function of the CU, and the CU-UP is used to implement the user plane function of the CU. For example, when the CU is configured to implement the function of the PDCP layer, the RRC layer, and the SDAP layer, the CU-CP is used to implement the function of the RRC layer and the control plane function of the PDCP layer, and the CU-UP is used to implement the function of the SDAP layer and the user plane function of the PDCP layer.

[0133] The CU-CP can interact with a network element in the core network for implementing the control plane function. The network element in the core network for implementing the control plane function can be an access and mobility function network element, for example, an AMF in a 5G system. The AMF is used to be responsible for the mobility management in the mobile network, such as the location update of the UE, the registration network of the UE, the handover of the UE, etc.

[0134] The CU-UP can interact with a network element in the core network for implementing the user plane function. The network element in the core network for implementing the user plane function, for example, a user function (UPF) in a 5G system, is used to be responsible for the forwarding and receiving of data in the UE.

[0135] The configuration of the above CU and DU is merely an example, and the CU and DU can be configured to have functions as needed. For example, the CU or the DU can be configured to have functions of more protocol layers, or the CU or the DU can be configured to have partial processing functions of the protocol layers. For example, partial functions of the RLC layer and functions of protocol layers above the RLC layer are arranged in the CU, and the remaining functions of the RLC layer and functions of protocol layers below the RLC layer are arranged in the DU. For another example, the functions of the CU or the DU can be divided according to a service type or other system requirements. For example, according to a delay, functions that need to meet a relatively low delay requirement are arranged in the DU, and functions that do not need to meet the delay requirement are arranged in the CU.

[0136] The DU and the RU can cooperate to jointly implement the functions of the PHY layer. One DU can be connected to one or more RUs. The functions of the DU and the RU can be configured in various ways according to design. For example, the DU is configured to implement baseband functions, and the RU is configured to implement intermediate radio frequency functions. For another example, the DU is configured to implement high-layer functions in the PHY layer, and the RU is configured to implement low-layer functions in the PHY layer or to implement the low-layer functions and radio frequency functions. The high-layer functions in the PHY layer can include a part of functions of the PHY layer that are closer to the MAC layer, and the low-layer functions in the PHY layer can include another part of functions of the PHY layer that are closer to the intermediate radio frequency side.

[0137] It should be noted that the access network device can be a device or apparatus with a chip, or a device or apparatus integrated with a circuit, or a chip, a chip system, a module, or a control unit in the foregoing devices or apparatus, and the specific application is not limited. It should be noted that in the present application, when referring to the access network device, it can refer to the access network device itself, or refer to a chip, a functional module, or an integrated circuit in the access network device that completes the method provided in the present application, and the specific application is not limited.

[0138] Hereinafter, the access network device is taken as an example of a gNB.

[0139] AMF: Access and Mobility Management Function, mainly responsible for user registration, reachability, mobility management, N1 / N2 interface signaling transmission, access authentication and authorization, etc.

[0140] NRF: Network Repository Function, provides the registration and discovery capabilities of network elements in the network.

[0141] NWDAF: It has data collection, training, analysis, and inference functions, can be used to collect relevant data from network elements, third-party service servers, terminal devices or network management systems, analyze and train based on relevant data, and provide data analysis results to network elements, third-party service servers, terminal devices or network management systems. The analysis results can assist the network in selecting service quality parameters for services, or assist the network in performing traffic routing, or assist the network in selecting background data transmission strategies, etc.

[0142] Traditional wireless positioning algorithms (e.g. DL-TDOA, DL-AOD, UL-TDOA, UL-AOA, etc.) have poor positioning accuracy in some scenarios, which cannot meet the demand of high-precision positioning. For example, traditional positioning algorithms generally need at least 3 path measurement information to estimate the position, but in a severe non-line-of-sight (NLOS) environment, it is almost impossible to find at least 3 line-of-sight (LOS) paths that can be used to calculate the position at the same time, which will lead to stronger NLOS paths being mistaken for LOS paths, and the measurement signal of NLOS paths is poor, resulting in poor positioning accuracy of traditional algorithms. Or in a light / medium NLOS environment, the number of LOS paths is sufficient, but LOS path misjudgment may also occur, resulting in poor positioning accuracy of traditional algorithms.

[0143] In order to solve the problem of poor accuracy of traditional positioning algorithms in NLOS environment, for example, in LOS or NLOS scenarios, AI-based positioning can improve positioning accuracy with a smaller number of TRP antennas. Positioning enhancement can include at least one sub-function, such as: access network device-based positioning enhancement, positioning management function network element-based positioning enhancement, and UE-based positioning enhancement. Since the AI model discussed in this application is used in a positioning scenario, the AI model mentioned in this application can refer to an AI positioning model. Currently, multiple AI positioning scenarios are discussed in 3GPP standards, and this application mainly considers the scenario where the AI / ML model is located in the LMF, or in other words, the AI model mentioned in this application can be specifically an AI / ML model.

[0144] According to the different output results of the AI / ML model, this positioning scenario also includes two categories. One is A-AIML, that is, the output result of the AI / ML model is the positioning intermediate information, such as the LOS / NLOS probability of the path, or the TOA estimate of the path, etc. After the LMF obtains the positioning intermediate information, it still needs to estimate the UE position based on the positioning intermediate information and the traditional positioning algorithm. The other is D-AIML, that is, the output result of the AI / ML model is the estimated UE position or the UE position estimation result. Hereinafter, the AI model is taken as an example of the D-AIML model, that is, the processing result of the AI model for the input data is the position of the UE.

[0145] The input data (or inference data) of the AI model in the process of AI model inference generally includes the measurement data reported by the UE / gNB. According to the type of measurement data and the source of data, this positioning scenario is further divided into positioning scenario 1 (or downlink positioning scenario) and positioning scenario 2 (or uplink positioning scenario). The difference between the two is that the measurement data used by the AI model and the data source of the measurement data are different. As shown in FIG. 4-1, in the positioning scenario 1, the measurement data can be the measurement data obtained by the UE measuring the PRS signal (referred to as PRS measurement data), and the data source is the UE. As shown in FIG. 4-2, in the positioning scenario 2, the measurement data can be the measurement data obtained by the gNB measuring the SRS signal (referred to as SRS measurement data), and the data source is the gNB. The same point of the two is that the LMF can perform inference on the collected measurement data based on the local AI model to obtain the inference result, for example, the estimation result of the UE position.

[0146] The AI model can be pre-configured to the LMF, for example, configured at the factory or network management, or the AI model can be trained by the LMF or other network elements. According to the network element that performs the training, this positioning scenario also includes two types. One type is trained by the LMF itself. The LMF performs AI positioning based on the trained AI model and the collected data. In order to facilitate the distinction, hereinafter the data used for training the AI model or the input data of the AI model in the process of training the AI model is referred to as the training data of the AI model. The other type is that the AI model is obtained by the LMF from other network elements, for example, from the NWDAF or the MTLF in the NWDAF. The 5G network introduces the NWDAF network element, which is divided into MTLF and AnLF. The MTLF can collect data in the network and train the AI / ML model based on the data, and can provide the trained model to the AnLF based on the request of the AnLF. The AnLF can perform data statistics and inference, or perform model inference based on the AI / ML model, and derive the corresponding analysis result according to the request of the consumer (such as AMF / SMF / PCF, etc.), and open the analysis result to the consumer. In the scenario where the LMF obtains the AI model from the MTLF, the MTLF can obtain the training data of the AI model from the LMF, train the AI model using the data, and then send the trained AI model to the LMF, and the LMF performs AI positioning based on the AI model and the inference data.

[0147] That is, whether the AI model is trained by the LMF or the MTLF, the LMF needs to collect the training data of the AI model. If the LMF trains the AI model itself, the LMF collects the training data of the AI model itself, and if the MTLF trains the model, the MTLF also needs to collect the training data through the LMF.

[0148] For convenience of description, hereinafter, the network element for requesting the LMF to provide the training data of the AI model is referred to as an AI training data consumer (MTLF or NWDAF), the network element for requesting the LMF to provide the AI positioning result is referred to as an AI inference result consumer (e.g., AMF / SMF / PCF, etc.), and the AI training data consumer and the AI inference result consumer are collectively referred to as an AI consumer. The present application does not limit the types of the AI training data consumer and the AI inference result consumer, and hereinafter, the AI training data consumer is taken as the MTLF, and the AI inference result consumer is taken as the AMF as an example.

[0149] The training data of the AI model can include not only the measurement data reported by the UE / gNB, but also a label corresponding to the measurement data, such as the estimated UE position based on the measurement data. Correspondingly, the training data of the AI model collected by the LMF from the UE / gNB can include not only the measurement data, but also the label (i.e., the UE position). In the downlink positioning scenario, the LMF can collect the training data from the UE through the LPP protocol, and in the uplink positioning scenario, the LMF can collect the training data from the gNB through the NRPPa protocol.

[0150] In the present application, the measurement data for the AI model can include the inference data of the AI model, and / or the training data of the AI model. As introduced above, the training data of the AI model can include not only the measurement data reported by the UE / gNB, but also a label corresponding to the measurement data. The measurement data for the AI model including the training data of the AI model can refer to including all or part of the training data, for example, including the measurement data reported by the UE / gNB and the label corresponding to the measurement data, or including the measurement data reported by the UE / gNB. The measurement data for the AI model is also referred to as data for the AI model, AI (measurement) data, (measurement) data for AI positioning, or measurement data, etc. For convenience of distinction, hereinafter, the measurement data reported by the UE / gNB in the training data of the AI model is referred to as AI (measurement) data of the UE / gNB. In actual application, the measurement data reported by the UE / gNB in the training data of the AI model can be referred to as measurement data for the AI model, data for the AI model, AI (measurement) data, (measurement) data for AI positioning, or (measurement) data for AI positioning, or measurement data, etc.

[0151] However, whether it is the positioning scenario 1 or the positioning scenario 2, the measurement data required by the LMF to be collected for the AI model is different from the measurement data required by the LMF to be collected when using the traditional wireless positioning algorithm.

[0152] For example, the data required to be collected for DL-TDOA positioning method includes DL RSTD and DL PRS RSRP, the data required to be collected for UL-TDOA positioning method includes UL RTOA and UL SRS-RSRP, the data required to be collected for UL-AoA includes UL AoA / ZoA (UL SRS-RSRP). The data required to be collected for AI model of positioning scenario 1 can include DL-CIR and DL-channel power delay profile (PDP). The data required to be collected for AI model of positioning scenario 2 can include UL-CIR and UL-PDP.

[0153] Therefore, it is necessary to enhance the UE / gNB to support providing the measurement data for the AI model. However, in practice, not all UEs / gNBs are enhanced, and therefore, there can be no enhanced UE / gNB in the service area of the LMF, or part of the UEs / gNBs in the service area of the LMF are enhanced and the others are not enhanced. For the UE / gNB that is not enhanced, the UE / gNB cannot return the corresponding data after the LMF requests the UE / gNB to provide the measurement data for the AI model, and for the enhanced UE / gNB, the UE / gNB can return the corresponding data after the LMF requests the UE / gNB to provide the measurement data for the AI model.

[0154] However, it is not clear how the LMF determines whether a specific UE / gNB can support providing the measurement data for the AI model. The UE and the LMF can negotiate the supported capabilities through the LPP protocol, for example, the LMF requests the capabilities of the UE, and then the UE reports the supported capabilities. For example, currently, the UE can support the corresponding data measurement capabilities for different positioning methods. For example, for DL-TDOA, the capability information supported by the UE can include DL-TDOA positioning capability and / or DL-TDOA data measurement capability and / or DL-PRS-RSRP measurement capability. However, based on the data measurement capability reported by the existing UE, the LMF cannot determine whether a specific UE / gNB (for example, the UE / gNB in its own service area) can support providing the measurement data for the AI model.

[0155] If there is no enhanced UE / gNB in the service area of the LMF, when the LMF needs to collect the measurement data for the AI model, the LMF still requests each UE / gNB in the service area to collect the measurement data for the AI model. When the timer expires or all UE / gNBs fail to respond, the LMF can determine that there is no enhanced UE / gNB in its own service area, which not only wastes the processing resources of the LMF and the UE / gNB, but also occupies too many signaling resources.

[0156] In addition, when there is no enhanced UE / gNB in the service area of the LMF, the LMF cannot collect the measurement data for the AI model, and thus cannot use the AI model inference according to the request of the AMF, nor can it provide the training data of the AI model to the MTLF according to the request of the MTLF. In the existing scheme, the AI positioning capability of the LMF mainly refers to whether the LMF supports using the AI model to calculate the UE position, and does not consider whether the LMF can discover the UE / gNB supporting the AI capability and collect the measurement data from the UE / gNB supporting the AI capability. For example, even if the AMF discovers an LMF supporting AI positioning, because the LMF cannot collect the AI positioning related measurement data from the UE / gNB, the LMF still cannot use the AI positioning method to calculate the position of the UE.

[0157] However, it is currently unclear how the AMF or the MTLF determines whether a specific LMF is an enhanced LMF that can support providing the measurement data for the AI model. If the LMF cannot collect and / or provide the measurement data for the AI model, the AI consumer still sends a request to the LMF to request the LMF to perform the model processing operation related to collecting the measurement data for the AI model, which can easily cause the AI consumer to wait for a long time, waste the processing resources of the AI consumer and the LMF, and occupy too many signaling resources.

[0158] In order to facilitate the LMF to perceive whether there is an enhanced UE in its service area or whether a specific UE in its service area is an enhanced UE in the AI positioning scenario, the present application proposes that the AI capability information of the UE can be defined, and the AI capability information of the UE is used to indicate that the UE supports providing the measurement data for the AI model. The LMF can determine that there is an enhanced UE in its service area by obtaining the AI capability information of the UE, and the UE can provide the measurement data for the AI model to the LMF.

[0159] Similarly, in order to facilitate the LMF to perceive whether there is an enhanced gNB in its service area or whether a specific gNB in its service area is an enhanced gNB in the AI positioning scenario, the present application proposes that the AI capability information of the gNB can be defined, and the AI capability information of the gNB is used to indicate that the gNB supports providing the measurement data for the AI model. The LMF can determine that there is an enhanced gNB in its service area by receiving the AI capability information of the gNB, and the gNB can provide the measurement data for the AI model to the LMF.

[0160] To facilitate the AI consumer to perceive whether there is an enhanced LMF or to perceive whether a specific LMF is an enhanced LMF, the present application proposes that AI capability information of the LMF can be defined, the AI capability information of the LMF being used to indicate that the LMF supports providing measurement data for an AI model. The AI consumer (such as an AMF or an MTLF) can determine that there is an enhanced LMF by receiving the AI capability information of the LMF, and the LMF can collect and / or provide measurement data for an AI model.

[0161] Hereinafter, an enhanced UE can refer to a UE supporting AI capability or a UE supporting providing measurement data for an AI model, an enhanced gNB can refer to a gNB supporting AI capability or a gNB supporting providing measurement data for an AI model, an enhanced LMF can refer to a LMF supporting AI capability or a LMF supporting providing measurement data for an AI model, AI capability information can refer to AI capability existence indication information, and in the communication method provided by the present application, AI capability can refer to AI positioning capability, and the two can be interchangeable. Correspondingly, AI capability information can refer to AI positioning capability information, and the two can be interchangeable.

[0162] The following describes several possible method examples based on the concept of the present application.

[0163] FIG. 5 schematically shows a possible flow of a communication method provided by the present application. As shown in FIG. 5, the communication method provided by the present application can include a UE AI capability information association flow, which can include S501a-S505a. The UE AI capability information association flow shown in FIG. 5 can be a first method example for an LMF to perceive an enhanced UE.

[0164] S501a, the UE sends information 1-1 to the AMF, and correspondingly, the AMF receives the information 1-1 sent by the UE;

[0165] The information 1-1 can include UE AI capability information, and the UE AI capability information is used to indicate that the UE supports providing measurement data for an AI model. Optionally, the information 1-1 can be a UL NAS message or be carried in a UL NAS message.

[0166] The information 1-1 can include a first identifier of the LMF and an AI capability association request, and the AI capability association request can include the UE AI capability information.

[0167] Optionally, the AI capability information of the UE is used to indicate the type of AI capability supported by the UE, for example, the AI capability information of the UE is used to indicate that the UE supports AI downlink positioning capability, or in other words, supports AI downlink data measurement capability, or in other words, supports providing AI downlink measurement data.

[0168] Optionally, the AI capability information of the UE is used to indicate the type of measurement data supported by the UE. For example, the AI capability information of the UE can indicate that the UE supports providing CIR measurement data and / or PDP measurement data.

[0169] Optionally, the AI capability association request can also include an association reason, which can be initial AI capability information of the UE or AI capability information update of the UE, etc.

[0170] S502a, the AMF verifies the AI capability information of the UE;

[0171] After the AMF receives information 1-1, it can verify whether the UE really supports AI capability, that is, whether it supports providing measurement data for AI model. As introduced in the foregoing, the AI model mentioned in the present application can refer to AI positioning model or D-AIML model.

[0172] The present application does not limit the way in which the AMF verifies whether the UE really supports AI capability. For example, the AMF can obtain the subscription information of the UE from the UDM to check whether the UE supports AI capability, or the AMF can determine whether the UE supports AI capability based on the configured local policy.

[0173] In actual application, the UDM can be replaced by UDR or other network element, as long as the network element can be used to provide a service of saving the subscription information of the UE and / or gNB.

[0174] S503a, the AMF sends information 1-2 to the LMF, and correspondingly, the LMF receives the information 1-2 sent by the AMF;

[0175] The AMF can send information 1-2 to the LMF, and the information 1-2 includes the AI capability information of the UE or the AI capability association request.

[0176] Optionally, the information 1-2 also includes the ID (such as SUPI) of the UE, so that the LMF determines the UE supporting AI capability.

[0177] Optionally, the information 1-2 also includes the location information of the UE. The present application does not limit the type of location information of the UE, for example, the location information of the UE can include TAI and / or cell ID.

[0178] Step S502a is an optional step. After receiving information 1-1, the AMF can send information 1-2 to the LMF without verifying whether the UE actually supports the AI capability. Based on performing S502a, the AMF can send information 1-2 to the LMF in the case of verification pass (i.e., the UE supports the AI capability).

[0179] S504a, the LMF sends information 1-3 to the AMF;

[0180] After receiving information 1-2, the LMF can determine that the UE supports the AI capability based on the AI capability information of the UE in information 1-2.

[0181] The LMF can save the AI capability information of the UE in information 1-2, and can also save some or all of other information. For example, the LMF can also save the UE ID and / or the location information of the UE in association with the AI capability information of the UE.

[0182] The LMF can also send information 1-3 to the AMF, and information 1-3 can be a response message of information 1-2. Information 1-3 can include association result information, which can be used to indicate that the LMF accepts the AI capability association request of the UE (AI capability association accept) or rejects the AI capability association request of the UE (AI capability association reject).

[0183] Information 1-3 can also include a second identifier of the LMF.

[0184] S505a, the AMF sends information 1-4 to the UE, and correspondingly, the UE receives information 1-4 sent by the AMF;

[0185] After receiving information 1-3 sent by the LMF, the AMF can send information 1-4 to the UE, and information 1-4 can include the association result information in information 1-3 and the first identifier of the LMF. Optionally, information 1-4 can be a DL NAS message or be carried in a DL NAS message.

[0186] S504a-S505a are optional steps.

[0187] The first identifier of the LMF in information 1-1 is used to indicate that the AMF sends information 1-1 to the LMF to deliver the AI capability information of the UE to the LMF. The present application does not limit the way in which the UE transmits the AI capability information of the UE to the LMF, nor does it limit that information 1-1 must carry the first identifier of the LMF, as long as the UE can deliver its AI capability information to the LMF. For example, the UE can forward its AI capability information to the LMF through other network elements. Alternatively, the UE can directly send its own AI capability information to the LMF, and accordingly, information 1-1 can be information 1-2.

[0188] The ID of the UE in information 1-2 is used to indicate that the LMF determines the UE supporting AI capability. The present application does not limit the way in which the LMF determines the UE.

[0189] The location information of the UE in information 1-2 is used to indicate the location of the UE supporting AI capability determined by the LMF. In this way, the LMF can not only determine that there is a UE supporting AI capability in its service area, but also determine the location of the UE supporting AI capability, which is conducive to more accurately determining the enhanced UE sub-area in the service area of the LMF according to the location of the UE supporting AI capability, that is, the LMF supports providing the measurement results for AI model reported by the UE in the sub-area.

[0190] With reference to FIG. 5, the communication method provided by the present application can include an AI capability information association process of the gNB, which can include S501b-S505b. The AI capability information association process of the gNB shown in FIG. 5 can be an example of the first method for the LMF to perceive the enhanced gNB.

[0191] S501b, the gNB sends information 1-5 to the AMF, and accordingly, the AMF receives information 1-5 sent by the gNB;

[0192] S502b, the AMF verifies the AI capability information of the gNB;

[0193] S503b, the AMF sends information 1-6 to the LMF;

[0194] S504b, the LMF sends information 1-7 to the AMF;

[0195] S505b, the AMF sends information 1-8 to the gNB;

[0196] S501b-S505b can be understood in sequence with reference to the content of S501a-S505a. For example, S501b can be understood with reference to the content after replacing the UE in S501a with a gNB, S502b can be understood with reference to the content after replacing the UE in S502a with a gNB, S503b can be understood with reference to the content after replacing the UE in S503a with a gNB, S504b can be understood with reference to the content after replacing the UE in S504a with a gNB, and S505b can be understood with reference to the content after replacing the UE in S505a with a gNB. For example, information 1-5 can be understood with reference to information 1-1, information 1-6 can be understood with reference to information 1-2, information 1-7 can be understood with reference to information 1-3, and information 1-8 can be understood with reference to information 1-4.

[0197] After the LMF receives the AI capability information of the UE and / or the AI capability information of the gNB, the LMF can determine that it supports the AI capability. Optionally, with reference to FIG. 5, the communication method provided in the present application can further include a process in which the LMF registers its AI capability information, and the process in which the LMF registers its AI capability information can include S506-S507.

[0198] S506, the LMF sends information 1-9 to the NRF, and correspondingly, the NRF receives the information 1-9 sent by the LMF.

[0199] Based on the AI capability information of the UE and / or the AI capability information of the gNB received by the LMF, the LMF can determine that it supports the AI capability. The LMF can send information 1-9 to the NRF. Information 1-9 can include the AI capability information of the LMF.

[0200] Optionally, based on the successful association of the AI capability information of the LMF and the UE and / or the AI capability information of the gNB, the LMF can further register its AI capability information in the NRF. Information 1-9 can be a registration request message sent by the LMF to the NRF or carried in the registration request message.

[0201] Optionally, information 1-9 further includes location information associated with the AI capability information of the LMF, and the location information indicates that the LMF has the AI capability in the location or area indicated by the location information. The LMF can determine the location information associated with the AI capability information of the LMF according to the location of the UE and / or the gNB in the service area that supports the AI capability.

[0202] The present application does not limit the type of the location information. For example, the location information can be TAI and / or cell ID.

[0203] In the present application, the AI capability information of the LMF can contain one or more of the following meanings: whether the LMF can provide AI measurement data; whether the LMF can collect AI data from the UE, or in other words, whether the LMF can provide AI measurement data on the UE side; whether the LMF can collect AI measurement data from the gNB, or in other words, whether the LMF can provide AI measurement data on the gNB side.

[0204] S507, the NRF sends information 1-10 to the LMF, and correspondingly, the LMF receives the information 1-10 sent by the NRF.

[0205] After receiving the information 1-9, the NRF can save the AI capability information of the LMF, and can also save part or all of the information in the information 1-9. For example, the NRF can also save the location information associated with the AI capability information of the LMF.

[0206] Optionally, the NRF can also send information 1-10 to the LMF. The information 1-10 can be a registration response message of the information 1-9 or carry information in the message to indicate whether the LMF is successfully registered.

[0207] After the LMF registers its AI capability information, it is beneficial for AI consumers (such as AMF or MTLF) to determine that the LMF is an enhanced LMF that supports collecting and / or providing measurement data for AI models by querying the registration information of the LMF.

[0208] FIG. 6-1 schematically shows another possible flow of the communication method provided by the present application. As shown in FIG. 6-1, the communication method provided by the present application can include an AI capability information acquisition process of the UE, which can include S601a-S602a. The AI capability information acquisition process of the UE shown in FIG. 6-1 can be an example of the second method for the LMF to perceive an enhanced UE.

[0209] S601a, the LMF sends information 2-1 to the UE, and correspondingly, the UE receives the information 2-1 sent by the LMF;

[0210] The information 2-1 can be used to request the AI capability information of the UE. The LMF can send the information 2-1 to the UE through the LPP protocol. The information 2-1 can be a capability request message or carried in a capability request message.

[0211] The information 2-1 can also be used to indicate the type of AI capability required or requested, or to indicate the type of measurement data required or requested. For example, the information 2-1 can include a field 1, which can be “NR-DL-AI Positioning-ProvideCapabilities-r19”, and the field 1 is used to indicate the AI downlink positioning capability requested. For example, the information 2-1 can include a field 2, which can be “NR-DL-AI Positioning-MeasurementCapability-r19”, and the field 2 is used to indicate the AI downlink positioning data measurement capability requested. For example, the information 2-1 can include a field 3, which can be “supportOfDL-CIR-MeasFR1-r19”, and the field 3 is used to request the downlink CIR measurement capability. For example, the information 2-1 can include a field 4, which can be “supportOfDL-PDP-MeasFR1-r19”, and the field 4 is used to request the downlink PDP measurement capability.

[0212] S602a, the UE sends information 2-2 to the LMF, and correspondingly, the LMF receives the information 2-2 sent by the UE.

[0213] After receiving the information 2-1, the UE can send information 2-2 to the LMF. The information 2-2 can include the AI capability information of the UE. The UE can send the information 2-2 to the LMF through the LPP protocol. The information 2-2 can be a response message of the information 2-1.

[0214] Optionally, the AI capability information of the UE is used to indicate that the UE supports the type of measurement data provided. For example, the AI capability information of the UE can indicate that the UE supports providing CIR measurement data and / or PDP measurement data.

[0215] The AI capability or the type of measurement data indicated by the AI capability information of the UE in the information 2-1 can be all or part of the types indicated in the information 2-1, and the AI capability information of the UE in the information 2-1 does not indicate that the UE supports the AI capability or the type of data not requested in the information 2-1. For example, the information 2-1 is used to request the downlink PDP measurement capability, and even if the UE supports providing CIR measurement data, the information 2-2 can not indicate that the UE supports providing CIR measurement data. Optionally, the information 2-1 can also indicate that the UE does not support the AI capability, or indicate the type of AI capability not supported.

[0216] Taking the information 2-1 including the above-mentioned fields 1 to 4 as an example, the information 2-2 can be as follows.

[0217] -->ProvideCapabilities

[0218] --> AI downlink positioning capability (NR-DL-AI Positioning-ProvideCapabilities-r19)

[0219] --> AI downlink data measurement capability (NR-DL-AI Positioning-MeasurementCapability-r19)

[0220] --> Downlink CIR measurement capability (supportOfDL-CIR-MeasFR1-r19)

[0221] --> Downlink PDP measurement capability (supportOfDL-PDP-MeasFR1-r19)

[0222] The present application does not limit the manner in which information 2-2 indicates the AI capability information of the UE, for example, taking field 1 as an example, information 2-2 can indicate that the UE supports the AI capability requested by field 1 by carrying field 1, or information 2-2 can indicate whether the UE supports the AI capability requested by field 1 through the corresponding value of field 1.

[0223] S601a is an optional step, in some examples, the UE can directly send information 2-2 to the LMF.

[0224] With reference to FIG. 6-1, the communication method provided by the present application can include an AI capability information acquisition process of the gNB, which can include S601b-S602b. The AI capability information acquisition process of the gNB shown in FIG. 6-1 can be an example of the second method for the LMF to perceive the enhanced gNB.

[0225] S601b, the LMF sends information 2-3 to the gNB, and correspondingly, the gNB receives the information 2-3 sent by the LMF;

[0226] Information 2-3 can be used to request the AI capability information of the gNB. For example, the LMF can send information 2-3 to the gNB through the NRPPa protocol. Information 2-3 can be a capability request message or carried in a capability request message.

[0227] The information 2-3 can also be used to indicate the type of AI capability required or requested, or to indicate the type of measurement data required or requested. For example, the information 2-3 can include a field 5, which can be "NR-UL-AI Positioning-ProvideCapabilities-r19", and the field 5 is used to indicate the AI uplink positioning capability requested. For example, the information 2-3 can include a field 6, which can be "NR-UL-AI Positioning-MeasurementCapability-r19", and the field 6 is used to indicate the AI uplink positioning data measurement capability requested. For example, the information 2-3 can include a field 7, which can be "support Of UL-CIR-MeasFR1-r19", and the field 7 is used to request the uplink CIR measurement capability. For example, the information 2-3 can include a field 8, which can be "supportOfUL-PDP-MeasFR1-r19", and the field 8 is used to request the uplink PDP measurement capability.

[0228] S602b, the gNB sends information 2-4 to the LMF, and correspondingly, the LMF receives the information 2-4 sent by the gNB.

[0229] After receiving the information 2-3, the gNB can send information 2-4 to the LMF. The information 2-4 can include the AI capability information of the gNB. The gNB can send the information 2-4 to the LMF through the NRPPa protocol. The information 2-4 can be a response message of the information 2-3.

[0230] Optionally, the AI capability information of the gNB is used to indicate the type of measurement data supported by the gNB to provide. For example, the AI capability information of the gNB can indicate that the gNB supports to provide CIR measurement data and / or PDP measurement data.

[0231] The AI capability or the type of measurement data indicated by the AI capability information of the gNB in the information 2-4 can be all or part of the types indicated by the information 2-3, and the AI capability information of the gNB in the information 2-4 does not indicate that the gNB supports the AI capability or the type of data not requested by the information 2-3. For example, the information 2-3 is used to request the downlink PDP measurement capability, and even if the gNB supports to provide CIR measurement data, the information 2-4 can not indicate that the gNB supports to provide CIR measurement data. Optionally, the information 2-4 can also indicate that the gNB does not support the AI capability, or indicate the type of AI capability not supported.

[0232] Taking the information 2-3 including the above-mentioned fields 5 to 8 as an example, the information 2-4 can be as follows.

[0233] --> Provide Capabilities (ProvideCapabilities)

[0234] --> AI Uplink Positioning Capabilities (NR-UL-AI Positioning-ProvideCapabilities-r19)

[0235] --> AI Uplink Data Measurement Capabilities (NR-UL-AI Positioning-MeasurementCapability-r19)

[0236] --> Uplink CIR Measurement Capabilities (supportOfUL-CIR-MeasFR1-r19)

[0237] --> Uplink PDP Measurement Capabilities (supportOfUL-PDP-MeasFR1-r19)

[0238] The present application does not limit the way information 2-4 indicates the AI capability information of the gNB, for example, taking field 5 as an example, information 2-4 can indicate that the gNB supports the AI capability requested by field 5 by carrying field 5, or information 2-4 can indicate whether the gNB supports the AI capability requested by field 5 through the corresponding value of field 5.

[0239] S601b is an optional step, in some examples, the gNB can directly send information 2-4 to the LMF.

[0240] In FIG. 6-1, the LMF actively triggers the request of AI positioning related capabilities to the UE / gNB through the LPP / NRPPa protocol, so that the LMF can know whether AI measurement data can be collected from the UE / gNB to perform AI positioning. In the prior art, the LMF cannot know whether AI measurement data can be collected from the UE / gNB, so the LMF cannot determine whether AI positioning can be normally performed. The present application triggers the acquisition of AI positioning capability information of the UE / gNB by the LMF, so that the LMF can determine whether AI positioning can be performed.

[0241] After the LMF receives the AI capability information of the UE and / or the AI capability information of the gNB, for example, after S602a and / or S602b, the LMF can determine that it supports AI capability. Optionally, continuing to refer to FIG. 6-1, the communication method provided by the present application can include the process of the LMF registering its own AI capability information, and the process of the LMF registering its own AI capability information can include S603a-S604a.

[0242] S603a, the LMF sends information 2-5 to the NRF;

[0243] S604a, the NRF sends information 2-6 to the LMF;

[0244] S603a and S604a can refer to the related content of S506 and S507 respectively, and information 2-5 and information 2-6 refer to information 1-9 and information 1-10 respectively, which will not be repeated here.

[0245] After the LMF registers its AI capability information, it is beneficial for AI consumers (such as AMF or MTLF) to determine that the LMF is an enhanced LMF by querying the registration information of the LMF, and the LMF supports collecting and / or providing measurement data for AI models.

[0246] FIG. 6-2 schematically shows another possible flow of the communication method provided by the present application. As shown in FIG. 6-2, the communication method provided by the present application can include an AI capability information acquisition procedure of the UE, which can include S601c-S602c. The AI capability information acquisition procedure of the UE shown in FIG. 6-2 can be an example of the third method for the LMF to perceive the enhanced UE.

[0247] S601c, the LMF sends information 3-1 to the UDM, and correspondingly, the UDM receives the information 3-1 sent by the LMF;

[0248] Information 3-1 can be used to request the subscription information of the UE. Optionally, before S601c, the LMF can obtain the IDs (or UE ID list) of one or more UEs in the service area of the LMF from the AMF, and then request the subscription information of one or more UEs in the UE ID list by sending information 3-1. The one or more UEs can be UEs in a certain specific area in the service area of the LMF, and the specific area can be, for example, an area applicable to the LMF-side AI positioning model.

[0249] Optionally, information 3-1 includes the IDs of one or more UEs in the UE ID list.

[0250] S602c, the UDM sends information 3-2 to the LMF, and correspondingly, the LMF receives the information 3-2 sent by the UDM;

[0251] After receiving information 3-1, the UDM can retrieve the subscription information of the UE indicated by information 3-1, and then send information 3-2 to the LMF. Information 3-2 can include all or part of the subscription information of the UE. Based on the fact that the subscription information of the UE includes the AI capability information of the UE, information 3-2 can include the AI capability information of the UE.

[0252] The LMF can optionally include an indication to obtain the UE AI capability information, in which case the UDM feeds back the AI capability information of the UE to the LMF if the UE supports the AI capability, or sends an indication indicating that the UE supports the AI capability; if the UE does not support the AI capability, feeds back a failure indication, or sends an indication indicating that the UE does not support the AI capability, or does not feed back anything.

[0253] After the LMF receives the information 3-2, the LMF can determine that the UE supports providing AI measurement data based on the AI capability information of the UE in the subscription information, or select a UE that supports providing AI measurement data from multiple UEs based on the subscription information of the multiple UEs.

[0254] With reference to FIG. 6-2, the communication method provided by the present application can include an AI capability information obtaining process of the gNB, which can include S601d-S602d. The AI capability information obtaining process of the gNB shown in FIG. 6-2 can be an example of the third method for the LMF to perceive the enhanced gNB.

[0255] S601d, the LMF sends information 3-3 to the UDM, and correspondingly, the UDM receives the information 3-3 sent by the LMF;

[0256] The information 3-3 can be used to request the subscription information of the gNB. Optionally, before S601d, the LMF can obtain the IDs of the gNBs (or a list of gNB IDs) in the service area of the LMF from the AMF, and then request the subscription information of one or more gNBs in the list of gNB IDs by sending the information 3-3.

[0257] Optionally, the information 3-3 includes the IDs of one or more gNBs in the list of gNB IDs.

[0258] S602d, the UDM sends information 3-4 to the LMF, and correspondingly, the LMF receives the information 3-4 sent by the UDM;

[0259] After the UDM receives the information 3-3, the UDM can retrieve the subscription information of the gNB indicated by the information 3-3, and then send the information 3-4 to the LMF. The information 3-4 can include all or part of the subscription information of the gNB. Based on the subscription information of the gNB including the AI capability information of the gNB, the information 3-4 can include the AI capability information of the gNB.

[0260] After the LMF receives the information 3-4, the LMF can determine that the gNB supports providing AI measurement data based on the AI capability information of the gNB in the subscription information, or select a gNB that supports providing AI measurement data from multiple gNBs based on the subscription information of the multiple gNBs.

[0261] Optionally, the information 3-1 and the information 3-3 can be carried in the same message. Similarly, the information 3-2 and the information 3-4 can be carried in the same message.

[0262] When the subscription information includes the AI capability information of the UE and / or the gNB, the LMF can determine itself as an enhanced LMF supporting collecting and / or providing the measurement data for the AI model. Optionally, with reference to FIG. 6-2, the communication method provided by the present application can include a procedure in which the LMF registers its AI capability information, and the procedure in which the LMF registers its AI capability information can include S603c-S604c.

[0263] S603c, the UDM sends information 3-5 to the NRF;

[0264] S604c, the NRF sends information 3-6 to the UDM;

[0265] S603c and S604c can refer to the related content of S506 and S507 respectively, and the information 3-5 and the information 3-6 refer to the information 1-9 and the information 1-10 respectively, which will not be repeated here.

[0266] Optionally, similar to the foregoing S506 and S507 or S603 and S604, after the LMF determines itself as an enhanced LMF, the LMF can register its AI capability information, and the AI capability information of the LMF is used to indicate that the LMF supports collecting and / or providing the measurement data for the AI model, so that it is beneficial for the AI consumer (such as the AMF or the MTLF) to determine the LMF as an enhanced LMF by querying the registration information of the LMF, and the LMF supports collecting and / or providing the measurement data for the AI model.

[0267] The communication method provided by the present application can include both the method procedure in which the LMF perceives the enhanced gNB and the method procedure in which the LMF perceives the enhanced UE. Alternatively, the communication method provided by the present application can include the method procedure in which the LMF perceives the enhanced gNB but not the method procedure in which the LMF perceives the enhanced UE. Alternatively, the communication method provided by the present application can include the method procedure in which the LMF perceives the enhanced UE but not the method procedure in which the LMF perceives the enhanced gNB.

[0268] The present application does not limit the specific method used by the LMF to perceive the enhanced UE, for example, the method used by the LMF to perceive the enhanced UE can refer to the AI capability information association process of the UE shown in FIG. 5 and / or the AI capability information acquisition process of the UE shown in FIG. 6-1 and / or the AI capability information acquisition process of the UE shown in FIG. 6-2. The present application does not limit the specific method used by the LMF to perceive the enhanced gNB, for example, the method used by the LMF to perceive the enhanced gNB can refer to the AI capability information association process of the gNB shown in FIG. 5 and / or the AI capability information acquisition process of the gNB shown in FIG. 6-1 and / or the AI capability information acquisition process of the gNB shown in FIG. 6-2.

[0269] The foregoing describes the method of the LMF to perceive the enhanced UE and the method of the LMF to perceive the enhanced gNB in conjunction with the processes shown in FIG. 5 and FIG. 6-1, respectively. The following describes an example of a communication method performed by the LMF to perceive the enhanced UE and / or the enhanced gNB in a communication system.

[0270] FIG. 7 schematically shows another possible process of a communication method provided by the present application. As shown in FIG. 7, the method can include S701-S704.

[0271] S701, the LMF determines a requirement related to collecting AI measurement data;

[0272] The requirement can be a requirement generated by the LMF, or a requirement proposed by other network elements to the LMF, for example, the LMF can determine the requirement based on receiving a request sent by other network elements. The possible types of requirements will be described later, which will not be expanded here.

[0273] S702, the LMF determines a measurement device that supports providing AI measurement data;

[0274] The measurement device can be a UE, or a gNB, or a UE and a gNB.

[0275] The present application does not limit the method flow of the LMF to determine the UE that supports providing AI measurement data, for example, the method flow can include the AI capability information association process of the UE shown in FIG. 5 and / or the AI capability information acquisition process of the UE shown in FIG. 6-1 and / or the AI capability information acquisition process of the UE shown in FIG. 6-2.

[0276] The present application does not limit the method flow of the LMF to determine the gNB that supports providing AI measurement data, for example, the method flow can include the AI capability information association process of the gNB shown in FIG. 5 and / or the AI capability information acquisition process of the gNB shown in FIG. 6-1 and / or the AI capability information acquisition process of the gNB shown in FIG. 6-2.

[0277] After S702, the LMF can acquire AI measurement data through S703a and / or S703b.

[0278] S703a, the LMF acquires AI measurement data from the UE supporting providing AI measurement data;

[0279] Based on the LMF determining the UE supporting providing AI measurement data, the LMF can collect measurement data from the UE, and the flow can refer to the flow shown in FIG. 8. As shown in FIG. 8, the detailed flow of S703a can include S801-S807.

[0280] S801, the LMF sends information 4-1 to the AMF;

[0281] The information 4-1 can be a downlink positioning message, used to instruct the UE to acquire AI measurement data. The UE is the UE determined by the LMF to support providing AI measurement data.

[0282] S802, the AMF establishes a signaling connection with the UE;

[0283] If the UE is in an idle state, the AMF triggers a service request flow to establish a signaling connection with the UE.

[0284] S803, the AMF sends information 4-2 to the UE;

[0285] The information 4-2 can be a DL NAS message, and the information 4-2 can be used to instruct the UE to collect and report AI measurement data.

[0286] S804, the UE performs positioning measurement;

[0287] The UE can perform positioning measurement or positioning processing based on the information 4-2, such as acquiring inference data and / or training data of the AI model. As introduced before, the training data of the AI model can include not only the measurement data of the UE on the downlink signal sent by the gNB, but also the UE position (i.e. label) calculated based on the measurement data.

[0288] S805, the UE establishes a signaling connection with the AMF;

[0289] If the UE enters an idle state after performing S804, the UE triggers a service request flow to establish a signaling connection with the AMF.

[0290] S806, the UE sends information 4-3 to the AMF;

[0291] The information 4-3 can be an UL NAS message, and the information 4-3 can include AI measurement data requested by the information 4-3.

[0292] S807, the AMF sends information 4-4 to the LMF;

[0293] The information 4-4 can be an uplink positioning message, and the information 4-4 can include AI measurement data received by the AMF from the UE.

[0294] In the drawings of the present application, the steps corresponding to the dashed lines are optional steps. As shown in FIG. 8, S802, S805-S807 are optional steps.

[0295] Alternatively, the process in which the LMF collects AI measurement data from the UE can refer to the process shown in FIG. 9.

[0296] S901, a user plane connection is established between the LMF and the UE, and the user plane message sent by the LMF to the UE includes information 5-1.

[0297] The LMF can send the information 5-1 to the UE through a user plane LPP message, and the information 5-1 is used to request the UE to collect and report AI measurement data.

[0298] S902a, the UE performs positioning processing.

[0299] The UE can perform positioning processing based on the information 5-1, such as obtaining inference data and / or training data of the AI model. The training data can include not only measurement data of the UE on the downlink signal sent by the gNB, but also the position of the UE (i.e., the label) calculated based on the measurement data.

[0300] S902b, the LMF performs positioning processing.

[0301] S902b is an optional step.

[0302] S903, the UE sends information 5-2 to the LMF through a user plane message.

[0303] The information 5-2 can include AI measurement data obtained by the UE based on the information 5-1. The UE can send the information 5-2 to the LMF through a user plane LPP message.

[0304] S703b, the LMF obtains AI measurement data from the gNB supporting providing AI measurement data.

[0305] Based on the determination of the LMF on the gNB supporting providing AI measurement data, the LMF can collect measurement data from the gNB, and the process can refer to the process shown in FIG. 10. As shown in FIG. 10, the detailed process of S703b can include S1001-S1006.

[0306] S1001, the LMF sends information 6-1 to the AMF.

[0307] The information 6-1 can be a network positioning message, and the information 6-1 is used to instruct to obtain AI measurement data from the gNB. The gNB is the gNB determined by the LMF to support providing AI measurement data.

[0308] S1002, the AMF establishes a signaling connection with the UE;

[0309] If the UE is in an idle state, the AMF triggers a service request procedure to establish a signaling connection with the UE. The UE can be a UE corresponding to a determined gNB.

[0310] S1003, the AMF sends information 6-2 to the gNB;

[0311] The information 6-2 can be a network positioning message, and the information 6-2 is used to instruct the gNB to collect and report AI measurement data. The AI measurement data can be measurement data of an uplink signal transmitted by the UE and measured by the gNB.

[0312] S1004, the gNB performs positioning measurement;

[0313] The gNB can perform positioning measurement based on the information 6-2, such as obtaining inference data and / or training data of an AI model. The training data can include, in addition to the measurement data of the uplink signal transmitted by the UE and measured by the gNB, a UE position (i.e., a label) calculated based on the measurement data.

[0314] S1005, the gNB sends information 6-3 to the AMF;

[0315] The information 6-3 can be a network positioning message, and the information 6-3 can be AI measurement data requested by the information 6-2.

[0316] S1006, the AMF sends information 6-4 to the LMF;

[0317] The information 6-4 can be a network positioning message, and the information 6-4 can include AI measurement data received by the AMF from the gNB.

[0318] S704, the LMF responds to the demand based on the collected AI measurement data;

[0319] After the LMF collects the AI measurement data, the LMF can respond to the demand based on the collected AI measurement data, such as training a local AI model, and / or using the local AI model to infer the collected AI measurement data (or performing AI positioning based on the AI model and the collected AI measurement data), and / or providing the collected AI measurement data to other network elements. The meaning of responding to the demand will be introduced in the following examples in combination with possible contents of the demand, which will not be introduced here.

[0320] The above steps S701 and S704 are optional steps.

[0321] The application does not limit the type of the requirement, nor the specific implementation of S701 and S704. In the following, the specific implementation of S701 and S704 will be described by way of example in connection with other examples of the communication method provided by the application.

[0322] In one possible example, the LMF can determine the requirement in S701 based on receiving a request of the MTLF.

[0323] FIG. 11 schematically shows another possible flow of the communication method provided by the application. As shown in FIG. 11, the method can include S1101-S1108.

[0324] S1101, the MTLF determines that AI measurement data needs to be collected;

[0325] In the case where the MTLF performs model training / inference, the MTLF determines that AI measurement data needs to be collected.

[0326] S1102, the MTLF sends information 7-1 to the NRF;

[0327] The information 7-1 can include indication information for indicating discovery of an LMF supporting providing AI measurement data, or for indicating discovery of an LMF capable of providing AI measurement data, or for indicating discovery of an LMF supporting AI capability. The indication information can be AI capability existence indication information.

[0328] The indication information can be used to indicate discovery of an LMF providing AI measurement data of a first type. The AI measurement data of the first type can include AI measurement data collected from a UE and / or AI measurement data collected from a gNB.

[0329] Alternatively, the indication information can be used to indicate discovery of an LMF supporting collection of AI measurement data, which can support collection of AI measurement data from a UE, or support collection of AI measurement data from a gNB, or support both collection of AI measurement data from a UE and collection of AI measurement data from a gNB.

[0330] Alternatively, the indication information can be used to indicate discovery of an LMF supporting collection of AI measurement data from a UE, which can support collection of AI measurement data from a gNB or not support collection of AI measurement data from a gNB.

[0331] Alternatively, the indication information can be used to indicate discovery of an LMF supporting collection of AI measurement data from a gNB, which can support collection of AI measurement data from a UE or not support collection of AI measurement data from a UE.

[0332] The information 7-1 can further include location information 7-1, which is used to indicate a first area, which can be an area included in a service area of the LMF discovered by the indication information. The location information 7-1 can be AOI information.

[0333] S1103, the NRF sends information 7-2 to the MTLF.

[0334] After receiving the information 7-1, the NRF can query or discover the LMFs that meet the conditions indicated by the information 7-1, or in other words, the LMFs discovered by the indication information 7-1. For example, the NRF can discover the LMFs whose service areas contain the first area and support collecting AI measurement data, and then send information 7-2 to the MTLF.

[0335] The information 7-2 can include information of the LMF discovered by the indication information 7-1. The information 7-2 can be a response message of the information 7-1. In this application, the information of the LMF can include the profile of the NF of the LMF, which can include one or more of the following information: the identity of the LMF, the address of the LMF, the AI capability information of the LMF, and the service area information of the LMF.

[0336] S1104, the MTLF sends information 7-3 to the LMF.

[0337] After receiving the information 7-2, the MTLF can determine the LMF that supports providing AI measurement data based on the information 7-2, and then send information 7-3 to the LMF. The information 7-3 can include request information, which is used to indicate providing or indicating obtaining AI measurement data.

[0338] The request information can also indicate the type of AI measurement data. For example, the request information can indicate providing data for training or inference of an AI model, or indicating providing AI (measurement) data of a UE / gNB, or indicating AI (measurement) data of a UE / gNB and a label, where the label can be the location of the UE. For example, the request information can indicate providing AI measurement data collected from a UE, or indicating providing AI measurement data collected from a gNB, or indicating providing AI measurement data collected from a UE and a gNB.

[0339] The information 7-3 can also include location information 7-3. The location information 7-3 is used to indicate a second area, which can be the range or area of the AI measurement data indicated by the request information to be obtained. In this application, the range of the AI measurement data can refer to the range or area where the measurement device providing the AI measurement data is located. The measurement device can be a UE and / or a gNB. The location information 7-3 can be the AoI of the AI model, or the ID of one or more cells.

[0340] S1105, the LMF determines a measurement device supporting providing AI measurement data;

[0341] After the LMF receives the information 7-3, the LMF can determine a measurement device supporting providing AI measurement data. Based on the information 7-3 further comprising the location information 7-3, the measurement device determined by the LMF is used to collect AI measurement data within the second area.

[0342] The step S1105 can be understood with reference to the content of the step S702, which will not be repeated here.

[0343] S1106a, the LMF acquires AI measurement data from a UE supporting providing AI measurement data;

[0344] The step S1106a can be understood with reference to the content of the step S703a, which will not be repeated here.

[0345] S1106b, the LMF acquires AI measurement data from a gNB supporting providing AI measurement data;

[0346] The step S1106b can be understood with reference to the content of the step S703b.

[0347] S1107, the LMF sends information 7-4 to the MTLF;

[0348] Before the step S1107, the steps S1106a and / or S1106b can be performed, and accordingly, the information 7-4 can comprise AI measurement data acquired or collected by the LMF in the steps S1106a and / or S1106b. The information 7-4 can be a response to the information 7-3, and the LMF can send the information 7-4 to the MTLF based on the information 7-3, or in other words, the LMF sends AI measurement data requested to be acquired by the LMF in the information 7-3 to the MTLF.

[0349] S1108, the MTLF trains an AI model based on the collected AI measurement data.

[0350] In the communication method shown in FIG. 11, based on the LMF registering its AI capability information, it is beneficial for the MTLF to determine the LMF as an enhanced LMF by querying the registration information of the LMF, and the LMF supports collecting and / or providing measurement data for an AI model.

[0351] In the step S701, the LMF can specifically determine a requirement related to collecting AI measurement data based on receiving the information 7-3 sent by the MTLF in the step S1104. Accordingly, the step S704 can specifically comprise the step S1107, i.e., the LMF sends the information 7-4 to the MTLF.

[0352] Optionally, S1104 can be performed without S1102 and S1103. Accordingly, the MTLF can use other methods to determine the LMF that supports providing AI measurement data, for example, the MTLF can determine the LMF that supports providing AI measurement data based on the LMF supporting AI positioning (e.g., deploying an AI model or supporting using an AI model for positioning inference). Alternatively, the MTLF can not need to determine whether the LMF supports providing AI measurement data before S1104.

[0353] S1101 is an optional step, and the present application does not limit the reason why the MTLF performs S1104.

[0354] In one possible example, the LMF can determine the requirement in S701 based on receiving the request from the AMF.

[0355] FIG. 12 schematically shows another possible flow of the communication method provided by the present application. As shown in FIG. 12, the method can include S1201-S1211.

[0356] S1201, the client sends information 8-1 to the GMLC;

[0357] The information 9-1 can include a UE ID, and the information 9-1 can be used to indicate obtaining the location or the positioning result of the UE indicated by the UE ID. The information 9-1 can be a positioning request or carried in a positioning request.

[0358] The present application does not limit the type of the client, for example, the client can be a client of an external positioning service. The UE ID can be, for example, a SUPI or a GPSI. In the subsequent steps of the method shown in FIG. 12, the UE refers to the UE indicated by the information 8-1.

[0359] S1202, the GMLC sends information 8-2 to the UDM;

[0360] After receiving the information 8-1, the GMLC can send information 8-2 to the UDM, and the information 8-2 is used to indicate obtaining the serving AMF of the UE. The UE refers to the UE indicated by the information 8-1.

[0361] S1203, the UDM sends information 8-3 to the GMLC;

[0362] The UDM can send information 8-3 to the GMLC based on the information 8-2. After receiving the information 8-2, the UDM can query the serving AMF of the UE indicated by the UE ID or the AMF served by the UE. The information 8-3 can include information of the AMF, and the information of the AMF includes, for example, an identifier of the AMF.

[0363] S1204, the GMLC sends information 8-4 to the AMF;

[0364] After receiving the information 8-3, the GMLC can send information 8-4 to the AMF based on the information 8-3. The information 8-4 is used to indicate to obtain the location of the UE. The information 8-4 can be a request message. The information 8-4 can include the identity of the UE, such as the UE ID in the information 8-1.

[0365] S1205, the AMF establishes a signaling connection with the UE;

[0366] After receiving the information 8-4, if the UE is currently in an idle state, the AMF triggers a service request process to establish a signaling connection with the UE.

[0367] S1206, the AMF selects an LMF;

[0368] After receiving the information 8-4, the AMF can select an LMF. For example, the AMF can select a suitable LMF for the UE based on information of a plurality of LMFs. The information of the LMF can include one or more of a service area of the LMF, a load condition of the LMF, AI capability information of the LMF, an address of the LMF, and an identity of the LMF.

[0369] The present application does not limit the specific method of the AMF selecting a suitable LMF based on the information of one or more LMFs. For example, the service area of the LMF includes a cell where the UE is located, the LMF supports AI positioning (such as deploying an AI model and supporting positioning inference using the AI model), and the LMF supports providing AI measurement data.

[0370] The present application does not limit the method of the AMF determining that the LMF supports providing AI measurement data. For example, the AMF can determine that the LMF supports providing AI measurement data by querying the AI capability information of the LMF from the NRF, and the specific process can be understood with reference to S1102 and S1103, only replacing the MTLF in S1102 and S1103 with the AMF.

[0371] S1207, the AMF sends information 8-5 to the LMF;

[0372] After determining the LMF, the AMF can send information 8-5 to the LMF, and the information 8-5 is used to instruct the LMF to locate the UE. Optionally, the information 8-5 can also instruct the LMF to perform AI positioning on the UE, or to perform positioning or positioning inference on the UE based on an AI model.

[0373] Step S1206 is an optional step, for example, the AMF can send information 8-5 to the LMF.

[0374] S1208, the LMF performs AI positioning on the UE;

[0375] After receiving the information 8-5, the LMF can perform AI positioning for the UE. The LMF can collect AI measurement data, and then process or infer the collected AI measurement data using an AI positioning model to obtain the position of the UE.

[0376] The AI measurement data collected by the LMF can be AI measurement data collected from the UE, or AI measurement data collected from the gNB, or include AI measurement data collected from the UE and AI measurement data collected from the gNB. The AI measurement data collected from the gNB in S1208 can refer to measurement data of an uplink signal sent by the UE and measured by the gNB.

[0377] The method for the LMF to collect AI measurement data can refer to S702 and S703a, or S702 and S703b, or S702, S703a and S703b, which will not be repeated here.

[0378] The LMF can determine the method for positioning the UE based on the positioning method indicated by the information 8-5, or alternatively, the LMF can determine whether to use a traditional positioning method or an AI positioning method to calculate the position of the UE based on internal logic.

[0379] S1209, the LMF sends information 8-6 to the AMF;

[0380] After the LMF performs AI positioning for the UE, the LMF can send information 8-6 to the AMF. The information 8-6 can be a response message of the information 8-5. The information 8-6 can include the result of the AI positioning of the UE by the LMF (e.g., the position information of the UE).

[0381] S1210, the AMF sends information 8-7 to the GMLC;

[0382] After the AMF receives the information 8-6, the AMF can send information 8-7 to the GMLC. The information 8-7 can be a response message of the information 8-4. The information 8-7 can include the result of the AI positioning of the UE by the LMF, e.g., the position information of the UE.

[0383] S1211, the GMLC sends information 8-8 to the client.

[0384] After the GMLC receives the information 8-7, the GMLC can send information 8-8 to the client. The information 8-8 can be a response message of the information 8-1. The information 8-8 can include the result of the AI positioning of the UE by the LMF, e.g., the position information of the UE.

[0385] In S1206, the AMF can select the LMF based on the AI positioning capability of the LMF, for example, when the AMF expects to calculate the UE position using the AI positioning method, the AMF can select an LMF supporting AI positioning according to whether the LMF supports the AI positioning capability. In the existing scheme, the AI positioning capability of the LMF mainly refers to whether the LMF supports calculating the UE position using the AI model, and does not consider whether the LMF can discover the UE / gNB supporting the AI capability and collect the measurement data from the UE / gNB supporting the AI capability. That is, even if the AMF discovers an LMF supporting AI positioning, the LMF still cannot calculate the UE position using the AI positioning method because the LMF cannot collect the AI positioning related measurement data from the UE / gNB.

[0386] In the communication method shown in FIG. 12, based on the LMF registering its own AI capability information, it is beneficial for the AMF to determine that the LMF is an enhanced LMF by querying the registration information of the LMF, and the LMF supports collecting and / or providing the measurement data for the AI model.

[0387] In S701, the LMF can specifically determine the requirement related to collecting the AI measurement data based on the information 8-5 sent by the AMF in S1207. Correspondingly, S704 can specifically include S1208 and S1209, that is, the LMF performs AI positioning on the UE after collecting the AI measurement data, and sends the information 8-6 to the AMF.

[0388] The application does not limit the way in which the LMF determines its own AI capability information (that is, the AI capability information for indicating the support of providing AI measurement data). After the LMF determines its own AI capability information, in the examples of FIG. 11 and FIG. 12, the LMF registers its own AI capability information with the NRF for the MTLF or the AMF to query the AI capability information of the LMF. The application does not limit the use of the AI capability information of the LMF registered by the LMF with the NRF, for example, other network elements (or other AI consumers) other than the MTLF or the AMF can query the AI capability information of the LMF through the NRF. In the examples of FIG. 11 and FIG. 12, the LMF registers its own AI capability information with the NRF, and the LMF can also register its own AI capability information with other types of network elements as long as the network element can save the AI capability information of the LMF and provide a query service for the information. Correspondingly, the AI consumer of the AI capability information (such as the MTLF or the AMF) can query the AI capability information of the LMF from the network element. Alternatively, after the LMF determines its own AI capability information, the LMF can actively send its own AI capability information to the AI consumer of the AI capability information (such as the MTLF and / or the AMF), or respond to the request of the AI consumer of the AI capability information.

[0389] That is, the LMF can determine its own AI capability information, and an AI consumer (e.g., MTLF or AMF) of the AI capability can obtain the AI capability information of the LMF. Hereinafter, an example in which the AI consumer obtains the capability information of the LMF from the NRF is taken.

[0390] In order to facilitate the AI consumer to efficiently perceive the enhanced LMF or determine whether a specific LMF supports collecting and / or providing measurement data for an AI model in the case that the LMF does not determine its own AI capability information or does not register its own AI capability information, the present application further proposes that the AI consumer can perceive the enhanced LMF or determine whether a specific LMF supports collecting and / or providing measurement data for an AI model based on AI capability information of a measurement unit. The measurement unit can be a UE and / or a gNB.

[0391] The present application does not limit the method for the AI consumer to determine the AI capability information of the measurement unit. For example, the AI consumer can determine the AI capability information of the measurement unit according to any one or more of the methods for the LMF to determine the AI capability information of the measurement unit introduced in the foregoing. Hereinafter, an example in which the AI consumer obtains the AI capability information of the UE from the UDM is taken to introduce an example of the method for the AI consumer to determine the AI capability information of the LMF.

[0392] In one possible example, the AI consumer can be an MTLF, and the MTLF can perceive the enhanced LMF based on the AI capability information of the UE.

[0393] FIG. 13 schematically shows another possible flow of the communication method provided by the present application. As shown in FIG. 13, the method can include S1300-S1309.

[0394] S1300, the UDM stores the subscription information of the UE;

[0395] The UDM is configured with the subscription information of one or more UEs, and the subscription information of the UE can include UE capability information. The UE capability information can be used to indicate whether the UE supports providing AI measurement data. Alternatively, the UE capability information can be AI capability information of the UE, and based on the UE supporting providing AI measurement data, the subscription information of the UE including the UE capability information can be used to indicate that the UE supports providing AI measurement data, and the subscription information of the UE not including the UE capability information can be used to indicate that the UE does not support providing AI measurement data.

[0396] The subscription information of the UE can further include information of an LMF serving the UE, i.e., information of an LMF serving the UE. The information of the LMF can refer to the related content in the foregoing, e.g., the information of the LMF can include an identifier of the LMF.

[0397] S1301, the MTLF sends information 9-1 to the AMF;

[0398] When the MTLF determines to collect AI measurement data in the first area to train the AI model, the MTLF can send information 9-1 to the AMF, where the information 9-1 is used to indicate to obtain the identity of the UE in the first area. The first area can be the area indicated by the AOI information. In this application, the AOI information can include a TA list and / or a cell list. The area indicated by the AOI information can include the area of multiple TAs and / or cells.

[0399] S1302, the AMF sends information 9-2 to the MTLF;

[0400] After receiving the information 9-1, the AMF can send the information 9-2 to the MTLF. The information 9-2 can be a response message of the information 9-1. The information 9-2 can include the identity of one or more UEs. The one or more UEs are all or part of the UEs in the first area requested by the information 9-1.

[0401] S1303, the MTLF sends information 9-3 to the UDM;

[0402] S1304, the UDM sends information 9-4 to the MTLF;

[0403] Through S1303 and S1304, the MTLF can obtain the information 9-4 from the UDM based on the identity of the UE in the information 9-2. The information 9-4 can be part or all of the subscription information of the UE. The subscription information of the UE can refer to the related content in S1300. The information 9-4 can include the UE capability information and the information of the serving AMF of the UE.

[0404] S1303 and S1304 can refer to S601c and S602c respectively, and / or S601d and S602d. The information 9-3 and the information 9-4 can refer to the information 3-1 and the information 3-2 respectively, and / or the information 3-3 and the information 3-4.

[0405] S1305, the MTLF determines the LMF supporting providing AI measurement data based on the information 9-4;

[0406] After receiving the information 9-4, the MTLF can filter out the UE supporting providing AI measurement data based on the information 9-4, and then determine that the serving LMF of the UE supports providing AI measurement data.

[0407] S1306, the MTLF sends information 9-5 to the LMF;

[0408] After the MTLF determines the LMF that supports providing the AI measurement data, the MTLF can send information 9-5 to the LMF. Step S1306 can be understood with reference to the related content of S1104, and information 9-5 can be understood with reference to the meaning of information 7-3. For example, information 9-5 can include request information, the request information being used to indicate to provide or indicate to obtain the AI measurement data. For example, information 7-3 can further include location information, the location information being used to indicate a third area, the third area being a range of the AI measurement data indicated to be obtained by the request information.

[0409] S1307, the LMF collects the AI measurement data.

[0410] After the LMF receives information 9-5, the LMF can collect the AI measurement data based on information 9-5. Based on the fact that information 9-5 further includes the location information used to indicate the third area, the LMF can collect the AI measurement data within the third area.

[0411] In order to improve the efficiency of the LMF collecting the AI measurement data, the LMF can determine a measurement device that supports providing the AI measurement data (within the third area), and then collect the AI measurement data from the determined measurement device. Details can be referred to S702 and S703a, or S702 and S703b, or S702, S703a and S703b.

[0412] S1308, the LMF sends information 9-6 to the MTLF.

[0413] After the LMF collects the AI measurement data, the LMF can send information 9-6 to the MTLF. Information 9-6 can be a response message of information 9-5. Information 9-6 can include the AI measurement data collected by the LMF.

[0414] In this application, the interaction between the MTLF and the LMF can be realized through the AMF or through the GMLC and the AMF.

[0415] S1309, the MTLF trains the AI model using the AI measurement data.

[0416] After the MTLF receives information 9-6, the MTLF can train the AI model based on the AI measurement data provided by the LMF.

[0417] In S701, the LMF can specifically determine the demand related to collecting the AI measurement data based on the information 9-5 received by the MTLF in S1306. Correspondingly, S704 can specifically include S1307 and S1308, that is, after the LMF collects the AI measurement data, the LMF performs S1308.

[0418] In one possible example, the AI consumer can be the AMF, and the AMF can perceive the enhanced LMF based on the AI capability information of the UE.

[0419] FIG. 14 schematically shows another possible flow of the communication method provided by the present application. As shown in FIG. 14, the method can include S1400-S1406.

[0420] S1400, the UDM stores the subscription information of the UE;

[0421] S1400 can be understood with reference to the content of S1300.

[0422] S1401, the AMF sends information 10-1 to the UDM;

[0423] S1402, the UDM sends information 10-2 to the AMF;

[0424] Through S1401 and S1402, the AMF can obtain information 10-2 from the UDM, and information 10 can be part or all of the subscription information of the UE. The subscription information of the UE can be referred to the related content in S1300. Information 9-4 can include UE capability information and information of the serving AMF of the UE.

[0425] S1401 and S1402 can be respectively referred to S601c and S602c, and / or S601d and S602d. Information 10-1 and information 10-2 can be respectively referred to information 3-1 and information 3-2, and / or information 3-3 and information 3-4.

[0426] S1403, the AMF determines that the LMF supporting providing AI measurement data based on information 10-2;

[0427] After receiving information 10-2, the AMF can filter out the UE supporting providing AI measurement data based on information 10-2, and then determine that the serving LMF of the UE supports providing AI measurement data.

[0428] S1404, the AMF sends information 10-3 to the LMF;

[0429] After determining the LMF supporting providing AI measurement data, the AMF can send information 10-3 to the LMF, and information 10-3 is used to instruct the LMF to position the UE. Optionally, information 10-3 can also instruct the LMF to perform AI positioning on the UE, or perform positioning or positioning inference on the UE based on an AI model.

[0430] Step S1404 can be understood with reference to the related content of S1207, and information 10-3 can be understood with reference to the meaning of information 8-5.

[0431] S1405, the LMF collects AI measurement data and performs positioning based on an AI model and the collected data;

[0432] Step S1405 can refer to the related content of S1208.

[0433] S1406, the LMF sends information 10-4 to the AMF.

[0434] After the LMF obtains the positioning result, it can send information 10-4 to the AMF, which can include the positioning result obtained by the LMF.

[0435] Step S1406 can refer to the related content of S1209.

[0436] In S701, the LMF can determine the requirement related to collecting AI measurement data based on the information 10-3 sent by the AMF in S1404. Accordingly, S704 can specifically include S1405 and S1406, that is, the LMF collects AI measurement data and performs AI positioning on the UE, and sends information 10-4 to the AMF.

[0437] In this application, the interaction between MTLF and LMF can also be through AMF (that is, MTLF first sends the request to the AMF whose service area contains the area in the request message, and then AMF discovers LMF and forwards the request to LMF), or through GMLC and AMF (that is, the request path is MTLF-->GMLC-->AMF-->LMF). If the data request passes through the AMF, the AMF can also determine the list of UEs in the area based on the area information of the request, and then further filter out the UEs that support providing AI measurement data by AMF / LMF.

[0438] This application does not limit the number of network elements involved in the communication system in each method example, for example, the communication system can include more or fewer network elements. In at least one method example, one or more network elements of the communication system can be replaced by other network elements. This application does not limit the function of each network element in the communication system in each method example, and the name and / or function of the network element can change as the communication system evolves.

[0439] The foregoing takes DL-CIR and DL-PDP as examples of the data required for the AI model of positioning scenario 1 to collect. The data required for the AI model of positioning scenario 1 to collect can include channel measurement data measured by the UE, such as measurement data of PRS signals (referred to as PRS measurement data), wherein the PRS measurement data can include at least one of timing, power, and phase information of the PRS signal.

[0440] Similarly, the data required to be collected for the AI model of positioning scenario 2 is exemplified by UL-CIR and UL-PDP. The data required to be collected for the AI model of positioning scenario 2 can include channel measurement data measured by the gNB, for example, measurement data of SRS signals (referred to as SRS measurement data) measured by the gNB, wherein the SRS measurement data can include at least one of timing, power and phase information of the SRS signals.

[0441] Optionally, the PRS signal can be another type of reference signal, and the SRS signal can be another type of reference signal.

[0442] The communication apparatus provided in the fifth aspect of the present application is introduced in the foregoing. The communication apparatus can include a sending module. Optionally, the communication apparatus can further include a receiving module. Optionally, the communication apparatus can further include a processing module. The communication apparatus can be used to perform the steps or processes performed by the UE or gNB in the examples shown in FIG. 5 or FIG. 6-1 or FIG. 7 or FIG. 8 or FIG. 9 or FIG. 10 or FIG. 11 or FIG. 12, the sending module can be used to perform the sending steps or actions performed by the UE / gNB, the receiving module can be used to perform the receiving steps performed by the UE / gNB, and the processing module can be used to perform the internal operations or actions performed by the UE / gNB. For example, the sending module can be used to perform S501a, the receiving module can be used to perform S505a, and the processing module can be used to perform S804. Details can be referred to the related introduction in the foregoing method examples.

[0443] The communication apparatus provided in the sixth aspect of the present application is also introduced in the foregoing. The communication apparatus can include a receiving module. Optionally, the communication apparatus can further include a sending module. Optionally, the communication apparatus can further include a processing module. The communication apparatus can be used to perform the steps or processes performed by the LMF in the examples shown in FIG. 5 or FIG. 6-1 or FIG. 6-2 or FIG. 7 or FIG. 8 or FIG. 9 or FIG. 10 or FIG. 11 or FIG. 12 or FIG. 13 or FIG. 14, the sending module can be used to perform the sending steps or actions performed by the LMF, the receiving module can be used to perform the receiving steps performed by the LMF, and the processing module can be used to perform the internal operations or actions performed by the LMF. For example, the receiving module can be used to perform S503a, the sending module can be used to perform S504a, and the processing module can be used to perform S702. Details can be referred to the related introduction in the foregoing method examples.

[0444] The foregoing also introduces a communication apparatus provided by the seventh aspect of the present application. The communication apparatus can include a sending module. Optionally, the communication apparatus can further include a receiving module. Optionally, the communication apparatus can further include a processing module. The communication apparatus can be configured to perform the steps or procedures performed by the MTLF in the example shown in FIG. 11, or be configured to perform the steps or procedures performed by the AMF in the example shown in FIG. 12, the sending module can be configured to perform the sending steps or actions performed by the LMF or the AMF, the receiving module can be configured to perform the receiving steps performed by the LMF or the AMF, and the processing module can be configured to perform the internal operations or actions performed by the LMF or the AMF. For example, the sending module can be configured to perform S1102, the receiving module can be configured to perform S1103, and the processing module can be configured to perform S1108. Details can be referred to the related description in the foregoing method examples.

[0445] The foregoing also introduces a communication apparatus provided by the eighth aspect of the present application. The communication apparatus can include a receiving module. Optionally, the communication apparatus can further include a sending module. Optionally, the communication apparatus can further include a processing module. The communication apparatus can be configured to perform the steps or procedures performed by the MTLF in the example shown in FIG. 13, or be configured to perform the steps or procedures performed by the AMF in the example shown in FIG. 14, the sending module can be configured to perform the sending steps or actions performed by the MTLF or the AMF, the receiving module can be configured to perform the receiving steps performed by the MTLF or the AMF, and the processing module can be configured to perform the internal operations or actions performed by the MTLF or the AMF. For example, the receiving module can be configured to perform S1304, the sending module can be configured to perform S1303, and the processing module can be configured to perform S1305 and / or S1309. Details can be referred to the related description in the foregoing method examples.

[0446] In the present application, the internal operations or actions can be other operations in the flowchart of the communication method except the sending operations and the receiving operations, for example, the steps described in the rectangular boxes in the flowchart.

[0447] The foregoing also introduces a communication apparatus provided by the ninth aspect of the present application. The communication apparatus includes a processor and a memory. The memory stores a computer program or computer instructions. The processor is configured to invoke and run the computer program or computer instructions stored in the memory, so that the processor implements the steps or processes performed by the target communication unit in the examples shown in FIG. 5 or FIG. 6-1 or FIG. 6-2 or FIG. 7 or FIG. 8 or FIG. 9 or FIG. 10 or FIG. 11 or FIG. 12 or FIG. 13 or FIG. 14. The target communication unit can be any one or more network elements in the corresponding communication method. For example, in the example shown in FIG. 6-2, the target communication unit can include at least one network element from among the LMF, the UDM, and the NRF.

[0448] The foregoing also introduces a communication apparatus provided by the tenth aspect of the present application. The communication apparatus includes a processor and an interface circuit. The processor is configured to communicate with other apparatuses through the interface circuit, and perform the steps or processes performed by the target communication unit in the examples shown in FIG. 5 or FIG. 6-1 or FIG. 6-2 or FIG. 7 or FIG. 8 or FIG. 9 or FIG. 10 or FIG. 11 or FIG. 12 or FIG. 13 or FIG. 14. The target communication unit can be any one or more network elements in the corresponding communication method. For example, in the example shown in FIG. 6-2, the target communication unit can include at least one network element from among the LMF, the UDM, and the NRF. The processor includes one or more.

[0449] The foregoing also introduces a communication apparatus provided by the eleventh aspect of the present application. The communication apparatus includes a processor configured to be connected to a memory, and invoke the program stored in the memory to perform the steps or processes performed by the target communication unit in the examples shown in FIG. 5 or FIG. 6-1 or FIG. 6-2 or FIG. 7 or FIG. 8 or FIG. 9 or FIG. 10 or FIG. 11 or FIG. 12 or FIG. 13 or FIG. 14. The target communication unit can be any one or more network elements in the corresponding communication method. For example, in the example shown in FIG. 6-2, the target communication unit can include at least one network element from among the LMF, the UDM, and the NRF. The memory can be located inside the communication apparatus or outside the communication apparatus. The processor includes one or more.

[0450] The foregoing also introduces a computer program product including computer instructions provided by the twelfth aspect of the present application. When the computer program product runs on a computer, the computer is caused to perform the steps or processes performed by the target communication unit in the examples shown in FIG. 5 or FIG. 6-1 or FIG. 6-2 or FIG. 7 or FIG. 8 or FIG. 9 or FIG. 10 or FIG. 11 or FIG. 12 or FIG. 13 or FIG. 14. The target communication unit can be any one or more network elements in the corresponding communication method. For example, in the example shown in FIG. 6-2, the target communication unit can include at least one network element from among the LMF, the UDM, and the NRF.

[0451] The foregoing also introduces a computer readable storage medium provided by the thirteenth aspect of the present application. The storage medium includes computer instructions, which, when executed on a computer, cause the computer to perform the steps or processes performed by the target communication unit in the examples shown in FIG. 5 or FIG. 6-1 or FIG. 6-2 or FIG. 7 or FIG. 8 or FIG. 9 or FIG. 10 or FIG. 11 or FIG. 12 or FIG. 13 or FIG. 14. The target communication unit can be any one or more network elements in the corresponding communication method. For example, in the example shown in FIG. 6-2, the target communication unit can include at least one network element of the LMF, the UDM, and the NRF.

[0452] The foregoing also introduces a chip (or chip device or chip system) provided by the fourteenth aspect of the present application. The chip includes a processor, which is configured to invoke computer programs or computer instructions in a memory, so as to cause the processor to perform the steps or processes performed by the target communication unit in the examples shown in FIG. 5 or FIG. 6-1 or FIG. 6-2 or FIG. 7 or FIG. 8 or FIG. 9 or FIG. 10 or FIG. 11 or FIG. 12 or FIG. 13 or FIG. 14. The target communication unit can be any one or more network elements in the corresponding communication method. For example, in the example shown in FIG. 6-2, the target communication unit can include at least one network element of the LMF, the UDM, and the NRF. Optionally, the processor is coupled to the memory through an interface.

[0453] In the present application, the processor mentioned anywhere can be a general central processing unit, a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits for controlling the execution of programs of the method provided by any of the above embodiments. The memory mentioned anywhere above can be a read-only memory (ROM) or other type of static storage device that can store static information and instructions, a random access memory (RAM), and the like.

[0454] The foregoing also introduces a communication system provided by the fifteenth aspect of the present application. The communication system includes all or part of the network elements in the examples shown in FIG. 5 or FIG. 6-1 or FIG. 6-2 or FIG. 7 or FIG. 8 or FIG. 9 or FIG. 10 or FIG. 11 or FIG. 12 or FIG. 13 or FIG. 14. For example, in the example shown in FIG. 6-2, the communication system can include at least one network element of the LMF, the UDM, and the NRF.

[0455] In this application, the processing module can be implemented by at least one processor or processor-related circuit. Specifically, the processor can include a modem chip, or a SoC chip or a SIP chip containing a modem core. The sending module and / or the receiving module can be implemented by a transceiver or a transceiver-related circuit. The sending module and / or the receiving module can also be referred to as a communication module or a communication interface. The storage module can be implemented by at least one memory.

[0456] Optionally, in this application, when the communication device is a circuit or chip responsible for communication functions, such as a modem chip or a SoC chip or a SIP chip containing a modem core, the functions of the processing module can be implemented by the circuit system including one or more processors or processing cores in the above-mentioned chip. The functions of the sending module and / or the receiving module can be implemented by the interface circuit or data transceiver circuit on the above-mentioned chip.

[0457] In this application, when the communication device is a UE, FIG. 15 shows a simplified structure diagram of a UE. As shown in FIG. 15, the UE includes a processor, a memory, and a transceiver. The memory can store computer program code, and the transceiver includes a transmitter 1531, a receiver 1532, a radio frequency circuit (not shown in the figure), an antenna 1533, and an input / output device (not shown in the figure).

[0458] The processor is mainly used for processing communication protocols and communication data, controlling the UE, executing software programs, and processing data of software programs, etc. The memory is mainly used for storing software programs and data. The radio frequency circuit is mainly used for conversion between baseband signals and radio frequency signals and processing of radio frequency signals. The antenna is mainly used for transceiving radio frequency signals in the form of electromagnetic waves. The input / output device can include a touch screen, a display screen, or a keyboard, etc. The input / output device is mainly used for receiving user input data and outputting data to the user. It should be noted that some types of UEs can not have an input / output device.

[0459] When data needs to be sent, the processor performs baseband processing on the data to be sent and outputs the baseband signal to the radio frequency circuit. Then, the radio frequency circuit performs radio frequency processing on the baseband signal and transmits the radio frequency signal in the form of electromagnetic waves through the antenna. When data is sent to the UE, the radio frequency circuit receives the radio frequency signal through the antenna. The radio frequency circuit converts the radio frequency signal into a baseband signal and outputs the baseband signal to the processor. The processor converts the baseband signal into data and processes the data. For ease of illustration, only one memory, one processor, and one transceiver are shown in FIG. 15. In actual UE products, there can be one or more processors and one or more memories. The memory can also be referred to as a storage medium or a storage device, etc. The memory can be independent of the processor or integrated with the processor, and the embodiments of this application do not limit this.

[0460] In the embodiments of the present application, the antenna and the radio frequency circuit with transceiving function can be regarded as a transceiving module of the UE, and the processor with processing function can be regarded as a processing module of the UE.

[0461] As shown in FIG. 15, the UE includes a processor 1510, a memory 1520 and a transceiver 1530. The processor 1510 can also be referred to as a processing unit, a processing board, a processing module, or a processing device, etc. The transceiver 1530 can also be referred to as a transceiving unit, a transceiver, or a transceiving device, etc.

[0462] Optionally, the devices for implementing the receiving function in the transceiver 1530 are regarded as a receiving module, and the devices for implementing the sending function in the transceiver 1530 are regarded as a sending module, that is, the transceiver 1530 includes a receiver and a transmitter. The transceiver can also be referred to as a transceiver, a transceiving module, or a transceiving circuit, etc. from time to time. The receiver can also be referred to as a receiver, a receiving module, or a receiving circuit, etc. from time to time. The transmitter can also be referred to as a transmitter, a transmitting module, or a transmitting circuit, etc. from time to time.

[0463] The processor 1510 is configured to perform the processing actions of the UE side in the examples shown in FIG. 5 or FIG. 6-1 or FIG. 7 or FIG. 8 or FIG. 9 or FIG. 10 or FIG. 11 or FIG. 12. The transceiver 1530 is configured to perform the transceiving actions of the UE in the examples shown in FIG. 5 or FIG. 6-1 or FIG. 6-2 or FIG. 7 or FIG. 8 or FIG. 9 or FIG. 10 or FIG. 11 or FIG. 12.

[0464] It should be understood that FIG. 15 is only an example and not limiting, and the above-mentioned UE including a transceiving module and a processing module can not depend on the structure shown in FIG. 15.

[0465] When the communication apparatus 1500 is a chip, the chip includes a processor, a memory and a transceiver. The transceiver can be an input / output circuit or a communication interface. The processor can be a processing module integrated on the chip or a microprocessor or an integrated circuit. The sending operation of the UE in the above method embodiments can be understood as the output of the chip, and the receiving operation of the UE in the above method embodiments can be understood as the input of the chip.

[0466] In the present application, when the communication apparatus is an access network device or a wireless access device, for example, a gNB or a base station, FIG. 16 shows a simplified base station structure diagram. The base station includes a 1610 part, a 1620 part and a 1630 part.

[0467] The 1610 part is mainly used for baseband processing, controlling the base station, etc.; the 1610 part is usually the control center of the base station, which can be usually referred to as a processor, and is configured to control the base station to perform the processing operations of the access network device side in the above method embodiments.

[0468] The 1620 part is mainly used for storing computer program codes and data.

[0469] The 1630 part is mainly used for transceiving radio frequency signals and converting radio frequency signals and baseband signals. The 1630 part can be referred to as a transceiver module, a transceiver, a transceiver circuit, or a transceiver, etc. The transceiver module of the 1630 part can also be referred to as a transceiver or a transceiver, etc., which includes an antenna 1633 and a radio frequency circuit (not shown in the figure), wherein the radio frequency circuit is mainly used for radio frequency processing. Optionally, the devices in the 1630 part used to realize the receiving function can be regarded as a receiver, and the devices used to realize the sending function can be regarded as a transmitter, that is, the 1630 part includes a receiver 1632 and a transmitter 1631. The receiver can also be referred to as a receiving module, a receiver, or a receiving circuit, etc., and the transmitter can be referred to as a transmitting module, a transmitter, or a transmitting circuit, etc.

[0470] The 1610 part and the 1620 part can include one or more single boards, and each single board can include one or more processors and one or more memories. The processor is used to read and execute the program in the memory to realize the baseband processing function and the control of the base station. If there are multiple single boards, the single boards can be interconnected to enhance the processing capability. As an optional implementation, multiple single boards can also share one or more processors, or multiple single boards can share one or more memories, or multiple single boards can share one or more processors at the same time.

[0471] For example, in an implementation, the transceiver module of the 1630 part is used to execute the transceiver-related processes performed by the gNB side in the examples shown in FIG. 5 or FIG. 6-1 or FIG. 7 or FIG. 8 or FIG. 9 or FIG. 10 or FIG. 11 or FIG. 12. The processor of the 1610 part is used to execute the processing-related processes performed by the gNB side in the examples shown in FIG. 5 or FIG. 6-1 or FIG. 7 or FIG. 8 or FIG. 9 or FIG. 10 or FIG. 11 or FIG. 12.

[0472] It should be understood that FIG. 16 is only an example and not a limitation, and the network device including the processor, the memory, and the transceiver described above can not depend on the structure shown in FIG. 16.

[0473] When the communication device 1600 is a chip, the chip includes a transceiver, a memory, and a processor. The transceiver can be an input / output circuit, a communication interface; the processor is an integrated processor on the chip, or a microprocessor, or an integrated circuit. The sending operation of the gNB in the above method embodiments can be understood as the output of the chip, and the receiving operation of the gNB in the above method embodiments can be understood as the input of the chip.

[0474] Those skilled in the art can clearly understand that the explanation and beneficial effects of the related content in any of the above-provided devices can refer to the corresponding method embodiments provided above for the convenience and brevity of description, and will not be repeated here.

[0475] In several embodiments provided in the present application, it should be understood that the disclosed system, device and method can be implemented in other ways. For example, the above-described device embodiments are only schematic, for example, the division of the units is only a logical function division, and actual implementation can have another division manner, for example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the units shown or discussed can be indirect coupling or communication connection through some interface, device or unit, and can be electrical, mechanical or other forms.

[0476] The units described as separate components can or can not be physically separated, and the components shown as units can or can not be physical units, that is, they can be located in one place, or can be distributed on a plurality of network units. Part or all of the units can be selected according to actual needs to achieve the purpose of the embodiment scheme.

[0477] In addition, each functional unit in each embodiment of the present application can be integrated in one processing unit, or each unit can exist physically, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of a software functional unit.

[0478] When the integrated unit is realized in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the present application essentially make contributions or the whole or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium, and includes a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present application. The foregoing storage medium includes: U disk, mobile hard disk, ROM, RAM, magnetic disk or optical disk, and various program codes that can be stored.

[0479] The above-described embodiments are only used to illustrate the technical solutions of the present application, but not limit the present application; although the present application is described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: it can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacement for part of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A communication method characterized by comprising: The method comprises: sending first information, the first information comprising artificial intelligence (AI) capability information of a first communication unit, the AI capability information of the first communication unit being used to indicate that the first communication unit supports providing measurement data for an AI positioning model.

2. The method of claim 1, wherein, The sending first information comprises: sending the first information to a second communication unit, the AI positioning model being deployed on the second communication unit.

3. The method of claim 2, wherein, After the sending first information, the method further comprises: receiving second information sent by the second communication unit, the second information being used to indicate that the first communication unit provides the measurement data.

4. The method according to claim 2 or 3, characterized in that, Before the sending first information, the method further comprises: receiving third information sent by the second communication unit, the third information being used to request the AI capability information of the first communication unit.

5. The method according to claim 2 or 3, characterized in that, The first information is sent to the second communication unit based on information of the second communication unit configured in the first communication unit.

6. The method according to any one of claims 1-5, characterized in that, The first communication unit is a terminal device, and the measurement data supported to be provided by the terminal device comprises measurement data of downlink data sent by a radio access device.

7. The method according to any one of claims 1-5, characterized in that, The first communication unit is a radio access device, and the measurement data supported to be provided by the radio access device comprises measurement data of uplink data sent by a terminal device.

8. The method according to any one of claims 1-7, characterized in that, The AI capability information of the first communication unit is further used to indicate a type of the measurement data supported to be provided by the first communication unit.

9. The method of claim 8, wherein, The type of the measurement data indicated by the AI capability information of the first communication unit comprises channel impulse response (CIR) and / or channel power delay profile (PDP).

10. A communication method characterized by comprising: The method comprises: receiving first information, the first information comprising artificial intelligence (AI) capability information of a first communication unit, the AI capability information of the first communication unit being used to indicate that the first communication unit supports providing measurement data for an AI positioning model, the AI positioning model being deployed on a second communication unit; sending second information to the first communication unit, the second information being used to indicate that the first communication unit provides the measurement data.

11. The method of claim 10, wherein, Before receiving the first information, the method further comprises: sending third information to the first communication unit, the third information being used to request the AI capability information of the first communication unit.

12. The method of claim 10, wherein, The first information is sent by a third communication unit, wherein the third communication unit is used to save subscription information of the first communication unit, the subscription information of the first communication unit comprising the AI capability information of the first communication unit, and before receiving the first information sent by the third communication unit, the method further comprises: sending fourth information to the third communication unit, the fourth information being used to request the subscription information of the first communication unit.

13. The method of claim 10, wherein, The first information is sent by a fourth communication unit, the fourth communication unit being used to train the AI positioning model, and the first information is used to indicate that the second communication unit provides the measurement data acquired from the first communication unit.

14. The method of claim 10, wherein, The first information is sent by a fifth communication unit, and the first information is used to instruct the second communication unit to perform positioning based on the AI positioning model and the measurement data obtained from the first communication unit.

15. The method according to any one of claims 10-14, characterized in that, The method further comprises: sending fifth information to a sixth communication unit, the fifth information comprising AI capability information of the second communication unit, the AI capability information of the second communication unit being used to indicate that the second communication unit supports providing the measurement data, and the sixth communication unit being used to save the AI capability information of the second communication unit.

16. A method of communication, comprising: The method comprises: sending first information, the first information comprising a first information element, the first information element being used to indicate that a communication unit supporting providing measurement data for an artificial intelligence (AI) positioning model is discovered; receiving second information, the second information comprising information of a first communication unit, and the first communication unit supporting providing the measurement data.

17. The method of claim 16, wherein, The first information further comprises a second information element, and the second information element is used to indicate a first area, and a service area of the first communication unit contains the first area.

18. The method of claim 17, wherein, The first area is determined according to a region of interest of the AI positioning model.

19. The method of claim 18, wherein, The method further comprises: sending third information to the first communication unit based on the information of the first communication unit, and the third information being used to instruct to provide the measurement data; receiving the measurement data provided by the first communication unit, and the received measurement data being used to process the AI positioning model.

20. The method of claim 17, wherein, The first area is determined according to a position of a terminal device or a cell of the terminal device.

21. The method of claim 20, wherein, The method further comprises: sending fourth information to the first communication unit based on the information of the first communication unit, and the fourth information being used to instruct the first communication unit to process the position of the terminal device based on the AI positioning model.

22. A method of communication, comprising: The method comprises: receiving first information, the first information comprising artificial intelligence (AI) capability information of a first communication unit, the AI capability information of the first communication unit being used to indicate that the first communication unit supports providing measurement data for an AI positioning model, and the first communication unit being served by a second communication unit; sending second information to the second communication unit, the second information being used to instruct the second communication unit to provide the measurement data, or sending third information to the second communication unit, the third information being used to instruct the second communication unit to perform positioning based on the AI positioning model and the measurement data.

23. The method of claim 22, wherein, The first information further comprises information of the second communication unit.

24. The method of claim 22 or 23, wherein, The first information is sent by a third communication unit, and the third communication unit is used to save subscription information of the first communication unit, and the subscription information of the first communication unit comprises the AI capability information of the first communication unit, and before the receiving first information, the method further comprises: sending fourth information to the third communication unit, and the fourth information being used to request the subscription information of the first communication unit.

25. A communications device, characterized by A module for performing the method according to any one of claims 1 to 24.

26. A communications device, characterized by comprising at least one processor coupled with a memory; the at least one processor configured to perform the method of any one of claims 1 to 24.

27. A readable storage medium characterized by, The storage medium has stored therein a computer program or instructions, which, when executed by a communication device, cause the communication device to implement the method of any one of claims 1 to 24.

28. A computer program product, characterised in that, The computer program product in the computer program, when executed by a communication device, causes the communication device to implement the method of any one of claims 1 to 24.

29. A chip, characterized by comprising a processor configured to invoke a computer program or computer instructions in a memory to cause the processor to perform the method of any one of claims 1 to 24.

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