Communication method and related device

Abstract

The invention provides a communication method and a related device, which can indicate a communication unit to support the provision of measurement data for an AI positioning model by transmitting AI capability information of the communication unit, thereby facilitating a network element for deploying the AI positioning model to obtain the measurement data for the AI positioning model from the communication unit more efficiently, and improving the measurement accuracy of the AI positioning model. And thus, the use efficiency of the AI positioning method is improved. The communication unit can be a terminal device or a wireless access device or an LMF or the like.

Description

Technical Field

[0001] This application relates to the field of communication technology, and in particular to a communication method and related apparatus. Background Technology

[0002] With the rapid development of wireless communication technology, base stations, as core components of networks, are constantly expanding their functions and application scenarios. In recent years, the technology of using base stations for environmental sensing has gradually attracted attention. This technology is based on the interaction between the base station and its surrounding environment, and achieves the perception and monitoring of the surrounding environment by collecting and analyzing the signals received by the base station. When using base stations for environmental sensing, if there are multiple sensing targets in the environment, with the introduction of terminal equipment to assist in sensing, the terminal equipment needs to send sensing reference signals through multiple beams to achieve the perception of targets in multiple beam directions.

[0003] However, when using base stations for environmental perception, given the limited reference signal resources of the base stations, artificial intelligence (AI) positioning can be used to improve positioning accuracy. However, how to efficiently utilize AI positioning methods remains a pressing issue. Summary of the Invention

[0004] The measurement data required for AI positioning models is generally different from that required for existing positioning methods. However, not all measurement data providers support providing measurement data for AI positioning models, which limits the efficiency of AI positioning methods.

[0005] This application provides a communication method and related apparatus that can transmit AI capability information of a communication unit to instruct the communication unit to support the provision of measurement data for AI positioning models. This enables network elements deploying AI positioning models to obtain measurement data for AI positioning models more efficiently from the communication unit, thereby improving the efficiency of AI positioning methods.

[0006] The following describes the communication method provided in the first aspect of this application. This 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 measurements 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.

[0007] The first communication unit can be a device or apparatus with a chip, or a device or apparatus with integrated circuitry, or a chip, chip system, module, or control unit in the aforementioned device or apparatus; specific details are not limited in this application. The chip can be a modem chip, also known as a baseband chip, or a system-on-chip (SoC) chip containing a modem core, or a system-in-package (SIP) chip. It should be noted that in this application, the term "first communication unit" can refer to the first communication unit itself, or to the chip, functional module, or integrated circuit within the first communication unit that implements the method provided in this application; specific details are not limited in this application. Similarly, in this application, the term "terminal device" can refer to the terminal device itself, or to the chip, functional module, or integrated circuit within the terminal device that implements the method provided in this application; specific details are not limited in this application. Similarly, in this application, the term "wireless access device" can refer to the wireless access device itself, or to the chip, functional module, or integrated circuit within the wireless access device that implements the method provided in this application; specific details are not limited in this application.

[0008] In the first aspect and its possible implementations, the method is described using the example of execution by a first communication unit. The method may 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. By sending its own AI capability information to other network elements, the first communication unit can notify other network elements that it supports providing measurement data for an AI positioning model, thereby enabling network elements deploying the AI ​​positioning model to more efficiently obtain measurement data for the AI ​​positioning model from the first communication unit, and thus improving the efficiency of the AI ​​positioning method.

[0009] Based on the first aspect, in one possible implementation, the first communication unit can send the first information to the second communication unit, where the AI ​​positioning model is deployed. This allows the second communication unit to more efficiently determine if the first communication unit supports providing measurement data for the AI ​​model, thereby enabling the second communication unit to more efficiently acquire measurement data for the AI ​​positioning model and ultimately improving the efficiency of the AI ​​positioning method.

[0010] This application does not limit the first communication unit to directly sending its AI capability information to the second communication unit. For example, it can forward its AI capability information to the second communication unit through other network elements. The second communication unit can provide positioning services to 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).

[0011] Based on the first aspect, in one possible implementation, after sending the first information, the first communication unit may also receive second information sent by the second communication unit, the second information being used to instruct the first communication unit to provide the measurement data.

[0012] Based on the first aspect, in one possible implementation, before sending the first information, the first communication unit may also receive third information sent by the second communication unit, the third information being used to request AI capability information from the first communication unit.

[0013] Optionally, the third information may also be used to indicate the type of AI capability requested, for example, to indicate the capability to request the first communication unit to collect AI measurement data of the target type.

[0014] Based on the first aspect, in one 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.

[0015] The following describes a communication method provided in the second aspect of this application. This method can be executed by a second communication unit. The second communication unit can be a communication unit for acquiring measurement data for an AI positioning model from a first communication unit. For example, the second communication unit can provide positioning services to 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 (Local Model for Positioning).

[0016] The second communication unit can be a device or apparatus with a chip, or a device or apparatus with integrated circuitry, or a chip, chip system, module, or control unit in the aforementioned device or apparatus; the specific application is not limited thereto. The chip can be a modem chip, also known as a baseband chip, or a system-on-chip (SoC) chip containing a modem core, or a system-in-package (SIP) chip. It should be noted that in this application, the term "second communication unit" can refer to either the second communication unit itself or the chip, functional module, or integrated circuit within the second communication unit that performs the method provided in this application; the specific application is not limited thereto. Similarly, in this application, the term "LMF" can refer to either the LMF itself or the chip, functional module, or integrated circuit within the LMF that performs the method provided in this application; the specific application is not limited thereto.

[0017] In the second aspect and its possible implementations, the method is described using the example of it being executed by a second communication unit. The method includes: the second communication unit receiving first information, the first information including artificial intelligence (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 AI ​​positioning model being deployed on the second communication unit. After receiving the first information, the second communication unit may also send second information to the first communication unit, the second information being used to instruct the first communication unit to provide the measurement data.

[0018] Based on the second aspect, in one possible implementation, before receiving the first information, the second communication unit also sends third information to the first communication unit, the third information being used to request the AI ​​capability information of the first communication unit.

[0019] Optionally, the third information may also be used to indicate the type of AI capability requested, for example, to indicate the capability to request the first communication unit to collect AI measurement data of the target type.

[0020] Based on the second aspect, in one possible implementation, the first information is sent by a third communication unit, wherein the third communication unit is used to store the 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 before the second communication unit receives the first information sent by the third communication unit, it can also send a fourth information to the third communication unit, the fourth information being used to request the subscription information of the first communication unit.

[0021] Based on the second aspect, in one possible implementation, the first information is sent by a fourth communication unit, which is used 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.

[0022] Based on the second aspect, in one possible implementation, the second communication unit further sends the measurement data obtained from the first communication unit to the fourth communication unit.

[0023] One or more instances of information appearing in this application may be replaced with other names (such as message, parcel, or signaling).

[0024] Based on the second aspect, in one possible implementation, the first information is sent by the 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.

[0025] Based on the second aspect, in one possible implementation, the second communication unit also sends the positioning result to the fifth communication unit.

[0026] Based on the second aspect, in one possible implementation, the second communication unit further sends fifth information to the sixth communication unit, the fifth information including the AI ​​capability information of the second communication unit, the AI ​​capability information of the second communication unit being used to instruct the second communication unit to support providing the measurement data, and the sixth communication unit being used to store the AI ​​capability information of the second communication unit.

[0027] Based on the first or second aspect, in one possible implementation, the first communication unit is a terminal device, and the measurement data provided by the terminal device includes measurement data of downlink data sent by the terminal device to the wireless access device.

[0028] Based on the first or second aspect, in one possible implementation, the first communication unit is a wireless access device, and the measurement data provided by the wireless access device includes measurement data of uplink data sent by the wireless access device to the terminal device.

[0029] Based on the first or second aspect, in one possible implementation, the AI ​​capability information of the first communication unit is further used to indicate the type of measurement data supported by the first communication unit.

[0030] Based on the first or second aspect, in one possible implementation, the type of measurement data indicated by the AI ​​capability information of the first communication unit includes channel impulse response (CIR) and / or channel power delay distribution (PDP).

[0031] The following describes the communication method provided in the third aspect of this application. This 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 this application, an AI training data consumer refers to a communication unit that requests training data for an AI model from a first communication unit, and an AI inference result consumer refers to a communication unit that requests AI localization results from a first communication unit. 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 (Model Training Logic Function). AI training data consumers and AI inference result consumers can be collectively referred to as AI consumers. This application does not limit the types of AI training data consumers and AI inference result consumers. For example, an AI training data consumer can be a model training logical function (MTLF) or a network data analytics function (NWDAF), and an AI inference result consumer can include at least one of AMF, SMF, PCF, MTLF, and NWDAF.

[0032] The second communication unit can be a device or apparatus with a chip, or a device or apparatus with integrated circuitry, or a chip, chip system, module, or control unit in the aforementioned device or apparatus; specific details are not limited in this application. The chip can be a modem chip, also known as a baseband chip, or a system-on-chip (SoC) chip containing a modem core, or a system-in-package (SIP) chip. It should be noted that in this application, the term "second communication unit" can refer to the second communication unit itself, or to the chip, functional module, or integrated circuit within the second communication unit that performs the method provided in this application; specific details are not limited in this application. Similarly, in this application, the term "MTLF" can refer to the MTLF itself, or to the chip, functional module, or integrated circuit within the MTLF that performs the method provided in this application; specific details are not limited in this application. Similarly, in this application, the term "AMF" can refer to the AMF itself, or to the chip, functional module, or integrated circuit within the AMF that performs the method provided in this application; specific details are not limited in this application.

[0033] In the third aspect and its possible implementation, the method is described using the example of execution by a second communication unit. The method includes: the second communication unit sending first information, the first information including a first information unit indicating the discovery of a communication unit that supports providing measurement data for an AI positioning model; and the second communication unit receiving second information, the second information including information about the first communication unit, which supports providing the measurement data. By sending the first information and receiving the second information, the second communication unit can discover an LMF capable of providing measurement data for the AI ​​model. This helps avoid the problem where the second communication unit (e.g., MTLF or AMF) discovers an LMF, but the LMF cannot collect AI measurement data from the UE / base station. This allows the LMF to determine which UEs / gNBs support providing AI measurement data when collecting AI measurement data, enabling the normal collection of AI measurement data and completing or assisting in the AI ​​positioning model training / inference process based on the AI ​​measurement data.

[0034] Based on the third aspect, in one possible implementation, the first information further includes a second information unit, which is used to indicate a first region, and the service area of ​​the first communication unit includes the first region.

[0035] The service area of ​​the first communication unit can refer to the area where the first communication unit supports providing location services. For example, the service area of ​​the LMF refers to the area where the LMF supports providing location services, or in other words, the LMF supports locating the UE within the service area.

[0036] Based on the third aspect, in one possible implementation, the first region is determined according to the region of interest of the AI ​​positioning model.

[0037] Based on the third aspect, in one possible implementation, the method further includes: sending third information to the first communication unit based on the information of the first communication unit, the third information being used to instruct the provision of the measurement data; receiving the measurement data provided by the first communication unit, the received measurement data being used to process the AI ​​positioning model.

[0038] In this application, the measurement data may include measurement data of the signal, and may also include tags corresponding to the measurement data of the signal (e.g., positioning results or the location of the terminal device).

[0039] Based on the third aspect, in one possible implementation, the first region is determined according to the location of the terminal device or the cell of the terminal device.

[0040] Based on the third aspect, in one possible implementation, the method further includes: sending fourth information to the first communication unit based on the information of the first communication unit, the fourth information being used to instruct the first communication unit to obtain the location of the terminal device based on the AI ​​positioning model.

[0041] The communication method provided in the fourth aspect of this application is described below. This 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 used to request training data for the AI ​​model from the second communication unit, and / or to request AI localization results from the second communication unit. 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 (Learning Data Factor). As described in the communication method provided in the third aspect, the fourth communication unit can be an AI training data consumer (e.g., MTLF), or an AI inference result consumer (e.g., AMF). With the evolution of network elements, MTLF can also be an AI inference result consumer, i.e., using an AI localization model for localization.

[0042] In the fourth aspect and its possible implementations, the method is described as being executed by a fourth communication unit. The method includes: the fourth communication unit receiving first information, the first information including the first communication unit's artificial intelligence (AI) capability information, the AI ​​capability information of the first communication unit indicating that the first communication unit supports providing measurement data for an AI positioning model, the first communication unit being provided by a second communication unit; then, the fourth communication unit sending second information to the second communication unit, the second information indicating that the second communication unit provides the measurement data, or sending third information to the second communication unit, the third information indicating that the second communication unit performs 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 (e.g., AMF or MTLF) filters out terminal devices or wireless access devices capable of providing AI measurement data based on the AI ​​capability information in the subscription information of the terminal device / wireless access device, avoiding the problem of the fourth communication unit directly requesting AI measurement data from the terminal device or wireless access device from the second communication unit (e.g., LMF) when the terminal device or wireless access device cannot provide the AI ​​measurement data.

[0043] Based on the fourth aspect, in one possible implementation, the first information also includes information from the second communication unit.

[0044] Based on the fourth aspect, in one possible implementation, the first information is sent by a third communication unit. The third communication unit stores the subscription information of the first communication unit, which includes its AI capability information. Before receiving the first information, the third communication unit can also send fourth information to the first communication unit, which requests the subscription information of the first communication unit. By storing the AI ​​capability information of the terminal device or wireless access device that can provide AI measurement data as its subscription information in the third communication unit (e.g., UDM), the fourth communication unit can first filter out terminal devices or wireless access devices that support providing AI measurement data. Thus, the fourth communication unit can directly request the AI ​​measurement data of the terminal device or wireless access device from the second communication unit that provides services to the terminal device or wireless access device.

[0045] The communication apparatus provided in the fifth aspect of this application is described below. This communication apparatus may be a first communication unit in the communication method of the first aspect or may be deployed within a first communication unit.

[0046] The communication device may include a transmitting module for transmitting first information, the first information including 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.

[0047] Based on the fifth aspect, in one possible implementation, the sending module is specifically used to send the first information to the second communication unit, on which the AI ​​positioning model is deployed.

[0048] Based on the fifth aspect, in one possible implementation, the communication device may further include a receiving module, which is used to receive second information sent by the second communication unit after the sending module sends the first information, the second information being used to instruct the first communication unit to provide the measurement data.

[0049] Based on the fifth aspect, in one 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 from the first communication unit.

[0050] Based on the fifth aspect, in one 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.

[0051] The following describes a communication apparatus provided in the sixth aspect of this application. This communication apparatus can be a second communication unit in the communication method of the second aspect or can be deployed within a second communication unit. The communication apparatus may include a receiving module. The receiving module is used to receive first information, the first information including 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, the AI ​​positioning model being deployed in the second communication unit.

[0052] The communication device may also include a sending module, which is used to send second information to the first communication unit after the receiving module receives the first information. The second information is used to instruct the first communication unit to provide the measurement data.

[0053] Based on the sixth aspect, in one possible implementation, the first information is sent by the first communication unit.

[0054] Based on the sixth aspect, in one 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 the AI ​​capability information of the first communication unit.

[0055] Based on the sixth aspect, in one possible implementation, the first information is sent by a third communication unit, wherein the third communication unit is used to store the 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 used to send a fourth information to the third communication unit before the receiving module receives the first information sent by the third communication unit, the fourth information being used to request the subscription information of the first communication unit.

[0056] Based on the sixth aspect, in one possible implementation, the first information is sent by a fourth communication unit, which is used 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.

[0057] Based on the sixth aspect, in one possible implementation, the first information is sent by the 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.

[0058] Based on the sixth aspect, in one possible implementation, the sending module is further configured to send fifth information to the sixth communication unit, the fifth information including the 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 store the AI ​​capability information of the second communication unit.

[0059] Based on the fifth or sixth aspect, in one possible implementation, the first communication unit is a terminal device, and the measurement data provided by the terminal device includes measurement data of downlink data sent by the terminal device to the wireless access device.

[0060] Based on the fifth or sixth aspect, in one possible implementation, the first communication unit is a wireless access device, and the measurement data provided by the wireless access device includes measurement data of uplink data sent by the wireless access device to the terminal device.

[0061] Based on the fifth or sixth aspect, in one possible implementation, the AI ​​capability information of the first communication unit is further used to indicate the type of measurement data supported by the first communication unit.

[0062] Based on the fifth or sixth aspect, in one possible implementation, the type of measurement data indicated by the AI ​​capability information of the first communication unit includes channel impulse response (CIR) and / or channel power delay distribution (PDP).

[0063] The following describes a communication apparatus provided in the seventh aspect of this application. This communication apparatus can be a second communication unit in the communication method provided in the third aspect, or can be deployed within a second communication unit. The communication apparatus may include a transmitting module for transmitting first information, the first information including a first information unit for indicating the discovery of a communication unit that supports providing measurement data for an artificial intelligence (AI) positioning model. The communication apparatus may also include a receiving module for receiving second information, the second information including information about a first communication unit that supports providing the measurement data.

[0064] Based on the seventh aspect, in one possible implementation, the first information further includes a second information unit, which is used to indicate a first region, and the service area of ​​the first communication unit includes the first region.

[0065] Based on the seventh aspect, in one possible implementation, the first region is determined according to the region of interest of the AI ​​positioning model.

[0066] Based on the seventh aspect, in one possible implementation, the sending module is further configured to send third information to the first communication unit based on the information of the first communication unit, the third information being used to indicate the provision of the measurement data, and the receiving module is further configured to receive the measurement data provided by the first communication unit, the received measurement data being used to process the AI ​​positioning model.

[0067] Based on the seventh aspect, in one possible implementation, the first region is determined according to the location of the terminal device or the cell of the terminal device.

[0068] Based on the seventh aspect, in one possible implementation, the sending module is further configured to send fourth information to the first communication unit based on the information of the first communication unit, the fourth information being used to instruct the first communication unit to obtain the location of the terminal device based on the AI ​​positioning model.

[0069] The following describes a communication apparatus provided in the eighth aspect of this application. This communication apparatus can be a second communication unit in the communication method provided in the fourth aspect, or can be deployed within a second communication unit. The communication apparatus may include a receiving module for receiving first information, the first information including artificial intelligence (AI) capability information of the 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 provided by the second communication unit. The communication apparatus may also include a sending module for 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.

[0070] Based on the eighth aspect, in one possible implementation, the first information further includes information from the second communication unit.

[0071] Based on the eighth aspect, in one possible implementation, the first information is sent by a third communication unit, which is used to store the subscription information of the first communication unit, the subscription information of the first communication unit including the AI ​​capability information of the first communication unit, and the sending module is further used to send a fourth information to the third communication unit before the receiving module receives the first information, the fourth information being used to request the subscription information of the first communication unit.

[0072] A ninth aspect of this application provides a communication device comprising a processor and a memory. The memory stores computer programs or computer instructions, and the processor is configured to call and execute the computer programs or computer instructions stored in the memory, causing the processor to implement any one of the implementation methods of any one of the first to fourth aspects.

[0073] Optionally, the communication device also includes a transceiver, and the processor controls the transceiver to send and receive signals or information.

[0074] A tenth aspect of this application provides a communication device including a processor and an interface circuit. The processor is configured to communicate with other devices via the interface circuit and to execute the method described in any one of the first to fourth aspects. The processor may include one or more devices.

[0075] The eleventh aspect of this application provides a communication device, including a processor for connection to a memory, for calling a program stored in the memory to execute the method described in any one of the first to fourth aspects. The memory may be located within or outside the communication device. The processor may include one or more processors.

[0076] In one implementation, at least one of the first communication unit, second communication unit, third communication unit, fourth communication unit, fifth communication unit and sixth communication unit may be a chip or chip system.

[0077] The twelfth aspect of this application provides a computer program product including computer instructions, which, when run on a computer, causes the computer to perform any of the implementations of any one of the first to fourth aspects.

[0078] The thirteenth aspect of this application provides a computer-readable storage medium including computer instructions that, when executed on a computer, cause the computer to perform any of the implementations of any one of the first to fourth aspects.

[0079] The fourteenth aspect of this application provides a chip (device) including a processor for calling a computer program or computer instructions in a memory to cause the processor to execute any one of the implementations of the first to fourth aspects described above.

[0080] Optionally, the processor is coupled to the memory via an interface.

[0081] The fifteenth aspect of this application provides a communication system, which includes at least one of the following: an entity executing a communication method provided in the first aspect, an entity executing a communication method provided in the second aspect, an entity executing a communication method provided in the third aspect, and an entity executing a communication method provided in the fourth aspect.

[0082] As can be seen from the above technical solution, by transmitting the AI ​​capability information of the communication unit, the communication unit is instructed to support providing measurement data for the AI ​​positioning model. This enables the network element deploying the AI ​​positioning model to obtain the measurement data for the AI ​​positioning model more efficiently from the communication unit, thereby improving the efficiency of the AI ​​positioning method. Attached Figure Description

[0083] Figure 1 This illustration shows an application scenario that utilizes base stations for sensing.

[0084] Figure 2 This illustration depicts an application scenario where terminal equipment assists base stations in sensing.

[0085] Figure 3-1 and Figure 3-2 Each schematic diagram illustrates a communication system according to an embodiment of this application;

[0086] Figure 3-3 This schematically illustrates a 5G network architecture based on service-oriented interfaces.

[0087] Figure 4-1 and Figure 4-2 The downlink positioning scenario and the uplink positioning scenario are illustrated respectively;

[0088] Figure 5 , Figure 6-1 , Figure 6-2 , Figures 7-14 The possible flows of the communication method provided in this application are illustrated schematically.

[0089] Figure 15 A simplified schematic diagram of the UE structure is shown;

[0090] Figure 16 A simplified schematic diagram of a base station structure is shown. Detailed Implementation

[0091] First, some terms used in the embodiments of this application will be explained to facilitate understanding by those skilled in the art.

[0092] (1) Configuration and Pre-configuration: In this application, both configuration and pre-configuration are used. Configuration refers to the process by which network devices such as base stations or servers send configuration information or parameter values ​​to the terminal via messages or signaling, so that the terminal can determine the communication parameters or resources for transmission based on these values ​​or information. Pre-configuration is similar to configuration. It can be a method by which network devices such as base stations or servers send parameter information or values ​​to the terminal via a communication link or carrier; it can also be a method by defining the corresponding parameters or parameter values ​​in a standard, or by setting the relevant parameters or values ​​in the terminal device in advance. This application does not limit this method. Furthermore, these values ​​and parameters can be changed or updated.

[0093] (2) In this application, “for indicating” can include both direct and indirect indication. When describing an indication information as indicating A, it can be understood that the indication information carries A, directly indicates A, or indirectly indicates A.

[0094] In this application, the information indicated by the instruction information is called the information to be instructed. In specific implementation, there are many ways to instruct the information to be instructed. For example, it can be implemented through direct instruction, such as through the information to be instructed itself or its index. It can also be implemented indirectly by instructing other information, where there is a relationship between the other information and the information to be instructed. Alternatively, only a part of the information to be instructed can be indicated, while the other parts are known or pre-agreed upon. For example, the instruction of specific information can be achieved by using a pre-agreed (e.g., protocol-defined) arrangement of various pieces of information, thereby reducing instruction overhead to some extent.

[0095] The information to be indicated can be sent as a whole or divided into multiple sub-information messages, and the sending period and / or timing of these sub-information messages can be the same or different. This application does not limit the specific sending method. The sending period and / or timing of these sub-information messages can be predefined, for example, according to a protocol, or configured by the transmitting device by sending configuration information to the receiving device. This configuration information can include, for example, but not limited to, one or a combination of at least two of RRC signaling, medium access control (MAC) layer signaling, and physical layer signaling. MAC layer signaling includes, for example, a medium access control control element (MAC CE); physical layer signaling includes, for example, downlink control information (DCI).

[0096] (3) The terms "system" and "network" in the embodiments of this application can be used interchangeably. "At least one" means one or more, and "more than one" means two or more. "And / or" describes the relationship between related objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, A and B exist simultaneously, or B exists alone, where A and B can be singular or plural. The character " / " generally indicates that the related objects before and after are in an "or" relationship. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, "at least one of A, B and C" includes A, B, C, AB, AC, BC or ABC. And, unless otherwise specified, the ordinal numbers such as "first" and "second" mentioned in the embodiments of this application are used to distinguish multiple objects and are not used to limit the order, sequence, priority or importance of multiple objects.

[0097] (4) In the embodiments of this application, "sending" and "receiving" indicate the direction of signal transmission. In this application, when entity A sends information to entity B, it can be that A sends directly to B, or A sends indirectly to B through other entities. Similarly, when entity B receives information from entity A, it can be that entity B receives the information sent by entity A directly, or entity B receives the information sent by entity A indirectly through other entities. Here, entities A and B can be RAN nodes or terminals, or modules within RAN nodes or terminals. The sending and receiving of information can be information interaction between RAN nodes and terminals, for example, information interaction between base stations and terminals; the sending and receiving of information can also be information interaction between two RAN nodes, for example, information interaction between CU and DU; the sending and receiving of information can also be information interaction between different modules within a device, for example, information interaction between a terminal chip and other modules of the terminal, or information interaction between a base station chip and other modules in 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.

[0098] (5) The artificial intelligence (AI) in this application embodiment enables machines to possess human-like intelligence, for example, allowing machines to use computer hardware and software to simulate certain intelligent human behaviors. To achieve artificial intelligence, machine learning methods can be employed. In machine learning methods, the machine learns (or trains) a model using training data. This model represents the mapping between input and output. The learned model can be used for reasoning (or prediction), that is, the model can be used to predict the output corresponding to a given input. This output can also be called the reasoning result (or prediction result).

[0099] (6) Routing ID: Used to identify the UE's serving LMF, which is information of the serving LMF configured locally by the UE. The routing ID will be referred to as the first identifier of the LMF in the following text.

[0100] (7) Correlation ID: Used to identify the UE's serving LMF. Hereafter, the correlation ID will be referred to as the LMF's second ID. The function of the LMF's second ID is similar to that of the LMF's first ID, the difference being that the LMF's first ID is used for identification between the AMF and the UE, while the LMF's second ID is used for identification between the LMF and the AMF.

[0101] (8) The positioning reference signal (PRS) is a downlink reference signal introduced in 3GPP Release 16, used for downlink positioning technology. In DL-TDOA (Downlink Time Difference of Arrival) positioning, the downlink time difference between two TRPs is measured based on the downlink PRS signal to determine the UE's location information; in Multi-RTT (Multi-Round Trip Time) positioning, the round-trip time delay between two TRPs is measured based on the uplink positioning SRS signal and the downlink PRS signal to determine the UE's location information; in DL-AoD positioning, the downlink departure angle (AoD) of multiple TRPs is measured based on the downlink PRS signal to determine the UE's location information.

[0102] (9) The sounding reference signal (SRS) is a reference pilot signal for the uplink wireless environment. It does not require any physical channel and is mainly used by base stations to measure uplink status information during wireless resource scheduling and wireless link adaptation.

[0103] The following is a full explanation of some of the English abbreviations used in this application.

[0104]

[0105]

[0106] References to "one embodiment" or "some embodiments" as described in this application mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0107] In the description of this application, unless otherwise stated, " / " means "or". For example, A / B can mean A or B. "And / or" in this document is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, and B alone. Furthermore, "at least one" means one or more, and "multiple" means two or more. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of single or multiple items. For example, at least one of a, b, or c can represent: a, b, c, a and b, a and c, b and c, or a and b and c. Where a, b, and c can be single or multiple.

[0108] With the rapid development of wireless communication technology, base stations, as core components of networks, are constantly expanding their functions and application scenarios. In recent years, the technology of using base stations for environmental sensing has gradually attracted attention. This technology is based on the interaction between the base station and its surrounding environment, and achieves the perception and monitoring of the surrounding environment by collecting and analyzing the signals received by the base station.

[0109] In the field of environmental sensing, traditional methods typically rely on specialized sensors and equipment, such as cameras, radar, or infrared detectors. However, these methods have several drawbacks, including high cost, difficult deployment, and susceptibility to weather conditions. In contrast, utilizing base stations for environmental sensing offers numerous advantages.

[0110] Base stations offer extensive coverage. As the infrastructure of wireless communication networks, base stations typically cover entire cities or specific areas. This means that using base stations for environmental sensing enables real-time monitoring of large areas, providing valuable data support for urban planning, traffic management, disaster early warning, and other fields. Secondly, base stations are continuously online. They need to provide communication services to users 24 hours a day, so they are always operational. This allows for real-time, continuous data collection and analysis for environmental sensing, enabling timely detection and handling of environmental problems. Furthermore, using base stations for environmental sensing can reduce costs. Since base stations are already widely deployed in cities, there is no need to install a large number of additional sensors and equipment. Simply upgrading and modifying existing base stations is sufficient to achieve environmental sensing and monitoring. This not only saves significant investment costs but also avoids redundant construction and resource waste.

[0111] When using base stations for sensing, there is a limitation in coverage; base stations can only effectively sense and detect strongly reflective targets within the visible area. For example... Figure 1 As shown, for a base station, the sensing area is divided into line-of-sight (LOS) and non-line-of-sight (NLOS) areas. Due to obstruction by obstacles, targets in the NLOS area cannot be effectively sensed. For the NLOS area, terminal devices can be introduced to assist the base station in sensing. For example, ... Figure 2 As shown, the terminal device assists the base station in achieving environmental perception. Specifically, the base station sends a sensing reference signal, which is reflected by a reflector and then by a cylinder before reaching the terminal device. The terminal device can measure this sensing reference signal to obtain the sensing measurement result. Both the reflector and the cylinder can be considered sensing targets. If multiple sensing targets need to be detected, different beams need to be used to send the sensing reference signal, thereby improving the detection accuracy of the sensing targets.

[0112] The following describes the communication system to which this application applies. This application also applies to other communication systems, but it does not limit the specific systems described herein.

[0113] Figure 3-1 This is a schematic diagram of a communication system according to an embodiment of this application. Please refer to... Figure 3-1The communication system includes terminal equipment 301, next generation node B (gNB) 302, next generation evolved node B (ng-eNB) 303, access and mobility management function (AMF) 304, location management function (LMF) 305, and sensing management function (SMF) 306.

[0114] Among them, terminal device 301 connects to access network equipment (such as Uu interface) via Uu interface. Figure 3-1 The system communicates with the gNB302 or ng-eNB303 in the LTE communication system. The ng-eNB303 is the access network device in the LTE communication system, and the gNB302 is the access network device in the New Radio (NR) communication system. In this communication system, access network devices communicate with each other via the Xn interface, and access network devices communicate with the AMF304 via the NG-C interface. The AMF304 and LMF305 communicate via the NL1 interface; the AMF304 acts as a router for communication between the access network devices and the LMF305. The LMF305 is a network element, module, or component in the NR core network that provides positioning functionality for terminal devices. The LMF305 is used to calculate the location of the terminal devices. The SMF306 can store environmental maps and reconstruct them; it interacts with the LMF305 to exchange environmental and measurement information.

[0115] The above Figure 3-1 In the communication system shown, LMF305 and SMF306 are two network elements deployed separately. In practical applications, LMF305 and SMF306 can also be deployed together or integrated, meaning LMF305 and SMF306 are the same network element. This application does not specify the specifics. For example, Figure 3-2 As shown, the LMF305 and SMF306 are deployed or integrated together to form a single network element that provides sensing and positioning capabilities.

[0116] The above Figure 3-1 and Figure 3-2 This example only illustrates a communication system comprising two access network devices: a gNB and an ng-eNB. In practical applications, the communication system may include at least one access network device; this application does not specify a particular device.

[0117] In this application, the above Figure 3-1 andFigure 3-2 In the communication systems shown, LMF is the current name used in the communication system. In future communication systems, the name of LMF may change as the communication system evolves. For example, LMF can also be called a positioning device, positioning center, positioning server, positioning management device, or positioning management function device. This application does not specifically limit the name of LMF. In current or future communication systems, any functional network element with a similar function to LMF, even with other names, can be understood as LMF in the embodiments of this application, and is applicable to the information transmission and information reception methods provided in the embodiments of this application.

[0118] In this application, the above Figure 3-1 and Figure 3-2 In the communication systems shown, the name of the SMF may change as the communication system evolves. Any functional network element with a name similar to SMF can be understood as the SMF of this application and is applicable to the method provided in this application. For example, SMF can also be a communication sensing function, location management function, sensing management function entity, sensing function network element, sensing network element, sensing server, location server, or other names. Specifically, this application does not limit the name of the SMF. The following embodiments mainly use the description method of SMF to introduce the execution operation of this functional network element.

[0119] Figure 3-3 This illustration schematically depicts a 5G network architecture based on service-oriented interfaces. This application does not limit the specific structure of the 5G network; for example, a 5G network may include more or fewer network elements. Figure 3-3 One or more network elements in the network can be replaced with other network elements. This application does not limit the scope of network elements. Figure 3-3 The functions of each network element, and the names and / or functions of the network elements may change as the communication system evolves.

[0120] The technical solution of this application can be applied to cellular communication systems related to the 3rd Generation Partnership Project (3GPP). For example, 4th generation (4G) communication systems, 5G communication systems, and communication systems beyond the 5th generation. For example, the 6th generation communication system. For example, the 4th generation communication system may include the Long Term Evolution (LTE) communication system. The 5th generation communication system may include the New Radio (NR) communication system. The technical solution of this application can also be applied to Wireless Fidelity (WiFi) systems, communication systems supporting the convergence of multiple wireless technologies, device-to-device (D2D) systems, or V2X communication systems.

[0121] The following describes the terminal equipment, access network equipment, sensing management function, and positioning management function involved in this application.

[0122] Terminal equipment, also known as user equipment (UE), mobile station (MS), mobile terminal (MT), fixed wireless access (FWA), customer premises equipment (CPE), etc., refers to devices that include wireless communication functions (providing voice / data connectivity to users). Examples include handheld devices with wireless connectivity, vehicle-mounted devices, and MTC terminals. Currently, terminal devices can include: mobile phones, tablets, laptops, PDAs, mobile internet devices (MIDs), wearable devices, virtual reality (VR) devices, augmented reality (AR) devices, wireless terminals in industrial control, wireless terminals in self-driving (e.g., drones, vehicles), wireless terminals in remote medical surgery, wireless terminals in smart grids, wireless terminals in transportation safety, wireless terminals in smart cities, and wireless terminals in smart homes. For example, wireless terminals in self-driving can be drones, helicopters, or airplanes. For example, wireless terminals in vehicle-to-everything (V2X) can be in-vehicle equipment, vehicle-mounted equipment, in-vehicle modules, vehicles, or ships. Wireless terminals in industrial control can be cameras, robots, or robotic arms. Wireless terminals in smart homes can be televisions, air conditioners, robot vacuums, speakers, or set-top boxes. The terminal device can also be a device or module that is connected to the communication system shown above and has corresponding communication functions. The terminal device typically contains a communication module, circuit, or chip that performs the corresponding communication functions, and it also contains program instructions for performing those functions. In the following text, the terminal device will be described as a UE (User Equipment).

[0123] It should be noted that the UE can be a device or apparatus with a chip, or a device or apparatus with integrated circuitry, or a chip, chip system, module, or control unit in the device or apparatus shown above; this application does not impose any specific limitation. It should also be noted that in this application, when referring to the UE, it can refer to the UE itself, or to the chip, functional module, or integrated circuit within the UE that performs the method provided in this application; this application does not impose any specific limitation.

[0124] Access network equipment is a device deployed in a radio access network to provide wireless communication functions for a UE. Access network equipment enables a UE to access a radio access network (RAN) node of a wireless network, and may also be referred to as a wireless access device, access network equipment, RAN entity, access node, network node, or communication device, etc.

[0125] Specifically, the access network equipment can be an access network device for a 3GPP-related cellular system, such as a 4G communication system or a 5G communication system. The access network equipment can also be an access network device in an open RAN (O-RAN or ORAN) or a cloud radio access network (CRAN). Alternatively, the access network equipment can also be an access network device in a communication system formed by the integration of two or more of the above communication systems.

[0126] Access network equipment includes, but is not limited to: evolved Node B (eNB), RNC, Node B (NB), basestation controller (BSC), base transceiver station (BTS), home base station (e.g., home evolved Node B, or home Node B, HNB), baseband unit (BBU), access point (AP) in wireless fidelity (WIFI) systems, macro base station, micro base station, wireless relay node, donor node, radio controller in CRAN scenarios, wireless backhaul node, transmission point (TP), or transmission and reception point (TRP), etc., and can also be access network equipment in 5G mobile communication systems. For example, next-generation base station (gNB) in NR systems, TRP, TP; or one or a group of antenna panels (including multiple antenna panels) of a base station in a 5G mobile communication system; or, access network equipment can also be network nodes constituting gNB or transmission point. Examples include centralized units (CUs), distributed units (DUs), centralized unit control planes (CU-CPs), centralized unit user planes (CU-UPs), and radio units (RUs). CUs and DUs can be separate entities or included in the same network element, such as a BBU. RUs can be included in radio equipment or radio units, such as remote radio units (RRUs), active antenna units (AAUs), or remote radio heads (RRHs). Alternatively, access network equipment can be servers, wearable devices, vehicles, or in-vehicle equipment. For example, in V2X technology, access network equipment can be roadside units (RSUs). It should be understood that the aforementioned TRP can be a device or module located on the network side of the communication system and possessing corresponding communication functions. The TRP typically contains communication modules, circuits, or chips that perform the corresponding communication functions. The TRP can also be configured with program instructions for the corresponding communication functions.

[0127] It should be noted that CU (or CU-CP and CU-UP), DU, or RU may have different names in different systems, but those skilled in the art will understand their meaning. For example, in an open radio access network (ORAN) system, CU can also be called an open centralized unit (O-CU) or an open CU, DU can also be called an open distributed unit (O-DU), CU-CP can also be called an open centralized unit control plane (O-CU-CP), CU-UP can also be called an open centralized unit user plane (O-CU-UP), and RU can also be called an open radio unit (O-RU). This application does not impose any specific limitations on these names. Any of the units CU, CU-CP, CU-UP, DU, and RU in this application can be implemented through software modules, hardware modules, or a combination of software and hardware modules.

[0128] Optionally, for network elements in the ORAN system, each network element can implement the protocol layer functions shown in Table 1 below.

[0129] Table 1

[0130]

[0131] It should be noted that in the ORAN system, the access network equipment in this application can be one or more network elements listed in Table 1 above.

[0132] The architecture of the CU and DU of the access network equipment is described below. An access network equipment includes at least one CU and at least one DU. Optionally, the access network equipment may also include at least one RU.

[0133] The following example uses an access network device consisting of one CU and one DU. The CU has some core network functions and can include CU-CP and CU-UP. The CU and DU can be configured according to the protocol layer functions of the wireless network they implement. For example, the CU may be configured to implement the Packet Data Convergence Protocol (PDCP) layer and above (e.g., RRC and / or SDAP layers). The DU may be configured to implement protocol layers below the PDCP layer (e.g., RLC, MAC, and / or physical (PHY) layers). Alternatively, the CU may be configured to implement protocol layers above the PDCP layer (e.g., RRC and / or SDAP layers), and the DU may be configured to implement protocol layers below the PDCP layer (e.g., RLC, MAC, and / or PHY layers).

[0134] When a CU includes CU-CP and CU-UP, CU-CP is used to implement the control plane functions of the CU, and CU-UP is used to implement the user plane functions of the CU. For example, when a CU is configured to implement the functions of the PDCP layer, RRC layer, and SDAP layer, CU-CP is used to implement the RRC layer functions and the control plane functions of the PDCP layer, and CU-UP is used to implement the SDAP layer functions and the user plane functions of the PDCP layer.

[0135] The CU-CP can interact with network elements in the core network used to implement control plane functions. These network elements can be access and mobility function (AMF) network elements, such as the AMF in a 5G system. The AMF is responsible for mobility management in the mobile network, such as UE location updates, UE network registration, and UE handover.

[0136] CU-UP can interact with network elements in the core network used to implement user plane functions. These network elements, such as the user plane function (UPF) in a 5G system, are responsible for forwarding and receiving data in the UE.

[0137] The above CU and DU configurations are merely examples; the functions of the CU and DU can be configured as needed. For instance, the CU or DU can be configured to have more protocol layer functions, or only some protocol layer processing functions. For example, some RLC layer functions and protocol layer functions above the RLC layer can be placed in the CU, while the remaining RLC layer functions and protocol layer functions below the RLC layer can be placed in the DU. Furthermore, the functions of the CU or DU can be divided according to service type or other system requirements. For example, based on latency, functions that require low latency can be placed in the DU, while functions that do not require low latency can be placed in the CU.

[0138] DU and RU can cooperate to implement the functions of the PHY layer. A DU can be connected to one or more RUs. The functions of DU and RU can be configured in various ways depending on the design. For example, a DU can be configured to implement baseband functions, and an RU can be configured to implement mid-RF functions. Another example is that a DU can be configured to implement higher-level functions in the PHY layer, and an RU can be configured to implement lower-level functions in the PHY layer, or to implement both lower-level and RF functions. Higher-level functions in the physical layer can include a portion of the physical layer's functions that are closer to the MAC layer, while lower-level functions in the physical layer can include another portion of the physical layer's functions that are closer to the mid-RF side.

[0139] It should be noted that the access network equipment can be a device or apparatus with a chip, or a device or apparatus with integrated circuits, or a chip, chip system, module, or control unit in the aforementioned device or apparatus; this application does not impose any specific limitation. It should also be noted that in this application, the term "access network equipment" can refer to the access network equipment itself, or to the chip, functional module, or integrated circuit within the access network equipment that performs the method provided in this application; this application does not impose any specific limitation.

[0140] The following text uses gNB as an example of access network equipment.

[0141] AMF: Access and Mobility Management Function, mainly responsible for user registration, reachability, mobility management, N1 / N2 interface signaling transmission, access authentication and authorization, etc.

[0142] NRF: Network Memory Function, which provides the ability to register and discover network elements in the network.

[0143] NWDAF: It has data collection, training, analysis, and inference functions. It can be used to collect relevant data from network elements, third-party service servers, terminal devices, or network management systems, perform analysis and training based on the 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, or assist the network in performing traffic routing, or assist the network in selecting background data transmission strategies, etc.

[0144] Traditional wireless positioning algorithms (such as DL-TDOA, DL-AOD, UL-TDOA, UL-AOA, etc.) exhibit poor positioning accuracy in certain scenarios, failing to meet the demands of high-precision positioning. For example, traditional positioning algorithms typically require measurement information from at least three paths to estimate location. However, in heavily non-line-of-sight (NLOS) environments, it is nearly impossible to find at least three line-of-sight (LOS) paths that can be used simultaneously to calculate location. This can lead to stronger NLOS paths being mistakenly identified as LOS paths, while the measurement signals of NLOS paths are weaker, resulting in poor positioning accuracy for traditional algorithms. Alternatively, in light / moderate NLOS environments, even with a sufficient number of LOS paths, misidentification of LOS paths can still occur, leading to poor positioning accuracy for traditional algorithms.

[0145] To address the issue of poor accuracy in traditional positioning algorithms under NLOS environments, such as 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: positioning enhancement based on access network equipment, positioning enhancement based on positioning management function network elements, and positioning enhancement based on the UE. Since the AI ​​model discussed in this application is used for positioning scenarios, the AI ​​model mentioned in this application can refer to an AI positioning model. Currently, various AI positioning scenarios are discussed in the 3GPP standard. This application mainly considers scenarios where the AI / ML model is located in the LMF (Local Multi-Function), or in other words, the AI ​​model mentioned in this application can specifically be an AI / ML model.

[0146] Depending on the output of the AI / ML model, this localization scenario can be further divided into two categories. One is A-AIML, where the AI / ML model outputs intermediate localization information, such as the path's LOS / NLOS probability or TOA estimation. After obtaining this intermediate localization information, the LMF still needs to estimate the UE's position based on this information and traditional localization algorithms. The other is D-AIML, where the AI / ML model outputs an estimated UE position or a UE position estimation result. The following discussion uses a D-AIML model as an example, where the AI ​​model processes the input data to produce the UE's position.

[0147] During AI model inference, the input data (or inference data) typically includes measurement data reported by the UE / gNB. Depending on the type and source of the measurement data, this positioning scenario is further subdivided into Positioning Scenario 1 (or Downlink Positioning Scenario) and Positioning Scenario 2 (or Uplink Positioning Scenario). The difference lies in the measurement data used by the AI ​​model and its source. For example... Figure 4-1 As shown, in positioning scenario 1, the measurement data can be the measurement data obtained by the UE from measuring the PRS signal (referred to as PRS measurement data), and the data source is the UE. For example... Figure 4-2 As shown, in positioning scenario 2, the measurement data can be the measurement data obtained by the gNB from the SRS signal (referred to as SRS measurement data), and the data source is the gNB. The similarity between the two is that the LMF can perform inference on the collected measurement data based on a local AI model to obtain inference results, such as an estimate of the UE's location.

[0148] The AI ​​model can be pre-configured on the LMF, for example, configured at the factory or by the network management system, or it can be trained by the LMF or other network elements. Depending on the network element performing the training, this localization scenario includes two categories. One category is where the LMF collects data and trains the model itself. The LMF performs AI localization based on the trained AI model and the collected data. For clarity, the data used to train the AI ​​model, or the input data of the AI ​​model during training, will be referred to as the training data of the AI ​​model. The other category is where the AI ​​model is obtained by the LMF from other network elements, such as from the NWDAF or the MTLF within the NWDAF. 5G networks introduce the NWDAF network element, which is divided into MTLF and AnLF. The MTLF can collect data from the network and train AI / ML models based on this data, and can provide the trained model to the AnLF upon request. The AnLF can perform data statistics and inference, or perform model inference based on the AI / ML model, derive corresponding analysis results according to consumer (consumer) requests (e.g., AMF / SMF / PCF, etc.), and make these analysis results available to the consumer. In the scenario where LMF obtains AI models from MTLF, MTLF can obtain training data for the AI ​​model from LMF, use the data to train the AI ​​model, and then send the trained AI model back to LMF. LMF then performs AI localization based on the AI ​​model and inference data.

[0149] In other words, regardless of whether the AI ​​model is trained by LMF or MTLF, LMF needs to collect the training data for the AI ​​model. If LMF trains the AI ​​model itself, then LMF collects the training data for the AI ​​model itself; if MTLF trains the model, then MTLF also needs to collect the training data through LMF.

[0150] For ease of description, the network element used to request training data for the AI ​​model from the LMF will be referred to as the AI ​​training data consumer (MTLF or NWDAF), and the network element used to request AI localization results from the LMF will be referred to as the AI ​​inference result consumer (e.g., AMF / SMF / PCF, etc.). Both the AI ​​training data consumer and the AI ​​inference result consumer will be collectively referred to as the AI ​​consumer. This application does not limit the types of AI training data consumers and AI inference result consumers; the following text uses MTLF as the AI ​​training data consumer and AMF as the AI ​​inference result consumer as an example.

[0151] The training data for AI models includes not only measurement data reported by the UE / gNB, but also labels corresponding to the measurement data, such as the estimated UE location based on the measurement data. Similarly, the training data for AI models collected by the LMF from the UE / gNB includes not only measurement data, but also labels (i.e., UE location). In downlink positioning scenarios, the LMF can collect training data from the UE via the LPP protocol; in uplink positioning scenarios, the LMF can collect training data from the gNB via the NRPPa protocol.

[0152] In this application, the measurement data used for the AI ​​model may include inference data for the AI ​​model and / or training data for the AI ​​model. As described above, the training data for the AI ​​model may include not only the measurement data reported by the UE / gNB, but also the corresponding tags for the measurement data. The term "measurement data used for the AI ​​model including training data" can mean that it includes all or part of the training data, for example, including the measurement data reported by the UE / gNB and the corresponding tags, or simply the measurement data reported by the UE / gNB. The measurement data used for the AI ​​model may also be referred to as data used for the AI ​​model, AI (measurement) data, AI positioning (measurement) data, or simply measurement data, etc. For ease of distinction, the measurement data reported by the UE / gNB in ​​the training data for the AI ​​model will be referred to as the UE / gNB's AI (measurement) data. In practical applications, the measurement data reported by the UE / gNB in ​​the training data of the AI ​​model can be called measurement data applied to the AI ​​model, data used for the AI ​​model, AI (measurement) data, (measurement) data used for AI positioning, or measurement data, etc.

[0153] However, regardless of whether it is positioning scenario 1 or positioning scenario 2, the measurement data that LMF needs to collect for the AI ​​model is different from the measurement data that LMF needs to collect when using traditional wireless positioning algorithms.

[0154] For example, the data required for the DL-TDOA positioning method includes DL RSTD and DL PRS RSRP; the data required for the UL-TDOA positioning method includes UL RTOA and UL SRS-RSRP; and the data required for UL-AoA includes UL AoA / ZoA (UL SRS-RSRP). The AI ​​model for positioning scenario 1 requires data that can include DL-CIR and DL-channel power delay profile (PDP). The AI ​​model for positioning scenario 2 requires data that can include UL-CIR and UL-PDP.

[0155] Therefore, UE / gNB needs to be enhanced to enable it to provide measurement data for AI models. However, in practice, not all UE / gNBs are enhanced. Therefore, the LMF's service area may not have any enhanced UE / gNBs, or some UE / gNBs in the LMF's service area may be enhanced while others are not. For unenhanced UE / gNBs, the LMF requests measurement data for AI models, but the UE / gNB cannot return the corresponding data. However, for enhanced UE / gNBs, the LMF requests the measurement data for AI models, and the UE / gNB can return the corresponding data.

[0156] However, it is currently unclear how the LMF determines whether a specific UE / gNB can support providing measurement data for AI models. The UE and LMF can negotiate supported capabilities via the LPP protocol; for example, the LMF requests capabilities from the UE, and the UE reports the supported capabilities. For instance, currently, for different positioning methods, the UE may support corresponding data measurement capabilities. For example, for DL-TDOA, the UE's supported capability information might include DL-TDOA positioning capabilities and / or DL-TDOA data measurement capabilities and / or DL-PRS-RSRP measurement capabilities. However, based on the existing data measurement capabilities reported by the UE, the LMF cannot determine whether a specific UE / gNB (e.g., a UE / gNB within its own service area) can support providing measurement data for AI models.

[0157] If there are no enhanced UEs / gNBs in the LMF's service area, when the LMF needs to collect measurement data for the AI ​​model, it will still request the collection of measurement data from each UE / gNB in ​​the service area. Only when the timer expires or all UEs / gNBs fail to respond can the LMF determine that there are no enhanced UEs / gNBs in its service area. This not only wastes the processing resources of both the LMF and the UEs / gNBs but also consumes excessive signaling resources.

[0158] Furthermore, when there are no enhanced UEs / gNBs within the LMF's service area, the LMF cannot collect measurement data for the AI ​​model, and therefore cannot use the AI ​​model for inference as requested by the AMF, nor can it provide training data for the AI ​​model to the MTLF as requested. In existing solutions, the AI ​​positioning capability of the LMF mainly refers to whether the LMF supports using AI models to calculate the UE's location, without considering whether the LMF can discover UEs / gNBs that support AI capabilities and collect measurement data from them. For example, even if the AMF discovers an LMF that supports AI positioning, because that LMF cannot collect AI positioning-related measurement data from the UE / gNB, the LMF still cannot use the AI ​​positioning method to calculate the UE's location.

[0159] However, it is currently unclear how the AMF or MTLF determines whether a particular LMF is an enhanced LMF, i.e., capable of providing measurement data for AI models. If the LMF is unable to collect and / or provide measurement data for AI models, the AI ​​consumer still sends requests to the LMF to request it to perform model processing operations related to collecting measurement data for AI models. This can easily lead to long waiting times for the AI ​​consumer, waste processing resources for both the AI ​​consumer and the LMF, and consume excessive signaling resources.

[0160] To facilitate the LMF's ability to detect the presence of enhanced UEs within its service area, or to determine whether a specific UE within its service area is an enhanced UE, in AI positioning scenarios, this application proposes defining UE AI capability information. This AI capability information indicates that the UE supports providing measurement data for AI models. By acquiring the UE's AI capability information, the LMF can determine the presence of enhanced UEs within its service area, and these UEs can provide measurement data to the LMF for AI models.

[0161] Similarly, to enable the LMF to detect the presence of enhanced gNBs within its service area, or to determine whether a specific gNB within its service area is an enhanced gNB, in AI localization scenarios, this application proposes defining AI capability information for gNBs. This AI capability information indicates that the gNB supports providing measurement data for AI models. By receiving the gNB's AI capability information, the LMF can determine the presence of enhanced gNBs within its service area, and these gNBs can provide measurement data for AI models to the LMF.

[0162] To facilitate AI consumers' ability to perceive the existence of enhanced LMFs, or whether a specific LMF is an enhanced LMF, this application proposes defining AI capability information for an LMF. This AI capability information indicates that the LMF supports providing measurement data for AI models. AI consumers (e.g., AMFs or MTLFs) can determine the existence of an enhanced LMF by receiving its AI capability information, and that the LMF can collect and / or provide measurement data for AI models.

[0163] In the following text, "enhanced UE" can refer to a UE that supports AI capabilities or a UE that supports providing measurement data for AI models; "enhanced gNB" can refer to a gNB that supports AI capabilities or a gNB that supports providing measurement data for AI models; "enhanced LMF" can refer to an LMF that supports AI capabilities or an LMF that supports providing measurement data for AI models; and "AI capability information" can refer to AI capability existence indication information. In the communication method provided in this application, "AI capability" can refer to AI positioning capability, and the two are interchangeable. Correspondingly, "AI capability information" can refer to AI positioning capability information, and the two are interchangeable.

[0164] The following are examples of several possible methods based on this inventive concept.

[0165] Figure 5 This illustration shows one possible flow of the communication method provided in this application. For example... Figure 5 As shown, the communication method provided in this application may include a process for associating AI capability information of a UE, and the process for associating AI capability information of a UE may include S501a to S505a. Figure 5 The AI ​​capability information association process of the UE shown can be an example of the first method for LMF perception-enhanced UEs.

[0166] S501a, the UE sends information 1-1 to the AMF, and the AMF receives information 1-1 sent by the UE accordingly;

[0167] Information 1-1 may include the UE's AI capability information, which indicates that the UE supports providing measurement data for AI models. Optionally, Information 1-1 may be a UL NAS message or carried within a UL NAS message.

[0168] Information 1-1 may include the first identifier of the LMF and the AI ​​capability association request, which may include the UE's AI capability information.

[0169] Optionally, the UE's AI capability information is used to indicate the type of AI capability supported by the UE. For example, the UE's AI capability information is used to indicate that the UE supports AI downlink positioning capability, or supports AI downlink data measurement capability, or supports providing AI downlink measurement data.

[0170] Optionally, the UE's AI capability information can be used to indicate the types of measurement data that the UE supports providing. For example, the UE's AI capability information may indicate that the UE supports providing CIR measurement data and / or PDP measurement data.

[0171] Optionally, the AI ​​capability association request may also include an association reason, which may be the initial association of the UE's AI capability information or the update of the UE's AI capability information, etc.

[0172] S502a and AMF verify the AI ​​capability information of the UE;

[0173] After receiving the 1-1 message, the AMF can verify whether the UE truly supports AI capabilities, i.e., whether it supports providing measurement data for the AI ​​model. As mentioned above, the AI ​​model mentioned in this application can refer to an AI positioning model or a D-AIML model.

[0174] This application does not limit the method by which the AMF verifies whether the UE truly supports AI capabilities. For example, the AMF can obtain the UE's subscription information from the UDM to check whether the UE supports AI capabilities, or the AMF can determine whether the UE supports AI capabilities based on configured local policies.

[0175] In practical applications, UDM can be replaced by UDR or other network elements, as long as the network element can be used to provide services for storing the subscription information of UE and / or gNB.

[0176] S503a, AMF sends information 1-2 to LMF, and correspondingly, LMF receives information 1-2 sent by AMF;

[0177] AMF can send information 1-2 to LMF, which includes the UE's AI capability information or AI capability association request.

[0178] Optionally, information 1-2 may also include the UE's ID (e.g., SUPI) so that the LMF can identify UEs that support AI capabilities.

[0179] Optionally, information 1-2 may also include the UE's location information. This application does not limit the type of the UE's location information; for example, the UE's location information may include TAI and / or cell ID.

[0180] Step S502a is optional. After receiving information 1-1, the AMF can send information 1-2 to the LMF without verifying whether the UE truly supports AI capabilities. Based on the execution of S502a, the AMF can send information 1-2 to the LMF if the verification is successful (i.e., the UE supports AI capabilities).

[0181] S504a, LMF sends information 1-3 to AMF;

[0182] After receiving information 1-2, LMF can determine whether the UE supports AI capabilities based on the UE's AI capability information in information 1-2.

[0183] LMF can store the UE's AI capability information from information 1-2, and can also store some or all of other information. For example, LMF can also associate the UE's AI capability information with and store the UE ID and / or the UE's location information, etc.

[0184] The LMF can also send messages 1-3 to the AMF, which can be a response message to message 1-2. Message 1-3 may include association result information, which can be used to instruct the LMF to accept the AI ​​capability association request of the associated UE or reject the AI ​​capability association request of the UE.

[0185] Information 1-3 may also include a second identifier for the LMF.

[0186] S505a, AMF sends information 1-4 to UE, and correspondingly, UE receives information 1-4 sent by AMF;

[0187] After receiving information 1-3 from the LMF, the AMF can send information 1-4 to the UE. Information 1-4 may include the association result information from information 1-3 and the first identifier of the LMF. Optionally, information 1-4 may be a DL NAS message or be carried in a DLNAS message.

[0188] S504a-S505a are optional steps.

[0189] In Message 1-1, the first identifier of the LMF is used to instruct the AMF to send Message 1-1 to the LMF to transmit the UE's AI capability information to the LMF. This application does not limit the method by which the UE transmits its AI capability information to the LMF, nor does it limit Message 1-1 to necessarily carrying the first identifier of the LMF, as long as the UE can transmit 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, in which case Message 1-1 can be Message 1-2.

[0190] The UE ID in Information 1-2 is used to instruct the LMF to identify UEs that support AI capabilities. This application does not limit the method by which the LMF identifies the UE.

[0191] The UE location information in Information 1-2 is used to instruct the LMF to determine the location of UEs that support AI capabilities. In this way, the LMF can not only determine that there are UEs that support AI capabilities in its own service area, but also determine the location of UEs that support AI capabilities. This is beneficial for more accurately determining the enhanced UE sub-area in its service area based on the location of UEs that support AI capabilities. In other words, the LMF supports providing measurement results reported by UEs in this sub-area for AI models.

[0192] Continue to refer to Figure 5 The communication method provided in this application may include the AI ​​capability information association process of gNB, and the AI ​​capability information association process of gNB may include S501b to S505b. Figure 5 The AI ​​capability information association process shown for gNB can be an example of the first method for LMF perception-enhanced gNB.

[0193] S501b and gNB send information 1-5 to AMF, and AMF receives information 1-5 sent by gNB accordingly;

[0194] S502b and AMF verify the AI ​​capability information of gNB;

[0195] S503b, AMF sends information 1-6 to LMF;

[0196] S504b, LMF sends information 1-7 to AMF;

[0197] S505b and AMF send information 1-8 to gNB;

[0198] S501b to S505b can be understood by referring to the contents of S501a to S505a in sequence. For example, S501b can be understood by referring to the content after replacing UE with gNB in ​​S501a; S502b can be understood by referring to the content after replacing UE with gNB in ​​S502a; S503b can be understood by referring to the content after replacing UE with gNB in ​​S503a; S504b can be understood by referring to the content after replacing UE with gNB in ​​S504a; and S505b can be understood by referring to the content after replacing UE with gNB in ​​S505a. For example, information 1-5 can be understood by referring to information 1-1; information 1-6 can be understood by referring to information 1-2; information 1-7 can be understood by referring to information 1-3; and information 1-8 can be understood by referring to information 1-4.

[0199] After receiving AI capability information from the UE and / or gNB, the LMF can determine that it supports AI capabilities. Optional, continue to refer to... Figure 5 The communication method provided in this application may also include a process for LMF to register its own AI capability information, and the process for LMF to register its own AI capability information may include S506 to S507.

[0200] S506, LMF sends information 1-9 to NRF, and correspondingly, NRF receives information 1-9 sent by LMF;

[0201] Based on the AI ​​capability information received by the LMF from the UE and / or the gNB, the LMF can determine that it supports AI capabilities. The LMF can send information 1-9 to the NRF. Information 1-9 may include the LMF's AI capability information.

[0202] Optionally, based on the successful association of the AI ​​capability information of the LMF and UE and / or the AI ​​capability information of the gNB, the LMF can further register its own AI capability information with the NRF. Information 1-9 can be a registration request message sent by the LMF to the NRF or carried in such a registration request message.

[0203] Optionally, information 1-9 may also include location information associated with the AI ​​capability information of the LMF, which indicates that the LMF has the AI ​​capability at the location or area indicated by the location information. The LMF may determine the location information to be associated with the AI ​​capability information of the LMF based on the location of the UE and / or gNB that support the AI ​​capability within the service area.

[0204] This application does not limit the type of location information; for example, the location information can be TAI and / or cell ID.

[0205] In this application, the AI ​​capability information of the LMF may include 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 whether the LMF can provide AI measurement data on the UE side; whether the LMF can collect AI measurement data from the gNB, or whether the LMF can provide AI measurement data on the gNB side.

[0206] S507 and NRF send information 1-10 to LMF, and correspondingly, LMF receives information 1-10 sent by NRF;

[0207] After receiving information 1-9, the NRF can save the AI ​​capability information of the LMF, as well as some or all of the other information in information 1-9. For example, the NRF can also save the location information associated with the AI ​​capability information of the LMF.

[0208] Optionally, the NRF can also send messages 1-10 to the LMF. Messages 1-10 can be a registration response message of messages 1-9 or carried in the message to indicate whether the LMF registration was successful.

[0209] After an LMF registers its AI capabilities, it helps AI consumers (such as AMFs or MTLFs) to identify an LMF as an enhanced LMF by querying its registration information. This LMF supports the collection and / or provision of measurement data for AI models.

[0210] Figure 6-1 This illustration shows another possible flow of the communication method provided in this application. For example... Figure 6-1 As shown, the communication method provided in this application may include a process for obtaining AI capability information of a UE, and the process for obtaining AI capability information of a UE may include S601a to S602a. Figure 6-1 The process for obtaining AI capability information for the UE shown can be an example of a second method for LMF-enhanced perception UEs.

[0211] S601a, LMF sends information 2-1 to UE, and correspondingly, UE receives information 2-1 sent by LMF;

[0212] Message 2-1 can be used to request AI capability information from the UE. The LMF can send Message 2-1 to the UE via the LPP protocol. Message 2-1 can be a capability request message or carried within a capability request message.

[0213] 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, information 2-1 may include field 1, which may be “NR-DL-AIPositioning-ProvideCapabilities-r19”, indicating a request for AI downlink positioning capability. For example, information 2-1 may include field 2, which may be, for example, “NR-DL-AIPositioning-MeasurementCapability-r19”, indicating a request for AI downlink positioning data measurement capability. For example, information 2-1 may include field 3, which may be “supportOfDL-CIR-MeasFR1-r19”, indicating a request for downlink CIR measurement capability. For example, information 2-1 may include field 4, which may be “supportOfDL-PDP-MeasFR1-r19”, indicating a request for downlink PDP measurement capability.

[0214] S602a, the UE sends information 2-2 to the LMF, and the LMF receives information 2-2 sent by the UE accordingly;

[0215] After receiving information 2-1, the UE can send information 2-2 to the LMF. Information 2-2 may include the UE's AI capability information. The UE can send information 2-2 to the LMF via the LPP protocol. Information 2-2 can be a response message to information 2-1.

[0216] Optionally, the UE's AI capability information can be used to indicate the types of measurement data that the UE supports providing. For example, the UE's AI capability information may indicate that the UE supports providing CIR measurement data and / or PDP measurement data.

[0217] The AI ​​capability or measurement data type indicated by the UE's AI capability information in Message 2-1 can be all or part of the types indicated in Message 2-1. The UE's AI capability information in Message 2-1 does not indicate that the UE supports AI capabilities or data types not requested in Message 2-1. For example, if Message 2-1 is used to request downlink PDP measurement capabilities, even if the UE supports providing CIR measurement data, Message 2-2 may not indicate that the UE supports providing CIR measurement data. Optionally, Message 2-1 may also indicate that the UE does not support AI capabilities, or indicate the types of AI capabilities that are not supported.

[0218] Taking information 2-1, which includes fields 1 to 4 as an example, information 2-2 can be as follows.

[0219] -->ProvideCapabilities information

[0220] -->AI downlink positioning capabilities (NR-DL-AIPositioning-ProvideCapabilities-r19)

[0221] -->AI downlink data measurement capability (NR-DL-AIPositioning-MeasurementCapability-r19)

[0222] Downlink CIR measurement capability (supportOfDL-CIR-MeasFR1-r19)

[0223] -->Downlink PDP measurement capability (supportOfDL-PDP-MeasFR1-r19)

[0224] This application does not limit the way 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 by taking the value corresponding to field 1.

[0225] S601a is an optional step; in some examples, the UE can directly send information 2-2 to the LMF.

[0226] Continue to refer to Figure 6-1 The communication method provided in this application may include the AI ​​capability information acquisition process of gNB, which may include S601b to S602b. Figure 6-1 The process for acquiring AI capability information of gNB shown can be an example of a second method for LMF-based perception-enhanced gNB.

[0227] S601b, LMF sends information 2-3 to gNB, and gNB receives information 2-3 sent by LMF accordingly;

[0228] Message 2-3 can be used to request AI capability information from the gNB. For example, the LMF can send message 2-3 to the gNB via the NRPPa protocol. Message 2-3 can be a capability request message or be included in a capability request message.

[0229] 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, information 2-3 may include field 5, which could be “NR-UL-AIPositioning-ProvideCapabilities-r19”, indicating a request for AI uplink positioning capability. For example, information 2-3 may include field 6, such as “NR-UL-AIPositioning-MeasurementCapability-r19”, indicating a request for AI uplink positioning data measurement capability. For example, information 2-3 may include field 7, which could be “support Of UL-CIR-MeasFR1-r19”, indicating a request for uplink CIR measurement capability. For example, information 2-3 may include field 8, which could be “supportOf UL-PDP-MeasFR1-r19”, indicating a request for uplink PDP measurement capability.

[0230] S602b and gNB send information 2-4 to LMF, and correspondingly, LMF receives information 2-4 sent by gNB;

[0231] After receiving information 2-3, the gNB can send information 2-4 to the LMF. Information 2-4 can include the gNB's AI capability information. The gNB can send information 2-4 to the LMF via the NRPPa protocol. Information 2-4 can be a response message to information 2-3.

[0232] Optionally, the gNB's AI capability information is used to indicate the types of measurement data that the gNB supports providing. For example, the gNB's AI capability information may indicate that the gNB supports providing CIR measurement data and / or PDP measurement data.

[0233] The AI ​​capability or measurement data type indicated by the gNB's AI capability information in Message 2-4 can be all or some of the types indicated by Message 2-3. The gNB's AI capability information in Message 2-4 does not indicate that the gNB supports AI capabilities or data types not requested in Message 2-3. For example, if Message 2-3 is used to request downlink PDP measurement capability, even if the gNB supports providing CIR measurement data, Message 2-4 may not indicate that the gNB supports providing CIR measurement data. Optionally, Message 2-4 may also indicate that the gNB does not support AI capabilities, or indicate the types of AI capabilities that are not supported.

[0234] Taking information 2-3, which includes fields 5 to 8 above, as an example, information 2-4 can be as follows.

[0235] -->ProvideCapabilities information

[0236] -->AI uplink positioning capability (NR-UL-AIPositioning-ProvideCapabilities-r19)

[0237] AI Uplink Data Measurement Capability (NR-UL-AIPositioning-MeasurementCapability-r19)

[0238] -->Uplink CIR measurement capability (supportOfUL-CIR-MeasFR1-r19)

[0239] -->Uplink PDP measurement capability (supportOfUL-PDP-MeasFR1-r19)

[0240] This application does not limit the way in which information 2-4 indicates the AI ​​capability information of gNB. For example, taking field 5 as an example, information 2-4 can indicate that gNB supports the AI ​​capability requested by field 5 by carrying field 5, or information 2-4 can indicate whether gNB supports the AI ​​capability requested by field 5 by the value corresponding to field 5.

[0241] S601b is an optional step; in some examples, the gNB can directly send information 2-4 to the LMF.

[0242] Figure 6-1 In this invention, the LMF actively triggers a request for AI positioning capabilities from the UE / gNB via the LPP / NRPPa protocol. This allows the LMF to determine whether it can collect AI measurement data from the UE / gNB to perform AI positioning. In existing technologies, the LMF cannot determine whether AI measurement data can be collected from the UE / gNB, thus preventing it from accurately performing AI positioning. This invention addresses this by having the LMF trigger the acquisition of AI positioning capability information from the UE / gNB, enabling the LMF to determine whether AI positioning can be performed.

[0243] After receiving the AI ​​capability information from the UE and / or gNB, for example after S602a and / or S602b, the LMF can determine that it supports AI capabilities. Optionally, refer to [link to relevant documentation]. Figure 6-1 The communication method provided in this application may include a process for an LMF to register its own AI capability information, and the process for an LMF to register its own AI capability information may include S603a to S604a.

[0244] S603a and LMF send information 2-5 to NRF;

[0245] S604a and NRF send information 2-6 to LMF;

[0246] S603a and S604a can be referred to the relevant content of S506 and S507 respectively, and information 2-5 and information 2-6 can be referred to information 1-9 and information 1-10 respectively, which will not be repeated here.

[0247] After an LMF registers its AI capabilities, it helps AI consumers (such as AMFs or MTLFs) to identify an LMF as an enhanced LMF by querying its registration information. This LMF supports the collection and / or provision of measurement data for AI models.

[0248] Figure 6-2 This illustration shows another possible flow of the communication method provided in this application. For example... Figure 6-2 As shown, the communication method provided in this application may include a process for obtaining AI capability information of a UE, and the process for obtaining AI capability information of a UE may include S601c to S602c. Figure 6-2 The process for obtaining AI capability information for the UE shown can be an example of the third method for LMF-enhanced perception UEs.

[0249] S601c and LMF send information 3-1 to UDM, and UDM receives information 3-1 sent by LMF accordingly;

[0250] Message 3-1 can be used to request subscription information from a UE. Optionally, prior to S601c, the LMF can obtain the IDs (or a list of UE IDs) of one or more UEs within the LMF's service area from the AMF, and then request the subscription information of one or more UEs from the UE ID list by sending Message 3-1. These one or more UEs can be UEs within a specific area of ​​the LMF's service area, such as the area where the LMF's AI positioning model is applicable.

[0251] Optionally, information 3-1 includes the IDs of one or more UEs in the UE ID list.

[0252] S602c, UDM sends information 3-2 to LMF, and correspondingly, LMF receives information 3-2 sent by UDM;

[0253] After receiving information 3-1, the UDM can retrieve the UE's subscription information indicated by information 3-1, and then send information 3-2 to the LMF. Information 3-2 may include all or part of the UE's subscription information. Based on the UE's subscription information, which includes the UE's AI capability information, information 3-2 may include the UE's AI capability information.

[0254] The LMF may optionally include an indication to indicate the acquisition of UE AI capability information. If the UE supports AI capabilities, the UDM will feed back the UE's AI capability information to the LMF, or send an indication to indicate that the UE supports AI capabilities. If the UE does not support AI capabilities, the UDM will feed back a failure indication, or send an indication to indicate that the UE does not support AI capabilities, or feed back nothing.

[0255] After receiving information 3-2, LMF can determine whether a UE supports providing AI measurement data based on the UE's AI capability information in the subscription information, or select UEs that support providing AI measurement data from multiple UEs based on the subscription information of multiple UEs.

[0256] Continue to refer to Figure 6-2 The communication method provided in this application may include the AI ​​capability information acquisition process of gNB, which may include S601d to S602d. Figure 6-2 The process for acquiring AI capability information of gNB shown can be seen as an example of the third method for LMF-enhanced perception gNB.

[0257] S601d and LMF send information 3-3 to UDM, and UDM receives information 3-3 sent by LMF accordingly;

[0258] Message 3-3 can be used to request subscription information from gNBs. Optionally, prior to S601d, the LMF can obtain the IDs (or a list of gNB IDs) of each gNB within the LMF's service area from the AMF, and then request the subscription information of one or more gNBs from the gNB ID list by sending message 3-3.

[0259] Optionally, information 3-3 includes the IDs of one or more gNBs in the gNB ID list.

[0260] S602d and UDM send information 3-4 to LMF, and correspondingly, LMF receives information 3-4 sent by UDM.

[0261] After receiving information 3-3, the UDM can retrieve the subscription information of the gNB indicated by information 3-3, and then send information 3-4 to the LMF. Information 3-4 may include all or part of the subscription information of the gNB. The subscription information based on the gNB includes the gNB's AI capability information, and information 3-4 may include the gNB's AI capability information.

[0262] After receiving information 3-4, LMF can determine whether a gNB supports providing AI measurement data based on the gNB's AI capability information in the contract information, or select a gNB that supports providing AI measurement data from multiple gNBs based on the contract information of multiple gNBs.

[0263] Optionally, information 3-1 and information 3-3 can be carried in the same message. Similarly, information 3-2 and information 3-4 can be carried in the same message.

[0264] When the contract information includes AI capability information of the UE and / or gNB, the LMF can identify itself as an enhanced LMF, supporting the collection and / or provision of measurement data for AI models. Optionally, continue to refer to... Figure 6-2 The communication method provided in this application may include a process for an LMF to register its own AI capability information, and the process for an LMF to register its own AI capability information may include S603c to S604c.

[0265] S603c and LMF send information 3-5 to NRF;

[0266] S604c and NRF send information 3-6 to LMF;

[0267] S603c and S604c can be referred to the relevant content of S506 and S507 respectively, and information 3-5 and information 3-6 can be referred to information 1-9 and information 1-10 respectively, which will not be repeated here.

[0268] Similar to S506 and S507 or S603 and S604 above, optionally, after determining that it is an enhanced LMF, the LMF can register its AI capability information. The AI ​​capability information of the LMF is used to indicate that the LMF supports the collection and / or provision of measurement data for AI models. This is beneficial for AI consumers (such as AMF or MTLF) to determine that the LMF is an enhanced LMF that supports the collection and / or provision of measurement data for AI models by querying the registration information of the LMF.

[0269] The communication method provided in this application may include a method flow for LMF-aware enhanced gNB or a method flow for LMF-aware enhanced UE. Alternatively, the communication method provided in this application may include a method flow for LMF-aware enhanced gNB but not a method flow for LMF-aware enhanced UE. Or, the communication method provided in this application may include a method flow for LMF-aware enhanced UE but not a method flow for LMF-aware enhanced gNB.

[0270] This application does not limit the specific methods used in LMF-aware enhanced UEs. For example, methods for LMF-aware enhanced UEs can be found in [reference needed]. Figure 5 The process of associating AI capability information of the UE shown and / or Figure 6-1 The process for obtaining AI capability information for the UE shown and / or Figure 6-2The diagram illustrates the AI ​​capability information acquisition process for the UE. This application does not limit the specific method used by the LMF-enhanced perception gNB; for example, the method for the LMF-enhanced perception gNB can be found in [reference needed]. Figure 5 The process of associating gNB's AI capability information and / or Figure 6-1 The process for acquiring AI capability information of gNB shown and / or Figure 6-2 The diagram shows the process for obtaining AI capability information from gNB.

[0271] Combined with the preceding text Figure 5 and Figure 6-1 The flowcharts shown illustrate the methods for LMF-aware enhancement of UE and LMF-aware enhancement of gNB. Below are examples of communication methods performed by LMF-based enhanced UE and / or enhanced gNB in ​​a communication system.

[0272] Figure 7 This illustration shows another possible flow of the communication method provided in this application. For example... Figure 7 As shown, the method may include S701 to S704.

[0273] S701, LMF identifies the requirements related to collecting AI measurement data;

[0274] This requirement can be generated by the LMF, or it can be a requirement submitted to the LMF by other network elements outside the LMF. For example, the LMF can determine this requirement based on receiving requests from other network elements. The possible types of requirements will be introduced later, and will not be discussed here.

[0275] S702 and LMF confirm support for measurement devices that provide AI measurement data;

[0276] The measurement device can be a UE, or a gNB, or both a UE and a gNB.

[0277] This application does not limit the method flow for determining the UE that supports providing AI measurement data using the LMF. For example, the method flow may include... Figure 5 The process of associating AI capability information of the UE shown and / or Figure 6-1 The process for obtaining AI capability information for the UE shown and / or Figure 6-2 The process for obtaining AI capability information for the UE is shown below.

[0278] This application does not limit the method flow for LMF to determine gNBs that support providing AI measurement data; for example, the method flow may include Figure 5 The process of associating gNB's AI capability information and / or Figure 6-1 The process for acquiring AI capability information of gNB shown and / or Figure 6-2 The diagram shows the process for obtaining AI capability information from gNB.

[0279] After S702, LMF can acquire AI measurement data through S703a and / or S703b.

[0280] S703a and LMF obtain AI measurement data from UEs that support providing AI measurement data;

[0281] Based on the LMF (Light Filter Function), UEs that support providing AI measurement data have been identified. The LMF can collect measurement data from the UEs. This process can be referenced. Figure 8 The process is shown below. Figure 8 As shown, the refinement process of S703a may include S801 to S807.

[0282] S801, LMF sends information 4-1 to AMF;

[0283] Information 4-1 can be a downlink positioning message used to instruct the UE to obtain AI measurement data. This UE is the one identified by the LMF as supporting the provision of AI measurement data.

[0284] S802, AMF establishes a signaling connection with UE;

[0285] If the UE is in an idle state, the AMF triggers a service request process to establish a signaling connection with the UE.

[0286] S803, AMF sends information 4-2 to UE;

[0287] Information 4-2 can be a DL NAS message, which can be used to instruct the UE to collect and report AI measurement data.

[0288] S804, UE performs positioning measurement;

[0289] The UE can perform positioning measurements or positioning processing based on information 4-2, such as acquiring inference data and / or training data for the AI ​​model. As mentioned earlier, the training data for the AI ​​model includes not only measurement data of the downlink signals transmitted by the UE to the gNB, but also the UE location (i.e., tag) calculated based on the measurement data.

[0290] S805, UE and AMF establish signaling connection;

[0291] If the UE enters the idle state after executing S804, the UE triggers the service request process to establish a signaling connection with the AMF.

[0292] S806, UE sends information 4-3 to AMF;

[0293] Message 4-3 can be a UL NAS message, and Message 4-3 can include the AI ​​measurement data requested by Message 4-3.

[0294] S807, AMF sends information 4-4 to LMF;

[0295] Information 4-4 can be an uplink positioning message, and information 4-4 can include AI measurement data received by the AMF from the UE.

[0296] In the accompanying drawings of this application, the steps corresponding to the dashed lines are optional steps. For example... Figure 8 As shown, S802 and S805 to S807 are optional steps.

[0297] Alternatively, the process by which LMF collects AI measurement data from UE can be found in [reference needed]. Figure 9 The process is shown below.

[0298] S901, LMF and UE establish user plane connection, and LMF sends user plane messages to UE including information 5-1;

[0299] LMF can send Message 5-1 to UE via User Plane LPP message. Message 5-1 is used to request UE to collect and report AI measurement data.

[0300] S902a, UE performs positioning processing;

[0301] The UE can perform location processing based on Information 5-1, such as acquiring inference data and / or training data for the AI ​​model. The training data may include not only measurement data of downlink signals transmitted by the UE to the gNB, but also the UE location (i.e., tag) calculated based on the measurement data.

[0302] S902b and LMF perform positioning processing;

[0303] S902b is an optional step.

[0304] S903, the UE sends information 5-2 to the LMF via user plane messages;

[0305] Information 5-2 may include AI measurement data obtained by the UE based on Information 5-1. The UE can send Information 5-2 to the LMF via a User Plane LPP message.

[0306] S703b and LMF obtain AI measurement data from gNB that supports providing AI measurement data;

[0307] Based on the LMF, gNBs that support providing AI measurement data have been identified. The LMF can collect measurement data from the gNBs. This process can be referenced. Figure 10 The process is shown below. Figure 10 As shown, the detailed process of S703b may include S1001 to S1006.

[0308] S1001, LMF sends information 6-1 to AMF;

[0309] Message 6-1 can be a network location message, used to instruct the user to obtain AI measurement data from the gNB. This gNB is the one identified by the LMF as supporting the provision of AI measurement data.

[0310] S1002, AMF establishes a signaling connection with UE;

[0311] If the UE is in an idle state, the AMF triggers a service request procedure to establish a signaling connection with the UE. This UE can be the UE corresponding to a specific gNB.

[0312] S1003, AMF sends information 6-2 to gNB;

[0313] Information 6-2 can be a network location message, used to instruct the gNB to collect and report AI measurement data. This AI measurement data can be the measurement data of the uplink signals sent by the gNB to the UE.

[0314] S1004 and gNB perform positioning measurements;

[0315] The gNB can perform location measurements based on Information 6-2, such as acquiring inference data and / or training data for AI models. Training data may include not only measurement data of uplink signals transmitted by the gNB to the UE, but also the UE's location (i.e., tag) calculated based on the measurement data.

[0316] S1005 and gNB send information 6-3 to AMF;

[0317] Information 6-3 can be a network location message, and information 6-3 can be the AI ​​measurement data requested by information 6-2.

[0318] S1006, AMF sends information 6-4 to LMF;

[0319] Information 6-4 can be a network location message, and information 6-4 can contain AI measurement data received by the AMF from the gNB.

[0320] S704 and LMF respond to this need based on collected AI measurement data;

[0321] After collecting AI measurement data, the LMF can respond to the request based on the collected AI measurement data. For example, it can train a local AI model, and / or use the local AI model to perform inference on the collected AI measurement data (or perform AI localization based on the AI ​​model and the collected AI measurement data), and / or provide the collected AI measurement data to other network elements. The following sections will provide examples illustrating the meaning of responding to the request, but will not elaborate further here.

[0322] Steps S701 and S704 above are optional steps.

[0323] This application does not limit the type of the above-mentioned requirement, nor does it limit the specific implementation of S701 and S704. The following sections will illustrate the specific implementation of S701 and S704 with examples of other communication methods provided in this application.

[0324] In one possible example, the LMF can determine the requirements in the S701 based on the request received from the MTLF.

[0325] Figure 11 This illustration shows another possible flow of the communication method provided in this application. For example... Figure 11 As shown, the method may include S1101 to S1108.

[0326] S1101 and MTLF determine that AI measurement data needs to be collected;

[0327] When performing model training / inference at MTLF, MTLF determines that AI measurement data needs to be collected.

[0328] S1102, MTLF sends information 7-1 to NRF;

[0329] Information 7-1 may include indication information, which indicates the discovery of an LMF that supports providing AI measurement data, or, in other words, indicates the discovery of an LMF that can provide AI measurement data, or, in other words, indicates the discovery of an LMF that supports AI capabilities. This indication information may be an AI capability existence indication.

[0330] This indication information can be used to indicate the discovery of an LMF that provides Type I AI measurement data. Type I AI measurement data may include AI measurement data collected from the UE and / or AI measurement data collected from the gNB.

[0331] Alternatively, the indication information can be used to indicate the discovery of an LMF that supports the collection of AI measurement data, which can support the collection of AI measurement data from the UE, or support the collection of AI measurement data from the gNB, or support both the collection of AI measurement data from the UE and the collection of measurement data from the gNB.

[0332] Alternatively, the indication information can be used to indicate the discovery of an LMF that supports collecting AI measurement data from the UE, which may or may not support collecting AI measurement data from the gNB.

[0333] Alternatively, the indication information can be used to indicate the discovery of an LMF that supports collecting AI measurement data from a gNB, which may or may not support collecting AI measurement data from a UE.

[0334] Information 7-1 may also include location information 7-1, which indicates a first area, which may be an area encompassed by the service area of ​​the LMF discovered as indicated by the aforementioned indication information. This location information 7-1 may be AOI information.

[0335] S1103, NRF sends information 7-2 to MTLF;

[0336] After receiving message 7-1, the NRF can query or discover LMFs that meet the conditions indicated in message 7-1, or in other words, query or discover LMFs that are indicated by message 7-1. For example, the NRF can discover an LMF whose service area includes the first area and supports the collection of AI measurement data, and then send message 7-2 to the MTLF.

[0337] Message 7-2 may include information about the LMF discovered as indicated by Message 7-1. Message 7-2 may be a response message to Message 7-1. In this application, the LMF information may include the LMF's NF configuration information (profile), which may include one or more of the following: LMF identifier, LMF address, LMF AI capability information, and LMF service area information.

[0338] S1104, MTLF sends information 7-3 to LMF;

[0339] After receiving information 7-2, the MTLF can determine the LMF that supports providing AI measurement data based on information 7-2, and then send information 7-3 to that LMF. Information 7-3 may include request information, which is used to instruct the provision or acquisition of AI measurement data.

[0340] The request information can also indicate the type of AI measurement data. For example, the request information may indicate providing training data or inference data for the AI ​​model, or it may indicate providing AI (measurement) data for the UE / gNB, or it may indicate AI (measurement) data for the UE / gNB and tags, where the tags can be the location of the UE. For example, the request information may indicate providing AI measurement data collected from the UE, or it may indicate providing AI measurement data collected from the gNB, or it may indicate providing AI measurement data collected from both the UE and the gNB.

[0341] Information 7-3 may also include location information 7-3. Location information 7-3 is used to indicate a second area, which may be the range or region of the AI ​​measurement data to be acquired as indicated by the request information. In this application, the range of the AI ​​measurement data may refer to the range or region where the measuring device providing the AI ​​measurement data is located. The measuring device may be a UE and / or a gNB. Location information 7-3 may be the AoI of the AI ​​model, or the ID of one or more cells.

[0342] S1105 and LMF confirm support for measurement devices that provide AI measurement data;

[0343] After receiving information 7-3, the LMF can identify the measurement device that supports providing AI measurement data. Based on information 7-3, which also includes location information 7-3, the measurement device identified by the LMF is used to collect AI measurement data within the second area.

[0344] Step S1105 can be understood by referring to the content of step S702, and will not be repeated here.

[0345] S1106a, LMF obtains AI measurement data from UEs that support providing AI measurement data;

[0346] Step S1106a can be understood by referring to the content of step S703a, and will not be repeated here.

[0347] S1106b, LMF obtains AI measurement data from gNB that supports providing AI measurement data;

[0348] Step S1106b can be understood by referring to the content of step S703b.

[0349] S1107, LMF sends information 7-4 to MTLF;

[0350] Prior to S1107, S1106a and / or S1106b can be executed. Accordingly, information 7-4 may include the AI ​​measurement data acquired or collected by the LMF in S1106a and / or S1106b. Information 7-4 can be a response to information 7-3. The LMF can send information 7-4 to the MTLF based on information 7-3, or in other words, the LMF sends the AI ​​measurement data requested by information 7-3 to the MTLF.

[0351] S1108 and MTLF use collected AI measurement data to perform AI modeling.

[0352] exist Figure 11In the communication method shown, the AI ​​capability information registered by the LMF is beneficial for the MTLF to determine that the LMF is an enhanced LMF by querying the registration information of the LMF. The LMF supports the collection and / or provision of measurement data for AI models.

[0353] In S701, the LMF can specifically determine the requirements related to collecting AI measurement data based on receiving information 7-3 sent by the MTLF in S1104. Accordingly, S704 can specifically include S1107, that is, the LMF sends information 7-4 to the MTLF.

[0354] Optionally, steps S1102 and S1103 can be omitted before step S1104. Correspondingly, the MTLF can use other methods to determine if an LMF supports providing AI measurement data. For example, the MTLF can determine if an LMF supports providing AI measurement data based on whether the LMF supports AI localization (e.g., deploying an AI model or supporting localization inference using an AI model). Alternatively, the MTLF may not need to determine whether the LMF supports providing AI measurement data before step S1104.

[0355] S1101 is an optional step, and this application does not limit the reason for MTLF to perform S1104.

[0356] In one possible example, the LMF can determine the requirements in S701 based on receiving a request from the AMF.

[0357] Figure 12 This illustration shows another possible flow of the communication method provided in this application. For example... Figure 12 As shown, the method may include S1201 to S1211.

[0358] S1201, The client sends information 8-1 to the GMLC;

[0359] Information 9-1 may include the UE ID, and information 9-1 may be used to indicate the location or location result of the UE indicated by the UE ID. Information 9-1 may be a location request or may be carried in a location request.

[0360] This application does not limit the type of client; for example, the client can be a client for an external positioning service. The UE ID can be, for example, SUPI or GPSI. Figure 12 In the subsequent steps of the method shown, UE refers to the UE indicated by information 8-1.

[0361] S1202, GMLC sends information 8-2 to UDM;

[0362] After receiving information 8-1, the GMLC can send information 8-2 to the UDM. Information 8-2 is used to instruct the UE to obtain the serving AMF. The UE is the UE indicated by information 8-1.

[0363] S1203, UDM sends information 8-3 to GMLC;

[0364] The UDM can send information 8-3 to the GMLC based on information 8-2. After receiving information 8-2, the UDM can query the serving AMF of the UE indicated by the UE ID or the AMF of the UE's service. Information 8-3 may include information about the AMF, such as the AMF's identifier.

[0365] S1204, GMLC sends information 8-4 to AMF;

[0366] After receiving information 8-3, the GMLC can send information 8-4 to the AMF based on information 8-3. Information 8-4 is used to indicate the location of the UE. Information 8-4 can be a request message. Information 8-4 may include the UE's identifier, such as the UEID from information 8-1.

[0367] S1205, AMF establishes a signaling connection with UE;

[0368] After receiving 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.

[0369] S1206, AMF should be selected as LMF;

[0370] After receiving information 8-4, the AMF can select an LMF. For example, the AMF can select a suitable LMF for the UE based on information from multiple LMFs. The LMF information may include one or more of the following: the LMF's service area, LMF load status, LMF AI capability information, LMF address, and LMF identifier.

[0371] This application does not limit the specific method by which the AMF selects a suitable LMF based on information from one or more LMFs. For example, the service area of ​​the LMF includes the 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.

[0372] This application does not limit the method by which the AMF determines 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 NRF for the LMF's AI capability information. The specific process can be understood by referring to S1102 and S1103, simply by replacing MTLF with AMF in S1102 and S1103.

[0373] S1207, AMF sends information 8-5 to LMF;

[0374] After the AMF identifies the LMF, it can send information 8-5 to the LMF, which instructs the LMF to locate the UE. Optionally, information 8-5 can also instruct the LMF to perform AI-based location of the UE, or to perform location or location inference based on an AI model.

[0375] Step S1206 is an optional step; for example, AMF can send information 8-5 to the LMF.

[0376] S1208 and LMF perform AI positioning for UE;

[0377] After receiving information 8-5, LMF can perform AI positioning on the UE. LMF can collect AI measurement data, and then use the AI ​​positioning model to process or infer the location of the UE from the collected AI measurement data.

[0378] 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 a combination of AI measurement data collected from the UE and AI measurement data collected from the gNB. In S1208, the AI ​​measurement data collected from the gNB can refer to the measurement data of the uplink signals transmitted by the gNB to the UE.

[0379] The methods for collecting AI measurement data by LMF can be found in S702 and S703a, or S702 and S703b, or S702, S703a and S703b, which will not be elaborated here.

[0380] LMF can determine the method for locating the UE based on the location method indicated in information 8-5, or alternatively, LMF can determine, based on internal logic, whether to use a conventional location method or an AI location method to calculate the UE's location.

[0381] S1209, LMF sends information 8-6 to AMF;

[0382] After the LMF performs AI positioning on the UE, it can send message 8-6 to the AMF. Message 8-6 can be a response message to message 8-5. Message 8-6 may include the result of the LMF's AI positioning of the UE (e.g., the UE's location information).

[0383] S1210, AMF sends information 8-7 to GMLC;

[0384] After receiving information 8-6, AMF can send information 8-7 to GMLC. Information 8-7 can be a response message to information 8-4. Information 8-7 may include the results of LMF's AI positioning of the UE, such as the UE's location information.

[0385] S1211, GMLC sends information 8-8 to the client.

[0386] After receiving information 8-7, GMLC can send information 8-8 to the client. Information 8-8 can be a response message to information 8-1. Information 8-8 may include the results of LMF's AI positioning of the UE, such as the UE's location information.

[0387] In S1206, the AMF can select an LMF based on the LMF's AI positioning capabilities. For example, if the AMF wants to use AI positioning to calculate the UE's location, it can select an LMF that supports AI positioning based on whether the LMF supports AI positioning capabilities. However, in existing solutions, the AI ​​positioning capability of the LMF mainly refers to whether the LMF supports using AI models to calculate the UE's location, without considering whether the LMF can discover UEs / gNBs that support AI capabilities and collect measurement data from them. In other words, even if the AMF discovers an LMF that supports AI positioning, it still cannot use the AI ​​positioning method to calculate the UE's location because that LMF cannot collect AI positioning-related measurement data from the UE / gNB.

[0388] exist Figure 12 In the communication method shown, the AI ​​capability information registered by the LMF is beneficial for the AMF to determine that the LMF is an enhanced LMF by querying the registration information of the LMF. The LMF supports the collection and / or provision of measurement data for AI models.

[0389] In S701, the LMF can specifically determine the requirements related to collecting AI measurement data based on receiving information 8-5 sent by the AMF in S1207. Correspondingly, S704 can specifically include S1208 and S1209, that is, after collecting AI measurement data, the LMF performs AI positioning on the UE and sends information 8-6 to the AMF.

[0390] This application does not limit the method by which the LMF determines its own AI capability information (i.e., the AI ​​capability information used to indicate support for providing AI measurement data). After determining its own AI capability information, the LMF... Figure 11 and Figure 12In the example, taking the LMF registering its AI capability information with the NRF for the MTLF or AMF to query the LMF's AI capability information as an example, this application does not limit the purpose of the LMF registering its AI capability information with the NRF. For example, other network elements (or other AI consumers) besides the MTLF or AMF can query the LMF's AI capability information through the NRF. Figure 11 and Figure 12 In the example, taking the LMF registering its AI capability information with the NRF as an example, the LMF can also register its AI capability information with other types of network elements, as long as the network element can store the LMF's AI capability information and provide a query service for that information. Correspondingly, AI consumers of AI capability information (such as MTLF or AMF) can query the network element for the LMF's AI capability information. Alternatively, after determining its own AI capability information, the LMF can proactively send its AI capability information to AI consumers of AI capability information (such as MTLF and / or AMF), or respond to the AI ​​consumer's request with its own AI capability information.

[0391] In other words, an AI consumer with its own AI capabilities (such as an MTLF or an AMF) can obtain the AI ​​capability information of the LMF. The following text will continue to use the example of this AI consumer obtaining the LMF's capability information from an NRF.

[0392] To facilitate efficient perception of enhanced LMFs or determination of whether a specific LMF supports the collection and / or provision of measurement data for AI models even when the LMF has not determined or registered its own AI capability information, this application further proposes that AI consumers can perceive enhanced LMFs or determine whether a specific LMF supports the collection and / or provision of measurement data for AI models based on the AI ​​capability information of the measurement unit. The measurement unit can be a UE and / or a gNB.

[0393] This application does not limit the method by which the AI ​​consumer determines the AI ​​capability information of the measurement unit. For example, the AI ​​consumer can determine the AI ​​capability information of the measurement unit using any one or more methods described above for determining the AI ​​capability information of the measurement unit via LMF. The following section uses the example of the AI ​​consumer obtaining the UE's AI capability information from the UDM to illustrate an example of how the AI ​​consumer determines the AI ​​capability information of the LMF.

[0394] In one possible example, the AI ​​consumer could be an MTLF, which could be an LMF that enhances the perception of the UE's AI capabilities.

[0395] Figure 13 This illustration shows another possible flow of the communication method provided in this application. For example...Figure 13 As shown, the method may include S1301 to S1309.

[0396] S1300 and UDM store the UE's subscription information;

[0397] The UDM is configured with subscription information for one or more UEs, which may include UE capability information. UE capability information can be used to indicate whether the UE supports providing AI measurement data. Alternatively, UE capability information can be the UE's AI capability information. Based on the UE's support for providing AI measurement data, the UE's subscription information including UE capability information can indicate that the UE supports providing AI measurement data, while the UE's subscription information excluding UE capability information can indicate that the UE does not support providing AI measurement data.

[0398] The UE's subscription information may also include the UE's service LMF information, that is, the information of the LMF that provides services to the UE. The LMF information can be found in the relevant content above, such as the LMF's identifier.

[0399] S1301, MTLF sends information 9-1 to AMF;

[0400] When the MTLF determines that it needs to collect AI measurement data in the first area to train the AI ​​model, it can send information 9-1 to the AMF. Information 9-1 is used to instruct the acquisition of the UE's identifier in the first area. The first area can be the area indicated by the AOI information. In this application, the AOI information may include a TA list and / or a cell list. The area indicated by the AOI information may include an area with multiple TAs and / or cells.

[0401] S1302, AMF sends information 9-2 to MTLF;

[0402] After receiving message 9-1, the AMF can send message 9-2 to the MTLF. Message 9-2 can be a response message to message 9-1. Message 9-2 may include the identifiers of one or more UEs. These one or more UEs are all or some of the UEs in the first area requested by message 9-1.

[0403] S1303, MTLF sends information 9-3 to UDM;

[0404] S1304, UDM sends information 9-4 to MTLF;

[0405] Through S1303 and S1304, the MTLF can obtain information 9-4 from the UDM based on the UE identifier in information 9-2. Information 9-4 may be part or all of the UE's subscription information. The UE's subscription information can be referenced from the relevant content in S1300. Information 9-4 may include UE capability information and the UE's serving AMF information.

[0406] S1303 and S1304 can refer to S601c and S602c, and / or S601d and S602d, respectively. Information 9-3 and Information 9-4 can refer to Information 3-1 and Information 3-2, and / or Information 3-3 and Information 3-4, respectively.

[0407] S1305 and MTLF, based on Information 9-4, determine that LMFs support providing AI measurement data;

[0408] After receiving information 9-4, the MTLF can filter out UEs that support providing AI measurement data based on information 9-4, and then determine that the serving LMF of the UE supports providing AI measurement data.

[0409] S1306, MTLF sends information 9-5 to LMF;

[0410] Once the MTLF determines that an LMF supports providing AI measurement data, it can send information 9-5 to that LMF. Step S1306 can be understood with reference to the relevant content of S1104, and information 9-5 can be understood with reference to the meaning of information 7-3. For example, information 9-5 may include request information indicating the provision or acquisition of AI measurement data. For example, information 7-3 may also include location information indicating a third area, which can be the range of AI measurement data to be acquired as indicated by the request information.

[0411] S1307, LMF collects AI measurement data;

[0412] After receiving information 9-5, the LMF can collect AI measurement data based on information 9-5. Information 9-5 also includes location information indicating a third area, allowing the LMF to collect AI measurement data within that third area.

[0413] To improve the efficiency of LMF in collecting AI measurement data, LMF can identify measurement devices that support providing AI measurement data (within a third area), and then collect AI measurement data from the identified measurement devices. See S702 and S703a, or S702 and S703b, or S702, S703a, and S703b for details.

[0414] S1308, LMF sends information 9-6 to MTLF;

[0415] After collecting AI measurement data, the LMF can send message 9-6 to the MTLF. Message 9-6 can be a response message to message 9-5. Message 9-6 can include the AI ​​measurement data collected by the LMF.

[0416] In this application, the interaction between MTLF and LMF can be achieved through AMF or through GMLC and AMF.

[0417] S1309 and MTLF use AI measurement data to train AI models.

[0418] After receiving information 9-6, MTLF can train an AI model based on the AI ​​measurement data provided by LMF.

[0419] In S701, the LMF can specifically determine the requirements related to collecting AI measurement data based on the information 9-5 sent by the MTLF in S1306. Accordingly, S704 can specifically include S1307 and S1308, that is, after the LMF collects the AI ​​measurement data, it executes S1308.

[0420] In one possible example, the AI ​​consumer can be an AMF, which can be an LMF that enhances the perception of AI capabilities based on the UE.

[0421] Figure 14 This illustration shows another possible flow of the communication method provided in this application. For example... Figure 14 As shown, the method may include S1401 to S1406.

[0422] S1400 and UDM store the UE's subscription information;

[0423] S1400 can be understood by referring to the content of S1300.

[0424] S1401, AMF sends message 10-1 to UDM;

[0425] S1402, UDM sends information 10-2 to AMF;

[0426] Through S1401 and S1402, the AMF can obtain information 10-2 from the UDM. Information 10 can be part or all of the UE's subscription information. The UE's subscription information can be referenced from the relevant content in S1300. Information 9-4 may include UE capability information and the UE's serving AMF information.

[0427] S1401 and S1402 can refer to S601c and S602c respectively, and / or, S601d and S602d. Information 10-1 and Information 10-2 can refer to Information 3-1 and Information 3-2 respectively, and / or, Information 3-3 and Information 3-4.

[0428] S1403 and AMF, based on Information 10-2, determine that LMFs support providing AI measurement data;

[0429] After receiving information 10-2, the AMF can filter out UEs that support providing AI measurement data based on information 10-2, and then determine that the serving LMF of the UE supports providing AI measurement data.

[0430] S1404, AMF sends information 10-3 to LMF;

[0431] Once the AMF identifies an LMF that supports providing AI measurement data, it can send message 10-3 to that LMF. Message 10-3 instructs the LMF to locate the UE. Optionally, message 10-3 can also instruct the LMF to perform AI-based location of the UE, or to perform location or location inference based on an AI model.

[0432] Step S1404 can be understood by referring to the relevant content of S1207, and information 10-3 can be understood by referring to the meaning of information 8-5.

[0433] S1405, LMF collects AI measurement data and performs localization based on the AI ​​model and the collected data;

[0434] Step S1405 can be referenced from the relevant content of S1208.

[0435] S1406, LMF sends information 10-4 to AMF.

[0436] After obtaining the location result, the LMF can send information 10-4 to the AMF. Information 10-4 can include the location result obtained by the LMF.

[0437] Step S1406 can be referenced from the relevant content of S1209.

[0438] In S701, the LMF can specifically determine the requirements related to collecting AI measurement data based on receiving information 10-3 sent by the AMF in S1404. Accordingly, S704 can specifically include S1405 and S1406, that is, after collecting AI measurement data, the LMF performs AI positioning on the UE and sends information 10-4 to the AMF.

[0439] In this application, the interaction between MTLF and LMF can also be through AMF (i.e., MTLF first sends the request to the AMF whose service area includes the area in the request message, and then the AMF discovers the LMF and forwards the request to the LMF), or through GMLC and AMF (i.e., 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 the AMF / LMF can further filter out the UEs that support providing AI measurement data.

[0440] This application does not limit the number of network elements involved in the communication system in each method example. For example, the communication system may include more or fewer network elements. In at least one method example, one or more network elements of the communication system may be replaced with other network elements. This application does not limit the function of each network element in the communication system in each method example; the name and / or function of the network elements may change as the communication system evolves.

[0441] The preceding text used the example of the AI ​​model for positioning scenario 1, which requires the collection of DL-CIR and DL-PDP data. The data required for the AI ​​model for positioning scenario 1 may include channel measurement data measured by the UE, such as the UE's measurement data of the PRS signal (referred to as PRS measurement data). The PRS measurement data may include at least one of the timing, power, and phase information of the PRS signal.

[0442] Similarly, the data required for the AI ​​model in positioning scenario 2, as mentioned earlier, includes UL-CIR and UL-PDP. The data required for the AI ​​model in positioning scenario 2 may include channel measurement data measured by the gNB, such as the gNB's measurement data of the SRS signal (referred to as SRS measurement data). The SRS measurement data may include at least one of the timing, power, and phase information of the SRS signal.

[0443] Optionally, the PRS signal can be other types of reference signals, and the SRS signal can be other types of reference signals.

[0444] The preceding text described the communication apparatus provided in the fifth aspect of this application. This communication apparatus may include a transmitting module. Optionally, the communication apparatus may further include a receiving module. Optionally, the communication apparatus may further include a processing module. This communication apparatus can be used to perform... Figure 5 or Figure 6-1 or Figure 7 or Figure 8 or Figure 9 or Figure 10 or Figure 11 or Figure 12In the examples shown, the steps or procedures executed by the UE or gNB can be categorized as follows: the transmitting module can execute the transmitting steps or actions performed by the UE / gNB, the receiving module can execute the receiving steps performed by the UE / gNB, and the processing module can execute the internal operations or actions performed by the UE / gNB. For example, the transmitting module can execute S501a, the receiving module can execute S505a, and the processing module can execute S804. For details, please refer to the relevant descriptions in the aforementioned method examples.

[0445] The preceding text also described the communication apparatus provided in the sixth aspect of this application. This communication apparatus may include a receiving module. Optionally, the communication apparatus may further include a transmitting module. Optionally, the communication apparatus may further include a processing module. This communication apparatus can be used to perform... Figure 5 or Figure 6-1 or Figure 6-2 or Figure 7 or Figure 8 or Figure 9 or Figure 10 or Figure 11 or Figure 12 or Figure 13 or Figure 14 In the example shown, the steps or processes executed by the LMF include: the sending module can be used to execute the sending steps or actions performed by the LMF; the receiving module can be used to execute the receiving steps performed by the LMF; and the processing module is used to execute the internal operations or actions performed by the LMF. For example, the receiving module can be used to execute S503a, the sending module can be used to execute S504a, and the processing module can be used to execute S702. For details, please refer to the relevant descriptions in the aforementioned method examples.

[0446] The preceding text also described the communication apparatus provided in aspect seven of this application. This communication apparatus may include a transmitting module. Optionally, the communication apparatus may further include a receiving module. Optionally, the communication apparatus may further include a processing module. This communication apparatus can be used to perform... Figure 11 The steps or procedures performed by MTLF in the example shown, or, used to perform Figure 12 The steps or processes executed by the AMF (Advanced Management Function) are as follows: the transmitting module can be used to execute the transmitting steps or actions executed by the LMF (Low-Level Function) or AMF; the receiving module can be used to execute the receiving steps executed by the LMF or AMF; and the processing module can be used to execute the internal operations or actions executed by the LMF or AMF. For example, the transmitting module can be used to execute S1102, the receiving module can be used to execute S1103, and the processing module can be used to execute S1108. For details, please refer to the relevant descriptions in the aforementioned method examples.

[0447] The preceding text also described a communication apparatus provided in aspect eight of this application. This communication apparatus may include a receiving module. Optionally, the communication apparatus may further include a transmitting module. Optionally, the communication apparatus may further include a processing module. This communication apparatus can be used to perform... Figure 13 In the example shown, the steps or processes executed by the MTLF can be performed as follows: the transmitting module can be used to execute the transmitting steps or actions performed by the MTLF; the receiving module can be used to execute the receiving steps performed by the MTLF; and the processing module can be used to execute the internal operations or actions performed by the MTLF. Alternatively, the communication device can be used to execute... Figure 14 In the example shown, the steps or processes executed by the AMF include: the transmitting module can execute the transmitting steps or actions performed by the AMF; the receiving module can execute the receiving steps performed by the AMF; and the processing module can execute the internal operations or actions performed by the AMF. For example, the receiving module can execute S1304, the transmitting module can execute S1303, and the processing module can execute S1305 and / or S1309. For details, please refer to the relevant descriptions in the aforementioned method examples.

[0448] In this application, the internal operation or action can be other operations besides the sending and receiving operations in the flowchart of the communication method, such as the steps described within the rectangles of the flowchart.

[0449] The preceding text also described a communication apparatus provided in the ninth aspect of this application, which includes a processor and a memory. The memory stores computer programs or computer instructions, and the processor is used to call and execute the computer programs or computer instructions stored in the memory, causing the processor to perform, as described above... Figure 5 or Figure 6-1 or Figure 6-2 or Figure 7 or Figure 8 or Figure 9 or Figure 10 or Figure 11 or Figure 12 or Figure 13 or Figure 14 The example shown illustrates the steps or processes performed by the target communication unit. The target communication unit can be any one or more network elements in the corresponding communication method. For example, in... Figure 6-2 In the example shown, the target communication unit may include at least one network element from LMF, UDM, and NRF.

[0450] The preceding text also describes a communication apparatus provided in aspect ten of this application, which includes a processor and an interface circuit. The processor is used to communicate with other devices through the interface circuit and to perform actions such as... Figure 5 or Figure 6-1 or Figure 6-2 or Figure 7 or Figure 8 orFigure 9 or Figure 10 or Figure 11 or Figure 12 or Figure 13 or Figure 14 The example shown illustrates the steps or processes performed by the target communication unit. The target communication unit can be any one or more network elements in the corresponding communication method. For example, in... Figure 6-2 In the example shown, the target communication unit may include at least one network element from LMF, UDM, and NRF. The processor may include one or more.

[0451] The preceding text also describes the communication apparatus provided in the eleventh aspect of this application, including a processor for connection to a memory, for calling a program stored in the memory to execute, for example... Figure 5 or Figure 6-1 or Figure 6-2 or Figure 7 or Figure 8 or Figure 9 or Figure 10 or Figure 11 or Figure 12 or Figure 13 or Figure 14 The example shown illustrates the steps or processes performed by the target communication unit. The target communication unit can be any one or more network elements in the corresponding communication method. For example, in... Figure 6-2 In the example shown, the target communication unit may include at least one network element from LMF, UDM, and NRF. The memory may be located within or outside the communication device. The processor may include one or more components.

[0452] The preceding text also describes the computer program product including computer instructions provided in the twelfth aspect of this application, which, when run on a computer, causes the computer to perform actions such as... Figure 5 or Figure 6-1 or Figure 6-2 or Figure 7 or Figure 8 or Figure 9 or Figure 10 or Figure 11 or Figure 12 or Figure 13 or Figure 14 The example shown illustrates the steps or processes performed by the target communication unit. The target communication unit can be any one or more network elements in the corresponding communication method. For example, in... Figure 6-2 In the example shown, the target communication unit may include at least one network element from LMF, UDM, and NRF.

[0453] The preceding text also describes a computer-readable storage medium provided in aspect thirteen of this application, the storage medium including computer instructions that, when executed on a computer, cause the computer to perform actions such asFigure 15 or Figure 15 or Figure 15 or Figure 15 or Figure 5 or Figure 6-1 or Figure 7 or Figure 8 or Figure 9 or Figure 10 or Figure 11 The example shown illustrates the steps or processes performed by the target communication unit. The target communication unit can be any one or more network elements in the corresponding communication method. For example, in... Figure 12 In the example shown, the target communication unit may include at least one network element from LMF, UDM, and NRF.

[0454] The preceding text also describes the chip (or chip device or chip system) provided in aspect fourteen of this application, which includes a processor for calling a computer program or computer instructions stored in memory to cause the processor to execute... Figure 5 or Figure 6-1 or Figure 6-2 or Figure 7 or Figure 8 or Figure 9 or Figure 10 or Figure 11 or Figure 12 or Figure 15 or Figure 15 The example shown illustrates the steps or processes performed by the target communication unit. The target communication unit can be any one or more network elements in the corresponding communication method. For example, in... Figure 16 In the example shown, the target communication unit may include at least one network element from LMF, UDM, and NRF. Optionally, the processor is coupled to the memory via an interface.

[0455] In this application, the processor mentioned anywhere may be a general-purpose central processing unit, a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits for controlling the execution of a program that controls the methods provided in any of the above embodiments. The memory mentioned anywhere above may be read-only memory (ROM) or other types of static storage devices capable of storing static information and instructions, such as random access memory (RAM).

[0456] The preceding text also describes the communication system provided in aspect fifteen of this application, which includes... Figure 5 or Figure 6-1 or Figure 7 or Figure 8 or Figure 9 orFigure 10 or Figure 11 or Figure 12 or Figure 5 or Figure 6-1 or Figure 7 The examples shown include all or some of the network elements. For example, in Figure 8 The communication system shown in the example may include at least one of the following network elements: LMF, UDM, and NRF.

[0457] In this application, the processing module can be implemented by at least one processor or processor-related circuitry. Specifically, the processor may include a modem chip, or a SoC chip or SIP chip containing a modem core. The transmitting module and / or receiving module can be implemented by a transceiver or transceiver-related circuitry. The transmitting module and / or receiving module may also be referred to as a communication module or communication interface. The storage module can be implemented by at least one memory.

[0458] 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 SIP chip containing a modem core, the function of the processing module can be implemented by a circuit system in the aforementioned chip that includes one or more processors or processing cores. The functions of the transmitting module and / or receiving module can be implemented by the interface circuit or data transceiver circuit on the aforementioned chip.

[0459] In this application, when the communication device is a UE, Figure 9 A simplified schematic diagram of a UE structure is shown. (For example...) Figure 10 As shown, 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, radio frequency circuitry (not shown), an antenna 1533, and input / output devices (not shown).

[0460] The processor is primarily used for processing communication protocols and data; controlling the UE, executing software programs, and processing data from those programs. The memory is primarily used for storing software programs and data. The radio frequency (RF) circuitry is primarily used for converting baseband signals to RF signals and processing RF signals. The antenna is primarily used for transmitting and receiving RF signals in the form of electromagnetic waves. Input / output devices may include touchscreens, displays, or keyboards. These devices are primarily used for receiving user input data and outputting data to the user. It should be noted that some types of UEs may not have input / output devices.

[0461] When data needs to be transmitted, the processor performs baseband processing on the data to be transmitted and outputs a baseband signal to the radio frequency (RF) circuit. The RF circuit then processes the baseband signal and transmits it outwards via the antenna as electromagnetic waves. When data is sent to the UE, the RF circuit receives the RF signal through the antenna. The RF circuit converts the RF signal back into a baseband signal and outputs it to the processor. The processor converts the baseband signal back into data and processes that data. For ease of explanation, Figure 11 Only one memory, processor, and transceiver are shown in the illustration. In actual UE products, there may be one or more processors and one or more memories. Memory may also be referred to as storage medium or storage device, etc. Memory may be set up independently of the processor or integrated with the processor; this application embodiment does not impose any limitations on this.

[0462] In the embodiments of this application, the antenna and radio frequency circuit with transceiver function can be regarded as the transceiver module of the UE, and the processor with processing function can be regarded as the processing module of the UE.

[0463] like Figure 12 As shown, the UE includes a processor 1510, a memory 1520, and a transceiver 1530. The processor 1510 may also be referred to as a processing unit, processing board, processing module, or processing device, etc. The transceiver 1530 may also be referred to as a transceiver unit, transceiver, or transceiver device, etc.

[0464] Optionally, the device in transceiver 1530 used to implement the receiving function can be considered a receiving module, and the device in transceiver 1530 used to implement the transmitting function can be considered a transmitting module. That is, transceiver 1530 includes a receiver and a transmitter. A transceiver may also be called a transceiver unit, transceiver module, or transceiver circuit, etc. A receiver may also be called a receiver unit, receiving module, or receiving circuit, etc. A transmitter may also be called a transmitter, transmitting module, or transmitting circuit, etc.

[0465] Processor 1510 is used to perform the above Figure 16 or Figure 16 or ​ or ​ or ​ or ​ or ​ or ​ The example shown illustrates the processing actions on the UE side. Transceiver 1530 is used to perform the above. ​ or ​ or ​ or ​ or ​ or ​ or ​ or ​ or ​The example shown illustrates the UE's send and receive actions.

[0466] It should be understood that ​ This is merely an example and not a limitation; the UE described above, which includes a transceiver module and a processing module, may not depend on... ​ The structure shown.

[0467] When the communication device 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, a microprocessor, or an integrated circuit. In the above method embodiments, the UE's transmitting operation can be understood as the chip's output, and the UE's receiving operation can be understood as the chip's input.

[0468] In this application, when the communication device is an access network device or a wireless access device, such as a gNB or a base station, ​ A simplified schematic diagram of a base station structure is shown. The base station includes sections 1610, 1620, and 1630.

[0469] The 1610 section is mainly used for baseband processing and base station control; the 1610 section is usually the control center of the base station, which can be called a processor, and is used to control the base station to perform the processing operations on the access network equipment side in the above method embodiments.

[0470] Section 1620 is primarily used to store computer program code and data.

[0471] Section 1630 is primarily used for transmitting and receiving radio frequency (RF) signals, as well as converting RF signals to baseband signals. Section 1630 is commonly referred to as a transceiver module, transceiver, transceiver circuit, or transceiver unit. The transceiver module of section 1630, also called a transceiver or transceiver unit, includes antenna 1633 and RF circuitry (not shown in the figure), where the RF circuitry is mainly used for RF processing. Optionally, the device in section 1630 that performs the receiving function can be considered a receiver, and the device that performs the transmitting function can be considered a transmitter; that is, section 1630 includes receiver 1632 and transmitter 1631. The receiver can also be called a receiving module, receiver circuit, or receiving circuit, and the transmitter can be called a transmitting module, transmitter, or transmitting circuit.

[0472] Sections 1610 and 1620 may include one or more circuit boards, each of which may include one or more processors and one or more memories. The processors are used to read and execute programs from the memories to implement baseband processing functions and control the base station. If multiple circuit boards exist, they can be interconnected to enhance processing capabilities. As an alternative implementation, multiple circuit boards may share one or more processors, multiple circuit boards may share one or more memories, or multiple circuit boards may simultaneously share one or more processors.

[0473] For example, in one implementation, the transceiver module of part 1630 is used to perform... ​ or ​ or ​ or ​ or ​ or ​ or ​ or ​ The example shown illustrates the transmit / receive related processes executed by the gNB side. The processor in section 1610 is used to execute these processes. ​ or ​ or ​ or ​ or ​ or ​ or ​ or ​ The example shown illustrates the processing related to the actions performed by the gNB side.

[0474] It should be understood that ​ This is for illustrative purposes only and not as a limitation. The network devices mentioned above, including processors, memory, and transceivers, may not depend on... ​ The structure shown.

[0475] 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 or a communication interface; the processor can be a processor integrated on the chip, a microprocessor, or an integrated circuit. In the above method embodiments, the gNB's transmit operation can be understood as the chip's output, and the gNB's receive operation can be understood as the chip's input.

[0476] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the explanations and beneficial effects of the relevant contents in any of the above-mentioned devices can be referred to the corresponding method embodiments provided above, and will not be repeated here.

[0477] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection between apparatuses or units through some interfaces, and may be electrical, mechanical, or other forms.

[0478] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0479] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0480] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the essential contribution of the technical solution of this application, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, ROM, RAM, magnetic disks, or optical disks.

[0481] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit it. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

Claims

1. A communication method, characterized in that, The method includes: Send first information, the first information including artificial intelligence (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 AI positioning models.

2. The method according to claim 1, characterized in that, The sending of the first information includes: The first information is sent to a second communication unit, on which the AI ​​positioning model is deployed.

3. The method according to claim 2, characterized in that, After sending the first information, the method further includes: The system receives a second message sent by the second communication unit, the second message being used to instruct the first communication unit to provide the measurement data.

4. The method according to claim 2 or 3, characterized in that, Before sending the first information, the method further includes: The system receives third information sent by the second communication unit, the third information being used to request the AI ​​capability information from 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 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 provided by the terminal device includes measurement data of downlink data sent by the terminal device to the wireless access device.

7. The method according to any one of claims 1-5, characterized in that, The first communication unit is a wireless access device, and the measurement data provided by the wireless access device includes measurement data of uplink data sent by the wireless access device to the 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 also used to indicate the type of measurement data that the first communication unit supports providing.

9. The method according to claim 8, characterized in that, The type of measurement data indicated by the AI ​​capability information of the first communication unit includes channel impulse response (CIR) and / or channel power delay distribution (PDP).

10. A communication method, characterized in that, The method includes: Receive first information, the first information including artificial intelligence (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 AI ​​positioning model being deployed in the second communication unit; Send a second message to the first communication unit, the second message being used to instruct the first communication unit to provide the measurement data.

11. The method according to claim 10, characterized in that, Before receiving the first information, the method further includes: A third message is sent to the first communication unit, the third message being used to request the AI ​​capability information from the first communication unit.

12. The method according to claim 10, characterized in that, The first information is sent by a third communication unit, wherein the third communication unit is used to store the subscription information of the first communication unit, the subscription information of the first communication unit including the AI ​​capability information of the first communication unit, and before receiving the first information sent by the third communication unit, the method further includes: A fourth message is sent to the third communication unit, the fourth message being used to request the subscription information of the first communication unit.

13. The method according to claim 10, characterized in that, The first information is sent by the fourth communication unit, which is used to train the AI ​​positioning model. The first information is used to instruct the second communication unit to provide the measurement data obtained from the first communication unit.

14. The method according to claim 10, characterized in that, The first information is sent by the 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 includes: The sixth communication unit sends a fifth message, which includes the AI ​​capability information of the second communication unit. The AI ​​capability information of the second communication unit is used to indicate that the second communication unit supports providing the measurement data. The sixth communication unit is used to store the AI ​​capability information of the second communication unit.

16. A communication method, characterized in that, The method includes: Send a first message, the first message including a first information unit, the first information unit being used to indicate the discovery of a communication unit that supports providing measurement data for an artificial intelligence (AI) positioning model; Receive second information, the second information including information from the first communication unit, the first communication unit supporting the provision of the measurement data.

17. The method according to claim 16, characterized in that, The first information also includes a second information unit, which is used to indicate a first area, and the service area of ​​the first communication unit includes the first area.

18. The method according to claim 17, characterized in that, The first region is determined based on the region of interest of the AI ​​localization model.

19. The method according to claim 18, characterized in that, The method further includes: Based on the information from the first communication unit, a third message is sent to the first communication unit, the third message being used to instruct the provision of the measurement data; The measurement data provided by the first communication unit is received, and the received measurement data is used to process the AI ​​positioning model.

20. The method according to claim 17, characterized in that, The first area is determined based on the location of the terminal device or the cell of the terminal device.

21. The method according to claim 20, characterized in that, The method further includes: Based on the information from the first communication unit, a fourth message is sent to the first communication unit, the fourth message being used to instruct the first communication unit to obtain the location of the terminal device based on the AI ​​positioning model.

22. A communication method, characterized in that, The method includes: Receive first information, the first information including artificial intelligence (AI) capability information of the 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 AI positioning model, and the first communication unit is provided by the second communication unit; Send a second message to the second communication unit, the second message being used to instruct the second communication unit to provide the measurement data; or send a third message to the second communication unit, the third message being used to instruct the second communication unit to perform positioning based on the AI ​​positioning model and the measurement data.

23. The method according to claim 22, characterized in that, The first information also includes information from the second communication unit.

24. The method according to claim 22 or 23, characterized in that, The first information is sent by a third communication unit, which stores the 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. Before receiving the first information, the method further includes: A fourth message is sent to the third communication unit, the fourth message being used to request the subscription information of the first communication unit.

25. A communication device, characterized in that, Includes a module for performing the method as described in any one of claims 1 to 24.

26. A communication device, characterized in that, It includes at least one processor coupled to a memory; the at least one processor is used to perform the method as described in any one of claims 1 to 24.

27. A readable storage medium, characterized in that, The storage medium stores a computer program or instructions, which, when executed by a communication device, cause the communication device to implement the method as described in any one of claims 1 to 24.

28. A computer program product, characterized in that, When the computer program in the computer program product is executed by the communication device, the communication device performs the method as described in any one of claims 1 to 24.

29. A chip including a processor for invoking a computer program or computer instructions in memory to cause the processor to perform the method as claimed in any one of claims 1 to 24.

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