Positioning method and device and communication equipment

Abstract

The invention discloses a positioning method and device and communication equipment, and belongs to the technical field of communication, and the positioning method comprises the steps that first equipment receives a first request message, and the first request message is used for requesting positioning information of a target terminal; the first device performs an artificial intelligence (AI) positioning process according to the first request message to obtain positioning information of the target terminal; and the first device sends a first notification message, wherein the first notification message comprises positioning information of the target terminal.

Description

Technical Field

[0001] The present application belongs to the field of communication technology, and specifically relates to a positioning method, apparatus and communication equipment. Background Art

[0002] With the continuous development of communication technology, artificial intelligence (AI) has also been widely used in various parts of communication systems to improve the performance of communication systems.

[0003] However, there is still a lack of relevant AI positioning solutions for positioning technologies involved in communication systems. Summary of the Invention

[0004] The embodiments of the present application provide a positioning method, apparatus, and communication device that can implement AI positioning.

[0005] In a first aspect, a positioning method is provided, including: a first device receives a first request message, where the first request message is used to request positioning information of a target terminal; the first device performs an artificial intelligence (AI) positioning process according to the first request message to obtain the positioning information of the target terminal; and the first device sends a first notification message, where the first notification message includes the positioning information of the target terminal.

[0006] In a second aspect, a positioning method is provided, including: a third device receives a third request message sent by a first device, wherein the third request message is used to request information of a device having an inference function related to AI positioning; the third device sends a second response message to the first device according to the third request message, wherein the second response message includes device information of the second device.

[0007] In a third aspect, a positioning method is provided, including: a second device receives a second request message sent by a first device, the second request message being used to request the second device to obtain positioning analysis information of the target terminal based on an AI model, and the second device having an AI model inference function; and sends a first response message to the first device according to the second request message, wherein the first response message includes the positioning analysis information of the target terminal, and the positioning analysis information is generated by the second device based on reasoning of the AI model.

[0008] In a fourth aspect, a positioning method is provided, including: a fourth device sends a fifth request message to a third device, the fifth request message being used to register or update device information of the fourth device, wherein the device information of the fourth device includes AI positioning training-related capability information, and wherein the fourth device has an AI model training function.

[0009] In the fifth aspect, a positioning device is provided, including: a receiving module for receiving a first request message, wherein the first request message is used to request the positioning information of the target terminal; a positioning module for performing an artificial intelligence (AI) positioning process according to the first request message to obtain the positioning information of the target terminal; and a sending module for sending a first notification message, wherein the first notification message includes the positioning information of the target terminal.

[0010] In the sixth aspect, a positioning device is provided, including: a receiving module for receiving a third request message sent by a first device, wherein the third request message is used to request information of a device having an inference function related to AI positioning; a sending module, wherein the third device sends a second response message to the first device according to the third request message, and the second response message includes device information of the second device.

[0011] In the seventh aspect, a positioning device is provided, including: a receiving module for receiving a second request message sent by a first device, the second request message being used to request the second device to obtain the positioning analysis information of the target terminal based on an AI model, and the second device having an AI model inference function; a sending module for sending a first response message to the first device according to the second request message, wherein the first response message includes the positioning analysis information of the target terminal, and the positioning analysis information is generated by the second device based on the AI model inference.

[0012] In the eighth aspect, a positioning device is provided, including: a sending module for sending a fifth request message to a third device, wherein the fifth request message is used to register or update the device information of the fourth device, wherein the device information of the fourth device includes AI positioning training-related capability information, wherein the fourth device has an AI model training function.

[0013] In the ninth aspect, a communication device is provided, which includes a processor and a memory, wherein the memory stores programs or instructions that can be run on the processor, and when the program or instructions are executed by the processor, the steps of the method described in the first aspect, the second aspect, the third aspect, or the fourth aspect are implemented.

[0014] In the tenth aspect, a communication device is provided, comprising a processor and a communication interface, wherein the communication interface and the processor are coupled, and the processor is used to run programs or instructions to implement the steps of the method described in the first aspect, the second aspect, the third aspect, or the fourth aspect.

[0015] In the eleventh aspect, a readable storage medium is provided, on which a program or instruction is stored. When the program or instruction is executed by a processor, the steps of the method described in the first aspect, the second aspect, the third aspect, or the fourth aspect are implemented.

[0016] In the twelfth aspect, a wireless communication system is provided, including: a terminal and a network side device, wherein the terminal can be used to execute the steps of the method described in the first aspect or the second aspect or the third aspect or the fourth aspect.

[0017] In the thirteenth aspect, a chip is provided, which includes a processor and a communication interface, the communication interface and the processor are coupled, and the processor is used to run programs or instructions to implement the steps of the method described in the first aspect, the second aspect, the third aspect, or the fourth aspect.

[0018] In the fourteenth aspect, a computer program / program product is provided, which is stored in a storage medium and is executed by at least one processor to implement the steps of the method described in the first aspect, the second aspect, the third aspect, or the fourth aspect.

[0019] In an embodiment of the present application, the first device receives a first request message, performs an AI positioning process according to the first request message to obtain the positioning information of the target terminal, and sends a first response message including the positioning information of the target terminal. In this way, a complete AI positioning process is provided to realize AI positioning and ensure positioning accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 It is a structural diagram of a wireless communication system provided by an exemplary embodiment of the present application.

[0021] Figure 2 This is one of the flowcharts of the positioning method provided by an exemplary embodiment of the present application.

[0022] Figure 3 This is the second flowchart of the positioning method provided by an exemplary embodiment of the present application.

[0023] Figure 4 It is a schematic diagram of the interactive flow of a positioning method provided by an exemplary embodiment of the present application.

[0024] Figure 5 This is the third flowchart of the positioning method provided by an exemplary embodiment of the present application.

[0025] Figure 6 This is the fourth flowchart of the positioning method provided by an exemplary embodiment of the present application.

[0026] Figure 7 This is the fifth flowchart of the positioning method provided by an exemplary embodiment of the present application.

[0027] Figure 8This is one of the structural schematic diagrams of a positioning device provided by an exemplary embodiment of the present application.

[0028] Figure 9 This is the second structural diagram of the positioning device provided by an exemplary embodiment of the present application.

[0029] Figure 10 This is the third structural diagram of the positioning device provided by an exemplary embodiment of the present application.

[0030] Figure 11 This is the fourth structural diagram of the positioning device provided by an exemplary embodiment of the present application.

[0031] Figure 12 It is a structural diagram of a communication device provided by an exemplary embodiment of the present application.

[0032] Figure 13 It is a structural diagram of a network side device provided by an exemplary embodiment of the present application. DETAILED DESCRIPTION

[0033] The following will be combined with the accompanying drawings in the embodiments of this application to clearly describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field are within the scope of protection of this application.

[0034] The terms "first", "second", etc. in this application are used to distinguish similar objects, and are not used to describe a specific order or sequence. It should be understood that the terms used in this way are interchangeable where appropriate, so that the embodiments of the present application can be implemented in an order other than those illustrated or described herein, and the objects distinguished by "first" and "second" are generally of the same type, and do not limit the number of objects, for example, the first object can be one or more. In addition, "or" in this application represents at least one of the connected objects. For example, "A or B" covers three options, namely, Option 1: including A but not including B; Option 2: including B but not including A; Option 3: including both A and B. The character " / " generally indicates that the objects associated before and after are in an "or" relationship.

[0035] The term "indication" in this application can be either a direct indication (or explicit indication) or an indirect indication (or implicit indication). A direct indication can be understood as the sender explicitly informing the receiver of specific information, the operation to be performed, or the requested result, etc. in the instruction sent; an indirect indication can be understood as the receiver determining the corresponding information based on the instruction sent by the sender, or making a judgment and determining the operation to be performed or the requested result, etc. based on the judgment result.

[0036] It is worth noting that the technology described in the embodiments of the present application is not limited to the Long Term Evolution (LTE) / LTE-Advanced (LTE-A) system, but can also be used in other wireless communication systems, such as Code Division Multiple Access (CDMA), Time Division Multiple Access (TDMA), Frequency Division Multiple Access (FDMA), Orthogonal Frequency Division Multiple Access (OFDMA), Single-carrier Frequency Division Multiple Access (SC-FDMA) or other systems. The terms "system" and "network" in the embodiments of the present application are often used interchangeably, and the technology described can be used for the systems and radio technologies mentioned above, as well as for other systems and radio technologies. The following description describes a New Radio (NR) system for illustrative purposes, and NR terminology is used in most of the following description, but these technologies can also be applied to systems other than NR systems, such as 6th generation (6G) systems. th Generation, 6G) communication system.

[0037] Figure 1The block diagram of a wireless communication system applicable to the embodiments of the present application is shown. The wireless communication system includes a terminal 11 and a network-side device 12. The terminal 11 can be a mobile phone, a tablet computer (Tablet Personal Computer), a laptop computer (Laptop Computer), a notebook computer, a personal digital assistant (PDA), a handheld computer, a netbook, an ultra-mobile personal computer (UMPC), a mobile internet device (MID), an augmented reality (AR), a virtual reality (VR) device, a robot, a wearable device (Wearable Device), an aircraft (flight vehicle), a vehicle user equipment (VUE), a ship-borne device, a pedestrian user equipment (PUE), a smart home (home appliances with wireless communication capabilities, such as refrigerators, televisions, washing machines, or furniture, etc.), a game console, a personal computer (PC), a teller machine, or a self-service machine, etc., and other terminal-side devices. Wearable devices include: smart watches, smart bracelets, smart headphones, smart glasses, smart jewelry (smart bracelets, smart bracelets, smart rings, smart necklaces, smart anklets, smart anklets, etc.), smart wristbands, smart clothing, etc. Among them, the vehicle-mounted device can also be called a vehicle-mounted terminal, a vehicle-mounted controller, a vehicle-mounted module, a vehicle-mounted component, a vehicle-mounted chip or a vehicle-mounted unit, etc. It should be noted that the specific type of the terminal 11 is not limited in the embodiment of the present application. The network side device 12 may include an access network device or a core network device, wherein the access network device may also be called a radio access network (Radio Access Network, RAN) device, a radio access network function or a radio access network unit. The access network device may include a base station, a wireless local area network (Wireless Local Area Network, WLAN) access point (Access Point, AS) or a wireless fidelity (Wireless Fidelity, WiFi) node, etc.Among them, the base station can be referred to as Node B (NB), Evolved Node B (eNB), the next generation Node B (gNB), New Radio Node B (NR Node B), access point, Relay Base Station (RBS), Serving Base Station (SBS), Base Transceiver Station (BTS), radio base station, radio transceiver, Basic Service Set (BSS), Extended Service Set (ESS), Home Node B (HNB), Home Evolved Node B (home evolved Node B), Transmission Reception Point (TRP) or other appropriate terms in the relevant field. As long as the same technical effect is achieved, the base station is not limited to specific technical vocabulary. It should be noted that in the embodiment of the present application, only the base station in the NR system is used as an example for introduction, and the specific type of the base station is not limited.

[0038] The core network equipment may include but is not limited to at least one of the following: core network node, core network function, location management function (LMF), mobility management entity (MME), access and mobility management function (AMF), session management function (SMF), user plane function (UPF), policy control function (PCF), policy and charging rules function unit (PCRF), edge application server discovery function (EASDF), unified data management (UDM), unified data repository (UDR), home user server (HSS), centralized network configuration (CNC), network storage function (NRF), network exposure function (NEF), local NEF (L-NEF), binding support function (BSF), etc. Function, BSF), application function (AF), gateway mobile location center (GMLC), etc. It should be noted that in the embodiment of the present application, only the core network device in the NR system is introduced as an example, and the specific type of the core network device is not limited.

[0039] The technical solutions provided by the embodiments of the present application are described in detail below through some embodiments and their application scenarios in conjunction with the accompanying drawings.

[0040] like Figure 2FIG. 2 is a flow chart of a positioning method 200 provided in an exemplary embodiment of the present application. The method 200 may be, but is not limited to, performed by a first device, and specifically may be performed by at least one of hardware and software installed in the first device. In this embodiment, the method 200 may include at least the following steps.

[0041] S210: The first device receives a first request message.

[0042] The first device may be understood as a device having a positioning function. For example, the first device may be, but is not limited to, an LMF, a service function (SF), a UE, a RAN, and the like.

[0043] The first request message may be, but is not limited to, from a location services consumer (LCS consumer), and is used to request positioning information of the target terminal, such as location estimate information, positioning result, etc., from the first device. The LCS consumer may be a UE, an LCS client, an AF, etc.

[0044] In one implementation, the first request message may include but is not limited to at least one of the following 11)-16).

[0045] 11) A first indication is used to indicate that the positioning request is not perceived by the terminal (UE unaware indication).

[0046] 12) Geographical Area Description (GAD) types supported by the LCS consumer.

[0047] 13) The requested positioning service type, which includes terminal location estimation, etc.

[0048] 14) Requested location service quality information.

[0049] 15) The validity period of the requested terminal location.

[0050] 16) The requested location type, where the location type includes at least one of a current location, a historical location, and a predicted location.

[0051] It can be understood that the relevant descriptions in 11)-16) can refer to the description in TS23273 and will not be repeated here.

[0052] S220: The first device performs an AI positioning process according to the first request message to obtain positioning information of the target terminal.

[0053] Among them, the AI positioning process can be executed independently on the first device, that is, the first device is configured with an AI model for positioning; it can also be executed by other devices different from the first device and the execution results are sent to the first device, that is, the first device is not configured with an AI model for positioning, but needs to call the AI model on other devices for terminal positioning, etc.; the first device can also execute the AI positioning process together with other devices, such as other devices obtaining the intermediate positioning results based on the AI model and sending them to the first device, and then the first device determines the positioning result information based on the intermediate positioning results, etc. This embodiment does not impose any restrictions on this.

[0054] S230: The first device sends a first notification message.

[0055] The first notification message includes but is not limited to the location information of the target terminal. In one implementation, the first notification message can be sent directly by the first device to the LCS consumer, or to other objects, such as a recipient specified by the LCS consumer, which is not limited in this embodiment.

[0056] In addition, the interaction of the first request message and the first notification message between the first device and the LCS consumer may be direct interaction or indirect interaction. For example, when the interaction is not direct, the first device may forward the message via a Gateway Mobile Location Centre (GMLC), AMF, or the like.

[0057] It is worth noting that the AI model mentioned in the context of this application may also be referred to as an AI unit, AI structure, etc., or the AI model may also refer to a processing unit that can implement specific algorithms, formulas, processing procedures, capabilities, etc. related to AI, or the AI model may also be a processing method, algorithm, function, module or unit for a specific data set, or the AI model may be a processing method, algorithm, function, module or unit running on AI-related hardware such as a graphics processing unit (GPU), a neural network processing unit (NPU), a tensor processing unit (TPU), an application-specific integrated circuit (ASIC), etc. This application does not make specific restrictions on this. Optionally, the specific data set may include but is not limited to the input or output of the AI model.

[0058] Correspondingly, the AI model mentioned later can be described by an AI model identifier. The AI model identifier can be an AI unit identifier, an AI structure identifier, an AI algorithm identifier, a functional identifier (functionality ID), a physical identifier, a logical identifier, a global identifier, a local identifier, or an identifier of a specific data set associated with the AI model, or an identifier of a specific scenario related to the AI, an environment identifier related to the AI model, a channel feature identifier related to the AI model, an identifier of a device related to the AI model, or an identifier of a function, feature, capability, or module related to the AI. This application does not specifically limit this.

[0059] In this embodiment, the first device receives a first request message, performs an AI positioning process according to the first request message to obtain the positioning information of the target terminal, and sends a first response message including the positioning information of the target terminal. In this way, a complete AI positioning process is provided to implement AI positioning and ensure positioning accuracy.

[0060] like Figure 3 FIG. 3 is a flow chart of a positioning method 300 provided in an exemplary embodiment of the present application. The method 300 may be, but is not limited to, performed by a first device, and specifically may be performed by at least one of hardware and software installed in the first device. In this embodiment, the method 300 may include at least the following steps.

[0061] S310: The first device receives a first request message.

[0062] The first request message is used to request the location information of the target terminal.

[0063] S320: The first device performs an AI positioning process according to the first request message to obtain positioning information of the target terminal.

[0064] S330: The first device sends a first notification message.

[0065] The first notification message includes the location information of the target terminal.

[0066] It can be understood that the implementation process of S310-S330 can refer to the relevant description in the aforementioned method embodiment 200. Of course, in addition to this, as a possible implementation method, there are multiple implementation processes for the first device to perform the AI positioning process according to the first request message to obtain the positioning information of the target terminal, for example, it may include Figure 3 The contents of S321-S323 shown in FIG are as follows.

[0067] S321: The first device sends a second request message to the second device according to the first request message.

[0068] The second device has an AI model inference function. For example, in this embodiment, the second device may include but is not limited to a location analysis function (Analytics Location Function, AnLF) and the like.

[0069] The second request message is used to request the second device to obtain the positioning analysis information of the target terminal based on the AI model. In some embodiments, the second request message may include, but is not limited to, at least one of the following 201)-210), so that the positioning analysis information provided by the second device meets the positioning requirements.

[0070] 201) Analysis type or analysis identifier (analytics ID), used to request the second device to perform AI positioning reasoning to implicitly request the positioning analysis information from the second device, or the analysis type or analysis identifier is used to explicitly request the positioning analysis information from the second device so that the second device is clear about the analysis type requested by the first device.

[0071] For example, when the analytics ID=AI positioning, the second device may determine that the first device requests to obtain the positioning analysis information of the target terminal based on the AI model.

[0072] It is worth noting that the analysis types mentioned in the context of this application can also be referred to as inference types, and analysis identifiers can also be referred to as inference identifiers. Furthermore, the inference operations involved in the context of this application can also be understood as data analysis operations, inference functions can also be understood as data analysis functions, and inference tasks can be understood as data analysis tasks.

[0073] 202) Positioning performance requirements or positioning accuracy requirements.

[0074] The positioning performance requirement or positioning accuracy requirement may be, but is not limited to, determined by the first device based on the "requested location service quality information" in the request message, so as to request the second device to provide positioning analysis information that meets the requirements.

[0075] 203) The positioning method that the second device needs to adopt when obtaining the positioning analysis information.

[0076] The positioning method may include but is not limited to an uplink positioning method, a downlink positioning method, etc. The uplink positioning method may be understood as a method for acquiring positioning information based on measurement quantities reported by the RAN as input data for reasoning. The downlink positioning method may be understood as a method for acquiring positioning information based on measurement quantities reported by the UE as input data for reasoning.

[0077] In this embodiment, the indication of the positioning method to be adopted when the second device obtains the positioning analysis information can enable the second device to provide positioning analysis information that meets the requirements of the first device.

[0078] 204) The positioning inference method that needs to be adopted when the second device performs AI positioning inference.

[0079] The positioning reasoning method may include but is not limited to direct positioning (direct AI positioning), indirect positioning (indirect AI positioning), etc. The direct positioning may be understood as the reasoning output data being positioning result information, and the indirect positioning may be understood as the reasoning output data being positioning intermediate information.

[0080] In this embodiment, the second device is instructed to use a positioning reasoning method when performing AI positioning reasoning, so that the second device can provide positioning analysis information that meets the needs of the first device.

[0081] 205) Input data, used by the second device to perform AI positioning inference based on the input data to ensure that the positioning analysis information obtained by the second device meets the needs of the first device.

[0082] In some embodiments, the input data may be, but is not limited to, acquired by the first device when sending the second request message. In this embodiment, the input data may include, but is not limited to, at least one of the following 2051)-2053).

[0083] 2051) Positioning measurement data from the terminal or access network equipment.

[0084] The positioning measurement data is positioning measurement data for the target terminal, for example, positioning reference signal (PRS) measurement data for the target terminal provided by the terminal, sounding reference signal (SRS) measurement data for the target terminal from the RAN, etc.

[0085] In this embodiment, the terminal that provides the positioning measurement data and subsequent positioning assistance data may be the same as or different from the target terminal, and this is not limited here.

[0086] 2052) Positioning assistance data from the terminal or access network equipment.

[0087] Among them, the positioning assistance data can be but is not limited to reference time (Reference Time), reference location (Reference Location), PRS identifier (ID), PRS spectrum bandwidth, synchronization signal block (Synchronization Signal and PBCH block, SSB) configuration (configuration) of the target reference point (Target Reference Point), etc.

[0088] 2053) Positioning configuration data or positioning assistance data from the first device.

[0089] 206) The type or identifier of the output data is used to request the second device to provide the positioning analysis information corresponding to the type or identifier of the output data, thereby ensuring that the positioning analysis information provided by the second device meets the positioning requirements.

[0090] 207) The target terminal information is used to indicate that the object of AI positioning reasoning is the target terminal.

[0091] The information of the target terminal may be, but is not limited to, a terminal identification (ID) and the like.

[0092] 208) Manufacturer information corresponding to the first device.

[0093] 209) Information of a specified time is used to instruct to obtain the positioning analysis information of the target terminal corresponding to the specified time.

[0094] 210) Information of a designated area, used to instruct acquisition of positioning analysis information of the target terminal related to the designated area.

[0095] Wherein, in the case where the second request message includes information of the designated area, the second request message also includes first indication information, and the first indication information is used to indicate obtaining positioning analysis information of the target object within the designated area or outside the designated area.

[0096] It is worth noting that which information in the aforementioned 201)-210) is included in the second request message during the positioning process can be determined by protocol agreement or other means and is not limited here.

[0097] Based on this, after receiving the second request message, the second device infers the location analysis information of the target terminal based on the AI model and the information in the second request message and sends it. Prior to this, the second device may optionally determine or select the AI model used for location inference based on the second request message.

[0098] For example, the second device may select an AI model for positioning based on one or more of the analysis type or analysis identifier in the second request message, the positioning performance requirements or positioning accuracy requirements, and the manufacturer information corresponding to the first device, and then use the input data in the second request message as the input of the AI model to infer the positioning analysis information of the target terminal.

[0099] The positioning analysis information of the target terminal may be positioning analysis information corresponding to a specified time or related to a specified area.

[0100] In some embodiments, the positioning analysis information may be at least one of positioning intermediate information and positioning result information, wherein the positioning intermediate information is used to determine the positioning result information of the target terminal, such as used by the first device or the LCS consumer itself to determine the positioning result information based on the positioning intermediate information, which is not limited here.

[0101] In addition, the positioning analysis information can also be a prediction type result or a statistical type result. Among them, the prediction type result means that the positioning analysis information is predicted for a future time (i.e., the corresponding input data is a future time). The statistical type result, also known as the detection type result, means that the positioning analysis information is statistically obtained for the current time (i.e., the corresponding input data is the current time).

[0102] In one implementation, if the second device determines that it does not have the AI model based on the second request message, then the second device may obtain the AI model from the fourth device, or the second device obtains the AI model through local model training and, based on the AI model, performs the step of sending a first response message to the first device.

[0103] The fourth device may be understood as a device having a model training function, such as a model training location function (MTLF).

[0104] S322: The first device receives a first response message sent by the second device.

[0105] Among them, the first response message includes the positioning analysis information of the target terminal, and the positioning analysis information is generated by the second device based on the AI model reasoning.

[0106] In one embodiment, in addition to including the positioning analysis information of the target terminal, the first response message may also include at least one of the following 31)-36) so that the first device can understand the detailed information of the positioning analysis information based on the first response message, and then ensure whether it meets the positioning requirements.

[0107] 31) Accuracy information corresponding to the positioning analysis information.

[0108] 32) The positioning method used by the second device to obtain the positioning analysis information.

[0109] Among them, if the first response message includes the information described in 32), the first device can determine the positioning method adopted by the second device when determining the positioning analysis information based on the information.

[0110] 33) The positioning inference method used by the second device to obtain the positioning analysis information.

[0111] Among them, if the first response message includes the information described in 33), the first device can determine the positioning reasoning method adopted by the second device when determining the positioning analysis information based on the information.

[0112] 34) The type or identifier of the output data, used to indicate the type or identifier of the output data corresponding to the positioning analysis information.

[0113] Among them, if the first response message includes the information described in 34), the first device can determine the positioning analysis information provided by the second device based on the information, and determine how to process the positioning analysis information, such as whether to send it directly as the positioning information of the target terminal.

[0114] 35) The target terminal information is used to indicate that the object corresponding to the positioning analysis information is the target terminal.

[0115] 36) Credibility of the location analysis information. The credibility of the location analysis information may be applicable to prediction scenarios. For example, if the location analysis information is a prediction result, the first response message may include the credibility of the location analysis information, allowing the first device to ensure the credibility of the location analysis information and determine subsequent operations, such as whether to send it to the LCS consumer or a recipient designated by the LCS consumer.

[0116] S323: The first device determines the positioning information of the target terminal according to the positioning analysis information.

[0117] Among them, if the positioning analysis information is intermediate positioning information, then after receiving the positioning analysis information, the first device can directly use it as the positioning information of the target terminal, or determine the positioning result information based on the intermediate positioning information, and then use the positioning result information as the positioning information of the target terminal. There is no restriction here.

[0118] If the positioning analysis information is positioning result information, then the first device may directly use it as the positioning information of the target terminal.

[0119] In one implementation, for the aforementioned second device with AI model inference function, its relevant information (such as device identification, address, etc.) can be configured in the first device as agreed upon in the protocol, or it can be obtained from other devices by request, without any restriction here.

[0120] For example, in some embodiments, assuming that the relevant information of the second device is obtained from a third device by request, the first device may send a third request message to the third device, wherein the third request message is used to request information about a device with reasoning functions related to AI positioning. The third device may be understood as a device with a network storage function. For example, in this embodiment, the third device may be, but is not limited to, an NRF, a UDM, or a UDR.

[0121] The third request message may include but is not limited to at least one of the following 401)-410).

[0122] 401) The type of device requested.

[0123] For example, when NF type=Network Data Analytics Function (NWDAF), it indicates that the requested device is a NWDAF type device. Furthermore, when NF type=NWDAF containingAnLF, it indicates that the requested device is an AnLF type device.

[0124] 402) Analysis type or analysis identifier, used to indicate that the requested device needs to support the reasoning task corresponding to the analysis type or analysis identifier.

[0125] For example, when the analytics ID=AI positioning, the third device may determine that the device requested by the first device needs to support the reasoning task corresponding to AI positioning.

[0126] 403) The requested device needs to support the positioning method.

[0127] The positioning method that the requested device needs to support may be, but is not limited to, an uplink positioning method, a downlink positioning method, and the like.

[0128] 404) The requested device needs to support the positioning inference method.

[0129] The positioning inference methods that the requested device needs to support may include but are not limited to direct positioning, indirect positioning, etc.

[0130] 405) The target terminal information is used to indicate that the object corresponding to the reasoning task is the target terminal.

[0131] 406) Information about the time of interest is used to indicate that the requested device needs to support reasoning tasks within the time of interest. The time of interest can be current or future time, and can be a time point or a time period, without limitation.

[0132] 407) Information about the area of interest, indicating that the requested device needs to support reasoning tasks within the area of interest. The information about the area of interest can be a Tracking Area Identity (TAI) or other types of Area of Interest (AOI), etc., without limitation.

[0133] 408) Manufacturer information corresponding to the requested device.

[0134] 409) Manufacturer information corresponding to the first device.

[0135] Among them, the indication of the manufacturer information in 408)-409) can be used for the third device to determine whether the first device is allowed to obtain the positioning analysis information of the second device based on the above manufacturer information, thereby ensuring the smooth execution of the positioning process.

[0136] 410) Positioning accuracy requirement information. The positioning accuracy requirement information may be, but is not limited to, determined based on the positioning service quality information in the first request message.

[0137] Based on this, after receiving the third request message, the third device can query the stored or registered device information to feedback to the first device the device information that has the reasoning function related to AI positioning. For example, the third device can send a second response message to the first device, where the second response message includes the device information of the second device, and the second device has the reasoning function related to AI positioning.

[0138] In some embodiments, the second device may also be referred to as a second device instance. The device information of the second device may include but is not limited to at least one of the following 51)-56) for the first device to know the second device.

[0139] 51) Identification of the second device.

[0140] 53) The fully qualified domain name (FQDN) of the second device.

[0141] 54) Uniform Resource Locator (URL) of the second device.

[0142] 55) The Internet Protocol (IP) address of the second device.

[0143] 56) The Media Access Control (MAC) address of the second device.

[0144] In addition, in one implementation, the second response message may also include at least one of the following information 61)-65) corresponding to the second device.

[0145] 61) Manufacturer information corresponding to the second device.

[0146] 62) Positioning methods supported by the second device.

[0147] The positioning method may be, but is not limited to, an uplink positioning method, a downlink positioning method, and the like.

[0148] 63) Positioning inference method supported by the second device.

[0149] The positioning reasoning method may be, but is not limited to, direct positioning, indirect positioning, etc.

[0150] 64) The type or identifier of the output data is used to indicate that the second device supports the positioning analysis information corresponding to the output data type or identifier.

[0151] 65) Positioning accuracy, used to indicate the positioning accuracy or performance corresponding to the positioning analysis information of the second device.

[0152] It can be understood that, through the indication of the information in 61)-65), the first device can further understand the relevant information when the second device performs AI reasoning, such as positioning method, positioning reasoning method, etc., so that the first device can select a suitable second device to send the second request message when receiving the first request message from the LCS consumer, so as to ensure the reliability of the positioning result.

[0153] For example, after receiving the second response message, if the first device receives a first request message from the LCSconsumer, it can send a second request message to the second device indicated in the second response message to request to obtain the positioning analysis information of the target terminal based on the AI model.

[0154] Of course, in some embodiments, the first device may also send a third request message to the third device after receiving the first request message, and send a second request message to the second device indicated in the second response message fed back by the third device to request to obtain the positioning analysis information of the target terminal based on the AI model.

[0155] In some embodiments, the first device determines to use an AI-based positioning method to locate the target terminal. For example, the first device may determine to use an AI-based positioning method to locate the target terminal if a first condition is met, where the first condition includes: the first device obtains device information having an inference function related to AI positioning; conversely, if the first condition is not met, the first device may determine to use a positioning method other than the AI-based positioning method to locate the target terminal.

[0156] In some embodiments, for the aforementioned third device, in order to facilitate the first device and other devices to search for devices with AI positioning and reasoning related capability information for AI positioning and improve positioning efficiency, in addition to storing the devices with AI positioning and reasoning related capability information on the third device through a protocol agreement, the information can also be stored on the third device through a registration or update request.

[0157] For example, a second device with AI positioning and reasoning capabilities can send a fourth request message to the third device, where the fourth request message is used to register or update the device information of the second device. Upon receiving the fourth request message from the second device, the third device registers or updates the device information of the second device.

[0158] Among them, the AI positioning reasoning related capability information may include but is not limited to at least one of the following 701)-711).

[0159] 701) Positioning indication information, used to indicate that the second device supports positioning-related AI model reasoning, or used to indicate that the second device supports outputting terminal positioning-related reasoning results.

[0160] Among them, one form of the positioning indication information is to assign the supported data analysis result type (ie, analytic ID, or reasoning task type) to UE positioning info or AI positioning, that is, analytic ID = UE positioning info, or analytic ID = AI positioning, etc.

[0161] 702) Positioning methods supported by the second device. The positioning methods may include uplink positioning methods, downlink positioning methods, and the like. The uplink positioning method may be understood as a method for acquiring positioning information based on measurement quantities reported by the RAN as input data for inference. The downlink positioning method may be understood as a method for acquiring positioning information based on measurement quantities reported by the UE as input data for inference.

[0162] 703) Positioning inference method supported by the second device.

[0163] The positioning reasoning method may include but is not limited to direct positioning, indirect positioning, etc. Direct positioning may be understood as the reasoning output data being positioning result information, and indirect positioning may be understood as the reasoning output data being positioning intermediate information.

[0164] 704) allows the use of information about the object of the location analysis information.

[0165] For example, the object information may include, but is not limited to, at least one of the object type, object manufacturer information, object identifier, and object address information. The object type may include, but is not limited to, a UE, a Positioning Reference Unit (PRU), a gNB, a LMF, and the like.

[0166] 705) The type or granularity of input data required for inference.

[0167] The type of input data may include but is not limited to measurement data, intermediate characteristic data, auxiliary data, etc. The measurement data may be but is not limited to channel impulse response (CIR), power delay profile (PDP), delay profile (DP), reference signal received power (RSRP), reference signal received path power (RSRPP), or reference signal time difference (RSTD). The intermediate characteristic data may be but is not limited to time of arrival (TOA), path phase, etc. The auxiliary data may be but is not limited to reference signal configuration (RS configuration), etc.

[0168] In one implementation, if the type of the input data is measurement data, then the AI positioning reasoning-related capability information may also include signal type information corresponding to the measurement data, such as PRS, SRS, etc.

[0169] The granularity of the input data may be a Tracking Area (TA) granularity, a cell granularity, or other finer granularity, etc., wherein the finer granularity may be smaller than the cell granularity, etc.

[0170] 706) The type or granularity of the output data obtained by inference.

[0171] The output data may be, but not limited to, positioning analysis information, etc. Based on this, the type of the output data may be, but not limited to, positioning result information, intermediate positioning information (or intermediate features), etc.

[0172] The granularity of the output data may be, but is not limited to, positioning analysis information of TA granularity, positioning analysis information of cell granularity, or positioning analysis information of finer granularity.

[0173] 707) Supported positioning accuracy, used to indicate at least one of the precision and credibility of the inferred positioning analysis information. For example, the supported positioning accuracy may be a 98% confidence level positioning error of less than 0.5 meters.

[0174] 708) Device information of the second device.

[0175] Among them, the device information of the second device can be but is not limited to NF instance ID, FQDN, IP address, network element instance identification information, etc.

[0176] 709) Network element type (NF type), such as whether it has AI reasoning capabilities.

[0177] For example, when NF type=NWDAF, it indicates that the second device is a NWDAF type device. Further, when NF type=NWDAF containing AnLF, it indicates that the second device is a AnLF type device.

[0178] 710) Service area: used to indicate the supported positioning service area.

[0179] 711) Manufacturer information of the second device.

[0180] It is worth noting that by storing and recording the AI positioning and reasoning related capability information of the second device through the third device, it is convenient for other network elements (such as the first device) to find and discover devices with specific AI positioning and reasoning related capability information in the future to perform AI positioning and improve positioning efficiency.

[0181] In other embodiments, in order to facilitate the second device to search for devices with AI positioning training-related capability information to obtain the AI model, in addition to storing the devices with AI positioning training-related capability information on the third device through a protocol agreement, the devices may also be stored on the third device through a registration or update request.

[0182] For example, a fourth device with AI model training capabilities can send a fifth request message to a third device, where the fifth request message is used to register or update the device information of the fourth device. The third device can then receive the fifth request message sent by the fourth device and register or update its device information. The device information of the fourth device includes information about AI positioning training capabilities.

[0183] In some embodiments, the AI positioning training-related capability information may include but is not limited to at least one of the following 81)-87).

[0184] 81) First capability information, used to indicate that the fourth device supports the training of an AI model for positioning, or that the fourth device has the ability to train positioning-related AI models.

[0185] For example, the first capability information may be expressed in a supporting analytics ID, such as supporting analytics ID=AI positioning.

[0186] 82) A positioning method supported (or applicable) by the AI positioning model trained by the fourth device. The positioning method may be, but is not limited to, an uplink positioning method, a downlink positioning method, or the like. The uplink positioning method may be understood as a method for acquiring positioning information based on measurement quantities reported from the RAN as input data for reasoning. The downlink positioning method may be understood as a method for acquiring positioning information based on measurement quantities reported from the UE as input data for reasoning.

[0187] 83) The positioning reasoning method supported by the AI positioning model trained by the fourth device.

[0188] The positioning reasoning method may include but is not limited to direct positioning, indirect positioning, etc. Direct positioning can be understood as when reasoning is performed based on the AI positioning model trained by the fourth device, the output data of which is positioning result information; indirect positioning can be understood as when reasoning is performed based on the AI positioning model trained by the fourth device, the output data of which is positioning intermediate information.

[0189] 84) Information about the object allowing the AI positioning model trained using the fourth device.

[0190] For example, the object information may include, but is not limited to, at least one of the object type, object manufacturer information, object identifier, and object address information. The object type may include, but is not limited to, UE, PRU, gNB, LMF, etc.

[0191] 85) Input data type, used to indicate the type or granularity of input data required for model training, or the type or granularity of input data required for the trained AI positioning model.

[0192] The type of input data may include, but is not limited to, measurement data, intermediate characteristic data, and auxiliary data. The measurement data may include, but is not limited to, CIR, PDP, DP, RSRP, RSRPP, or RSTD. The intermediate characteristic data may include, but is not limited to, TOA, path phase, etc. The auxiliary data may include, but is not limited to, reference signal configuration (RS configuration), etc.

[0193] In one implementation, if the type of the input data is measurement data, then the AI positioning reasoning-related capability information may also include signal type information corresponding to the measurement data, such as PRS, SRS, etc.

[0194] The granularity of the input data may be TA granularity, cell granularity, finer granularity, etc.

[0195] 86) The type of output data is used to indicate the type or granularity of the output data corresponding to the trained AI positioning model.

[0196] The output data may be, but not limited to, positioning analysis information, etc. Based on this, the type of the output data may be, but not limited to, positioning result information, positioning intermediate features, etc.

[0197] The granularity of the output data may be, but is not limited to, positioning analysis information of TA granularity, positioning analysis information of cell granularity, or positioning analysis information of finer granularity.

[0198] 87) Supported positioning accuracy, used to indicate at least one of the fineness and credibility of the positioning analysis information output by the AI positioning model trained by the fourth device.

[0199] For example, the supported positioning accuracy may be a positioning error of less than 0.5 meters with a confidence level of 98%.

[0200] It is worth noting that by storing and recording the device information of the fourth device, such as AI positioning training-related capability information, through the first device, it can facilitate other network elements (such as the second device, etc.) to find and discover devices with specific AI positioning capabilities in the future, so as to train or obtain AI models.

[0201] In an embodiment of the present application, through the interaction between a first device such as LMF and a second device with AI reasoning function, positioning analysis information determined based on the AI method is obtained, so that the positioning accuracy can be improved while achieving terminal positioning.

[0202] It should be noted that in the context of this application, the first device and the second device and the fourth device can be deployed independently, such as being deployed on different physical entities respectively, or they can be deployed on the same physical entity at the same time, such as the first device and the second device and the fourth device are deployed on the same physical entity, or the second device and the fourth device are deployed on the same physical entity, and there is no restriction here.

[0203] Among them, for the situation where the first device, the second device and the fourth device are deployed on different physical entities, while realizing AI positioning, it can also avoid the need to upgrade the traditional first device (such as LMF) and add AI functions. At the same time, it can also avoid the problem of affecting the performance and efficiency of traditional positioning services due to the addition of AI functions.

[0204] For the situation where the first device and the second device and the fourth device are not deployed on the same physical entity, since it can avoid the signaling interaction process between the first device, the second device and the fourth device, such as the positioning service function can directly call the AI model inference function, the AI model training function, etc. through function calls to perform positioning of the target terminal, it can save signaling overhead.

[0205] Based on the positioning method provided in the aforementioned method embodiments 200-300, the following is combined with Figure 4 The implementation process of the positioning method provided in the aforementioned method embodiments 200-300 is further described as follows.

[0206] Among them, Figure 4 As shown, assuming that the first device, the second device, and the fourth device are independently deployed on different physical entities, and the first device is LMF, the second device is AnLF, the third device is NRF, and the fourth device is MTLF, then the implementation process may include but is not limited to the following steps.

[0207] S401: AnLF sends a fourth request message to NRF to register or update device information of the AnLF.

[0208] S402: The MTLF sends a fifth request message to the NRF to register or update device information of the MTLF.

[0209] S403: The LCS consumer sends a first request message to the LMF to request the location information of the target terminal.

[0210] S404: LMF sends a third request message to NRF based on the first request message to request information about devices with reasoning functions related to AI positioning.

[0211] S405: The NRF sends a second response message to the LMF, where the second response message includes information about the AnLF.

[0212] S406: LMF determines to use the AI-based positioning method according to the second response message.

[0213] S407, LMF obtains input data required for positioning inference.

[0214] S408, LMF sends a second request message to the AnLF corresponding to the AnLF information included in the second response message according to the first request message, so as to request the AnLF to obtain the positioning analysis information of the target terminal based on the AI model.

[0215] S409: The AnLF generates positioning analysis information of the target terminal according to the second request message and based on the AI model reasoning.

[0216] Optionally, if the AI model does not exist in the AnLF, the AnLF may obtain the AI model through local model training, or may request the AI model from the MTLF, which is not limited here.

[0217] S410: The AnLF sends a first response message to the LMF, where the first response message includes positioning analysis information of the target terminal.

[0218] S411, the LMF determines the positioning information of the target terminal based on the positioning analysis information.

[0219] S412, the LMF sends a first notification message, where the first notification message includes the location information of the target terminal.

[0220] It is understood that the various processes shown in the aforementioned S401-S412 can refer to the relevant descriptions in the aforementioned method embodiments 200-300 and achieve the same or corresponding technical effects. To avoid repetition, they will not be described here. Figure 4 The positioning process shown may include but is not limited to the steps shown in the aforementioned S401-S412. For example, it may include more or fewer steps than the aforementioned S401-S412, which is not limited here.

[0221] like Figure 5 FIG. 5 is a flow chart of a positioning method 500 provided in an exemplary embodiment of the present application. The method 500 may be, but is not limited to, performed by a third device, specifically, by at least one of hardware and software installed in the third device. In this embodiment, the method 500 may include at least the following steps.

[0222] S510: The third device receives a third request message sent by the first device, where the third request message is used to request information about a device having an inference function related to AI positioning.

[0223] S520: The third device sends a second response message to the first device according to the third request message, where the second response message includes device information of the second device.

[0224] In an optional implementation, the third request message includes at least one of the following: the type of the requested device; the analysis type or analysis identifier, used to indicate that the requested device needs to support the reasoning task corresponding to the analysis type or analysis identifier; the positioning method that the requested device needs to support; the positioning reasoning method that the requested device needs to support; the information of the target terminal, used to indicate that the object corresponding to the reasoning task is the target terminal; the information of the time of interest, used to indicate that the requested device needs to support the reasoning task within the time of interest; the information of the area of interest, used to indicate that the requested device needs to support the reasoning task within the area of interest; the manufacturer information corresponding to the requested device; the manufacturer information corresponding to the first device; and the positioning accuracy requirement information.

[0225] In an optional implementation, the second response message also includes at least one of the following information corresponding to the second device: manufacturer information corresponding to the second device; positioning methods supported by the second device; positioning inference methods supported by the second device; output data type or identifier, used to indicate that the second device supports positioning analysis information corresponding to the output data type or identifier; positioning accuracy, used to indicate the positioning accuracy or performance corresponding to the positioning analysis information of the second device.

[0226] In an optional implementation, the method also includes at least one of the following: the third device receives a fourth request message sent by the second device, and the fourth request message is used to register or update the device information of the second device, wherein the device information of the second device includes AI positioning reasoning-related capability information, and the second device has an AI model reasoning function; the third device receives a fifth request message sent by the fourth device, and the fifth request message is used to register or update the device information of the fourth device, wherein the device information of the fourth device includes AI positioning training-related capability information, and wherein the fourth device has an AI model training function.

[0227] In an optional implementation, the AI positioning reasoning-related capability information includes at least one of the following: positioning indication information, used to indicate that the second device supports positioning-related AI model reasoning, or used to indicate that the second device supports outputting terminal positioning-related reasoning results; the positioning method supported by the second device; the positioning reasoning method supported by the second device; information on objects allowed to use positioning analysis information; the type or granularity of the input data required for reasoning; the type or granularity of the output data obtained by reasoning; supported positioning accuracy, used to indicate at least one of the fineness and credibility of the positioning analysis information obtained by reasoning.

[0228] In an optional implementation, the AI positioning training-related capability information includes at least one of the following: first capability information, used to indicate that the fourth device supports the training of the AI model for positioning, or that the fourth device has the ability to train positioning-related AI models; the positioning method supported by the AI positioning model trained by the fourth device; the positioning inference method supported by the AI positioning model trained by the fourth device; the object allowed to use the AI positioning model trained by the fourth device; the type of input data, used to indicate the type or granularity of the input data required for model training, or the type or granularity of the input data required for the trained AI positioning model; the type of output data, used to indicate the type or granularity of the output data corresponding to the trained AI positioning model; the supported positioning accuracy, used to indicate at least one of the fineness and credibility of the positioning analysis information output by the AI positioning model trained by the fourth device.

[0229] In an optional implementation, the first device, the second device, and the fourth device are deployed in the same physical entity, or the first device, the second device, and the fourth device are deployed in different physical entities.

[0230] In an optional implementation, the first device includes a location service function LMF, or the second device includes an inference function AnLF; or the third device includes a network storage function NRF, or the fourth device has a model training function MTLF.

[0231] It can be understood that each implementation method in method embodiment 500 has the same or corresponding technical features as the aforementioned method embodiments 200-300. Therefore, the relevant descriptions of each implementation method in method embodiment 500 can refer to the relevant descriptions in the aforementioned method embodiments 200-300, and achieve the same or corresponding technical effects. To avoid repetition, they will not be repeated here.

[0232] like Figure 6 FIG. 6 is a flow chart of a positioning method 600 provided in an exemplary embodiment of the present application. The method 600 may be, but is not limited to, executed by a second device, and may specifically be executed by at least one of hardware and software installed in the second device. In this embodiment, the method 600 may include at least the following steps.

[0233] S610, the second device receives a second request message sent by the first device, where the second request message is used to request the second device to obtain positioning analysis information of the target terminal based on the AI model, and the second device has an AI model inference function.

[0234] S620, the second device sends a first response message to the first device, wherein the first response message includes positioning analysis information of the target terminal, and the positioning analysis information is generated by the second device according to the second request message and based on the AI model reasoning.

[0235] In an optional implementation, the second request message includes at least one of the following: an analysis type or an analysis identifier, used to indicate a request for the second device to perform AI positioning reasoning, or used to request the second device to obtain positioning analysis information; positioning performance requirements or positioning accuracy requirements; a positioning method, used to request the second device to obtain the positioning analysis information according to the positioning method; a positioning reasoning method to be adopted when the second device performs AI positioning reasoning; input data, used for the second device to perform AI positioning reasoning based on the input data; the type or identifier of the output data, used to request the second device to provide the positioning analysis information corresponding to the type or identifier of the output data; information of the target terminal, used to indicate that the object of AI positioning reasoning is the target terminal; manufacturer information corresponding to the first device; information of the specified time, used to indicate the acquisition of the positioning analysis information of the target terminal corresponding to the specified time; information of the specified area, used to indicate the acquisition of the positioning analysis information of the target terminal related to the specified area.

[0236] In an optional implementation, when the second request message includes information about the designated area, the second request message also includes first indication information, where the first indication information is used to indicate obtaining positioning analysis information of the target object within or outside the designated area.

[0237] In an optional implementation, the input data includes at least one of the following: positioning measurement data from a terminal or access network device; positioning assistance data from a terminal or access network device; positioning configuration data or positioning assistance data from the first device.

[0238] In an optional implementation, the positioning analysis information includes at least one of the following: intermediate positioning information, where the intermediate positioning result is used to determine positioning result information; and positioning result information.

[0239] In an optional implementation, the positioning analysis information includes at least one of the following information types: prediction type; statistical type.

[0240] In an optional implementation, the first response message also includes at least one of the following: accuracy information corresponding to the positioning analysis information; the positioning method used by the second device to obtain the positioning analysis information; the positioning inference method used by the second device to obtain the positioning analysis information; an output data type or identifier, used to indicate the type or identifier of the output data corresponding to the positioning analysis information; information of the target terminal, used to indicate that the object corresponding to the positioning analysis information is the target terminal; and the credibility of the positioning analysis information.

[0241] In an optional implementation, the method further includes: when the AI model does not exist in the second device, the second device obtains the AI model from a fourth device, or the second device obtains the AI model through model training, and the fourth device has an AI model training function.

[0242] In an optional implementation, the method also includes: the second device sends a fourth request message to the third device, and the fourth request message is used to register or update the device information of the second device, wherein the device information of the second device includes AI positioning reasoning related capability information.

[0243] In an optional implementation, the AI positioning reasoning-related capability information includes at least one of the following: positioning indication information, used to indicate that the second device supports positioning-related AI model reasoning, or used to indicate that the second device supports outputting terminal positioning-related reasoning results; the positioning method supported by the second device; the positioning reasoning method supported by the second device; information on objects allowed to use positioning analysis information; the type or granularity of the input data required for reasoning; the type or granularity of the output data obtained by reasoning; supported positioning accuracy, used to indicate at least one of the fineness and credibility of the positioning analysis information obtained by reasoning.

[0244] In an optional implementation, the first device, the second device, and the fourth device are deployed in the same physical entity, or the first device, the second device, and the fourth device are deployed in different physical entities.

[0245] In an optional implementation, the first device includes a location service function LMF, or the second device includes an inference function AnLF; or the third device includes a network storage function NRF, or the fourth device has a model training function MTLF.

[0246] It can be understood that each implementation method in method embodiment 600 has the same or corresponding technical features as the aforementioned method embodiments 200-300. Therefore, the relevant descriptions of each implementation method in method embodiment 600 can refer to the relevant descriptions in the aforementioned method embodiments 200-300, and achieve the same or corresponding technical effects. To avoid repetition, they will not be repeated here.

[0247] like Figure 7 FIG. 7 is a flow chart of a positioning method 700 provided in an exemplary embodiment of the present application. The method 700 may be, but is not limited to, performed by a fourth device, specifically, by at least one of hardware and software installed in the fourth device. In this embodiment, the method 700 may include at least the following steps.

[0248] S710, the fourth device sends a fifth request message to the third device, where the fifth request message is used to register or update the device information AI positioning training-related capability information of the fourth device, wherein the fourth device has an AI model training function.

[0249] In an optional implementation, the AI positioning training-related capability information includes at least one of the following: first capability information, used to indicate that the fourth device supports the training of the AI model for positioning, or that the fourth device has the ability to train positioning-related AI models; the positioning method supported by the AI positioning model trained by the fourth device; the positioning inference method supported by the AI positioning model trained by the fourth device; the object allowed to use the AI positioning model trained by the fourth device; the type of input data, used to indicate the type or granularity of the input data required for model training, or the type or granularity of the input data required for the trained AI positioning model; the type of output data, used to indicate the type or granularity of the output data corresponding to the trained AI positioning model; the supported positioning accuracy, used to indicate at least one of the fineness and credibility of the positioning analysis information corresponding to the AI positioning model trained by the fourth device.

[0250] In an optional implementation, the third device includes a network storage function NRF, or the fourth device has a model training function MTLF.

[0251] It can be understood that each implementation method in method embodiment 700 has the same or corresponding technical features as the aforementioned method embodiments 200-300. Therefore, the relevant descriptions of each implementation method in method embodiment 700 can refer to the relevant descriptions in the aforementioned method embodiments 200-300, and achieve the same or corresponding technical effects. To avoid repetition, they will not be repeated here.

[0252] The positioning method provided in the embodiment of the present application can be executed by a positioning device. In the embodiment of the present application, the positioning method performed by the positioning device is taken as an example to illustrate the positioning device provided in the embodiment of the present application.

[0253] like Figure 8 As shown, it is a structural diagram of a positioning device 800 provided in an embodiment of the present application. The device 800 includes a receiving module 810 for receiving a first request message, where the first request message is used to request the positioning information of the target terminal; a positioning module 820 for performing an artificial intelligence (AI) positioning process according to the first request message to obtain the positioning information of the target terminal; and a sending module 830 for sending a first notification message, where the first notification message includes the positioning information of the target terminal.

[0254] In an optional implementation, the AI positioning process is performed according to the first request message to obtain the positioning information of the target terminal, including: sending a second request message to a second device according to the first request message, the second request message is used to request the second device to obtain the positioning analysis information of the target terminal based on the AI model, and the second device has an AI model reasoning function; receiving a first response message sent by the second device, the first response message includes the positioning analysis information of the target terminal, and the positioning analysis information is generated by the second device based on the AI model reasoning; determining the positioning information of the target terminal according to the positioning analysis information.

[0255] In an optional implementation, the second request message includes at least one of the following: an analysis type or analysis identifier, used to request the second device to perform AI positioning reasoning, or to request the positioning analysis information from the second device; positioning performance requirements or positioning accuracy requirements; the positioning method that the second device needs to adopt when obtaining the positioning analysis information; the positioning reasoning method that the second device needs to adopt when performing AI positioning reasoning; input data, used for the second device to perform AI positioning reasoning based on the input data; the type or identifier of the output data, used to request the second device to provide the positioning analysis information corresponding to the type or identifier of the output data; information of the target terminal, used to indicate that the object of AI positioning reasoning is the target terminal; manufacturer information corresponding to the first device; information of the specified time, used to indicate the acquisition of the positioning analysis information of the target terminal corresponding to the specified time; information of the specified area, used to indicate the acquisition of the positioning analysis information of the target terminal related to the specified area.

[0256] In an optional implementation, when the second request message includes information about the specified area, the second request message also includes first indication information, and the first indication information is used to indicate obtaining positioning analysis information of the target object within the specified area or outside the specified area.

[0257] In an optional implementation, the input data includes at least one of the following: positioning measurement data from a terminal or access network device; positioning assistance data from a terminal or access network device; positioning configuration data or positioning assistance data from the first device.

[0258] In an optional implementation, the positioning analysis information includes at least one of the following: intermediate positioning information, where the intermediate positioning information is used to determine positioning result information of the target terminal; and positioning result information.

[0259] In an optional implementation, the positioning analysis information includes at least one of the following information types: prediction type; statistical type.

[0260] In an optional implementation, the first response message also includes at least one of the following: accuracy information corresponding to the positioning analysis information; the positioning method used by the second device to obtain the positioning analysis information; the positioning inference method used by the second device to obtain the positioning analysis information; the type or identifier of the output data, used to indicate the type or identifier of the output data corresponding to the positioning analysis information; the information of the target terminal, used to indicate that the object corresponding to the positioning analysis information is the target terminal; and the credibility of the positioning analysis information.

[0261] In an optional implementation, the sending module 830 is also used to: send a third request message to a third device, wherein the third request message is used to request device information having reasoning functions related to AI positioning; the receiving module 810 is also used to receive a second response message sent by the third device according to the third request message, wherein the second response message includes device information of the second device, wherein the second device has reasoning functions related to AI positioning.

[0262] In an optional implementation, the third request message includes at least one of the following: the type of the requested device; the analysis type or analysis identifier, used to indicate that the requested device needs to support the reasoning task corresponding to the analysis type or analysis identifier; the positioning method that the requested device needs to support; the positioning reasoning method that the requested device needs to support; the information of the target terminal, used to indicate that the object corresponding to the reasoning task is the target terminal; the information of the time of interest, used to indicate that the requested device needs to support the reasoning task within the time of interest; the information of the area of interest, used to indicate that the requested device needs to support the reasoning task within the area of interest; the manufacturer information corresponding to the requested device; the manufacturer information corresponding to the first device; and the positioning accuracy requirement information.

[0263] In an optional implementation, the second response message also includes at least one of the following information corresponding to the second device: manufacturer information corresponding to the second device; positioning methods supported by the second device; positioning inference methods supported by the second device; type or identifier of output data, used to indicate that the second device supports the positioning analysis information corresponding to the output data type or identifier; positioning accuracy, used to indicate the positioning accuracy or performance corresponding to the positioning analysis information of the second device.

[0264] In an optional implementation, the positioning module is further used to: determine an AI-based positioning method to locate the target terminal.

[0265] In an optional implementation, the determination to locate the target terminal based on the AI positioning method includes: when a first condition is met, the first device determines to locate the target terminal based on the AI positioning method, wherein the first condition includes: the first device obtains device information with reasoning functions related to AI positioning.

[0266] 14. The apparatus according to any one of claims 1 to 13, wherein in an optional implementation manner, the first device and the second device are deployed in the same physical entity, or the first device and the second device are deployed in different physical entities.

[0267] In an optional implementation, the first device includes a location service function LMF; or, the second device includes an inference function AnLF; or, the third device includes a network storage function NRF.

[0268] The positioning device 800 in the embodiments of the present application can be an electronic device, such as an electronic device with an operating system, or a component of an electronic device, such as an integrated circuit or chip. The electronic device can be a network-side device or other device other than a network-side device. For example, the network-side device can include, but is not limited to, the types of network-side devices 12 listed above, and is not specifically limited in the embodiments of the present application.

[0269] The positioning device 800 provided in the embodiment of the present application can achieve Figure 2-Figure 3 The various processes implemented by the method embodiment achieve the same technical effect and are not described here again to avoid repetition.

[0270] like Figure 9 As shown, it is a structural diagram of a positioning device 900 provided in an embodiment of the present application. The device 900 includes a receiving module 910, which is used to receive a third request message sent by a first device, and the third request message is used to request to obtain device information with reasoning functions related to AI positioning; a sending module 920, and the third device sends a second response message to the first device according to the third request message, and the second response message includes device information of the second device.

[0271] In an optional implementation, the third request message includes at least one of the following: the type of the requested device; the analysis type or analysis identifier, used to indicate that the requested device needs to support the reasoning task corresponding to the analysis type or analysis identifier; the positioning method that the requested device needs to support; the positioning reasoning method that the requested device needs to support; the information of the target terminal, used to indicate that the object corresponding to the reasoning task is the target terminal; the information of the time of interest, used to indicate that the requested device needs to support the reasoning task within the time of interest; the information of the area of interest, used to indicate that the requested device needs to support the reasoning task within the area of interest; the manufacturer information corresponding to the requested device; the manufacturer information corresponding to the first device; and the positioning accuracy requirement information.

[0272] In an optional implementation, the second response message also includes at least one of the following information corresponding to the second device: manufacturer information corresponding to the second device; positioning methods supported by the second device; positioning inference methods supported by the second device; output data type or identifier, used to indicate that the second device supports positioning analysis information corresponding to the output data type or identifier; positioning accuracy, used to indicate the positioning accuracy or performance corresponding to the positioning analysis information of the second device.

[0273] In an optional implementation, the receiving module 910 is also used for at least one of the following: receiving a fourth request message sent by the second device, the fourth request message being used to register or update the device information of the second device, wherein the device information of the second device includes AI positioning reasoning-related capability information, and the second device has an AI model reasoning function; receiving a fifth request message sent by the fourth device, the fifth request message being used to register or update the device information of the fourth device, wherein the device information of the fourth device includes AI positioning training-related capability information, and wherein the fourth device has an AI model training function.

[0274] In an optional implementation, the AI positioning reasoning-related capability information includes at least one of the following: positioning indication information, used to indicate that the second device supports positioning-related AI model reasoning, or used to indicate that the second device supports outputting terminal positioning-related reasoning results; the positioning method supported by the second device; the positioning reasoning method supported by the second device; information on objects allowed to use positioning analysis information; the type or granularity of the input data required for reasoning; the type or granularity of the output data obtained by reasoning; supported positioning accuracy, used to indicate at least one of the fineness and credibility of the positioning analysis information obtained by reasoning.

[0275] In an optional implementation, the AI positioning training-related capability information includes at least one of the following: first capability information, used to indicate that the fourth device supports the training of the AI model for positioning, or that the fourth device has the ability to train positioning-related AI models; the positioning method supported by the AI positioning model trained by the fourth device; the positioning inference method supported by the AI positioning model trained by the fourth device; the object allowed to use the AI positioning model trained by the fourth device; the type of input data, used to indicate the type or granularity of the input data required for model training, or the type or granularity of the input data required for the trained AI positioning model; the type of output data, used to indicate the type or granularity of the output data corresponding to the trained AI positioning model; the supported positioning accuracy, used to indicate at least one of the fineness and credibility of the positioning analysis information output by the AI positioning model trained by the fourth device.

[0276] In an optional implementation, the first device, the second device, and the fourth device are deployed in the same physical entity, or the first device, the second device, and the fourth device are deployed in different physical entities.

[0277] In an optional implementation, the first device includes a location service function LMF, or the second device includes an inference function AnLF; or the third device includes a network storage function NRF, or the fourth device has a model training function MTLF.

[0278] The positioning device 900 in the embodiments of the present application can be an electronic device, such as an electronic device with an operating system, or a component of an electronic device, such as an integrated circuit or chip. The electronic device can be a network-side device or other device other than a network-side device. For example, the network-side device can include, but is not limited to, the types of network-side devices 12 listed above, and is not specifically limited in the embodiments of the present application.

[0279] The positioning device 900 provided in the embodiment of the present application can achieve Figure 5 The various processes implemented by the method embodiment achieve the same technical effect and are not described here again to avoid repetition.

[0280] like Figure 10As shown, it is a structural diagram of a positioning device 1000 provided in an embodiment of the present application. The device 1000 includes a receiving module 1010, which is used to receive a second request message sent by a first device, and the second request message is used to request the second device to obtain the positioning analysis information of the target terminal based on the AI model, and the second device has an AI model reasoning function; a sending module 1020, which is used to send a first response message to the first device according to the second request message, wherein the first response message includes the positioning analysis information of the target terminal, and the positioning analysis information is generated by the second device based on the AI model reasoning.

[0281] In an optional implementation, the second request message includes at least one of the following: an analysis type or an analysis identifier, used to indicate a request for the second device to perform AI positioning reasoning, or used to request the second device to obtain positioning analysis information; positioning performance requirements or positioning accuracy requirements; the positioning method that the second device needs to adopt when obtaining the positioning analysis information; the positioning reasoning method that the second device needs to adopt when performing AI positioning reasoning; input data, used for the second device to perform AI positioning reasoning based on the input data; the type or identifier of the output data, used to request the second device to provide the positioning analysis information corresponding to the type or identifier of the output data; information of the target terminal, used to indicate that the object of AI positioning reasoning is the target terminal; manufacturer information corresponding to the first device; information of the specified time, used to indicate the acquisition of the positioning analysis information of the target terminal corresponding to the specified time; information of the specified area, used to indicate the acquisition of the positioning analysis information of the target terminal related to the specified area.

[0282] In an optional implementation, when the second request message includes information about the designated area, the second request message also includes first indication information, where the first indication information is used to indicate obtaining positioning analysis information of the target object within or outside the designated area.

[0283] In an optional implementation, the input data includes at least one of the following: positioning measurement data from a terminal or access network device; positioning assistance data from a terminal or access network device; positioning configuration data or positioning assistance data from the first device.

[0284] In an optional implementation, the positioning analysis information includes at least one of the following: intermediate positioning information, where the intermediate positioning result is used to determine positioning result information; and positioning result information.

[0285] In an optional implementation, the positioning analysis information includes at least one of the following information types: prediction type; statistical type.

[0286] In an optional implementation, the first response message also includes at least one of the following: accuracy information corresponding to the positioning analysis information; the positioning method used by the second device to obtain the positioning analysis information; the positioning inference method used by the second device to obtain the positioning analysis information; an output data type or identifier, used to indicate the type or identifier of the output data corresponding to the positioning analysis information; information of the target terminal, used to indicate that the object corresponding to the positioning analysis information is the target terminal; and the credibility of the positioning analysis information.

[0287] In an optional implementation, the device 1000 also includes a determination module: used to obtain the AI model from a fourth device when the AI model does not exist, or to obtain the AI model through model training, and the fourth device has an AI model training function.

[0288] In an optional implementation, the sending module 1020 is also used to: the second device sends a fourth request message to the third device, and the fourth request message is used to register or update the device information of the second device, wherein the device information of the second device includes AI positioning reasoning related capability information.

[0289] In an optional implementation, the AI positioning reasoning-related capability information includes at least one of the following: positioning indication information, used to indicate that the second device supports positioning-related AI model reasoning, or used to indicate that the second device supports outputting terminal positioning-related reasoning results; the positioning method supported by the second device; the positioning reasoning method supported by the second device; information on objects allowed to use positioning analysis information; the type or granularity of the input data required for reasoning; the type or granularity of the output data obtained by reasoning; supported positioning accuracy, used to indicate at least one of the fineness and credibility of the positioning analysis information obtained by reasoning.

[0290] In an optional implementation, the first device, the second device, and the fourth device are deployed in the same physical entity, or the first device, the second device, and the fourth device are deployed in different physical entities.

[0291] In an optional implementation, the first device includes a location service function LMF, or the second device includes an inference function AnLF; or the third device includes a network storage function NRF, or the fourth device has a model training function MTLF.

[0292] The positioning device 1000 in the embodiments of the present application can be an electronic device, such as an electronic device with an operating system, or a component of an electronic device, such as an integrated circuit or chip. The electronic device can be a network-side device or other device other than a network-side device. For example, the network-side device can include, but is not limited to, the types of network-side devices 12 listed above, and is not specifically limited in the embodiments of the present application.

[0293] The positioning device 1000 provided in the embodiment of the present application can achieve Figure 6 The various processes implemented by the method embodiment achieve the same technical effect and are not described here again to avoid repetition.

[0294] like Figure 11 As shown, it is a structural diagram of a positioning device 1100 provided in an embodiment of the present application. The device 1100 includes a sending module 1110, which is used to send a fifth request message to a third device, and the fifth request message is used to register or update the device information of the fourth device, wherein the device information of the fourth device includes AI positioning training-related capability information, and wherein the fourth device has an AI model training function.

[0295] In an optional implementation, the AI positioning training-related capability information includes at least one of the following: first capability information, used to indicate that the fourth device supports the training of the AI model for positioning, or that the fourth device has the ability to train positioning-related AI models; the positioning method supported by the AI positioning model trained by the fourth device; the positioning inference method supported by the AI positioning model trained by the fourth device; the object allowed to use the AI positioning model trained by the fourth device; the type of input data, used to indicate the type or granularity of the input data required for model training, or the type or granularity of the input data required for the trained AI positioning model; the type of output data, used to indicate the type or granularity of the output data corresponding to the trained AI positioning model; the supported positioning accuracy, used to indicate at least one of the fineness and credibility of the positioning analysis information corresponding to the AI positioning model trained by the fourth device.

[0296] In an optional implementation, the third device includes a network storage function NRF, or the fourth device has a model training function MTLF.

[0297] The positioning device 1100 in the embodiments of the present application can be an electronic device, such as an electronic device with an operating system, or a component of an electronic device, such as an integrated circuit or chip. The electronic device can be a network-side device or other device other than a network-side device. For example, the network-side device can include, but is not limited to, the types of network-side devices 12 listed above, and is not specifically limited in the embodiments of the present application.

[0298] The positioning device 1100 provided in the embodiment of the present application can achieve Figure 7 The various processes implemented by the method embodiment achieve the same technical effect and are not described here again to avoid repetition.

[0299] like Figure 12 As shown, an embodiment of the present application further provides a communication device 1200, including a processor 1201 and a memory 1202, wherein the memory 1202 stores a program or instruction that can be run on the processor 1201. For example, when the communication device 1200 is a terminal, the program or instruction, when executed by the processor 1201, implements the various steps of the above-mentioned positioning method embodiment and can achieve the same technical effect. When the communication device 1200 is a network-side device, the program or instruction, when executed by the processor 1201, implements the various steps of the above-mentioned positioning method embodiment and can achieve the same technical effect. To avoid repetition, it will not be repeated here.

[0300] The embodiment of the present application also provides a network side device. Figure 13 As shown, the network side device 1300 includes: a processor 1301, a network interface 1302 and a memory 1303. The network interface 1302 is, for example, a common public radio interface (CPRI).

[0301] Specifically, the network side device 1300 of the embodiment of the present application further includes: instructions or programs stored in the memory 1303 and executable on the processor 1301, and the processor 1301 calls the instructions or programs in the memory 1303 to execute. Figure X The methods executed by the modules shown in X achieve the same technical effects, so they will not be described here to avoid repetition.

[0302] An embodiment of the present application further provides a readable storage medium, on which a program or instruction is stored. When the program or instruction is executed by a processor, each process of the above-mentioned positioning method embodiment is implemented and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0303] The processor is the processor in the terminal described in the above embodiment. The readable storage medium includes a computer-readable storage medium, such as a computer read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk. In some examples, the readable storage medium may be a non-transitory readable storage medium.

[0304] An embodiment of the present application further provides a chip, which includes a processor and a communication interface, wherein the communication interface is coupled to the processor, and the processor is used to run programs or instructions to implement the various processes of the above-mentioned positioning method embodiment, and can achieve the same technical effect. To avoid repetition, it will not be repeated here.

[0305] It should be understood that the chip mentioned in the embodiments of the present application can also be called a system-level chip, a system chip, a chip system or a system-on-chip chip, etc.

[0306] An embodiment of the present application further provides a computer program / program product, which is stored in a storage medium and executed by at least one processor to implement the various processes of the above-mentioned positioning method embodiment and can achieve the same technical effect. To avoid repetition, it is not repeated here.

[0307] An embodiment of the present application also provides a wireless communication system, including: a first device, a second device, a third device and a fourth device, wherein the first device is used to implement the various processes of the above-mentioned positioning method embodiments 200-300, the second device is used to implement the various processes of the above-mentioned positioning method embodiment 600, the third device is used to implement the various processes of the above-mentioned positioning method embodiment 500, and the fourth device is used to implement the various processes of the above-mentioned positioning method embodiment 700 and can achieve the same technical effects. To avoid repetition, they will not be repeated here.

[0308] It should be noted that, in this article, the terms "comprise", "include" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the presence of other identical elements in the process, method, article or device comprising the element. In addition, it should be pointed out that the scope of the methods and devices in the embodiments of the present application is not limited to performing functions in the order shown or discussed, and may also include performing functions in a substantially simultaneous manner or in the opposite order according to the functions involved. For example, the described method may be performed in an order different from that described, and various steps may also be added, omitted or combined. In addition, the features described with reference to certain examples may be combined in other examples.

[0309] Through the description of the above embodiments, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of a computer software product plus a necessary general-purpose hardware platform, or of course, by hardware. The computer software product is stored in a storage medium (such as ROM, RAM, magnetic disk, optical disk, etc.) and includes a number of instructions for enabling a terminal or network-side device to execute the methods described in each embodiment of the present application.

[0310] The embodiments of the present application are described above in conjunction with the accompanying drawings, but the present application is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of this application, ordinary technicians in this field can also make many forms of implementation methods without departing from the purpose of this application and the scope of protection of the claims. These implementation methods are all within the protection of this application.

Claims

1. A positioning method, characterized in that: include: The first device receives a first request message, where the first request message is used to request positioning information of a target terminal; The first device performs an artificial intelligence (AI) positioning process according to the first request message to obtain positioning information of the target terminal; The first device sends a first notification message, where the first notification message includes the location information of the target terminal.

2. The method according to claim 1, wherein The first device performs an AI positioning process according to the first request message to acquire positioning information of the target terminal, including: The first device sends a second request message to the second device according to the first request message, where the second request message is used to request the second device to obtain positioning analysis information of the target terminal based on the AI model, and the second device has an AI model inference function; The first device receives a first response message sent by the second device, where the first response message includes positioning analysis information of the target terminal, where the positioning analysis information is generated by the second device based on reasoning of the AI model; The first device determines the positioning information of the target terminal according to the positioning analysis information.

3. The method according to claim 2, wherein The second request message includes at least one of the following: An analysis type or analysis identifier, used to request the second device to perform AI positioning inference, or to request the positioning analysis information from the second device; Positioning performance requirements or positioning accuracy requirements; a positioning method to be adopted by the second device when acquiring the positioning analysis information; The positioning inference method that needs to be adopted when the second device performs AI positioning inference; Input data, used for the second device to perform AI positioning inference based on the input data; The type or identifier of the output data is used to request the second device to provide the positioning analysis information corresponding to the type or identifier of the output data; The target terminal information is used to indicate that the object of AI positioning reasoning is the target terminal; manufacturer information corresponding to the first device; The information of the specified time is used to instruct to obtain the positioning analysis information of the target terminal corresponding to the specified time; The information of the designated area is used to instruct to obtain the positioning analysis information of the target terminal related to the designated area.

4. The method according to claim 3, wherein In the case where the second request message includes information about the designated area, the second request message further includes first indication information, where the first indication information is used to indicate obtaining positioning analysis information of the target object within or outside the designated area.

5. The method according to claim 4, wherein The input data includes at least one of the following: Positioning measurement data from terminals or access network equipment; Positioning assistance data from terminals or access network equipment; Positioning configuration data or positioning assistance data from the first device.

6. The method according to any one of claims 2 to 5, characterized in that The positioning analysis information includes at least one of the following: intermediate positioning information, where the intermediate positioning information is used to determine positioning result information of the target terminal; Positioning result information.

7. The method according to any one of claims 2 to 6, wherein: The positioning analysis information includes at least one of the following information types: Forecast type; Statistical type.

8. The method according to claim 2, wherein The first response message further includes at least one of the following: Accuracy information corresponding to the positioning analysis information; a positioning method used by the second device when acquiring the positioning analysis information; a positioning inference method used by the second device when acquiring the positioning analysis information; The type or identifier of the output data, used to indicate the type or identifier of the output data corresponding to the positioning analysis information; The target terminal information is used to indicate that the object corresponding to the positioning analysis information is the target terminal; The credibility of the positioning analysis information.

9. The method according to any one of claims 1 to 8, wherein The method further comprises: The first device sends a third request message to the third device, where the third request message is used to request information of a device having an inference function related to AI positioning; The first device receives a second response message sent by the third device according to the third request message, where the second response message includes device information of the second device, wherein the second device has an inference function related to AI positioning.

10. The method according to claim 9, wherein The third request message includes at least one of the following: The type of device being requested; An analysis type or analysis identifier, used to indicate that the requested device needs to support the reasoning task corresponding to the analysis type or analysis identifier; The requested device needs to support the positioning method; The positioning inference method that the requested device needs to support; The target terminal information is used to indicate that the object corresponding to the reasoning task is the target terminal; Information about the time of interest, used to indicate that the requested device needs to support the reasoning task within the time of interest; Information about a region of interest, used to indicate that the requested device needs to support reasoning tasks within the region of interest; The manufacturer information corresponding to the requested device; manufacturer information corresponding to the first device; Positioning accuracy requirement information.

11. The method according to claim 9, wherein The second response message also includes at least one of the following information corresponding to the second device: manufacturer information corresponding to the second device; a positioning method supported by the second device; a positioning inference method supported by the second device; The type or identifier of the output data, used to indicate that the second device supports the positioning analysis information corresponding to the output data type or identifier; Positioning accuracy is used to indicate the positioning accuracy or performance corresponding to the positioning analysis information of the second device.

12. The method according to any one of claims 1 to 11, wherein The method further comprises: The first device determines an AI-based positioning method to locate the target terminal.

13. The method according to claim 12, wherein: The first device determines to locate the target terminal based on the AI positioning method, including: When a first condition is met, the first device determines to locate the target terminal based on the AI positioning method, wherein the first condition includes: the first device obtains device information having a reasoning function related to AI positioning.

14. The method according to any one of claims 1 to 13, wherein The first device and the second device are deployed in the same physical entity, or the first device and the second device are deployed in different physical entities.

15. The method according to any one of claims 1 to 13, wherein The first device includes a location service function LMF; or, the second device includes an inference function AnLF; or, the third device includes a network storage function NRF.

16. A positioning method, characterized in that: include: The third device receives a third request message sent by the first device, where the third request message is used to request information about a device having an inference function related to AI positioning; The third device sends a second response message to the first device according to the third request message, where the second response message includes device information of the second device.

17. The method according to claim 16, wherein The third request message includes at least one of the following: The type of device being requested; An analysis type or analysis identifier, used to indicate that the requested device needs to support the reasoning task corresponding to the analysis type or analysis identifier; The requested device needs to support the positioning method; The positioning inference method that the requested device needs to support; Information of the target terminal, used to indicate that the object corresponding to the reasoning task is the target terminal; Information about the time of interest, used to indicate that the requested device needs to support the reasoning task within the time of interest; Information about a region of interest, used to indicate that the requested device needs to support reasoning tasks within the region of interest; The manufacturer information corresponding to the requested device; manufacturer information corresponding to the first device; Positioning accuracy requirement information.

18. The method according to claim 16, wherein The second response message also includes at least one of the following information corresponding to the second device: Manufacturer information corresponding to the second device; a positioning method supported by the second device; a positioning inference method supported by the second device; An output data type or identifier, used to indicate that the second device supports positioning analysis information corresponding to the output data type or identifier; Positioning accuracy is used to indicate the positioning accuracy or performance corresponding to the positioning analysis information of the second device.

19. The method according to any one of claims 16 to 18, wherein The method further comprises at least one of the following: The third device receives a fourth request message sent by the second device, where the fourth request message is used to register or update device information of the second device, wherein the device information of the second device includes AI positioning reasoning-related capability information, and the second device has an AI model reasoning function; The third device receives a fifth request message sent by the fourth device, where the fifth request message is used to register or update device information of the fourth device, wherein the device information of the fourth device includes AI positioning training-related capability information, and wherein the fourth device has an AI model training function.

20. The method according to claim 19, wherein The AI positioning reasoning capability information includes at least one of the following: Positioning indication information, used to indicate that the second device supports positioning-related AI model reasoning, or used to indicate that the second device supports outputting terminal positioning-related reasoning results; a positioning method supported by the second device; a positioning inference method supported by the second device; Information about the subjects who are permitted to use location analysis information; The type or granularity of input data required for inference; The type or granularity of the inference output data; The supported positioning accuracy is used to indicate at least one of the fineness and credibility of the inferred positioning analysis information.

21. The method according to claim 19, wherein The AI positioning training-related capability information includes at least one of the following: First capability information, used to indicate that the fourth device supports training of an AI model for positioning, or that the fourth device has the ability to train a positioning-related AI model; A positioning method supported by the AI positioning model trained by the fourth device; The positioning inference method supported by the AI positioning model trained by the fourth device; An object that allows the use of an AI positioning model trained using the fourth device; The type of input data, which indicates the type or granularity of input data required for model training, or the type or granularity of input data required by the trained AI positioning model; The type of output data, which indicates the type or granularity of the output data corresponding to the trained AI positioning model; The supported positioning accuracy is used to indicate at least one of the fineness and credibility that can be achieved by the positioning analysis information output by the AI positioning model trained by the fourth device.

22. The method according to any one of claims 16 to 21, wherein The first device, the second device, and the fourth device are deployed in the same physical entity, or the first device, the second device, and the fourth device are deployed in different physical entities.

23. The method according to any one of claims 16 to 21, wherein The first device includes a location service function LMF, or the second device includes an inference function AnLF; or the third device includes a network storage function NRF, or the fourth device has a model training function MTLF.

24. A positioning method, characterized in that: include: The second device receives a second request message sent by the first device, where the second request message is used to request the second device to obtain positioning analysis information of the target terminal based on the AI model, and the second device has an AI model inference function; The second device sends a first response message to the first device, wherein the first response message includes positioning analysis information of the target terminal, and the positioning analysis information is generated by the second device according to the second request message and based on the AI model reasoning.

25. The method of claim 24, wherein: The second request message includes at least one of the following: An analysis type or analysis identifier, used to indicate a request for the second device to perform AI positioning inference, or to request the second device to obtain positioning analysis information; Positioning performance requirements or positioning accuracy requirements; a positioning method to be adopted by the second device when acquiring the positioning analysis information; The positioning inference method that needs to be adopted when the second device performs AI positioning inference; Input data, used for the second device to perform AI positioning inference based on the input data; The type or identifier of the output data is used to request the second device to provide the positioning analysis information corresponding to the type or identifier of the output data; The target terminal information is used to indicate that the object of AI positioning reasoning is the target terminal; manufacturer information corresponding to the first device; The information of the specified time is used to instruct to obtain the positioning analysis information of the target terminal corresponding to the specified time; The information of the designated area is used to instruct to obtain the positioning analysis information of the target terminal related to the designated area.

26. The method of claim 25, wherein: In the case where the second request message includes information about the designated area, the second request message further includes first indication information, where the first indication information is used to indicate obtaining positioning analysis information of the target object within or outside the designated area.

27. The method of claim 25, wherein: The input data includes at least one of the following: Positioning measurement data from terminals or access network equipment; Positioning assistance data from terminals or access network equipment; Positioning configuration data or positioning assistance data from the first device.

28. The method according to any one of claims 24 to 27, wherein The positioning analysis information includes at least one of the following: Intermediate positioning information, where the intermediate positioning result is used to determine the positioning result information; Positioning result information.

29. The method according to any one of claims 24 to 28, wherein The positioning analysis information includes at least one of the following information types: Forecast type; Statistical type.

30. The method according to any one of claims 24 to 29, wherein The first response message further includes at least one of the following: Accuracy information corresponding to the positioning analysis information; a positioning method used by the second device when acquiring the positioning analysis information; a positioning inference method used by the second device when acquiring the positioning analysis information; Output data type or identifier, used to indicate the type or identifier of output data corresponding to the positioning analysis information; The target terminal information is used to indicate that the object corresponding to the positioning analysis information is the target terminal; The credibility of the positioning analysis information.

31. The method according to any one of claims 24 to 29, wherein The method further comprises: When the AI model does not exist in the second device, the second device obtains the AI model from the fourth device, or the second device obtains the AI model through model training, and the fourth device has an AI model training function.

32. The method according to any one of claims 24 to 31, wherein The method further comprises: The second device sends a fourth request message to the third device, where the fourth request message is used to register or update device information of the second device, wherein the device information of the second device includes AI positioning and reasoning related capability information.

33. The method of claim 32, wherein: The AI positioning reasoning capability information includes at least one of the following: Positioning indication information, used to indicate that the second device supports positioning-related AI model reasoning, or used to indicate that the second device supports outputting terminal positioning-related reasoning results; a positioning method supported by the second device; a positioning inference method supported by the second device; Information about the subjects who are permitted to use location analysis information; The type or granularity of input data required for inference; The type or granularity of the inference output data; The supported positioning accuracy is used to indicate at least one of the fineness and credibility of the inferred positioning analysis information.

34. The method according to any one of claims 24 to 33, wherein The first device, the second device, and the fourth device are deployed in the same physical entity, or the first device, the second device, and the fourth device are deployed in different physical entities.

35. The method according to any one of claims 24 to 33, wherein The first device includes a location service function LMF, or the second device includes an inference function AnLF; or the third device includes a network storage function NRF, or the fourth device has a model training function MTLF.

36. A positioning method, characterized in that: include: The fourth device sends a fifth request message to the third device, where the fifth request message is used to register or update the device information AI positioning training-related capability information of the fourth device, wherein the fourth device has an AI model training function.

37. The method of claim 36, wherein: The AI positioning training-related capability information includes at least one of the following: First capability information, used to indicate that the fourth device supports training of an AI model for positioning, or that the fourth device has the ability to train a positioning-related AI model; A positioning method supported by the AI positioning model trained by the fourth device; The positioning inference method supported by the AI positioning model trained by the fourth device; An object that allows the use of an AI positioning model trained using the fourth device; The type of input data, which indicates the type or granularity of input data required for model training, or the type or granularity of input data required by the trained AI positioning model; The type of output data, which indicates the type or granularity of the output data corresponding to the trained AI positioning model; The supported positioning accuracy is used to indicate at least one of the fineness and credibility that can be achieved by the positioning analysis information corresponding to the AI positioning model trained by the fourth device.

38. The method according to any one of claims 36 to 37, wherein The third device includes a network storage function NRF, or the fourth device has a model training function MTLF.

39. A positioning device, characterized in that: include: A receiving module, configured to receive a first request message, where the first request message is used to request location information of a target terminal; a positioning module, configured to perform an artificial intelligence (AI) positioning process according to the first request message to obtain positioning information of the target terminal; The sending module is configured to send a first notification message, where the first notification message includes the location information of the target terminal.

40. The device according to claim 39, wherein The performing the AI positioning process according to the first request message to acquire the positioning information of the target terminal includes: Sending a second request message to a second device according to the first request message, where the second request message is used to request the second device to obtain positioning analysis information of the target terminal based on an AI model, where the second device has an AI model inference function; receiving a first response message sent by the second device, where the first response message includes positioning analysis information of the target terminal, where the positioning analysis information is generated by the second device based on reasoning of the AI model; The positioning information of the target terminal is determined according to the positioning analysis information.

41. A positioning device, characterized in that: include: a receiving module, configured to receive a third request message sent by the first device, wherein the third request message is used to request information of a device having an inference function related to AI positioning; A sending module, wherein the third device sends a second response message to the first device according to the third request message, where the second response message includes device information of the second device.

42. The device according to claim 41, wherein The receiving module is further configured to: receiving a fourth request message sent by the second device, where the fourth request message is used to register or update device information of the second device, wherein the device information of the second device includes AI positioning and reasoning-related capability information, and the second device has an AI model reasoning function; Receive a fifth request message sent by a fourth device, where the fifth request message is used to register or update device information of the fourth device, wherein the device information of the fourth device includes AI positioning training-related capability information, and wherein the fourth device has an AI model training function.

43. A positioning device, characterized in that: include: a receiving module, configured to receive a second request message sent by the first device, where the second request message is used to request the second device to obtain positioning analysis information of the target terminal based on the AI model, where the second device has an AI model inference function; A sending module is used to send a first response message to the first device according to the second request message, wherein the first response message includes positioning analysis information of the target terminal, and the positioning analysis information is generated by the second device based on the AI model reasoning.

44. A positioning device, characterized in that include: A sending module is used to send a fifth request message to the third device, where the fifth request message is used to register or update the device information of the fourth device, wherein the device information of the fourth device includes AI positioning training-related capability information, and wherein the fourth device has an AI model training function.

45. A communication device, characterized in that The method comprises a processor and a memory, wherein the memory stores a program or instruction that can be run on the processor, and when the program or instruction is executed by the processor, the method implements the steps of the method according to any one of claims 1 to 15, or the steps of the method according to any one of claims 16 to 23, or the steps of the method according to any one of claims 24 to 35, or the steps of the method according to any one of claims 36 to 38.

46. A readable storage medium, characterized in that The readable storage medium stores a program or instruction, which, when executed by a processor, implements the steps of the method according to any one of claims 1 to 15, or implements the steps of the method according to any one of claims 16 to 23, or implements the steps of the method according to any one of claims 24 to 35, or implements the steps of the method according to any one of claims 36 to 38.

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