Device used for wireless communication system, and method

Abstract

The present disclosure relates to a device used for a wireless communication system, and a method. For example, a user equipment may send to a location management function (LMF) in a core network a request message for model selection of a location model deployed at the user equipment, the request message at least comprising a user equipment capability of the user equipment, such that the LMF selects, at least on the basis of the request message, from a plurality of location models one or more location models to be deployed at the user equipment. Additionally or alternatively, the user equipment may send to the LMF a request message for model switching of location models, such that the LMF selects, at least on the basis of the request message, from a plurality of location models one or more update location models to be deployed at the user equipment. Additionally or alternatively, on the basis of the mobility of the user equipment, switching from one LMF to another LMF can be performed for management of a location service of the user equipment. Additionally or alternatively, a data analytics function (NWDAF) in the core network may be used to analyze the location precision.

Description

Devices and Methods for Wireless Communication Systems Cross - Reference to Related Applications This application claims priority based on and to Chinese Patent Application No. 202410088821.9, titled "Devices and Methods for Wireless Communication Systems", filed on January 22, 2024, the entire content of which is incorporated herein by reference. Technical Field The present disclosure generally relates to technologies for wireless communication systems, and specifically to technologies that apply technologies such as artificial intelligence (AI) / machine learning (ML) to the positioning function in wireless communication systems. Background Art Wireless communication systems can use a variety of protocols and standards for data transmission between devices. These protocols and standards have undergone long - term development, including but not limited to the 3rd Generation Partnership Project (3GPP), 3GPP Long Term Evolution (LTE) (e.g., 4G communication), and 3GPP New Radio (NR) (e.g., 5G communication), and even 6G communication, etc. Compared with traditional wireless communication systems, new wireless communication systems (such as 5G NR communication systems and 6G communication systems) have significantly improved in terms of wireless transmission speed, latency, capacity, flexibility, and reliability, providing more possibilities for new usage models. In a wireless communication system, to support position estimation in a terrestrial wireless network, a network device can estimate the position of a mobile user equipment by measuring radio frequency (RF) reference signals from the mobile user equipment, thereby achieving positioning. The positioning management function (LMF) entity associated with the positioning process is located on the core network side, and it can calculate or estimate the final position of the user equipment. As an example, in a traditional core network-assisted positioning process, parameters such as the time difference between uplink and downlink signals and the angle of arrival / departure of signals can be calculated based on the actual measurement results of the positioning reference signals reported by the user equipment, so as to determine the relative position between the network device and the user equipment. Due to problems such as the mobility and privacy of the user equipment during the positioning process, other network element devices in the core network (for example, Gateway Mobile Location Center (GMLC), Access and Mobility Management Function (AMF), Unified Data Repository (UDR), and NRF, etc.) can be appropriately introduced to assist the LMF, so as to achieve the position estimation of the target user equipment. This position estimation result can include the position based on the earth coordinate system, or can also include the position based on the local coordinate system at the cell level. It should be understood that the position estimation result can also include the estimation of the moving speed of the user equipment and / or the accuracy analysis of the position estimation, etc. In necessary cases, the LMF can also obtain additional information based on the assisted positioning of the Global Navigation Satellite System (GNSS) and the Position Reference Unit (PRU), so as to achieve further positioning of the user equipment. However, the positioning function in the current wireless communication system usually requires multiple measurements, calculations, and a series of interactions between devices, making it impossible to achieve a good balance between the efficiency and accuracy of positioning. Therefore, enhanced positioning services that can further improve the accuracy and efficiency of positioning are needed. Summary of the Invention The present disclosure proposes devices and methods for a wireless communication system. More specifically, the present disclosure proposes a technical solution that applies technologies such as artificial intelligence / machine learning to the positioning function in a wireless communication system, in which specific communication processes and related parameters are designed for multiple aspects such as the training, selection, and switching of the positioning model, thereby improving the accuracy and efficiency of positioning. In addition, the present disclosure also supports the switching of the LMF and the analysis of positioning accuracy, and can further enhance the positioning service. According to a first aspect of the present disclosure, there is provided an electronic device for a user equipment in a wireless communication system, the electronic device including at least one processor and at least one memory, the at least one memory including computer program instructions, wherein the at least one memory and the computer program instructions are configured to cause the user equipment to perform the following operations through the at least one processor: training a positioning model deployed at the user equipment, wherein the input of the positioning model includes at least the assisted positioning data obtained by the user equipment from the Location Management Function (LMF) in the core network and the intensity of the positioning reference signal measured by the user equipment itself, and wherein the output of the positioning model includes at least the positioning result of the user equipment. Correspondingly, according to the first aspect of the present disclosure, there is also provided a method for a user equipment in a wireless communication system. The method includes training a positioning model deployed at the user equipment, where the input of the positioning model includes at least the assisted positioning data obtained by the user equipment from a positioning management function (LMF) in the core network and the strength of the positioning reference signal measured by the user equipment itself, and where the output of the positioning model includes at least the positioning result of the user equipment. According to the second aspect of the present disclosure, there is provided an electronic device for a core network device in a core network. The electronic device includes at least one processor and at least one memory. The at least one memory includes computer program instructions, where the at least one memory and the computer program instructions are configured to cause the core network device to perform the following operations through the at least one processor: training a positioning model deployed at the core network device, where the input of the positioning model includes at least the assisted positioning data obtained by the core network device from a network device or a user equipment in a wireless communication system, and the assisted positioning data correspondingly includes at least the strength of the channel sounding reference signal from the user equipment measured by the network device or the strength of the positioning reference signal measured by the user equipment itself, and where the output of the positioning model includes at least the positioning result of the user equipment. Correspondingly, according to the second aspect of the present disclosure, there is also provided a method for a core network device in a core network. The method includes training a positioning model deployed at the core network device, where the input of the positioning model includes at least the assisted positioning data obtained by the core network device from a network device or a user equipment in a wireless communication system, and the assisted positioning data correspondingly includes at least the strength of the channel sounding reference signal from the user equipment measured by the network device or the strength of the positioning reference signal measured by the user equipment itself, and where the output of the positioning model includes at least the positioning result of the user equipment. According to the third aspect of the present disclosure, there is provided an electronic device for a user equipment in a wireless communication system. The electronic device includes at least one processor and at least one memory. The at least one memory includes computer program instructions, where the at least one memory and the computer program instructions are configured to cause the user equipment to perform the following operations through the at least one processor: sending a request message for model selection of a positioning model deployed at the user equipment to a positioning management function (LMF) in the core network via an access and mobility management function (AMF) in the core network, and the request message includes at least the user equipment capabilities of the user equipment, such that the LMF selects one or more positioning models from a plurality of positioning models for deployment at the user equipment at least based on the request message. Correspondingly, according to a third aspect of the present disclosure, there is also provided a method for a user equipment in a wireless communication system. The method includes sending, via an access and mobility management function (AMF) in a core network, a request message for model selection of a positioning model deployed at the user equipment to a positioning management function (LMF) in the core network, where the request message includes at least the user equipment capabilities of the user equipment, such that the LMF selects one or more positioning models from a plurality of positioning models for deployment at the user equipment at least based on the request message. According to a fourth aspect of the present disclosure, there is provided an electronic device for a user equipment in a wireless communication system. The electronic device includes at least one processor and at least one memory, where the at least one memory includes computer program instructions, and the at least one memory and the computer program instructions are configured to, through the at least one processor, cause the user equipment to perform the following operations: sending, via an access and mobility management function (AMF) in a core network, a request message for model switching of a positioning model deployed at the user equipment to a positioning management function (LMF) in the core network, where the request message includes at least the user equipment capabilities of the user equipment, such that the LMF selects one or more updated positioning models from a plurality of positioning models for deployment at the user equipment at least based on the request message. Correspondingly, according to a fourth aspect of the present disclosure, there is also provided a method for a user equipment in a wireless communication system. The method includes: sending, via an access and mobility management function (AMF) in a core network, a request message for model switching of a positioning model deployed at the user equipment to a positioning management function (LMF) in the core network, where the request message includes at least the user equipment capabilities of the user equipment, such that the LMF selects one or more updated positioning models from a plurality of positioning models for deployment at the user equipment at least based on the request message. According to a fifth aspect of the present disclosure, there is provided an electronic device for a core network device in a core network. The electronic device includes at least one processor and at least one memory, where the at least one memory includes computer program instructions, and the at least one memory and the computer program instructions are configured to, through the at least one processor, cause the core network device to perform the following operations: determining, based on positioning management function (LMF) profile information, to switch from a first LMF in the core network to a second LMF for positioning of a user equipment in a wireless communication system, where the LMF profile information includes at least an identifier of the first LMF and an identifier or function identifier of a supported positioning model, and an identifier of the second LMF and an identifier or function identifier of a supported positioning model. Correspondingly, according to a fifth aspect of the present disclosure, there is also provided a method for a core network device in a core network. The method includes: determining to switch from a first Location Management Function (LMF) to a second LMF in the core network for positioning a user equipment in a wireless communication system, where the LMF profile information includes at least an identifier of the first LMF and an identifier of a supported positioning model or a function identifier, and an identifier of the second LMF and an identifier of a supported positioning model or a function identifier. According to a sixth aspect of the present disclosure, there is provided an electronic device for a Location Management Function (LMF) in a core network. The electronic device includes at least one processor and at least one memory. The at least one memory includes computer program instructions, where the at least one memory and the computer program instructions are configured to, through the at least one processor, cause the LMF to perform the following operations: sending information associated with a positioning model to a Network Data Analytics Function (NWDAF) in the core network, so that the NWDAF analyzes the information to obtain the positioning accuracy of the positioning model with respect to a user equipment in a wireless communication system. Correspondingly, according to a sixth aspect of the present disclosure, there is also provided a method for a Location Management Function (LMF) in a core network. The method includes: sending information associated with a positioning model to a Network Data Analytics Function (NWDAF) in the core network, so that the NWDAF analyzes the information to obtain the positioning accuracy of the positioning model with respect to a user equipment in a wireless communication system. According to a seventh aspect of the present disclosure, there is provided a computer-readable storage medium having one or more instructions stored thereon, where the one or more instructions, when executed by one or more processors of an electronic device, cause the electronic device to execute the methods according to various embodiments of the present disclosure. According to an eighth aspect of the present disclosure, there is provided a computer program product including program instructions, where the program instructions, when executed by one or more processors of a computer, cause the computer to execute the methods according to various embodiments of the present disclosure. The above summary is provided to summarize some exemplary embodiments and to provide a basic understanding of aspects of the subject matter described herein. Therefore, the above features are merely examples and should not be construed as narrowing the scope or spirit of the subject matter described herein in any way. Other features, aspects, and advantages of the subject matter described herein will become apparent from the following detailed description in conjunction with the accompanying drawings. Description of the Drawings A better understanding of the present disclosure can be obtained when considering the following detailed description of the embodiments in conjunction with the accompanying drawings. The same or similar reference numerals are used in the various drawings to denote the same or similar components. The accompanying drawings, together with the following detailed description, are included in this specification and form a part of the specification, and are used to illustrate the embodiments of the present disclosure and to explain the principles and advantages of the present disclosure. Among them: FIG. 1 shows an exemplary architecture diagram of a wireless communication system according to an embodiment of the present disclosure. FIG. 2 shows an exemplary electronic device for a user equipment according to an embodiment of the present disclosure. FIG. 3 shows an exemplary electronic device for a core network device according to an embodiment of the present disclosure. FIG. 4 shows a flowchart of a communication interaction according to a first embodiment of the present disclosure. FIGS. 5A-5B show a flowchart of a communication interaction according to a second embodiment of the present disclosure. FIG. 6 shows a flowchart of a communication interaction according to a third embodiment of the present disclosure. FIG. 7 shows a flowchart of a communication interaction according to a fourth embodiment of the present disclosure. FIG. 8 shows a flowchart of a communication interaction according to a sixth embodiment of the present disclosure. FIG. 9 shows a flowchart of an exemplary method for a user equipment in a wireless communication system according to a first embodiment of the present disclosure. FIG. 10 shows a flowchart of an exemplary method for a core network device in a wireless communication system according to a second embodiment of the present disclosure. FIG. 11 shows a flowchart of an exemplary method for a user equipment in a wireless communication system according to a third embodiment of the present disclosure. FIG. 12 shows a flowchart of an exemplary method for a user equipment in a wireless communication system according to a fourth embodiment of the present disclosure. FIG. 13 shows a flowchart of an exemplary method for a core network device in a wireless communication system according to a fifth embodiment of the present disclosure. FIG. 14 shows a flowchart of an exemplary method for a core network device in a wireless communication system according to a sixth embodiment of the present disclosure. FIG. 15 is a block diagram of an example structure of a personal computer as an information processing device that can be adopted in an embodiment of the present disclosure; FIG. 16 is a block diagram of a first example showing a schematic configuration of a base station to which the technology of the present disclosure can be applied; FIG. 17 is a block diagram of a second example showing a schematic configuration of a base station to which the technology of the present disclosure can be applied; FIG. 18 is a block diagram of an example showing a schematic configuration of a smart phone to which the technology of the present disclosure can be applied. FIG. 19 is a block diagram showing an example of a schematic configuration of an in-vehicle navigation device to which the technology of the present disclosure can be applied. While embodiments described in the present disclosure may be susceptible to various modifications and alternative forms, specific embodiments thereof are shown by way of example in the drawings and are described in detail herein. However, it should be understood that the drawings and the detailed description thereof are not intended to limit the embodiments to the particular forms disclosed, but on the contrary, are intended to cover all modifications, equivalents, and alternatives falling within the spirit and scope of the claims. DETAILED DESCRIPTION The following describes representative applications of various aspects such as devices and methods according to the present disclosure. The description of these examples is only to add context and help understand the described embodiments. Thus, it will be clear to those skilled in the art that the embodiments described below can be implemented without some or all of the specific details. In other cases, well-known process steps are not described in detail to avoid unnecessarily obscuring the described embodiments. Other applications are possible, and the solutions of the present disclosure are not limited to these examples. Typically, a wireless communication system includes at least a network device and a user equipment, and the network device can provide communication services for one or more user equipments. In the present disclosure, the term “network device” (or “base station”, “control device”) has the full breadth of its ordinary meaning, and at least includes a wireless communication station that is part of a wireless communication system or a radio system to facilitate communication. As an example, the network device can be, for example, an eNB of the 4G communication standard, a gNB of the 5G communication standard, a remote radio head, a wireless access point, a drone control tower, or a communication device performing similar functions. In the present disclosure, “network device”, “base station” and “control device” can be used interchangeably, or the “network device” can be implemented as part of the “base station”. Application examples will be described in detail below with reference to the drawings taking the network device as an example. In the present disclosure, the term “user equipment (UE)” or “terminal device” has the full breadth of its ordinary meaning, and at least includes a terminal device that is part of a wireless communication system or a radio system to facilitate communication. As an example, the user equipment can be, for example, a terminal device such as a mobile phone, a laptop computer, a tablet computer, an in-vehicle communication device, a wearable device, a sensor, or an element thereof. In the present disclosure, “user equipment” (hereinafter may be abbreviated as “UE”) and “terminal device” can be used interchangeably, or the “user equipment” can be implemented as part of the “terminal device”. In the present disclosure, the term "network device side" / "base station side" has the full breadth of its ordinary meaning, and generally indicates the side that transmits data in the downlink of a communication system, or indicates the side that receives data in the uplink of a communication system. Similarly, the term "user equipment side" / "terminal device side" has the full breadth of its ordinary meaning, and correspondingly can indicate the side that receives data in the downlink of a communication system, or indicates the side that transmits data in the uplink of a communication system. It should be noted that although the following mainly describes the embodiments of the present disclosure based on a communication system including a network device and a user equipment, these descriptions can be correspondingly extended to the case of a communication system including any other types of network device side and user equipment side. For example, the operations on the network device side can correspond to the operations of a base station, and the operations on the user equipment side can correspondingly correspond to the operations of a terminal device. FIG. 1 shows an example architecture diagram of a wireless communication system according to an embodiment of the present disclosure. It should be understood that FIG. 1 only shows one of various types and possible arrangements of wireless communication systems; the features of the present disclosure can be implemented in any one of various systems as needed. As shown in FIG. 1, the wireless communication system 100 includes one or more user equipments (e.g., UE devices) and one or more network devices (e.g., RAN devices, which may include gNBs, etc.). The network device and the user equipment can be configured to communicate through a wireless transmission medium. The network device can also be configured to communicate with a network (e.g., the core network of a cellular service provider, a telecommunications network such as a public switched telephone network (PSTN), and / or the Internet) through a wired medium (e.g., a cable). As an example, as shown in FIG. 1, the network device can be configured to communicate with other entities in the core network via an access and mobility management (AMF) entity in the core network, and thus can communicate with a remote server. According to an embodiment of the present disclosure, the user equipment and / or the network device can communicate with a location management service (LMF) in the core network via the AMF. The LMF can obtain the location information of the user equipment, and optionally can provide various location-related information services for the user equipment in combination with a geographic information system. These services are collectively referred to as location services (LCS). Specifically, the LMF can calculate or verify the location of the user equipment and estimate its moving speed. Optionally, the LMF can also estimate the accuracy of the location. It should be understood that during the location process, the user equipment can be used as a position reference unit (PRU). It should be understood that the network elements related to the positioning function in the core network may also include a Gateway Mobile Location Center (GLMC), a Location Retrieval Function (LRF), and a Network Exposure Function (NEF). The GLMC contains functions that need to support location services. There may be more than one GMLC in the same Public Land Mobile Network (PLMN). The LRF may be located at the GMLC or may be independent of the GMLC in terms of location. The LRF may retrieve or verify location information, provide routing and / or related information for a user equipment (e.g., a user equipment initiating an Internet Protocol (IP) Multimedia Subsystem (IMS) emergency session). The NEF may provide a method to access location services through an External Access Function (AF) or an Internal AF. Specifically, the AF may use an Application Programming Interface (API) to access location services from the NEF. According to the Quality of Service (QoS) requirements, the NEF may forward the location request to the GMLC or (optionally via the Unified Data Management (UDM)) expose the event of requesting location information from the serving AMF. In addition, the network elements of the core network may include a Network Data Analytics Function (NWDAF), which may include an Analysis Logic Function (AnLF) and a Model Training Logic Function (MTLF). The NWDAF may analyze the data input by multiple network elements. For example, the NWDAF may analyze location-related data from the GMLC to output statistical results. Moreover, the MTLF in the NWDAF may perform functions related to model training. It should be understood that the LCS server may request the positioning service of the user equipment, so that the network elements related to the positioning function in the core network communicate with the user equipment and / or network devices via the AMF to obtain the location information of the user equipment. Artificial intelligence is a newly emerging technical science in recent years for researching and developing technologies to simulate, extend, and expand human intelligence. By way of example and not limitation, artificial intelligence algorithms may include one or more of the following: linear regression, logistic regression, decision tree, naive Bayes, support vector machine, random forest, artificial neural network, K-nearest neighbor. Those skilled in the art should understand that machine learning belongs to a type of artificial intelligence technology, which may involve processes such as data collection, model training, and analysis and reasoning of data. By way of example, machine learning technology may be involved in the Lifecycle Service (LCS). The LCS may include, but is not limited to, data collection, model training, model deployment, model inference, model selection, activation, deactivation, switching, and fallback, model detection, model update, and model migration, etc. According to embodiments of the present disclosure, applying artificial intelligence / machine learning technologies to the aforementioned new wireless communication system can make it intelligent and improve the working efficiency of the network architecture. Those skilled in the art should recognize that applying artificial intelligence / machine learning technologies to the positioning service in a wireless communication system can greatly improve the accuracy and efficiency of positioning. However, currently, such a combination still lacks supporting standards for application in actual communication scenarios. Therefore, some technical solutions considering actual communication scenarios are needed to enable existing wireless communication systems to support artificial intelligence / machine learning technologies to provide enhanced positioning services. For example, it is necessary to consider how to better implement model deployment, model training, model selection, model switching, positioning analysis, etc. for the positioning function of user equipment with the help of the core network and network devices, so as to enhance the positioning service. It should be understood that embodiments of the present disclosure involve the core network participating in the positioning of user equipment, and thus can support at least the following three positioning modes: · UE assisted mode: In this mode, the UE can obtain position measurement results and send the measurement results to another entity (such as the LMF) to calculate the position; · UE based mode: In this mode, the UE can use the assist data provided by the serving PLMN to obtain position measurement results and calculate a position estimate; · Network based mode: In this mode, the serving PLMN obtains position measurement results of signals sent by the target UE and calculates a position estimate. The transmission of the UE signal can be transparent or opaque to the UE. FIG. 2 shows an exemplary electronic device 200 for a user equipment (e.g., a "UE" device) in system 100 according to an embodiment of the present disclosure. The electronic device 200 shown in FIG. 2 may include various units to implement various embodiments according to the present disclosure. In this example, the electronic device 200 includes a communication unit 202 and a control unit 204. In one implementation, the electronic device 200 is implemented as the user equipment itself or a part thereof, or is implemented as a device for controlling the user equipment or otherwise related to the user equipment or a part of such a device. Various operations described below in connection with the user equipment can be implemented by units 202, 204 of the electronic device 200 or other possible units. According to an embodiment of the present disclosure, the processing unit 204 may be configured to train a positioning model deployed at a user equipment. In this embodiment, the input of the positioning model may at least include the assisted positioning data obtained by the user equipment from the LMF in the core network and the strength of the positioning reference signal measured by the user equipment itself. The output of the positioning model may at least include the positioning result of the user equipment. Additionally or alternatively, according to another embodiment of the present disclosure, the communication unit 202 may be configured to send a request message for model selection of a positioning model deployed at the user equipment to the LMF in the core network via the AMF in the core network. This request message may at least include the user equipment capabilities of the user equipment, such that the LMF may select one or more positioning models from multiple positioning models for deployment at the user equipment based at least on this request message. Additionally or alternatively, according to yet another embodiment of the present disclosure, the communication unit 202 may be configured to send a request message for model switching of a positioning model deployed at the user equipment to the LMF in the core network via the AMF in the core network. This request message may at least include the user equipment capabilities of the user equipment, such that the LMF may select one or more updated positioning models from multiple positioning models for deployment at the user equipment based at least on this request message. FIG. 3 shows an exemplary electronic device for a core network device according to an embodiment of the present disclosure. The electronic device 300 shown in FIG. 3 may include various units to implement various embodiments according to the present disclosure. In this example, the electronic device 300 includes a communication unit 302 and a processing unit 304. In one implementation, the electronic device 300 is implemented as the core network device itself or a part thereof, or is implemented as a device related to the core network device or a part of the device. Various operations described below in connection with the core network device may be implemented by the units 302, 304 of the electronic device 300 or other possible units. According to an embodiment of the present disclosure, the core network device may be an LMF or an NWDAF. The processing unit 304 may be configured to train a positioning model deployed at the core network device. In this embodiment, the input of the positioning model may at least include the assisted positioning data obtained by the core network device from network devices or user equipment in the radio communication system, and the assisted positioning data may correspondingly at least include the strength of the channel sounding reference signal from the user equipment measured by the network device or the strength of the positioning reference signal measured by the user equipment itself. The output of the positioning model may at least include the positioning result of the user equipment. Additionally or alternatively, according to another embodiment of the present disclosure, the core network device may be an LMF device, or a GMLT device or an AMF device. In this embodiment, the processing unit 304 may determine to switch from a first LMF in the core network to a second LMF based on the LMF profile information for positioning a user equipment in the wireless communication system. The LMF profile information may at least include the identifier of the first LMF and the identifier or function identifier of the positioning model it supports, as well as the identifier of the second LMF and the identifier or function identifier of the positioning model it supports. Additionally or alternatively, according to yet another embodiment of the present disclosure, the core network device may be an LMF. The communication unit 302 may be configured to send information associated with a positioning model to an NWDAF in the core network, such that the NWDAF analyzes the information to obtain the positioning accuracy of the positioning model for a user equipment in the wireless communication system. In some embodiments, the electronic device 200 or 300 may be implemented at a chip level, or may also be implemented at a device level by including other external components (such as radio links, antennas, etc.). For example, each electronic device may operate as a communication device as a whole machine. It should be noted that the above-mentioned respective units are only logical modules divided according to their specific implemented functions, rather than limiting the specific implementation manners. For example, they can be implemented in software, hardware, or a combination of software and hardware. In the hardware implementation manner, the hardware can be programmed or configured to execute functions. In the software or software-hardware combination implementation manner, the software can be used to configure the hardware and / or the processor. In actual implementation, the above-mentioned respective units can be implemented as independent physical entities, or can also be implemented by a single entity (such as a processor (CPU or DSP, etc.), an integrated circuit, etc.). Among them, the processing circuit may refer to various implementations of a digital circuit system, an analog circuit system, or a mixed-signal (a combination of analog and digital) circuit system that executes functions in a computing system. The processing circuit may include, for example, circuits such as an integrated circuit (IC), an application-specific integrated circuit (ASIC), a part or circuit of a single processor core, the entire processor core, a single processor, a programmable hardware device such as a field-programmable gate array (FPGA), and / or a system including multiple processors. The present disclosure proposes novel technical solutions for applying artificial intelligence / machine learning technologies to the positioning function in a wireless communication system from six aspects: training of the positioning model deployed at the user equipment, training of the positioning model deployed at the LMF, selection of the positioning model, switching of the positioning model, LMF switching, and data analysis of the positioning model. These technical solutions involve the participation and / or interaction of the core network device. The following will introduce these solutions in detail through six embodiments. First Embodiment - Training of the positioning model deployed on the user equipment side According to a first embodiment of the present disclosure, the positioning model can be deployed unidirectionally at the user equipment. The user equipment (e.g., UE equipment) can communicate with the LMF via the AMF at the non-access stratum (NAS), or can communicate with the LMF via the network equipment (e.g., RAN equipment, which can include gNB, etc.) at the access stratum (AS) and then via the AMF. Thus, as an example, the main core network devices involved in the first embodiment include the AMF and the LMF. According to a first embodiment of the present disclosure, the positioning model deployed at the user equipment can be trained. As an example but not a limitation, when the LCS client indicates a need for training of the positioning model, the training process can be initiated. The signaling interaction process regarding the communication of the first embodiment of the present disclosure will be described below with reference to FIG. 4. As shown in FIG. 4, the user equipment (shown as UE in the figure) in the wireless communication system can receive a request message for model training from the LMF via the AMF in the core network. Specifically, the LMF can first send the request message for model training to the AMF (as an example but not a limitation, this request message can be included in the Namf_Communication_N1N2MessageTransfer service operation invoked by the LMF for the AMF). When the UE is in an idle connection state (e.g., CM-IDLE state), the AMF can initiate a network-triggered service request process so that the AMF can establish (e.g., directly establish or establish via the network equipment (shown as RAN in the figure)) communication with the UE, thereby sending the request message for model training to the UE (as an example but not a limitation, this request message can be included in the DL NAS TRANSPORT message sent by the AMF to the UE). It should be understood that the above request message for model training can at least include the auxiliary positioning data provided by the LMF to the UE. According to a first embodiment of the present disclosure, this auxiliary positioning data is related to the training of the positioning model on the UE side and can at least include one or more of the following: positioning application scenario, desired positioning accuracy, inference duration, and training data reliability, etc. Additionally or optionally, the auxiliary positioning data can also include coordinate system parameters, information indicating whether auxiliary PRU is required, etc. It should also be understood that the above request message for model training can also optionally include a request for the user equipment capabilities (UE capabilities) of the UE. Additionally or optionally, the request message for the model can also include a request for the UE to confirm the completion of the training of the positioning model. After the UE receives a request message for model training from the LMF, it can perform positioning measurements and then conduct positioning model training. For example, in positioning measurements, the UE can obtain the positioning reference signal strength measured by itself. Therefore, according to the first embodiment of the present disclosure, the input of the positioning model deployed at the UE can at least include assisted positioning data and the positioning reference signal strength measured by the UE itself. The output of the positioning model can at least include the positioning result of the UE. It should be understood that the positioning result can be an inferred positioning result used as intermediate data for the model training algorithm, or a direct positioning result of the user equipment, including, for example, position or angle, etc. It should be understood that artificial intelligence algorithms (e.g., including machine learning algorithms, etc.) can be used to train the positioning model. As an example rather than a limitation, the positioning model can be supervised to learn the relationship between input parameters and output parameters, so as to achieve the estimation and prediction of the position. Generally, the algorithm can be repeatedly executed several times to make the model converge, and then the training ends. After the UE finishes training the positioning model deployed at the UE, it can send a completion message of model training to the LMF via the AMF in the core network. Specifically, in the case where the UE enters the idle connection state (e.g., CM-IDLE state) due to the long model training time, the UE can initiate a UE-triggered service request procedure, enabling the UE to establish (e.g., directly establish or establish via the RAN) communication with the AMF, so as to send the completion message of model training to the AMF (as an example rather than a limitation, this completion message can be included in the UL NAS TRANSPORT message sent by the UE to the AMF), and then sent to the LMF (as an example rather than a limitation, this completion message can be included in the Namf_Communication_N1InfoNotify service operation invoked by the AMF for the LMF). This completion message can indicate the confirmation that the training of the positioning model by the UE has been completed. It should be understood that in the case where the request message for model training includes a request for UE capabilities, the completion message of model training can include the UE capabilities provided by the UE. As an example rather than a limitation, in this embodiment, the UE capabilities can include one or more of the following: the application scenarios supported by the model that the UE can support, the size of the model, the type of the model, the prediction latency of the model, and the prediction accuracy of the model, etc. Additionally or optionally, after the UE trains the positioning model deployed at the UE, the positioning result can be reported to the LMF via the AMF. For example, the positioning result can be included in the completion message of the model training, such that the LMF detects and verifies the result of the model training at the UE (not shown in the figure). Specifically, the LMF can generate an adjustment message for adjusting the parameters or structure of the positioning model on the UE side, at least based on the comparison between the received positioning result (e.g., the inferred positioning result or the direct positioning result) and the true positioning data available at the LMF. It should be understood that the analysis result of the above comparison can be obtained by the LMF with the assistance of the NWDAF. Subsequently, the UE can receive the adjustment message from the LMF via the AMF and adjust the parameters and structure of the positioning model deployed at the UE based on the adjustment message. By way of example and not limitation, in the case where the positioning model is trained using an artificial neural network algorithm, adjusting the parameters and structure of the model includes adjusting the number of layers of the network and the weights of each layer, etc. Optionally, the completion message of the model training can also include information associated with the positioning model deployed on the UE side, such as the identifier or functional identifier of the positioning model, etc. It should be noted that the information interaction diagram in FIG. 4 only provides an example and is not intended to be limiting. The figure may include more or fewer steps, and the steps may also be executed in an order different from the order depicted in the figure. For example, when the UE is in a normal connected state, the network-triggered service request procedure and the UE-triggered service request procedure in FIG. 4 can be omitted. Additionally, if the request message for model training does not request the UE to confirm upon completion of the model training and does not request the UE capabilities, then the transmission of the completion information of the model training can be omitted. In summary, according to the first embodiment of the present disclosure, it is possible to support the training of the positioning model on the user equipment side, thereby implementing the positioning function of the user equipment. With the data assistance provided by the core network equipment, the efficiency and accuracy of positioning on the user equipment side can be improved. Second Embodiment - Training of the Positioning Model Deployed on the Core Network Side According to the second embodiment of the present disclosure, the positioning model can be deployed unilaterally at the core network. By way of example and not limitation, the positioning model can be deployed at the LMF or NWDAF in the core network. According to the second embodiment of the present disclosure, the positioning model deployed at the core network equipment (e.g., the LMF or NWDAF) can be trained. By way of example and not limitation, when the LCS client indicates the need for training of the positioning model, the training process can be initiated. The signaling interaction process of the communication regarding the second embodiment of the present disclosure will be described below with reference to FIGS. 5A and 5B respectively. An interaction diagram showing the deployment and training of a positioning model at the LMF in the core network is shown in FIG. 5A. As shown in FIG. 5A, the LMF can send a request message for model training to network devices (shown as RAN in the figure) in the wireless communication system via the AMF. Specifically, the LMF can first send the request message for model training to the AMF (by way of example and not limitation, this request message can be included in the Namf_Communication_N1N2MessageTransfer service operation invoked by the LMF for the AMF). In the case where the user equipment (shown as UE in the figure) that the LMF aims to locate is in an idle connection state (e.g., CM-IDLE state), the AMF can initiate a network-triggered service request procedure so that the AMF can establish communication with the UE (and thus with the RAN) (it should be understood that the separate communication between the AMF and the RAN may not require a network-triggered service request procedure). As shown in FIG. 5A, the AMF can send the request message for model training to the RAN (by way of example and not limitation, this request message can be included in the N2Transport message sent by the AMF to the RAN). According to a second embodiment of the present disclosure, the request message may include a request for auxiliary positioning data for positioning model training at the LMF. It should be understood that, optionally, the above request message for model training may further include a request for the user equipment capabilities (UE capabilities) of the UE. This request message may optionally be further sent by the RAN to the UE (not shown in the figure). Next, in response to receiving the request message for model training from the LMF, the RAN can cause the UE to measure the strength of the positioning reference signal (PRS, which is a downlink reference signal), and the UE can directly send the strength of the positioning reference signal measured by itself to the LMF via the AMF as part of the auxiliary positioning data. In other words, in this case, the LMF can receive the auxiliary positioning data including the strength of the positioning reference signal measured by the UE itself from the UE via the AMF. Alternatively, in response to receiving the request message for model training from the LMF, the RAN can measure the strength of the channel sounding reference signal (SRS, which is an uplink reference signal) from the UE, and the RAN can send the strength of the channel sounding reference signal measured by it to the LMF via the AMF as part of the auxiliary positioning data. In other words, in this case, the LMF can receive the auxiliary positioning data including the strength of the channel sounding reference signal from the RAN via the AMF. It can be seen that the LMF can obtain auxiliary positioning data from the RAN or the UE (generally, either one can be executed). Accordingly, in the case of obtaining auxiliary positioning data from the RAN, the auxiliary positioning data may include the intensity of the SRS from the UE measured by the RAN; in the case of obtaining auxiliary positioning data from the UE, the auxiliary positioning data may include the intensity of the PRS measured by the UE itself. It should be understood that the above auxiliary positioning data may at least further include one or more of the following: the identifier of the cell to which the UE is connected (from which the location and coverage of the cell can be known), the time delay of the positioning reference signal transmitted by the UE measured by the RAN, and the phase information, incident angle, Doppler frequency shift, and timestamp information, etc. of the positioning reference signal of the UE. Additionally or optionally, the auxiliary positioning data may further include coordinate system parameters, information indicating whether auxiliary PRU is required, etc. The LMF can receive auxiliary positioning data from the RAN or the UE via the AMF, and then can train the positioning model deployed at the LMF (as an example but not a limitation, the auxiliary positioning data may be included in the Namf_Communication_N2InfoNotify service operation called by the AMF for the LMF). Therefore, according to the second embodiment of the present disclosure, the input of the positioning model deployed at the LMF may at least include auxiliary positioning data (the auxiliary positioning data may at least include the intensity of the channel sounding reference signal from the UE measured by the RAN or the intensity of the positioning reference signal measured by the UE itself). The output of the positioning model may at least include the positioning result of the UE. The positioning result may be the final positioning result, including data such as location or angle, etc. It should be understood that artificial intelligence algorithms (such as, including machine learning algorithms, etc.) can be used to train the positioning model. As an example but not a limitation, the positioning model can be supervised learning to make it learn the relationship between the input parameters and the output parameters, so as to realize the estimation and prediction of the location. Generally, the algorithm can be repeatedly executed several times to make the model converge, and then the training ends. It should be understood that in the case where a request for UE capabilities is included in the request message for model training (for example, when receiving auxiliary positioning data), the LMF can receive the UE capabilities provided by the UE from the RAN via the AMF, or the LMF can receive the UE capabilities from the UE via the AMF. As an example but not a limitation, in this embodiment, the UE capabilities may include one or more of the following: positioning method, positioning model, and the accuracy of previous positioning. Nearby or optionally, the UE capabilities may further include one or more of the following: the application scenario of the model that the UE can support, the size of the model, the type of the model, the prediction delay of the model, and the prediction accuracy of the model, etc. After the LMF trains the positioning model deployed at the LMF, a completion message of the model training can be sent to the RAN via the AMF in the core network. The completion message can indicate the confirmation from the LMF that the training of the positioning model has been completed. By way of example and not limitation, the completion message can be included in the Namf_Communication_N1InfoNotify service operation invoked by the LMF for the AMF. Further, by way of example and not limitation, the completion message can be included in the N2Transport message sent by the AMF to the RAN. It should be noted that the information interaction diagram in FIG. 5A only provides examples and is not intended to be limiting. The diagram may include more or fewer steps, and the steps may also be executed in an order different from the order depicted in the diagram. For example, the network-triggered service request process in FIG. 5A can be optional, and the transmission of the completion information of the model training can also be optional. FIG. 5B shows an interaction diagram for deploying and training a positioning model at the NWDAF in the core network. As shown in FIG. 5B, in response to an indication from the LMF in the core network (indicating that the training of the positioning model is required), the NWDAF can send a request message for model training to the network device (shown as the RAN) in the wireless communication system via the AMF. Specifically, the NWDAF can first send the request message for model training to the AMF. In the case where the user equipment to be located (shown as the UE in the figure) is in an idle connection state (e.g., CM-IDLE state), the AMF can initiate a network-triggered service request process so that the AMF can establish communication with the UE (and thus with the RAN). As shown in FIG. 5B, the AMF can send the request message for model training to the RAN. According to the second embodiment of the present disclosure, the request message can include a request for auxiliary positioning data for the positioning model training at the NWDAF. It should be understood that optionally, the above request message for model training can further include a request for the user equipment capability (UE capability) of the UE. The request message can optionally be further sent by the RAN to the UE (not shown in the figure). Next, in response to receiving a request message for model training from the NWDAF, the RAN may cause the UE to measure the strength of the positioning reference signal (PRS, which is a downlink reference signal), and the UE may directly send the strength of the positioning reference signal measured by itself to the NWDAF via the AMF as part of the assisted positioning data. In other words, in this case, the NWDAF may receive, via the AMF, the assisted positioning data including the strength of the positioning reference signal measured by the UE itself from the UE. Alternatively, in response to receiving a request message for model training from the NWDAF, the RAN may measure the strength of the channel sounding reference signal (SRS, which is an uplink reference signal) from the UE, and the RAN may send the strength of the channel sounding reference signal measured by it to the NWDAF via the AMF as part of the assisted positioning data. In other words, in this case, the NWDAF may receive, via the AMF, the assisted positioning data including the strength of the channel sounding reference signal from the RAN. It can be seen that the NWDAF can obtain the assisted positioning data from the RAN or the UE (generally, either of the two can be executed). Accordingly, in the case of obtaining the assisted positioning data from the RAN, the assisted positioning data may include the strength of the SRS from the UE measured by the RAN; in the case of obtaining the assisted positioning data from the UE, the assisted positioning data may include the strength of the PRS measured by the UE itself. It should be understood that the above assisted positioning data may at least further include one or more of the following: the identifier of the cell to which the UE is connected (from which the location and coverage of the cell can be known), the time delay of the positioning reference signal sent by the UE measured by the RAN, and the phase information, incident angle, Doppler frequency shift, and timestamp information, etc. of the UE's positioning reference signal. Additionally or optionally, the assisted positioning data may further include coordinate system parameters, information indicating whether assisted PRU is required, etc. The NWDAF may receive the assisted positioning data from the RAN or the UE via the AMF, and then may train the positioning model deployed at the NWDAF. Additionally or optionally, the assisted positioning data may be further processed at the LMF and then sent to the NWDAF. According to the second embodiment of the present disclosure, the input of the positioning model deployed at the NWDAF may at least include the assisted positioning data (the assisted positioning data may at least include the strength of the channel sounding reference signal from the UE measured by the RAN or the strength of the positioning reference signal measured by the UE itself). The output of the positioning model may at least include the positioning result of the UE. The positioning result may be the final positioning result, including data such as position or angle, etc. It should be understood that artificial intelligence algorithms (for example, including machine learning algorithms, etc.) may be used to train the positioning model. It should be understood that in the case where a request for UE capabilities is included in the request message for model training (for example, when receiving assisted positioning data), the NWDAF may receive the UE capabilities provided by the UE from the RAN via the AMF, or the NWDAF may receive the UE capabilities from the UE via the AMF. By way of example and not limitation, in this embodiment, the UE capabilities may include one or more of the following: positioning method, positioning model, and accuracy of previous positioning. Nearby or optionally, the UE capabilities may also include one or more of the following: application scenarios of the model that the UE can support, size of the model, type of the model, prediction latency of the model, and prediction accuracy of the model, etc. After the NWDAF finishes training the positioning model deployed at the NWDAF, a completion message of the model training may be sent to the RAN via the AMF in the core network. The completion message may indicate the confirmation by the NWDAF that the training of the positioning model has been completed. It should be noted that the information interaction diagram in FIG. 5B only provides examples and is not intended to be limiting. The figure may include more or fewer steps, and the steps may also be executed in an order different from the order of the steps depicted in the figure. For example, the network-triggered service request process in FIG. 5B may be optional, and the transmission of the completion information of the model training may also be optional. It should be recognized that more details about the communication process, communication messages, and model training in FIG. 5B can be referred to the detailed description in FIG. 5A and will not be repeated here. In summary, according to the second embodiment of the present disclosure, the training of the positioning model can be supported on the core network side, thereby realizing the positioning function of the user equipment. With the assistance of the data provided by the user equipment and the network equipment, the efficiency and accuracy of the core network for positioning the user equipment can be improved. According to the present disclosure, the core network device or the network device may manage the positioning model deployed on the user equipment side, but the reverse is not supported. This is because the positioning model on the core network side does not only serve a single target user equipment, and other user equipment resident in the cell where the user equipment is located or user equipment that may enter the cell may all need the positioning model on the core network side for positioning services. Therefore, the third and fourth embodiments below will respectively describe the model selection and model switching of the positioning model deployed on the user equipment side. Third Embodiment - Model Selection of the Positioning Model The third embodiment of the present disclosure mainly relates to the unilateral deployment of a positioning model at a user equipment. The user equipment (e.g., UE device) can communicate with the LMF via the AMF in the non-access stratum (NAS), or can communicate with the LMF via a network device (e.g., RAN device, which can include gNB, etc.) in the access stratum (AS) and then via the AMF. Generally speaking, in the initial stage, the user equipment hopes to obtain some positioning models adapted to itself for subsequent positioning measurements and training of the positioning model. According to the third embodiment of the present disclosure, the LMF can participate in selecting an appropriate positioning model for the user equipment. The signaling interaction process of the communication regarding the third embodiment of the present disclosure will be introduced below in conjunction with FIG. 6. As shown in FIG. 6, a user equipment (shown as UE in the figure) in a wireless communication system can send a request message for model selection of the positioning model deployed at the UE to the LMF via the AMF in the core network. Specifically, when the UE is in an idle connection state (e.g., CM-IDLE state), the UE can initiate a UE-triggered service request process, enabling the UE to establish (e.g., directly establish or establish via a network device (shown as RAN in the figure)) communication with the AMF, so as to send the request message for model selection to the AMF (by way of example and not limitation, this request message can be included in the UL NAS TRANSPORT message sent by the UE to the AMF). Further, the AMF can send the request message for model selection to the LMF (by way of example and not limitation, this request message can be included in the Namf_Communication_N1N2MessageTransfer service operation invoked by the AMF for the LMF). It should be understood that the above request message for model selection can at least include the user equipment capabilities of the UE (UE capabilities). According to the third embodiment of the present disclosure, the UE capabilities can include one or more of the following: the application scenarios of the models that the UE can support, the size of the models, the types of the models, the prediction latency of the models, and the prediction accuracy of the models, etc. Additionally or optionally, the request message for model selection can also include one or more of the following: the number of training models, and the desired positioning accuracy, etc. After the LMF receives a request message for model selection from the UE, it can select one or more positioning models from multiple positioning models for deployment at the requesting UE, at least based on the request message. It should be understood that the LMF can select one or more positioning models suitable for deployment at the UE based on the UE capabilities in the request message (and optionally, the number of training models, the desired positioning accuracy, etc.). In other words, the LMF can match the model requirements on the UE side with the functions of the multiple positioning models available for selection, so as to select the (one or more) positioning models with a higher degree of match with the UE (for example, the degree of match is higher than a certain threshold) for use by the UE. It should be understood that, as an example, the above-mentioned multiple positioning models available for selection can be stored at the LMF. As another example, the multiple positioning models can be stored at the Analytical Data Repository Function (ADRF) in the core network, and the ADRF can be managed by the NWDAF. Each model can have a corresponding model identifier (ID) or function identifier (ID), so that the UE (and the LMF) can obtain the corresponding model according to the model ID / function ID. Additionally or optionally, in the scenario where the multiple positioning models are stored at the ADRF, as shown in Figure 6, before the LMF performs model selection, the LMF can perform a simple interaction with the ADRF via the NWDAF. Specifically, the LMF can send a retrieval request for the multiple positioning models stored at the ADRF to the NWDAF. The NWDAF can execute the retrieval process to determine whether the multiple positioning models are stored at the ADRF. If the NWDAF determines that the multiple positioning models are indeed stored at the ADRF, it can send a confirmation message for the retrieval request to the LMF. After the LMF confirms that the multiple positioning models it knows are indeed stored at the ADRF, it can perform the aforementioned model selection operation. After the LMF selects the positioning model to be deployed at the UE, it can send a result message of the model selection to the UE via the AMF in the core network. Specifically, the LMF can send the result message of the model selection to the AMF (as an example but not a limitation, the result message can be included in the Namf_Communication_N1N2MessageTransfer service operation called by the LMF for the AMF), and then sent to the UE (as an example but not a limitation, the result message can be included in the DL NAS TRANSPORT message sent by the AMF to the UE). The result message can include the identifier or function identifier of the one or more positioning models selected by the LMF. Alternatively, in the case where multiple positioning models are stored in the LMF, the UE may establish a connection based on positioning protocol messages (e.g., LPP messages) (this way belongs to the user plane (UP) secure transmission mode) to download one or more positioning models it selects from the LMF; in the case where multiple positioning models are stored in the ADRF, the UE may establish a connection based on positioning protocol messages (e.g., LPP messages) (this way belongs to the user plane (UP) secure transmission mode) to download the selected one or more positioning models from the ADRF indicated by the LMF. It should be noted that the information interaction diagram in FIG. 6 only provides examples and is not intended to be restrictive. The figure may include more or fewer steps, and the steps may also be executed in an order different from the order depicted in the figure. For example, the UE receiving the identifier or function identifier of the selected one or more positioning models from the LMF and downloading the selected one or more positioning models from the LMF / ADRF may be executed alternatively. In summary, according to the third embodiment of the present disclosure, the hardware requirements at the user equipment can be reduced, for example, it is not required to store multiple positioning models at the user equipment. Selecting the positioning model by the LMF based on factors such as UE capabilities can improve the selection speed and adaptability of the positioning model. Fourth Embodiment - Model Switching of the Positioning Model The fourth embodiment of the present disclosure mainly relates to the unilateral deployment of the positioning model at the user equipment. Generally speaking, if the matching degree between one or more positioning models currently used by the user equipment (e.g., UE equipment) decreases and the positioning effect deteriorates, then it may be considered to switch the current positioning model to a more suitable updated positioning model. According to the fourth embodiment of the present disclosure, the LMF can participate in switching a suitable positioning model for the user equipment. The signaling interaction process of the communication regarding the fourth embodiment of the present disclosure will be introduced below with reference to FIG. 7. As shown in FIG. 7, the user equipment (shown as UE in the figure) in the wireless communication system may receive a prompt message for model switching from the LMF via the AMF in the core network. Specifically, the LMF may first send the prompt message to the AMF (by way of example and not limitation, this request message may be included in the Namf_Communication_N1N2MessageTransfer service operation invoked by the LMF for the AMF). In the case where the UE is in the idle connection state (e.g., CM-IDLE state), the AMF may initiate a network-triggered service request process so that the AMF can establish (e.g., directly establish or establish via a network device (shown as RAN in the figure)) communication with the UE, thereby sending the prompt message for model switching to the UE (by way of example and not limitation, this prompt message may be included in the DL NAS TRANSPORT message sent by the AMF to the UE). It should be understood that the hint message received by the UE for model switching can indicate to the UE that the positioning effect of its current positioning model is poor and that it is necessary to consider switching the current positioning model. By way of example and not limitation, when the LCS client is not satisfied with the positioning information reported by the UE (for example, the accuracy of the positioning information is lower than a certain threshold) or has additional requirements, the LMF can send the above hint message to the UE, thereby triggering the UE to send a request message for model switching. In this embodiment, the UE can send a request message for model switching of the positioning model deployed at the UE to the LMF via the AMF. Specifically, the UE can send the request message for model switching to the AMF (by way of example and not limitation, this request message can be included in the UL NAS TRANSPORT message sent by the UE to the AMF). Further, the AMF can send the request message for model switching to the LMF (by way of example and not limitation, this request message can be included in the Namf_Communication_N1N2MessageTransfer service operation invoked by the AMF for the LMF). It should be understood that the above hint message for model switching can include a request for the user equipment capabilities (UE capabilities) of the UE. Correspondingly, the request message for model switching sent by the UE can at least include the UE capabilities of the UE. According to the fourth embodiment of the present disclosure, the UE capabilities can include one or more of the following: the application scenarios of the models that the UE can support, the size of the models, the types of the models, the prediction latency of the models, and the prediction accuracy of the models, etc. Additionally or optionally, the request message for model switching can also include one or more of the following: the models previously used by the user equipment, the number of training models, and the desired positioning accuracy, etc. It should be understood that compared with the parameters in the request message for model selection in the third embodiment, since the requirements of the UE may change, the parameters in the request message for model switching in the fourth embodiment may also change accordingly. After the LMF receives the request message for model switching from the UE, it can select one or more updated positioning models from multiple positioning models for deployment at the UE that sent the request, at least based on the request message. It should be understood that the LMF can select one or more updated positioning models suitable for deployment at the UE based on the UE capabilities in the request message (and optionally, the models previously used by the user equipment, the number of training models, the desired positioning accuracy, etc.). In other words, the LMF can match the current model requirements on the UE side with the functions of multiple available positioning models, so as to select the (one or more) updated positioning models with a higher degree of matching with the current UE (for example, the matching degree is higher than a certain threshold) for the UE to use. It should be understood that, as an example, the above-mentioned multiple alternative positioning models can be stored at the LMF. As another example, the multiple positioning models can be stored at the Analytical Data Repository Function (ADRF) in the core network, and the ADRF can be managed by the NWDAF. Each model can have a corresponding model identifier (ID) or function identifier (ID), so that the UE (and the LMF) can obtain the corresponding model according to the model ID / function ID. Additionally or optionally, in the scenario where the multiple positioning models are stored at the ADRF, as shown in Figure 7, before the LMF performs model switching, the LMF can perform a simple interaction with the ADRF via the NWDAF. Specifically, the LMF can send a retrieval request for the multiple positioning models stored at the ADRF to the NWDAF. The NWDAF can execute the retrieval process to determine whether the multiple positioning models are stored at the ADRF. If the NWDAF determines that the multiple positioning models are indeed stored at the ADRF, it can send a confirmation message for the retrieval request to the LMF. After the LMF confirms that the multiple positioning models it knows are indeed stored at the ADRF, it can perform the aforementioned model switching operation. After the LMF switches the positioning model deployed at the UE (i.e., selects an updated positioning model), it can send a result message of the model switching to the UE via the AMF in the core network. Specifically, the LMF can send the result message of the model switching to the AMF (as an example but not a limitation, this result message can be included in the Namf_Communication_N1N2MessageTransfer service operation called by the LMF for the AMF), and then to the UE (as an example but not a limitation, this result message can be included in the DL NASTRANSPORT message sent by the AMF to the UE). The result message can include the identifier or updated function identifier of one or more updated positioning models selected by the LMF. Alternatively, in the case where the multiple positioning models are stored at the LMF, the UE can download one or more updated positioning models it selects from the LMF in a way that establishes a connection based on positioning protocol messages (e.g., LPP messages) (this way belongs to the user plane (UP) secure transmission method); in the case where the multiple positioning models are stored at the ADRF, the UE can download one or more updated positioning models it selects from the ADRF indicated by the LMF in a way that establishes a connection based on positioning protocol messages (e.g., LPP messages) (this way belongs to the user plane (UP) secure transmission method). It should be noted that the information interaction diagram in FIG. 7 only provides examples and is not intended to be limiting. The figure may include more or fewer steps, and the steps may also be executed in an order different from the order depicted in the figure. For example, the UE may alternatively receive the identifier(s) of the selected one or more updated positioning models or the updated function identifier from the LMF and download the selected one or more updated positioning models from the LMF / ADRF. It should be recognized that more details regarding the system network structure and communication processes, etc. in FIG. 7 can be referred to the detailed description in FIG. 6 and will not be repeated here. In summary, according to the fourth embodiment of the present disclosure, it is possible to timely detect the degradation of the positioning function of the user equipment and quickly switch to an updated positioning model with the assistance of the LMF, thereby further improving the effectiveness and adaptability of the positioning model. As described above, the first to fourth embodiments of the present disclosure relate to the interaction between the user equipment and / or network equipment and the core network equipment. It should be understood that the interaction between the devices within the core network itself can also achieve the improvement of the positioning function. The following will describe the positioning services that can be mainly achieved through the network elements in the core network through the fifth and sixth embodiments respectively. Fifth Embodiment - LMF Switching Since the user equipment is usually mobile, the current LMF serving the user equipment may find that it can no longer support the positioning service for the user equipment. By way of example and not limitation, when the current LMF (hereinafter simply referred to as the first LMF) learns that the LCS client is not satisfied with the positioning information reported for the user equipment (for example, the accuracy of the positioning information is lower than a certain threshold) or has additional requirements, it can initiate the LMF switching process (which can also be referred to as the LMF reselection process in this article), so as to switch to another LMF (hereinafter simply referred to as the second LMF) that is more suitable for the current user equipment, in order to better support and manage the positioning function of the user equipment. It should be understood that core network devices such as the AMF and GLMC can participate in or support the above LMF switching process. Specifically, the core network device can determine to switch from the first LMF in the core network to the second LMF based on the LMF profile information for the positioning of the user equipment in the radio communication system. According to the fifth embodiment of the present disclosure, the LMF profile information may include the identifiers of multiple LMFs and the identifiers (IDs) of the positioning models or function identifiers (IDs) supported by them. It should be understood that the LMF profile information at least includes the identifier of the first LMF and the identifier of the positioning model or function identifier supported by it, as well as the identifier of the second LMF and the identifier of the positioning model or function identifier supported by it. Additionally or optionally, the LMF profile information may further include the indication information related to the positioning management of the LMF provided by the NWDAF. According to the fifth embodiment of the present disclosure, profile information about each LMF can be added to the content of the LCS model. Specific examples are as follows, where the added content is indicated by bold and underlined: - LCS client type. - Requested quality of service information, e.g., - LCS accuracy, - Response time (latency), - Access type (3GPP / N3GPP). Note 1: The positioning method may vary depending on the access type. For example, in the case of WLAN access, location determination may only correspond to retrieving IP addressing information from the N3IWF / TNGF; as another example, for wired access, location determination may only correspond to retrieving the geographical coordinates corresponding to the GLI or HFC node ID defined in clause 4.7.8 of TS23.316

[0021] as in. - RAT type (e.g., 5G NR, eLTE, or any RAT type designated for NR satellite access) and / or the serving AN node of the target UE (i.e., gNB or NG-eNB). - RAN configuration information. - LMF capabilities, including support for Uu-based positioning defined in clause 4.3.8 of TS23.586

[0040] and / or ranging / sidelink positioning defined in clause 4.3.8 of TS23.586

[0040] . - LMF load. - LMF location. - Positioning models supported by the LMF - LCS model ID / function ID - Indicating single event reporting or multiple event reporting. - Duration of event reporting. - Network slicing information, e.g., S-NSSAI and / or NSI ID. - LMF service area consisting of one or more TAs. - Supported GAD shapes. - Support for LCS when involving MBSR. - The requested UE has maintained a user plane connection with certain LMFs. When receiving a NAS message from the UE (including the LMF ID and the LPP message (see step in clause 6.3.1) When reporting an event for the delayed 5GC-MT-LR), the AMF sends an LPP message to the LMF, as indicated by the LMF ID. Note 2: The description of how the UE encapsulates the LMF ID in the NAS message is recorded in TS24.571

[0036] . description. The UDM may store the LMF ID in the UE subscription data. During the positioning process, the GMLC receives the LMF ID from the UDM and provides it to the AMF. The GMLC may be configured with the following parameters: - LMF ID and / or - Each group ID and its associated LMF ID. It should be understood that the above profile information of the LMF can be configured to be stored at the AMF, LMF or GLMC. Correspondingly, the above LMF handover / reselection process can be implemented separately at the AMF, the first LMF, and the GLMC. Additionally or alternatively, the above LMF handover / reselection process can also be performed by a combination of multiple devices. By way of example and not limitation, the LMF handover / reselection process can be triggered by the AMF. When the profile information of the LMF is located at the AMF, the AMF side can directly complete the LMF handover process; when the profile information of the LMF is located at the first LMF, the AMF can instruct the LMF to perform the LMF handover process (this process can optionally also be based on additional information provided by the GMLC to the LMF); when the profile information of the LMF is located at the GMLC, the AMF can instruct the GMLC to perform the LMF handover process, and the GMLC can provide the ID of the selected second LMF to the AMF. In summary, according to the fifth embodiment of the present disclosure, by adding profile information of the LMF related to the positioning model in the LCS model, it is possible to quickly switch to the LMF suitable for the current user equipment when the user equipment moves, so as to provide better positioning services. Sixth embodiment - NWDAF analysis The NWDAF in the core network includes a function for analyzing positioning data. For example, core network devices such as the AMF, GMLC, or operation, maintenance, and management (OAM) can input positioning-related data to the NWDAF, and the NWDAF can output statistical and predicted results of positioning accuracy after analysis. As described above, for example, according to the first and second embodiments of the present disclosure, a positioning model can be deployed at a user equipment or an LMF, and can be trained using an artificial intelligence algorithm. Therefore, according to the sixth embodiment of the present disclosure, the LMF can obtain information associated with the used positioning model, and can send the information to the NWDAF as an input parameter of the positioning analysis module of the NWDAF, so that the NWDAF analyzes the information. The signaling interaction process of the communication according to the sixth embodiment of the present disclosure will be introduced below with reference to FIG. 8. As shown in FIG. 8, the LMF in the core network can send information associated with the positioning model to the NWDAF in the core network, so that the NWDAF analyzes the information to obtain the positioning accuracy of the positioning model with respect to the user equipment in the radio communication system. For example, the information associated with the positioning model can at least include an identifier or a function identifier of the positioning model. Table 1 below shows the data collected by the NWDAF for positioning accuracy analysis. As shown in Table 1, the sixth embodiment of the present disclosure proposes to use the NWDAF to increase the analysis of the information related to the positioning model provided by the LMF (shown in bold and underlined in Table 1), so as to further output more accurate positioning statistics and prediction results. Table 1 Data Collected by the NWDAF for Location Accuracy Analysis In summary, according to the sixth embodiment of the present disclosure, by providing information associated with the positioning model to the NWDAF, the NWDAF can be enabled to output more accurate positioning statistics and prediction results. It should be noted that the six embodiments (the first to the sixth embodiments) proposed in the present disclosure can be executed separately or in combination. By way of example and not limitation, the first, third, and fourth embodiments of the present disclosure can be combined and executed in various orders. In some examples, the model can be selected according to the third embodiment, and then the positioning model deployed at the user equipment can be trained according to the first embodiment; in other embodiments, the model can be selected according to the third embodiment, and then the model can be switched according to the fourth embodiment when the model is not applicable; in still other embodiments, the model can be switched according to the fourth embodiment, and then the positioning model deployed at the user equipment can be trained according to the first embodiment; in yet other embodiments, the model can be selected according to the third embodiment, the positioning model can be trained according to the first embodiment, and the model can be switched according to the fourth embodiment. By way of example and not limitation, the second, fifth, and sixth embodiments of the present disclosure can be executed in various orders when the execution entity is the LMF. In some examples, the positioning model deployed at the LMF can be trained according to the second embodiment, and the information associated with the positioning model can be sent to the NWDAF for analysis according to the sixth embodiment (the execution order of the two can be interchanged); in other embodiments, the positioning model deployed at the switched LMF can be trained according to the second embodiment, and (for example, when the current LMF is not applicable to the user equipment) the LMF can be switched according to the fifth embodiment; in still other embodiments, the positioning accuracy of the switched LMF can be analyzed according to the sixth embodiment, and (for example, when the positioning effect is poor) the LMF switching process can be performed according to the fifth embodiment. In addition, the second and sixth embodiments of the present disclosure can also be executed in various orders when the execution entity is the NWDAF. It should be understood that, unless otherwise clearly stated or in obvious contradiction with the context, there is no limitation on the execution order for the combined execution of the above embodiments. Generally speaking, according to the multiple technical solutions proposed in the present disclosure for applying artificial intelligence ( / machine learning) technology to the positioning function of user equipment in a wireless communication system, multiple aspects of the positioning service have been improved. For example, the present disclosure supports unilateral deployment of the positioning model on the user equipment side or the core network side, and supports training the positioning model using artificial intelligence methods, thus being able to improve the efficiency and accuracy of positioning on the user equipment side or the core network side. The training method of the positioning model according to the embodiments of the present disclosure can make full use of the measurement data of the user equipment in different positions and at different speeds, and give play to the prediction advantages of the artificial intelligence algorithm. In addition, the present disclosure supports the LMF in the core network to perform model selection and model switching of the positioning model on the user equipment side, which can reduce the hardware requirements of the user equipment, so as to use the core network element with stronger storage capacity and computing power to implement the storage of multiple models and the computing processes involved in model selection or switching, further improving the efficiency. In addition, with the assistance of the core network element (for example, analyzing the positioning model data, timely switching the LMF and switching the positioning model, etc.), the present disclosure can better meet the positioning requirements of the LCS client for the user equipment in various environments. Exemplary method FIG. 9 shows a flowchart of an example method 900 for a user equipment (or more specifically, electronic device 200) in a wireless communication system according to a first embodiment of the present disclosure. As shown in FIG. 9, the method 900 may include training a positioning model deployed at the user equipment (block S902). In the method 900, the input of the positioning model may at least include assisted positioning data obtained by the user equipment from a positioning management function (LMF) in the core network and the strength of positioning reference signals measured by the user equipment itself. The output of the positioning model may at least include the positioning result of the user equipment. For detailed example operations of the method, reference may be made to the above description of the operations of the user equipment (or more specifically, electronic device 200), which will not be repeated here. FIG. 10 shows a flowchart of an example method 1000 for a core network device (or more specifically, electronic device 300) in a wireless communication system according to a second embodiment of the present disclosure. The core network device may be a positioning management function (LMF) or a network data analytics function (NWDAF) in this embodiment. As shown in FIG. 10, the method 1000 may include training a positioning model deployed at the core network device (block S1002). In the method 1000, the input of the positioning model may at least include assisted positioning data obtained by the core network device from network devices or user equipment in the wireless communication system, and the assisted positioning data may correspondingly at least include the strength of channel sounding reference signals from the user equipment measured by the network device or the strength of positioning reference signals measured by the user equipment itself. The output of the positioning model may at least include the positioning result of the user equipment. For detailed example operations of the method, reference may be made to the above description of the operations of the core network device (or more specifically, electronic device 300), which will not be repeated here. FIG. 11 shows a flowchart of an example method 1100 for a user equipment (or more specifically, electronic device 200) in a wireless communication system according to a third embodiment of the present disclosure. As shown in FIG. 11, the method 1100 may include sending a request message for model selection of a positioning model deployed at the user equipment to a positioning management function (LMF) in the core network via an access and mobility management function (AMF) in the core network (block S1102). In the method 1100, the request message may at least include the user equipment capabilities of the user equipment, such that the LMF can at least select one or more positioning models from multiple positioning models for deployment at the user equipment based on the request message. For detailed example operations of the method, reference may be made to the above description of the operations of the user equipment (or more specifically, electronic device 200), which will not be repeated here. FIG. 12 shows a flowchart of an exemplary method 1200 for a user equipment (or more specifically, electronic device 200) in a wireless communication system according to a fourth embodiment of the present disclosure. As shown in FIG. 12, the method 1200 may include sending a request message for a model switch of a positioning model deployed at the user equipment to a positioning management function (LMF) in the core network via an access and mobility management function (AMF) in the core network (block S1202). In the method 1200, the request message may at least include the user equipment capabilities of the user equipment, such that the LMF may at least select one or more updated positioning models from a plurality of positioning models for deployment at the user equipment based on the request message. For a detailed example operation of the method, reference may be made to the operation description of the user equipment (or more specifically, electronic device 200) above, which will not be repeated here. FIG. 13 shows a flowchart of an exemplary method 1300 for a core network device (or more specifically, electronic device 300) in a wireless communication system according to a fifth embodiment of the present disclosure. The core network device may be a positioning management function (LMF), an access and mobility management function (AMF), or a gateway mobile location center (GMLC) in this embodiment. As shown in FIG. 13, the method 1300 may include determining to switch from a first LMF to a second LMF in the core network for positioning of a user equipment in the wireless communication system based on LMF profile information (block S1302). In the method 1300, the LMF profile information may at least include an identifier of the first LMF and an identifier or function identifier of the supported positioning model, and an identifier of the second LMF and an identifier or function identifier of the supported positioning model. For a detailed example operation of the method, reference may be made to the operation description of the core network device (or more specifically, electronic device 300) above, which will not be repeated here. FIG. 14 shows a flowchart of an exemplary method 1400 for a core network device (or more specifically, electronic device 300) in a wireless communication system according to a sixth embodiment of the present disclosure. The core network device may be a positioning management function (LMF) in this embodiment. As shown in FIG. 14, the method 1400 may include sending information associated with a positioning model to a network data analytics function (NWDAF) in the core network, such that the NWDAF analyzes the information to obtain the positioning accuracy of the positioning model with respect to a user equipment in the wireless communication system (block S1402). For a detailed example operation of the method, reference may be made to the operation description of the core network device (or more specifically, electronic device 300) above, which will not be repeated here. As described above, the exemplary methods according to the six embodiments of the present disclosure may be executed separately or in various combinations in multiple orders. The solution of the present disclosure may be implemented in the following exemplary manner. (1) An electronic device for a user equipment in a wireless communication system, the electronic device comprising at least one processor and at least one memory, the at least one memory including computer program instructions, wherein the at least one memory and the computer program instructions are configured to, by means of the at least one processor, cause the user equipment to perform the following operations: Train a positioning model deployed at the user equipment, wherein the input of the positioning model includes at least the assistance positioning data obtained by the user equipment from a positioning management function (LMF) in a core network and the strength of a positioning reference signal measured by the user equipment itself, and wherein the output of the positioning model includes at least the positioning result of the user equipment. (2) The electronic device according to clause (1), wherein the positioning result includes one of the following: inference positioning result, and a direct positioning result. (3) The electronic device according to clause 1, wherein the assistance positioning data includes at least one or more of the following: a positioning application scenario, a desired positioning accuracy, an inference duration, and a training data reliability. (4) The electronic device according to clause (2), the at least one memory and the computer program instructions are further configured to, by means of the at least one processor, cause the user equipment to perform the following operations: Before training the positioning model, receive, via an access and mobility management function (AMF) in the core network a request message for model training from the LMF, the request message including at least the assistance positioning data; and After training the positioning model, send, via the AMF, a completion message of the model training to the LMF, the completion message indicating a confirmation that the training of the positioning model by the user equipment has been completed. (5) The electronic device according to clause (4), wherein the request message further includes a request for the user equipment user equipment capabilities, and wherein the completion message further includes the user equipment capabilities. (6) The electronic device according to clause (5), wherein the user equipment capabilities include one or more of the following: the application scenarios of the models that the user equipment can support, the size of the models, the types of the models, the prediction latency of the models, and the prediction accuracy of the models. (7) The electronic device according to clause (4), wherein the completion message further includes the positioning result, enabling the LMF to generate an adjustment message for adjusting the parameters or structure of the positioning model at least based on a comparison between the positioning result and true positioning data, and the at least one memory and computer program instructions are further configured to cause the user equipment to perform the following operations through the at least one processor: Receive the adjustment message from the LMF via the AMF; and Adjust the parameters or structure of the positioning model based on the adjustment message. (8) An electronic device for a core network device in a core network, the electronic device including at least one processing processor and at least one memory, the at least one memory including computer program instructions, wherein the at least one memory and computer program instructions are configured to cause the core network device to perform the following operations through the at least one processor: Train a positioning model deployed at the core network device, wherein the input of the positioning model includes at least the auxiliary positioning data obtained by the core network device from network devices or user equipment in a wireless communication system, and the auxiliary positioning data correspondingly includes at least the intensity of a channel sounding reference signal measured by a network device from the user equipment or the intensity of a positioning reference signal measured by the user equipment itself, and wherein the output of the positioning model includes at least the positioning result of the user equipment. (9) The electronic device according to clause (8), wherein the auxiliary positioning data includes at least one or more of the following: the identifier of the cell to which the user equipment is connected, the time delay of a positioning reference signal transmitted by the user equipment measured by a network device, and the phase information, incident angle, Doppler frequency shift, and timestamp information of the user equipment's positioning reference signal. (10) The electronic device according to clause (8), wherein the core network device includes a Location Management Function (LMF). (11) The electronic device according to clause (8), wherein the core network device includes a Network Data Analytics Function (NWDAF). (12) The electronic device according to clause (10), wherein the at least one memory and computer program instructions are further configured to cause the core network device to perform the following operations through the at least one processor: Before training the positioning model: Via the Access and Mobility Management Function (AMF) in the core network to network devices in the wireless communication system Sending a request message for model training, where the request message includes a request for the auxiliary positioning data; as well as Do one of the following: The network device causes the user equipment to measure the positioning reference information in response to the request message. After measuring the strength of the positioning reference signal, receiving the auxiliary positioning data including the strength of the positioning reference signal measured by the user equipment itself from the user equipment via the AMF; or The network device measures the channel sounding reference from the user equipment in response to the request message. After measuring the strength of the signal, the auxiliary positioning data including the strength of the channel sounding reference signal is received from the network device via the AMF; After training the localization model: Send a model training completion message to the network device via AMF, which indicates that the core Confirmation that the training of the positioning model of the heart network device has been completed. (13) The electronic device according to clause (11), wherein the at least one memory and the computer program instructions further The device is configured to cause the core network device to perform the following operations through the at least one processor: Before training the positioning model: In response to an instruction from the Location Management Function (LMF) in the core network, the access and A mobility management function (AMF) sends a request message for model training to a network device in the wireless communication system, where the request message includes a request for the assisted positioning data; and Do one of the following: The network device causes the user equipment to measure the positioning reference information in response to the request message. After measuring the strength of the positioning reference signal, receiving the auxiliary positioning data including the strength of the positioning reference signal measured by the user equipment itself from the user equipment via the AMF; or The network device measures the channel sounding reference from the user equipment in response to the request message. After measuring the strength of the signal, the auxiliary positioning data including the strength of the channel sounding reference signal is received from the network device via the AMF; After training the localization model: Send a model training completion message to the network device via AMF, which indicates that the core Confirmation that the training of the positioning model for the core network device has been completed. (14) The electronic device according to clause (12) or (13), wherein the request message further includes a request for the user equipment capabilities of the user equipment, so that the network device also obtains the user equipment capabilities of the user equipment from the user equipment in response to the request message, and the at least one memory and computer program instructions are further configured to cause the core network device to perform the following operations through the at least one processor: Receive the user equipment capabilities from the network device via the AMF. (15) The electronic device according to clause (14), wherein the user equipment capabilities include one or more of the following: positioning method, positioning model, accuracy of previous positioning, application scenarios of models supported by the user equipment, size of the model, type of the model, prediction latency of the model, prediction accuracy of the model. (16) The electronic device according to clause (10), the at least one memory and computer program instructions are further configured to cause the core network device to perform the following operations through the at least one processor: Determine to switch from the LMF itself to another LMF in the core network for the positioning of the user equipment based on the LMF profile information, wherein the LMF profile information at least includes the identifier of the LMF and the identifier or functional identifier of the supported positioning model, and the identifier of the other LMF and the identifier or functional identifier of the supported positioning model. (17) The electronic device according to clause (10), the at least one memory and computer program instructions are further configured to cause the core network device to perform the following operations through the at least one processor: Send information associated with the positioning model to the Network Data Analytics Function (NWDAF) in the core network, so that the NWDAF analyzes the information to obtain the positioning accuracy of the positioning model for the user equipment, wherein the information associated with the positioning model at least includes the identifier or functional identifier of the positioning model. (18) The electronic device according to clause (1) or (8), wherein the training uses an artificial intelligence algorithm. (19) The electronic device according to clause (18), wherein the artificial intelligence algorithm includes one of the following (19) The electronic device according to clause (18), wherein the artificial intelligence algorithm includes one of the following wherein the information associated with the positioning model at least includes the identifier or functional identifier of the positioning model. (18) The electronic device according to clause (1) or (8), wherein the training uses an artificial intelligence algorithm. (19) The electronic device according to clause (18), wherein the artificial intelligence algorithm includes one of the following ​One or more: linear regression, logistic regression, decision tree, naive Bayes, support vector machine, random forest, artificial neural network, K-nearest neighbor. (20) An electronic device for a user equipment in a wireless communication system, the electronic device comprising at least one processor and at least one memory, the at least one memory including computer program instructions, wherein the at least one memory and the computer program instructions are configured to, by means of the at least one processor, cause the user equipment to perform the following operations: Send a request message for model selection of a positioning model deployed at the user equipment to a positioning management function (LMF) in the core network via an access and mobility management function (AMF) in the core network, the request message including at least the user equipment capabilities of the user equipment, such that the LMF selects one or more positioning models from a plurality of positioning models for deployment at the user equipment based at least on the request message. (21) The electronic device according to clause (20), wherein the request message further includes one or more of the following: the number of training models, and the desired positioning accuracy. (22) The electronic device according to clause (20), wherein the plurality of positioning models are stored at the LMF. (23) The electronic device according to clause (20), wherein the plurality of positioning models are stored at an analytical data repository function (ADRF) in the core network, and the ADRF is managed by a network data analytics function (NWDAF). (24) The electronic device according to clause (23), wherein the LMF sends a retrieval request for the plurality of positioning models stored at the ADRF to the NWDAF, such that the NWDAF sends an acknowledgement message for the retrieval request to the LMF in the case where it is determined that the plurality of positioning models are indeed stored at the ADRF. (25) The electronic device according to clause (22) or (24), the at least one memory and the computer program instructions are further configured to, by means of the at least one processor, cause the user equipment to perform the following operations: After the LMF selects the one or more positioning models, receive a model selection result message from the LMF via the AMF, the result message including identifiers or functional identifiers of the one or more positioning models. (26) The electronic device according to clause (22), the at least one memory and the computer program instructions further configured to cause the user equipment to perform the following operations via the at least one processor: After the LMF selects the one or more positioning models, download the one or more positioning models from the LMF by establishing a connection based on positioning protocol messages in a manner. (27) The electronic device according to clause (24), the at least one memory and the computer program instructions are further configured to cause the user equipment to perform the following operations via the at least one processor: After the LMF selects the one or more positioning models, download the one or more positioning models from the ADRF by establishing a connection based on positioning protocol messages in a manner. (28) The electronic device according to clause (20), wherein the user equipment capabilities include one or more of the following: the application scenarios of the models that the user equipment can support, the size of the models, the types of the models, the prediction latency of the models, and the prediction accuracy of the models. (29) The electronic device according to clause (20), the at least one memory and the computer program instructions are further configured to cause the user equipment to perform the following operations via the at least one processor: Train the positioning model deployed at the user equipment, wherein the input of the positioning model includes at least the auxiliary positioning data obtained by the user equipment from the LMF and the strength of the positioning reference signal measured by the user equipment itself, and wherein the output of the positioning model includes at least the positioning result of the user equipment. (30) The electronic device according to clause (20), the at least one memory and the computer program instructions are further configured to cause the user equipment to perform the following operations via the at least one processor: Send a request message for model switching of the positioning model deployed at the user equipment to the LMF via the AMF, wherein the request message includes at least the user equipment capabilities of the user equipment, so that the LMF selects one or more updated positioning models from the multiple positioning models for deployment at the user equipment at least based on the request message. (31) An electronic device for a user equipment in a wireless communication system, the electronic device includes at least one a processor and at least one memory, the at least one memory including computer program instructions, wherein the at least one memory and the computer program instructions are configured to, by means of the at least one processor, cause the user equipment to perform the following operations: send a request message for model switching of a positioning model deployed at the user equipment to a positioning management function (LMF) in the core network via an access and mobility management function (AMF) in the core network The request message includes at least the user equipment capabilities of the user equipment, such that the LMF selects one or more updated positioning models from a plurality of positioning models for deployment at the user equipment at least based on the request message. (32) The electronic device according to clause (31), wherein the request message is triggered based on the LMF's response to the positioning The accuracy of the positioning information reported by the service client for the user equipment is lower than a threshold. (33) The electronic device according to clause (31), wherein the request message further includes one or more of the following: the model previously used by the user equipment, the number of training models, and the desired positioning accuracy. (34) The electronic device according to clause (31), wherein the plurality of positioning models are stored at the LMF. (35) The electronic device according to clause (31), wherein the plurality of positioning models are stored in the analysis data repository function (ADRF) in the core network, and the ADRF is managed by the network data analysis function (NWDAF). (36) The electronic device according to clause (35), wherein the LMF sends a retrieval request for the plurality of positioning models stored at the ADRF to the NWDAF, such that the NWDAF sends an acknowledgment message for the retrieval request to the LMF in the case where it is determined that the plurality of positioning models are indeed stored at the ADRF. (37) The electronic device according to clause (34) or (36), the at least one memory and the computer pro gram instructions are further configured to, by means of the at least one processor, cause the user equipment to perform the following operations: After the LMF selects the one or more updated positioning models, receive a model switching result message from the LMF via the AMF, the result message including identifiers of the one or more updated positioning models or updated function identifiers. (38) The electronic device according to clause (34), the at least one memory and the computer program instructions further configured to cause the user equipment to perform the following operations by means of the at least one processor: after the one or more updated positioning models are selected by the LMF, download the one or more updated positioning models from the LMF by establishing a connection based on positioning protocol messages in a manner. (39) The electronic device according to clause (36), wherein the at least one memory and the computer program instructions are further configured to cause the user equipment to perform the following operations by means of the at least one processor: after the one or more positioning models are selected by the LMF, download the one or more positioning models from the ADRF indicated by the LMF by establishing a connection based on positioning protocol messages in a manner. (40) The electronic device according to clause (31), wherein the user equipment capabilities include one or more of the following: the application scenarios of the models that the user equipment can support, the size of the models, the types of the models, the prediction latency of the models, and the prediction accuracy of the models. (41) The electronic device according to clause (31), wherein the at least one memory and the computer program instructions are further configured to cause the user equipment to perform the following operations by means of the at least one processor: train the updated positioning model deployed at the user equipment, wherein the input of the updated positioning model at least includes the assisted positioning data obtained by the user equipment from the LMF and the strength of the positioning reference signal measured by the user equipment itself, and wherein the output of the updated positioning model at least includes the positioning result of the user equipment. (42) An electronic device for a core network device in a core network, the electronic device comprising at least one processor and at least one memory, the at least one memory comprising computer program instructions, wherein the at least one memory and the computer program instructions are configured to cause the core network device to perform the following operations by means of the at least one processor: determine to switch from a first LMF to a second LMF in the core network for positioning of a user equipment in a wireless communication system, wherein the LMF profile information at least includes the identifier of the first LMF and the identifier or function identifier of the supported positioning model, and the identifier of the second LMF and the identifier or function identifier of the supported positioning model. (43) The electronic device according to clause (42), wherein the core network device includes an access and mobility management function (AMF), a first LMF, or a gateway mobile location center (GLMC). (44) The electronic device according to clause (42), wherein the handover is triggered based on the first LMF in response to the accuracy of the positioning information reported by the positioning service client for the user equipment being lower than a threshold value. (45) An electronic device for a positioning management function (LMF) in a core network, the electronic device includes at least one processor and at least one memory, the at least one memory includes computer program instructions, wherein the at least one memory and the computer program instructions are configured to cause the LMF to perform the following operations through the at least one processor: Send information associated with a positioning model to a network data analysis function (NWDAF) in the core network, so that the NWDAF analyzes the information to obtain the positioning accuracy of the positioning model for a user equipment in a wireless communication system. (46) The electronic device according to clause (45), wherein the information associated with the positioning model at least includes the identifier of the positioning model or the function identifier. (47) The electronic device according to clause (45), wherein the positioning model is deployed at the LMF or at the user equipment, and is trained using an artificial intelligence algorithm. (48) The electronic device according to clause (45), the at least one memory and the computer program instructions are further configured to cause the LMF to perform the following operations through the at least one processor: Train the positioning model deployed at the LMF, wherein the input of the positioning model at least includes the auxiliary positioning data obtained by the LMF from network devices or user devices in the wireless communication system, and the auxiliary positioning data correspondingly at least includes the strength of the channel sounding reference signal measured by the network device from the user equipment or the strength of the positioning reference signal measured by the user equipment itself, and wherein the output of the positioning model at least includes the positioning result of the user equipment. (49) The electronic device according to clause (45), the at least one memory and the computer program instructions are further configured to cause the LMF to perform the following operations through the at least one processor: Based on the LMF profile information, determine to switch from the LMF itself to another LMF in the core network for the positioning of the user equipment, wherein the LMF profile information at least includes the identifier of the LMF and the identifier or functional identifier of the supported positioning model, as well as the identifier of the other LMF and the identifier or functional identifier of the supported positioning model. (50) A method for a user equipment in a wireless communication system, the method comprising: Train a positioning model deployed at the user equipment, wherein the input of the positioning model at least includes the assisted positioning data obtained by the user equipment from the positioning management function (LMF) in the core network and the strength of the positioning reference signal measured by the user equipment itself, and wherein the output of the positioning model at least includes the positioning result of the user equipment. (51) A method for a core network device in a core network, the method comprising: Train a positioning model deployed at the core network device, wherein the input of the positioning model at least includes the assisted positioning data obtained by the core network device from a network device or user equipment in the wireless communication system, and the assisted positioning data accordingly at least includes the strength of the channel sounding reference signal measured by the network device from the user equipment or the strength of the positioning reference signal measured by the user equipment itself, and wherein the output of the positioning model at least includes the positioning result of the user equipment. (52) A method for a user equipment in a wireless communication system, the method comprising: Send a request message for model selection of a positioning model deployed at the user equipment via the access and mobility management function (AMF) in the core network to the positioning management function (LMF) in the core network, wherein the request message at least includes the user equipment capabilities of the user equipment, such that the LMF selects one or more positioning models from a plurality of positioning models for deployment at the user equipment at least based on the request message. (53) A method for a user equipment in a wireless communication system, the method comprising: Send, via the access and mobility management function (AMF) in the core network, a request message for model selection of a positioning model deployed at the user equipment to the positioning management function (LMF) in the core network Send a request message for model switching of the positioning model deployed at the user equipment, where the request message includes at least the user equipment capabilities of the user equipment, such that the LMF selects one or more updated positioning models from a plurality of positioning models for deployment at the user equipment based at least on the request message. (54) A method for a core network device in a core network, the method comprising: Based on positioning management function (LMF) profile information, determine to switch from a first LMF in the core network to a second LMF for positioning of a user equipment in a wireless communication system, where the LMF profile information includes at least an identifier of the first LMF and an identifier or function identifier of the supported positioning model, and an identifier of the second LMF and an identifier or function identifier of the supported positioning model. (55) A method for a positioning management function (LMF) in a core network, the method comprising: Send information associated with a positioning model to a network data analytics function (NWDAF) in the core network, such that the NWDAF analyzes the information to obtain the positioning accuracy of the positioning model with respect to a user equipment in a wireless communication system. (56) A computer-readable storage medium storing one or more executable instructions, the one or more executable instructions, when executed by one or more processors of an electronic device, cause the electronic device to execute the method according to any one of clauses (50)-(55). (57) A computer program product comprising executable instructions, the executable instructions, when executed by one or more processors of a computer, cause the computer to execute the method according to any one of clauses (50)-(55). It should be noted that the above application examples are merely exemplary. The embodiments of the present disclosure can also be executed in any other appropriate manner in the above application examples, and the beneficial effects obtained by the embodiments of the present disclosure can still be achieved. Moreover, the embodiments of the present disclosure can also be applied to other similar application examples, and the beneficial effects obtained by the embodiments of the present disclosure can still be achieved. It should be understood that the machine-executable instructions in the machine-readable storage medium or program product according to the embodiments of the present disclosure can be configured to perform operations corresponding to the above device and method embodiments. When referring to the above device and method embodiments, the embodiments of the machine-readable storage medium or program product are clear to those skilled in the art, and thus will not be described repeatedly. The machine-readable storage medium and program product for carrying or including the above machine-executable instructions also fall within the scope of the present disclosure. Such a storage medium may include, but is not limited to, floppy disks, optical disks, magneto-optical disks, memory cards, memory sticks, and the like. In addition, it should be understood that the above series of processes and devices can also be implemented by software and / or firmware. In the case of implementation by software and / or firmware, a program constituting the software is installed from a storage medium or a network into a computer having a dedicated hardware structure, such as the general personal computer 1500 shown in FIG. 15. When various programs are installed in this computer, it can perform various functions and the like. FIG. 15 is a block diagram showing an example structure of a personal computer as an information processing device that can be adopted in the embodiments of the present disclosure. In one example, this personal computer may correspond to the above-described exemplary terminal device according to the present disclosure. In FIG. 15, a central processing unit (CPU) 1501 executes various processes according to a program stored in a read-only memory (ROM) 1502 or a program loaded from a storage section 1508 into a random access memory (RAM) 1503. In the RAM 1503, data required when the CPU 1501 executes various processes and the like is also stored as needed. The CPU 1501, ROM 1502, and RAM 1503 are connected to each other via a bus 1504. An input / output interface 1505 is also connected to the bus 1504. The following components are connected to the input / output interface 1505: an input section 1506 including a keyboard, a mouse, etc.; an output section 1507 including a display such as a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 1508 including a hard disk, etc.; and a communication section 1509 including a network interface card such as a LAN card, a modem, etc. The communication section 1509 performs communication processing via a network such as the Internet. As needed, a drive 1510 is also connected to the input / output interface 1505. A removable medium 1511 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc. is mounted on the drive 1510 as needed, so that a computer program read therefrom is installed into the storage section 1508 as needed. In the case of implementing the above series of processes by software, a program constituting the software is installed from a network such as the Internet or a storage medium such as the removable medium 1511. Those skilled in the art should understand that such a storage medium is not limited to the removable medium 1511 shown in FIG. 15 that stores a program and is distributed separately from the device to provide the program to the user. Examples of the removable medium 1511 include magnetic disks (including floppy disks (registered trademark)), optical discs (including compact disc read-only memory (CD-ROM) and digital versatile disc (DVD)), magneto-optical discs (including mini discs (MD) (registered trademark)), and semiconductor memories. Alternatively, the storage medium may be a ROM 1502, a hard disk included in the storage section 1508, etc., in which a program is stored and is distributed to the user together with the device containing them. The technology of the present disclosure can be applied to various products. For example, the implementation of the method according to the present disclosure may involve various network devices / base stations. For example, the electronic device 200 according to an embodiment of the present disclosure may be implemented as various user devices / terminal devices or be included in various user devices / terminal devices, and the methods shown in FIGS. 9, 11, or 12 may also be implemented by various user devices / terminal devices. For example, the network device / base station mentioned in the present disclosure may be implemented as any type of base station, such as a gNB (evolved Node B). A gNB may include one or more transmission and reception points (TRPs). A user equipment may be connected to one or more TRPs within one or more gNBs. For example, the user equipment may be able to receive transmissions from multiple gNBs (and / or multiple TRPs provided by the same gNB). For example, a gNB may include a macro gNB and a small gNB. A small gNB may be a gNB that covers a cell smaller than a macro cell, such as a pico gNB, a micro gNB, and a home (femto) gNB. Instead, the base station may be implemented as any other type of base station, such as a NodeB and a base transceiver station (BTS). The base station may include: a main body configured to control wireless communication (also referred to as base station equipment); and one or more remote radio heads (RRHs) provided at locations different from the main body. In addition, various types of terminals described below may operate as a base station by temporarily or semi-persistently performing base station functions. For example, the user equipment mentioned in the present disclosure is also referred to as a terminal device in some examples and can be implemented as a mobile terminal (such as a smart phone, a tablet personal computer (PC), a notebook PC, a portable game terminal, a portable / dongle-type mobile router, and a digital camera device) or a vehicle-mounted terminal (such as a car navigation device). The user equipment can also be implemented as a terminal for performing machine-to-machine (M2M) communication (also referred to as a machine type communication (MTC) terminal). In addition, the user equipment can be a wireless communication module (such as an integrated circuit module including a single chip) installed on each of the above terminals. In some cases, the user equipment can communicate using multiple wireless communication technologies. For example, the user equipment can be configured to communicate using two or more of GSM, UMTS, CDMA2000, WiMAX, LTE, LTE-A, WLAN, NR, Bluetooth, etc. In some cases, the user equipment can also be configured to communicate using only one wireless communication technology. Examples according to the present disclosure will be described below with reference to FIGS. 16 to 19. Examples of base stations It should be understood that the term base station in the present disclosure has the full breadth of its ordinary meaning and includes at least a wireless communication station used as part of a wireless communication system or a radio system to facilitate communication. Examples of base stations can be, for example, but not limited to the following: The base station can be one or both of a base transceiver station (BTS) and a base station controller (BSC) in a GSM system, one or both of a radio network controller (RNC) and a NodeB in a WCDMA system, an eNB in LTE and LTE-Advanced systems, or a corresponding network node in a future communication system (such as a gNB, an eLTE eNB, etc. that may appear in a 5G communication system). Some functions of the base stations in the present disclosure can also be implemented as an entity having a control function for communication in D2D, M2M, and V2V communication scenarios, or as an entity playing a role in spectrum coordination in a cognitive radio communication scenario. First example FIG. 16 is a block diagram showing a first example of a schematic configuration of a base station (taking a gNB as an example in this figure) to which the technology of the present disclosure can be applied. The gNB 1600 includes a plurality of antennas 1610 and a base station device 1620. The base station device 1620 and each antenna 1610 can be connected to each other via an RF cable. In one implementation, the gNB 1600 (or the base station device 1620) here can correspond to the above network device. Each of the antennas 1610 includes single or multiple antenna elements (such as multiple antenna elements included in a multiple-input multiple-output (MIMO) antenna), and is used for the base station device 1620 to transmit and receive wireless signals. As shown in FIG. 16, the gNB 1600 may include multiple antennas 1610. For example, the multiple antennas 1610 may be compatible with multiple frequency bands used by the gNB 1600. The base station device 1620 includes a controller 1621, a memory 1622, a network interface 1623, and a wireless communication interface 1625. The controller 1621 may be, for example, a CPU or a DSP, and operates various functions of the higher layers of the base station device 1620. For example, the controller 1621 generates data packets based on the data in the signals processed by the wireless communication interface 1625, and transmits the generated packets via the network interface 1623. The controller 1621 may bundle data from multiple baseband processors to generate a bundled packet, and transmit the generated bundled packet. The controller 1621 may have a logical function to execute controls such as radio resource control, radio bearer control, mobility management, admission control, and scheduling. The control may be executed in combination with a nearby gNB or a core network node. The memory 1622 includes a RAM and a ROM, and stores programs executed by the controller 1621 and various types of control data (such as a terminal list, transmission power data, and scheduling data). The network interface 1623 is a communication interface for connecting the base station device 1620 to the core network 1624. The controller 1621 may communicate with a core network node or another gNB via the network interface 1623. In this case, the gNB 1600 and the core network node or other gNBs may be connected to each other through logical interfaces (such as the S1 interface and the X2 interface). The network interface 1623 may also be a wired communication interface or a wireless communication interface for a wireless backhaul line. If the network interface 1623 is a wireless communication interface, compared with the frequency band used by the wireless communication interface 1625, the network interface 1623 may use a higher frequency band for wireless communication. The wireless communication interface 1625 supports any cellular communication scheme (such as Long Term Evolution (LTE) and LTE-Advanced), and provides a wireless connection to terminals in the cell located at the gNB 1600 via the antenna 1610. The wireless communication interface 1625 generally may include, for example, a baseband (BB) processor 1626 and an RF circuit 1627. The BB processor 1626 may perform, for example, encoding / decoding, modulation / demodulation, and multiplexing / demultiplexing, and perform various types of signal processing of layers (such as L1, Media Access Control (MAC), Radio Link Control (RLC), and Packet Data Convergence Protocol (PDCP)). Instead of the controller 1621, the BB processor 1626 may have a part or all of the above-described logical functions. The BB processor 1626 may be a memory for storing a communication control program, or a module including a processor configured to execute the program and related circuits. The update program may change the functions of the BB processor 1626. The module may be a card or blade inserted into a slot of the base station device 1620. Alternatively, the module may also be a chip mounted on the card or blade. Meanwhile, the RF circuit 1627 may include, for example, mixers, filters, and amplifiers, and transmit and receive wireless signals via the antenna 1610. Although FIG. 16 shows an example in which one RF circuit 1627 is connected to one antenna 1610, the present disclosure is not limited to this illustration, and one RF circuit 1627 may be connected to multiple antennas 1610 simultaneously. As shown in FIG. 16, the wireless communication interface 1625 may include multiple BB processors 1626. For example, the multiple BB processors 1626 may be compatible with multiple frequency bands used by the gNB 1600. As shown in FIG. 16, the wireless communication interface 1625 may include multiple RF circuits 1627. For example, the multiple RF circuits 1627 may be compatible with multiple antenna elements. Although FIG. 16 shows an example in which the wireless communication interface 1625 includes multiple BB processors 1626 and multiple RF circuits 1627, the wireless communication interface 1625 may also include a single BB processor 1626 or a single RF circuit 1627. Second Example FIG. 17 is a block diagram showing a second example of a schematic configuration of a base station (taking the gNB as an example in this figure) to which the technology of the present disclosure can be applied. The gNB 1730 includes multiple antennas 1740, a base station device 1750, and a Remote Radio Head (RRH) 1760. The RRH 1760 and each antenna 1740 may be connected to each other via an RF cable. The base station device 1750 and the RRH 1760 may be connected to each other via a high-speed line such as an optical fiber cable. In one implementation, the gNB 1730 (or the base station device 1750) here may correspond to the above-described network device. Each of the antennas 1740 includes single or multiple antenna elements (such as the multiple antenna elements included in a MIMO antenna) and is used for the RRH 1760 to transmit and receive wireless signals. As shown in FIG. 17, the gNB 1730 may include multiple antennas 1740. For example, the multiple antennas 1740 may be compatible with multiple frequency bands used by the gNB 1730. The base station device 1750 includes a controller 1751, a memory 1752, a network interface 1753, a wireless communication interface 1755, and a connection interface 1757. The controller 1751, the memory 1752, and the network interface 1753 are the same as the controller 1621, the memory 1622, and the network interface 1623 described with reference to FIG. 16. The wireless communication interface 1755 supports any cellular communication scheme (such as LTE and LTE-Advanced) and provides wireless communication to terminals located in the sector corresponding to the RRH 1760 via the RRH 1760 and the antennas 1740. The wireless communication interface 1755 may generally include, for example, a BB processor 1756. The BB processor 1756 is the same as the BB processor 1626 described with reference to FIG. 16, except that the BB processor 1756 is connected to the RF circuit 1764 of the RRH 1760 via the connection interface 1757. As shown in FIG. 17, the wireless communication interface 1755 may include multiple BB processors 1756. For example, the multiple BB processors 1756 may be compatible with multiple frequency bands used by the gNB 1730. Although FIG. 17 shows an example in which the wireless communication interface 1755 includes multiple BB processors 1756, the wireless communication interface 1755 may also include a single BB processor 1756. The connection interface 1757 is an interface for connecting the base station device 1750 (wireless communication interface 1755) to the RRH 1760. The connection interface 1757 may also be a communication module for communication in the above-mentioned high-speed line for connecting the base station device 1750 (wireless communication interface 1755) to the RRH 1760. The RRH 1760 includes a connection interface 1761 and a wireless communication interface 1763. The connection interface 1761 is an interface for connecting the RRH 1760 (wireless communication interface 1763) to the base station device 1750. The connection interface 1761 may also be a communication module for communication in the above-mentioned high-speed line. The wireless communication interface 1763 transmits and receives wireless signals via the antenna 1740. The wireless communication interface 1763 generally may include, for example, an RF circuit 1764. The RF circuit 1764 may include, for example, mixers, filters, and amplifiers, and transmits and receives wireless signals via the antenna 1740. Although FIG. 17 shows an example where one RF circuit 1764 is connected to one antenna 1740, the present disclosure is not limited to this illustration, and one RF circuit 1764 may be connected to multiple antennas 1740 simultaneously. As shown in FIG. 17, the wireless communication interface 1763 may include multiple RF circuits 1764. For example, the multiple RF circuits 1764 may support multiple antenna elements. Although FIG. 17 shows an example where the wireless communication interface 1763 includes multiple RF circuits 1764, the wireless communication interface 1763 may also include a single RF circuit 1764.Examples of user equipment First example FIG. 18 is a block diagram showing an example of a schematic configuration of a smartphone 1800 to which the techniques of the present disclosure may be applied. The smartphone 1800 includes a processor 1801, a memory 1802, a storage device 1803, an external connection interface 1804, a camera device 1806, a sensor 1807, a microphone 1808, an input device 1809, a display device 1810, a speaker 1811, a wireless communication interface 1812, one or more antenna switches 1815, one or more antennas 1816, a bus 1817, a battery 1818, and an auxiliary controller 1819. In one implementation, the smartphone 1800 (or the processor 1801) here may correspond to the above-described user equipment (or more specifically, the electronic device 200). The processor 1801 may be, for example, a CPU or a system on chip (SoC), and controls the functions of the application layer and other layers of the smartphone 1800. The memory 1802 includes RAM and ROM, and stores data and programs executed by the processor 1801. The storage device 1803 may include storage media such as semiconductor memories and hard disks. The external connection interface 1804 is an interface for connecting external devices (such as memory cards and universal serial bus (USB) devices) to the smartphone 1800. The imaging device 1806 includes an image sensor (such as a charge-coupled device (CCD) and a complementary metal oxide semiconductor (CMOS)), and generates a captured image. The sensor 1807 may include a set of sensors, such as a measurement sensor, a gyro sensor, a geomagnetic sensor, and an acceleration sensor. The microphone 1808 converts the sound input to the smart phone 1800 into an audio signal. The input device 1809 includes, for example, a touch sensor configured to detect a touch on the screen of the display device 1810, a keypad, a keyboard, buttons, or switches, and receives operations or information input from the user. The display device 1810 includes a screen (such as a liquid crystal display (LCD) and an organic light emitting diode (OLED) display), and displays the output image of the smart phone 1800. The speaker 1811 converts the audio signal output from the smart phone 1800 into sound. The wireless communication interface 1812 supports any cellular communication scheme (such as LTE and LTE-Advanced), and performs wireless communication. The wireless communication interface 1812 generally may include, for example, a BB processor 1813 and an RF circuit 1814. The BB processor 1813 may perform, for example, encoding / decoding, modulation / demodulation, and multiplexing / demultiplexing, and perform various types of signal processing for wireless communication. Meanwhile, the RF circuit 1814 may include, for example, mixers, filters, and amplifiers, and transmit and receive wireless signals via the antenna 1816. The wireless communication interface 1812 may be a single chip module on which the BB processor 1813 and the RF circuit 1814 are integrated. As shown in FIG. 18, the wireless communication interface 1812 may include a plurality of BB processors 1813 and a plurality of RF circuits 1814. Although FIG. 18 shows an example in which the wireless communication interface 1812 includes a plurality of BB processors 1813 and a plurality of RF circuits 1814, the wireless communication interface 1812 may also include a single BB processor 1813 or a single RF circuit 1814. In addition, in addition to the cellular communication scheme, the wireless communication interface 1812 may support other types of wireless communication schemes, such as short-range wireless communication schemes, near-field communication schemes, and wireless local area network (LAN) schemes. In this case, the wireless communication interface 1812 may include a BB processor and an RF circuit 1814 for each wireless communication scheme. Each of the antenna switches 1815 switches the connection destination of the antenna 1816 among a plurality of circuits included in the wireless communication interface 1812 (for example, circuits for different wireless communication schemes). Each of the antennas 1816 includes a single or multiple antenna elements (such as multiple antenna elements included in a MIMO antenna), and is used to transmit and receive wireless signals for the wireless communication interface 1812. As shown in FIG. 18, the smart phone 1800 may include multiple antennas 1816. Although FIG. 18 shows an example in which the smart phone 1800 includes multiple antennas 1816, the smart phone 1800 may also include a single antenna 1816. In addition, the smart phone 1800 may include an antenna 1816 for each wireless communication scheme. In this case, the antenna switch 1815 may be omitted from the configuration of the smart phone 1800. The bus 1817 connects the processor 1801, the memory 1802, the storage device 1803, the external connection interface 1804, the imaging device 1806, the sensor 1807, the microphone 1808, the input device 1809, the display device 1810, the speaker 1811, the wireless communication interface 1812, and the auxiliary controller 1819 to each other. The battery 1818 supplies power to the respective blocks of the smart phone 1800 shown in FIG. 18 via a feeder line, which is partially shown as a dashed line in the figure. The auxiliary controller 1819 operates the minimum necessary functions of the smart phone 1800, for example, in the sleep mode. In the smart phone 1800 shown in FIG. 18, a communication unit 202 such as that in FIG. 2 may be implemented by the wireless communication interface 1812; a processing unit 204 may be implemented by the processor 1801 or the auxiliary controller 1819. Second Example FIG. 19 is a block diagram showing an example of a schematic configuration of an in-vehicle navigation device 1920 to which the technology of the present disclosure can be applied. The in-vehicle navigation device 1920 includes a processor 1921, a memory 1922, a global positioning system (GPS) module 1924, a sensor 1925, a data interface 1926, a content player 1927, a storage medium interface 1928, an input device 1929, a display device 1930, a speaker 1931, a wireless communication interface 1933, one or more antenna switches 1936, one or more antennas 1937, and a battery 1938. In one implementation, the in-vehicle navigation device 1920 (or the processor 1921) here may correspond to the above-mentioned user equipment (or more specifically, the electronic device 200). The processor 1921 may be, for example, a CPU or an SoC, and controls the navigation function and other functions of the in-vehicle navigation device 1920. The memory 1922 includes a RAM and a ROM, and stores data and programs executed by the processor 1921. The GPS module 1924 uses GPS signals received from GPS satellites to measure the position of the vehicle navigation device 1920 (such as latitude, longitude, and altitude). The sensor 1925 may include a set of sensors, such as a gyro sensor, a geomagnetic sensor, and an air pressure sensor. The data interface 1926 is connected to, for example, the in-vehicle network 1941 via a terminal (not shown) and acquires data generated by the vehicle (such as vehicle speed data). The content player 1927 reproduces content stored in a storage medium (such as a CD and a DVD) inserted into the storage medium interface 1928. The input device 1929 includes, for example, a touch sensor, a button, or a switch configured to detect a touch on the screen of the display device 1930 and receives operations or information input from the user. The display device 1930 includes a screen such as an LCD or an OLED display and displays an image of the navigation function or the reproduced content. The speaker 1931 outputs the sound of the navigation function or the reproduced content. The wireless communication interface 1933 supports any cellular communication scheme (such as LTE and LTE-Advanced) and performs wireless communication. The wireless communication interface 1933 generally may include, for example, a BB processor 1934 and an RF circuit 1935. The BB processor 1934 may perform, for example, encoding / decoding, modulation / demodulation, and multiplexing / demultiplexing and perform various types of signal processing for wireless communication. At the same time, the RF circuit 1935 may include, for example, a mixer, a filter, and an amplifier and transmits and receives wireless signals via the antenna 1937. The wireless communication interface 1933 may also be a single chip module on which the BB processor 1934 and the RF circuit 1935 are integrated. As shown in FIG. 19, the wireless communication interface 1933 may include a plurality of BB processors 1934 and a plurality of RF circuits 1935. Although FIG. 19 shows an example in which the wireless communication interface 1933 includes a plurality of BB processors 1934 and a plurality of RF circuits 1935, the wireless communication interface 1933 may also include a single BB processor 1934 or a single RF circuit 1935. In addition, in addition to the cellular communication scheme, the wireless communication interface 1933 may support other types of wireless communication schemes, such as a short-range wireless communication scheme, a near-field communication scheme, and a wireless LAN scheme. In this case, for each wireless communication scheme, the wireless communication interface 1933 may include a BB processor 1934 and an RF circuit 1935. Each of the antenna switches 1936 switches the connection destination of the antenna 1937 among a plurality of circuits included in the wireless communication interface 1933 (such as circuits for different wireless communication schemes). Each of the antennas 1937 includes single or multiple antenna elements (such as multiple antenna elements included in a MIMO antenna), and is used for the wireless communication interface 1933 to transmit and receive wireless signals. As shown in FIG. 19, the car navigation device 1920 may include multiple antennas 1937. Although FIG. 19 shows an example in which the car navigation device 1920 includes multiple antennas 1937, the car navigation device 1920 may also include a single antenna 1937. In addition, the car navigation device 1920 may include an antenna 1937 for each wireless communication scheme. In this case, the antenna switch 1936 may be omitted from the configuration of the car navigation device 192O. The battery 1938 supplies power to each block of the car navigation device 1920 shown in FIG. 19 via a feeder line, which is partially shown as a dashed line in the figure. The battery 1938 accumulates the power supplied from the vehicle. In the car navigation device 1920 shown in FIG. 19, a communication unit 202 such as that in FIG. 2 may be implemented by the wireless communication interface 1933; the processing unit 204 may be implemented by the processor 1921. The technology of the present disclosure may also be implemented as an in-vehicle system (or vehicle) 1940 including one or more blocks of the car navigation device 1920, the in-vehicle network 1941, and the vehicle module 1942. The vehicle module 1942 generates vehicle data (such as vehicle speed, engine speed, and fault information), and outputs the generated data to the in-vehicle network 1941. The exemplary embodiments of the present disclosure have been described above with reference to the accompanying drawings, but the present disclosure is of course not limited to the above examples. Those skilled in the art can obtain various changes and modifications within the scope of the appended claims, and it should be understood that these changes and modifications will naturally fall within the technical scope of the present disclosure. For example, multiple functions included in one unit in the above embodiments may be implemented by separate devices. Alternatively, multiple functions implemented by multiple units in the above embodiments may be respectively implemented by separate devices. In addition, one of the above functions may be implemented by multiple units. Needless to say, such a configuration is included in the technical scope of the present disclosure. In this specification, the steps described in the flowcharts include not only the processes executed in time series in the described order, but also the processes executed in parallel or separately rather than necessarily in time series. In addition, even in the steps of time-series processing, needless to say, the order can also be appropriately changed. Although the present disclosure has been described in detail along with its advantages, it should be understood that various changes, substitutions, and alterations can be made without departing from the spirit and scope of the present disclosure as defined by the appended claims. Moreover, the term "comprising," "including," or any other variant thereof in the embodiments of the present disclosure is intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a series of elements not only includes those elements but also includes other elements not expressly listed, or further includes elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the statement "comprising one..." does not exclude the presence of additional identical elements in the process, method, article, or apparatus that includes the element.

Claims

1. An electronic device for a user equipment in a wireless communication system, the electronic device comprising at least one processor and at least one memory, the at least one memory including computer program instructions, wherein the at least one memory and the computer program instructions are configured to, via the at least one processor, cause the user equipment to perform the following operations: Train a positioning model deployed at the user equipment, wherein the input of the positioning model includes at least the auxiliary positioning data obtained by the user equipment from a positioning management function (LMF) in a core network and the strength of a positioning reference signal measured by the user equipment itself, and wherein the output of the positioning model includes at least the positioning result of the user equipment.

2. The electronic device according to claim 1, wherein the positioning result includes one of the following: an inference positioning result, and a direct positioning result.

3. The electronic device according to claim 1, wherein the auxiliary positioning data includes at least one or more of the following: a positioning application scenario, a desired positioning accuracy, an inference duration, and training data reliability.

4. The electronic device according to claim 2, the at least one memory and the computer program instructions are further configured to, via the at least one processor, cause the user equipment to perform the following operations: Before training the positioning model, receive, via an access and mobility management function (AMF) in the core network, a request message for model training from the LMF, the request message including at least the auxiliary positioning data; and After training the positioning model, send, via the AMF, a completion message of model training to the LMF, the completion message indicating the confirmation that the user equipment has completed the training of the positioning model.

5. The electronic device according to claim 4, wherein the request message further includes a request for the user equipment capabilities of the user equipment, and wherein the completion message further includes the user equipment capabilities.

6. The electronic device according to claim 5, wherein the user equipment capabilities include one or more of the following: the application scenarios of the model that the user equipment can support, the size of the model, the type of the model, the prediction latency of the model, and the prediction accuracy of the model.

7. The electronic device according to claim 4, wherein the completion message further includes the positioning result, such that the LMF generates an adjustment message for adjusting the parameters or structure of the positioning model at least based on a comparison between the positioning result and the true positioning data, the at least one memory and the computer program instructions are further configured to, via the at least one processor, cause the user equipment to perform the following operations: Receive the adjustment message from the LMF via the AMF; and Adjust the parameters or structure of the positioning model based on the adjustment message.

8. An electronic device for a core network device in a core network, the electronic device comprising at least one processor and at least one memory, the at least one memory including computer program instructions, wherein the at least one memory and the computer program instructions are configured to, via the at least one processor, cause the core network device to perform the following operations: Train a positioning model deployed at the core network device, wherein the input of the positioning model includes at least the auxiliary positioning data obtained by the core network device from a network device or a user equipment in a wireless communication system, and the auxiliary positioning data correspondingly includes at least the intensity of a channel sounding reference signal from the user equipment measured by the network device or the intensity of a positioning reference signal measured by the user equipment itself, and wherein the output of the positioning model includes at least the positioning result of the user equipment.

9. The electronic device according to claim 8, wherein the auxiliary positioning data includes at least one or more of the following: an identifier of a cell to which the user equipment is connected, a time delay of a positioning reference signal transmitted by the user equipment measured by the network device, and phase information, incident angle, Doppler frequency shift, and timestamp information of the positioning reference signal of the user equipment.

10. The electronic device according to claim 8, wherein the core network device includes a Location Management Function (LMF).

11. The electronic device according to claim 8, wherein the core network device includes a Network Data Analytics Function (NWDAF).

12. The electronic device according to claim 10, wherein the at least one memory and the computer program instructions are further configured to, via the at least one processor, cause the core network device to perform the following operations: Before training the positioning model: Send a request message for model training to a network device in a wireless communication system via an Access and Mobility Management Function (AMF) in the core network, the request message including a request for the auxiliary positioning data; and Perform one of the following: After the network device causes the user equipment to measure the intensity of the positioning reference signal in response to the request message, receive the auxiliary positioning data including the intensity of the positioning reference signal measured by the user equipment itself via the AMF from the user equipment; or After the network device measures the intensity of the channel sounding reference signal from the user equipment in response to the request message, receive the auxiliary positioning data including the intensity of the channel sounding reference signal via the AMF from the network device; After training the positioning model: Send a completion message of model training to the network device via the AMF, the completion message indicating an acknowledgement that the core network device has completed training on the positioning model.

13. The electronic device according to claim 11, wherein the at least one memory and the computer program instructions are further configured to, via the at least one processor, cause the core network device to perform the following operations: Before training the positioning model: In response to an indication from a Location Management Function (LMF) in the core network, a request message for model training is sent to a network device in the radio communication system via an Access and Mobility Management Function (AMF) in the core network, and the request message includes a request for the auxiliary positioning data; and Perform one of the following: After the network device causes the user equipment to measure the strength of a positioning reference signal in response to the request message, receive, via the AMF, the auxiliary positioning data including the strength of the positioning reference signal measured by the user equipment itself from the user equipment; or After the network device measures the strength of a channel sounding reference signal from the user equipment in response to the request message, receive, via the AMF, the auxiliary positioning data including the strength of the channel sounding reference signal from the network device; After training the positioning model: Send a completion message of model training to the network device via the AMF, and the completion message indicates the confirmation of the core network device that the training of the positioning model has been completed.

14. The electronic device according to claim 12 or 13, wherein the request message further includes a request for the user equipment capabilities of the user equipment, so that the network device also obtains the user equipment capabilities of the user equipment from the user equipment in response to the request message, and the at least one memory and the computer program instructions are further configured to cause the core network device to perform the following operations through the at least one processor: Receive the user equipment capabilities from the network device via the AMF.

15. The electronic device according to claim 14, wherein the user equipment capabilities include one or more of the following: positioning method, positioning model, accuracy of previous positioning, application scenarios of the model that the user equipment can support, size of the model, type of the model, prediction latency of the model, prediction accuracy of the model.

16. The electronic device according to claim 10, wherein the at least one memory and the computer program instructions are further configured to cause the core network device to perform the following operations through the at least one processor: Based on the LMF profile information, determine to switch from the LMF itself to another LMF in the core network for the positioning of the user equipment, wherein the LMF profile information at least includes the identifier of the LMF and the identifier or function identifier of the supported positioning model, and the identifier of the other LMF and the identifier or function identifier of the supported positioning model.

17. The electronic device according to claim 10, wherein the at least one memory and the computer program instructions are further configured to cause the core network device to perform the following operations through the at least one processor: Send information associated with the positioning model to a Network Data Analytics Function (NWDAF) in the core network, so that the NWDAF analyzes the information to obtain the positioning accuracy of the positioning model for the user equipment, wherein the information associated with the positioning model at least includes the identifier or function identifier of the positioning model.

18. The electronic device according to claim 1 or 8, wherein the training uses an artificial intelligence algorithm.

19. The electronic device according to claim 18, wherein the artificial intelligence algorithm includes one or more of the following: linear regression, logistic regression, decision tree, naive Bayes, support vector machine, random forest, artificial neural network, K-nearest neighbor.

20. An electronic device for a user equipment in a wireless communication system, the electronic device comprising at least one processor and at least one memory, the at least one memory including computer program instructions, wherein the at least one memory and the computer program instructions are configured to, via the at least one processor, cause the user equipment to perform the following operations: Send a request message for model selection of a positioning model deployed at the user equipment to a positioning management function (LMF) in the core network via an access and mobility management function (AMF) in the core network, the request message including at least the user equipment capabilities of the user equipment, such that the LMF selects one or more positioning models from a plurality of positioning models for deployment at the user equipment based at least on the request message.

21. The electronic device according to claim 20, wherein the request message further includes one or more of the following: the number of training models, and the desired positioning accuracy.

22. The electronic device according to claim 20, wherein the plurality of positioning models are stored at the LMF.

23. The electronic device according to claim 20, wherein the plurality of positioning models are stored at an analytics data repository function (ADRF) in the core network, and the ADRF is managed by a network data analytics function (NWDAF).

24. The electronic device according to claim 23, wherein the LMF sends a retrieval request for the plurality of positioning models stored at the ADRF to the NWDAF, such that the NWDAF sends a confirmation message for the retrieval request to the LMF in case it determines that the plurality of positioning models are indeed stored at the ADRF.

25. The electronic device according to claim 22 or 24, the at least one memory and the computer program instructions are further configured to, via the at least one processor, cause the user equipment to perform the following operations: After the LMF selects the one or more positioning models, receive a result message of model selection from the LMF via the AMF, the result message including the identifiers or functional identifiers of the one or more positioning models.

26. The electronic device according to claim 22, the at least one memory and the computer program instructions are further configured to, via the at least one processor, cause the user equipment to perform the following operations: After the LMF selects the one or more positioning models, download the one or more positioning models from the LMF by establishing a connection based on positioning protocol messages.

27. The electronic device according to claim 24, the at least one memory and the computer program instructions are further configured to, via the at least one processor, cause the user equipment to perform the following operations: After the one or more positioning models are selected by the LMF, the one or more positioning models are downloaded from the ADRF by establishing a connection based on positioning protocol messages.

28. The electronic device according to claim 20, wherein the user equipment capabilities include one or more of the following: the application scenarios of the models that the user equipment can support, the size of the models, the types of the models, the prediction latency of the models, and the prediction accuracy of the models.

29. The electronic device according to claim 20, wherein the at least one memory and the computer program instructions are further configured to, via the at least one processor, cause the user equipment to perform the following operations: Train a positioning model deployed at the user equipment, wherein the input of the positioning model includes at least the assisted positioning data obtained by the user equipment from the LMF and the strength of the positioning reference signal measured by the user equipment itself, and wherein the output of the positioning model includes at least the positioning result of the user equipment.

30. The electronic device according to claim 20, wherein the at least one memory and the computer program instructions are further configured to, via the at least one processor, cause the user equipment to perform the following operations: Send a request message for model switching of the positioning model deployed at the user equipment to the LMF via the AMF, the request message including at least the user equipment capabilities of the user equipment, such that the LMF selects one or more updated positioning models from the multiple positioning models for deployment at the user equipment based at least on the request message.

31. An electronic device for a user equipment in a wireless communication system, the electronic device including at least one processor and at least one memory, the at least one memory including computer program instructions, wherein the at least one memory and the computer program instructions are configured to, via the at least one processor, cause the user equipment to perform the following operations: Send a request message for model switching of the positioning model deployed at the user equipment to the positioning management function (LMF) in the core network via the access and mobility management function (AMF) in the core network, the request message including at least the user equipment capabilities of the user equipment, such that the LMF selects one or more updated positioning models from multiple positioning models for deployment at the user equipment based at least on the request message.

32. The electronic device according to claim 31, wherein the request message is triggered based on the LMF's response that the accuracy of the positioning information reported by the positioning service client for the user equipment is lower than a threshold.

33. The electronic device according to claim 31, wherein the request message further includes one or more of the following: the model previously used by the user equipment, the number of training models, and the desired positioning accuracy.

34. The electronic device according to claim 31, wherein the multiple positioning models are stored at the LMF.

35. The electronic device according to claim 31, wherein the plurality of positioning models are stored at an Analytical Data Repository Function (ADRF) in the core network, and the ADRF is managed by a Network Data Analytics Function (NWDAF).

36. The electronic device according to claim 35, wherein the LMF sends a retrieval request for the plurality of positioning models stored at the ADRF to the NWDAF, such that the NWDAF sends an acknowledgement message for the retrieval request to the LMF when determining that the plurality of positioning models are indeed stored at the ADRF.

37. The electronic device according to claim 34 or 36, wherein the at least one memory and the computer program instructions are further configured to, via the at least one processor, cause the user equipment to perform the following operations: After the LMF selects the one or more updated positioning models, receive, via the AMF from the LMF, a result message of the model switch, the result message including identifiers of the one or more updated positioning models or an updated function identifier.

38. The electronic device according to claim 34, wherein the at least one memory and the computer program instructions are further configured to, via the at least one processor, cause the user equipment to perform the following operations: After the LMF selects the one or more updated positioning models, download the one or more updated positioning models from the LMF by establishing a connection based on positioning protocol messages.

39. The electronic device according to claim 36, wherein the at least one memory and the computer program instructions are further configured to, via the at least one processor, cause the user equipment to perform the following operations: After the LMF selects the one or more positioning models, download the one or more positioning models from the ADRF indicated by the LMF by establishing a connection based on positioning protocol messages.

40. The electronic device according to claim 31, wherein the user equipment capabilities include one or more of the following: application scenarios of models that the user equipment can support, sizes of models, types of models, prediction latency of models, and prediction accuracy of models.

41. The electronic device according to claim 31, wherein the at least one memory and the computer program instructions are further configured to, via the at least one processor, cause the user equipment to perform the following operations: Train an updated positioning model deployed at the user equipment, wherein the input of the updated positioning model includes at least the assisted positioning data obtained by the user equipment from the LMF and the strength of the positioning reference signal measured by the user equipment itself, and wherein the output of the updated positioning model includes at least the positioning result of the user equipment.

42. An electronic device for a core network device in a core network, the electronic device including at least one processor and at least one memory, the at least one memory including computer program instructions, wherein the at least one memory and the computer program instructions are configured to, via the at least one processor, cause the core network device to perform the following operations: Based on the Location Management Function (LMF) profile information, it is determined to switch from the first LMF in the core network to the second LMF for the positioning of a user equipment in a wireless communication system. Wherein the LMF profile information at least includes the identifier of the first LMF and the identifier or function identifier of the supported positioning model, as well as the identifier of the second LMF and the identifier or function identifier of the supported positioning model.

43. The electronic device according to claim 42, wherein the core network device includes an Access and Mobility Management Function (AMF), the first LMF, or a Gateway Mobile Location Center (GLMC).

44. The electronic device according to claim 42, wherein the switch is triggered based on the first LMF in response to the accuracy of the positioning information reported by the positioning service client for the user equipment being lower than a threshold.

45. An electronic device for a Location Management Function (LMF) in a core network, the electronic device includes at least one processor and at least one memory, the at least one memory includes computer program instructions, wherein the at least one memory and the computer program instructions are configured to, through the at least one processor, cause the LMF to perform the following operations: Send information associated with a positioning model to a Network Data Analytics Function (NWDAF) in the core network, so that the NWDAF analyzes the information to obtain the positioning accuracy of the positioning model for a user equipment in a wireless communication system.

46. The electronic device according to claim 45, wherein the information associated with the positioning model at least includes the identifier or function identifier of the positioning model.

47. The electronic device according to claim 45, wherein the positioning model is deployed at the LMF or at the user equipment and is trained using an artificial intelligence algorithm.

48. The electronic device according to claim 45, the at least one memory and the computer program instructions are further configured to, through the at least one processor, cause the LMF to perform the following operations: Train the positioning model deployed at the LMF. Wherein the input of the positioning model at least includes the auxiliary positioning data obtained by the LMF from network devices or user equipment in a wireless communication system, and the auxiliary positioning data correspondingly at least includes the strength of the channel sounding reference signal from the user equipment measured by the network device or the strength of the positioning reference signal measured by the user equipment itself, and wherein the output of the positioning model at least includes the positioning result of the user equipment.

49. The electronic device according to claim 45, the at least one memory and the computer program instructions are further configured to, through the at least one processor, cause the LMF to perform the following operations: Based on the LMF profile information, determine to switch from the LMF itself to another LMF in the core network for the positioning of the user equipment. Wherein the LMF profile information at least includes the identifier of the LMF and the identifier or function identifier of the supported positioning model, as well as the identifier of the other LMF and the identifier or function identifier of the supported positioning model.

50. A method for a user equipment in a wireless communication system, the method comprising: Training a positioning model deployed at the user equipment, wherein the input of the positioning model at least comprises assisted positioning data obtained by the user equipment from a positioning management function (LMF) in a core network and the strength of a positioning reference signal measured by the user equipment itself, and wherein the output of the positioning model at least comprises the positioning result of the user equipment.

51. A method for a core network device in a core network, the method comprising: Training a positioning model deployed at the core network device, wherein the input of the positioning model at least comprises assisted positioning data obtained by the core network device from a network device or a user equipment in a wireless communication system, and the assisted positioning data correspondingly at least comprises the strength of a channel sounding reference signal from the user equipment measured by the network device or the strength of a positioning reference signal measured by the user equipment itself, and wherein the output of the positioning model at least comprises the positioning result of the user equipment.

52. A method for a user equipment in a wireless communication system, the method comprising: Sending, via an access and mobility management function (AMF) in a core network, a request message for model selection of a positioning model deployed at the user equipment to a positioning management function (LMF) in the core network, the request message at least comprising the user equipment capabilities of the user equipment, such that the LMF selects one or more positioning models from a plurality of positioning models for deployment at the user equipment at least based on the request message.

53. A method for a user equipment in a wireless communication system, the method comprising: Sending, via an access and mobility management function (AMF) in a core network, a request message for model switching of a positioning model deployed at the user equipment to a positioning management function (LMF) in the core network, the request message at least comprising the user equipment capabilities of the user equipment, such that the LMF selects one or more updated positioning models from a plurality of positioning models for deployment at the user equipment at least based on the request message.

54. A method for a core network device in a core network, the method comprising: Determining to switch from a first LMF in a core network to a second LMF based on LMF profile information for positioning a user equipment in a wireless communication system, wherein the LMF profile information at least comprises the identifier of the first LMF and the identifier or function identifier of the supported positioning model, and the identifier of the second LMF and the identifier or function identifier of the supported positioning model.

55. A method for a positioning management function (LMF) in a core network, the method comprising: Sending information associated with a positioning model to a network data analytics function (NWDAF) in the core network, such that the NWDAF analyzes the information to obtain the positioning accuracy of the positioning model with respect to a user equipment in a wireless communication system.

56. A computer-readable storage medium storing one or more executable instructions, the one or more executable instructions, when executed by one or more processors of an electronic device, cause the electronic device to perform the method according to any one of claims 50-55.

57. A computer program product comprising executable instructions that, when executed by one or more processors of a computer, cause the computer to perform the method according to any one of claims 50-55.

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