Information transmission method and apparatus, and storage medium

Abstract

The present disclosure relates to the technical field of communications, and provides information transmission methods and apparatus, and a storage medium. A method comprises: a network device may send first information to a terminal, wherein the first information may comprise a first identifier and / or a first area, the first identifier is an identifier related to a condition of a first element, and the first element is at least one of the following: a TRP, a TRP set, a cell, and an area. The terminal obtains the identifier related to the condition of at least one of the TRP, the TRP set, the cell, or the area, so that the identifier on a network side related to the condition is synchronized to the terminal, and thus the terminal can keep consistent with the condition on the network side by means of the first information, thereby ensuring the performance of AI / ML models or AI / ML functions.

Description

Information transmission method and device, and storage medium

[0001] The present disclosure claims priority to a Chinese patent application No. 202411094433.8, filed on August 9, 2024, with the Chinese Patent Office, and entitled “Information transmission method and device, and storage medium”, the entire content of which is incorporated herein by reference. TECHNICAL FIELD

[0002] The present disclosure relates to the field of communication technology, and more particularly, to an information transmission method and device, and storage medium. BACKGROUND

[0003] In a wireless communication system, the AI(Artificial Intelligence) / ML(Machine Learning) capability can be used, such as applying an AI / ML model to a UE(user experience) positioning scenario. In the UE positioning scenario, an AI / ML model needs to be trained first, which can be used to predict or infer the UE position and / or to determine the intermediate measurement quantity of the UE position, such as ToA(Time of Arrival). In the case where the UE has a positioning requirement, the trained AI / ML model is used.

[0004] Currently, the training data or input data of the AI / ML model can be the collected measurement quantity, which can be determined by the UE / gNB(Next generation NodeB) / TRP(Transmission-Reception Point) through measuring the DL-PRS(Downlink Positioning Reference Signal) / UL-SRS-pos(Uplink Sounding Reference Signal Position).

[0005] In order to ensure that the training phase and the inference phase can be normally executed and do not appear phenomena such as positioning accuracy decline, the measurement conditions and / or network side conditions for collecting measurement quantity in the training phase and the inference phase need to be the same, therefore, how to ensure the consistency of the measurement conditions and / or network side conditions in the training phase and the inference phase is a technical problem to be solved at present. SUMMARY

[0006] The present disclosure provides an information transmission method, device and storage medium, and solves the technical problem that it is difficult to ensure consistency of measurement conditions and / or network side conditions in a training phase and an inference phase.

[0007] In a first aspect, the present disclosure provides an information transmission method applied to a terminal, comprising:

[0008] receiving first information sent by a network device, wherein the first information comprises a first identifier and / or a first area;

[0009] The first identifier is an identifier related to a condition of a first element, and the first element comprises at least one of a transmission reception point (TRP), a TRP set, a cell, and an area, wherein the area comprises at least one cell.

[0010] In a second aspect, the present disclosure provides an information transmission method applied to a network device, comprising:

[0011] sending first information to a terminal, wherein the first information comprises a first identifier and / or a first area;

[0012] The first identifier is an identifier related to a condition of a first element, and the first element comprises at least one of a transmission reception point (TRP), a TRP set, a cell, and an area, wherein the area comprises at least one cell.

[0013] In a third aspect, the present disclosure provides an information transmission device applied to a terminal, comprising:

[0014] a receiving unit configured to receive first information sent by a network device, wherein the first information comprises a first identifier and / or a first area;

[0015] The first identifier is an identifier related to a condition of a first element, and the first element comprises at least one of a transmission reception point (TRP), a TRP set, a cell, and an area, wherein the area comprises at least one cell.

[0016] In a fourth aspect, the present disclosure provides an information transmission device applied to a network device, comprising:

[0017] a sending unit configured to send first information to a terminal, wherein the first information comprises a first identifier and / or a first area;

[0018] The first identifier is an identifier related to a condition of a first element, and the first element comprises at least one of a transmission reception point (TRP), a TRP set, a cell, and an area, wherein the area comprises at least one cell.

[0019] In a fifth aspect, an information transmission apparatus is provided, which is applied to a terminal and includes a memory, a transceiver and a processor,

[0020] The memory is configured to store a computer program; the transceiver is configured to transceive data under control of the processor; and the processor is configured to read the computer program in the memory and execute the method of the first aspect.

[0021] In a sixth aspect, an information transmission apparatus is provided, which is applied to a network device and includes a memory, a transceiver and a processor,

[0022] The memory is configured to store a computer program; the transceiver is configured to transceive data under control of the processor; and the processor is configured to read the computer program in the memory and execute the method of the second aspect.

[0023] In a seventh aspect, a non-transitory readable storage medium is provided, which stores a computer program, and the computer program is configured to make the processor execute the method of the first aspect or the method of the second aspect.

[0024] In the technical solution of the present disclosure, the network device can send first information to the terminal, and the first information can include a first identifier and / or a first area. The first identifier is an identifier related to a condition of a first element, and the first element is at least one of a TRP, a TRP set, a cell or an area. The terminal obtains an identifier related to a condition of at least one of the TRP, the TRP set, the cell or the area, thereby synchronizing the identifier related to the condition on the network side to the terminal, so that the terminal can maintain consistency with the condition on the network side through the first information, and ensure the performance of the AI / ML model or AI / ML function.

[0025] It should be understood that the content described in the foregoing summary section is not intended to define key or important features of the embodiments of the present disclosure, nor is it intended to limit the scope of the present disclosure. Other features of the present disclosure will become apparent from the following description. BRIEF DESCRIPTION OF DRAWINGS

[0026] In order to more clearly illustrate the technical solutions in the present disclosure or the related art, the following will briefly introduce the drawings needed to be used in the embodiments or the related art description. Obviously, the drawings in the following description are some embodiments of the present disclosure, and other drawings can also be obtained by those skilled in the art without any creative labor.

[0027] FIG. 1 is a schematic diagram of the architecture of a communication system provided by an embodiment of the present disclosure;

[0028] FIG. 2 is a flowchart of an information transmission method according to an embodiment of the present disclosure;

[0029] FIG. 3 is a signaling diagram of an information transmission method according to an embodiment of the present disclosure;

[0030] FIG. 4 is another flowchart of an information transmission method according to an embodiment of the present disclosure;

[0031] FIG. 5 is an example diagram of a TRP according to an embodiment of the present disclosure;

[0032] FIG. 6 is another signaling diagram of an information transmission method according to an embodiment of the present disclosure;

[0033] FIG. 7 is a structural schematic diagram of an information transmission apparatus according to an embodiment of the present disclosure;

[0034] FIG. 8 is another structural schematic diagram of an information transmission apparatus according to an embodiment of the present disclosure;

[0035] FIG. 9 is a structural schematic diagram of an information transmission apparatus according to an embodiment of the present disclosure;

[0036] FIG. 10 is another structural schematic diagram of an information transmission apparatus according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0037] In the embodiments of the present disclosure, the term “and / or” describes the association relationship of the associated objects, which means that there can be three relationships, for example, A and / or B can represent the following three cases: A exists alone, A and B exist together, and B exists alone. The character “ / ” generally represents an “or” relationship between the associated objects before and after it.

[0038] In the embodiments of the present disclosure, the term “multiple” means two or more, and other quantifiers are similar.

[0039] The technical solutions in the embodiments of the present disclosure will be described in detail below with reference to the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are only part of the embodiments of the present disclosure, not all embodiments. Based on the embodiments in the present disclosure, all other embodiments obtained by those of ordinary skill in the art without creative labor are within the scope of protection of the present disclosure.

[0040] The embodiments of the present disclosure provide a communication method, apparatus and storage medium. By synchronizing the network side condition-related identifier to the terminal, the terminal can maintain consistency with the network side condition through the first information, and ensure the accuracy and precision of the AI / ML model or AI / ML function.

[0041] The method and the device are based on the same application concept, and the implementation of the device and the method can be referred to each other because the principles of the method and the device for solving problems are similar, and the repeated parts will not be described again.

[0042] The technical solutions provided by the embodiments of the present disclosure can be applied to various systems. For example, the applicable systems can be a long term evolution (LTE) system, an LTE frequency division duplex (FDD) system, an LTE time division duplex (TDD) system, a long term evolution advanced (LTE-A) system, a universal mobile system (UMTS), a worldwide interoperability for microwave access (WiMAX) system, a 5G new radio (NR) system and its evolved communication system, a 6G (sixth generation mobile communication technology) system, and the like. The various systems can include terminal devices and network devices. The system can also include a core network part, such as an evolved packet system (EPC), a 5G core network (5GC), and the like.

[0043] The terminal device involved in the embodiments of the present disclosure can refer to a device that provides voice and / or data connectivity for a user, a handheld device with wireless connection function, or other processing devices connected to a wireless modem, etc. In different systems, the name of the terminal device can also be different, for example, in the 5G system or the 6G system, the terminal device can be called user equipment (User Equipment, UE). The wireless terminal device can be a USB storage device, other personal computer memory devices and a dongle, and can also communicate with one or more core networks (Core Network, CN) through a radio access network (Radio Access Network, RAN). The wireless terminal device can be a mobile terminal device, such as a mobile phone (or called “cellular” phone) and a computer with a mobile terminal device, for example, it can be a portable, pocket, handheld, computer built-in or vehicle-mounted mobile device, which exchanges language and / or data with the radio access network. For example, personal communication service (Personal Communication Service, PCS) phones, cordless phones, session initiation protocol (Session Initiated Protocol, SIP) phones, wireless local loop (Wireless Local Loop, WLL) stations, personal digital assistants (Personal Digital Assistant, PDA), personal computers, tablet computers, machine type communication (Machine-type Communication, MTC) terminal devices, etc. The wireless terminal device can also be called a system, a subscriber unit, a subscriber station, a mobile station, a mobile, a remote station, an access point, a remote terminal, an access terminal, a user terminal, a user agent, a user device, and a wireless access device and a router / modem that meet the limitations of the present definition, etc. The embodiments of the present disclosure are not limited.

[0044] The network device involved in the embodiments of the present disclosure can be a base station, which can include multiple cells serving terminals. According to different application scenarios, the base station can also be referred to as an access point, or can be a device in an access network that communicates with wireless terminal devices through one or more sectors over an air interface, or other names. The network device can be used to exchange received air frames with Internet Protocol (IP) packets as a router between the wireless terminal device and the rest of the access network, which can include an Internet Protocol (IP) communication network. The network device can also coordinate the management of the properties of the air interface. For example, the network device involved in the embodiments of the present disclosure can be an evolved network device (eNB or e-NodeB) in a long term evolution (LTE) system, a 5G base station (gNB) in a 5G network architecture, etc., and can also be a home evolved base station (HeNB), a relay node, a femto, a pico, a network test device, etc., which is not limited in the embodiments of the present disclosure. In some network structures, the network device can include a centralized unit (CU) node and a distributed unit (DU) node, and the centralized unit and the distributed unit can also be arranged geographically apart.

[0045] The network device and the terminal device can each use one or more antennas for multiple-input multiple-output (MIMO) transmission, which can be single-user MIMO or multi-user MIMO. According to the form and number of antenna combinations, MIMO transmission can be 2D-MIMO, 3D-MIMO, FD-MIMO or massive-MIMO, or can be diversity transmission or precoding transmission or beamforming transmission, etc.

[0046] The terminal sending related information or the like to the network side device in the embodiments of the present disclosure only indicates that the terminal sends related information in a wireless signal manner, and the intended recipient is the network device, which can obtain the related information by receiving the wireless signal.

[0047] The communication scenario of the present disclosure will be described below. FIG. 1 is a schematic diagram of the architecture of a communication system provided by the embodiments of the present disclosure. As shown in FIG. 1, a communication system 100 is provided by the embodiments of the present disclosure.

[0048] The communication system 100 includes a first network element 110, a second network element 120, and a terminal 130. The first network element 110 can be connected to the second network element 120. The second network element 120 can be connected to the terminal 130.

[0049] The first network element 110 is a network element in a core network. The second network element 120 is a network element in an access network.

[0050] For example, the first network element 110 can be a core network element, such as an LMF (Location Management Function), a UDF (User Plane Function), or the like. The second network element can be an access network element, such as a TRP (Transmission-Reception Point) or a gNB or an NG-RAN (Next Generation Radio Access Network) or the like.

[0051] In a wireless communication system, the AI (Artificial Intelligence) / ML (Machine Learning) capability can be used to improve the throughput, accuracy, reliability, and robustness, and reduce resource consumption.

[0052] The following takes the positioning scenario as an example to briefly describe the application of the AI / ML function to the communication system 100 provided by the present disclosure.

[0053] 1. When the AI / ML model is deployed in the second network element 120 and the terminal 130 as shown in FIG. 1, the second network element 120 is, for example, a base station or a TRP. In this case, the terminal or the base station or the TRP determines the measurement quantity by measuring the DL-PRS / UL-SRS-pos, and uses the measurement quantity as the input of the AI / ML model to predict or infer the position of the terminal.

[0054] 2. When the AI / ML model is deployed in the first network element 110 as shown in FIG. 1, the first network element 110 is, for example, an LMF. The terminal or the base station or the TRP determines the measurement quantity by measuring the DL-PRS / UL-SRS-pos, and sends the measurement quantity to the LMF. The LMF uses the received measurement quantity as the input of the AI / ML model to predict or infer the position of the terminal.

[0055] In the embodiments of the present disclosure, the AI / ML model or the AI / ML function can use the measurement quantity as the input data, and calculate the input data through the AI / ML model or the AI / ML function to predict the position of the terminal.

[0056] When the AI / ML model is deployed at the terminal side, there are two methods for obtaining the terminal position by the AI / ML model prediction:

[0057] 1. Direct positioning method - the AI / ML model directly shows the position of the terminal.

[0058] 2. Indirect positioning method - the AI / ML model outputs an intermediate quantity used to determine the position of the terminal.

[0059] However, whether it is the direct positioning method or the indirect positioning method, it is necessary to ensure that the conditions of the network side in the training phase of the AI / ML model and the conditions of the network side in the inference phase are consistent, so as to avoid the difference in data or measurement quantity caused by the inconsistency between the conditions of the network side in the training phase and the conditions of the network side in the inference phase, thereby reducing the processing accuracy of the AI / ML model. Therefore, how to ensure that the conditions of the network side in the training phase and the conditions of the network side in the inference phase are consistent is a technical problem to be solved at present.

[0060] In order to solve the above technical problems, in the technical scheme of the present disclosure, the network device can send first information to the terminal, and the first information can include a first identifier and / or a first area. The first identifier is an identifier related to the condition of the first element, and the first element is at least one of the following: a TRP, a TRP set, a cell, and an area. The terminal obtains an identifier related to the condition of at least one of the TRP, the TRP set, the cell, or the area, realizes synchronization of the identifier related to the condition of the network side to the terminal, so that the terminal can maintain consistency with the condition of the network side through the first information, and ensure the AI / ML model or AI / ML function.

[0061] FIG. 2 is a flowchart of an information transmission method provided by an embodiment of the present disclosure, as shown in FIG. 2, the information transmission method can include:

[0062] Step 201, receiving first information sent by a network device. The first information can include a first identifier and / or a first area. The first identifier is an identifier related to the condition of the first element. The first element includes at least one of the following: a TRP, a TRP set, a cell, and an area, and the area includes at least one cell.

[0063] In some embodiments, the condition can refer to the condition for determining the reference signal sent by the network device in the training phase or the inference phase, and the reference signal can be used to determine the measurement quantity. The condition may, for example, include at least one of the following: a DL-PRS configuration, a beam configuration of the DL-PRS, etc. In addition, the network device can be an LMF, an AI function entity, a base station, a TRP, etc.

[0064] In some embodiments, the TPR set can include at least one TRP. A cell (cell) can refer to an area within the coverage of a wireless network of a network element (such as a base station or a TRP). The area can also be referred to as a cell set, i.e., the cell set can include at least one cell.

[0065] In some embodiments, the first identifier is an identifier related to a condition of the first element. It can be understood that the first identifier is an identifier related to a condition. The condition is generally set for the first element. For example, a TRP corresponds to a condition 1, and a cell corresponds to a condition 2. In this case, the first identifier can include an identifier related to the condition 1 and an identifier related to the condition 2.

[0066] In some embodiments, the first identifier can not be an identifier of the first element itself. For example, the first element is a TRP, and the first identifier is not a TRP identifier, but the first identifier can be associated with the TRP identifier; the first element is a TRP set, and the first identifier is not a TRP set identifier, but the first identifier can be associated with the TRP set identifier; the first element is a cell, and the first identifier is not a cell identifier, but the first identifier can be associated with the cell identifier; the first element is an area, and the first identifier is not an area identifier, but the first identifier can be associated with the area identifier.

[0067] In the embodiments of the present disclosure, the terminal can receive the first information sent by the network device, and the first information can specifically include the first identifier and / or the first area. The first identifier is an identifier related to a condition of the first element, and the first element is at least one of a TRP, a TRP set, a cell, and an area. The terminal obtains an identifier related to a condition in at least one of the TRP, the TRP set, the cell, or the area, thereby synchronizing the identifier related to the condition on the network side to the terminal, so that the terminal can learn the condition on the network side through the first information, and then the terminal can confirm the consistency of the condition on the network side in the training stage and the condition on the network side in the inference stage of the AI / ML model or AI / ML function, thereby ensuring the performance of the AI / ML model or AI / ML function.

[0068] FIG. 3 is a signaling diagram of an information transmission method provided by an embodiment of the present disclosure. The information transmission method can include the following steps:

[0069] Step 301, the network device sends first information to the terminal. Correspondingly, the terminal can receive the first information sent by the network device. The first information can include a first identifier and / or a first area. The first identifier is an identifier related to a condition of a first element. The first element includes at least one of a TRP, a TRP set, a cell, and an area, and the area includes at least one cell.

[0070] In some embodiments, the network device sending the first information to the terminal can refer to the network device sending first signaling to the terminal, the first signaling carrying the first information. The first signaling may, for example, be downlink control information (DCI), MAC-CE (Media Access Control Control Element) signaling, or custom signaling. In addition, the network device can be an LMF, an AI function entity, a base station, a TRP, or the like.

[0071] In some embodiments, the terminal can receive the first signaling sent by the network device and obtain the first information from the first signaling.

[0072] In some embodiments, the network device sending the first information to the terminal can refer to sending the first information to the terminal as auxiliary information.

[0073] In some embodiments, the first identifier can be an identifier associated with the condition. The first identifier can be related to the condition of the first element. Specifically, the network device can first determine the condition of the first element, and then set the identifier for the condition of the first element to obtain the first identifier.

[0074] In some embodiments, before performing step 301, the network device can also determine the first information. Specifically, the network device can determine the first information according to the first identifier associated with the condition and / or the first area.

[0075] In some embodiments, the first area can be an effective area when the network device collects the measurement quantity, such as an effective area of a reference signal configuration or an effective area of a reference signal measurement. The first area can be obtained by configuration. Specifically, the first signaling can set a first field and / or a second field. The first field can be used to carry the first information, and the second field can carry the first area.

[0076] As an optional implementation, after step 301, the information transmission method provided by the embodiments of the present disclosure further includes:

[0077] Step 302, the terminal sends second information to the network device. Accordingly, the network device can receive the second information sent by the terminal. The second information can include identifier-related information and / or area-related information.

[0078] The identifier-related information can refer to information that the terminal needs to feed back to the network device based on the first identifier after receiving the first identifier. The area-related information can refer to information that the terminal needs to feed back to the network device based on the first area after receiving the first area.

[0079] In some embodiments, step 302 can include that the terminal sends second signaling to the network device, and the second signaling can carry the second information.

[0080] In some embodiments, the identity-related information can be information associated with an identity of a condition required by the terminal. The area-related information can be information associated with an effective area required by the terminal.

[0081] In the embodiments of the present disclosure, the network device can send first information to the terminal, and the first information can include a first identity and / or a first area. The terminal obtains an identity related to a condition in at least one of a TRP, a TRP set, a cell, or an area, so as to synchronize the network side identity related to the condition to the terminal, so that the terminal can maintain consistency with the network side condition through the first information, and ensure the performance of the AI / ML model or AI / ML function. The terminal sends second information to the network device, so that the needs of the terminal can be known by the network device in time, and then the network device can quickly respond, improve the processing security, and ensure the use precision and accuracy of the AI / ML model or AI / ML function.

[0082] FIG. 4 is another flowchart of an information transmission method provided by the embodiments of the present disclosure, which can include the following steps:

[0083] Step 401, the terminal can receive first information sent by the network device. The first information can include a first identity, for example. The first identity is an identity related to a condition of a first element. The first element includes at least one of a TRP, a TRP set, a cell, an area, and the area includes at least one cell.

[0084] In some embodiments, the network device, such as an LMF, an AI function entity, a base station, or a TRP, sends the first information to the terminal.

[0085] In some embodiments, the first identity satisfies at least one of the following conditions of the first element:

[0086] The first identity is an identity related to a condition of a TRP;

[0087] The first identity is an identity related to a condition of a TRP set;

[0088] The first identity is an identity related to a condition of a cell;

[0089] The first identity is an identity related to a condition of an area.

[0090] In some embodiments, in the case that the first identity is an identity related to a condition of a TRP, the first identity can be set at the level of the TPR. Specifically, the condition of one TRP can be associated with one first identity. The condition of the TRP can refer to the condition of a single TRP device.

[0091] In some embodiments, in the case that the first identifier is a condition-related identifier of a TRP set, the first identifier can be set at the level of the TRP set. Specifically, the condition of one TRP set can be associated with one first identifier.

[0092] In some embodiments, the condition of a TRP set can refer to the conditions of one or more TRPs included in the TRP set, and instead of separately identifying the conditions of each TRP, the conditions of the one or more TRPs included in the TRP set are jointly identified, and the terminal only needs to know the identifier of the condition of the TRP set, without needing to know the identifier of the condition of each TRP in the TRP set.

[0093] In some embodiments, in the case that the first identifier is a condition-related identifier of a cell, the first identifier can be set at the level of the cell. Specifically, the condition of one cell can be associated with one first identifier.

[0094] In some embodiments, the condition of a cell can refer to the condition of a single cell.

[0095] In some embodiments, in the case that the first identifier is a condition-related identifier of a region, the first identifier can be set at the level of the region. Specifically, the condition of one region can be associated with one first identifier.

[0096] In some embodiments, the condition of a region can refer to the conditions of one or more cells included in the region, and instead of separately identifying the conditions of each cell, the conditions of the one or more cells included in the region are jointly identified, and the terminal only needs to know the identifier of the condition of the region, without needing to know the identifier of the condition of each cell in the region.

[0097] It can be understood that according to different hierarchical manners such as TRP, TRP set, cell, and region, the network side conditions can be more conveniently managed, and in turn, a variety of scenarios can be applied in subsequent consistency judgment, and the accuracy of the consistency judgment can be improved.

[0098] In some embodiments, in the case that the first identifier is related to the condition of a TRP set, the first information further includes set information of the TRP set; wherein the set information of the TRP set includes a TRP set identifier, and / or an identifier of at least one TRP in the TRP set.

[0099] It can be understood that sending the set information of the TRP set to the terminal through the first information can enable the terminal to determine the TRPs included in the TRP set according to the set information of the TRP set, facilitate the terminal to master the network side conditions, and improve the security and accuracy of the AI / ML.

[0100] Step 402, the terminal determines whether the first condition is met, if yes, step 403 is performed, if not, step 404 is performed.

[0101] In some embodiments, the first condition can refer to a condition in which the network device can normally use the AI / ML model or the AI / ML function.

[0102] In some embodiments, the first condition includes at least one of the following:

[0103] The first identifier is different from the second identifier.

[0104] The second indication information is received, and the second indication information indicates that the identifier-related information is reported.

[0105] In some embodiments, the second indication information is carried in the positioning request sent by the LMF. Accordingly, the terminal can receive the positioning request.

[0106] In some embodiments, a certain field in the positioning request can be set to carry the second indication information. That is, the network device sends the positioning request to the terminal, and the positioning request can carry the second indication information. For example, a certain field in the positioning request can be set to carry the second indication information. For example, assuming that the field is 1 bit, if the field takes the value 1, it can be determined that the second indication information is received. If the field takes the value 0, it can be determined that the second indication information is not received.

[0107] In some embodiments, the terminal can send the second information when it is determined that the first identifier is different from the second identifier. And / or, the terminal can send the second information when it is determined that the second indication information is received.

[0108] In some embodiments, the terminal can receive the second indication information after or before receiving the first information. The second indication information can be carried in the third signaling. The third signaling may, for example, be DCI signaling or MAC CE signaling or custom signaling, and the embodiments do not limit the type of signaling too much.

[0109] In some embodiments, the terminal can obtain the second indication information from the third signaling.

[0110] Step 403, the terminal sends the second information to the network device, for example, the LMF. The second information may, for example, include identifier-related information.

[0111] In some embodiments, the identifier-related information includes at least one of the following:

[0112] The second identifier, wherein the second identifier is an identifier related to the condition of the first element;

[0113] The first indication information indicates that the first identifier is different from the second identifier.

[0114] The fallback request is used to request the network device to fallback to a first positioning function. The first positioning function is a positioning function other than a function of positioning based on an AI / ML model or an AI / ML function, for example, a traditional positioning function.

[0115] The AI / ML model or the AI / ML function supported by the terminal.

[0116] The failed AI / ML model or the AI / ML function.

[0117] The valid AI / ML model or the AI / ML function.

[0118] In some embodiments, the AI / ML model can refer to an AI model or an ML model. The AI / ML function can refer to an AI function or an ML function.

[0119] In some embodiments, the second identifier can be an identifier related to a condition of the first element. If the second identifier is the same as the first identifier, the condition associated with the second identifier is the same as the condition associated with the first identifier. If the second identifier is different from the first identifier, the condition associated with the second identifier is different from the condition associated with the first identifier.

[0120] In some embodiments, the network device can obtain the first indication information and determine that the first identifier is different from the second identifier under the indication of the first indication information. Therefore, the network device can determine that the condition corresponding to the first identifier is inconsistent with the condition corresponding to the second identifier, and there is still a problem of inconsistent conditions.

[0121] In some embodiments, the terminal device sends a fallback request to the network device. Accordingly, the network device receives the fallback request and responds. After receiving the response of the network device, the terminal can fallback to the first positioning function. The first positioning function is a positioning function other than a function of positioning based on an AI / ML model or an AI / ML function.

[0122] In some embodiments, the terminal can also provide the network device with the AI / ML model or the AI / ML function supported by the terminal, the failed AI / ML model or the AI / ML function, and / or the valid AI / ML model or the AI / ML function.

[0123] For example, the identification-related information can carry function information of the AI / ML model or the AI / ML function supported by the terminal, function information of the failed AI / ML model or the AI / ML function, and / or function information of the valid AI / ML model or the AI / ML function.

[0124] After the network device receives the function information of the AI / ML model or AI / ML function supported by the terminal, the function information of the failed AI / ML model or AI / ML function, or the function information of the effective AI / ML model or AI / ML function, the network device can determine the AI / ML model or AI / ML function supported by the terminal, the failed AI / ML model or AI / ML function, and / or the effective AI / ML model or AI / ML function according to the function information of the AI / ML model or AI / ML function supported by the terminal, the function information of the failed AI / ML model or AI / ML function, or the function information of the effective AI / ML model or AI / ML function.

[0125] In some embodiments, the network device can send the first information to the terminal again according to the AI / ML model or AI / ML function supported by the terminal, the failed AI / ML model or AI / ML function, and / or the effective AI / ML model or AI / ML function.

[0126] For example, after determining the AI / ML model or AI / ML function supported by the terminal and the failed AI / ML model or AI / ML function, the network device can exclude the failed AI / ML model or AI / ML function from the AI / ML model or AI / ML function supported by the terminal, and then determine the target AI / ML model or AI / ML function from the remaining AI / ML model or AI / ML function. Finally, the first element corresponding to the measurement quantity of the target AI / ML model or AI / ML function is confirmed. Then, a new condition of the first element corresponding to the measurement quantity is determined. The identification of the new condition of the first element is carried in the first information as the first identification.

[0127] In some embodiments, the second identification is any one of:

[0128] the identification related to the condition of the first element corresponding to the AI / ML model or AI / ML function of the terminal;

[0129] the identification related to the condition of the first element expected by the terminal.

[0130] It can be understood that the specific acquisition steps of the first element condition-related identifier corresponding to the AI / ML model or AI / ML function of the terminal can include: determining a measurement quantity corresponding to the AI / ML model or AI / ML function of the terminal, and the measurement quantity is obtained by measuring the DL-PRS respectively transmitted by the at least one TRP, so that the condition of the first element in which the at least one TRP obtaining the measurement quantity is acquired, thereby determining the identifier associated with the condition of the first element in which the at least one TRP obtaining the measurement quantity as the first element condition-related identifier corresponding to the AI / ML model or AI / ML function of the terminal.

[0131] It can be understood that the first element condition-related identifier expected by the terminal can mean that the condition of the first element is known when the first element known by the terminal is known, and therefore the terminal sends the known first element condition-related identifier to the network device.

[0132] In some embodiments, the second identifier satisfies at least one of the following conditions of the first element:

[0133] The second identifier is a TRP condition-related identifier;

[0134] The second identifier is a TRP set condition-related identifier;

[0135] The second identifier is a cell condition-related identifier;

[0136] The second identifier is a region condition-related identifier.

[0137] In some embodiments, in the case where the second identifier is a TRP condition-related identifier, the second identifier can be set at the level of the TPR. Specifically, the condition of one TRP can be associated with one second identifier. The condition of the TRP can refer to the condition of a single TRP device.

[0138] In some embodiments, in the case where the second identifier is a TRP set condition-related identifier, the second identifier can be set at the level of the TRP set. Specifically, the condition of one TRP set can be associated with one second identifier.

[0139] In some embodiments, the condition of the TRP set can mean that the conditions of one or more TRPs included in the TRP set do not individually identify the conditions of each TRP, but jointly identify the conditions of one or more TRPs included in the TRP set. The terminal only needs to recognize the identifier of the condition of the TRP set, and does not need to know the identifier of the condition of each TRP in the TRP set.

[0140] In some embodiments, when the second identity is a condition-related identity of a cell, the second identity can be set at the level of the cell. Specifically, the condition of one cell can be associated with one second identity.

[0141] In some embodiments, the condition of a cell can refer to the condition of a single cell.

[0142] In some embodiments, when the second identity is a condition-related identity of a region, the second identity can be set at the level of the region. Specifically, the condition of one region can be associated with one second identity.

[0143] In some embodiments, the condition of a region can refer to the condition of one or more cells included in the region, which does not separately identify the condition of each cell, but jointly identifies the condition of the one or more cells included in the region. The terminal only needs to recognize the identity of the condition of the region, and does not need to know the identity of the condition of each cell in the region.

[0144] It can be understood that, according to different hierarchical manners such as TRP, TRP set, cell, region, etc., the TRP can be more conveniently managed, and then a plurality of scenarios can be applied in subsequent consistency judgment, and the accuracy of the consistency judgment can be improved.

[0145] Step 404: The terminal performs positioning processing through an AI / ML model or an AI / ML function.

[0146] In some embodiments, step 404 can include: obtaining a measurement quantity corresponding to the first element, inputting the measurement quantity into the AI / ML model or the AI / ML function, and obtaining a positioning result of the terminal. The AI / ML model or the AI / ML function can be an AI / ML model or an AI / ML function of the terminal.

[0147] In some embodiments, the measurement quantity corresponding to the first element can refer to at least one of: a measurement quantity obtained by the terminal by measuring the DL-PRS transmitted by the TRP in the first element; a measurement quantity obtained by the terminal by measuring the DL-PRS transmitted by the TRP in the TRP set of the first element; and a measurement quantity obtained by the terminal by measuring the DL-PRS transmitted by the TRP in the region of the first element.

[0148] In some embodiments, the measurement quantity corresponding to the first element can include that the terminal detects the DL-PRS transmitted by at least one TRP to obtain a plurality of measurement quantities. The at least one TRP can be at least one of the TRP in the first element, the TRP set, the cell, or the region.

[0149] In particular, the at least one TRP can be one or more of the TRPs in the first element, or one or more of the TRPs in the TRP set, or one or more of the TRPs in the cell, or one or more of the TRPs in the area.

[0150] In the embodiments of the present disclosure, after the network device sends the first information to the terminal, the terminal can determine whether the first condition is met. The setting of the first condition can determine whether to keep consistent with the AI / ML model or AI / ML function of the network side. In the case of meeting the first condition, it cannot keep consistent, in this case, the terminal can feed back the second information to the network device, and feed back the content related to the identifier to the network device, and complete the information synchronization in time. In the case of not meeting the first condition, it can be determined that the AI / ML model or AI / ML function can be used for positioning of the terminal, and the positioning result of the terminal is obtained. The safe and efficient positioning of the terminal is realized.

[0151] As shown in the embodiment of FIG. 4, the terminal can perform step 404 in the case of determining that the first condition is not met. The first condition not being met includes at least one of the following:

[0152] The first identifier is the same as the second identifier, and the TRP corresponding to the first identifier is the same as the TRP corresponding to the second identifier.

[0153] As described above, the input of the AI / ML model can be a measurement quantity, which can be obtained by measuring the DL-PRS by the terminal. The DL-PRS is transmitted by the TRP. Here, the TRP transmitting the DL-PRS can be one or more.

[0154] It can be understood that the first identifier is an identifier related to the condition of the first element. The second identifier can also be an identifier related to the condition of the first element. In the case of the terminal, the first identifier and the second identifier are the same, the condition associated with the first identifier is the same as the condition associated with the second identifier, and at this time the terminal can use the AI / ML model or AI / ML function corresponding to the condition. That is, the first identifier and the second identifier are the same, which can solve the consistency of the "condition" in different stages.

[0155] As an optional implementation, the terminal can measure the DL-PRS transmitted by each of the plurality of TRPs to obtain a plurality of measurement quantities, and the plurality of measurement quantities collectively constitute the measurement quantity related to the input of the AI / ML model. In order to facilitate understanding, FIG. 5 shows an example diagram of a TRP. Referring to FIG. 5, it is assumed that there are 18 TRPs numbered 0-17 in the area 501, and the terminal can detect the DL-PRS transmitted by the 18 TRPs respectively to obtain the measurement quantity corresponding to each of the 18 TRPs. The first identifier can be associated with one or more TRPs, for example.

[0156] In some embodiments, during the AI / ML model training process, the terminal can determine a plurality of TRPs corresponding to a first identifier respectively. That is, the plurality of TRPs correspond to an identifier set, and the identifier set includes the first identifiers corresponding to the plurality of TRPs respectively. During model inference, the terminal determines that the plurality of TRPs related to the model input are consistent with the plurality of TRPs in the training stage, and the identifier set corresponding to the plurality of TRPs in the inference stage is consistent with the identifier set of the plurality of TRPs in the training stage. At this time, the conditions of the network side are consistent with those of the terminal side, and the UE can use the measurement quantities corresponding to the plurality of TRPs for model inference.

[0157] It can be understood that the plurality of TRPs in the inference stage and the plurality of TRPs in the training stage can mean that the conditions of the plurality of TRPs in the inference stage and the conditions of the plurality of TRPs in the training stage are the same.

[0158] In some embodiments, during the AI / ML model training process, the terminal uses the measurement quantities corresponding to the TRP set with the same first identifier to train the AI model; during model inference, the terminal determines the TRP set of the measurement quantity related to the model input. If the TRP set in the inference stage is consistent with the TRP set in the training stage, and the first identifier of the TRP set in the inference stage is consistent with the first identifier of the TRP set in the training stage, it can be determined that the conditions in the training stage and the conditions in the inference stage are consistent, and the terminal can use the measurement quantities corresponding to the TRP set for model inference.

[0159] In some embodiments, the network device configures a cell list while configuring the DL-PRS to the terminal, and the cell list includes 1-256 cell identifiers. At this time, 1 cell in the cell list can correspond to 1 first identifier. That is, the cell list not only includes 1-256 cell identifiers, but also includes the first identifier corresponding to each cell identifier.

[0160] In some embodiments, the first identifier is at the regional level, and 1 region corresponds to 1 first identifier. The network device can configure a cell list while configuring the DL-PRS to the terminal, and the cell list includes at least one cell identifier belonging to the same region. At this time, 1 cell list as a whole corresponds to 1 first identifier.

[0161] As shown in the embodiment of FIG. 4, satisfying the first condition can include that the first identifier and the second identifier are different. In the case where the first identifier and the second identifier are not the same, the conditions associated with the first identifier and the second identifier are also different. At this time, the difference between the first identifier and the second identifier still exists the problem that the conditions in different stages are inconsistent.

[0162] The first identifier and the second identifier being different can satisfy at least one of the following:

[0163] The first identifier and the second identifier corresponding to the TRP are different.

[0164] The first identity and the second identity corresponding to the TRP set are different;

[0165] The first identity and the second identity corresponding to the cell are different;

[0166] The first identity and the second identity corresponding to the cell set are different.

[0167] In some embodiments, the first identity and the second identity are different in any of the following aspects:

[0168] The first identity and the second identity are different for M consecutive times, M being a positive integer.

[0169] The first identity and the second identity are different for N times within a first time period, N being a positive integer.

[0170] In some embodiments, taking the first element as a TRP, the first identity and the second identity being different for M consecutive times can mean that the first identity and the second identity corresponding to the TRP are different for M consecutive times. The first identity and the second identity being different for M times can mean that the first identity and the second identity of each positioning process in M consecutive positioning processes are different. Specifically, in the first positioning process, the first identity corresponding to a first TRP is received, and the second identity corresponding to the first TRP is different from the first identity. Then, in the second positioning process, the first identity corresponding to a second TRP is received, and the second identity corresponding to the second TRP is different from the first identity. In this case, the two consecutive different times can be recorded, and M is 2.

[0171] In some embodiments, the first time period can be a predefined time period or a time period negotiated by the terminal and the network device. For example, the network device can send a first time length to the terminal. The terminal receives the first time length and confirms the first time length. After confirmation, the first time length can be used to determine the first time period.

[0172] In some embodiments, the first identity and the second identity being different for N times within the first time period can mean that the first identity and the second identity corresponding to the TRP are different for N times in each positioning process within the first time period. It can be understood that the N times of positioning within the first time period can be consecutive or non-consecutive.

[0173] In some embodiments, the first identity and the second identity being different for N times within the first time period can mean that the first identity and the second identity corresponding to the TRP set are different for N times within the first time period.

[0174] Based on the difference of the first element, the difference of the first identity and the second identity can be divided into the following cases:

[0175] Case 1, the first element includes P TRPs (the input of the AI / ML model or AI / ML function of the terminal corresponds to the measurement quantity of the P TRPs), the first identifier and the second identifier are different, and any one of the following conditions is met:

[0176] The first identifier and the second identifier corresponding to the P TRPs are different;

[0177] The first identifier and the second identifier corresponding to at least one of the P TRPs are different;

[0178] The first identifier and the second identifier corresponding to Q TRPs of the P TRPs are different, and Q is greater than or equal to a first quantity threshold, or the ratio of Q to P is greater than or equal to a first ratio threshold;

[0179] P is a positive integer, and Q is a positive integer.

[0180] In some embodiments, the first identifier and the second identifier corresponding to the P TRPs are different can include that the first identifier corresponding to the P TRPs indicated by the first information is different from the second identifier corresponding to the P TRPs expected by the AI / ML model or AI / ML function of the terminal.

[0181] In some embodiments, the first identifier and the second identifier corresponding to the P TRPs are different can include that the first identifier corresponding to the TRP set in which the P TRPs are located is different from the second identifier.

[0182] In some embodiments, the first identifier and the second identifier corresponding to the P TRPs are different can include that the first identifier of the P TRPs included in the inference data of the AI model is different from the second identifier of the P TRPs included in the training data.

[0183] In some embodiments, the first identifier and the second identifier corresponding to Q TRPs of the P TRPs are different can include that the number of the first identifier of the P TRPs included in the inference data of the AI model and the second identifier of the P TRPs included in the training data is Q. Q is greater than or equal to a first quantity threshold, or the ratio of Q to P is greater than or equal to a first ratio threshold.

[0184] Case 2, the first identifier includes P' cells (the input of the AI / ML model or AI / ML function of the terminal corresponds to the measurement quantity of the P' TRPs), the first identifier and the second identifier are different, and any one of the following conditions is met:

[0185] The first identifier and the second identifier corresponding to the P' cells are different;

[0186] The first identifier and the second identifier corresponding to at least one of the P' cells are different;

[0187] The first identifier and the second identifier corresponding to Q' of the P' cells are different, and Q' is greater than or equal to a second quantity threshold, or a ratio of Q' to P' is greater than or equal to a second ratio threshold;

[0188] P' is a positive integer, and Q' is a positive integer.

[0189] In some embodiments, the conditions of the P' cells are respectively associated with the first identifier on the network side. The conditions of the P' cells are respectively associated with the second identifier on the terminal side.

[0190] The first identifier and the second identifier corresponding to the P' cells can mean that the first identifier and the second identifier associated with the conditions of each cell of the P' cells are different.

[0191] In some embodiments, the first identifier and the second identifier corresponding to at least one cell of the P' cells can mean that, assuming that the at least one cell all use cell #1, the first identifier and the second identifier corresponding to each cell #1 are different.

[0192] In some embodiments, the first identifier and the second identifier corresponding to Q' of the P' cells can mean that there are Q' cells in the P' cells, and the first identifier and the second identifier corresponding to each cell #2 are different.

[0193] Case 3, the first element includes P'' regions (the input of the AI / ML model or AI / ML function of the terminal corresponds to the measurement quantity of the P'' TRPs), and the first identifier and the second identifier are different, satisfying any one of the following:

[0194] The first identifier and the second identifier corresponding to the P'' regions are different.

[0195] The first identifier and the second identifier corresponding to at least one region of the P'' regions are different.

[0196] The first identifier and the second identifier corresponding to Q'' of the P'' regions are different, and Q'' is greater than or equal to a third quantity threshold, or a ratio of Q'' to P'' is greater than or equal to a third ratio threshold.

[0197] P'' is a positive integer, and Q'' is a positive integer.

[0198] In some embodiments, the first identifier and the second identifier corresponding to the P'' regions can mean that the first identifier corresponding to the P'' regions sent by the network device is different from the second identifier corresponding to the P'' regions of the AI / ML model or AI / ML function of the terminal device.

[0199] In case 4, the first element includes P''' sets of TPRs (the input of the AI / ML model or AI / ML function of the terminal corresponds to the measurement quantity of P''' TRPs), the first identifier and the second identifier are different, and any one of the following conditions is satisfied:

[0200] The first identifier and the second identifier corresponding to the P''' sets of TPRs are different.

[0201] The first identifier and the second identifier corresponding to at least one of the P''' sets of TPRs are different.

[0202] The first identifier and the second identifier corresponding to Q''' of the P''' sets of TPRs are different, and Q''' is greater than or equal to a fourth quantity threshold or the ratio of Q''' to P''' is greater than or equal to a fourth ratio threshold.

[0203] P''' is a positive integer, and Q''' is a positive integer.

[0204] In some embodiments, the first identifier and the second identifier corresponding to the P''' sets of TPRs can mean that the first identifier corresponding to the P''' sets of TPRs sent by the network device is different from the second identifier corresponding to the P''' sets of TPRs of the AI / ML model or AI / ML function of the terminal device.

[0205] It should be noted that the cases 1-4 involve several parameters, such as at least one of the following: M, N, P, Q, P', Q', P'', Q'', P''', Q''', a first quantity threshold, a first ratio threshold, a second quantity threshold, a second ratio threshold, a third quantity threshold, a third ratio threshold, a fourth quantity threshold, or a fourth ratio threshold. The specific values of the parameters can be pre-agreed values in a protocol or values configured by the network device for the terminal device.

[0206] In some embodiments, the network device can issue a DCI or other instructions or information to complete the configuration of the above-mentioned parameters through the instructions or information. The above-mentioned parameters can be configured at one time or in multiple times. For example, the network device can issue a first configuration signaling to configure M and N, and then issue a second configuration signaling to configure P, Q, a first quantity threshold, and a first ratio threshold. Then, a third configuration signaling is issued to configure P', Q', a second quantity threshold, and a second ratio threshold.

[0207] In the embodiments of the present disclosure, the same or different of the first identifier and the second identifier is described in detail, so that the terminal can quickly complete the consistency identification of different stages according to the first identifier and the second identifier. The efficiency and accuracy of the consistency identification are effectively improved. In addition, the transmission of the first identifier can avoid the direct transmission of the "condition" and can avoid the direct leakage of information in the communication process, thereby improving the communication security.

[0208] FIG. 6 is another signaling diagram of an information transmission method provided by an embodiment of the present disclosure, which can include the following steps:

[0209] S601, a network device, such as an LMF, sends first information to a terminal. Accordingly, the terminal can receive the first information. The first information may, for example, include a first area.

[0210] In some embodiments, the first area includes at least one of the following:

[0211] a validity area of a reference signal configuration;

[0212] a validity area of a reference signal measurement;

[0213] a validity area corresponding to an AI / ML model or AI / ML function of the network device.

[0214] In some embodiments, the network device can send a reference signal, such as a DL-PRS, to the terminal. The reference signal can include configuration information of the validity area. For example, the reference signal can carry an area identifier. The area identifier is, for example, an area tracking code or the like. The present embodiment does not limit how to divide the area and define the area identifier.

[0215] In some embodiments, the validity area of the reference signal configuration can refer to a validity area directly defined by the reference signal.

[0216] In some embodiments, the validity area can refer to an area in which assistance data is available. The assistance data may, for example, be NR-DL-TDOA-ProvideAssistanceData.

[0217] In some embodiments, the validity area of the reference signal measurement can refer to a signal coverage area in which the terminal can measure the reference signal after the reference signal is sent. For example, after the reference signal is sent by a TRP, a terminal within 100 meters can measure the reference signal. Therefore, the validity area of the reference signal measurement can refer to a signal coverage area formed by a circle with the TRP sending the reference signal as the center and 100 meters as the radius.

[0218] In some embodiments, the validity area corresponding to the AI / ML model or AI / ML function can be obtained by the following steps: determining a measurement quantity corresponding to the AI / ML model or AI / ML function, obtaining a TRP corresponding to the measurement quantity, and determining the validity area according to the TRP corresponding to each measurement quantity.

[0219] In some embodiments, the effective area corresponding to the AI / ML model or AI / ML function of the network device includes at least one of the following: a TRP, a TRP set, a cell, or an area.

[0220] In some embodiments, the AI / ML model or AI / ML function of the network device can correspond to a measurement quantity, and the TRP corresponding to the measurement quantity can be used to determine at least one of the following: a TRP, a TRP set, a cell, or an area.

[0221] Specifically, the effective area corresponding to the AI / ML model or AI / ML function of the network device can include at least one of the following: an area corresponding to a TRP, an area corresponding to a TRP set, an area corresponding to a cell, or an area corresponding to at least one cell in the area.

[0222] It can be understood that the area corresponding to a TRP can refer to the radiation range of the signal transmitted by the TRP, that is, the range in which the signal can be detected. Alternatively, the area corresponding to a TRP can also refer to the radiation range formed by one or more TRPs. Alternatively, the area corresponding to a TRP set can refer to the radiation range formed by one or more TRPs of the TRP set. The area corresponding to a cell can refer to the coverage range of the cell. The area can refer to the area obtained by merging the coverage ranges of at least one cell in the area.

[0223] S602, the terminal sends second information to the network device. Accordingly, the network device can receive the second information. The second information may, for example, include area-related information.

[0224] In some embodiments, the terminal sends the second information when a second condition is met.

[0225] In some embodiments, the second condition being met can include: receiving third indication information, the third indication information indicating that the first area currently configured by the network device is different from the first area maintained by the terminal device (i.e., the first area previously configured by the network device); and the first area being different from the second area. In some embodiments, the third indication information can be carried in the positioning request sent by the LMF. Accordingly, the terminal can receive the positioning request.

[0226] In some embodiments, a certain field in the positioning request can be set to carry the third indication information. That is, the network device sends a positioning request to the terminal, and the positioning request can carry the third indication information. For example, a certain field in the positioning request can be set to carry the third indication information. For example, assuming that the field is 1 bit, if the field takes the value 1, it can be determined that the third indication information is received. If the field takes the value 0, it can be determined that the third indication information is not received.

[0227] In some embodiments, the terminal can perform step 602 according to the third indication information.

[0228] In some embodiments, the first area being different from the second area can mean that the area information of the first area is different from the area information of the second area. Specifically, the terminal receiving the first area means receiving the area information of the first area, and the area information of the second area of the terminal being different from the area information of the first area means that the first area and the second area are different. The area information may, for example, be area identification, area name, and the like.

[0229] In some embodiments, the area-related information includes a third area, and the third area is any one of the following: an effective area corresponding to an AI / ML model or an AI / ML function of the terminal, and an effective area expected by the terminal.

[0230] In some embodiments, the effective area corresponding to the AI / ML model or the AI / ML function of the terminal can be determined by a measurement quantity corresponding to the AI / ML model or the AI / ML function of the terminal. Specifically, the measurement quantity corresponding to the AI / ML model or the AI / ML function of the terminal can be used to obtain a TRP corresponding to the measurement quantity, and at least one of the following can be obtained: the TRP corresponding to the measurement quantity, a TRP set in which the TRP corresponding to the measurement quantity is located, a cell in which the TRP corresponding to the measurement quantity is located, or an area in which the TRP corresponding to the measurement quantity is located, and the third area can be determined according to at least one of the following: the TRP corresponding to the measurement quantity, the TRP set in which the TRP corresponding to the measurement quantity is located, the cell in which the TRP corresponding to the measurement quantity is located, or the area in which the TRP corresponding to the measurement quantity is located.

[0231] In some embodiments, the third area includes at least one of the following: a TRP, a TRP set, a cell, or an area.

[0232] In some embodiments, the third area can include an area corresponding to a TRP. And / or, the third area can include an area corresponding to a TRP set. And / or, the third area can include an area corresponding to a cell. And / or, the third area can include an area corresponding to at least one cell.

[0233] In some embodiments, in the case where the first area is an effective area configured by a reference signal, and / or an effective area for reference signal measurement, the third area is located in the first area.

[0234] For example, the TRP, the TRP set, the cell, or the cell set corresponding to the AI / ML model or the AI / ML function of the terminal is located in an effective area configured by the network device to the terminal device.

[0235] As an optional implementation, after step 602, the information transmission method provided by the embodiments of the present disclosure further includes

[0236] Step 603, the terminal sends the first measurement quantity and / or the second area to the network device. The second area is at least one of a TRP, a TRP set, a cell or an area corresponding to the first measurement quantity, and the first measurement quantity is a measurement quantity determined based on a reference signal.

[0237] In some embodiments, the second area is an area corresponding to at least one of the TRP, the TRP set, the cell or the area corresponding to the first measurement quantity. For example, the second area can be an area corresponding to the TRP.

[0238] The TRP corresponding to the first measurement quantity belongs to a TRP configured by the network device, the TRP set corresponding to the first measurement quantity belongs to a TRP set configured by the network device, the cell corresponding to the first measurement quantity belongs to a cell configured by the network device, and the area corresponding to the first measurement quantity belongs to an area configured by the network device.

[0239] In some embodiments, the measurement quantity can include at least one of CIR (Channel Impulse Response), PDR (Power Delay Profile) and DP (Delay Profile). The CIP can refer to time information, power information and phase information related to the channel response. The PDR can include time information and power information related to the channel response. The DP can include time information related to the channel response.

[0240] In some embodiments, step 603 can include: in a case where the second area belongs to an effective area corresponding to an AI / ML model or an AI / ML function of the network device, sending the first measurement quantity and / or the second area to the network device.

[0241] In the embodiments of the present disclosure, after the network device sends the first information to the terminal, the terminal can receive the first information. The first information can include a first area. The first area can be an area configured by the network device for the terminal, so that the terminal knows the area situation of the network side. On this basis, the terminal can send second information to the network device, and the second information includes area related information, so that the network side can learn the area requirement of the terminal in time, and realize the area synchronization of the two. Thus, the phenomenon of low positioning accuracy caused by unsynchronized areas can be solved.

[0242] It should be noted that the first information in the embodiments of the present disclosure can exist in the stages of data collection, model or function inference, model or function performance monitoring, etc. of the AI / ML model or AI / ML function.

[0243] In order to facilitate understanding, the following specific examples are given to explain the scheme of the present disclosure in detail.

[0244] Example 1

[0245] Step 1: LMF determines first information, the first information includes first identification, the first identification is identification related to the condition of the first element, the first element includes at least one of the following: TRP, TRP set, cell, area. The area includes at least one cell.

[0246] For example, the first identification of the network side "condition" can also be called associated identification (associated ID), which is related to the TRP or TRP set or cell or area.

[0247] Step 2: LMF sends the first information to the terminal.

[0248] As described above, the number of TRPs can include multiple. Therefore, the relationship between the associated identification determined or sent by the LMF and multiple TRPs can be as follows:

[0249] Possibility 1: The associated identification is related to the TRP.

[0250] That is, the associated identification is related to the TRP, and one TRP corresponds to one associated identification. The TRP ID is generally represented by dl-PRS-ID, which can be extended here to one TRP-ID or one dl-PRS-ID or one PRS configuration corresponding to one associated identification.

[0251] During model training, the UE trains the AI model using the measurement quantity corresponding to multiple TRPs, and the UE side maintains the associated identification corresponding to each TRP in the multiple TRPs, and the multiple TRPs correspond to one associated identification set; During model inference, if the multiple TRPs of the measurement quantity determined by the UE as the model input are consistent with the multiple TRPs in the training stage, and the associated identification set corresponding to the multiple TRPs in the inference stage is consistent with the associated identification set of the multiple TRPs in the training stage, the network side "condition" is consistent, and the UE can use the measurement quantity corresponding to the multiple TRPs for model inference.

[0252] Possibility 2: The associated identification is related to the TRP set.

[0253] That is, the associated identification is related to the TRP set, and one TRP set corresponds to one associated identification. The LMF indicates the TRP set while configuring the associated identification to the UE, specifically, the LMF indicates the TRPs included in the TRP set, for example, the LMF indicates that the TRP set includes M dl-PRS-IDs corresponding to M TRPs. Or, the LMF indicates the associated identification while indicating the dl-PRS-ID corresponding to each TRP in the M TRPs included in the TRP set, at this time, the associated identification corresponding to each TRP in the M TRPs included in the TRP set is the same.

[0254] In the model training, the UE trains the AI model using the measurement quantity corresponding to the TRP set with the same association identifier; in the model inference, if the TRP set of the measurement quantity determined by the UE is consistent with the TRP set in the training stage, and the association identifier of the TRP set in the inference stage is consistent with the association identifier of the TRP set in the training stage, the network side "condition or additional condition" is consistent, and the UE can use the measurement quantity corresponding to the TRP set to perform model inference.

[0255] Possibility 3: The association identifier is related to the cell.

[0256] That is, the association identifier is related to the cell, and one cell corresponds to one association identifier. Among them, the LMF configures the region ID-cell list while configuring the DL-PRS for the UE, and the region ID-cell list includes 1-256 NR cell IDs. At this time, one NR cell ID in the region ID-cell list can correspond to one association identifier. That is, the region ID-cell list not only includes 1-256 NR cell IDs, but also includes the association identifier corresponding to each NR cell ID.

[0257] Possibility 4: The association identifier is related to the region (cell set).

[0258] That is, the association identifier is related to the region (cell set), and one region corresponds to one association identifier. Among them, the LMF configures the region ID-cell list while configuring the DL-PRS for the UE, and at this time, one region ID-cell list corresponds to one association identifier.

[0259] In some embodiments, after the terminal receives the first information, it can also send second information to the LMF, and the second information can specifically include information in behavior 1 and / or behavior 2.

[0260] Behavior 1: The terminal sends the association identifier (second identifier) of the network side "condition" of the AI model or the AI function, or the association identifier (second identifier) of the preferred network side "condition", or the association identifier (second identifier) of the network side "condition" corresponding to the training data or inference data of the AI model or the AI function to the LMF.

[0261] Behavior 2: The terminal does not need to report the association identifier (second identifier) corresponding to its own AI model, but determines the consistency of the association identifier according to the indication of the LMF in the training phase and the inference phase, for example, determines that the association identifier of the inference data of the AI model or AI function is different from the association identifier of the training data, and then the terminal sends the supported AI / ML model or AI / ML function or the valid AI / ML model or AI / ML function to the LMF, or sends a fallback request, and the like. This scheme does not require the terminal to send its supported association identifier, but requires the LMF to carry / indicate the association identifier in the related configuration of the data collection phase and the inference phase of the AI / ML model or AI / ML function of the terminal.

[0262] In some embodiments, the execution of behavior 1 can need to meet certain conditions, for example, the first condition in the embodiments of the present disclosure.

[0263] The first condition can include the following points:

[0264] 1. When the terminal determines that the association identifier of the inference data of the AI model or AI function sent by the LMF does not meet the association identifier of the training data, that is, the first identifier and the second identifier are different, the terminal sends the difference between the first identifier and the second identifier as a piece of information to the LMF.

[0265] 2. The above-mentioned “the association identifier of the inference data of the AI model or AI function sent by the LMF does not meet the association identifier of the training data” can be extended to M times of not meeting the association identifier of the training data within a period of time or N times of not meeting the association identifier of the training data in succession, and the terminal sends the difference between the first identifier and the second identifier as a piece of information to the LMF.

[0266] In some embodiments, the LMF can configure the values of the period of time, M, and N.

[0267] In some embodiments, the information sent by the terminal to the LMF includes: the current association identifier sent by the LMF does not meet the association identifier of the training data of the inference data of the AI model or AI function; and / or, the association identifier of the training data of the inference data of the AI model or AI function; and / or, several association identifiers (different association identifiers can correspond to different AI models or AI functions) of the “conditions or additional conditions” expected by the UE on the network side.

[0268] As described above, the association identifier can be related to a TRP or a set of TRPs or a cell or a region, and the association identifier of the inference data of the AI model or AI function not meeting the association identifier of the training data can include the following cases:

[0269] 1. The association identifier is related to a TRP

[0270] The inference data of the AI model includes the association identifiers of the plurality of TRPs, which are different from the association identifiers of the plurality of TRPs included in the training data, recorded as 1 time of not satisfying;

[0271] The inference data of the AI model includes the association identifiers of the plurality of TRPs, which are different from the association identifiers of the plurality of TRPs included in the training data, recorded as 1 time of not satisfying;

[0272] The inference data of the AI model includes the association identifiers of the plurality of TRPs, which are different from the association identifiers of the plurality of TRPs included in the training data, recorded as 1 time of not satisfying;

[0273] The first proportion threshold or the first quantity threshold can be agreed by a protocol or configured by the LMF.

[0274] 2. The association identifier is related to the TRP set

[0275] The inference data of the AI model includes the association identifiers of the TRP set, which are different from the association identifiers of the TRP set included in the training data, recorded as 1 time of not satisfying;

[0276] 3. The association identifier is related to the cell

[0277] The inference data of the AI model corresponds to the association identifiers of the plurality of cells, which are different from the association identifiers of the plurality of cells corresponding to the training data, recorded as 1 time of not satisfying;

[0278] The inference data of the AI model corresponds to the association identifiers of the plurality of cells, which are different from the association identifiers of the plurality of cells corresponding to the training data, recorded as 1 time of not satisfying, otherwise as not satisfying;

[0279] The inference data of the AI model corresponds to the association identifiers of the plurality of cells, which are different from the association identifiers of the plurality of cells corresponding to the training data, recorded as 1 time of not satisfying;

[0280] The second quantity threshold and the second proportion threshold can be agreed by a protocol or configured by the LMF.

[0281] 4. The association identifier is related to the area

[0282] The inference data of the AI model includes the association identifiers of the areas where the plurality of TRPs are located, which are different from the association identifiers of the areas where the plurality of TRPs included in the training data are located, recorded as 1 time of not satisfying.

[0283] In some embodiments, when the terminal sends the second information to the LMF, it is a dynamic report, which can be reported according to the indication of the LMF or actively reported by the terminal.

[0284] In some embodiments, the LMF sends a positioning request to the terminal, which can carry indication information indicating that the UE reports the association identifier of the AI model or AI function. The terminal can report the relevant information in behavior 1 and / or behavior 2 according to the indication information.

[0285] In some embodiments, the terminal can trigger a positioning request and carry the relevant information in behavior 1 and / or behavior 2. For example, the terminal downloads a new AI model, and the association identifier associated with the AI model may change. The UE actively tells the LMF the changed association identifier.

[0286] Example 2

[0287] Step 1: The LMF determines first information, which includes: a validity area (first area) of reference signal configuration, which can be DL-PRS;

[0288] Step 2: The LMF sends the first information to the UE.

[0289] In step 1, the validity area (first area) of reference signal configuration can be an area where assistance data (such as NR-DL-TDOA-ProvideAssistanceData) is available. The UE can determine the validity area of DL-PRS and other assistance data based on the validity area, i.e., the validity area of reference signal configuration related assistance data, which is mainly controlled by the LMF.

[0290] The LMF sends the validity area (first area) of reference signal configuration to the UE. When the UE determines that the validity area of “LMF sent” or “inference data of AI model or AI function” does not meet the validity area of training data, the UE sends the information to the LMF.

[0291] The information sent by the UE to the LMF includes: the validity area of reference signal configuration of the training data of “inference data of AI model or AI function” does not meet the validity area of reference signal configuration of the training data of “inference data of AI model or AI function” sent by the LMF (third indication information); and / or, the validity area of reference signal configuration of the training data of “inference data of AI model or AI function” (third area); and / or, several validity areas of reference signal configuration of the network side “conditions or additional conditions” expected by the UE (third area).

[0292] Dynamic reporting: report the validity area of reference signal configuration (third area) according to the indication of the LMF, or actively report the validity area of reference signal configuration (third area) by the UE.

[0293] In addition to the effective area (third area) of the reference signal configuration, the effective area (third area) of the AI model or AI function can also be included, which can be sent by the UE to the LMF. The effective area (third area) of the AI model or AI function can be, for example, when the AI model corresponds to multiple TRP measurement quantities, the effective area is all TRP combinations corresponding to the AI model or AI function, that is, the effective area (third area) of the AI model or AI function can be N effective TRP sets, that is, the effective area of the AI model is mainly related to the measurement of the UE.

[0294] In step 2, the LMF sends the effective area (first area) of the reference signal configuration to the UE, based on which the UE can determine the measurement quantity related to the AI model, and determine the effective area (third area) corresponding to the AI model or AI function, and send the effective area corresponding to the AI model or AI function to the LMF. Here, the TRP or TRP set included in the effective area (third area) corresponding to the AI model or AI function should belong to or be located in the effective area (first area) of the reference signal configuration.

[0295] When the AI model is on the LMF side, the LMF sends the effective area (first area) corresponding to the AI model or AI function to the UE, and of course, the LMF can also configure the effective area (first area) of the reference signal configuration to the UE.

[0296] When the TRP set (third area) corresponding to the measurement quantity determined by the UE does not satisfy the effective area (first area) corresponding to the AI model or AI function, the UE does not provide the measurement quantity to the LMF.

[0297] The UE provides the measurement quantity and the auxiliary information (second area corresponding to the measurement quantity) for determining the effective area corresponding to the AI model or AI function, such as TRP-ID or dl-PRS-ID, to the LMF according to the configuration of the LMF.

[0298] Based on the same technical concept, the disclosure also provides an information transmission device. The information transmission device can realize the functions of the terminal in the foregoing embodiments.

[0299] Referring to FIG. 7, FIG. 7 is a structural schematic diagram of an information transmission device provided by an embodiment of the disclosure. As shown in FIG. 7, the information transmission device can include a receiving unit 701, a processing unit 702, and a sending unit 703.

[0300] The receiving unit 701 is configured to receive first information sent by a network device, wherein the first information includes a first identifier and / or a first area.

[0301] The first identifier is an identifier related to a condition of the first element, and the first element includes at least one of the following: a transmission reception point (TRP), a TRP set, a cell, and a region including at least one cell.

[0302] In some embodiments, the first identifier is related to a condition of the first element in at least one of the following manners:

[0303] The first identifier is an identifier related to a condition of the TRP.

[0304] The first identifier is an identifier related to a condition of the TRP set.

[0305] The first identifier is an identifier related to a condition of the cell.

[0306] The first identifier is an identifier related to a condition of the region.

[0307] In some embodiments, when the first identifier is related to a condition of a TRP set, the first information further includes set information of the TRP set.

[0308] The set information of the TRP set includes a TRP set identifier and / or an identifier of at least one TRP in the TRP set.

[0309] In some embodiments, the sending unit 703 is configured to send second information to the network device, where the second information includes identifier-related information and / or region-related information.

[0310] In some embodiments, the identifier-related information includes at least one of the following:

[0311] A second identifier, which is an identifier related to a condition of the first element.

[0312] First indication information, which indicates that the first identifier is different from the second identifier.

[0313] A fallback request for requesting the network device to fallback to a first positioning function, which is a positioning function other than a positioning function based on an AI / ML model or an AI / ML function.

[0314] An AI / ML model or an AI / ML function supported by the terminal.

[0315] An invalid AI / ML model or an AI / ML function.

[0316] A valid AI / ML model or an AI / ML function.

[0317] In some embodiments, the second identity is any one of:

[0318] a condition-related identity of the first element corresponding to the AI / ML model or AI / ML function of the terminal;

[0319] a condition-related identity of the first element expected by the terminal.

[0320] In some embodiments, the second identity satisfies at least one of the following conditions of the first element:

[0321] the second identity is a condition-related identity of the TRP;

[0322] the second identity is a condition-related identity of the TRP set;

[0323] the second identity is a condition-related identity of the cell;

[0324] the second identity is a condition-related identity of the area.

[0325] In some embodiments, the second information includes the identity-related information, and the processing unit 702 is specifically further configured to perform the following operations:

[0326] in the case where the first condition is satisfied, sending the second information to the network device by the sending unit 703;

[0327] wherein the first condition is satisfied includes at least one of:

[0328] the first identity is different from the second identity;

[0329] receiving second indication information indicating that the identity-related information is reported.

[0330] In some embodiments, the first identity is different from the second identity satisfies any one of:

[0331] the first identity is different from the second identity for M consecutive times, and M is a positive integer;

[0332] the first identity is different from the second identity for N times within a first time period, and N is a positive integer.

[0333] In some embodiments, the first element includes P TRPs, and the first identity is different from the second identity satisfies any one of:

[0334] the first identity corresponding to the P TRPs is different from the second identity;

[0335] The first identity and the second identity corresponding to at least one of the P TRPs are different;

[0336] The first identity and the second identity corresponding to Q of the P TRPs are different, and the Q is greater than or equal to a first quantity threshold, or a ratio of the Q to the P is greater than or equal to a first ratio threshold;

[0337] The P is a positive integer, and the Q is a positive integer.

[0338] In some embodiments, the first identity includes P' cells, and the first identity and the second identity being different satisfies any one of the following:

[0339] The first identity and the second identity corresponding to the P' cells are different;

[0340] The first identity and the second identity corresponding to at least one of the P' cells are different;

[0341] The first identity and the second identity corresponding to Q' of the P' cells are different, and the Q' is greater than or equal to a second quantity threshold, or a ratio of the Q' to the P' is greater than or equal to a second ratio threshold;

[0342] The P' is a positive integer, and the Q' is a positive integer.

[0343] In some embodiments, the first area includes at least one of the following:

[0344] An effective area of a reference signal configuration;

[0345] An effective area of a reference signal measurement;

[0346] An effective area corresponding to an AI / ML model or an AI / ML function of the network device.

[0347] In some embodiments, the effective area corresponding to the AI / ML model or the AI / ML function of the network device includes at least one of the following: a TRP, a TRP set, a cell, or an area.

[0348] In some embodiments, the sending unit 703 is further configured to perform the following operations:

[0349] Send the first measurement quantity and / or the second area to the network device; wherein,

[0350] The second area is at least one of the following: a TRP, a TRP set, a cell, or an area corresponding to the first measurement quantity, and the first measurement quantity is a measurement quantity determined based on a reference signal.

[0351] In some embodiments, the processing unit 702 is specifically further configured to perform the following operations:

[0352] In a case where the second area belongs to a valid area corresponding to an AI / ML model or an AI / ML function of the network device, the first measurement quantity and / or the second area are sent to the network device by the sending unit 703.

[0353] In some embodiments, the area-related information includes a third area, and the third area is any one of a valid area corresponding to an AI / ML model or an AI / ML function of the terminal and a valid area expected by the terminal.

[0354] In some embodiments, the third area includes at least one of a TRP, a TRP set, a cell, or an area.

[0355] In some embodiments, in a case where the first area is a valid area configured by the reference signal and / or a valid area for reference signal measurement, the third area is located in the first area.

[0356] It should be noted that the above apparatus provided by the embodiments of the present disclosure can realize all method steps realized by the network device performing method embodiments and achieve the same technical effects. Therefore, the same parts and beneficial effects of the method embodiments will not be described in detail.

[0357] Based on the same technical concept, the embodiments of the present disclosure also provide an information transmission apparatus. The information transmission apparatus can realize the functions of the network device in the foregoing embodiments.

[0358] Referring to FIG. 8, it is a structural schematic diagram of the information transmission apparatus provided by the embodiments of the present disclosure. As shown in FIG. 8, the information transmission apparatus can include a receiving unit 801 and a sending unit 802.

[0359] The sending unit 802 is configured to send first information to a terminal, and the first information includes a first identifier and / or a first area.

[0360] The first identifier is an identifier related to a condition of a first element, and the first element includes at least one of a transmission reception point (TRP), a TRP set, a cell, an area, and the area includes at least one cell.

[0361] In some embodiments, the first identifier satisfies at least one of the following conditions of the first element:

[0362] The first identifier is an identifier related to a condition of the TRP;

[0363] The first identifier is an identifier related to a condition of the TRP set;

[0364] The first identifier is a condition-related identifier of the cell.

[0365] The first identifier is a condition-related identifier of the area.

[0366] In some embodiments, in a case where the first identifier is related to a condition of a TRP set, the first information further includes set information of the TRP set.

[0367] The set information of the TRP set includes a TRP set identifier, and / or an identifier of at least one TRP in the TRP set.

[0368] In some embodiments, the receiving unit 801 can be specifically configured to:

[0369] Receive second information sent by the terminal, the second information including identifier-related information and / or area-related information.

[0370] In some embodiments, the identifier-related information includes at least one of the following:

[0371] A second identifier, the second identifier being a condition-related identifier of the first element;

[0372] First indication information, the first indication information indicating that the first identifier is different from the second identifier;

[0373] A fallback request, the fallback request being used to request the network device to fallback to a first positioning function, the first positioning function being a positioning function other than a function of positioning based on an artificial intelligence (AI) / machine learning (ML) model or an AI / ML function;

[0374] An AI / ML model or an AI / ML function supported by the terminal;

[0375] An invalid AI / ML model or an AI / ML function;

[0376] A valid AI / ML model or an AI / ML function.

[0377] In some embodiments, the second identifier is any one of the following:

[0378] A condition-related identifier of the first element corresponding to an AI / ML model or an AI / ML function of the terminal;

[0379] A condition-related identifier of the first element expected by the terminal.

[0380] In some embodiments, the second identifier is related to a condition of the first element satisfying at least one of the following:

[0381] The second identifier is a condition-related identifier of the TRP.

[0382] The second identifier is a condition-related identifier of the TRP set.

[0383] The second identifier is a condition-related identifier of the cell.

[0384] The second identifier is a condition-related identifier of the area.

[0385] In some embodiments, the first area includes at least one of the following:

[0386] An effective area of a reference signal configuration;

[0387] An effective area of a reference signal measurement;

[0388] An effective area corresponding to an AI / ML model or AI / ML function of the network device.

[0389] In some embodiments, the effective area corresponding to the AI / ML model or AI / ML function of the network device includes at least one of the following: a TRP, a TRP set, a cell, or an area.

[0390] In some embodiments, the receiving unit 801 is further configured to perform the following operations:

[0391] Receive the first measurement quantity and / or the second area sent by the terminal; wherein,

[0392] The second area is at least one of the following: a TRP, a TRP set, a cell, or an area corresponding to the first measurement quantity, and the first measurement quantity is a measurement quantity determined based on a reference signal.

[0393] In some embodiments, the area-related information includes a third area, and the third area is any one of the following: an effective area corresponding to an AI / ML model or AI / ML function of the terminal, and an effective area expected by the terminal.

[0394] In some embodiments, the third area includes at least one of the following: a TRP, a TRP set, a cell, or an area.

[0395] In some embodiments, when the first area is an effective area of a reference signal configuration and / or an effective area of a reference signal measurement, the third area is located in the first area.

[0396] It should be noted that the above apparatus provided by the embodiments of the present disclosure can realize all the method steps achieved by the method embodiments performed by the network device, and achieve the same technical effects. Therefore, the same parts and beneficial effects of the method embodiments are not described in detail herein.

[0397] FIG. 9 is a structural schematic diagram of an information transmission apparatus provided by an embodiment of the present disclosure. As shown in FIG. 9, the apparatus includes a memory 901, a transceiver 902 and a processor 903. The information transmission apparatus is, for example, a terminal.

[0398] The memory 901 is configured to store a computer program.

[0399] The transceiver 902 is configured to receive, under control of the processor 903, first information sent by a network device, wherein the first information includes first identification and / or first area.

[0400] The first identification is identification related to a condition of a first element, and the first element includes at least one of the following: a transmission reception point (TRP), a TRP set, a cell, and an area including at least one cell.

[0401] The processor 903 is configured to read the computer program stored in the memory 901 and perform related operations.

[0402] In some embodiments, the first identification satisfies at least one of the following conditions of the first element:

[0403] The first identification is identification related to a condition of the TRP.

[0404] The first identification is identification related to a condition of the TRP set.

[0405] The first identification is identification related to a condition of the cell.

[0406] The first identification is identification related to a condition of the area.

[0407] In some embodiments, when the first identification is related to a condition of the TRP set, the first information further includes set information of the TRP set.

[0408] The set information of the TRP set includes a TRP set identification and / or an identification of at least one TRP in the TRP set.

[0409] In some embodiments, the transceiver 902 is specifically configured to:

[0410] Send second information to the network device, wherein the second information includes identification related information and / or area related information.

[0411] In some embodiments, the identity-related information comprises at least one of:

[0412] a second identity, the second identity being an identity related to a condition of the first element;

[0413] first indication information, the first indication information indicating that the first identity is different from the second identity;

[0414] a fallback request for requesting the network device to fallback to a first positioning function, the first positioning function being a positioning function other than a positioning function based on an AI / ML model or an AI / ML function;

[0415] an AI / ML model or an AI / ML function supported by the terminal;

[0416] a failed AI / ML model or an AI / ML function;

[0417] a valid AI / ML model or an AI / ML function.

[0418] In some embodiments, the second identity is any one of:

[0419] an identity related to a condition of the first element corresponding to an AI / ML model or an AI / ML function of the terminal;

[0420] an identity related to a condition of the first element expected by the terminal.

[0421] In some embodiments, the second identity satisfies at least one of the conditions of the first element:

[0422] the second identity is an identity related to a condition of the TRP;

[0423] the second identity is an identity related to a condition of the TRP set;

[0424] the second identity is an identity related to a condition of the cell;

[0425] the second identity is an identity related to a condition of the area.

[0426] In some embodiments, the second information comprises the identity-related information, and the processor 903 is specifically configured to:

[0427] in a case where a first condition is satisfied, sending, by the transceiver 902, the second information to the network device;

[0428] wherein the first condition being satisfied comprises at least one of:

[0429] The first identity is different from the second identity.

[0430] The second indication information is received, and the second indication information indicates that the identity-related information is reported.

[0431] In some embodiments, the first identity being different from the second identity satisfies any one of the following:

[0432] The first identity is different from the second identity for M consecutive times, and M is a positive integer.

[0433] The first identity is different from the second identity for N times within a first time period, and N is a positive integer.

[0434] In some embodiments, the first element includes P TRPs, and the first identity being different from the second identity satisfies any one of the following:

[0435] The first identity corresponding to the P TRPs is different from the second identity.

[0436] The first identity corresponding to at least one TRP of the P TRPs is different from the second identity.

[0437] The first identity corresponding to Q TRPs of the P TRPs is different from the second identity, and Q is greater than or equal to a first quantity threshold, or a ratio of Q to P is greater than or equal to a first ratio threshold.

[0438] P is a positive integer, and Q is a positive integer.

[0439] In some embodiments, the first identity includes P' cells, and the first identity being different from the second identity satisfies any one of the following:

[0440] The first identity corresponding to the P' cells is different from the second identity.

[0441] The first identity corresponding to at least one cell of the P' cells is different from the second identity.

[0442] The first identity corresponding to Q' cells of the P' cells is different from the second identity, and Q' is greater than or equal to a second quantity threshold, or a ratio of Q' to P' is greater than or equal to a second ratio threshold.

[0443] P' is a positive integer, and Q' is a positive integer.

[0444] In some embodiments, the first area includes at least one of the following:

[0445] An effective area of a reference signal configuration;

[0446] An effective area of a reference signal measurement;

[0447] an effective area corresponding to the AI / ML model or AI / ML function of the network device.

[0448] In some embodiments, the effective area corresponding to the AI / ML model or AI / ML function of the network device comprises at least one of: a TRP, a set of TRPs, a cell, or a zone.

[0449] In some embodiments, the transceiver 902 is specifically further configured to

[0450] send, to the network device, the first measurement quantity and / or the second area; wherein

[0451] the second area is at least one of: a TRP, a set of TRPs, a cell, or a zone corresponding to the first measurement quantity, and the first measurement quantity is a measurement quantity determined based on a reference signal.

[0452] In some embodiments, the processor 903 is specifically configured to:

[0453] in a case where the second area belongs to an effective area corresponding to the AI / ML model or AI / ML function of the network device, send, to the network device via the transceiver 902, the first measurement quantity and / or the second area.

[0454] In some embodiments, the zone-related information comprises a third area, and the third area is any one of: an effective area corresponding to an AI / ML model or AI / ML function of the terminal, and an effective area expected by the terminal.

[0455] In some embodiments, the third area comprises at least one of: a TRP, a set of TRPs, a cell, or a zone.

[0456] In some embodiments, in a case where the first area is an effective area configured for the reference signal, and / or an effective area for reference signal measurement, the third area is located in the first area.

[0457] In FIG. 9, the bus architecture can include any number of interconnected buses and bridges, specifically, various circuitry of one or more processors represented by the processor 903 and memory represented by the memory. The bus architecture can also link various other circuitry, such as peripheral devices, voltage regulators, and power management circuitry, which are well known in the art and thus, the present disclosure will not further describe them. The bus interface provides an interface. The transceiver can be a plurality of elements, i.e., including a transmitter and a receiver, providing a unit for communicating with various other devices on transmission media, including wireless channels, wired channels, optical cables, and the like. The processor 903 is responsible for managing the bus architecture and general processing, and the memory can store data used by the processor 903 in performing operations.

[0458] The processor 903 can be a central processing unit (CPU), an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or a complex programmable logic device (CPLD), and the processor 903 can also adopt a multi-core architecture.

[0459] FIG. 10 is a structural schematic diagram of an information transmission device provided by an embodiment of the present disclosure. As shown in FIG. 10, the device includes a memory 1001, a transceiver 1002, and a processor 1003. The information transmission device is, for example, a network device.

[0460] The memory 1001 is configured to store a computer program.

[0461] The transceiver 1002 is configured to send, under control of the processor 1003, first information to a terminal, where the first information includes a first identifier and / or a first area.

[0462] The first identifier is an identifier related to a condition of a first element, and the first element includes at least one of the following: a transmission reception point (TRP), a TRP set, a cell, and an area including at least one cell.

[0463] The processor 1003 is configured to read the computer program stored in the memory 1001 and perform related operations.

[0464] In some embodiments, the first identifier satisfies at least one of the following conditions of the first element:

[0465] The first identifier is an identifier related to a condition of the TRP.

[0466] The first identifier is a condition-related identifier of the TRP set.

[0467] The first identifier is a condition-related identifier of the cell.

[0468] The first identifier is a condition-related identifier of the area.

[0469] In some embodiments, in a case where the first identifier is related to a condition of a TRP set, the first information further includes set information of the TRP set.

[0470] The set information of the TRP set includes a TRP set identifier, and / or an identifier of at least one TRP in the TRP set.

[0471] In some embodiments, the transceiver 1002 is specifically further configured to:

[0472] receive second information sent by the terminal, the second information including identifier-related information and / or area-related information.

[0473] In some embodiments, the identifier-related information includes at least one of the following:

[0474] a second identifier, the second identifier being a condition-related identifier of the first element;

[0475] first indication information, the first indication information indicating that the first identifier is different from the second identifier;

[0476] a fallback request, the fallback request being used to request the network device to fallback to a first positioning function, the first positioning function being a positioning function other than a function of positioning based on an artificial intelligence (AI) / machine learning (ML) model or an AI / ML function;

[0477] an AI / ML model or an AI / ML function supported by the terminal;

[0478] an invalid AI / ML model or an AI / ML function;

[0479] a valid AI / ML model or an AI / ML function.

[0480] In some embodiments, the second identifier is any one of the following:

[0481] a condition-related identifier of the first element corresponding to an AI / ML model or an AI / ML function of the terminal;

[0482] a condition-related identifier of the first element expected by the terminal.

[0483] In some embodiments, the second identifier satisfies the condition of the first element as at least one of:

[0484] The second identifier is a condition-related identifier of the TRP.

[0485] The second identifier is a condition-related identifier of the TRP set.

[0486] The second identifier is a condition-related identifier of the cell.

[0487] The second identifier is a condition-related identifier of the area.

[0488] In some embodiments, the first area includes at least one of:

[0489] An effective area of a reference signal configuration.

[0490] An effective area of a reference signal measurement.

[0491] An effective area corresponding to an AI / ML model or AI / ML function of the network device.

[0492] In some embodiments, the effective area corresponding to the AI / ML model or AI / ML function of the network device includes at least one of: a TRP, a TRP set, a cell, or an area.

[0493] In some embodiments, the transceiver 1002 is specifically further configured to:

[0494] Receive the first measurement quantity and / or the second area sent by the terminal; wherein,

[0495] The second area is at least one of: a TRP, a TRP set, a cell, or an area corresponding to the first measurement quantity, and the first measurement quantity is a measurement quantity determined based on a reference signal.

[0496] In some embodiments, the area-related information includes a third area, and the third area is any one of: an effective area corresponding to an AI / ML model or AI / ML function of the terminal, and an effective area expected by the terminal.

[0497] In some embodiments, the third area includes at least one of: a TRP, a TRP set, a cell, or an area.

[0498] In some embodiments, when the first area is an effective area of a reference signal configuration and / or an effective area of a reference signal measurement, the third area is located in the first area.

[0499] In FIG. 10, the bus architecture can include any number of interconnected buses and bridges, which are represented by the processor 1003 and the various circuits of the memory represented by the memory 1001 linked together. The bus architecture can also link various other circuits such as peripheral devices, voltage regulators, and power management circuits, which are well known in the art, and thus, the present disclosure will not further describe them. The bus interface provides an interface. The transceiver can be a plurality of elements, i.e., including a transmitter and a receiver, providing a unit for communicating with various other devices on transmission media, including wireless channels, wired channels, optical cables, and the like. The user interface can also be an interface capable of connecting external and internal required devices for different user devices, including but not limited to a keypad, a display, a speaker, a microphone, a joystick, and the like.

[0500] The processor 1003 is responsible for managing the bus architecture and general processing, and the memory can store data used by the processor 1003 when performing operations.

[0501] In some embodiments, the processor 1003 can be a CPU (Central Processing Unit), an ASIC (Application Specific Integrated Circuit), an FPGA (Field-Programmable Gate Array), or a CPLD (Complex Programmable Logic Device), and the processor 1003 can also adopt a multi-core architecture.

[0502] The processor 1003 is used to execute any of the methods provided by the embodiments of the present disclosure according to the executable instructions obtained by calling the programs stored in the memory. The processor 1003 and the memory 1001 can also be physically arranged separately.

[0503] It should be noted that the above-described apparatus provided by the embodiments of the present disclosure can realize all the method steps realized by the above-mentioned method embodiments, and can achieve the same technical effects, and thus, the same parts and beneficial effects in the embodiments of the present disclosure will not be described in detail.

[0504] It should be noted that the division of units in the embodiments of the present disclosure is illustrative, and is only a logical functional division. Actual implementation can have another division manner. In addition, each functional unit in each embodiment of the present disclosure can be integrated in one processing unit, or each unit can exist physically, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of a software functional unit.

[0505] The integrated unit, if implemented in the form of a software function unit and sold or used as an independent product, can be stored in a processor-readable storage medium. Based on such an understanding, the technical solutions of the present disclosure, essentially or in other words, the part that contributes to the related art or the whole or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium, and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) or a processor to perform all or part of the steps of the methods described in the various embodiments of the present disclosure.

[0506] It should be noted that the above-mentioned device provided by the embodiments of the present disclosure can realize all the method steps realized by the method embodiments and achieve the same technical effects. Therefore, the same parts and beneficial effects of the method embodiments will not be described in detail.

[0507] The embodiments of the present disclosure also provide a non-transitory readable storage medium, which stores a computer program. The computer program is used to make a processor execute all the method steps of the network device in the above-mentioned method embodiments.

[0508] The embodiments of the present disclosure also provide a non-transitory readable storage medium, which stores a computer program. The computer program is used to make a processor execute all the method steps of the terminal device in the above-mentioned method embodiments.

[0509] The non-transitory readable storage medium can be any available medium or data storage device that can be accessed by a computer, including but not limited to a magnetic storage (such as a floppy disk, a hard disk, a magnetic tape, a magneto-optical disk (MO), etc.), an optical storage (such as a CD, a DVD, a BD, a HVD, etc.), and a semiconductor storage (such as a ROM, an EPROM, an EEPROM, a non-volatile memory (NAND FLASH), a solid-state disk (SSD)), etc.

[0510] The embodiments of the present disclosure also provide a computer program product, which includes a computer program. The computer program is executed by a processor to implement the method described in any one of the above-mentioned method embodiments.

[0511] Those skilled in the art should understand that the embodiments of the present disclosure can be provided as a method, a system, or a computer program product. Therefore, the present disclosure can take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present disclosure can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to a magnetic disk storage and an optical storage, etc.) containing computer-usable program code.

[0512] The present disclosure is described in reference to flowchart and / or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the present disclosure. It will be understood that each block of the flowchart and / or block diagrams, and combinations of blocks in the flowchart and / or block diagrams, can be implemented by computer executable instructions. The computer executable instructions can be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart and / or block diagram block or blocks.

[0513] These computer executable instructions can also be stored in a processor readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the processor readable memory produce an article of manufacture including instructions which implement the function specified in the flowchart and / or block diagram block or blocks.

[0514] It will be apparent to those skilled in the art that various modifications and variations can be made to the present disclosure without departing from the spirit or scope of the disclosure. Thus, it is intended that the present disclosure cover the modifications and variations of this disclosure provided they come within the scope of the appended claims and their equivalents.

Claims

1. A method of information transmission, wherein, The method applied to a terminal comprises: receiving first information sent by a network device, the first information comprising a first identifier and / or a first area; wherein the first identifier is an identifier related to a condition of a first element, the first element comprising at least one of the following: a transmission reception point (TRP), a TRP set, a cell, an area comprising at least one cell.

2. The method of claim 1, wherein, The first identifier is related to the condition of the first element in at least one of the following ways: The first identifier is a condition-related identifier of the TRP; The first identifier is a condition-related identifier of the TRP set; The first identifier is a condition-related identifier of the cell; The first identifier is a condition-related identifier of the area.

3. The method of claim 2, wherein, When the first identifier is related to the condition of the TRP set, the first information further comprises set information of the TRP set; wherein the set information of the TRP set comprises a TRP set identifier and / or an identifier of at least one TRP in the TRP set.

4. The method according to any one of claims 1 to 3, wherein, The method further comprises: sending second information to the network device, the second information comprising identifier-related information and / or area-related information.

5. The method of claim 4, wherein, The identifier-related information comprises at least one of the following: a second identifier, which is an identifier related to the condition of the first element; first indication information, which indicates that the first identifier is different from the second identifier; a fallback request for requesting the network device to fallback to a first positioning function, which is a positioning function other than a function based on an artificial intelligence (AI) / machine learning (ML) model or AI / ML function; an AI / ML model or AI / ML function supported by the terminal; an invalid AI / ML model or AI / ML function; a valid AI / ML model or AI / ML function.

6. The method of claim 5, wherein, The second identifier is any one of the following: an identifier related to the condition of the first element corresponding to an AI / ML model or AI / ML function of the terminal; an identifier related to the condition of the first element expected by the terminal.

7. The method of claim 5 or 6, wherein, The second identifier is related to the condition of the first element in at least one of the following ways: The second identifier is a condition-related identifier of the TRP; The second identifier is a condition-related identifier of the TRP set; The second identifier is a condition-related identifier of the cell; The second identifier is a condition-related identifier of the area.

8. The method of claim 4, wherein, The second information comprises the identifier-related information, and the sending of the second information to the network device comprises: sending the second information to the network device when a first condition is met; wherein the first condition comprises at least one of the following: The first identifier is different from the second identifier; receiving second indication information indicating that the identifier-related information is reported.

9. The method of claim 8, wherein, The first identifier is different from the second identifier in any one of the following ways: The first identifier is different from the second identifier for M consecutive times, M being a positive integer; The first identifier is different from the second identifier for N times within a first time period, N being a positive integer.

10. The method of claim 8 or 9, wherein, The first element includes P TRPs, and the first identity and the second identity satisfy any one of the following conditions: The first identity and the second identity of the P TRPs are different; The first identity and the second identity of at least one of the P TRPs are different; The first identity and the second identity of Q TRPs of the P TRPs are different, and the Q is greater than or equal to a first quantity threshold, or a ratio of the Q to the P is greater than or equal to a first proportion threshold; The P is a positive integer, and the Q is a positive integer.

11. The method of claim 8 or 9, wherein, The first identity includes P' cells, and the first identity and the second identity satisfy any one of the following conditions: The first identity and the second identity of the P' cells are different; The first identity and the second identity of at least one of the P' cells are different; The first identity and the second identity of Q' cells of the P' cells are different, and the Q' is greater than or equal to a second quantity threshold, or a ratio of the Q' to the P' is greater than or equal to a second proportion threshold; The P' is a positive integer, and the Q' is a positive integer.

12. The method of claim 1, wherein, The first area includes at least one of the following: An effective area of a reference signal configuration; An effective area of a reference signal measurement; An effective area corresponding to an AI / ML model or an AI / ML function of the network device.

13. The method of claim 12, wherein, The effective area corresponding to the AI / ML model or the AI / ML function of the network device includes at least one of the following: a TRP, a TRP set, a cell, or an area.

14. The method of claim 13, wherein, The method further includes: sending, to the network device, a first measurement quantity and / or a second area; wherein The second area is at least one of a TRP, a TRP set, a cell, or an area corresponding to the first measurement quantity, and the first measurement quantity is a measurement quantity determined based on a reference signal.

15. The method of claim 14, wherein, The sending, to the network device, the first measurement quantity and / or the second area includes: In a case where the second area belongs to an effective area corresponding to an AI / ML model or an AI / ML function of the network device, sending, to the network device, the first measurement quantity and / or the second area.

16. The method of claim 4, wherein, The area-related information includes a third area, and the third area is any one of the following: an effective area corresponding to an AI / ML model or an AI / ML function of the terminal, and an effective area expected by the terminal.

17. The method of claim 16, wherein, The third area includes at least one of the following: a TRP, a TRP set, a cell, or an area.

18. The method of claim 17, wherein, In a case where the first area is an effective area of a reference signal configuration and / or an effective area of a reference signal measurement, the third area is located in the first area.

19. An information transmission method, wherein, The method applied to a network device includes: sending, to a terminal, first information, the first information including a first identity and / or a first area; The first identity is a condition-related identity of a first element, and the first element includes at least one of the following: a transmission reception point (TRP), a TRP set, a cell, and an area including at least one cell.

20. The method of claim 19, wherein, The first identity and the condition of the first element satisfy at least one of the following conditions: The first identity is a condition-related identity of the TRP; The first identifier is a condition-related identifier of the TRP set; The first identifier is a condition-related identifier of the cell; The first identifier is a condition-related identifier of the area.

21. The method of claim 20, wherein, In a case where the first identifier is condition-related to a TRP set, the first information further includes set information of the TRP set; The set information of the TRP set includes a TRP set identifier, and / or an identifier of at least one TRP in the TRP set.

22. The method of any one of claims 19-21, wherein, The method further includes: receiving second information sent by the terminal, the second information including identifier-related information and / or area-related information.

23. The method of claim 22, wherein, The identifier-related information includes at least one of the following: A second identifier, the second identifier being a condition-related identifier of the first element; First indication information, the first indication information indicating that the first identifier is different from the second identifier; A fallback request for requesting the network device to fallback to a first positioning function, the first positioning function being a positioning function other than a function of positioning based on an artificial intelligence (AI) / machine learning (ML) model or an AI / ML function; An AI / ML model or an AI / ML function supported by the terminal; An invalid AI / ML model or an AI / ML function; A valid AI / ML model or an AI / ML function.

24. The method of claim 23, wherein, The second identifier is any one of the following: A condition-related identifier of the first element corresponding to an AI / ML model or an AI / ML function of the terminal; A condition-related identifier of the first element expected by the terminal.

25. The method of claim 23 or 24, wherein, The second identifier is condition-related to the first element and meets at least one of the following: The second identifier is a condition-related identifier of the TRP; The second identifier is a condition-related identifier of the TRP set; The second identifier is a condition-related identifier of the cell; The second identifier is a condition-related identifier of the area.

26. The method of claim 19, wherein, The first area includes at least one of the following: An effective area of a reference signal configuration; An effective area of reference signal measurement; An effective area corresponding to an AI / ML model or an AI / ML function of the network device.

27. The method of claim 26, wherein, The effective area corresponding to the AI / ML model or the AI / ML function of the network device includes at least one of the following: a TRP, a TRP set, a cell, or an area.

28. The method of claim 27, wherein, The method further includes: receiving a first measurement quantity and / or a second area sent by the terminal; wherein The second area is at least one of a TRP, a TRP set, a cell, or an area corresponding to the first measurement quantity, and the first measurement quantity is a measurement quantity determined based on a reference signal.

29. The method of claim 22, wherein, The area-related information includes a third area, the third area being any one of the following: an effective area corresponding to an AI / ML model or an AI / ML function of the terminal, and an effective area expected by the terminal.

30. The method of claim 29, wherein, The third area includes at least one of the following: a TRP, a TRP set, a cell, or an area.

31. The method of claim 30, wherein, In a case where the first area is an effective area of a reference signal configuration and / or an effective area of reference signal measurement, the third area is located in the first area.

32. An information transmission apparatus, wherein, The apparatus is applied to a terminal, and the apparatus includes: A receiving unit is configured to receive first information sent by a network device, wherein the first information comprises a first identifier and / or a first area. The first identifier is an identifier related to a condition of a first element, and the first element comprises at least one of a transmission reception point (TRP), a TRP set, a cell, and an area comprising at least one cell.

33. An information transmission apparatus, wherein, The apparatus is applied to a network device, and the apparatus comprises: A sending unit is configured to send first information to a terminal, wherein the first information comprises a first identifier and / or a first area. The first identifier is an identifier related to a condition of a first element, and the first element comprises at least one of a transmission reception point (TRP), a TRP set, a cell, and an area comprising at least one cell.

34. An information transmission apparatus, wherein, The apparatus is applied to a terminal, and the apparatus comprises a memory, a transceiver, and a processor, The memory is configured to store a computer program; the transceiver is configured to transceive data under control of the processor; and the processor is configured to read the computer program in the memory and perform the method in any one of claims 1-18.

35. An information transmission apparatus, wherein, The apparatus is applied to a network device, and the apparatus comprises a memory, a transceiver, and a processor, The memory is configured to store a computer program; the transceiver is configured to transceive data under control of the processor; and the processor is configured to read the computer program in the memory and perform the method in any one of claims 19-31.

36. A non-transitory readable storage medium, wherein, The non-transient readable storage medium stores a computer program, and the computer program is configured to make the processor perform the method in any one of claims 1-18; or perform the method in any one of claims 19-31.

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