Positioning method, network node, communication system, and storage medium

Abstract

The present disclosure relates to a positioning method, a network node, a communication system, and a storage medium. The positioning method comprises: receiving first information sent by a second network node, the first information being used for indicating information about measurement of a terminal by the second network node and report information about an artificial intelligence (AI) model output result; and on the basis of the information about the measurement and the AI model, obtaining a first result, the report information being used for sending the first result, and the first result being used by a third network node to position the terminal. The present disclosure improves positioning accuracy and reduces positioning errors.

Description

Positioning method, network node, communication system and storage medium Technical Field

[0001] The present disclosure relates to the field of communication technology, and in particular to a positioning method, a network node, a communication system, and a storage medium. Background Art

[0002] In recent years, artificial intelligence (AI) technology has made continuous breakthroughs in many fields, including but not limited to AI-based positioning.

[0003] There are currently multiple deployment options for AI-based positioning. For example, the AI ​​model can be deployed on the base station side, with the location management function (LMF) assisting in positioning.

[0004] Summary of the Invention

[0005] In the AI-based positioning process, positioning error is an issue that needs to be addressed urgently.

[0006] The embodiments of the present disclosure provide a positioning method, a network node, a communication system, and a storage medium.

[0007] According to a first aspect of an embodiment of the present disclosure, a positioning method is proposed, comprising: receiving first information sent by a second network node, the first information being used to indicate measurement information of the second network node on a terminal, and reporting information of an output result of an artificial intelligence (AI) model; obtaining a first result based on the measurement information and the AI ​​model; wherein the reporting information is used to send the first result, and the first result is used by a third network node to locate the terminal.

[0008] According to a second aspect of an embodiment of the present disclosure, a positioning method is proposed, comprising: sending first information to a first network node, the first information being used to indicate measurement information of the second network node on the terminal, and reporting information of an output result of an artificial intelligence (AI) model; wherein the measurement information is used by the first network node to obtain a first result based on the AI ​​model, the reporting information is used to send the first result, and the first result is used by a third network node to locate the terminal.

[0009] According to a third aspect of an embodiment of the present disclosure, a positioning method is proposed, the method including: receiving a first result, the first result being used to locate the terminal; wherein the first result is obtained based on measurement information and an AI model, the first result is sent based on reporting information of an output result of the AI ​​model, and the measurement information and the reporting information are indicated by the first information sent by the second network node to the first network node.

[0010] According to a fourth aspect of an embodiment of the present disclosure, a positioning method is proposed, which includes: a second network node sends first information to a first network node, where the first information is used to indicate measurement information of the terminal by the second network node, and reporting information of an output result of an artificial intelligence (AI) model; the first network node receives the first information sent by the second network node; the first network node obtains a first result based on the measurement information and the AI ​​model; the first network node sends the first result based on the measurement information; the third network node receives the first result; and the first result is used by the third network node to locate the terminal.

[0011] According to a fifth aspect of an embodiment of the present disclosure, a network node is proposed, including: a transceiver module for receiving first information sent by a second network node, the first information being used to indicate measurement information of the second network node on the terminal, and reporting information of an output result of an artificial intelligence (AI) model; a processing module for obtaining a first result based on the measurement information and the AI ​​model; wherein the reporting information is used to send the first result, and the first result is used by a third network node to locate the terminal.

[0012] According to a sixth aspect of an embodiment of the present disclosure, a network node is proposed, including: a transceiver module, used to send first information to a first network node, the first information being used to indicate measurement information of the second network node on the terminal, and reporting information of an output result of an artificial intelligence (AI) model; wherein the measurement information is used by the first network node to obtain a first result based on the AI ​​model, the reporting information is used to send the first result, and the first result is used by a third network node to locate the terminal.

[0013] According to a seventh aspect of an embodiment of the present disclosure, a network node is proposed, including: a transceiver module, configured to receive a first result, wherein the first result is used to locate a terminal; wherein the first result is obtained based on measurement information and an AI model, and the first result is sent based on reporting information of an output result of the AI ​​model, and the measurement information and the reporting information are sent by a second network node to a first information indication of the first network node.

[0014] According to an eighth aspect of an embodiment of the present disclosure, a network node is proposed, comprising: one or more processors; wherein the terminal is configured to execute the first aspect and any one of the positioning methods in the first aspect.

[0015] According to a ninth aspect of an embodiment of the present disclosure, a network node is proposed, comprising: one or more processors; wherein the network device is configured to execute the second aspect and any one of the positioning methods in the second aspect.

[0016] According to a tenth aspect of an embodiment of the present disclosure, a network node is proposed, comprising: one or more processors; wherein the network device is used to execute the third aspect and any one of the positioning methods in the third aspect.

[0017] According to an eleventh aspect of an embodiment of the present disclosure, a communication system is proposed, including a first network node, a second network node, and a third network node, wherein the first network node is configured to implement the first aspect and any one of the positioning methods in the first aspect, the second network node is configured to implement the second aspect and any one of the positioning methods in the second aspect, and the third network node is configured to implement the third aspect and any one of the positioning methods in the third aspect.

[0018] According to the twelfth aspect of an embodiment of the present disclosure, a storage medium is proposed, which stores instructions. When the instructions are executed on a communication device, the communication device executes a positioning method such as the first aspect and any one of the first aspect or the second aspect and the second aspect or the third aspect and any one of the third aspect.

[0019] In the present disclosure, the first network node receives the measurement information and the reporting information of the AI ​​model output result sent by the second network node. The reporting information can be used to report the AI ​​model, so that the third network node can accurately obtain the terminal's location information based on the output result of the AI ​​model, thereby improving the accuracy of positioning and reducing the positioning error. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the technical solutions in the embodiments of the present disclosure, the following drawings required for describing the embodiments are introduced. The following drawings are merely some embodiments of the present disclosure and do not impose specific limitations on the protection scope of the present disclosure.

[0021] Figure 1a is a schematic diagram of the architecture of an AI function.

[0022] FIG1 b is a schematic diagram of an AI-based positioning architecture according to an exemplary embodiment of the present disclosure.

[0023] FIG1c is a schematic diagram of an AI-based positioning architecture according to an exemplary embodiment of the present disclosure.

[0024] FIG1d is a schematic diagram of an AI-based positioning architecture according to an exemplary embodiment of the present disclosure.

[0025] FIG1e is a schematic diagram of a communication system architecture according to an embodiment of the present disclosure.

[0026] FIG2 a is a schematic diagram showing an interaction of a positioning method according to an embodiment of the present disclosure.

[0027] FIG2 b is a schematic diagram illustrating an interaction of a positioning method according to an embodiment of the present disclosure.

[0028] FIG3 a is a flow chart of a positioning method according to an embodiment of the present disclosure.

[0029] FIG3 b is a flow chart of a positioning method according to an embodiment of the present disclosure.

[0030] FIG3 c is a flow chart of a positioning method according to an embodiment of the present disclosure.

[0031] FIG4 a is a flow chart of a positioning method according to an embodiment of the present disclosure.

[0032] FIG4 b is a flow chart of a positioning method according to an embodiment of the present disclosure.

[0033] FIG4 c is a flow chart of a positioning method according to an embodiment of the present disclosure.

[0034] FIG5 a is a flow chart of a positioning method according to an embodiment of the present disclosure.

[0035] FIG5 b is a flow chart of a positioning method according to an embodiment of the present disclosure.

[0036] FIG6 is a schematic diagram showing an interaction of a positioning method according to an embodiment of the present disclosure.

[0037] FIG7 a is an interactive schematic diagram of a positioning method according to an exemplary embodiment of the present disclosure.

[0038] FIG7 b is an interactive schematic diagram of a positioning method according to an exemplary embodiment of the present disclosure.

[0039] FIG7 c is an interactive schematic diagram of a positioning method according to an exemplary embodiment of the present disclosure.

[0040] FIG8 a is a schematic structural diagram of a first network node according to an embodiment of the present disclosure.

[0041] FIG8 b is a schematic structural diagram of a second network node according to an embodiment of the present disclosure.

[0042] FIG8c is a schematic structural diagram of a second network node according to an embodiment of the present disclosure.

[0043] Fig. 9a is a schematic structural diagram of a communication device according to an exemplary embodiment.

[0044] FIG9 b is a schematic diagram showing a chip structure according to an exemplary embodiment. DETAILED DESCRIPTION

[0045] The embodiments of the present disclosure provide a positioning method, a network node, a communication system, and a storage medium.

[0046] In a first aspect, an embodiment of the present disclosure proposes a positioning method, which includes: receiving first information sent by a second network node, where the first information is used to indicate measurement information of the second network node on the terminal, and reporting information of an output result of an artificial intelligence (AI) model; obtaining a first result based on the measurement information and the AI ​​model; wherein the reporting information is used to send the first result, and the first result is used by a third network node to locate the terminal.

[0047] In the above embodiment, the first network node receives the measurement information and the reporting information of the AI ​​model output result sent by the second network node. The reporting information can be used for reporting the AI ​​model, so that the third network node can accurately obtain the terminal location information based on the output result of the AI ​​model, thereby improving the positioning accuracy and reducing the positioning error.

[0048] In some optional embodiments of the first aspect, the method further includes: sending the first result and the reporting information to the third network node; or, processing the first result to obtain a second result, and sending the second result and the reporting information to the third network node.

[0049] In the above embodiment, the first result and the reporting information, or the second result and the reporting information, can be directly sent to the third network node. Since the reporting information is sent by the second network node to the first network node, it can identify which second network node the first result or the second result comes from, or which specific TRP or measurement of the second network node it comes from, so that the third network node can perform positioning more accurately.

[0050] In some optional embodiments of the first aspect, the method further includes: sending the first result to the second network node based on the reported information; or processing the first result to obtain a second result, and sending the second result to the second network node based on the reported information.

[0051] In the above embodiment, the first result or the second result can be sent to the second network node corresponding to the reported information based on the reported information. The second network node sends the first result or the second result to the third network node, so that the third network node can accurately know which network node the first result or the second result originated from, thereby improving positioning accuracy.

[0052] In some optional embodiments of the first aspect, the reporting information includes an identifier corresponding to the measurement information.

[0053] In the above embodiment, the reported information may include an identifier corresponding to the measurement information to identify the base station, TRP, measurement and other information corresponding to the measurement information, so that the first result or the second result can be sent based on the reported information to improve the accuracy of positioning.

[0054] In some optional embodiments of the first aspect, the identifier includes at least one of the following: a new air interface positioning protocol a identifier; a positioning management function measurement identifier; and a radio access network measurement identifier.

[0055] In the above embodiment, the identification corresponding to the measurement may include at least one of the following, and flexibly adapt to different situations to identify the measurement information.

[0056] In some optional embodiments of the first aspect, the measurement information includes at least one of the following: measurement data of the terminal by the first transmission point TRP of the second network node; an identifier of the second network node; an identifier of the first TRP; an identifier of the cell where the first TRP is located; a timestamp, where the timestamp is used to indicate the time of measurement; the quality of the measurement; the type of the positioning signal, where the positioning signal is used to measure and obtain the measurement data; beam information, where the beam information is used to indicate the beam for receiving the positioning signal; line-of-sight information, where the line-of-sight information is used to indicate the line-of-sight when receiving the positioning signal; and non-line-of-sight information, where the non-line-of-sight information is used to indicate the non-line-of-sight when receiving the positioning signal.

[0057] In the above embodiment, the measurement information may include at least one of the above items, so that a first result can be obtained based on the measurement information and the AI ​​model for positioning and improving communication efficiency.

[0058] In some optional embodiments of the first aspect, the method further includes: receiving second information sent by the second network node, the second information being used to request the first network node to assist in positioning based on the AI ​​model; or, receiving third information sent by the third network node, the third information being used to request the first network node to assist in positioning based on the AI ​​model.

[0059] In the above embodiment, the second information from the second network node or the third information from the third network node can be received to respond to the request, perform assisted positioning based on the AI ​​model, and improve communication efficiency.

[0060] In some optional embodiments of the first aspect, the second information and the third information include at least one of the following: information requesting the first network node to perform AI model-assisted positioning; the type of the first result; the reporting mechanism of the first result; the reporting resources of the first result; parameters for processing the first result; response time information, the response time information is used to indicate that the first network node feeds back the first result within the response time information; and requirement information, the requirement information is used to indicate the conditions required for AI model-assisted positioning.

[0061] In the above embodiment, the second information and the third information may include at least one of the above items, so that the first network node can receive the request and determine whether to approve the request.

[0062] In some optional embodiments of the first aspect, the type information of the first result includes at least one of the following: time information; power information; angle information.

[0063] In the above embodiment, the type information of the first result may include at least one of the above items, so as to adapt to different situations, flexibly perform reasoning of the AI ​​model, and obtain the first result.

[0064] In some optional embodiments of the first aspect, the demand information includes at least one of the following: the amount of data that the first network node needs to process when assisted positioning based on the AI ​​model; the time interval in which the first network node needs to perform assisted positioning based on the AI ​​model; and the identifier of the target network node to which the first network node needs to send the first result.

[0065] In the above embodiment, the demand information includes at least one of the above items, so that the first network node can determine whether to approve the request, thereby improving communication efficiency.

[0066] In some optional embodiments of the first aspect, the measurement information is obtained based on fourth information sent by the third network node to the second network node, and the fourth information includes at least one of the following: an identifier of the second TRP that needs to be measured; an identifier of the base station where the second TRP is located; an identifier of the cell where the second TRP is located; the type of measurement data; a reporting mechanism for measurement data; and a reporting resource for measurement data.

[0067] In the above embodiment, the measurement information can be obtained based on the fourth information. The fourth information includes at least one of the above items and can configure the second network node to perform measurement to obtain the measurement information.

[0068] In some optional embodiments of the first aspect, the fourth information is further used to indicate an identifier of the first network node.

[0069] In the above embodiment, the fourth information may also be used to indicate the identifier of the first network node, so as to instruct the second network node to accurately send the first information to the first network node, thereby improving communication efficiency.

[0070] In some optional embodiments of the first aspect, the parameter includes reference time information.

[0071] In the above embodiment, the parameters may include reference time information to facilitate calculation of the first result and obtain a richer and better second result.

[0072] In a second aspect, a positioning method is provided, the method comprising: sending first information to a first network node, the first information being used to indicate measurement information of the terminal by the second network node, and reporting information of an output result of an artificial intelligence (AI) model; wherein the measurement information is used by the first network node to obtain a first result based on the AI ​​model, the reporting information is used to send the first result, and the first result is used by a third network node to locate the terminal.

[0073] In some optional embodiments of the second aspect, the method also includes: receiving the first result or the second result sent by the first network node, where the first result or the second result is sent based on the reported information; sending the first result or the second result to the third network node; or processing the first result to obtain a third result, and sending the third result to the third network node.

[0074] In some optional embodiments of the second aspect, the reporting information includes an identifier corresponding to the measurement information.

[0075] In some optional embodiments of the second aspect, the identifier includes at least one of the following: a new air interface positioning protocol a identifier; a positioning management function measurement identifier; and a radio access network measurement identifier.

[0076] In some optional embodiments of the second aspect, the measurement information includes at least one of the following: measurement data of the terminal by the first transmission point TRP of the second network node; an identifier of the second network node; an identifier of the first TRP; an identifier of the cell where the first TRP is located; a timestamp, where the timestamp is used to indicate the time of measurement; the quality of the measurement; the type of the positioning signal, where the positioning signal is used to measure and obtain the measurement data; beam information, where the beam information is used to indicate the beam for receiving the positioning signal; line-of-sight information, where the line-of-sight information is used to indicate the line-of-sight when receiving the positioning signal; and non-line-of-sight information, where the non-line-of-sight information is used to indicate the non-line-of-sight when receiving the positioning signal.

[0077] In some optional embodiments of the second aspect, the method further includes: the second network node sending second information to the first network node, where the second information is used to request the first network node to assist in positioning based on the AI ​​model.

[0078] In some optional embodiments of the second aspect, the second information includes at least one of the following: information requesting the first network node to perform AI model-assisted positioning; the type of the first result; the reporting mechanism of the first result; the reporting resources of the first result; parameters for processing the first result; response time information, the response time information is used to indicate that the first network node feeds back the first result within the response time information; and requirement information, the requirement information is used to indicate the conditions required for AI model-assisted positioning.

[0079] In some optional embodiments of the second aspect, the type information of the first result includes at least one of the following: time information; power information; angle information.

[0080] In some optional embodiments of the second aspect, the demand information includes at least one of the following: the amount of data that the first network node needs to process when assisted positioning based on the AI ​​model; the time interval in which the first network node needs to perform assisted positioning based on the AI ​​model; and the identifier of the target network node to which the first network node needs to send the first result.

[0081] In some optional embodiments of the second aspect, the method further includes: receiving fourth information sent by a third network node, the fourth information being used to determine measurement information, the fourth information including at least one of the following: an identifier of a second TRP that needs to be measured; an identifier of a base station where the second TRP is located; an identifier of a cell where the second TRP is located; a type of measurement data; a reporting mechanism for measurement data; and reporting resources for measurement data.

[0082] In some optional embodiments of the second aspect, the fourth information is further used to indicate an identifier of the first network node.

[0083] In some optional embodiments of the second aspect, the parameters include reference time information.

[0084] According to a third aspect, a positioning method is provided, comprising: receiving a first result, the first result being used to locate the terminal; wherein the first result is obtained based on measurement information and an AI model, the first result is sent based on reporting information of an output result of the AI ​​model, and the measurement information and the reporting information are indicated by the first information sent by the second network node to the first network node.

[0085] In some optional embodiments of the third aspect, receiving the first result includes: receiving the first result and the reporting information sent by the first network node; or receiving the second result and the reporting information sent by the first network node, the second result being obtained by the first network node processing the first result.

[0086] In some optional embodiments of the third aspect, receiving the first result includes: receiving the first result or the second result sent by the second network node; wherein, the first result or the second result is sent by the first network node to the second network node based on the reported information, and the second result is obtained based on processing the first result.

[0087] In some optional embodiments of the third aspect, the reporting information includes an identifier corresponding to the measurement information.

[0088] In some optional embodiments of the third aspect, the identifier includes at least one of the following: a new air interface positioning protocol a identifier; a positioning management function measurement identifier; and a radio access network measurement identifier.

[0089] In some optional embodiments of the third aspect, the measurement information includes at least one of the following: measurement data of the first transmission point TRP of the second network node on the terminal; an identifier of the second network node; an identifier of the first TRP; an identifier of the cell where the first TRP is located; a timestamp, wherein the timestamp is used to indicate the time of measurement; the quality of the measurement; the type of the positioning signal, wherein the positioning signal is used to measure and obtain the measurement data; beam information, wherein the beam information is used to indicate the beam for receiving the positioning signal; line-of-sight information, wherein the line-of-sight information is used to indicate the line-of-sight when receiving the positioning signal; and non-line-of-sight information, wherein the non-line-of-sight information is used to indicate the non-line-of-sight when receiving the positioning signal.

[0090] In some optional embodiments of the third aspect, the method also includes: sending fourth information to the second network node, the fourth information including at least one of the following: an identifier of the second TRP that needs to be measured; an identifier of the base station where the second TRP is located; an identifier of the cell where the second TRP is located; the type of measurement data; a reporting mechanism for the measurement data; and a reporting resource for the measurement data.

[0091] In some optional embodiments of the third aspect, the fourth information is further used to indicate an identifier of the first network node.

[0092] In a fourth aspect, a positioning method is provided, the method comprising: a second network node sending first information to a first network node, where the first information is used to indicate measurement information of the second network node on the terminal and reporting information of an output result of an artificial intelligence (AI) model;

[0093] The first network node receives the first information sent by the second network node; the first network node obtains a first result based on the measurement information and the AI ​​model; wherein the reporting information is used to send the first result, and the first result is used by the third network node to locate the terminal.

[0094] In a fifth aspect, a network node is provided, including: a transceiver module for receiving first information sent by a second network node, the first information being used to indicate the measurement information of the second network node on the terminal, and the reporting information of the output result of the artificial intelligence AI model; a processing module for obtaining a first result based on the measurement information and the AI ​​model; wherein the reporting information is used to send the first result, and the first result is used by a third network node to locate the terminal.

[0095] In some optional embodiments of the fifth aspect, the transceiver module is further used to: send the first result and the reporting information to the third network node; or, the processing module is further used to: process the first result to obtain a second result, and the transceiver module is further used to: send the second result and the reporting information to the third network node.

[0096] In some optional embodiments of the fifth aspect, the transceiver module is further used to: send the first result to the second network node based on the reported information; or, the processing module is further used to: process the first result to obtain a second result, and the transceiver module is further used to: send the second result to the second network node based on the reported information.

[0097] In some optional embodiments of the fifth aspect, the reporting information includes an identifier corresponding to the measurement information.

[0098] In some optional embodiments of the fifth aspect, the identifier includes at least one of the following: a new air interface positioning protocol a identifier; a positioning management function measurement identifier; and a radio access network measurement identifier.

[0099] In some optional embodiments of the fifth aspect, the measurement information includes at least one of the following: measurement data of the terminal by the first transmission point TRP of the second network node; an identifier of the second network node; an identifier of the first TRP; an identifier of the cell where the first TRP is located; a timestamp, wherein the timestamp is used to indicate the time of measurement; the quality of the measurement; the type of the positioning signal, wherein the positioning signal is used to measure and obtain the measurement data; beam information, wherein the beam information is used to indicate the beam for receiving the positioning signal; line-of-sight information, wherein the line-of-sight information is used to indicate the line-of-sight when receiving the positioning signal; and non-line-of-sight information, wherein the non-line-of-sight information is used to indicate the non-line-of-sight when receiving the positioning signal.

[0100] In some optional embodiments of the fifth aspect, the legal module is also used to: receive second information sent by the second network node, the second information being used to request the first network node to assist in positioning based on the AI ​​model; or, receive third information sent by the third network node, the third information being used to request the first network node to assist in positioning based on the AI ​​model.

[0101] In some optional embodiments of the fifth aspect, the second information and the third information include at least one of the following: information requesting the first network node to perform AI model-assisted positioning; the type of the first result; the reporting mechanism of the first result; the reporting resources of the first result; parameters for processing the first result; response time information, the response time information is used to indicate that the first network node feeds back the first result within the response time information; and requirement information, the requirement information is used to indicate the conditions required for AI model-assisted positioning.

[0102] In some optional embodiments of the fifth aspect, the type information of the first result includes at least one of the following: time information; power information; angle information.

[0103] In some optional embodiments of the fifth aspect, the demand information includes at least one of the following: the amount of data that the first network node needs to process when assisted positioning based on the AI ​​model; the time interval in which the first network node needs to perform assisted positioning based on the AI ​​model; and the identifier of the target network node to which the first network node needs to send the first result.

[0104] In some optional embodiments of the fifth aspect, the measurement information is obtained based on fourth information sent by the third network node to the second network node, and the fourth information includes at least one of the following: an identifier of the second TRP that needs to be measured; an identifier of the base station where the second TRP is located; an identifier of the cell where the second TRP is located; the type of measurement data; a reporting mechanism for measurement data; and a reporting resource for measurement data.

[0105] In some optional embodiments of the fifth aspect, the fourth information is further used to indicate an identifier of the first network node.

[0106] In some optional embodiments of the fifth aspect, the parameters include reference time information.

[0107] In a sixth aspect, a network node is provided, including: a transceiver module for sending first information to a first network node, wherein the first information is used to indicate the measurement information of the second network node on the terminal, and the reporting information of the output result of the artificial intelligence AI model; wherein the measurement information is used by the first network node to obtain a first result based on the AI ​​model, the reporting information is used to send the first result, and the first result is used by the third network node to locate the terminal.

[0108] In some optional embodiments of the sixth aspect, the transceiver module is also used to: receive the first result or the second result sent by the first network node, where the first result or the second result is sent based on the reported information; send the first result or the second result to the third network node; or the network node also includes a processing module for processing the first result to obtain a third result, and the transceiver model is also used to: send the third result to the third network node.

[0109] In some optional embodiments of the sixth aspect, the reporting information includes an identifier corresponding to the measurement information.

[0110] In some optional embodiments of the sixth aspect, the identifier includes at least one of the following: a new air interface positioning protocol a identifier; a positioning management function measurement identifier; and a radio access network measurement identifier.

[0111] In some optional embodiments of the sixth aspect, the measurement information includes at least one of the following: measurement data of the first transmission point TRP of the second network node on the terminal; an identifier of the second network node; an identifier of the first TRP; an identifier of the cell where the first TRP is located; a timestamp, the timestamp being used to indicate the time of measurement; the quality of the measurement; the type of the positioning signal, the positioning signal being used to measure and obtain the measurement data; beam information, the beam information being used to indicate the beam for receiving the positioning signal; line-of-sight information, the line-of-sight information being used to indicate the line-of-sight when receiving the positioning signal; and non-line-of-sight information, the non-line-of-sight information being used to indicate the non-line-of-sight when receiving the positioning signal.

[0112] In some optional embodiments of the sixth aspect, the transceiver module is further used to: send second information to the first network node, where the second information is used to request the first network node to assist in positioning based on the AI ​​model.

[0113] In some optional embodiments of the sixth aspect, the second information includes at least one of the following: information requesting the first network node to perform AI model-assisted positioning; the type of the first result; the reporting mechanism of the first result; the reporting resources of the first result; parameters for processing the first result; response time information, the response time information is used to indicate that the first network node feeds back the first result within the response time information; and requirement information, the requirement information is used to indicate the conditions required for AI model-assisted positioning.

[0114] In some optional embodiments of the sixth aspect, the type information of the first result includes at least one of the following: time information; power information; angle information.

[0115] In some optional embodiments of the sixth aspect, the demand information includes at least one of the following: the amount of data that the first network node needs to process when assisted by the AI ​​model for positioning; the time interval in which the first network node needs to perform assisted positioning based on the AI ​​model; and the identifier of the target network node to which the first network node needs to send the first result.

[0116] In some optional embodiments of the sixth aspect, the transceiver module is also used to: receive fourth information sent by the third network node, the fourth information is used to determine measurement information, and the fourth information includes at least one of the following: an identifier of the second TRP that needs to be measured; an identifier of the base station where the second TRP is located; an identifier of the cell where the second TRP is located; the type of measurement data; a reporting mechanism for measurement data; and a reporting resource for measurement data.

[0117] In some optional embodiments of the sixth aspect, the fourth information is further used to indicate an identifier of the first network node.

[0118] In some optional embodiments of the sixth aspect, the parameters include reference time information.

[0119] In the seventh aspect, a network node is provided, including: a transceiver module for receiving a first result, the first result being used to locate the terminal; wherein the first result is obtained based on measurement information and an AI model, and the first result is sent based on the reporting information of the output result of the AI ​​model, and the measurement information and the reporting information are sent by the second network node to the first network node by the first information indication.

[0120] In some optional embodiments of the seventh aspect, the transceiver module receives the first result in the following manner: receiving the first result and the reporting information sent by the first network node; or receiving the second result and the reporting information sent by the first network node, the second result being obtained by the first network node processing the first result.

[0121] In some optional embodiments of the seventh aspect, the transceiver module receives the first result in the following manner: receiving the first result or the second result sent by the second network node; wherein, the first result or the second result is sent by the first network node to the second network node based on the reported information, and the second result is obtained based on processing the first result.

[0122] In some optional embodiments of the seventh aspect, the reporting information includes an identifier corresponding to the measurement information.

[0123] In some optional embodiments of the seventh aspect, the identifier includes at least one of the following: a new air interface positioning protocol a identifier; a positioning management function measurement identifier; and a radio access network measurement identifier.

[0124] In some optional embodiments of the seventh aspect, the measurement information includes at least one of the following: measurement data of the terminal by the first transmission point TRP of the second network node; an identifier of the second network node; an identifier of the first TRP; an identifier of the cell where the first TRP is located; a timestamp, wherein the timestamp is used to indicate the time of measurement; the quality of the measurement; the type of the positioning signal, wherein the positioning signal is used to measure and obtain the measurement data; beam information, wherein the beam information is used to indicate the beam for receiving the positioning signal; line-of-sight information, wherein the line-of-sight information is used to indicate the line-of-sight when receiving the positioning signal; and non-line-of-sight information, wherein the non-line-of-sight information is used to indicate the non-line-of-sight when receiving the positioning signal.

[0125] In some optional embodiments of the seventh aspect, the transceiver module is also used to: send fourth information to the second network node, and the fourth information includes at least one of the following: an identifier of the second TRP that needs to be measured; an identifier of the base station where the second TRP is located; an identifier of the cell where the second TRP is located; the type of measurement data; a reporting mechanism for measurement data; and a reporting resource for measurement data.

[0126] In some optional embodiments of the seventh aspect, the fourth information is further used to indicate an identifier of the first network node.

[0127] In an eighth aspect, a network node is provided, comprising: one or more processors; wherein the terminal is used to execute the first aspect and any one of the positioning methods in the first aspect.

[0128] In a ninth aspect, a network node is provided, comprising: one or more processors; wherein the network device is used to execute the second aspect and any one of the positioning methods in the second aspect.

[0129] In a tenth aspect, a network node is provided, comprising: one or more processors; wherein the network device is used to execute the third aspect and any one of the positioning methods in the third aspect.

[0130] In the eleventh aspect, a communication system is provided, comprising a first network node and a second network node, wherein the first network node is configured to implement the first aspect and any one of the positioning methods in the first aspect, and the second network node is configured to implement the second aspect and any one of the positioning methods in the second aspect or the third aspect and any one of the positioning methods in the third aspect.

[0131] In the twelfth aspect, a storage medium is provided, which stores instructions. When the instructions are executed on a communication device, the communication device executes a positioning method such as the first aspect and any one of the first aspect, or the second aspect and any one of the second aspect, or the third aspect and any one of the third aspect.

[0132] In the thirteenth aspect, an embodiment of the present disclosure proposes a program product, including a computer program. When the computer program is executed by a communication device, the communication device executes the method described in the first aspect or the second aspect or the third aspect and the optional implementation of the third aspect.

[0133] In a fourteenth aspect, an embodiment of the present disclosure proposes a computer program, which, when executed on a computer, enables the computer to execute the method described in the optional implementation of the first aspect, the second aspect, or the third aspect.

[0134] In a fifteenth aspect, an embodiment of the present disclosure provides a chip or a chip system, wherein the chip or chip system includes a processing circuit configured to execute the method described in the optional implementation of the first aspect, the second aspect, or the third aspect.

[0135] It is understandable that the terminal, access network device, first network element, other network elements, core network device, communication system, storage medium, program product, computer program, chip, or chip system involved in each embodiment of the present disclosure are all used to perform the method proposed in the embodiment of the present disclosure. Therefore, the beneficial effects that can be achieved can refer to the beneficial effects of the corresponding method and will not be repeated here.

[0136] The present disclosure provides a positioning method, a network node, a communication system, and a storage medium. In some embodiments, the terms positioning method, information processing method, and positioning method are interchangeable; the terms communication device, information processing device, and communication device are interchangeable; and the terms information processing system and communication system are interchangeable.

[0137] The embodiments of the present disclosure are not exhaustive and are merely illustrative of some embodiments, and are not intended to be a specific limitation on the scope of protection of the present disclosure. In the absence of contradiction, each step in a certain embodiment can be implemented as an independent embodiment, and the steps can be arbitrarily combined. For example, a solution after removing some steps in a certain embodiment can also be implemented as an independent embodiment, and the order of the steps in a certain embodiment can be arbitrarily exchanged. In addition, the optional implementation methods in a certain embodiment can be arbitrarily combined; in addition, the embodiments can be arbitrarily combined. For example, some or all steps of different embodiments can be arbitrarily combined, and a certain embodiment can be arbitrarily combined with the optional implementation methods of other embodiments.

[0138] In each embodiment of the present disclosure, unless otherwise specified or provided for, the terms and / or descriptions between the embodiments are consistent and may be referenced by each other. The technical environments in different embodiments may be combined to form new embodiments based on their inherent logical relationships.

[0139] The terms used in the embodiments of the present disclosure are only for the purpose of describing specific embodiments and are not intended to limit the present disclosure.

[0140] In the embodiments of the present disclosure, unless otherwise specified, elements expressed in the singular, such as "a", "an", "the", "above", "said", "the", "the", etc., may mean "one and only one", or "one or more", "at least one", etc. For example, when using articles such as "a", "an", "the" in English in translation, the noun following the article may be understood as a singular expression or a plural expression.

[0141] In the embodiments of the present disclosure, “plurality” refers to two or more.

[0142] In some embodiments, the terms "at least one," "one or more," "a plurality of," "multiple," etc. may be used interchangeably.

[0143] In some embodiments, descriptions such as "at least one of A and B," "A and / or B," "A in one case, B in another case," or "in response to one case A, in response to another case B" may include the following technical solutions depending on the situation: in some embodiments, A (A is executed independently of B); in some embodiments, B (B is executed independently of A); in some embodiments, execution is selected from A and B (A and B are selectively executed); and in some embodiments, A and B (both A and B are executed). The same applies when there are more branches, such as A, B, and C.

[0144] In some embodiments, "A or B" and other descriptions may include the following technical solutions depending on the situation: in some embodiments, A (A is executed independently of B); in some embodiments, B (B is executed independently of A); in some embodiments, execution is selected from A and B (A and B are selectively executed). The above is also applicable when there are more branches such as A, B, C, etc.

[0145] The prefixes such as "first" and "second" in the embodiments of the present disclosure are only used to distinguish different description objects and do not constitute any restriction on the position, order, priority, quantity or content of the description objects. For the statement of the description object, please refer to the description in the context of the claims or embodiments, and no unnecessary restriction should be constituted due to the use of prefixes. For example, if the description object is a "field", the ordinal number before the "field" in the "first field" and the "second field" does not limit the position or order between the "fields". "First" and "second" do not limit whether the "fields" they modify are in the same message, nor do they limit the order of the "first field" and the "second field". For another example, if the description object is a "level", the ordinal number before the "level" in the "first level" and the "second level" does not limit the priority between the "levels". For another example, the number of description objects is not limited by the ordinal number and can be one or more. Taking "first device" as an example, the number of "devices" can be one or more. In addition, the objects modified by different prefixes can be the same or different. For example, if the description object is "device", then the "first device" and the "second device" can be the same device or different devices, and their types can be the same or different; for example, if the description object is "information", then the "first information" and "the performance of each AI model" can be the same information or different information, and their contents can be the same or different.

[0146] In some embodiments, “including A,” “comprising A,” “used to indicate A,” and “carrying A” can be interpreted as directly carrying A or indirectly indicating A.

[0147] In some embodiments, terms such as "in response to...", "in response to determining...", "in the case of...", "at the time of...", "when...", "if...", "if...", etc. can be used interchangeably.

[0148] In some embodiments, terms such as "greater than", "greater than or equal to", "not less than", "more than", "more than or equal to", "not less than", "higher than", "higher than or equal to", "not less than", and "above" can be replaced with each other, and terms such as "less than", "less than or equal to", "not greater than", "less than", "less than or equal to", "not more than", "lower than", "lower than or equal to", "not higher than", and "below" can be replaced with each other.

[0149] In some embodiments, devices and equipment can be interpreted as physical or virtual, and their names are not limited to the names recorded in the embodiments. In some cases, they can also be understood as "equipment", "device", "circuit", "network element", "node", "function", "unit", "section", "system", "network", "chip", "chip system", "entity", "subject", etc.

[0150] In some embodiments, "network" can be interpreted as devices included in the network, such as access network equipment, core network equipment, etc.

[0151] In some embodiments, "access network device (AN device)" may also be referred to as "radio access network device (RAN device)", "base station (BS)", "radio base station", "fixed station", and in some embodiments may also be understood as "node", "access point", "transmission point (TP)", "reception point (RP)", "transmission and / or reception point (TRP)" "panel", "antenna panel", "antenna array", "cell", "macro cell", "small cell", "femto cell", "pico cell", "sector", "cell group", "serving cell", "carrier", "component carrier", "bandwidth part (BWP)", etc.

[0152] In some embodiments, "terminal" or "terminal device" may be referred to as "user equipment (UE)", "user terminal" "mobile station (MS)", "mobile terminal (MT)", subscriber station, mobile unit, subscriber unit, wireless unit, remote unit, mobile device, wireless device, wireless communication device, remote device, mobile subscriber station, access terminal, mobile terminal, wireless terminal, remote terminal, handset, user agent, mobile client, client, etc.

[0153] In some embodiments, obtaining data, information, etc. may comply with the laws and regulations of the country where the data is obtained.

[0154] In some embodiments, data, information, etc. may be obtained with the user's consent.

[0155] In addition, each element, each row, or each column in the table of the embodiment of the present disclosure can be implemented as an independent embodiment, and the combination of any elements, any rows, and any columns can also be implemented as an independent embodiment.

[0156] The widespread adoption of 5G technology is bringing tremendous changes to every aspect of our lives. According to the International Telecommunication Union (ITU), 5G will permeate every aspect of future society, building a comprehensive, user-centric information ecosystem. 5G user experience rates can reach 100 megabits per second (Mbit / s) to 1 gigabit per second (Gbit / s), enabling premium services like mobile virtual reality. 5G peak rates can reach 10 Gbit / s to 20 Gbit / s, with traffic density reaching 10 megabits per second per square meter (Mbit / s / m²), supporting a thousand-fold increase in mobile traffic. 5G connection density can reach 1 million per square meter (m²), effectively supporting massive IoT devices. 5G transmission latency can reach milliseconds, meeting the stringent requirements of connected vehicles and industrial control. 5G can support speeds of 500 kilometers per hour (km / h), ensuring a superior user experience even in high-speed rail environments. It is foreseeable that 5G, as a representative of new infrastructure, will reshape the future information society.

[0157] In recent years, AI technology has achieved continuous breakthroughs in numerous fields. The continued development of fields like intelligent voice and computer vision has not only brought a rich variety of applications to smart terminals, but has also found widespread application in education, transportation, home furnishings, healthcare, retail, security, and other fields. While bringing convenience to people's lives, it is also promoting industrial upgrading across various industries. AI technology is also rapidly interpenetrating with other disciplines. Its development integrates knowledge from different disciplines while also providing new directions and methods for their development.

[0158] In wireless AI research, application cases of artificial intelligence include: AI-based CSI enhancement; AI-based beam management; and AI-based positioning.

[0159] Figure 1a is a schematic diagram of the AI ​​architecture. As shown in Figure 1a, the AI ​​architecture includes functions such as data collection, model management, model training, and model inference.

[0160] AI-based positioning includes but is not limited to the following five deployment methods:

[0161] For example, AI / machine learning (ML) directly targets:

[0162] 1) UE-based positioning: the model is deployed on the UE side, and AI / ML directly locates;

[0163] 2) UE-assisted LMF-based positioning, the model is deployed on the LMF side, and AI / ML directly locates;

[0164] 3) Next generation radio access network (NG-RAN) node assisted positioning, the model is deployed on the LMF side, and AI / ML directly locates.

[0165] Another example is AI / ML-assisted positioning:

[0166] 4) UE-assisted LMF-based positioning, the model is deployed on the UE side, and AI / ML assists positioning;

[0167] 5) NG-RAN node-assisted positioning: the model is deployed on the next generation NodeB (gNB) side, and AI / ML assists in positioning.

[0168] AI / ML direct positioning can be understood as the AI ​​or ML model outputting location information, that is, obtaining positioning results. AI / ML assisted positioning can be understood as the AI ​​or ML model outputting intermediate parameters for positioning, which can be used to calculate location information. In other words, the AI ​​or ML model does not directly obtain positioning results.

[0169] In some embodiments, for the above deployment method 5), when the AI ​​model is deployed on the base station side, there are three AI-based positioning architectures that can be considered:

[0170] First, each transmission point (transmission and receiving point, TRP) corresponds to an AI model, or each TRP corresponds to an ML model. Figure 1b is a schematic diagram of an AI-based positioning architecture shown in an exemplary embodiment of the present disclosure. As shown in Figure 1b, 18 TRPs (TRP0~TRP17) are taken as an example for illustration, but the present disclosure does not limit the number of TRPs. Each TRP corresponds to an ML model, and the time domain path delay profile (PDP) (for example, PDP 0~PDP 17) measured by each TRP can be input into the corresponding ML model, and the output unknown direct path (unobserved direct path) arrival time (time of arrival, ToA) is passed to the LMF. Positioning is performed by LMF based on the unobserved direct path ToA and traditional positioning methods.

[0171] Second, multiple TRPs correspond to the same AI model, or multiple TRPs correspond to the same ML model. Figure 1c is a schematic diagram of an AI-based positioning architecture shown in an exemplary embodiment of the present disclosure. As shown in Figure 1c, multiple TRPs correspond to the same ML model, for example, 18 TRPs (TRP0~TRP17). The time domain carrier to interference ratio (CIR) (for example, CIR0~CIR17) measured by each TRP is input into the same ML model, and the output unobserved direct path ToA is passed to LMF. LMF performs positioning based on unobserved direct path ToA and traditional positioning methods. LMF outputs location information.

[0172] Third, multiple TRPs correspond to the same AI model, or multiple TRPs correspond to the same ML model. Some of the multiple TRPs belong to the gNB that deploys the AI ​​model or ML model, while others belong to other gNBs. Figure 1d is a schematic diagram of an AI-based positioning architecture according to an exemplary embodiment of the present disclosure. As shown in Figure 1d, the gNB that deploys the ML model is gNB1. The time-domain CIR measured by gNB1's TRP and the time-domain CIR measured by gNB2's TRP are both input into the ML model on gNB1's side, and the output unobserved direct path ToA is passed to the LMF. The LMF performs positioning based on the unobserved direct path ToA and traditional positioning methods. The LMF outputs location information. gNB2 is any gNB different from gNB1.

[0173] It can be understood that each TRP has its corresponding subordinate gNB, and each gNB can have multiple TRPs. In non-AI-based positioning, the positioning intermediate parameters corresponding to each TRP are calculated by the corresponding gNB and transmitted to the LMF by the corresponding gNB. Among them, the positioning intermediate parameters represent the intermediate parameters used to calculate the location information during the positioning process. For example, it can be a time-related parameter, that is, the ToA of the unknown direct path shown in Figures 1b to 1d; line of sight (LoS) or non-line of sight (NLoS) indicator, etc.

[0174] For the third positioning architecture mentioned above, when AI model training is deployed on a gNB, the output of the AI ​​model includes not only the intermediate positioning parameters of this gNB, but also the intermediate positioning parameters of other gNBs. If the intermediate positioning parameters are directly transmitted to the LMF, it will lead to large positioning errors.

[0175] Therefore, the present disclosure proposes a positioning method, in which a first network node receives measurement information sent by a second network node and reporting information of the AI ​​model output result. The reporting information can be used to report the AI ​​model so that the third network node can accurately obtain the terminal's location information based on the output result of the AI ​​model, thereby improving the accuracy of positioning and reducing positioning errors.

[0176] FIG1e is a schematic diagram of a communication system architecture according to an embodiment of the present disclosure.

[0177] As shown in Figure 1e, communication system 100 includes a first network node 101, a second network node 102, and a third network node 103. First network node 101 may be a gNB that deploys an AI model and is a base station for inference (gNBx for inference). Second network node 102 may be a base station (gNBy) different from first network node 101 and not a gNB that deploys an AI model. Third network node 103 may be a LMF. Of course, this disclosure is merely illustrative; the first, second, and third network nodes may also be other types of nodes in the communication system. Although this disclosure uses gNBs and LMFs as examples, it is not limited thereto.

[0178] In some embodiments, the network node may include at least one of an access network device and a core network device.

[0179] In some embodiments, the access network device is, for example, a node or device that accesses a terminal to a wireless network. The access network device may include an evolved NodeB (eNB) in a fifth generation mobile communication technology (5G) communication system, a next generation evolved NodeB (ng-eNB), a gNB, a node B (NB), a home node B (HNB), a home evolved node B (HeNB), a wireless backhaul device, a radio network controller (RNC), a base station controller (BSC), a base transceiver station (BTS), a base band unit (BBU), a mobile switching center, a base station in a 6G communication system, an open base station (Open RAN), a cloud base station (Cloud RAN), a base station in other communication systems, and at least one of an access node in a Wi-Fi system, but is not limited thereto.

[0180] In some embodiments, the technical solution of the present disclosure can be applied to the Open RAN architecture. In this case, the interfaces between or within the access network devices involved in the embodiments of the present disclosure can be transformed into internal interfaces of the Open RAN, and the processes and information interactions between these internal interfaces can be implemented through software or programs.

[0181] In some embodiments, the access network device can be composed of a centralized unit (CU) and a distributed unit (DU), where the CU can also be called a control unit. The CU-DU structure can be used to split the protocol layer of the access network device, with the functions of some protocol layers centrally controlled by the CU, and the functions of the remaining part or all of the protocol layers distributed in the DU, which is centrally controlled by the CU, but is not limited to this.

[0182] In some embodiments, a core network device may be a device including one or more network elements, or may be multiple devices or device groups, each including all or part of the one or more network elements. The network element may be virtual or physical. The core network may include, for example, at least one of an Evolved Packet Core (EPC), a 5G Core Network (5GCN), and a Next Generation Core (NGC).

[0183] It can be understood that the communication system described in the embodiment of the present disclosure is for the purpose of more clearly illustrating the technical solution of the embodiment of the present disclosure, and does not constitute a limitation on the technical solution proposed in the embodiment of the present disclosure. Ordinary technicians in this field can know that with the evolution of the system architecture and the emergence of new business scenarios, the technical solution proposed in the embodiment of the present disclosure is also applicable to similar technical problems.

[0184] The following embodiments of the present disclosure may be applied to the communication system 100 shown in FIG1 , or a portion thereof, but are not limited thereto. The entities shown in FIG1 are illustrative only. The communication system may include all or part of the entities shown in FIG1 , or may include other entities outside of FIG1 . The number and form of the entities are arbitrary, and the entities may be physical or virtual. The connection relationships between the entities are illustrative only. The entities may be connected or disconnected, and the connection may be in any manner, including direct or indirect, wired or wireless.

[0185] The embodiments of the present disclosure can be applied to Long Term Evolution (LTE), LTE-Advanced (LTE-A), LTE-Beyond (LTE-B), SUPER 3G, IMT-Advanced, 4th generation mobile communication system (4G), 5th generation mobile communication system (5G), 5G new radio (NR), future radio access (FRA), new radio access technology (RAT), new radio (NR), new radio access (NX), future generation radio access (FX), Global System for Mobile communications (GSM (registered trademark)), CDMA2000, Ultra Mobile Broadband (UMB), IEEE 802.11 (Wi-Fi (registered trademark)), IEEE 802.16 (WiMAX (registered trademark)), IEEE 802.20, Ultra-WideBand (UWB), Bluetooth (registered trademark), Public Land Mobile Network (PLMN) networks, Device-to-Device (D2D) systems, Machine-to-Machine (M2M) systems, Internet of Things (IoT) systems, Vehicle-to-Everything (V2X), systems utilizing other positioning methods, and next-generation systems based on and extending these methods. Furthermore, a combination of multiple systems (e.g., LTE or LTE-A combined with 5G) may also be employed.

[0186] FIG2a is a schematic diagram illustrating an interaction of a positioning method according to an embodiment of the present disclosure. As shown in FIG2a , the present disclosure embodiment relates to a positioning method for a communication system 100, the method comprising:

[0187] Step S2101 : The third network node 103 sends fourth information to the second network node 102 .

[0188] In some embodiments, the second network node 102 receives fourth information sent by the third network node 103 .

[0189] In some embodiments, the fourth information is used to determine measurement information, wherein the measurement information represents information related to the second network node measuring an uplink positioning signal sent by the terminal for positioning the terminal. The fourth information may indicate how the second network node performs the measurement.

[0190] In some embodiments, the fourth information includes at least one of the following: an identifier of the second TRP that needs to be measured; an identifier of the base station where the second TRP is located; an identifier of the cell where the second TRP is located; the type of measurement data; a reporting mechanism for measurement data; and a reporting resource for measurement data.

[0191] Optionally, the fourth information includes an identifier of a second TRP that needs to be measured. That is, the fourth information can be used to indicate which TRP, or which TRPs, need to measure the uplink positioning signal sent by the terminal. For the sake of convenience of description, the present disclosure refers to the TRP that needs to be measured as indicated by the fourth information as the second TRP. It can be understood that the second network node may correspond to multiple subordinate TRPs. Based on the identifier of the second TRP included in the fourth information, the TRP that needs to be measured can be determined from the multiple TRPs, thereby obtaining the measurement information.

[0192] Optionally, the fourth information includes an identifier of the base station where the second TRP is located. The fourth information may indicate the identifier of the base station where the second TRP is located, that is, the identifier of the second network node. The second network node may subsequently send its identifier to the first network node to inform the first network node of the source of the measurement information, that is, which gNB the measurement information comes from.

[0193] Optionally, the fourth information includes an identifier of the cell where the second TRP is located. The fourth information may indicate an identifier of the cell where the second TRP is located.

[0194] Optionally, the fourth information includes the type of measurement data. The measurement data type indicates the type of data measured by the second network node when measuring the uplink positioning signal. For example, the measurement data type may include, but is not limited to, angle of arrival (AOA), sounding reference signal-reference signal received power (SRS-RSRP), relative time of arrival (RToA), gNB Rx-Tx time difference (gNB Rx-Tx time difference), zero angle of arrival (Z-AOA), multiple uplink angles of arrival (UL-AoA), CIR, PDP, and delay profile (DP). Of course, the above measurement data types are merely exemplary and are not exhaustive in this disclosure, but are not limited to these. For example, when the measurement data type indicated by the fourth information is AOA, the second network node measures the AOA of the uplink positioning signal. For another example, when the measurement data type indicated by the fourth information is SRS-RSRP, the second network node measures the SRS-RSRP of the uplink positioning signal.

[0195] Optionally, the fourth information includes a reporting mechanism for the measurement data. The reporting mechanism indicates the mechanism by which the second network node reports the measurement data, i.e., the mechanism by which the measurement information is reported. For example, reporting mechanisms may include periodic reporting, on-demand reporting, etc. This disclosure does not provide examples one by one, but is not limited to these. For periodic reporting, the fourth information may also indicate the reporting period for periodic reporting.

[0196] Optionally, the fourth information includes reporting resources of the measurement data. The reporting resources indicate which resources the measurement data is reported based on, that is, which resources the measurement information is reported based on. For example, the reporting resources may include time domain resources, frequency domain resources, etc.

[0197] In some embodiments, the second network node may determine the measurement information based on the fourth information, that is, perform corresponding measurements on the uplink positioning signal of the terminal based on the fourth information to obtain the measurement information.

[0198] In some embodiments, the measurement information includes at least one of the following: measurement data of the terminal by the first TRP of the second network node; the identifier of the second network node; the identifier of the first TRP; the identifier of the cell where the first TRP is located; a timestamp, which is used to indicate the time of measurement; the quality of the measurement; the type of positioning signal, which is used to measure and obtain measurement data; beam information, which is used to indicate the beam for receiving the positioning signal; line-of-sight information, which is used to indicate the line-of-sight when receiving the positioning signal; and non-line-of-sight information, which is used to indicate the non-line-of-sight when receiving the positioning signal.

[0199] Optionally, the measurement information may include the measurement data of the terminal by the first TRP of the second network node. In the present disclosure, the TRP that measures the uplink positioning signal of the terminal and obtains the measurement data is referred to as the first TRP. It is understandable that the second TRP that needs to be measured, which is indicated by the third network node through the fourth information, may be the same as or different from the first TRP used by the actual second network node for measurement. The measurement information may include the measurement data of the terminal by the first TRP. For example, the first TRP can measure the uplink positioning signal of the terminal to obtain measurement data, include the measurement data in the measurement information, and subsequently use it to indicate to the first network node.

[0200] Optionally, the measurement information may include an identifier of a second network node. The second network node is the network node that measures the terminal's uplink positioning signal and obtains the measurement data. The inclusion of the identifier of the second network node in the measurement information indicates that the measurement data in the measurement information was obtained by the second network node. Including the identifier of the second network node in the measurement information can subsequently be indicated to the first network node.

[0201] Optionally, the measurement information may include an identifier of a first TRP. The first TRP is the TRP that measures the terminal's uplink positioning signal and obtains the measurement data. The inclusion of the identifier of the first TRP in the measurement information indicates that the measurement data in the measurement information was obtained by measuring the first TRP. Including the first TRP in the measurement information may subsequently indicate the first network node.

[0202] Optionally, the measurement information may include an identifier of the cell where the first TRP is located. The identifier of the cell where the first TRP is located is included in the measurement information, which can be subsequently indicated to the first network node.

[0203] Optionally, the measurement information may include a timestamp. The timestamp is used to indicate the time of measurement. That is, the measurement information may include the time when the first TRP measures the uplink positioning signal of the terminal, which may be subsequently indicated to the first network node.

[0204] Optionally, the measurement information may include the quality of the measurement. For example, the quality of the measurement may be information about the precision of the measurement. The quality of the measurement may be used to characterize information such as the precision and accuracy of the measurement.

[0205] Optionally, the measurement information may include the type of positioning signal. The positioning signal is used to obtain measurement data. The types of positioning signals include, for example, synchronization signal and PBCH block (SSB), positioning reference signal (PRS), etc.

[0206] Optionally, the measurement information may include beam information. The beam information is used to indicate the beam from which the positioning signal is received. That is, the measurement information may include the beam from which the measured positioning signal is received, or the beams from which the measured positioning signal is received. The measurement information may include the beam information, which is subsequently indicated to the first network node.

[0207] Optionally, the measurement information may include line-of-sight information. The line-of-sight information is used to indicate line-of-sight information when receiving the positioning signal, that is, whether a direct path exists between the terminal sending the positioning signal and the second network node receiving the positioning signal.

[0208] Optionally, the measurement information may include non-line-of-sight information. The non-line-of-sight information is used to indicate non-line-of-sight information when receiving the positioning signal, that is, there is no direct path between the terminal sending the positioning signal and the second network node receiving the positioning signal.

[0209] In some embodiments, the name of the fourth information is not limited, and it can be, for example, "instruction information", "configuration information", etc.

[0210] In some embodiments, the terminal includes, for example, a mobile phone, a wearable device, an Internet of Things device, a car with communication function, a smart car, a tablet computer, a computer with wireless transceiver function, a virtual reality (VR) terminal device, an augmented reality (AR) terminal device, a wireless terminal device in industrial control, a wireless terminal device in self-driving, a wireless terminal device in remote medical surgery, a wireless terminal device in a smart grid, a wireless terminal device in transportation safety, a wireless terminal device in a smart city, and at least one of a wireless terminal device in a smart home, but is not limited thereto.

[0211] In step S2102 , the second network node 102 sends second information to the first network node 101 , or the third network node 103 sends third information to the first network node.

[0212] In some embodiments, the first network node 101 receives the second information sent by the second network node 102 , or the first network node 101 receives the third information sent by the third network node 103 .

[0213] In some embodiments, both the second information and the third information are used to request the first network node to perform AI-based model-assisted positioning. The second information is the information sent by the second network node to the first network node when requesting AI-based model-assisted positioning. The third information is the information sent by the third network node to the first network node when requesting AI-based model-assisted positioning. The second and third information may be the same or different. For example, the second and third information may differ in format or carry different signaling.

[0214] In some embodiments, the second information and the third information include at least one of the following: information requesting the first network node to assist in positioning based on the AI ​​model; the type of the first result; the reporting mechanism of the first result; the reporting resources of the first result; parameters for processing the first result; response time information, the response time information is used to indicate that the first network node feeds back the first result within the response time information; requirement information, the requirement information is used to indicate the conditions required for assisted positioning based on the AI ​​model.

[0215] Optionally, the second information / third information may include information requesting the first network node to assist in positioning based on an AI model. Based on the information, the first network node may activate the AI ​​model to assist the second network node or the third network node in positioning the terminal.

[0216] Optionally, the second information / third information may include type information of the first result. The first result is the output result of the AI ​​model, or a result of processing the output result. The type information of the first result may include, for example, time information, power information, and angle information. Time information may include arrival time, power information may include reference signal received power, and angle information may include arrival angle. The first network node may determine the type of the result output by the AI ​​model based on this information.

[0217] Optionally, the second information / third information may include a reporting mechanism for the first result. For example, the first result may be reported periodically or on-demand. That is, the first network node may determine a reporting mechanism for the first result based on the information.

[0218] Optionally, the second information / third information may include reporting resources for the first result. For example, the reporting resources may include time domain resources, frequency domain resources, etc. The first network node may determine which reporting resource to use to report the first result based on the information.

[0219] Optionally, the second information / third information may include parameters for processing the first result. That is, the second network node may directly report the first result for positioning purposes. Alternatively, the first result may be processed to obtain a second result, which may be reported for positioning purposes. The processing of the first result may be based on parameters indicated by the second information / third information. For example, the parameters may include reference time information. Assuming the first result includes the first path arrival time relative to a certain subframe, the first path arrival time at another reference time point can be calculated based on the reference time information.

[0220] Optionally, the second information / third information may include response time information. The response time information is used to instruct the first network node to feedback the first result within the response time information. Of course, it may also refer to feedback of the second result. Instructing the first network node to feedback the first result within the response time information indicates that the first network node is expected to feedback the first result within the response time. If the first network node cannot feedback the first result within the response time, the first network node may also send feedback information about the second information to the second network node requesting AI model-assisted positioning, with the feedback information including a disapproval of the second network node's request. Alternatively, the first network node may send feedback information about the third information to the third network node requesting AI model-assisted positioning, with the feedback information including a disapproval of the third network node's request. Conversely, if the first network node agrees to the second network node's request, the first network node may send feedback information about the second information to the second network node, with the feedback information including an approval of the second network node's request. Alternatively, if the first network node agrees to the third network node's request, the first network node may send feedback information about the third information to the third network node, with the feedback information including an approval of the third network node's request.

[0221] Optionally, the second information / third information may include requirement information. The requirement information is used to indicate the conditions required for AI model-assisted positioning. For example, the requirement information may include the amount of data that the first network node needs to process when performing AI model-assisted positioning; the time interval during which the first network node needs to perform AI model-assisted positioning; and the identifier of the target network node to which the first network node needs to send the first result. Optionally, the requirement information includes the amount of data that the first network node needs to process when performing AI model-assisted positioning. If the first network node is unable to process this amount of data, it may indicate in the feedback information that it does not agree to the request of the second or third network node. Optionally, the requirement information may include the time interval during which the first network node needs to perform AI model-assisted positioning. That is, within this time interval, the first network node needs to report the first result or the second result based on the AI ​​model. If the first network node is unable to report the first result or the second result based on the AI ​​model within this time interval, it may indicate in the feedback message that it does not agree to the request of the second or third network node. Optionally, the requirement information may include the identifier of the target network node to which the first network node needs to send the first result. That is, it indicates to which network node the first network node can send the first result. For example, it may be sent to the second network node, or to the third network node.

[0222] In some embodiments, after receiving the second information, the first network node may determine whether to agree to the second network node's request for AI model-assisted positioning. If the request is agreed, feedback information indicating approval of the request may be sent to the second network node. If the request is not agreed, feedback information indicating disapproval of the request may be sent to the second network node. Accordingly, after receiving the third information, the first network node may determine whether to agree to the third network node's request for AI model-assisted positioning. If the request is agreed, feedback information indicating approval of the request may be sent to the third network node. If the request is not agreed, feedback information indicating disapproval of the request may be sent to the third network node.

[0223] In some embodiments, the names of the second information and the third information are not limited, and may be, for example, "request information" or the like.

[0224] Step S2103 : The second network node 102 sends first information to the first network node 101 .

[0225] In some embodiments, the first network node 101 receives first information sent by the second network node 102 .

[0226] In some embodiments, the first information is used to indicate the measurement information of the terminal by the second network node, as well as the reporting information of the output result of the AI ​​model. The output result of the AI ​​model includes the first result or the second result. The reporting information is used to send the first result, which can be used to send the first result, or it can be used to send the second result after processing the first result. The first result is used by the third network node to locate the terminal. For example, the third network node can locate based on the first result, or it can locate based on the second result after processing the first result.

[0227] In some embodiments, the measurement information indicated by the first information may refer to the above embodiment, and this disclosure will not repeat it. The reporting information of the AI ​​model output result indicated by the first information may include an identifier corresponding to the measurement. The identifier corresponding to the measurement can be used by the third network node to determine which measurement corresponds to the first result or the second result.

[0228] In some embodiments, the measurement corresponding identifier includes at least one of the following: a New Radio Positioning Protocol a (NRPPa) transaction ID; a Location Management Function (LMF) measurement ID; or a Radio Access Network (RAN) measurement ID. The NRPPa transaction ID, LMF measurement ID, and RAN measurement ID can identify the positioning process.

[0229] In some embodiments, the identifier corresponding to the measurement may also include the identifier of the first TRP performing the measurement, the identifier of the cell corresponding to the first TRP, and the identifier of the base station corresponding to the first TRP, that is, the identifier of the second network node.

[0230] In some embodiments, the name of the first information is not limited, and it can be, for example, "instruction information", "configuration information", etc.

[0231] In step S2104 , the first network node 101 obtains a first result based on the measurement information and the AI ​​model.

[0232] In some embodiments, the first network node 101 may input part or all of the measurement information into an AI model to obtain a first result. For example, data such as CIR and PDP may be input into the AI ​​model to obtain intermediate positioning parameters, such as AoA and ToA.

[0233] In some embodiments, the first network node may report the first result, or may process the first result to obtain a second result and report the second result.

[0234] Step S2105 : The first network node 101 sends the first result to the second network node 102 , or the first network node 101 sends the second result to the second network node 102 .

[0235] In some embodiments, the second network node 102 receives the first result or the second result sent by the first network node based on the reporting information.

[0236] In some embodiments, the first network node 101 may send the first result or the second result to the second network node corresponding to the identifier based on the identifier of the second network node in the reporting information.

[0237] In some embodiments, the first result or the second result corresponds to measurement information of a second network node. Therefore, the first network node can send the first result or the second result to the second network node, which in turn sends the first result or the second result to a third network node. The third network node can then determine that the first result or the second result corresponds to the second network node. This improves the accuracy of positioning performed by the third network node based on the first result or the second result. In other words, positioning accuracy is improved and errors are reduced.

[0238] In some embodiments, if the first network node sends a first result to the second network node, the second network node may send the first result to a third network node, or process the first result to obtain a second result, and send the second result to the third network node.

[0239] Step S2106 : The second network node 102 sends the first result or the second result to the third network node 103 .

[0240] In some embodiments, the third network node 103 receives the first result or the second result sent by the second network node 102 .

[0241] In some embodiments, the first result or the second result can be used by a third network node to perform positioning to obtain location information of the terminal.

[0242] Step S2107: The third network node 103 performs positioning based on the first result or the second result to obtain location information.

[0243] In some embodiments, the third network node may perform positioning based on the first result or the second result to obtain location information. For example, the third network node may obtain location information based on a traditional positioning method and the first result or the second result.

[0244] In some embodiments, the first network node can be a gNB deploying an AI model, a base station for inference (gNBx for inference), the second network node can be another base station (gNBy), a gNB not deploying an AI model. The third network node can be a LMF, but this is not limited to this.

[0245] The positioning method involved in the embodiments of the present disclosure may include at least one of steps S2101 to S2107. Steps S2101 to S2107 can each be a separate embodiment. The embodiments can be combined in any manner and implemented in an adjusted order, provided they are not in conflict. For example, steps S2103 and S2104 can be implemented as independent embodiments. For another example, steps S2105 and S2106 can be implemented as independent embodiments, but the present invention is not limited thereto.

[0246] In some embodiments, some steps are optional, and one or more of these steps may be omitted or replaced in different embodiments.

[0247] In some embodiments, reference may be made to other optional implementations described before or after the description corresponding to FIG. 2 a .

[0248] It will be appreciated that the dashed line in FIG2 a indicates that step S2102 is optional. That is, first network node 101 may receive the second information sent by second network node 102, or first network node 101 may receive the third information sent by third network node 103. Although the step of first network node 101 receiving the third information sent by third network node 103 is indicated by a dashed line, there is no priority relationship between the two. Either method may be selected based on actual circumstances, and this disclosure does not impose any limitation.

[0249] FIG2b is a schematic diagram illustrating an interaction of a positioning method according to an embodiment of the present disclosure. As shown in FIG2b , the present disclosure embodiment relates to a positioning method for a communication system 100, the method comprising:

[0250] Step S2201 : The third network node 103 sends fourth information to the second network node 102 .

[0251] The optional implementation of step S2201 can refer to the optional implementation of step S2101 in Figure 2a and other related parts in the embodiment involved in Figure 2a, which will not be repeated here.

[0252] Step S2202 : The second network node 102 sends second information to the first network node 101 , or the third network node 103 sends third information to the first network node.

[0253] The optional implementation of step S2202 can refer to the optional implementation of step S2102 in Figure 2a and other related parts in the embodiment involved in Figure 2a, which will not be repeated here.

[0254] Step S2203 : The second network node 102 sends first information to the first network node 101 .

[0255] The optional implementation of step S2203 can refer to the optional implementation of step S2103 in Figure 2a and other related parts in the embodiment involved in Figure 2a, which will not be repeated here.

[0256] In step S2204 , the first network node 101 obtains a first result based on the measurement information and the AI ​​model.

[0257] The optional implementation of step S2204 can refer to the optional implementation of step S2104 in Figure 2a and other related parts in the embodiment involved in Figure 2a, which will not be repeated here.

[0258] Step S2205 : The first network node 101 sends the first result and reporting information to the third network node 103 , or the first network node 101 sends the second result and reporting information to the third network node 103 .

[0259] In some embodiments, the third network node 103 receives the first result and reporting information, or the second result and reporting information, sent by the first network node 101 .

[0260] In some embodiments, the first result or the second result corresponds to measurement information of the second network node. If the first network node directly sends the first result or the second result to the third network node, the third network node cannot determine which network node, which TRP, which measurement, etc. the measurement information corresponds to. Therefore, in this embodiment, both the first result and the reporting information can be sent to the third network node, or both the second result and the reporting information can be sent to the third network node, so that the third network node can determine which network node, which TRP, which measurement, etc. the first result or the second result corresponds to.

[0261] Step S2206: The third network node 103 performs positioning based on the first result or the second result to obtain location information.

[0262] The optional implementation of step S2206 can refer to the optional implementation of step S2107 in Figure 2a and other related parts in the embodiment involved in Figure 2a, which will not be repeated here.

[0263] The positioning method involved in the embodiments of the present disclosure may include at least one of steps S2201 to S2206. Steps S2201 to S2206 can each be a separate embodiment. The embodiments can be combined in any manner and implemented in an adjusted order, provided they are not in conflict. For example, steps S2203 and S2204 can be implemented as independent embodiments, and step S2205 can be implemented as a separate embodiment, but the present invention is not limited thereto.

[0264] In some embodiments, some steps are optional, and one or more of these steps may be omitted or replaced in different embodiments.

[0265] In some embodiments, reference may be made to other optional implementations described before or after the description corresponding to FIG. 2 b .

[0266] It will be appreciated that the dashed line in FIG2b indicates that step S2202 is optional. That is, first network node 101 may receive the second information sent by second network node 102, or first network node 101 may receive the third information sent by third network node 103. Although the step of first network node 101 receiving the third information sent by third network node 103 is indicated by a dashed line, there is no priority relationship between the two. Either method may be selected based on actual circumstances, and this disclosure does not impose any limitation.

[0267] FIG3a is a flowchart of a positioning method according to an embodiment of the present disclosure. As shown in FIG3a, the embodiment of the present disclosure relates to a positioning method, which is executed by a first network node 101. The method includes:

[0268] Step S3101, obtaining the second information or the third information.

[0269] The optional implementation of step S3101 can refer to the optional implementation of step S2102 in Figure 2a and other related parts in the embodiment involved in Figure 2a, which will not be repeated here.

[0270] In some embodiments, the first network node 101 receives the second information sent by the second network node 102 or receives the third information sent by the third network node 103, but is not limited thereto and may also receive the second information or third information sent by other entities.

[0271] In some embodiments, the first network node 101 obtains the second information or the third information specified by the protocol.

[0272] In some embodiments, the first network node 101 obtains the second information or the third information from an upper layer(s).

[0273] In some embodiments, the first network node 101 performs processing to obtain the second information or the third information.

[0274] In some embodiments, step S3101 is omitted, and the first network node 101 autonomously implements the function indicated by the second information or the third information, or the above function is default or acquiescent.

[0275] Step S3102, obtaining first information.

[0276] The optional implementation of step S3102 can refer to the optional implementation of step S2103 in Figure 2a and other related parts in the embodiment involved in Figure 2a, which will not be repeated here.

[0277] In some embodiments, the first network node 101 receives the first information sent by the second network node 102, but is not limited thereto. The first information sent by other entities may also be received.

[0278] In some embodiments, the first network node 101 obtains first information specified by a protocol.

[0279] In some embodiments, the first network node 101 obtains the first information from an upper layer(s).

[0280] In some embodiments, the first network node 101 performs processing to obtain the first information.

[0281] In some embodiments, step S3102 is omitted, and the first network node 101 autonomously implements the function indicated by the first information, or the above function is default or by default.

[0282] Step S3103: Obtain a first result based on the measurement information and the AI ​​model.

[0283] The optional implementation of step S3103 can refer to the optional implementation of step S2104 in Figure 2a and other related parts in the embodiment involved in Figure 2a, which will not be repeated here.

[0284] In some embodiments, the first result is obtained based on the measurement information and the AI ​​model.

[0285] Step S3104: Send the first result or the second result.

[0286] The optional implementation of step S3104 can refer to the optional implementation of step S2105 in Figure 2a and other related parts in the embodiment involved in Figure 2a, which will not be repeated here.

[0287] In some embodiments, the first network node 101 sends the first result or the second result to the second network node 102 , but is not limited thereto. The first result or the second result may also be sent to other entities.

[0288] The positioning method involved in the embodiments of the present disclosure may include at least one of steps S3101 to S3104. Each of steps S3101 to S3104 can be implemented as a separate embodiment. The embodiments can be combined in any manner and implemented in a different order, provided they are not in conflict. For example, steps S3102 and S3103 can be implemented as separate embodiments, but are not limited thereto.

[0289] In some embodiments, some steps are optional, and one or more of these steps may be omitted or replaced in different embodiments.

[0290] In some embodiments, reference may be made to other optional implementations described before or after the description corresponding to FIG. 3 a .

[0291] FIG3b is a flowchart of a positioning method according to an embodiment of the present disclosure. As shown in FIG3b , the embodiment of the present disclosure relates to a positioning method, which is executed by the first network node 101. The method includes:

[0292] Step S3201, obtaining the second information or the third information.

[0293] The optional implementation of step S3201 can refer to the optional implementation of step S2102 in Figure 2a and other related parts in the embodiment involved in Figure 2a, which will not be repeated here.

[0294] In some embodiments, the first network node 101 receives the second information sent by the second network node 102 or receives the third information sent by the third network node 103, but is not limited thereto and may also receive the second information or third information sent by other entities.

[0295] In some embodiments, the first network node 101 obtains the second information or the third information specified by the protocol.

[0296] In some embodiments, the first network node 101 obtains the second information or the third information from an upper layer(s).

[0297] In some embodiments, the first network node 101 performs processing to obtain the second information or the third information.

[0298] In some embodiments, step S3201 is omitted, and the first network node 101 autonomously implements the function indicated by the second information or the third information, or the above function is default or acquiescent.

[0299] Step S3202, obtain first information.

[0300] The optional implementation of step S3202 can refer to the optional implementation of step S2103 in Figure 2a and other related parts in the embodiment involved in Figure 2a, which will not be repeated here.

[0301] In some embodiments, the first network node 101 receives the first information sent by the second network node 102, but is not limited thereto. The first information sent by other entities may also be received.

[0302] In some embodiments, the first network node 101 obtains first information specified by a protocol.

[0303] In some embodiments, the first network node 101 obtains the first information from an upper layer(s).

[0304] In some embodiments, the first network node 101 performs processing to obtain the first information.

[0305] In some embodiments, step S3202 is omitted, and the first network node 101 autonomously implements the function indicated by the first information, or the above function is default or by default.

[0306] Step S3203: Obtain a first result based on the measurement information and the AI ​​model.

[0307] The optional implementation of step S3203 can refer to the optional implementation of step S2104 in Figure 2a and other related parts in the embodiment involved in Figure 2a, which will not be repeated here.

[0308] In some embodiments, the first result is obtained based on the measurement information and the AI ​​model.

[0309] Step S3204: Send the first result and report information, or send the second result and report information.

[0310] The optional implementation of step S3204 can refer to the optional implementation of step S2205 in Figure 2b and other related parts in the embodiment involved in Figure 2a, which will not be repeated here.

[0311] In some embodiments, the first network node 101 sends the first result and reporting information, or sends the second result and reporting information to the third network node 102, but is not limited thereto. The first result and reporting information, or the second result and reporting information may also be sent to other entities.

[0312] FIG3c is a flowchart of a positioning method according to an embodiment of the present disclosure. As shown in FIG3c, the embodiment of the present disclosure relates to a positioning method, which is executed by the first network node 101. The method includes:

[0313] Step S3301, obtain first information.

[0314] The optional implementation of step S3301 can refer to the optional implementation of step S2103 in Figure 2a and other related parts in the embodiment involved in Figure 2a, which will not be repeated here.

[0315] In some embodiments, the first network node 101 receives the first information sent by the second network node 102, but is not limited thereto. The first information sent by other entities may also be received.

[0316] In some embodiments, the first network node 101 obtains first information specified by a protocol.

[0317] In some embodiments, the first network node 101 obtains the first information from an upper layer(s).

[0318] In some embodiments, the first network node 101 performs processing to obtain the first information.

[0319] In some embodiments, step S3301 is omitted, and the first network node 101 autonomously implements the function indicated by the first information, or the above function is default or by default.

[0320] Step S3302: Obtain a first result based on the measurement information and the AI ​​model.

[0321] The optional implementation of step S3302 can refer to the optional implementation of step S2104 in Figure 2a and other related parts in the embodiment involved in Figure 2a, which will not be repeated here.

[0322] In some embodiments, the first result is obtained based on the measurement information and the AI ​​model.

[0323] FIG4a is a flowchart of a positioning method according to an embodiment of the present disclosure. As shown in FIG4a , the embodiment of the present disclosure relates to a positioning method, which is executed by the second network node 102 and includes:

[0324] Step S4101, obtain the fourth information.

[0325] The optional implementation of step S4101 can refer to the optional implementation of step S2101 in Figure 2a and other related parts in the embodiment involved in Figure 2a, which will not be repeated here.

[0326] In some embodiments, the second network node 102 receives the fourth information sent by the third network node 103 , but is not limited thereto. The second network node 102 may also receive the fourth information sent by other entities.

[0327] In some embodiments, the second network node 102 obtains fourth information specified by the protocol.

[0328] In some embodiments, the second network node 102 obtains the fourth information from an upper layer(s).

[0329] In some embodiments, the second network node 102 performs processing to obtain the fourth information.

[0330] In some embodiments, step S4101 is omitted, and the second network node 102 autonomously implements the function indicated by the fourth information, or the above function is default or by default.

[0331] Step S4102, sending the second information.

[0332] The optional implementation of step S4102 can refer to the optional implementation of step S2102 in Figure 2a and other related parts in the embodiment involved in Figure 2a, which will not be repeated here.

[0333] In some embodiments, the second network node 102 sends the second information to the first network node 101 , but is not limited thereto. The second information may also be sent to other entities.

[0334] Step S4103, sending the first information.

[0335] The optional implementation of step S4103 can refer to the optional implementation of step S2103 in Figure 2a and other related parts in the embodiment involved in Figure 2a, which will not be repeated here.

[0336] In some embodiments, the second network node 102 sends the first information to the first network node 101 , but is not limited thereto. The first information may also be sent to other entities.

[0337] Step S4104, obtaining the first result or the second result.

[0338] The optional implementation of step S4104 can refer to the optional implementation of step S2105 in Figure 2a and other related parts in the embodiment involved in Figure 2a, which will not be repeated here.

[0339] In some embodiments, the second network node 102 receives the first result or the second result sent by the first network node 101 , but is not limited thereto and may also receive the first result or the second result sent by other entities.

[0340] In some embodiments, the second network node 102 obtains the first result or the second result specified by the protocol.

[0341] In some embodiments, the second network node 102 obtains the first result or the second result from an upper layer(s).

[0342] In some embodiments, the second network node 102 performs processing to obtain the first result or the second result.

[0343] In some embodiments, step S4104 is omitted, and the second network node 102 autonomously implements the function indicated by the first result or the second result, or the above function is default or by default.

[0344] Step S4105: Send the first result or the second result.

[0345] The optional implementation of step S4105 can refer to the optional implementation of step S2106 in Figure 2a and other related parts in the embodiment involved in Figure 2a, which will not be repeated here.

[0346] In some embodiments, the second network node 102 sends the first result or the second result to the third network node 103 , but is not limited thereto. The first result or the second result may also be sent to other entities.

[0347] FIG4 b is a flowchart of a positioning method according to an embodiment of the present disclosure. As shown in FIG4 b , the embodiment of the present disclosure relates to a positioning method, which is executed by the second network node 102. The method includes:

[0348] Step S4201, obtain the fourth information.

[0349] The optional implementation of step S4201 can refer to the optional implementation of step S2101 in Figure 2a and other related parts in the embodiment involved in Figure 2a, which will not be repeated here.

[0350] In some embodiments, the second network node 102 receives the fourth information sent by the third network node 103 , but is not limited thereto. The second network node 102 may also receive the fourth information sent by other entities.

[0351] In some embodiments, the second network node 102 obtains fourth information specified by the protocol.

[0352] In some embodiments, the second network node 102 obtains the fourth information from an upper layer(s).

[0353] In some embodiments, the second network node 102 performs processing to obtain the fourth information.

[0354] In some embodiments, step S4201 is omitted, and the second network node 102 autonomously implements the function indicated by the fourth information, or the above function is default or by default.

[0355] Step S4202, sending the second information.

[0356] The optional implementation of step S4202 can refer to the optional implementation of step S2102 in Figure 2a and other related parts in the embodiment involved in Figure 2a, which will not be repeated here.

[0357] In some embodiments, the second network node 102 sends the second information to the first network node 101 , but is not limited thereto. The second information may also be sent to other entities.

[0358] Step S4203, sending the first information.

[0359] The optional implementation of step S4203 can refer to the optional implementation of step S2103 in Figure 2a and other related parts in the embodiment involved in Figure 2a, which will not be repeated here.

[0360] In some embodiments, the second network node 102 sends the first information to the first network node 101 , but is not limited thereto. The first information may also be sent to other entities.

[0361] FIG4c is a flowchart of a positioning method according to an embodiment of the present disclosure. As shown in FIG4c , the embodiment of the present disclosure relates to a positioning method, which is executed by the second network node 102. The method includes:

[0362] Step S4301, sending the first information.

[0363] The optional implementation of step S4301 can refer to the optional implementation of step S2103 in Figure 2a and other related parts in the embodiment involved in Figure 2a, which will not be repeated here.

[0364] In some embodiments, the second network node 102 sends the first information to the first network node 101 , but is not limited thereto. The first information may also be sent to other entities.

[0365] FIG5a is a flowchart of a positioning method according to an embodiment of the present disclosure. As shown in FIG5a, the embodiment of the present disclosure relates to a positioning method, which is executed by the third network node 103. The method includes:

[0366] Step S5101, sending the fourth information.

[0367] The optional implementation of step S5101 can refer to the optional implementation of step S2101 in Figure 2a and other related parts in the embodiment involved in Figure 2a, which will not be repeated here.

[0368] In some embodiments, the third network node 103 sends the fourth information to the second network node 102 , but is not limited thereto. The fourth information may also be sent to other entities.

[0369] Step S5102, sending the third information.

[0370] The optional implementation of step S5102 can refer to the optional implementation of step S2102 in Figure 2a and other related parts in the embodiment involved in Figure 2a, which will not be repeated here.

[0371] In some embodiments, the third network node 103 sends the third information to the first network node 101 , but is not limited thereto. The third information may also be sent to other entities.

[0372] Step S5103, obtaining the first result or the second result.

[0373] The optional implementation of step S5103 can refer to the optional implementation of step S2106 in Figure 2a and other related parts in the embodiment involved in Figure 2a, which will not be repeated here.

[0374] In some embodiments, the third network node 103 receives the first result or the second result sent by the second network node 102 , but is not limited thereto. The third network node 103 may also receive the first result or the second result sent by other entities.

[0375] In some embodiments, the third network node 103 obtains the first result or the second result specified by the protocol.

[0376] In some embodiments, the third network node 103 obtains the first result or the second result from an upper layer(s).

[0377] In some embodiments, the third network node 103 performs processing to obtain the first result or the second result.

[0378] In some embodiments, step S5103 is omitted, and the third network node 103 autonomously implements the function indicated by the first result or the second result, or the above function is default or acquiescent.

[0379] Step S5104: Perform positioning based on the first result or the second result to obtain location information.

[0380] The optional implementation of step S5104 can refer to the optional implementation of step S2107 in Figure 2a and other related parts in the embodiment involved in Figure 2a, which will not be repeated here.

[0381] In some embodiments, the location information is obtained by positioning based on the first result or the second result.

[0382] FIG5b is a flowchart of a positioning method according to an embodiment of the present disclosure. As shown in FIG5b , the embodiment of the present disclosure relates to a positioning method, which is executed by the third network node 103. The method includes:

[0383] Step S5201, sending the fourth information.

[0384] The optional implementation of step S5201 can refer to the optional implementation of step S2101 in Figure 2a and other related parts in the embodiment involved in Figure 2a, which will not be repeated here.

[0385] In some embodiments, the third network node 103 sends the fourth information to the second network node 102 , but is not limited thereto. The fourth information may also be sent to other entities.

[0386] Step S5202, sending the third information.

[0387] The optional implementation of step S5202 can refer to the optional implementation of step S2102 in Figure 2a and other related parts in the embodiment involved in Figure 2a, which will not be repeated here.

[0388] In some embodiments, the third network node 103 sends the third information to the first network node 101 , but is not limited thereto. The third information may also be sent to other entities.

[0389] Step S5203: Obtain the first result and reporting information, or the second result and reporting information.

[0390] The optional implementation of step S5203 can refer to the optional implementation of step S2205 in Figure 2b and other related parts in the embodiment involved in Figure 2a, which will not be repeated here.

[0391] In some embodiments, the third network node 103 receives the first result and reporting information, or the second result and reporting information, sent by the first network node 101, but is not limited thereto and may also receive the first result and reporting information, or the second result and reporting information, sent by other entities.

[0392] In some embodiments, the third network node 103 obtains the first result and reporting information, or the second result and reporting information specified by the protocol.

[0393] In some embodiments, the third network node 103 obtains the first result and reporting information, or the second result and reporting information from an upper layer(s).

[0394] In some embodiments, the third network node 103 performs processing to obtain the first result and reporting information, or the second result and reporting information.

[0395] In some embodiments, step S5203 is omitted, and the third network node 103 autonomously implements the functions indicated by the first result and reported information, or the second result and reported information, or the above functions are default or acquiescent.

[0396] Step S5204: Perform positioning based on the first result or the second result to obtain location information.

[0397] The optional implementation of step S5204 can refer to the optional implementation of step S2107 in Figure 2a and other related parts in the embodiment involved in Figure 2a, which will not be repeated here.

[0398] Figure 6 is a schematic diagram of an interaction of a positioning method according to an embodiment of the present disclosure. As shown in Figure 6, an embodiment of the present disclosure relates to a positioning method for a communication system, the method comprising:

[0399] Step S6101 : The second network node 102 sends first information to the first network node 101 .

[0400] In some embodiments, the above method may include the method of the above embodiments related to the communication system 100, the first network node 101, the second network node 102 and the third network node 103, etc., which will not be repeated here.

[0401] Step S6102 : The first network node 101 receives first information sent by the second network node 102 .

[0402] In some embodiments, the above method may include the method of the above embodiments related to the communication system 100, the first network node 101, the second network node 102 and the third network node 103, etc., which will not be repeated here.

[0403] In step S6103 , the first network node 101 obtains a first result based on the measurement information and the AI ​​model.

[0404] In some embodiments, the above method may include the method of the above embodiments related to the communication system 100, the first network node 101, the second network node 102 and the third network node 103, etc., which will not be repeated here.

[0405] Step S6104: The first network node 101 sends a first result based on the reported information.

[0406] In some embodiments, the above method may include the method of the above embodiments related to the communication system 100, the first network node 101, the second network node 102 and the third network node 103, etc., which will not be repeated here.

[0407] Step S6105: The third network node 103 receives the first result.

[0408] In some embodiments, the above method may include the method of the above embodiments related to the communication system 100, the first network node 101, the second network node 102 and the third network node 103, etc., which will not be repeated here.

[0409] The present disclosure provides a positioning method as follows:

[0410] In some embodiments, the positioning method is applied to a first network node, where the first network node deploys an AI model and performs an AI-based positioning operation. The AI-based positioning operation includes the following steps:

[0411] 1) Receiving first information from the second network node, where the first information includes measurement information for AI model input. Optionally, the first information may also include reporting information for AI model output results, such as an NRPPa transaction ID, LMF measurement ID, and RAN measurement ID between the second network node and the third network node.

[0412] 2) Using the measurement information or using input information obtained based on the measurement information, reasoning based on the AI ​​model to obtain a first result.

[0413] 3) Sending a first result or a second result, where the first result includes the output result of the AI ​​model, and the second result includes other results obtained based on the output result of the AI ​​model.

[0414] In some embodiments, examples of information included in the first result include:

[0415] The base station identity (ID) of the TRP is used to indicate the base station identity of the TRP where the measurement is performed, such as the next generation radio access network node identity (NG-RAN node identity);

[0416] TRP identifier, used to uniquely identify a TRP within a base station;

[0417] Cell ID, used to indicate the cell where the TRP is located;

[0418] NRPPa Transaction ID, used to uniquely identify a transaction or interaction in the New Radio Positioning Protocol a (NRPPa);

[0419] RAN measurement ID, used to uniquely identify a measurement in a base station or TRP;

[0420] LMF measurement ID, used to uniquely identify a measurement in LMF;

[0421] TRP measurement data is used to indicate TRP measurement data, wherein the TRP measurement data includes at least one of the following information:

[0422] TRP measurement data values ​​include, but are not limited to, the following measurement values:

[0423] CIR;

[0424] PDP;

[0425] DP;

[0426] Angle of Arrival;

[0427] SRS-RSRP;

[0428] RTOA;

[0429] gNB Rx-Tx Time Difference;

[0430] Z-AoA, for example, Z-AoA, multiple UL-AoA.

[0431] Timestamp, indicating the time of measurement

[0432] Measurement quality, used to indicate the quality of the measurement, for example, it may be information on the accuracy of the measurement;

[0433] Measurement beam information, used to indicate the receiving beam information when receiving the uplink positioning signal, such as SSB, PRS;

[0434] Positioning signal type, used to indicate the type of positioning signal received, such as SRS, pos-SRS, etc.

[0435] LoS / NLoS information, used to indicate LoS or NLoS information when receiving positioning signals;

[0436] In some embodiments, sending the first result includes any one of the following options:

[0437] Sending the first information to a second network node, where the second network node is a node that sends the first information to the first network node;

[0438] Alternatively, the message is sent to a third network node, where the third network node is another node different from the first network node and the second network node.

[0439] For ease of understanding, the embodiments of the present disclosure will provide an exemplary illustration of the positioning method based on Figures 7a, 7b, and 7c. The communication system involved in the positioning method includes multiple different network nodes, which are described as a first network node, a second network node, and a third network node for ease of description. It should be noted that in Figures 7a, 7b, 7c, and related embodiments, the first network node includes a gNB deploying an AI model and a base station for inference (gNBx for inference). The second network node can be another base station (gNBy) or a gNB without an AI model deployed. The third network node can be a LMF. However, this is not limited to this.

[0440] Figure 7a is a schematic diagram illustrating interactions in a positioning method according to an exemplary embodiment of the present disclosure. As shown in Figure 7a , the positioning method, executed by communication system 100, includes: a third network node sending fourth information to a second network node; and the second network node sending second information and first information to a first network node. The first network node performs model inference and sends either the first result or the second result to the second network node. The second network node may send the second result to the third network node for positioning purposes.

[0441] In some embodiments, in response to the first network node sending the first result to the second network node, the second network node sends the second result to the third network node, wherein the second result includes the first result or another result obtained based on the first result.

[0442] The second result example is the same as the first result example.

[0443] In some embodiments, the method further includes the first network node receiving second information sent by the second network node, where the second information is used to request AI-related processing, and the information includes at least one of the following information:

[0444] Requests for AI processing;

[0445] Configuration information about the AI ​​model output type, for example, whether the output is time-related information such as TOA, power information such as RSRP, or angle information such as AoA;

[0446] Response time information, that is, the second network node expects the first network node to feedback the first result within the response time;

[0447] AI processing requirements, such as the amount of data to be processed, the processing time (i.e., the time interval), and the output target node information. For example, LMF identification or NG-RAN node identification.

[0448] In some embodiments, the request for AI processing may be, for example, a request for assisted positioning based on an AI model.

[0449] In some embodiments, the configuration information of the AI ​​model output type may be type information of the first result.

[0450] In some embodiments, the second information is included in an Xn application protocol (XnAP) message, for example, the XnAP message is an AI reasoning request message.

[0451] In some embodiments, the method further includes: the first network node sending fifth information to the second network node, where the fifth information is used to provide feedback on whether the first network node agrees to perform AI-related processing.

[0452] The fifth information is included in the XnAP message. For example, the XnAP message is an AI reasoning feedback message.

[0453] In some embodiments, the method further includes receiving fourth information from the third network node, where the fourth information includes any one of the following information:

[0454] gNB ID where the TRP is located;

[0455] TRP ID;

[0456] Cell ID, for example, the ID of the cell where the TRP is located;

[0457] Measurement result type configuration, including: Angle of Arrival, SRS-RSRP, RTOA, gNB Rx-Tx Time Difference, Z-AoA, such as Z-AoA, multiple UL-AoA;

[0458] Measurement result reporting configuration: such as periodic reporting, on-demand reporting, and reporting resources;

[0459] Information about the network node where AI inference occurs, such as the node identifier of the first network node, NG-RAN node identity.

[0460] In some embodiments, the fourth information is included in an NRPPa message, for example, it may be a measurement request (Measurement Request) signaling.

[0461] In some embodiments, the first network node can be a gNB deploying an AI model, a base station for inference (gNBx for inference), the second network node can be another base station (gNBy), a gNB not deploying an AI model. The third network node can be a LMF, but this is not limited to this.

[0462] Figure 7b is a schematic diagram illustrating interactions in a positioning method according to an exemplary embodiment of the present disclosure. As shown in Figure 7b , the positioning method includes: a third network node sending fourth information to a second network node, which in turn sends third information to a first network node. The second network node sends first information to the first network node. The first network node performs model inference and sends the first or second result to the third network node for positioning.

[0463] In some embodiments, in response to the first network node sending the second result to the third network node, the method further includes the first network node receiving third information from the third network node, where the third information is used to configure information for performing AI operations and result reporting on the second network node, and the third information includes any one of the following information:

[0464] A request for AI processing and an identifier of the second network node involved, including a TRP ID and a cell ID;

[0465] Configuration information about the AI ​​model output type, for example, whether the output is time-related information such as TOA, power information such as RSRP, or angle information such as AoA;

[0466] Response time information, that is, the second network node expects the first network node to feedback the first result within the response time;

[0467] AI processing requirements, such as the amount of data to be processed, the processing time (i.e., the time interval), and the output target node information. For example, LMF identification or NG-RAN node identification;

[0468] Measurement result reporting configuration: such as periodic reporting, on-demand reporting, and reporting resources;

[0469] Other parameters used to calculate the first result, such as reference time information, etc.

[0470] In some embodiments, the method further includes the first network node receiving fourth information from the third network node, where an example of the fourth information is the same as the aforementioned fourth information.

[0471] In some embodiments, the first network node can be a gNB deploying an AI model, a base station for inference (gNBx for inference), the second network node can be another base station (gNBy), a gNB not deploying an AI model. The third network node can be a LMF, but this is not limited to this.

[0472] Figure 7c is a schematic diagram illustrating interactions in a positioning method according to an exemplary embodiment of the present disclosure. As shown in Figure 7c, the positioning method includes: a third network node sending fourth information to a second network node; the second network node sending second information and first information to a first network node; the first network node performing model inference and sending either the first result or the second result to the third network node for positioning.

[0473] In some embodiments, in response to the first network node sending the second result to the third network node, the method further includes the second network node receiving fourth information from the third network node, where the fourth information is used to configure the second network node to perform corresponding measurements and report information.

[0474] The fourth information includes:

[0475] gNB ID where the TRP is located;

[0476] TRP ID;

[0477] Cell ID, for example, the ID of the cell where the TRP is located;

[0478] Measurement result type configuration, including: Angle of Arrival, SRS-RSRP, RTOA, gNB Rx-Tx Time Difference, Z-AoA, such as Z-AoA, multiple UL-AoA;

[0479] Measurement result reporting configuration: such as periodic reporting, on-demand reporting, and reporting resources;

[0480] Information about the network node where AI inference occurs, such as the node identifier of the first network node, NG-RAN node identity.

[0481] In some embodiments, the method further includes the first network node receiving second information from the second network node, the second information including:

[0482] Requests for AI processing;

[0483] Configuration information about the AI ​​model output type, for example, whether the output is time-related information such as TOA, power information such as RSRP, or angle information such as AoA;

[0484] Response time information, that is, the second network node expects the first network node to feedback the first result within the response time;

[0485] AI processing requirements, such as the amount of data to be processed, the processing time (i.e., the time interval), and the output target node information. For example, LMF identification or NG-RAN node identification.

[0486] In some embodiments, the first network node can be a gNB deploying an AI model, a base station for inference (gNBx for inference), the second network node can be another base station (gNBy), a gNB not deploying an AI model. The third network node can be a LMF, but this is not limited to this.

[0487] Figure 8a is a schematic diagram of the structure of the first network node proposed in an embodiment of the present disclosure. As shown in Figure 8a, the first network node 7100 may include: a transceiver module 7101 and a processing module 7102. The transceiver module 7101 is used to receive first information sent by the second network node, and the first information is used to indicate the second network node's measurement information on the terminal, as well as the reporting information of the output result of the artificial intelligence (AI) model. The processing module 7102 is used to obtain a first result based on the measurement information and the AI ​​model; wherein the reporting information is used to send the first result, and the first result is used by the third network node to locate the terminal.

[0488] In some embodiments, the transceiver module 7101 is further configured to send the first result and the reporting information to a third network node. Alternatively, the processing module 7102 is further configured to process the first result to obtain a second result, and the transceiver module 7101 is further configured to send the second result and the reporting information to the third network node.

[0489] In some embodiments, the transceiver module 7101 is further configured to: send the first result to the second network node based on the reported information. Alternatively, the processing module 7102 is further configured to: process the first result to obtain a second result, and the transceiver module 7101 is further configured to: send the second result to the second network node based on the reported information.

[0490] In some embodiments, the reported information includes an identifier corresponding to the measurement information.

[0491] In some embodiments, the identifier includes at least one of the following: a new air interface positioning protocol a identifier, a positioning management function measurement identifier, and a radio access network measurement identifier.

[0492] In some embodiments, the measurement information includes at least one of the following: measurement data of the terminal from the first transmission point (TRP) of the second network node; an identifier of the second network node; an identifier of the first TRP; an identifier of the cell in which the first TRP is located; a timestamp indicating the time of measurement; a quality of the measurement; a type of positioning signal used to measure and obtain the measurement data; beam information indicating the beam used to receive the positioning signal; line-of-sight information indicating line-of-sight when receiving the positioning signal; and non-line-of-sight information indicating non-line-of-sight when receiving the positioning signal.

[0493] In some embodiments, the method module is further configured to: receive second information sent by a second network node, the second information being used to request the first network node to perform assisted positioning based on the AI ​​model; or receive third information sent by a third network node, the third information being used to request the first network node to perform assisted positioning based on the AI ​​model.

[0494] In some embodiments, the second information and the third information include at least one of the following: information requesting the first network node to perform AI model-assisted positioning; a type of the first result; a reporting mechanism for the first result; a reporting resource for the first result; parameters for processing the first result; response time information, the response time information being used to instruct the first network node to feedback the first result within the response time information; and requirement information, the requirement information being used to indicate conditions required for AI model-assisted positioning.

[0495] In some embodiments, the type information of the first result includes at least one of the following: time information, power information, and angle information.

[0496] In some embodiments, the requirement information includes at least one of the following: the amount of data that the first network node needs to process when performing AI model-assisted positioning; the time interval during which the first network node needs to perform AI model-assisted positioning; and the identifier of the target network node to which the first network node needs to send the first result.

[0497] In some embodiments, the measurement information is obtained based on fourth information sent by the third network node to the second network node, where the fourth information includes at least one of the following: an identifier of a second TRP for which measurement is to be performed; an identifier of a base station where the second TRP is located; an identifier of a cell where the second TRP is located; a type of measurement data; a reporting mechanism for the measurement data; and a reporting resource for the measurement data.

[0498] In some embodiments, the fourth information is further used to indicate an identifier of the first network node.

[0499] In some embodiments, the parameters include reference time information.

[0500] Figure 8b is a schematic diagram of the structure of the second network node proposed in an embodiment of the present disclosure. As shown in Figure 8b, the second network node 7200 may include: a transceiver module 7201, which is used to send first information to the first network node, where the first information is used to indicate the second network node's measurement information on the terminal, as well as reporting information of the output result of the artificial intelligence (AI) model. The measurement information is used by the first network node to obtain the first result based on the AI ​​model, and the reporting information is used to send the first result, which is used by the third network node to locate the terminal.

[0501] In some embodiments, the transceiver module 7201 is further configured to receive a first result or a second result sent by a first network node, where the first result or the second result is sent based on the reported information, and to send the first result or the second result to a third network node. Alternatively, the network node further includes a processing module 7202 configured to process the first result to obtain a third result, and the transceiver module is further configured to send the third result to the third network node.

[0502] In some embodiments, the reported information includes an identifier corresponding to the measurement information.

[0503] In some embodiments, the identifier includes at least one of the following: a new air interface positioning protocol a identifier, a positioning management function measurement identifier, and a radio access network measurement identifier.

[0504] In some embodiments, the measurement information includes at least one of the following: measurement data of the terminal from the first transmission point (TRP) of the second network node; an identifier of the second network node; an identifier of the first TRP; an identifier of the cell in which the first TRP is located; a timestamp indicating the time of measurement; a quality of the measurement; a type of positioning signal used to measure and obtain the measurement data; beam information indicating the beam used to receive the positioning signal; line-of-sight information indicating line-of-sight when receiving the positioning signal; and non-line-of-sight information indicating non-line-of-sight when receiving the positioning signal.

[0505] In some embodiments, the transceiver module 7201 is further used to: send second information to the first network node, where the second information is used to request the first network node to assist in positioning based on the AI ​​model.

[0506] In some embodiments, the second information includes at least one of the following: information requesting the first network node to perform AI model-assisted positioning; a type of the first result; a reporting mechanism for the first result; a reporting resource for the first result; parameters for processing the first result; response time information, the response time information being used to instruct the first network node to feedback the first result within the response time information; and requirement information, the requirement information being used to indicate conditions required for AI model-assisted positioning.

[0507] In some embodiments, the type information of the first result includes at least one of the following: time information, power information, and angle information.

[0508] In some embodiments, the requirement information includes at least one of the following: the amount of data that the first network node needs to process when performing AI model-assisted positioning; the time interval during which the first network node needs to perform AI model-assisted positioning; and the identifier of the target network node to which the first network node needs to send the first result.

[0509] In some embodiments, the transceiver module 7201 is further configured to: receive fourth information sent by a third network node, the fourth information being used to determine measurement information, the fourth information including at least one of the following: an identifier of a second TRP for which measurement is to be performed; an identifier of a base station where the second TRP is located; an identifier of a cell where the second TRP is located; a type of measurement data; a reporting mechanism for the measurement data; and a reporting resource for the measurement data.

[0510] In some embodiments, the fourth information is further used to indicate an identifier of the first network node.

[0511] In some embodiments, the parameters include reference time information.

[0512] Figure 8c is a schematic diagram of the structure of the third network node proposed in an embodiment of the present disclosure. As shown in Figure 8b, the third network node 7300 may include: a transceiver module 7301, configured to receive a first result, the first result used to locate the terminal; wherein the first result is obtained based on measurement information and an AI model, the first result is sent based on reporting information of the AI ​​model output result, and the measurement information and reporting information are sent by the second network node to the first network node as a first information indication.

[0513] In some embodiments, the transceiver module 7301 receives the first result in the following manner: receiving the first result and reporting information sent by the first network node; or receiving the second result and reporting information sent by the first network node, where the second result is obtained by the first network node processing the first result.

[0514] In some embodiments, the transceiver module 7301 receives the first result in the following manner: receiving the first result or the second result sent by the second network node; wherein the first result or the second result is sent by the first network node to the second network node based on the reported information, and the second result is obtained based on processing the first result.

[0515] In some embodiments, the reported information includes an identifier corresponding to the measurement information.

[0516] In some embodiments, the identifier includes at least one of the following: a new air interface positioning protocol a identifier; a positioning management function measurement identifier; and a radio access network measurement identifier.

[0517] In some embodiments, the measurement information includes at least one of the following: measurement data of the terminal by the first transmission point TRP of the second network node; an identifier of the second network node; an identifier of the first TRP; an identifier of the cell where the first TRP is located; a timestamp, where the timestamp is used to indicate the time of measurement; the quality of the measurement; the type of the positioning signal, where the positioning signal is used to measure and obtain the measurement data; beam information, where the beam information is used to indicate the beam for receiving the positioning signal; line-of-sight information, where the line-of-sight information is used to indicate the line-of-sight when receiving the positioning signal; and non-line-of-sight information, where the non-line-of-sight information is used to indicate the non-line-of-sight when receiving the positioning signal.

[0518] In some embodiments, the transceiver module 7301 is also used to: send fourth information to the second network node, the fourth information including at least one of the following: an identifier of the second TRP that needs to be measured; an identifier of the base station where the second TRP is located; an identifier of the cell where the second TRP is located; the type of measurement data; a reporting mechanism for the measurement data; and a reporting resource for the measurement data.

[0519] In some embodiments, the fourth information is further used to indicate an identifier of the first network node.

[0520] In some embodiments, the third network node 7300 may further include a processing module 7302 configured to execute the steps in the above embodiments. For example, the processing module 7302 is configured to perform positioning based on the first result or the second result to obtain location information.

[0521] Figure 9a is a schematic diagram of the structure of a communication device 8100 proposed in an embodiment of the present disclosure. Communication device 8100 can be a network device, a terminal, a chip, a chip system, or a processor that supports a network device in implementing any of the above methods, or a chip, a chip system, or a processor that supports a terminal in implementing any of the above methods. Optionally, the network device can be an access network device, a core network device, or the like. Optionally, the terminal can be a user equipment, or the like. Communication device 8100 can be used to implement the methods described in the above method embodiments. For details, please refer to the description of the above method embodiments.

[0522] As shown in Figure 9a, communication device 8100 includes one or more processors 8101. Processor 8101 can be a general-purpose processor or a dedicated processor, for example, a baseband processor or a central processing unit. The baseband processor can be used to process communication protocols and communication data, while the central processing unit can be used to control the communication device, execute programs, and process program data. Communication device 8100 is used to perform any of the above methods. Optionally, the communication device can be a base station, a baseband chip, a terminal device, a terminal device chip, a DU or CU, etc.

[0523] In some embodiments, the communication device 8100 further includes one or more memories 8102 for storing instructions. Optionally, all or part of the memories 8102 may be located outside the communication device 8100.

[0524] In some embodiments, the communication device 8100 further includes one or more transceivers 8103. When the communication device 8100 includes one or more transceivers 8103, the transceiver 8103 performs the communication step S2101 such as sending and / or receiving in the above method, and the processor 8101 performs other steps.

[0525] In some embodiments, a transceiver may include a receiver and / or a transmitter. The receiver and transmitter may be separate or integrated. Optionally, the terms transceiver, transceiver unit, transceiver, and transceiver circuit may be used interchangeably; the terms transmitter, transmitting unit, transmitter, and transmitting circuit may be used interchangeably; and the terms receiver, receiving unit, receiver, and receiving circuit may be used interchangeably.

[0526] In some embodiments, the communication device 8100 may include one or more interface circuits 8104. Optionally, the interface circuit 8104 is connected to the memory 8102. The interface circuit 8104 may be configured to receive signals from the memory 8102 or other devices, and may be configured to send signals to the memory 8102 or other devices. For example, the interface circuit 8104 may read instructions stored in the memory 8102 and send the instructions to the processor 8101.

[0527] The communication device 8100 described in the above embodiment may be a network device or a terminal, but the scope of the communication device 8100 described in the present disclosure is not limited thereto, and the structure of the communication device 8100 may not be limited by FIG. 9a. The communication device may be an independent device or may be part of a larger device. For example, the communication device may be: 1) an independent integrated circuit IC, or a chip, or a chip system or subsystem; (2) a collection of one or more ICs, optionally, the above IC collection may also include a storage component for storing data or programs; (3) an ASIC, such as a modem; (4) a module that can be embedded in other devices; (5) a receiver, a terminal device, an intelligent terminal device, a cellular phone, a wireless device, a handheld device, a mobile unit, an in-vehicle device, a network device, a cloud device, an artificial intelligence device, etc.; (6) others, etc.

[0528] FIG9 b is a schematic diagram of the structure of the chip 8200 proposed in an embodiment of the present disclosure. If the communication device 8100 can be a chip or a chip system, please refer to the schematic diagram of the structure of the chip 8200 shown in FIG9 b , but the present disclosure is not limited thereto.

[0529] The chip 8200 includes one or more processors 8201 , and the chip 8200 is configured to execute any of the above methods.

[0530] In some embodiments, the chip 8200 further includes one or more interface circuits 8202. Optionally, the interface circuit 8202 is connected to the memory 8203. The interface circuit 8202 can be used to receive signals from the memory 8203 or other devices, and can be used to send signals to the memory 8203 or other devices. For example, the interface circuit 8202 can read instructions stored in the memory 8203 and send the instructions to the processor 8201.

[0531] In some embodiments, the interface circuit 8202 executes the communication step S2101 of sending and / or receiving in the above method, and the processor 8201 executes other steps.

[0532] In some embodiments, terms such as interface circuit, interface, transceiver pin, and transceiver may be used interchangeably.

[0533] In some embodiments, the chip 8200 further includes one or more memories 8203 for storing instructions. Alternatively, all or part of the memories 8203 may be outside the chip 8200.

[0534] The present disclosure also proposes a storage medium having instructions stored thereon, which, when executed on the communication device 8100, causes the communication device 8100 to execute any of the above methods. Optionally, the storage medium is an electronic storage medium. Optionally, the storage medium is a computer-readable storage medium, but is not limited thereto, and may also be a storage medium readable by other devices. Optionally, the storage medium may be a non-transitory storage medium, but is not limited thereto, and may also be a temporary storage medium.

[0535] The present disclosure also provides a program product, which, when executed by the communication device 8100, enables the communication device 8100 to perform any of the above methods. Optionally, the program product is a computer program product.

[0536] The present disclosure also proposes a computer program, which, when executed on a computer, causes the computer to perform any one of the above methods.

Claims

1. A positioning method, characterized in that: The method is performed by a first network node, and includes: Receive first information sent by the second network node, where the first information is used to indicate measurement information of the second network node on the terminal and reporting information of an output result of the artificial intelligence (AI) model; Obtaining a first result based on the measurement information and the AI ​​model; The reported information is used to send the first result, and the first result is used by a third network node to locate the terminal.

2. The method according to claim 1, characterized in that The method further comprises: Sending the first result and the reporting information to the third network node; or, The first result is processed to obtain a second result, and the second result and the reporting information are sent to the third network node.

3. The method according to claim 1, characterized in that The method further comprises: Based on the reported information, sending the first result to the second network node; or, The first result is processed to obtain a second result, and the second result is sent to the second network node based on the reporting information.

4. The method according to any one of claims 1 to 3, characterized in that The reporting information includes an identifier corresponding to the measurement information.

5. The method according to claim 4, characterized in that The identification includes at least one of the following: New air interface positioning protocol a identifier; Positioning management function measurement identification; Radio access network measurement identifier.

6. The method according to claim 1, characterized in that The measurement information includes at least one of the following: measurement data of the terminal by the first transmission point TRP of the second network node; an identifier of the second network node; an identifier of the first TRP; an identifier of the cell where the first TRP is located; A timestamp, which is used to indicate the time of measurement; the quality of the measurements; The type of positioning signal used to obtain measurement data; Beam information, where the beam information is used to indicate a beam for receiving the positioning signal; Line of sight information, the line of sight information being used to indicate the line of sight when receiving the positioning signal; Non-line-of-sight information, where the non-line-of-sight information is used to indicate the non-line-of-sight when receiving the positioning signal.

7. The method according to any one of claims 1 to 6, characterized in that The method further comprises: receiving second information sent by the second network node, where the second information is used to request the first network node to assist in positioning based on the AI ​​model; or, Receive third information sent by the third network node, where the third information is used to request the first network node to assist in positioning based on the AI ​​model.

8. The method according to claim 7, characterized in that The second information and the third information include at least one of the following: Requesting the first network node for information on assisting positioning based on the AI ​​model; the type of the first result; a reporting mechanism for the first result; a reporting resource for the first result; parameters for processing the first result; response time information, where the response time information is used to instruct the first network node to feed back the first result within the response time information; Requirement information, where the requirement information is used to indicate the conditions required for AI model-assisted positioning.

9. The method according to claim 8, characterized in that The type information of the first result includes at least one of the following: Time information; Power information; Angle information.

10. The method according to claim 8, characterized in that The demand information includes at least one of the following: The amount of data that needs to be processed by the first network node when assisting positioning based on the AI ​​model; The first network node needs to assist in positioning based on the AI ​​model during a time interval; The first network node needs to send the first result to an identifier of a target network node.

11. The method according to any one of claims 1 to 10, characterized in that: The measurement information is obtained by measurement based on fourth information sent by the third network node to the second network node, where the fourth information includes at least one of the following: The identifier of the second TRP to be measured; an identifier of the base station where the second TRP is located; an identifier of the cell where the second TRP is located; Type of measurement data; Reporting mechanism for measurement data; Reporting resources for measurement data.

12. The method according to claim 11, characterized in that The fourth information is further used to indicate an identifier of the first network node.

13. The method according to claim 8, characterized in that The parameters include reference time information.

14. A positioning method, characterized in that: The method is performed by a second network node, and includes: Sending first information to the first network node, where the first information is used to indicate measurement information of the terminal by the second network node and reporting information of an output result of the artificial intelligence (AI) model; The measurement information is used by the first network node to obtain a first result based on the AI ​​model, the reporting information is used to send the first result, and the first result is used by the third network node to locate the terminal.

15. The method according to claim 14, characterized in that The method further comprises: receiving the first result or the second result sent by the first network node, where the first result or the second result is sent based on the reported information; The first result or the second result is sent to the third network node; or the first result is processed to obtain a third result, and the third result is sent to the third network node.

16. The method according to claim 14 or 15, characterized in that The reporting information includes an identifier corresponding to the measurement information.

17. The method according to claim 16, characterized in that The identification includes at least one of the following: New air interface positioning protocol a identifier; Positioning management function measurement identification; Radio access network measurement identifier.

18. The method according to claim 14, characterized in that The measurement information includes at least one of the following: measurement data of the terminal by the first transmission point TRP of the second network node; an identifier of the second network node; an identifier of the first TRP; an identifier of the cell where the first TRP is located; A timestamp, which is used to indicate the time of measurement; the quality of the measurements; The type of positioning signal used to obtain measurement data; Beam information, where the beam information is used to indicate a beam for receiving the positioning signal; Line of sight information, the line of sight information being used to indicate the line of sight when receiving the positioning signal; Non-line-of-sight information, where the non-line-of-sight information is used to indicate the non-line-of-sight when receiving the positioning signal.

19. The method according to any one of claims 14 to 17, wherein: The method further comprises: The second network node sends second information to the first network node, where the second information is used to request the first network node to assist in positioning based on the AI ​​model.

20. The method according to claim 19, characterized in that The second information includes at least one of the following: Requesting the first network node for information on assisting positioning based on the AI ​​model; the type of the first result; a reporting mechanism for the first result; a reporting resource for the first result; parameters for processing the first result; response time information, where the response time information is used to instruct the first network node to feed back the first result within the response time information; Requirement information, where the requirement information is used to indicate the conditions required for AI model-assisted positioning.

21. The method according to claim 20, characterized in that The type information of the first result includes at least one of the following: Time information; Power information; Angle information.

22. The method according to claim 20, characterized in that The demand information includes at least one of the following: The amount of data that needs to be processed by the first network node when assisting positioning based on the AI ​​model; The first network node needs to assist in positioning based on the AI ​​model during a time interval; The first network node needs to send the first result to an identifier of a target network node.

23. The method according to any one of claims 14 to 22, characterized in that: The method further comprises: receiving fourth information sent by the third network node, where the fourth information is used to determine measurement information, and the fourth information includes at least one of the following: The identifier of the second TRP to be measured; an identifier of the base station where the second TRP is located; an identifier of the cell where the second TRP is located; Type of measurement data; Reporting mechanism for measurement data; Reporting resources for measurement data.

24. The method according to claim 23, wherein The fourth information is further used to indicate an identifier of the first network node.

25. The method according to claim 20, wherein The parameters include reference time information.

26. A positioning method, characterized in that: The method is performed by a third network node, and includes: receiving a first result, where the first result is used to locate the terminal; The first result is obtained based on measurement information and an AI model, the first result is sent based on reporting information of an output result of the AI ​​model, and the measurement information and the reporting information are indicated by the first information sent by the second network node to the first network node.

27. The method according to claim 26, characterized in that The receiving the first result includes: receiving the first result and the reporting information sent by the first network node; or, A second result and the reporting information sent by the first network node are received, where the second result is obtained by the first network node processing the first result.

28. The method according to claim 26, characterized in that The receiving the first result includes: receiving the first result or the second result sent by the second network node; The first result or the second result is sent by the first network node to the second network node based on the reported information, and the second result is obtained by processing the first result.

29. The method according to any one of claims 26 to 28, characterized in that The reporting information includes an identifier corresponding to the measurement information.

30. The method according to claim 29, wherein The identification includes at least one of the following: New air interface positioning protocol a identifier; Positioning management function measurement identification; Radio access network measurement identifier.

31. The method according to claim 26, wherein The measurement information includes at least one of the following: measurement data of the terminal by the first transmission point TRP of the second network node; an identifier of the second network node; an identifier of the first TRP; an identifier of the cell where the first TRP is located; A timestamp, which is used to indicate the time of measurement; the quality of the measurements; The type of positioning signal used to obtain measurement data; Beam information, where the beam information is used to indicate a beam for receiving the positioning signal; Line of sight information, the line of sight information being used to indicate the line of sight when receiving the positioning signal; Non-line-of-sight information, where the non-line-of-sight information is used to indicate the non-line-of-sight when receiving the positioning signal.

32. The method according to any one of claims 26 to 31, wherein: The method further comprises: Sending fourth information to the second network node, where the fourth information includes at least one of the following: The identifier of the second TRP to be measured; an identifier of the base station where the second TRP is located; an identifier of the cell where the second TRP is located; Type of measurement data; Reporting mechanism for measurement data; Reporting resources for measurement data.

33. The method according to claim 32, characterized in that The fourth information is further used to indicate an identifier of the first network node.

34. A positioning method, characterized in that: include: The second network node sends first information to the first network node, where the first information is used to indicate measurement information of the terminal by the second network node and reporting information of an output result of the artificial intelligence AI model; The first network node receives first information sent by the second network node; The first network node obtains a first result based on the measurement information and the AI ​​model; The first network node sends the first result based on the measurement information; The third network node receives the first result; the first result is used by the third network node to locate the terminal.

35. A network node, characterized in that: include: a transceiver module, configured to receive first information sent by a second network node, where the first information is used to indicate measurement information of the second network node on the terminal and reporting information of an output result of an artificial intelligence (AI) model; a processing module, configured to obtain a first result based on the measurement information and the AI ​​model; The reported information is used to send the first result, and the first result is used by a third network node to locate the terminal.

36. A network node, characterized in that include: A transceiver module, configured to send first information to the first network node, where the first information is used to indicate measurement information of the second network node on the terminal and reporting information of an output result of the artificial intelligence (AI) model; The measurement information is used by the first network node to obtain a first result based on the AI ​​model, the reporting information is used to send the first result, and the first result is used by the third network node to locate the terminal.

37. A network node, characterized in that: include: a transceiver module, configured to receive a first result, where the first result is used to locate the terminal; The first result is obtained based on measurement information and an AI model, the first result is sent based on reporting information of an output result of the AI ​​model, and the measurement information and the reporting information are indicated by the first information sent by the second network node to the first network node.

38. A network node, characterized in that: include: one or more processors; The processor is configured to execute the positioning method according to any one of claims 1 to 13.

39. A network node, characterized in that: include: one or more processors; The processor is configured to execute the positioning method according to any one of claims 14 to 25.

40. A network node, characterized in that include: one or more processors; The processor is configured to execute the positioning method described in any one of claims 26 to 33.

41. A communication system, characterized in that include: A first network node and a second network node and a third network node, wherein the first network node is configured to implement the positioning method of any one of claims 1-13, the second network node is configured to implement the positioning method of any one of claims 14-25; and the third network node is configured to implement the positioning method of any one of claims 26-33.

42. A storage medium, characterized in that include: The storage medium stores instructions, and when the instructions are executed on the communication device, the communication device executes the positioning method according to any one of claims 1-13, 14-25, or 26-33.

43. A program product, characterized in that include: A computer program, when executed by a communication device, causes the communication device to perform the positioning method according to any one of claims 1-13, 14-25, or 26-33.

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