Communication method and communication device

Abstract

The invention provides a method and a device for transmitting information, which are applied to a scene in which an AI (Artificial Intelligence) is combined with a wireless network, in particular to a scene in which an AI model for positioning is combined with the wireless network. The method comprises: receiving indication information from a location management function network element, the indication information being used for indicating an artificial intelligence (AI) positioning function or an AI positioning model, the AI positioning function or the AI positioning model belonging to a plurality of AI positioning functions or AI positioning models, and the plurality of AI positioning functions or AI positioning models corresponding to a plurality of different measurement quantity sets, the measurement quantity set comprises one or more measurement quantities; and sending a channel measurement result to the position management function network element according to the indication information, wherein a measurement quantity corresponding to the channel measurement result corresponds to the AI positioning function or the AI positioning model indicated by the indication information. According to the scheme of the invention, the signaling overhead can be reduced according to the corresponding relation between the input / output measurement quantity of the AI positioning case and different AI positioning functions or AI positioning models.

Description

Technical Field

[0001] The present application relates to the field of communication technology, and more specifically, to a communication method and a communication device. Background Art

[0002] In artificial intelligence (AI)-based positioning technology, the AI ​​positioning model can be deployed in different devices or nodes, for example, usually deployed on the positioning device side, such as the location management function (LMF) network element, or deployed on the base station (gNodeB, gNB) side. The AI ​​positioning model takes the channel measurement results reported by the channel measurement network element as input and the location of the terminal device as output. Therefore, the channel measurement network element usually needs to report the channel measurement report to the location management function network element.

[0003] The protocol supports that in uplink positioning, LMF sends NR positioning protocol A (NR positioning protocol A, NRPPa) measurement request to the base station (gNodeB, gNB), gNB measures the sounding reference signal (SRS) sent by the UE, obtains the reference signal received path power (RSRPP) result, and sends the RSRPP result to LMF. The study found that the signaling overhead is large, and how to reduce the signaling overhead is an urgent problem to be solved. Summary of the invention

[0004] The present application provides a communication method and a communication device, which can be applied to AI positioning scenarios in order to reduce signaling overhead.

[0005] In a first aspect, a communication method is provided, which can be executed by a first device, or can also be executed by a chip or circuit of the first device, which is not limited in the present application. For ease of description, the following description is given by taking the execution by the first device as an example.

[0006] The method includes: receiving indication information from a location management function network element, the indication information is used to indicate an AI positioning function, the AI ​​positioning function belongs to multiple AI positioning functions, and the multiple AI positioning functions correspond to multiple different measurement quantity sets, and the measurement quantity set includes one or more measurement quantities; sending a channel measurement result to the location management function network element according to the indication information, and the measurement quantity corresponding to the channel measurement result corresponds to the AI ​​positioning function indicated by the indication information.

[0007] Optionally, the first device determines the AI ​​positioning function according to the indication information, and further determines the measurement value corresponding to the AI ​​positioning function.

[0008] Exemplarily, the location management function network element may be a positioning node or positioning device, such as LMF, used to manage the location of the terminal device.

[0009] It should be understood that multiple AI positioning functions correspond to multiple different measurement quantity sets one by one, and each measurement quantity set includes one or more measurement quantities, which can be one of the following: line-of-sight identification result; arrival time estimation result; arrival angle estimation result; line-of-sight identification result corresponding to each path in the first path set; delay corresponding to each path in the second path set; amplitude corresponding to each path in the third path set; phase corresponding to each path in the fourth path set. Among them, at least two path sets in the first path set, the second path set, the third path set, and the fourth path set can be the same or different, and the specific interpretation is shown in the relevant description below.

[0010] According to the scheme provided in the present application, the first device can determine the channel measurement result to be sent to the location management function network element according to the AI ​​positioning function indicated by the indication information. For example, the AI ​​positioning model can be an AI positioning model for positioning. Assuming that the input of the AI ​​positioning model is the channel measurement result, since there is a correspondence between the measurement quantity corresponding to the channel measurement result and the AI ​​positioning function indicated by the indication information, the first device can determine the channel measurement result reported to the location management function network element according to the indication information and the correspondence. In other words, the first device can implicitly know the channel measurement result expected by the location management function network element based on the received indication information, or in other words, it knows the requirements of the corresponding channel measurement report. Correspondingly, the location management function network element can implicitly know which AI positioning function is associated with the channel measurement result through analysis based on the received channel measurement result, and then perform AI positioning.

[0011] In combination with the first aspect, in some implementations of the first aspect, the indication information is carried in a measurement request message from a location management function network element.

[0012] Optionally, the measurement request message and the indication information sent by the location management function network element may be sent together or independently. In other words, the indication information may not be carried in the measurement request message. In this case, the measurement request message and the indication information may be sent simultaneously or separately, and this application does not limit this.

[0013] Based on the above scheme, when the location management function network element determines the indication information, it carries the indication information in the measurement request message and sends it to the first device, so that the first device determines the AI ​​positioning function based on the indication information, and then based on the correspondence between the measurement quantity corresponding to the channel measurement result and the AI ​​positioning function indicated by the indication information, the channel measurement result corresponding to the measurement quantity corresponding to the AI ​​positioning function is reported to the location management function network element. This implementation method helps to reduce signaling overhead.

[0014] In conjunction with the first aspect, in some implementations of the first aspect, the AI ​​positioning function corresponds to one or more of the following measurement quantities:

[0015] Line of sight (LOS) recognition results;

[0016] Time of arrival (TOA) estimation results;

[0017] Angle of arrival (AOA) estimation result;

[0018] The LOS identification result corresponding to each path in the first path set;

[0019] The delay corresponding to each path in the second path set;

[0020] The amplitude corresponding to each path in the third path set;

[0021] The phase corresponding to each path in the fourth path set;

[0022] At least two of the first path set, the second path set, the third path set and the fourth path set are the same or different.

[0023] Exemplarily, the LOS identification result includes line-of-sight LOS and non-line-of-sight (NLOS), and / or LOS probability. Among them, the LOS probability is used to determine the NLOS degree of the channel environment. Different NLOS degrees (that is, different channel conditions) have different degrees of influence on the reasoning accuracy of the AI ​​positioning model due to different channel measurement results. Therefore, the first device can obtain the NLOS degree of the channel based on the channel measurement results, thereby obtaining the current channel conditions.

[0024] It should be understood that the above-mentioned sight range identification results, arrival time estimation results and arrival angle estimation results can be regarded as the measurement quantity of a channel measurement, and a channel may include one or more paths (e.g., a path set). For example, the sight range identification result may be the average LOS probability of the sight range identification results corresponding to all paths in a channel, or the LOS or NLOS identification result with the highest frequency of occurrence. The arrival time estimation result may be the average value of the arrival time estimation results corresponding to all paths in a channel. The arrival angle estimation result may be the average value of the arrival angle estimation results corresponding to all paths in a channel.

[0025] Based on the above scheme, the first device can determine the measurement quantity corresponding to the channel measurement result corresponding to the AI ​​positioning function based on the received indication information, and then obtain the channel measurement result according to the channel measurement, and report the channel measurement result corresponding to the AI ​​positioning function indicated by the indication information. This implementation method helps to reduce signaling overhead.

[0026] In combination with the first aspect, in certain implementations of the first aspect, the first device is an access network device, and the channel measurement result is obtained based on a first channel measurement, and the first channel measurement includes: measuring a detection reference signal from a terminal device; or, the first device is a terminal device, and the channel measurement result is obtained based on a second channel measurement, and the second channel measurement includes: measuring a positioning reference signal or a channel state information reference signal from the access network device; or, the first device is a first terminal device, and the channel measurement result is obtained based on a third channel measurement, and the third channel measurement includes: measuring a side positioning reference signal from a second terminal device.

[0027] Based on the above scheme, channel measurement methods for uplink AI positioning scenarios, downlink AI positioning scenarios and sidelink AI positioning scenarios are provided. By defining the correspondence between the measurement quantity corresponding to the channel measurement result and the AI ​​positioning function indicated by the indication information, the signaling overhead can be reduced.

[0028] In combination with the first aspect, in certain implementation methods of the first aspect, the AI ​​positioning function also corresponds to one of the following reporting methods: the measurement result of each path in the same measurement amount is reported independently; or, the measurement result of each path in the same measurement amount is reported in a differential manner.

[0029] Based on the above scheme, the first device can determine the AI ​​positioning function based on the received indication information, and determine the reporting method of the corresponding channel measurement result according to the AI ​​positioning function, and then obtain the channel measurement result according to the channel measurement, and report the channel measurement result associated with the AI ​​positioning function to the location management function network element in a corresponding reporting method. Compared with the current scheme that uses multiple signalings to indicate the reporting method and the AI ​​positioning function respectively, or uses multiple fields in a signaling to indicate the reporting method and the AI ​​positioning function, the technical scheme of the present application is based on the correspondence between the AI ​​positioning function or the AI ​​positioning model and the measurement quantity. Furthermore, based on the correspondence between the AI ​​positioning function or the AI ​​positioning model and the reporting method, by sending indication information, it is possible to simultaneously indicate the measurement quantity and reporting method corresponding to the AI ​​positioning function or the AI ​​positioning model, thereby reducing signaling overhead.

[0030] In combination with the first aspect, in certain implementations of the first aspect, the channel measurement results are included in the measurement report, and the measurement results of each path in the same measurement quantity are reported in a differential manner, including: the measurement results of each path in the same measurement quantity in the same measurement report are reported in a differential manner.

[0031] That is, the measurement results of the same measurement quantity in different measurement reports are reported independently.

[0032] Based on the above scheme, for reporting the same measurement quantity in the same measurement report, considering differential reporting of the measurement results of each path can reduce signaling overhead. For example, including the first path and the second path, the differential delay measurement results of multiple paths may include the delay measurement result corresponding to the first path and the first differential value, and the first differential value is used to represent the difference between the delay measurement result corresponding to the second path and the delay measurement result corresponding to the first path. Compared with directly reporting the delay measurement results corresponding to the first path and the second path, differential reporting can reduce signaling overhead.

[0033] In combination with the first aspect, in certain implementations of the first aspect, the AI ​​positioning function includes one or more AI positioning models, and the measurement quantity corresponding to the channel measurement result corresponds to the one or more AI positioning models.

[0034] Based on the above scheme, the AI ​​positioning function can further include at least one AI positioning model, so each AI positioning model can correspond to a measurement amount and / or reporting method corresponding to a channel measurement result. Therefore, after receiving the indication information, the first device can determine the AI ​​positioning function, and can implicitly determine one or more AI positioning models corresponding to the AI ​​positioning function, as well as the measurement amount and / or reporting method of the channel measurement result corresponding to each AI positioning model, and then send the corresponding measurement result to the location management function network element according to the indication information. Compared with the current scheme that separately indicates the reporting method and the AI ​​positioning function, the signaling overhead can be reduced.

[0035] In a second aspect, a communication method is provided, which can be executed by a location management function network element, or can also be executed by a chip or circuit of the location management function network element, which is not limited in this application. For ease of description, the following description is taken as an example of execution by a location management function network element.

[0036] The method includes: sending indication information to a first device, where the indication information is used to indicate an AI positioning function, where the AI ​​positioning function belongs to multiple AI positioning functions, and the multiple AI positioning functions correspond to multiple different measurement quantity sets, where the measurement quantity set includes one or more measurement quantities; receiving a channel measurement result from the first device, where the measurement quantity corresponding to the channel measurement result corresponds to the AI ​​positioning function indicated by the indication information.

[0037] Optionally, before sending the indication information to the first device, the location management function network element also includes determining the indication information, and performing AI positioning on the UE after receiving the channel measurement result.

[0038] According to the scheme provided in the present application, the location management function network element can implicitly indicate the measurement quantity of the channel measurement result corresponding to the AI ​​positioning function by sending an indication message to the first device. For example, the AI ​​model can be an AI model for positioning. Assuming that the input of the AI ​​positioning model is the channel measurement result, since there is a correspondence between the measurement quantity corresponding to the channel measurement result and the AI ​​positioning function indicated by the indication message, the first device can determine the channel measurement result reported to the location management function network element based on the indication message and the correspondence. In other words, the first device can implicitly know the channel measurement result expected by the location management function network element based on the received indication message, or in other words, it knows the requirements of the corresponding channel measurement report. Correspondingly, the location management function network element can implicitly know which AI positioning function is associated with the channel measurement result through analysis based on the received channel measurement result, and then perform AI positioning.

[0039] In combination with the second aspect, in some implementations of the second aspect, the indication information is carried in a measurement request message sent by the location management function network element.

[0040] In combination with the second aspect, in certain implementations of the second aspect, the AI ​​positioning function corresponds to any one of the following measurement quantities: line-of-sight LOS identification result; arrival time TOA estimation result; arrival angle AOA estimation result; LOS identification result corresponding to each path in the first path set; time delay corresponding to each path in the second path set; amplitude corresponding to each path in the third path set; phase corresponding to each path in the fourth path set; wherein at least two path sets among the first path set, the second path set, the third path set and the fourth path set are the same or different.

[0041] In combination with the second aspect, in certain implementations of the second aspect, the first device is an access network device, and the channel measurement result is obtained based on a first channel measurement, and the first channel measurement includes: measuring a detection reference signal from a terminal device; or, the first device is a terminal device, and the channel measurement result is obtained based on a second channel measurement, and the second channel measurement includes: measuring a positioning reference signal or a channel state information reference signal from the access network device; or, the first device is a first terminal device, and the channel measurement result is obtained based on a third channel measurement, and the third channel measurement includes: measuring a side positioning reference signal from a second terminal device.

[0042] In combination with the second aspect, in certain implementation methods of the second aspect, the AI ​​positioning function also corresponds to one of the following reporting methods: the measurement result of each path in the same measurement amount is reported independently; the measurement result of each path in the same measurement amount is reported in a differential manner.

[0043] In combination with the second aspect, in certain implementations of the second aspect, the channel measurement results are included in the measurement report, and the measurement results of each path in the same measurement quantity are reported in a differential manner, including: the measurement results of each path in the same measurement quantity in the same measurement report are reported in a differential manner.

[0044] That is, the measurement results of the same measurement quantity in different measurement reports are reported independently.

[0045] In combination with the second aspect, in certain implementations of the second aspect, the AI ​​positioning function includes one or more AI positioning models, and the measurement quantity corresponding to the channel measurement result corresponds to the one or more AI positioning models.

[0046] The beneficial effects of the above-mentioned second aspect and some implementation methods of the second aspect can be referred to the relevant description of the first aspect, which will not be repeated here.

[0047] In a third aspect, a communication method is provided, which can be executed by a first device, or can also be executed by a chip or circuit of the first device, which is not limited in the present application. For ease of description, the following description is given by taking the execution by the first device as an example.

[0048] The method includes: receiving indication information from a location management function network element, the indication information is used to indicate an AI positioning model, the AI ​​positioning model belongs to multiple AI positioning models, and the multiple AI positioning models correspond to multiple different measurement quantity sets, and the measurement quantity set includes one or more measurement quantities; sending a channel measurement result to the location management function network element according to the indication information, and the measurement quantity corresponding to the channel measurement result corresponds to the AI ​​positioning model indicated by the indication information.

[0049] Optionally, the first device determines an AI positioning model according to the indication information, and further determines a measurement value corresponding to the AI ​​positioning model.

[0050] It should be understood that multiple AI positioning models correspond one-to-one to multiple different measurement quantity sets, and each measurement quantity set includes one or more measurement quantities, which can be one of the following: line-of-sight recognition result; arrival time estimation result; arrival angle estimation result; line-of-sight recognition result corresponding to each path in the first path set; delay corresponding to each path in the second path set; amplitude corresponding to each path in the third path set; phase corresponding to each path in the fourth path set. Among them, at least two path sets in the first path set, the second path set, the third path set, and the fourth path set can be the same or different, and the specific interpretation is shown in the relevant description above.

[0051] According to the scheme provided in the present application, the first device can determine the channel measurement result to be sent to the location management function network element according to the AI ​​positioning model indicated by the indication information. For example, the AI ​​model can be an AI model for positioning. Assuming that the input of the AI ​​positioning model is the channel measurement result, since there is a correspondence between the measurement quantity corresponding to the channel measurement result and the AI ​​positioning model indicated by the indication information, the first device can determine the channel measurement result reported to the location management function network element according to the indication information and the correspondence. In other words, the first device can implicitly know the channel measurement result expected by the location management function network element based on the received indication information, or in other words, it knows the requirements of the corresponding channel measurement report. Correspondingly, the location management function network element can implicitly know which AI positioning model is associated with the channel measurement result through analysis based on the received channel measurement result, and then perform AI positioning.

[0052] In combination with the third aspect, in some implementations of the third aspect, the indication information is carried in a measurement request message from a location management function network element.

[0053] In conjunction with the third aspect, in certain implementations of the third aspect, the AI ​​positioning model corresponds to one or more of the following measurement quantities:

[0054] Line of sight LOS recognition results;

[0055] Arrival time TOA estimation results;

[0056] Arrival angle AOA estimation result;

[0057] The LOS identification result corresponding to each path in the first path set;

[0058] The delay corresponding to each path in the second path set;

[0059] The amplitude corresponding to each path in the third path set;

[0060] The phase corresponding to each path in the fourth path set;

[0061] Among them, at least two of the first path set, the second path set, the third path set and the fourth path set are the same or different, and the relevant interpretation of the measurement quantity can refer to the above related description.

[0062] In combination with the third aspect, in certain implementations of the third aspect, the first device is an access network device, and the channel measurement result is obtained based on a first channel measurement, and the first channel measurement includes: measuring a detection reference signal from a terminal device; or, the first device is a terminal device, and the channel measurement result is obtained based on a second channel measurement, and the second channel measurement includes: measuring a positioning reference signal or a channel state information reference signal from the access network device; or, the first device is a first terminal device, and the channel measurement result is obtained based on a third channel measurement, and the third channel measurement includes: measuring a side positioning reference signal from a second terminal device.

[0063] In combination with the third aspect, in certain implementation methods of the third aspect, the AI ​​positioning model also corresponds to one of the following reporting methods: the measurement results of each path in the same measurement quantity are reported independently; the measurement results of each path in the same measurement quantity are reported in a differential manner.

[0064] In combination with the third aspect, in certain implementations of the third aspect, the channel measurement results are included in the measurement report, and the measurement results of each path in the same measurement quantity are reported in a differential manner, including: the measurement results of each path in the same measurement quantity in the same measurement report are reported in a differential manner.

[0065] That is, the measurement results of each path in the same measurement quantity in different measurement reports are reported independently.

[0066] The beneficial effects of the third aspect and certain implementation methods of the third aspect can be referred to the relevant description of the first aspect, which will not be repeated here.

[0067] In a fourth aspect, a communication method is provided, which can be executed by a location management function network element, or can also be executed by a chip or circuit of the location management function network element, which is not limited in this application. For ease of description, the following description is taken as an example of execution by a location management function network element.

[0068] The method includes: sending indication information to a first device, where the indication information is used to indicate an AI positioning model, where the AI ​​positioning model belongs to multiple AI positioning models, and the multiple AI positioning models correspond to multiple different measurement quantity sets, and the measurement quantity set includes one or more measurement quantities; receiving a channel measurement result from the first device, where the measurement quantity corresponding to the channel measurement result corresponds to the AI ​​positioning model indicated by the indication information.

[0069] Optionally, before sending the indication information to the first device, the location management function network element also includes determining the indication information, and performing AI positioning on the UE after receiving the channel measurement result.

[0070] According to the scheme provided in the present application, the location management function network element can implicitly indicate the measurement quantity of the channel measurement result corresponding to the AI ​​positioning model by sending an indication message to the first device. For example, the AI ​​model can be an AI model used for positioning. Assuming that the input of the AI ​​positioning model is the channel measurement result, since there is a corresponding relationship between the measurement quantity corresponding to the channel measurement result and the AI ​​positioning model indicated by the indication message, the first device can determine the channel measurement result reported to the location management function network element based on the indication message and the corresponding relationship. In other words, the first device can implicitly know the channel measurement result expected by the location management function network element based on the received indication message, or in other words, it knows the requirements of the corresponding channel measurement report. Correspondingly, the location management function network element can implicitly know which AI positioning model is associated with the channel measurement result through analysis based on the received channel measurement result, and then perform AI positioning.

[0071] In combination with the fourth aspect, in certain implementations of the fourth aspect, the indication information is carried in a measurement request message sent by the location management function network element.

[0072] In combination with the fourth aspect, in certain implementations of the fourth aspect, the AI ​​positioning model corresponds to any one of the following measurement quantities: line-of-sight LOS identification result; arrival time TOA estimation result; arrival angle AOA estimation result; LOS identification result corresponding to each path in the first path set; time delay corresponding to each path in the second path set; amplitude corresponding to each path in the third path set; phase corresponding to each path in the fourth path set; wherein at least two path sets among the first path set, the second path set, the third path set and the fourth path set are the same or different.

[0073] In combination with the fourth aspect, in certain implementations of the fourth aspect, the first device is an access network device, and the channel measurement result is obtained based on a first channel measurement, and the first channel measurement includes: measuring a detection reference signal from a terminal device; or, the first device is a terminal device, and the channel measurement result is obtained based on a second channel measurement, and the second channel measurement includes: measuring a positioning reference signal or a channel state information reference signal from the access network device; or, the first device is a first terminal device, and the channel measurement result is obtained based on a third channel measurement, and the third channel measurement includes: measuring a side positioning reference signal from a second terminal device.

[0074] In combination with the fourth aspect, in certain implementation methods of the fourth aspect, the AI ​​positioning model also corresponds to one of the following reporting methods: the measurement results of each path in the same measurement quantity are reported independently; the measurement results of each path in the same measurement quantity are reported in a differential manner.

[0075] In combination with the fourth aspect, in certain implementations of the fourth aspect, the channel measurement results are included in the measurement report, and the measurement results of each path in the same measurement quantity are reported in a differential manner, including: the measurement results of each path in the same measurement quantity in the same measurement report are reported in a differential manner.

[0076] That is, the measurement results of each path in the same measurement quantity in different measurement reports are reported independently.

[0077] The beneficial effects of the fourth aspect and certain implementation methods of the fourth aspect can be referred to the relevant description of the third aspect, which will not be repeated here.

[0078] In a fifth aspect, a communication device is provided, which includes: a transceiver unit for receiving indication information from a location management function network element, the indication information is used to indicate an AI positioning function; the transceiver unit is also used to send a channel measurement result to the location management function network element according to the indication information, and the measurement quantity corresponding to the channel measurement result corresponds to the AI ​​positioning function indicated by the indication information.

[0079] Optionally, the processing unit is used to determine the AI ​​positioning function according to the indication information, and determine the measurement value corresponding to the AI ​​positioning function.

[0080] The transceiver unit may perform the reception and transmission processing in the aforementioned first aspect, and the processing unit of the communication device may perform other processing except reception and transmission in the aforementioned first aspect.

[0081] In a sixth aspect, a communication device is provided, comprising: a transceiver unit for sending indication information to a first device, the indication information being used to indicate an AI positioning function; the transceiver unit is also used to receive a channel measurement result from the first device, and the measurement amount corresponding to the channel measurement result corresponds to the AI ​​positioning function indicated by the indication information.

[0082] Optionally, the processing unit is used to determine the indication information and perform AI positioning on the UE after receiving the channel measurement result.

[0083] The transceiver unit may perform the reception and transmission processing in the aforementioned second aspect, and the processing unit of the communication device may perform other processing except reception and transmission in the aforementioned second aspect.

[0084] In the seventh aspect, a communication device is provided, which includes: a transceiver unit for receiving indication information from a location management function network element, the indication information is used to indicate an AI positioning model; the transceiver unit is also used to send a channel measurement result to the location management function network element according to the indication information, and the measurement quantity corresponding to the channel measurement result corresponds to the AI ​​positioning model indicated by the indication information.

[0085] Optionally, the processing unit is used to determine the AI ​​positioning model according to the indication information, and determine the measurement amount corresponding to the AI ​​positioning model. The transceiver unit can perform the receiving and sending processing in the aforementioned third aspect, and the processing unit of the communication device can perform other processing except receiving and sending in the aforementioned third aspect.

[0086] In an eighth aspect, a communication device is provided, comprising: a transceiver unit for sending indication information to a first device, the indication information being used to indicate an AI positioning model; the transceiver unit is also used to receive a channel measurement result from the first device, a measurement quantity corresponding to the channel measurement result and the AI ​​positioning model indicated by the indication information.

[0087] Optionally, the processing unit is used to determine the indication information and perform AI positioning on the UE after receiving the channel measurement result.

[0088] The transceiver unit may perform the reception and transmission processing in the aforementioned fourth aspect, and the processing unit of the communication device may perform other processing except reception and transmission in the aforementioned fourth aspect.

[0089] In a ninth aspect, a communication device is provided, comprising a processor, wherein the processor is used to execute a computer program so that the device executes the method in the above-mentioned first to fourth aspects and any possible implementation manner thereof.

[0090] Optionally, there are one or more processors.

[0091] Optionally, the communication device further comprises a memory, and the memory is used to store the computer program, and the memory is one or more.

[0092] Optionally, the memory may be integrated with the processor, or the memory may be provided separately from the processor, or the memory may be located within the processor.

[0093] Optionally, the communication device further includes a transceiver circuit, such as a transceiver or an input-output circuit.

[0094] In the tenth aspect, a communication system is provided, including: a first device and a location management function network element, the first device is used to execute the method in the above-mentioned first aspect or third aspect and any possible implementation manner, and the location management function network element is used to execute the method in the above-mentioned second aspect or fourth aspect and any possible implementation manner.

[0095] In the eleventh aspect, a computer-readable storage medium is provided, which stores a computer program or code. When the computer program or code is run on a computer, the computer executes the method in the above-mentioned first to fourth aspects and any possible implementation manner thereof.

[0096] In the twelfth aspect, a chip is provided, comprising at least one processor, wherein the processor is used to run a computer program so that a device equipped with the chip executes the methods in the above-mentioned first to fourth aspects and any possible implementation manner thereof.

[0097] The chip may include an output circuit or interface for sending information or data, and an input circuit or interface for receiving information or data.

[0098] In a thirteenth aspect, a computer program product is provided, the computer program product comprising: a computer program code, when the computer program code is run on the computer, the method in the above-mentioned first to fourth aspects and any possible implementation manner thereof is executed. BRIEF DESCRIPTION OF THE DRAWINGS

[0099] Figure 1 is a schematic diagram of a wireless communication system 100 applicable to an embodiment of the present application.

[0100] Figure 2is a schematic diagram of a wireless communication system 200 applicable to an embodiment of the present application.

[0101] Figure 3 is a schematic diagram of a wireless communication system 300 applicable to an embodiment of the present application.

[0102] Figure 4 It is a schematic diagram of a network element involved in an embodiment of the present application.

[0103] Figure 5 It is a schematic diagram of AI / ML network elements or modules.

[0104] Figure 6 It is a schematic diagram of an AI positioning model framework.

[0105] Figure 7 It is a schematic diagram of TDOA positioning.

[0106] Figure 8 It is a schematic diagram of LOS and NLOS.

[0107] Fig. 9 It is a schematic flow chart of a communication method 900 provided in an embodiment of the present application.

[0108] Fig.10 It is a schematic flow chart of a communication method 1000 provided in an embodiment of the present application.

[0109] Fig.11 It is a schematic flowchart of a communication method 1100 provided in an embodiment of the present application.

[0110] Fig.12 It is a schematic flowchart of a communication method 1200 provided in an embodiment of the present application.

[0111] Fig.13 It is a schematic diagram of a communication device 1300 provided in an embodiment of the present application.

[0112] Fig.14 It is a schematic diagram of another communication device 1400 provided in an embodiment of the present application.

[0113] Fig.15 It is a schematic diagram of a chip system 1500 provided in an embodiment of the present application. DETAILED DESCRIPTION

[0114] The technical solution in this application will be described below in conjunction with the accompanying drawings.

[0115] The technical solution provided in the present application can be applied to various communication systems, such as: the fifth generation (5th generation, 5G) or new radio (new radio, NR) system, long term evolution (long term evolution, LTE) system, LTE frequency division duplex (frequency division duplex, FDD) system, LTE time division duplex (time division duplex, TDD) system, wireless local area network (wireless local area network, WLAN) system, satellite communication system, future communication system, such as the sixth generation mobile communication system, or, a fusion system of multiple systems, etc. The technical solution provided in the present application can also be applied to device to device (device to device, D2D) communication, vehicle to everything (vehicle-to-everything, V2X) communication, machine to machine (machine to machine, M2M) communication, machine type communication (machine type communication, MTC), and Internet of things (Internet of things, IoT) communication system or other communication systems.

[0116] A device in a communication system can send a signal to another device or receive a signal from another device. The signal may include information, signaling, or data, etc. The device may also be replaced by an entity, a network entity, a communication device, a communication module, a node, a communication node, etc., and the present application is described by taking the device as an example. For example, the communication system may include at least one terminal device and at least one network device. The network device may send a downlink signal to the terminal device, and / or the terminal device may send an uplink signal to the network device. It is understandable that the terminal device / network device in the present application may be replaced by the first device, and the location management function network element executes the corresponding communication method in the present application.

[0117] The terminal devices in the embodiments of the present application include various devices with wireless communication functions, which can be used to connect people, objects, machines, etc. The terminal devices can be widely used in various scenarios, such as: cellular communication, D2D, V2X, peer to peer (P2P), M2M, MTC, IoT, virtual reality (VR), augmented reality (AR), industrial control, automatic driving, telemedicine, smart grid, smart furniture, smart office, smart wear, smart transportation, smart city drones, robots, remote sensing, passive sensing, positioning, navigation and tracking, autonomous delivery, etc. The terminal device can be a terminal in any of the above scenarios, such as an MTC terminal, an IoT terminal, etc. The terminal device may be a user equipment (UE), terminal, fixed device, mobile station device or mobile device of the third generation partnership project (3GPP) standard, a subscriber unit, a handheld device, a vehicle-mounted device, a wearable device, a cellular phone, a smart phone, a session initialization protocol (SIP) phone, a wireless data card, a personal digital assistant (PDA), a computer, a tablet computer, a notebook computer, a wireless modem, a handheld device (handset), a laptop computer, a computer with wireless transceiver function, a smart book, a vehicle, a satellite, a global positioning system (GPS) device, a target tracking device, an aircraft (such as a drone, a helicopter, a multi-copter, a quadcopter, or an airplane, etc.), a ship, a remote control device, a smart home device, an industrial device, or a device built into the above-mentioned device (for example, a communication module, a modem or a chip in the above-mentioned device, etc.), or other processing devices connected to the wireless modem. For the convenience of description, the terminal device is described below by taking the terminal or UE as an example.

[0118] It should be understood that in some scenarios, the UE can also be used to act as a base station. For example, the UE can act as a scheduling entity that provides sidelink signals between UEs in scenarios such as V2X, D2D or P2P.

[0119] In the embodiment of the present application, the device for realizing the function of the terminal device can be the terminal device, or it can be a device that can support the terminal device to realize the function, such as a chip system or a chip, which can be installed in the terminal device. In the embodiment of the present application, the chip system can be composed of a chip, or it can include a chip and other discrete devices.

[0120] The network device in the embodiment of the present application may be a device for communicating with a terminal device, and the network device may also be referred to as an access network device or a wireless access network device, such as a base station. The network device in the embodiment of the present application may refer to a wireless access network (RAN) node (or device) that connects a terminal device to a wireless network. Base station can broadly cover various names as follows, or replace with the following names, such as: NodeB, evolved NodeB (eNB), next generation NodeB (gNB), relay station, access point, transmission point (TRP), transmission point (TP), master station, auxiliary station, multi-standard wireless (motor slide retainer, MSR) node, home base station, network controller, access node, wireless node, access point (AP), transmission node, transceiver node, baseband unit (BBU), remote radio unit (RRU), active antenna unit (AAU), remote radio head (RRH), central unit (CU), distributed unit (DU), positioning node, etc. The base station can be a macro base station, a micro base station, a relay node, a donor node or the like, or a combination thereof. The base station can also refer to a communication module, a modem or a chip used to be set in the aforementioned device or apparatus. The base station can also be a mobile switching center and a device that performs the base station function in D2D, V2X, and M2M communications, a network-side device in a 6G network, or a device that performs the base station function in a future communication system. The base station can support networks with the same or different access technologies. The embodiments of this application do not limit the specific technology and specific device form used by the network device.

[0121] A base station can be fixed or mobile. For example, a helicopter or drone can be configured to act as a mobile base station, and one or more cells can move according to the location of the mobile base station. In other examples, a helicopter or drone can be configured to act as a device that communicates with another base station.

[0122] In some deployments, the network device mentioned in the embodiments of the present application may be a device including a CU, or a DU, or a device including a CU and a DU, or a control plane CU node (central unit control plane (central unit-control plane, CU-CP)) and a user plane CU node (central unit user plane (central unit-user plane, CU-UP)) and a DU node. For example, the network device may include a gNB-CU-CP, a gNB-CU-UP, and a gNB-DU.

[0123] In some deployments, multiple RAN nodes collaborate to assist the terminal in achieving wireless access, and different RAN nodes implement part of the functions of the base station. For example, the RAN node can be a CU, DU, CU-CP, CU-UP, or RU. The CU and DU can be set separately, or can also be included in the same network element, such as a BBU. The RU can be included in a radio frequency device or a radio frequency unit, such as an RRU, AAU, or RRH.

[0124] The RAN node may support one or more types of fronthaul interfaces, and different fronthaul interfaces correspond to DUs and RUs with different functions. If the fronthaul interface between the DU and the RU is a common public radio interface (CPRI), the DU is configured to implement one or more baseband functions, and the RU is configured to implement one or more radio frequency functions. If the fronthaul interface between the DU and the RU is another interface, relative to the CPRI, part of the downlink and / or uplink baseband functions, such as, for downlink, one or more of precoding, digital beamforming (BF), or inverse fast Fourier transform (IFFT) / cyclic prefix (CP) are moved from the DU to the RU for implementation, and for uplink, one or more of digital beamforming (BF), or fast Fourier transform (FFT) / cyclic prefix (CP) are moved from the DU to the RU for implementation. In a possible implementation, the interface may be an enhanced common public radio interface (eCPRI). In the eCPRI architecture, the division between DU and RU is different, corresponding to different types (category, Cat) of eCPRI, such as eCPRI Cat A, B, C, D, E, F.

[0125] Taking eCPRI Cat A as an example, for downlink transmission, based on layer mapping, the DU is configured to implement layer mapping and one or more functions before it (i.e., one or more functions of coding, rate matching, scrambling, modulation, and layer mapping), while other functions after layer mapping (e.g., RE mapping, digital beamforming (BF), or one or more functions of inverse fast Fourier transform (IFFT) / adding cyclic prefix (CP)) are moved to the RU for implementation. For uplink transmission, based on de-RE mapping, the DU is configured to implement de-mapping and one or more functions before it (i.e., one or more functions of decoding, de-rate matching, de-scrambling, demodulation, inverse discrete Fourier transform (IDFT), channel equalization, and de-RE mapping), while other functions after de-mapping (e.g., one or more functions of digital BF or fast Fourier transform (FFT) / removing CP) are moved to the RU for implementation. It can be understood that for the functional description of DU and RU corresponding to various types of eCPRI, reference can be made to the eCPRI protocol and will not be repeated here.

[0126] In one possible design, the processing unit for implementing the baseband function in the BBU is called a baseband high layer (BBH) unit, and the processing unit for implementing the baseband function in the RRU / AAU / RRH is called a baseband low layer (BBL) unit.

[0127] In different systems, CU (or CU-CP and CU-UP), DU or RU may also have different names, but those skilled in the art can understand their meanings. For example, in the ORAN system, CU may also be called O-CU (open CU), DU may also be called O-DU, CU-CP may also be called O-CU-CP, CU-UP may also be called O-CU-UP, and RU may also be called O-RU. Any unit in the CU (or CU-CP, CU-UP), DU and RU in this application may be implemented by a software module, a hardware module, or a combination of a software module and a hardware module.

[0128] In the embodiment of the present application, the device for realizing the function of the network device can be a network device, or a device capable of supporting the network device to realize the function, such as a chip system or a chip, which can be installed in the network device. In the embodiment of the present application, the chip system can be composed of a chip, or can include a chip and other discrete devices.

[0129] Network devices and terminal devices can be deployed on land, including indoors or outdoors, handheld or vehicle-mounted; they can also be deployed on the water; they can also be deployed on aircraft, balloons and satellites in the air. The scenarios in which network devices and terminal devices are located are not limited in the embodiments of the present application. In addition, terminal devices and network devices can be hardware devices, or they can be software functions running on dedicated hardware, software functions running on general-purpose hardware, such as virtualization functions instantiated on a platform (e.g., a cloud platform), or entities including dedicated or general-purpose hardware devices and software functions. The present application does not limit the specific forms of terminal devices and network devices.

[0130] In the embodiment of the present application, the location management function network element may be a positioning node or positioning device, such as LMF, for positioning and managing the location of the terminal device. Exemplarily, the device for positioning or managing the location of the terminal device may be a location management function network element, or a chip system, chip or circuit of the location management function network element, which may be installed in the location management function network element. The chip system may be composed of a chip, or may include a chip and other discrete devices.

[0131] Optionally, the location management function network element may be a core network device, which refers to a device in the core network (CN) that provides service support for terminal devices. The core network device may include one or more core network elements. Taking the 5G core network as an example, the 5G core network includes an access and mobility management function (AMF) network element responsible for services such as mobility management and access management, a session management function (SMF) network element responsible for session management, a user plane function (UPF) network element responsible for data packet routing and forwarding and quality of service (QoS) control on the user plane, and a policy control function (PCF) network element. The above core network elements may work independently or be combined to implement certain control functions, such as AMF, SMF and PCF may be combined as a core network device. All or part of the above core network elements may be independent in form or integrated in the same device, which is not limited here.

[0132] In an embodiment of the present application, the first device may be a terminal device or a network device, or a component of a terminal device or a network device (such as a chip or circuit). Optionally, the network device may be a network device provided with one or more AI modules. For example, the network device may be a core network device, an access network node (RAN node), or one or more devices in OAM. For example, the AI ​​module may be a RAN intelligent controller (RIC), such as a near real-time RIC or a non-real-time RIC. For example, the near real-time RIC is set in a RAN node (for example, in a CU or DU), and the non-real-time RIC is set in an OAM, a cloud server, a core network device, or other network devices. The location management function network element is a network element for training an AI positioning model and / or a storage network element for an AI positioning model library, or is also a selection / inference network element for an AI positioning model, for example, an AI positioning model for positioning is configured in a location management function network element.

[0133] Exemplarily, the first device and the location management function network element may be logically deployed separately. As different implementation methods, the first device and the location management function network element may be physically deployed in the same network element or different network elements, without limitation. For example, the first device is a terminal device, and the location management function network element is a server (also called a host) or a cloud device in an over the top (OTT) system. The terminal device and the server or cloud device of the OTT system can communicate through the Internet. For another example, the first device is a module in the terminal device (for example, a module of the physical layer), and the location management function network element is another module of the device (such as LMF) (for example, a module of the application layer, such as an application module connected to an OTT server). It can be understood that in the embodiments of the present application, the module can be implemented by hardware, or by software, or by a combination of hardware and software, without limitation.

[0134] First, a communication system applicable to an embodiment of the present application is briefly introduced as follows.

[0135] Figure 1 1 is a schematic diagram of a wireless communication system 100 applicable to an embodiment of the present application. Figure 1 As shown, the wireless communication system includes a wireless access network 100. The wireless access network 100 may be a next generation (e.g., 6G or higher) wireless access network, or a traditional (e.g., 5G, 4G, 3G, or 2G) wireless access network. One or more terminal devices (120a-120j, collectively referred to as 120) may be connected to each other or to one or more network devices (110a, 110b, collectively referred to as 110) in the wireless access network 100. Figure 1This is just a schematic diagram. The wireless communication system may also include other devices, such as core network devices, wireless relay devices and / or wireless backhaul devices. Figure 1 Not drawn in.

[0136] In practical applications, the wireless communication system may include multiple network devices and multiple terminal devices at the same time without limitation. A network device may serve one or more terminal devices at the same time. A terminal device may also access one or more network devices at the same time. The embodiment of the present application does not limit the number of terminal devices and network devices included in the wireless communication system.

[0137] Figure 2 2 is a schematic diagram of a wireless communication system 200 applicable to an embodiment of the present application. Figure 2 As shown, the wireless communication system 200 may include at least one network device, such as Figure 2 The wireless communication system 200 may also include at least one terminal device, such as Figure 2 The terminal device 220 and the terminal device 230 shown in the figure, the wireless communication system 200 may also include a positioning device, such as Figure 2 The positioning device 240 is shown. Exemplarily, the positioning device 240 is a positioning management function LMF network element, referred to as LMF.

[0138] Among them, the positioning device and the network device can communicate through interface messages. For example, taking the network device 210 as a gNB and the positioning device 240 as an LMF as an example, the gNB and the LMF can exchange information through NRPPa messages. For another example, taking the network device 210 as an eNB and the positioning device 240 as an LMF as an example, the eNB and the LMF can exchange information through LTE positioning protocol (LPP) messages.

[0139] The terminal device and the positioning device may communicate directly or through other devices, such as network devices and / or core network elements. Figure 2 As shown, the terminal device 220 and the positioning device 240 can communicate through the network device 210.

[0140] Optionally, the positioning device and the network device may be different modules of the same device, or may be separate different devices.

[0141] Figure 3 Schematic diagram of a wireless positioning system applicable to the embodiment of the present application. Figure 3As shown, the wireless positioning system mainly includes access network equipment, terminal equipment and positioning equipment. Among them, the positioning equipment is mainly responsible for receiving positioning service requests, collecting positioning-related measurement results, calculating positioning results, and providing corresponding wireless positioning services. Optionally, the positioning equipment can receive positioning service requests from access network equipment or upper-layer applications. As an example, the positioning equipment can be a location management function network element, such as LMF. For access network equipment and terminal equipment, please refer to the above description.

[0142] Figure 4 Schematic diagram of the device involved in the embodiment of the present application. Figure 4 As shown, it includes UE, location management function network element and access network equipment. Optionally, it also includes access mobility management function (AMF) network element. As an example, the access network device may be ng-eNB or gNB, wherein ng-eNB represents a 4G base station that can access the 5G core network, and gNB represents a 5G base station, both of which are network elements of NR-RAN. The wireless access network device or base station mentioned in the embodiment of the present application may be ng-eNB or gNB, without limitation. The UE and the wireless access network device communicate through corresponding interfaces, for example, the UE and the gNB communicate through the NR-Uu interface, and the UE and the ng-eNB communicate through the LTE-Uu interface. In the embodiment of the present application, the NR-Uu interface and the LTE-Uu interface are used to transmit positioning-related signaling and / or data. In addition, the gNB and the AMF, and the ng-eNB and the AMF communicate through the NG-C interface, such as transmitting positioning-related signaling. The AMF and the LMF communicate through the NL1 interface, such as transmitting positioning-related signaling. Optionally, the interaction between UE and LMF is based on the LTE positioning protocol (LPP) protocol, and the interaction between NG-RAN and LMF is based on the NRPPa protocol, which is transparently transmitted across AMF. It should be understood that NG-RAN is only used as an example. When the technical solution of the present application is applied to future wireless communication systems, such as 6G systems, NG-RAN is correspondingly an access network device in the 6G system. Similarly, the names of the network elements, the interface names between the network elements, and the message names are only used as examples. In future wireless communication systems, network elements, interfaces, and interface messages with the same or similar functions can be used to implement the technical solution of the present application.

[0143] In addition, in order to support machine learning functions in wireless communication systems, AI nodes may also be introduced into wireless communication systems.

[0144] Optionally, the communication system also includes at least one AI node.

[0145] Optionally, the AI ​​node is deployed in one or more of the following: a network device, a terminal device, a core network, or a positioning device; or, the AI ​​node may be deployed separately, such as deployed in a location other than any of the above devices. The AI ​​node may communicate with other devices in the communication system, and the other devices may be, for example, one or more of the following: a network device, a terminal device, a core network element, or a positioning device.

[0146] Optionally, the AI ​​node is used to perform AI-related operations. As an example, the AI-related operations may include: one or more of: model failure test, model performance test, model training test, or data collection.

[0147] For example, the network device may forward the data related to the AI ​​positioning model reported by the terminal device to the AI ​​node, and the AI ​​node may perform AI-related operations. For another example, the network device or the terminal device may forward the data related to the AI ​​positioning model to the AI ​​node, and the AI ​​node may perform AI-related operations. For another example, the AI ​​node may send the output of AI-related operations, such as one or more of the trained neural network model, model evaluation, or test results, to the network device and / or the terminal device. For example, the AI ​​node may directly send the output of AI-related operations to the network device and the terminal device. For another example, the AI ​​node may send the output of AI-related operations to the terminal device through the network device. For another example, the AI ​​node may send the output of AI-related operations to the network device through the terminal device.

[0148] It is understood that the present application does not limit the number of AI nodes. For example, when there are multiple AI nodes, the multiple AI nodes can be divided based on functions, such as different AI nodes are responsible for different functions.

[0149] It can also be understood that AI nodes can be independent devices, or they can be integrated into the same device to implement different functions, or they can be network elements in hardware devices, or they can be software functions running on dedicated hardware, or they can be virtualized functions instantiated on a platform (for example, a cloud platform). This application does not limit the specific form of the above-mentioned AI nodes.

[0150] Exemplarily, the AI ​​node may be an AI network element or an AI module.

[0151] Figure 5It is a schematic diagram of an AI / ML network element or module. Among them, if an AI network element is introduced, it means that the AI ​​network element corresponds to an independent network element; if an AI module is introduced, the AI ​​module can be located inside a certain network element. As described above, the network elements involved in the embodiments of the present application include UE, wireless access network equipment and LMF, and optionally, AMF. An AI module can be set inside one or more of these UEs, wireless access network equipment, AMF (if the network element is involved) and LMF, or one or more of the UEs, wireless access network equipment, AMF and LMF introduce corresponding AI network elements, or a combination of these two methods, which is not limited in the present application.

[0152] The AI ​​module is used to implement the corresponding AI function. The AI ​​modules deployed in different network elements may be the same or different. The model of the AI ​​module can implement different functions according to different parameter configurations. The model of the AI ​​module can be configured based on one or more of the following parameters: structural parameters (such as the number of neural network layers, the width of the neural network, the connection relationship between layers, the weight of the neuron, the activation function of the neuron, or at least one of the biases in the activation function), input parameters (such as the type of input parameters and / or the dimension of input parameters), or output parameters (such as the type of output parameters and / or the dimension of output parameters). Among them, the bias in the activation function can also be called the bias of the neural network.

[0153] An AI module can have one or more models. A model can be inferred to obtain an output, which includes one parameter or multiple parameters. The learning process, training process, or inference process of different models can be deployed in different nodes or devices, or can be deployed in the same node or device.

[0154] It should be understood that if one or more of the UE, the wireless access network device, the AMF and the LMF introduces the corresponding AI network element, and the AI ​​operation is performed by the corresponding AI network element, the UE, the wireless access network device, the AMF or the LMF needs to send the information related to the AI ​​operation to the corresponding AI network element. For example, the LMF introduces the corresponding AI network element, and the AI ​​network element performs the reasoning operation of the AI ​​model. After the LMF receives the channel measurement report from the first device (such as the access network device or the UE), the channel measurement result carried in the channel measurement report is sent to the corresponding AI network element. For another example, in uplink positioning, if the access network device introduces the corresponding AI network element, it is assumed that the input of the AI ​​model is the channel feature extracted from the channel measurement result as input, and the channel measurement result is obtained by the access network device measuring the SRS of the UE. Therefore, after the access network device obtains the channel measurement result, it sends the channel measurement result to the corresponding AI network element, and the AI ​​network element extracts the channel feature from the channel measurement result through the AI ​​model, and then returns the extracted channel feature to the access network device, and then the access network device sends the channel feature to the LMF.

[0155] It is understandable. Figures 1 to 5 This is a simplified schematic diagram for ease of understanding. The wireless communication system may also include other network devices, or other terminal devices, or other AI nodes. Figures 1 to 5 Not drawn in.

[0156] In order to facilitate understanding of the embodiments of the present application, the terms involved in the embodiments of the present application are briefly explained below.

[0157] (1) Artificial Intelligence (AI):

[0158] It is to enable machines to learn, accumulate experience, and solve problems that humans can solve through experience, such as natural language understanding, image recognition, and chess. Artificial intelligence can be understood as the intelligence displayed by machines made by humans. Usually artificial intelligence refers to the technology that presents human intelligence through computer programs. The goals of artificial intelligence include understanding intelligence by building computer programs with symbolic reasoning or inference.

[0159] (2) Machine learning (ML):

[0160] ML is an implementation of artificial intelligence. Machine learning is a method that can give machines the ability to learn, so that machines can complete functions that cannot be completed by direct programming. In a practical sense, machine learning is a method of using data to train a model and then using the model to make predictions. There are many machine learning methods, such as neural networks (NN), decision trees, support vector machines, etc. Machine learning theory mainly designs and analyzes some algorithms that allow computers to learn automatically. Machine learning algorithms are a type of algorithm that automatically analyzes data to obtain patterns and uses the patterns to predict unknown data.

[0161] (3) AI Model:

[0162] An AI model is an algorithm or computer program that can realize AI functions. An AI model represents the mapping relationship between the input and output of the model, or in other words, an AI model is a function model that maps input of a certain dimension to output of a certain dimension. The parameters of the function model can be obtained through machine learning training. For example, f(x) = mx 2 +n is a quadratic function model, which can be regarded as an AI model, m and n are parameters of the AI ​​model, and m and n can be obtained through machine learning training. Exemplarily, the AI ​​models mentioned in the embodiments below in this application are not limited to neural networks, linear regression models, decision tree models, support vector machines (SVM), Bayesian networks, Q learning models or other machine learning (ML) models.

[0163] AI model design mainly includes data collection links (for example, collecting training data and / or reasoning data), model training links, and model reasoning links. It can also include reasoning result application links. In the aforementioned data collection link, the data source is used to provide training data sets and reasoning data. In the model training link, the AI ​​model is obtained by analyzing or training the training data provided by the data source. Learning the AI ​​model through the model training node is equivalent to using the training data to learn the mapping relationship between the input and output of the AI ​​model. In the model reasoning link, the AI ​​model trained through the model training link is used to reason based on the reasoning data provided by the data source to obtain the reasoning result. This link can also be understood as: inputting the reasoning data into the AI ​​model, and obtaining the output through the AI ​​model, which is the reasoning result. The reasoning result can indicate: the configuration parameters used (executed) by the execution object, and / or the operation performed by the execution object. The reasoning result is published in the reasoning result application link, for example, the reasoning result can be uniformly planned by the execution (actor) entity, for example, the execution entity can send the reasoning result to one or more execution objects (for example, core network equipment, access network equipment, or terminal equipment, etc.) for execution. For example, the execution entity can also provide feedback on the performance of the AI ​​model to the data source, facilitating the subsequent update and training of the AI ​​model.

[0164] It is understood that the implementation of the AI ​​model can be a hardware circuit, or software, or a combination of software and hardware, without limitation. Non-limiting examples of software include: program code, program, subroutine, instruction, instruction set, code, code segment, software module, application, or software application, etc.

[0165] (4) Neural network (NN):

[0166] Neural networks are a specific implementation of AI or machine learning. According to the universal approximation theorem, neural networks can theoretically approximate any continuous function, thus enabling neural networks to learn any mapping.

[0167] A neural network can be composed of neural units, and a neural unit can refer to an operation unit with xs and intercept 1 as input. A neural network is a network formed by connecting many of the above single neural units together, that is, the output of one neural unit can be the input of another neural unit. The input of each neural unit can be connected to the local receptive field of the previous layer to extract the features of the local receptive field, and the local receptive field can be an area composed of several neural units.

[0168] Taking the AI ​​model type as a neural network as an example, the AI ​​model involved in the present disclosure may be a deep neural network (DNN). Depending on how the network is constructed, DNN may include a feedforward neural network (FNN), a convolutional neural network (CNN), and a recurrent neural network (RNN).

[0169] (5) Fingerprint:

[0170] Since the multipath propagation of signals is dependent on the environment, the multipath structure of the channel at each location is unique. The radio waves emitted by the terminal are reflected and refracted to produce a multipath signal with a specific pattern that is closely related to the surrounding environment. Such multipath characteristics can be called the "fingerprint" information of the location. The positioning method based on the "fingerprint" information can be called fingerprint positioning. For example, the positioning of the mobile terminal is achieved based on the "fingerprint" information of the mobile terminal.

[0171] (6) Training data set and inference data:

[0172] In the field of machine learning, ground truth usually refers to data that is believed to be accurate or real.

[0173] The training data set is used for training the AI ​​model. The training data set may include the input of the AI ​​model, or the input and target output of the AI ​​model. The training data set includes one or more training data. The training data may include training samples input to the AI ​​model, or may include the target output of the AI ​​model. The target output may also be referred to as a label, sample label, or label sample. The label is the true value.

[0174] In the field of communications, training data sets can include simulation data collected through simulation platforms, experimental data collected in experimental scenarios, or measured data collected in actual communication networks. Due to differences in the geographical environment and channel conditions in which the data is generated, such as indoor and outdoor conditions, mobile speeds, frequency bands, or antenna configurations, the collected data can be classified when acquiring the data. For example, data with the same channel propagation environment and antenna configuration can be grouped together.

[0175] Model training is essentially learning some of its features from the training data. In the process of training AI models (such as neural network models), because we hope that the output of the AI ​​model is as close as possible to the value we really want to predict, we can compare the current network's predicted value with the target value we really want, and then update the weight vector of each layer of the AI ​​model according to the difference between the two (of course, there is usually an initialization process before the first update, that is, pre-configuring parameters for each layer in the AI ​​model). For example, if the network's predicted value is high, adjust the weight vector to make it predict lower, and keep adjusting until the AI ​​model can predict the target value we really want or a value very close to the target value we really want. Therefore, it is necessary to predefine "how to compare the difference between the predicted value and the target value", which is the loss function or objective function, which are important equations used to measure the difference between the predicted value and the target value. Among them, taking the loss function as an example, the higher the output value (loss) of the loss function, the greater the difference, so the training of the AI ​​model becomes a process of minimizing this loss as much as possible, so that the value of the loss function is less than the threshold, or the value of the loss function meets the target requirements. For example, the AI ​​model is a neural network, and adjusting the model parameters of the neural network includes adjusting at least one of the following parameters: the number of layers, width, weights of neurons, or parameters in the activation function of the neurons of the neural network.

[0176] Inference data can be used as input to the trained AI model for inference of the AI ​​model. During the model inference process, the inference data is input into the AI ​​model, and the corresponding output is the inference result.

[0177] Figure 6 It is an AI application framework.

[0178] In the aforementioned data collection link, the data source is used to provide training data sets and reasoning data. In the model training link, the AI ​​model is obtained by analyzing or training the training data provided by the data source. Among them, the AI ​​model represents the mapping relationship between the input and output of the model. Learning the AI ​​model through the model training node is equivalent to using the training data to learn the mapping relationship between the input and output of the model. In the model reasoning link, the AI ​​model trained through the model training link is used to reason based on the reasoning data provided by the data source to obtain the reasoning result. This link can also be understood as: inputting the reasoning data into the AI ​​model, and obtaining the output through the AI ​​model, which is the reasoning result. The reasoning result can indicate: the configuration parameters used (executed) by the execution object, and / or the operation performed by the execution object. The reasoning result is published in the reasoning result application link, for example, the reasoning result can be uniformly planned by the execution (actor) entity, for example, the execution entity can send the reasoning result to one or more execution objects (for example, network devices or terminal devices, etc.) for execution. For example, the execution entity can also feedback the performance of the model to the data source to facilitate the subsequent implementation of the model update training.

[0179] It is understandable that a network element with an artificial intelligence function may be included in the communication system. The above-mentioned AI model design-related links may be performed by one or more network elements with artificial intelligence functions. In one possible design, an AI function (such as an AI module or an AI entity) may be configured in an existing network element in the communication system to implement AI-related operations, such as training and / or reasoning of an AI model. For example, the existing network element may be a network device or a terminal device, etc. Or in another possible design, an independent network element may also be introduced into the communication system to perform AI-related operations, such as training an AI model. The independent network element may be referred to as an AI network element or an AI node, etc., and the embodiment of the present application does not limit this name. Exemplarily, the AI ​​network element may be directly connected to the network device in the communication system, or indirectly connected through a third-party network element and the network device. Among them, the third-party network element may be a core network element such as an authentication management function (AMF) network element, a user plane function (UPF) network element, an operation and maintenance management (OAM), a cloud server or other network element, without limitation. Exemplarily, the independent network element may be deployed on one or more of the network device side, the terminal device side, or the core network side. Optionally, it may be deployed on a cloud server.

[0180] The training process of different models can be deployed in different devices or nodes, or in the same device or node. The reasoning process of different models can be deployed in different devices or nodes, or in the same device or node. Exemplarily, the model parameters of the AI ​​model may include one or more of the following structural parameters of the model (such as the number of layers of the model, and / or weights, etc.), the input parameters of the model (such as input dimensions, number of input ports), or the output parameters of the model (such as output dimensions, number of output ports). It can be understood that the input dimension may refer to the size of an input data. For example, when the input data is a sequence, the input dimension corresponding to the sequence may indicate the length of the sequence. The number of input ports may refer to the number of input data. Similarly, the output dimension may refer to the size of an output data. For example, when the output data is a sequence, the output dimension corresponding to the sequence may indicate the length of the sequence. The number of output ports may refer to the number of output data.

[0181] (7) Time difference of arrival (TDOA): A positioning method that uses time difference.

[0182] Figure 7 This is a schematic diagram of TDOA positioning. Figure 7 As shown, it is assumed that the distance between network device #1 and the terminal device is d1, and the transmission time when network device #1 transmits signals to the terminal device is t1; the distance between network device #2 and the terminal device is d2, and the transmission time when network device #2 transmits signals to the terminal device is t2; the distance between network device #3 and the terminal device is d3, and the transmission time when network device #3 transmits signals to the terminal device is t3.

[0183] In TDOA, as an example, multiple network devices can send reference signals, such as positioning reference signals (PRS), to terminal devices, and the terminal devices determine the location of the terminal devices by measuring the TDOA of the reference signals, where the TDOA of the reference signals can also be called reference signal time difference (RSTD). Figure 7For example, assume that the reference signal sent by network device #1 to the terminal device is P1, the reference signal sent by network device #2 to the terminal device is P2, and the reference signal sent by network device #3 to the terminal device is P3. The terminal device measures the TDOA of P2 and P1, that is, t2-t1. Using t2-t1, the distance difference d2-d1 between network device #2 and network device #1 can be inferred, and a curve is obtained. Each point on the curve satisfies the distance difference d2-d1 to network device #2 and network device #1. Similarly, the terminal device measures the TDOA of P3 and P1, that is, t3-t1. Using t3-t1, the distance difference d3-d1 between network device #3 and network device #1 can be inferred, and another curve is obtained. Each point on the curve satisfies the distance difference d3-d1 to network device #3 and network device #1. The intersection of the above two curves can be used to determine the location of the terminal device. The mathematical model can be expressed as formula 1:

[0184]

[0185] Among them, (a i , b i ) represents the position coordinates of network device #i. (a, b) represents the position coordinates of the terminal device to be found. For example, a represents the position coordinates of the terminal device to be found on the X axis, and b represents the position coordinates of the terminal device to be found on the Y axis. c represents the speed of light.

[0186] Since there are certain synchronization errors between different network devices, the corresponding measurement values ​​also have certain uncertainties. Figure 7 The dashed lines in the figure indicate the intervals.

[0187] The above combination Figure 7 This article introduces a method for positioning based on a reference signal sent by a network device to a terminal device, which can also be called downlink TDOA (DL-TDOA) or observed time difference of arrival OTDOA. Similarly, positioning can also be performed based on a reference signal sent by a terminal device to a network device, such as SRS. This positioning method can be called uplink TDOA (UL-TDOA).

[0188] It can be understood that in addition to measuring the time difference, positioning can also be performed by measuring the angle. The angle can be the angle of arrival AOA, or it can be the angle of departure (angle of depature, AOD). The angle of arrival is used to indicate the angle between the direction in which the receiving end receives the signal and the reference direction; the angle of departure is used to indicate the angle between the direction in which the transmitting end sends the signal and the reference direction. Among them, the reference direction can be a direction determined according to the position and / or shape of the antenna.

[0189] In actual communication scenarios, due to the influence of noise and interference, there will be certain measurement errors in the measurement values ​​of time or angle, and the corresponding positioning results will also have certain errors.

[0190] Figure 8 is a schematic diagram of LOS and NLOS. Figure 8 As shown, the LOS between the network device and the terminal device (such as Figure 8 The dotted line in the figure is blocked by an obstruction, and the reference signal transmitted between the network device and the terminal device is actually the reflected NLOS (such as Figure 8 The solid line in the figure shows that the distance of NLOS (i.e., d2+d3) is greater than the distance of LOS (i.e., d1). If NLOS is considered as LOS when estimating the position, a large measurement error may occur. Therefore, the classification of LOS and NLOS is also important for positioning accuracy.

[0191] In AI-based positioning technology, the AI ​​positioning model is usually deployed in the LMF. The AI ​​positioning model takes the channel measurement results reported by the channel measurement network element as input and the location of the terminal device as output. Therefore, the channel measurement network element usually needs to report the channel measurement report to the location management function network element. Exemplarily, the protocol supports that in uplink positioning, the LMF sends an NRPPa measurement request to the gNB to obtain the measurement result. Correspondingly, the gNB measures the SRS signal sent by the UE, obtains the RSRPP result, and sends the RSRPP result to the LMF. Among them, RSRPP is defined as the linear average power value of the i-th path of the channel response obtained by measuring the SRS on the corresponding subband. In addition, the protocol supports reporting of RSRPP results including RSRPP absolute value reporting and RSRPP differential value reporting. Considering that in the current solution, the location management function network element manages the terminal device positioning function in the process of managing the AI ​​positioning function or AI positioning model, the monitoring strategy of the AI ​​positioning function or AI positioning model, the update strategy of the AI ​​positioning function or AI positioning model, the measurement quantity corresponding to the AI ​​positioning function or AI positioning model, and the reporting method of the measurement results obtained by measuring the measurement quantity, usually multiple signalings are used to indicate them separately, or multiple fields in one signaling are used to indicate them separately, which may bring more signaling overhead.

[0192] In view of this, an embodiment of the present application provides a communication method and device, which is based on the correspondence between the input / output measurement quantities of the AI ​​positioning use case and the AI ​​positioning function or AI positioning model. The AI ​​positioning function or AI positioning model can be indicated by sending indication information, so that the first terminal device can determine the measurement quantity corresponding to the AI ​​positioning function or AI positioning model, that is, by obtaining the indication information, the AI ​​positioning function or AI positioning model, and the measurement quantity corresponding to the AI ​​positioning function or AI positioning model can be determined at the same time, thereby achieving the purpose of reducing signaling overhead.

[0193] The communication method provided by the embodiment of the present application will be described in detail below with reference to the accompanying drawings. The embodiment provided by the present application can be applied to the above Figure 1 or Figure 2 The communication system shown is not limited.

[0194] Fig. 9 9 is a schematic flow chart of a communication method 900 provided in an embodiment of the present application. Fig. 9 As shown, method 900 may include the following multiple steps. It should be understood that the method may be performed by the first device and the location management function network element, or may be performed by the chip or circuit of the first device and the location management function network element, and this application does not limit this. For ease of description, the following example is taken as the execution subject of the first device and the location management function network element.

[0195] S910, the location management function network element sends indication information to the first device (ie, the network element that performs channel measurement, or simply referred to as the channel measurement network element, or referred to as the reference signal measurement node, etc.), and correspondingly, the first device receives the indication information from the location management function network element.

[0196] Among them, the indication information is used to indicate the AI ​​positioning function or the AI ​​positioning model, the AI ​​positioning function or the AI ​​positioning model belongs to multiple AI positioning functions or AI positioning models, and the multiple AI positioning functions or AI positioning models correspond to multiple different measurement quantity sets, and the measurement quantity set includes one or more measurement quantities.

[0197] In the embodiment of the present application, the AI ​​model refers to an AI model used for positioning, referred to as an AI positioning model for short.

[0198] Optionally, the indication information is carried in a measurement request message from a location management function network element. For example, the location management function network element sends a measurement request message to the first device, and the measurement request message carries the indication information. The measurement request message is used to instruct the first device to perform channel measurement. In other words, the measurement request message is used to trigger the first device to perform channel measurement.

[0199] Optionally, the measurement request message and the indication information sent by the location management function network element may be sent together or independently. In other words, the indication information may not be carried in the measurement request message. In this case, the measurement request message and the indication information may be sent simultaneously or separately, and this application does not limit this.

[0200] S920: The first device sends a channel measurement result to the location management function network element according to the indication information. Correspondingly, the location management function network element receives the channel measurement result from the first device.

[0201] Among them, the measurement quantity corresponding to the channel measurement result corresponds to the AI ​​positioning function or AI positioning model indicated by the indication information.

[0202] Optionally, the channel measurement result is included in a measurement report. For example, the first device sends a measurement report to the location management function network element, and the measurement report carries the channel measurement result.

[0203] In an embodiment of the present application, a channel measurement report is used to report channel measurement results (or channel features extracted from channel measurement results, and each embodiment is described by taking channel measurement results as an example), and the channel measurement results are used by the location management function network element to perform AI-related operations, such as model reasoning based on an AI positioning model. Therefore, the AI ​​positioning model uses the channel measurement results (or channel features extracted from the channel measurement results) as input and the location of the terminal device as output, so the purpose of the channel measurement report is to report the input of the AI ​​positioning model. Based on this premise, the channel measurement results in the channel measurement report in this application are determined based on the AI ​​positioning function or AI positioning model indicated by the indication information from the location management function network element. The channel measurement network element (such as UE or gNB) feeds back the measurement quantity corresponding to the channel measurement result corresponding to the AI ​​positioning function or AI positioning model to the location management function network element. For the correspondence between the input / output measurement quantities of the AI ​​positioning use case and different AI positioning functions or AI positioning models, the AI ​​positioning function or AI positioning model can be determined through the indication information, and then the measurement quantity corresponding to the AI ​​positioning function or AI positioning model is determined to perform positioning of the terminal device. Compared with indicating the AI ​​positioning function or AI positioning model and the measurement quantity corresponding to the AI ​​positioning function or AI positioning model through multiple signaling, the signaling overhead can be reduced.

[0204] Exemplarily, in an uplink positioning scenario, when the first device is a network device, the channel measurement result is obtained based on a first channel measurement, and the first channel measurement includes: the network device measures a sounding reference signal (eg, SRS) from the terminal device.

[0205] Exemplarily, in a downlink positioning scenario, when the first device is a terminal device, the channel measurement result is obtained based on a second channel measurement, where the second channel measurement includes: the terminal device measures a positioning reference signal (e.g., PRS, or preamble) or a channel state information reference signal (CSI-RS) from an access network device;

[0206] Exemplarily, in a sidelink positioning scenario, when the first device is a first terminal device, the channel measurement result is obtained based on a third channel measurement, and the third channel measurement includes: the first terminal device measures a sidelink positioning reference signal (SL-PRS) from the second terminal device.

[0207] In the embodiment of the present application, the first device may be a terminal device or a network device. Optionally, when the first device is a network device, the AI ​​positioning model configured in the network device is used for auxiliary positioning, and the AI ​​positioning model configured in the location management function network element is used for direct positioning.

[0208] In an embodiment of the present application, the input of the AI ​​positioning model is the channel measurement result, and the output of the AI ​​positioning model is used to directly or indirectly determine the location of the terminal device. For example, the output of the AI ​​positioning model can be the location of the terminal device, or it can be auxiliary positioning information used to determine the location of the terminal device, without limitation.

[0209] As an example, the channel measurement result may be used as the input of the AI ​​positioning model. For the AI ​​positioning model, the input of the AI ​​positioning model may be the channel measurement result obtained based on the reference signal measurement, and the output of the AI ​​positioning model may be the location of the terminal device.

[0210] For example, the AI ​​positioning model is used to directly locate the position of the terminal device. In this case, the input of the AI ​​positioning model is the channel measurement result obtained based on the reference signal measurement, and the output is the position of the terminal device, such as the position coordinates of the terminal device on the X-axis and Y-axis.

[0211] For another example, the AI ​​positioning model is used to assist in positioning the terminal device (or indirectly). In this case, the input of the AI ​​positioning model is the channel measurement result obtained based on the reference signal measurement, and the output is auxiliary positioning information, which is used to determine the location of the terminal device. The auxiliary positioning information includes but is not limited to at least one of the following: LOS probability, AOA, AOD, time of arrival (TOA), or TDOA of the reference signal.

[0212] As another example, auxiliary positioning information based on channel measurement results can be used as input to an AI positioning model. For an AI positioning model, the input of the AI ​​positioning model may be auxiliary positioning information based on channel measurement results, and the output of the AI ​​positioning model may be the location of the terminal device. The auxiliary positioning information based on the channel measurement results may be obtained in a traditional manner, or may be the output of a certain AI positioning model, without limitation. The auxiliary positioning information includes, but is not limited to, at least one of the following: LOS probability, AOA, AOD, time of arrival (TOA), or TDOA of a reference signal.

[0213] For example, the AI ​​positioning model is used to directly locate the position of the terminal device. In this case, the input of the AI ​​positioning model is auxiliary positioning information based on the channel measurement results, and the output is the position of the terminal device.

[0214] For another example, the AI ​​positioning model is used to assist in positioning the terminal device (or indirectly position the terminal device). In this case, the input of the AI ​​positioning model is auxiliary positioning information based on the channel measurement result, and the output is another auxiliary positioning information, which is used to determine the location of the terminal device.

[0215] It should be noted that the embodiments of the present application are mainly described by taking channel measurement based on a reference signal to obtain a channel measurement result as an example, and are not limited to this. For example, the channel measurement result may also include the result of pedestrian dead-reckoning (PDR) measurement of the terminal; or, the channel measurement result may also include a camera environment monitoring recognition result, such as an indoor factory surveillance camera environment monitoring recognition result.

[0216] In the embodiment of the present application, the AI ​​positioning function or AI positioning model corresponds to one or more of the following measurement quantities:

[0217] (1) LOS recognition results;

[0218] Exemplarily, the LOS identification result includes LOS or NLOS, and / or LOS probability.

[0219] Among them, LOS refers to the transmission of signals between the transmitting antenna and the receiving antenna at a distance where they can "see each other". It can be understood that there are no obstacles between the two antennas that affect signal propagation, and the signal can be fully transmitted. Non-line-of-sight refers to the transmission of signals between the transmitting antenna and the receiving antenna at a distance where they "cannot see each other". It can be understood that there are obstacles between the two antennas that affect signal propagation, and the signal cannot be fully transmitted. The LOS probability can be used to determine the NLOS degree of the channel environment. Different NLOS degrees (that is, different channel conditions) have different degrees of influence on the inference accuracy of the AI ​​positioning model due to different channel measurement results. Therefore, the first device can obtain the NLOS degree of the channel based on the channel measurement results, thereby obtaining the current channel conditions. For example, LOS (1) or NLOS (0) can be used to indicate that the LOS between the network device and the terminal device is not blocked by an obstruction, and the reference signal transmitted between the network device and the terminal device is not affected.

[0220] The channel propagation condition of the LOS path has a direct line of sight path, but may also include scenarios with NLOS paths. In other words, there is at least one LOS path (i.e., a pure LOS path), but the number of NLOS paths is not limited. The channel propagation condition of the NLOS path does not have a direct line of sight path, that is, there is only a scenario with an NLOS path. For example, the line-of-sight identification result can be regarded as a measurement quantity of a channel measurement. A channel may include one or more paths (e.g., a path set). The line-of-sight identification result may be the average LOS probability of the line-of-sight identification results corresponding to all paths in a channel, or the LOS or NLOS identification result with the highest frequency.

[0221] (2) Arrival time TOA estimation results.

[0222] Exemplarily, TOA is a method for calculating the physical distance by using the transmission delay of a wireless signal between two nodes, that is, determining the location by measuring the time interval from sending a signal to receiving a signal, and usually requires synchronization of timing at the receiving node. For example, the arrival time estimation result can be regarded as a measurement quantity of a channel measurement, a channel can include one or more paths (such as a path set), and the arrival time estimation result can be the average of the arrival time estimation results corresponding to all paths in a channel.

[0223] (3) Arrival angle AOA estimation results.

[0224] Exemplarily, by sending a data packet with direction finding capability using a single antenna, a low energy (LE) device can make its direction available to a peer device. The peer device includes an RF switch and an antenna array, which switches the antenna and obtains IQ samples when receiving a portion of the data packet. The IQ samples can be used to calculate the phase difference of the radio signals received by different elements of the antenna array, which can then be used to estimate the angle of arrival AoA. For example, the angle of arrival estimation result can be regarded as a measurement quantity of a channel measurement, a channel can include one or more paths (e.g., a set of paths), and the angle of arrival estimation result can be the average of the angle of arrival estimation results corresponding to all paths in a channel.

[0225] (4) LOS identification results corresponding to each path in the first path set.

[0226] Exemplarily, the first path set includes one or more paths, and the LOS identification result corresponding to each path includes LOS or NLOS, and / or LOS probability. The LOS identification result corresponding to each path can be the same or different, and the present application does not limit the number of paths. For example, the first path set includes path #1, wherein the LOS identification result of path #1 can be LOS(1) or NLOS(0), indicating that there is a direct line of sight for path #1, that is, there is no obstacle between the network device and the terminal device, and the signal can be completely transmitted. Optionally, the first path set also includes path #2, wherein the LOS identification result of path #2 can be LOS(0) or NLOS(1), indicating that there is no direct line of sight for path #2, that is, there is an obstacle between the network device and the terminal device, and the signal cannot be completely transmitted, that is, the LOS identification results corresponding to path #1 and path #2 are different.

[0227] (5) The delay corresponding to each path in the second path set.

[0228] Exemplarily, the second path set includes one or more paths, and the delay corresponding to each path can be the same or different. The present application does not limit the number of paths. For example, the second path set includes path #3, and the delay of path #3 is delay #1. Optionally, the second path set can also include path #4, and the delay of path #4 is delay #2, where delay #1 = 10ms, delay #2 = 8ms, that is, the delays corresponding to path #3 and path #4 are different; or, delay #1 = delay #2 = 5ms, that is, the delays corresponding to path #3 and path #4 are the same.

[0229] (6) The amplitude corresponding to each path in the third path set.

[0230] Exemplarily, the third path set includes one or more paths, and the amplitude corresponding to each path can be the same or different, and the present application does not limit the number of paths. For example, the third path set includes path #5, and the amplitude of path #5 is amp1. Optionally, the third path set can also include path #6, and the amplitude of path #6 is amp2, for example, amp1=1, amp2=2, that is, the amplitudes corresponding to path #5 and path #6 are different; or, amp1=amp2=0.5, that is, the amplitudes corresponding to path #5 and path #6 are the same.

[0231] (7) The phase corresponding to each path in the fourth path set.

[0232] Exemplarily, the fourth path set includes one or more paths, and the phase corresponding to each path can be the same or different, and the present application does not limit the number of paths. For example, the fourth path set includes path #7, and the phase of path #7 is phase1. Optionally, the fourth path set can also include path #8, and the phase of path #8 is phase2, for example, phase1 = 30°, phase2 = 45°, that is, the phases corresponding to path #7 and path #8 are different; or, phase1 = phase2 = 10°, that is, the phases corresponding to path #7 and path #8 are the same.

[0233] It should be noted that at least two of the first path set, the second path set, the third path set, and the fourth path set are the same or different. For example, assuming that the first path set and the second path set are the same, for example, the first path set and the second path set both include path #1, path #2, path #3, and path #4, then the channel result obtained by the first device performing channel measurement according to the reference signal includes the LOS identification results and delays corresponding to the four paths.

[0234] For example, the LOS identification result corresponding to path #1 is LOS(1) and the delay is 2ms, the LOS identification result corresponding to path #2 is LOS(1) and the delay is 3ms, the LOS identification result corresponding to path #3 is NLOS(1) and the delay is 6ms, and the LOS identification result corresponding to path #4 is NLOS(1) and the delay is 4ms. It can be seen that the LOS identification results of path #1 and path #2 are the same, but the delays are different, and the LOS identification results of path #3 and path #4 are the same, and the delays are also the same.

[0235] For another example, assuming that the second path set, the third path set and the fourth path set are the same, for example, the second path set, the third path set and the fourth path set all include path #3, path #4, path #5, path #6, path #7 and path #8, then the channel result obtained by the first device performing channel measurement according to the reference signal includes the delays, amplitudes and phases corresponding to the six paths. For example, the delay corresponding to path #3 is 2ms, the amplitude is 1, and the phase is 30°, the delay corresponding to path #4 is 2ms, the amplitude is 2, and the phase is 20°, the delay corresponding to path #5 is 5ms, the amplitude is 1, and the phase is 45°, the delay corresponding to path #6 is 2ms, the amplitude is 0, and the phase is 30°, the delay corresponding to path #7 is 4ms, the amplitude is 2, and the phase is 45°, and the delay corresponding to path #8 is 6ms, the amplitude is 2, and the phase is 30°. It can be seen from this that the time delays of paths #3, #4 and #6 are the same, the amplitudes of paths #3 and #5 are the same, the amplitudes of paths #4, #7 and #8 are the same, the phases of paths #3, #6 and #8 are the same, the amplitudes of paths #5 and #7 are the same, etc.

[0236] In the embodiment of the present application, the AI ​​positioning function or AI positioning model also corresponds to one of the following reporting methods:

[0237] (1) The measurement results of each diameter in the same measurement volume are reported independently.

[0238] Exemplarily, the measurement result of each path in the same measurement quantity is reported independently, including: the measurement result of each path in the same measurement quantity in the same measurement report is reported independently. For example, assuming that there are path #1, path #2, path #3 and path #4, and the measurement quantity corresponding to the AI ​​positioning function or AI positioning model indicated by the indication information is the delay corresponding to each path, then in the same measurement report, the delays corresponding to path #1, path #2, path #3 and path #4 are reported independently, for example, the delay corresponding to path #1 is 2ms, the delay corresponding to path #2 is 4ms, the delay corresponding to path #3 is 6ms, and the delay corresponding to path #4 is 5ms, that is, the measurement report may include: path #1, path #2, path #3 and path #4 and their corresponding delay results, such as 2ms, 4ms, 6ms and 5ms, and this application does not limit the number of paths.

[0239] Optionally, the measurement results of each path in the same measurement quantity in different measurement reports may also be reported independently.

[0240] (2) The measurement results of each diameter in the same measurement quantity are reported in a differential manner.

[0241] Exemplarily, the measurement result of each path in the same measurement quantity is reported in a differential manner, including: the measurement result of each path in the same measurement quantity in the same measurement report is reported in a differential manner. For example, assuming that there are path #1, path #2, path #3 and path #4, and the measurement quantity corresponding to the AI ​​positioning function or AI positioning model indicated by the indication information is the delay corresponding to each path, then in the same measurement report, the delays corresponding to path #1, path #2, path #3 and path #4 can be differentially reported based on the reference path, and the delay corresponding to the reference path is reported in absolute value. For example, if the delay corresponding to path #1 is 2ms, the delay corresponding to path #2 is 4ms, the delay corresponding to path #3 is 6ms, and the delay corresponding to path #4 is 5ms, then the measurement report may include: path #1 and its corresponding delay delay #1 is 2ms, path #2 and its delay difference △1 with path #1 is 2ms, path #3 and its delay difference △2 with path #2 is 2ms, and path #4 and its delay difference △3 with path #3 is -1ms. Then, after receiving the measurement report, the location management function network element can determine that the delay delay#2 corresponding to path #2 is 4ms based on delay#1 and △1, determine that the delay delay#3 corresponding to path #3 is 6ms based on delay#2 and △2, and determine that the delay delay#4 corresponding to path #4 is 5ms based on delay#3 and △3. This application does not limit the number of paths.

[0242] It should be understood that reporting the measurement results in a differential manner can reduce signaling overhead.

[0243] Optionally, the measurement results of the same measurement quantity in different measurement reports may also be reported in a differential manner, which can further reduce signaling overhead.

[0244] Exemplarily, in an uplink positioning scenario, assuming that the measurement quantity corresponding to the AI ​​positioning function or AI positioning model indicated by the location management function network element is the arrival time TOA estimation result, the terminal device measures the two PRSs from the access network device respectively, and reports the channel measurement results in different measurement reports. For example, the terminal device performs channel measurement on PRS#1 from the access network device, and obtains channel measurement result #1 as TOA#1. The terminal device performs channel measurement on PRS#2 from the access network device, and obtains channel measurement result #2 as TOA#2. Then, measurement result #1 is carried as TOA#1 in measurement report #1, and △TOA is carried in measurement report #2, where TOA#1+△TOA=TOA#2. Then, after receiving measurement report #1 and measurement report #2, the location management function network element can further determine that the TOA corresponding to measurement result #2 is TOA #2 based on TOA #1 and △TOA. That is to say, the location management function network element can explicitly know that channel measurement result #1 is TOA #1 based on the two measurement reports obtained, and implicitly know that channel measurement result #2 is TOA #2, etc.

[0245] To sum up, the first device can determine the corresponding measurement amount and / or reporting method according to the AI ​​positioning function or AI positioning model indicated by the received indication information, and then send the corresponding channel measurement result to the location management function network element according to the determined reporting method.

[0246] Exemplarily, there is a mapping relationship between the AI ​​positioning function or AI positioning model and the measurement amount and / or reporting method corresponding to the channel measurement result, that is, the first device can determine the measurement amount and / or reporting method corresponding to the channel measurement result according to the received indication information and the mapping relationship, and then send the channel measurement result to the location management function network element. In other words, different indication information indicates different AI positioning functions or AI positioning models, and the corresponding channel measurement results The corresponding measurement amount and / or reporting method may also be different.

[0247] The mapping relationship may be predefined, and the predefined relationship may include a predefined relationship, such as a protocol definition. Alternatively, the mapping relationship is configured or preconfigured, and the preconfiguration may be implemented by pre-saving corresponding codes, tables, or other methods that can be used to indicate relevant information in the device, and the present application does not limit the specific implementation method thereof.

[0248] Optionally, the mapping relationship can exist in the form of a table, function, text, or string, such as for storage or transmission.

[0249] In an embodiment of the present application, the AI ​​positioning function or the AI ​​positioning model belongs to multiple AI positioning functions or multiple AI positioning models, and the multiple AI positioning functions or multiple AI positioning models correspond one-to-one to multiple different measurement quantity sets, each measurement quantity set includes one or more measurement quantities, wherein the measurement quantity includes a line-of-sight recognition result; an arrival time estimation result; an arrival angle estimation result; a line-of-sight recognition result corresponding to each path in the first path set; a time delay corresponding to each path in the second path set; an amplitude corresponding to each path in the third path set; and one of the phases corresponding to each path in the fourth path set. The interpretation of the specific measurement quantities can refer to the above-mentioned relevant description.

[0250] Below, the mapping relationship between the AI ​​positioning model or AI positioning function indicated by the indication information and the measurement amount / reporting method corresponding to the channel measurement result is exemplified in the form of a table, wherein the mapping relationship between the measurement amount corresponding to the above-mentioned channel measurement result and the AI ​​positioning function can satisfy the following Table 1, and the mapping relationship between the reporting method of the above-mentioned channel measurement result and the AI ​​positioning function can satisfy the following Table 2. It should be noted that Tables 1 to 2 provided in the present application are applicable to uplink, downlink or side positioning scenarios, which are only examples given for ease of understanding and do not constitute any limitation on this scheme. Optionally, the present application does not limit the number of corresponding relationships between the AI ​​positioning function and the measurement amount in Table 1 (for example, a row in a table). For example, AI positioning function #1 to AI positioning function #7, and AI positioning function #8 to AI positioning function #33 in Table 1 can be independently formed into new tables, that is, Table 1 can be split into multiple other tables for examples, and the present application does not limit this, nor does it limit the splitting method.

[0251] Table 1

[0252]

[0253]

[0254] In one example, assuming that the value of the LOS identification result "1" represents LOS, and the value "0" represents NLOS, if the value of the LOS identification result corresponding to the AI ​​positioning function #1 measured by the first device is 1, it means that the measurement result corresponding to the AI ​​positioning function #1 represents LOS. If the value of the LOS identification result corresponding to the AI ​​positioning function #1 measured is 0, it means that the measurement result corresponding to the AI ​​positioning function #1 represents NLOS. It should be understood that the LOS identification result can reflect the parameters of the channel environment, or the parameters that can reflect the channel conditions. In other words, changes in the channel environment can be reflected in the measurement results of the LOS identification result. For example, the LOS identification result represents a parameter that can reflect the degree of NLOS of the channel.

[0255] In an example, it is assumed that the arrival time TOA estimation result corresponding to the AI ​​positioning function #2 measured by the first device is TOA1, wherein TOA1 can be a specific value or a value range, which is not limited.

[0256] In one example, it is assumed that the arrival time AOA estimation result corresponding to the AI ​​positioning function #3 measured by the first device is AOA1, wherein AOA1 can be a specific value or a value range, which is not limited.

[0257] In one example, assuming that the value of the line-of-sight LOS recognition result "1" represents LOS, and the value "0" represents NLOS, and the first path set includes path #1 and path #2, if the value of the LOS recognition result of path #1 in the first path set corresponding to the AI ​​positioning function #4 measured by the first device is 1, and the value of the LOS recognition result of path #2 in the first path set is 0, it means that the measurement result of path #1 in the first path set represents LOS, and the measurement result of path #2 in the first path set represents LOS. This application does not limit the number of paths in the first set.

[0258] In one example, the second path set includes path #1, path #2 and path #3. Assuming that the delay of path #1 in the second path set corresponding to the AI ​​positioning function #5 measured by the first device is 4ms, the delay of path #2 in the second path set is 3ms, and the delay of path #3 in the second path set is 4ms. This application does not limit the number of paths in the second set.

[0259] In one example, the third path set includes path #1 and path #2. Assume that the amplitude of path #1 in the third path set corresponding to AI positioning function #6 measured by the first device is amp1, and the amplitude of path #2 in the third path set is amp2, wherein the amplitude corresponding to each path can be a specific value or a range of values, which is not limited. The present application does not limit the number of paths in the third set.

[0260] In one example, the fourth path set includes path #1 and path #2. Assume that the phase of path #1 in the fourth path set corresponding to the AI ​​positioning function #7 measured by the first device is phase 1, and the phase of path #2 in the fourth path set is phase 2, wherein the phase corresponding to each path can be a specific value or a range of values, which is not limited. The present application does not limit the number of paths in the fourth set.

[0261] It should be understood that the above mapping relationships between AI positioning functions #1 to AI positioning functions #7 and the measured quantities are only examples for easy understanding. The specific implementation methods of the mapping relationships between other AI positioning functions #8 to AI positioning functions #33 and the measured quantities can be referred to the above related descriptions. For the sake of brevity, they will not be repeated here.

[0262] Optionally, for the above Table 1, the AI ​​positioning function may correspond to one or more AI positioning models, that is, the measurement quantity corresponding to the channel measurement result corresponds to one or more AI positioning models. For example, taking AI positioning function #3 as an example, if AI positioning function #3 includes AI positioning model #1 and AI positioning model #2, the arrival angle AOA estimation result corresponding to AI positioning model #1 measured by the first device may be AOA11, and the arrival angle AOA estimation result corresponding to AI positioning model #2 may be AOA12. When the indication information received by the first device indicates AI positioning function #3, the measurement result reported by the first device may be the arrival angle AOA estimation result AOA11 corresponding to AI positioning model #1 contained in AI positioning function #3, and the arrival angle AOA estimation result AOA12 corresponding to AI positioning model #2 contained in AI positioning function #3. It should be understood that this implementation method is also applicable to other AI positioning functions in the above Table 1, and for the sake of brevity, it will not be repeated here.

[0263] Considering that in the embodiment of the present application, the AI ​​positioning function also corresponds to one of the following reporting methods: the measurement result of each path in the same measurement amount is reported independently (independent reporting for short); or, the measurement result of each path in the same measurement amount is reported in a differential manner (differential reporting for short), that is, for each AI positioning function in Table 1 above, it can correspond to independent reporting or differential reporting. In this case, the AI ​​positioning function in Table 1 that can correspond to both independent reporting and differential reporting can be replaced by two AI positioning functions, one corresponding to independent reporting and the other corresponding to differential reporting. Below, the mapping relationship between each AI positioning function and the reporting method shown in Table 1 is explained by taking Table 2 as an example. It should be understood that Table 2 is only an example given for ease of understanding and does not constitute a limitation on the technical solution of the present application. For example, the reporting method corresponding to AI positioning function #1 may be differential reporting, or the reporting method corresponding to AI positioning function #5 may also be independent reporting, and the present application does not limit this.

[0264] Table 2

[0265]

[0266]

[0267] As shown in Table 2, the reporting mode corresponding to AI positioning function #5, AI positioning function #12, AI positioning function #15, AI positioning function #16, AI positioning function #18 to AI positioning function #23, AI positioning function #26, AI positioning function #27, AI positioning function #29, AI positioning function #30, AI positioning function #32, and AI positioning function #33 is differential reporting, and the reporting mode corresponding to AI positioning function #1 to AI positioning function #4, AI positioning function #6 to AI positioning function #11, AI positioning function #13, AI positioning function #14, AI positioning function #17, AI positioning function #24, AI positioning function #25, AI positioning function #28, and AI positioning function #31 is independent reporting.

[0268] Optionally, the reporting method in the above Table 2 can be explicitly indicated or implicitly indicated. For example, Table 2 may only reflect the mapping relationship between the AI ​​positioning function and the differential reporting method. After the first device receives the indication information from the location management function network element, if the reporting method corresponding to the AI ​​positioning function indicated by the indication information is empty, it indicates that the measurement result of the measurement quantity corresponding to the AI ​​positioning function is reported to the location management function network element in an independent reporting manner.

[0269] It should be understood that the mapping relationship between the AI ​​positioning function and the measurement amount corresponding to the measurement result shown in Table 1 above and the mapping relationship between the AI ​​positioning function and the reporting method of the measurement result shown in Table 2 can be implemented independently or in combination, and this application does not limit this. For example, one or more rows in Table 1 can be embodied in a table with the corresponding reporting method in Table 2, that is, after receiving the indication information from the location management function network element, the first device can simultaneously know the measurement amount corresponding to the AI ​​positioning function and the reporting method of the measurement result.

[0270] Exemplarily, assuming that the indication information sent by the location management function network element indicates AI positioning function #19, the first device sends the measurement results of the delay corresponding to each path in the first path set and the amplitude corresponding to each path in the first path set to the location management function network element in a differential reporting manner. For example, the first path set includes path #1, path #2, and path #3, then the first device can obtain the delay and amplitude corresponding to path #1, path #2, and path #3 by performing channel measurement based on the reference signal, and at the same time, the first device can determine that the measurement results of the delay and amplitude corresponding to path #1, path #2, and path #3 corresponding to AI positioning function #19 can be reported to the location management function network element in a differential manner. For example, the measurement results reported by the first device include: the delay delay#1 of path #1 is 4ms, the delay difference △1 between path #2 and path #1 is -1ms, the delay difference △2 between path #3 and path #2 is 1ms, the amplitude of path #1 is amp1, the amplitude difference between path #2 and path #1 is △1', and the amplitude difference between path #3 and path #2 is △2'. Then, after receiving the measurement results, the location management function network element can determine that the delay delay#2 of path #2 is 3ms based on the delay delay#1 and △1 of path #1, determine that the delay delay#3 of path #3 is 4ms based on the delay delay#2 and △2 of path #2, and determine that the amplitude of path #2 is amp2=amp1+△1' based on the amplitude amp1 and △1' of path #1, and determine that the amplitude of path #3 is amp3=amp2+△2' based on the amplitude amp2 and △2' of path #2. Optionally, the first device can also use the delay and amplitude corresponding to path #2 as a reference to report the delay and amplitude corresponding to path #1 and path #3 to the location management function network element in a differential manner, as long as the location management function network element and the first device are pre-defined, and this application does not limit this. Other combination implementations are similar and will not be repeated here for the sake of brevity.

[0271] It should be understood that the above Table 1 and Table 2 are merely examples given for ease of understanding and do not constitute any limitation on the technical solution of the present application.

[0272] It should be noted that the above Tables 1 and 2 respectively illustrate the mapping relationship between the AI ​​positioning function and the measurement quantity, and the AI ​​positioning function and the reporting method corresponding to the measurement result. Optionally, the mapping relationship between the AI ​​positioning model and the measurement quantity, and the AI ​​positioning model and the reporting method corresponding to the measurement result in the embodiment of the present application can also be reflected in the form of a table. The specific implementation method can refer to the above Tables 1 and 2 respectively. For example, replacing the AI ​​positioning function in Tables 1 and 2 with the AI ​​positioning model can illustrate the mapping relationship between AI positioning model #1 to AI positioning model #33 and the measurement quantity, as well as the mapping relationship between AI positioning model #1 to AI positioning model #33 and the reporting method corresponding to the measurement result.

[0273] Optionally, the mapping relationship between the AI ​​positioning model and the reporting method can be explicitly indicated or implicitly indicated. For example, only the mapping relationship between the AI ​​positioning model and the differential reporting method can be reflected. Then, after the first device receives the indication information from the location management function network element, if the reporting method corresponding to the AI ​​positioning model indicated by the indication information is empty, it indicates that the measurement result of the measurement quantity corresponding to the AI ​​positioning model is reported to the location management function network element in an independent reporting manner.

[0274] It should be understood that the mapping relationship between the AI ​​positioning model and the measurement quantity corresponding to the measurement result, and the mapping relationship between the AI ​​positioning model and the reporting method of the measurement result can be implemented independently or in combination, and this application does not limit this. For example, the mapping relationship between the AI ​​positioning model, the measurement quantity corresponding to the measurement result, and the reporting method of the measurement result can be reflected in a table, that is, after the first device receives the indication information from the location management function network element, it can know the measurement quantity corresponding to the AI ​​positioning model and the reporting method of the measurement result at the same time.

[0275] Exemplarily, assuming that the indication information sent by the location management function network element indicates the AI ​​positioning function #21, the first device sends the measurement results of the delay corresponding to each path in the first path set and the phase corresponding to each path in the first path set to the location management function network element in a differential reporting manner. For example, the first path set includes path #1 and path #2, then the first device can obtain the delay and phase corresponding to path #1 and path #2 by performing channel measurement based on the reference signal, and the first device can determine that the measurement results of the delay and phase corresponding to path #1 and path #2 corresponding to the AI ​​positioning function #21 can be reported to the location management function network element in a differential manner. For example, the measurement results reported by the first device include: the delay delay#1 of path #1 is 4ms, the delay difference △1 between path #2 and path #1 is -1ms, the phase of path #1 is phase1, and the phase difference between path #2 and path #1 is △1'. Then, after receiving the measurement results, the location management function network element can determine that the delay delay#2 of path #2 is 3ms based on the delay delay#1 and △1 of path #1, and determine that the phase of path #2 is phase2=phase1+△1' based on the phase phase1 and △1' of path #1. Optionally, the first device can also use the delay and phase corresponding to path #2 as a reference, and report the delay and phase corresponding to path #1 to the location management function network element in a differential manner, as long as the location management function network element and the first device are pre-defined, and this application does not limit this. Other combined implementations are similar and will not be repeated here for the sake of brevity.

[0276] Optionally, the first device may also determine a monitoring strategy for the AI ​​positioning function or the AI ​​positioning model, an update strategy for the AI ​​positioning function or the AI ​​positioning model, etc. based on the indication information.

[0277] Exemplarily, the monitoring strategy of the AI ​​positioning function or AI positioning model includes at least one of the following:

[0278] (1) Monitoring the data distribution of the measurement results of the measurement quantity corresponding to the input of the AI ​​positioning function / model: for example, monitoring is performed based on the signal to interference plus noise ratio (SINR) of the channel measurement result. When the SINR satisfies the first condition, it meets the current monitoring criteria and no operation is required for the AI ​​positioning function / model; otherwise, the AI ​​positioning function / model needs to be operated; wherein the first condition includes that the SINR is greater than or equal to the first threshold and less than or equal to the second threshold, or the SINR is greater than the first threshold and less than the second threshold, or the SINR is greater than or equal to the first threshold and less than the second threshold, or the SINR is greater than or equal to the first threshold and less than the second threshold, or the SINR is greater than the first threshold and less than the second threshold;

[0279] (2) Monitoring based on the data distribution of the results outputted by the AI ​​positioning function / model: For example, monitoring is performed based on the position results outputted by the AI ​​direct positioning function / model. For the same AI direct positioning function / model, if the position results outputted twice adjacently meet the second condition, it is necessary to perform an operation on the AI ​​positioning function / model; otherwise, it is not necessary to perform an operation on the AI ​​positioning function / model; wherein the position results outputted twice adjacently meet the second condition, including that the difference between the position results outputted twice adjacently is greater than a third threshold, or that the difference between the position results outputted twice adjacently is greater than or equal to the third threshold;

[0280] (3) Monitoring based on the correct value of the result outputted by the AI ​​positioning function / model: For example, monitoring is performed based on the position result outputted by the AI ​​direct positioning function / model. For the same AI direct positioning function / model, for the first input with a known output, that is, the first input corresponding to the existing output label or true value, if the output position result satisfies the third condition, it is necessary to operate on the AI ​​positioning function / model; otherwise, it is not necessary to operate on the AI ​​positioning function / model; wherein, the output position result satisfies the third condition including that the difference between the output position result and the correct value of the output position result, that is, the true value, is greater than a third threshold, or that the difference between the output position result and the true value is greater than or equal to the third threshold.

[0281] Among them, the above operations on the AI ​​positioning function / model include one or more of switching, updating, or deactivating.

[0282] Exemplarily, the update strategy of the AI ​​positioning function or the AI ​​positioning model includes at least one of the following:

[0283] (1) Update all parameters of the AI ​​positioning function or AI positioning model;

[0284] (2) Update some parameters of the AI ​​positioning function or AI positioning model;

[0285] (3) Switch to the specified AI positioning function or AI positioning model.

[0286] Based on the monitoring strategy and update strategy of the above-mentioned AI positioning function or AI positioning model, the first device can monitor and update the AI ​​positioning function or AI positioning model in a timely manner, can obtain a more accurate location of the terminal device, and realize effective management of the terminal device.

[0287] To summarize, by defining the correspondence between the measurement quantity corresponding to the channel measurement result and the AI ​​positioning function or AI positioning model indicated by the indication information, and defining the correspondence between the AI ​​positioning function or AI positioning model and the reporting method of the measurement result, after receiving the indication information, the first device can determine the channel measurement result expected by the location management function network element, and report the measurement result to the location management function network element in a corresponding reporting method, which can reduce signaling overhead.

[0288] The following combination Figures 10 to 12 , the application of the embodiments of the present application in the uplink positioning scenario, the downlink positioning scenario and the side positioning scenario are illustrated respectively, and it should be understood that, Figures 9 to 12 The method embodiments shown can be combined with each other. Figures 9 to 12 The steps in the method embodiments shown can refer to each other. For example, in the embodiments of the present application, Fig.10 and Fig.12 The method embodiment shown can be regarded as implementing Fig. 9 A possible implementation of the functions of the method embodiment shown, wherein: Fig.10 This section mainly describes the uplink positioning scenario. Fig.11 The following mainly describes the downlink positioning scenario. Fig.12 The following mainly describes the side positioning scenario.

[0289] Fig.10 1 is a flow chart of the communication method 1000 provided in the embodiment of the present application. Fig.10 As shown, taking LMF as the location management function network element, the first device as gNB, and the second device as UE as an example, the model selection / inference in this implementation method occurs on the LMF side. The model uses the gNB to measure the SRS sent by the UE to obtain the corresponding channel measurement result as the input of the AI ​​positioning model, and the UE position is used as the output. It should be understood that the above Fig. 9 The relevant description in the embodiment shown is also applicable to this implementation. Fig. 9 and Fig.10 There may be the same or similar technical means between them. Fig.10 and Fig. 9 The contents already described in the illustrated embodiment will not be repeated.

[0290] S1010, LMF sends an AI positioning measurement request #1 (i.e., an example of the above-mentioned measurement request message) to gNB. Correspondingly, gNB receives the AI ​​positioning measurement request #1 from LMF. The AI ​​positioning measurement request #1 carries indication information, which is used to indicate the AI ​​positioning function or AI positioning model.

[0291] Exemplarily, LMF sends AI positioning measurement request #1 to gNB through NRPPa signaling, requesting gNB to report the measurement results of SRS.

[0292] Optionally, the indication information may not be carried in the AI ​​positioning measurement request #1, that is, the AI ​​positioning measurement request #1 and the indication information may be carried in different messages, and the two may be sent simultaneously or separately.

[0293] S1020. The gNB configures the UE to send SRS based on the AI ​​positioning measurement request #1.

[0294] S1030, the UE sends SRS to the gNB, and correspondingly, the gNB receives the SRS from the UE.

[0295] S1040, gNB measures the SRS and obtains measurement result #1 (i.e., an example of a channel measurement result).

[0296] S1050, gNB sends measurement result #1 to LMF according to the indication information.

[0297] The specific implementation method of gNB sending measurement result #1 to LMF according to the indication information can refer to the relevant description of the above method 900. The AI ​​positioning function or AI positioning model indicated by the indication information corresponds to the measurement amount corresponding to the channel measurement result; at the same time, the AI ​​positioning function or AI positioning model indicated by the indication information also corresponds to the reporting method. The specific content and interpretation of the measurement amount and reporting method can refer to the relevant description of the above method 900. For example, if the indication information indicates the AI ​​positioning function #5 shown in Table 1 above, Figure 2It can be known that the reporting method corresponding to AI positioning function #5 is differential reporting, then the gNB configures the UE to send SRS, measures the SRS from the UE to obtain the corresponding measurement result #1, and reports it to the LMF. Among them, assuming that the second path set includes path #1, path #2 and path #3, the measurement result #1 includes: the delay delay #1 corresponding to path #1 is 4ms, the difference △1 between path #2 and the delay between path #1 and path #3 is -1ms, and the difference △2 between path #3 and path #2 is 1ms. Then, after receiving the measurement result #1, the location management function network element can determine that the delay delay #2 corresponding to path #2 is 3ms according to delay #1 and △1, and the delay delay #3 corresponding to path #3 is 4ms according to delay #2 and △2. Optionally, the first device can also use the delay corresponding to path #2 as a reference, and the delays corresponding to path #1 and path #3 are reported in a differential manner, as long as the location management function network element and the first device are pre-defined.

[0298] Optionally, the method may further include step S1060 (not shown in the figure).

[0299] S1060, LMF selects an AI positioning model based on measurement result #1 and performs AI positioning. For example, measurement result #1 is used as the input of the AI ​​positioning model to output the UE position. The AI ​​positioning model can be deployed on the LMF side, or the UE / base station can use the AI ​​positioning model to extract channel response features. The LMF uses the extracted features as the input of the AI ​​positioning model to obtain the UE position.

[0300] Exemplarily, the UE sends an uplink SRS to the base station, and the gNB obtains the channel response. For example, the AI ​​positioning model is deployed on the LMF side, the gNB sends the channel response to the LMF, and the LMF uses the channel responses of multiple gNBs as input to the AI ​​positioning model and outputs the UE's location information. Assuming that the number of gNB antennas is 16 and the number of subcarriers is 4096, each gNB needs to send 16*4096 complex information to the LMF. For another example, the AI ​​positioning model is deployed on both the gNB and LMF sides. Each gNB takes the channel response as input, and the AI ​​positioning model on the gNB side extracts the channel response features and sends them to the LMF. The LMF takes the received channel response features as input and uses the AI ​​positioning model on the LMF side to obtain the UE position. For example, the channel response feature may be a noise signal corresponding to a weak signal power, or may be a signal multipath response corresponding to a strong signal power, including one or more of the number of paths, the amplitude, phase, or angle information of each path, etc. The dimension of the channel response feature is determined by the output dimension of the AI ​​positioning model on the gNB side. For example, the gNB can extract a channel response feature of dimension

[128] from a channel response of dimension [16,4096] and send it to the LMF.

[0301] It should be noted that in the embodiments of the present application, the transmission of information and / or data between devices is not limited to direct transmission, or indirect transmission (including transparent transmission), etc. Therefore, device A sends information to device B, which includes device A directly sending the information to device B through the interface between device A and device B, and may also include device A sending the message to device C, and device C sending the message to device B, and there is no limit on how many relays are forwarded from device A to device B. For example, UE sends measurement result #1 to LMF, which may include: UE directly sends measurement result #1 to LMF through LPP message; or UE sends measurement result #1 to LMF through gNB; or UE sends measurement result #1 to LMF through gNB and AMF, and UE sends measurement result #1 to LMF through AMF, etc., all of which are not limited. The interactions between other devices are similar, which can be understood by those skilled in the art and will not be repeated. For specific interface messages between devices, please refer to Figure 4 Instructions in .

[0302] In an embodiment of the present application, LMF selects an adapted AI positioning model based on measurement result #1. It is understandable that if an AI positioning model is based on the delay, amplitude and phase of multiple paths contained in the measurement result #1 as input, then the AI ​​positioning model can be selected for positioning reasoning. For example, if the payload of the channel measurement report contains information about 32 paths, and the AI ​​positioning model A in the model library of LMF uses information about 256 paths as input, and the AI ​​positioning model B uses information about 32 paths as input, then LMF can select AI positioning model B for positioning reasoning.

[0303] In an embodiment of the present application, the reference signal measurement node gNB parses the measurement result #1 required by the LMF based on the AI ​​positioning function indicated by the LMF and reports it, so that the LMF uses the measurement result #1 as the input of the AI ​​positioning model and obtains the position of the UE as the output of the AI ​​positioning model to achieve AI positioning, while reducing the signaling overhead caused by separately indicating the reporting method and the AI ​​positioning function.

[0304] Fig.11 1 is a flow chart of a communication method 1100 provided in an embodiment of the present application. Fig.11 As shown, taking LMF as the location management function network element, the first device as gNB, and the second device as UE as an example, the model selection / inference in this implementation method occurs on the LMF side. The model uses the UE to measure the PRS sent by the gNB to obtain the corresponding channel measurement result as the input of the AI ​​positioning model, and the UE position as the output. It should be understood that the above Fig. 9 The relevant description in the embodiment shown is also applicable to this implementation. Fig. 9 and Fig.11 There may be the same or similar technical means between them. Fig.11 and Fig. 9 The contents already described in the illustrated embodiment will not be repeated.

[0305] S1110, LMF sends an AI positioning measurement request #2 (i.e., an example of the above-mentioned measurement request message) to the UE. Correspondingly, the UE receives the AI ​​positioning measurement request #2 from the LMF. The AI ​​positioning measurement request #2 carries indication information, which is used to indicate the AI ​​positioning function or the AI ​​positioning model.

[0306] Exemplarily, the LMF sends an AI positioning measurement request #2 to the UE via LPP signaling, requesting the UE to report the measurement results of the PRS.

[0307] Optionally, the indication information may not be carried in the AI ​​positioning measurement request #2, that is, the AI ​​positioning measurement request #2 and the indication information may be carried in different messages, and the two may be sent simultaneously or separately.

[0308] S1120, LMF configures gNB to send PRS.

[0309] S1130, gNB sends PRS to UE based on the configuration of LMF, and correspondingly, UE receives PRS from gNB.

[0310] S1140, the UE measures the PRS from the gNB and obtains measurement result #2 (i.e., an example of a channel measurement result).

[0311] S1150, the UE sends measurement result #2 to the LMF according to the indication information.

[0312] Among them, the specific implementation method of the UE sending the measurement result #2 to the LMF according to the indication information can refer to the relevant description of the above method 900, and the AI ​​positioning function or AI positioning model indicated by the indication information corresponds to the measurement amount corresponding to the channel measurement result; at the same time, the AI ​​positioning function or AI positioning model indicated by the indication information also corresponds to the reporting method. Among them, the specific content and interpretation of the measurement amount and the reporting method can refer to the relevant description of the above method 900, and for the sake of brevity, it is not repeated here.

[0313] Optionally, the method may further include step S1160 (not shown in the figure).

[0314] S1160, LMF selects an AI positioning model based on measurement result #2 and performs AI positioning. For example, measurement result #2 is used as the input of the AI ​​positioning model to output the UE position. The AI ​​positioning model can be deployed on the LMF side, or the UE / base station can use the AI ​​positioning model to extract channel response features. The LMF uses the extracted features as the input of the AI ​​positioning model to obtain the UE position.

[0315] Exemplarily, the gNB sends a downlink PRS to the UE, the UE obtains a channel response, and sends the channel response or the features extracted from the channel response by the AI ​​positioning model to the LMF. The features based on the channel response may be the channel response itself or the features extracted from the channel response by the AI ​​positioning model.

[0316] In an embodiment of the present application, the reference signal measurement node gNB parses the measurement result #1 required by the LMF based on the AI ​​positioning function indicated by the LMF and reports it, so that the LMF uses the measurement result #1 as the input of the AI ​​positioning model and obtains the position of the UE as the output of the AI ​​positioning model to achieve AI positioning, which can reduce signaling overhead.

[0317] Fig.12 1 is a flow chart of the communication method 1200 provided in the embodiment of the present application. Fig.12 As shown, taking LMF as the location management function network element, the first device as UE#1, and the second device as UE#2 as an example, the model selection / inference in this implementation method occurs on the LMF side. The model uses UE#1 to measure the SL-PRS sent by UE#2 to obtain the corresponding channel measurement result as the input of the AI ​​positioning model, and the UE position is used as the output. It should be understood that the above Fig. 9 The relevant description in the embodiment shown is also applicable to this implementation. Figures 9 to 12 There may be the same or similar technical means between them. Fig.12 With the above Figures 9 to 11 The contents already described in the illustrated embodiment will not be repeated.

[0318] S1210, LMF sends AI positioning measurement request #3 (i.e., an example of the above-mentioned measurement request message) to UE#1. Correspondingly, UE#1 receives AI positioning measurement request #3 from LMF. AI positioning measurement request #3 carries indication information, which is used to indicate the AI ​​positioning function or AI positioning model.

[0319] Exemplarily, the LMF sends an AI positioning measurement request #3 to the UE via LPP signaling, requesting UE #1 to report the measurement results of the SL-PRS.

[0320] Optionally, the indication information may not be carried in the AI ​​positioning measurement request #3, that is, the AI ​​positioning measurement request #3 and the indication information may be carried in different messages, and the two may be sent simultaneously or separately.

[0321] S1220, LMF configures UE#2 to send PRS.

[0322] S1230, UE#2 sends SL-PRS to UE#1 based on the configuration of LMF, and correspondingly, UE#1 receives SL-PRS from UE#2.

[0323] S1240, UE#1 measures the SL-PRS from UE#2 and obtains measurement result #3 (ie, an example of a channel measurement result).

[0324] S1250, UE#1 sends measurement result #3 to LMF according to the indication information.

[0325] The specific implementation method of UE#1 sending measurement result #3 to LMF according to the indication information can refer to the relevant description of the above method 900, and the AI ​​positioning function or AI positioning model indicated by the indication information corresponds to the measurement amount corresponding to the channel measurement result; at the same time, the AI ​​positioning function or AI positioning model indicated by the indication information also corresponds to the reporting method. The specific content and interpretation of the measurement amount and reporting method can refer to the relevant description of the above method 900, and will not be repeated here for the sake of brevity.

[0326] Optionally, the method may further include step S1260 (not shown in the figure).

[0327] S1260, LMF selects an AI positioning model based on measurement result #3 and performs AI positioning. For example, measurement result #3 is used as the input of the AI ​​positioning model to output the UE position. The AI ​​positioning model can be deployed on the LMF side, or UE#1 / UE#2 can use the AI ​​positioning model to extract channel response features. LMF uses the extracted features as the input of the AI ​​positioning model to obtain the UE position.

[0328] Exemplarily, UE#2 sends a sidelink SL-PRS to UE#1, UE#1 obtains a channel response, and sends the channel response or features extracted from the channel response by the AI ​​positioning model to the LMF. The features based on the channel response may be the channel response itself or features extracted from the channel response by the AI ​​positioning model.

[0329] In an embodiment of the present application, the reference signal measurement node gNB parses the measurement result #1 required by the LMF based on the AI ​​positioning function indicated by the LMF and reports it, so that the LMF uses the measurement result #1 as the input of the AI ​​positioning model and obtains the position of the UE as the output of the AI ​​positioning model to achieve AI positioning, which can reduce signaling overhead.

[0330] Above, combined Figures 1 to 12 The method provided by the embodiment of the present application is described in detail. Figures 13 to 15 The device provided in the embodiment of the present application is described in detail. It should be understood that the description of the device embodiment corresponds to the description of the method embodiment, so the contents not described in detail can be referred to the method embodiment above, and for the sake of brevity, they are not described here.

[0331] Fig.13 1 is a schematic diagram of a communication device 1300 provided in an embodiment of the present application. The device 1300 includes a transceiver unit 1310, and optionally, also includes a processing unit 1320. The transceiver unit 1310 can be used to implement corresponding communication functions. The transceiver unit 1310 can also be called a communication interface or a communication unit. The processing unit 1320 can be used to perform processing.

[0332] Optionally, the device 1300 may further include a storage unit, which may be used to store instructions and / or data, and the processing unit 1320 may read the instructions and / or data in the storage unit so that the device implements the aforementioned method embodiment.

[0333] Exemplarily, the communication device 1300 may be a first device, or a communication device applied to the first device or used in conjunction with the first device and capable of implementing the method executed by the first device, such as a chip, a chip system or a circuit. Fig.15 Description of the chip system shown.

[0334] Exemplarily, the communication device 1300 may be a location management function network element, or may be a communication device applied to a location management function network element or used in conjunction with a location management function network element and capable of implementing a method executed by a location management function network element, such as a chip, a chip system or a circuit. For details, see Fig.15 For example, the location management function network element may be the LMF in the above method embodiment.

[0335] As a design, the device 1300 is used to perform the above Figures 9 to 12 The steps or processes performed by the first device in the method embodiment are as follows: the transceiver unit 1310 is used to perform the transceiver-related operations on the first device side in the above method embodiment; the processing unit 1320 is used to perform the above Figures 9 to 12Operations related to processing on the first device side in the method embodiment.

[0336] As another design, the device 1300 is used to execute the above Figures 9 to 12 In the method embodiment, the location management function network element performs the steps or processes, the transceiver unit 1310 is used to perform the operations related to the transceiver side of the location management function network element in the above method embodiment, and the processing unit 1320 is used to perform the above Figures 9 to 12 The method embodiment includes operations related to processing on the location management function network element side.

[0337] It should be understood that the specific process of each unit executing the above corresponding steps has been described in detail in the above method embodiment, and for the sake of brevity, it will not be repeated here.

[0338] It should also be understood that the device 1300 here is embodied in the form of a functional unit. The term "unit" here may refer to an application specific integrated circuit (ASIC), an electronic circuit, a processor (such as a shared processor, a dedicated processor or a group processor, etc.) and a memory for executing one or more software or firmware programs, a merged logic circuit and / or other suitable components that support the described functions. In an optional example, those skilled in the art may understand that the device 1300 may be specifically a network element in the above-mentioned embodiment (such as a first device, and also such as a location management function network element), and may be used to execute the various processes and / or steps corresponding to the network element in the above-mentioned method embodiments. To avoid repetition, they will not be described here.

[0339] The apparatus 1300 of each of the above-mentioned schemes has the function of implementing the corresponding steps performed by the network element (such as the first device, and also such as the location management function network element) in the above-mentioned method. The function can be implemented by hardware, or by hardware executing the corresponding software implementation. The hardware or software includes one or more modules corresponding to the above-mentioned functions; for example, the transceiver unit can be replaced by a transceiver (for example, the sending unit in the transceiver unit can be replaced by a transmitter, and the receiving unit in the transceiver unit can be replaced by a receiver), and other units, such as the processing unit, can be replaced by a processor, respectively performing the sending and receiving operations and related processing operations in each method embodiment.

[0340] In addition, the transceiver unit 1310 may also be a transceiver circuit (for example, may include a receiving circuit and a sending circuit), and the processing unit may be a processing circuit.

[0341] It should be pointed out that Fig.13The device in the embodiment may be a network element in the foregoing embodiment, or may be a chip or a chip system, such as a system on chip (SoC). The transceiver unit may be an input / output circuit or a communication interface; the processing unit may be a processor or a microprocessor or an integrated circuit integrated on the chip. This is not limited here.

[0342] Fig.14 FIG. 1 is a schematic diagram of another communication device 1400 provided in an embodiment of the present application. Fig.14 As shown, the device 1400 includes a transceiver 1430, and the transceiver 1430 is used for receiving and / or sending signals. For example, the processor 1410 is used to control the transceiver 1430 to receive and / or send signals.

[0343] Optionally, the device 1400 further includes a processor 1410 and a memory 1420, the processor 1410 is coupled to the memory 1420, the memory 1420 is used to store computer programs or instructions and / or data, and the processor 1410 is used to execute the computer program or instructions stored in the memory 1420, or read the data stored in the memory 1420 to execute the method in each method embodiment above. For example, the processor 1410 is used to control the transceiver 1430 to receive and / or send a signal.

[0344] Optionally, there are one or more processors 1410 .

[0345] Optionally, the memory 1420 is one or more.

[0346] Optionally, the memory 1420 is integrated with the processor 1410 or provided separately.

[0347] As an example, the processor 1410 may have Fig.13 The processing unit 1320 shown in FIG. 1 may have the function of a storage unit, the memory 1420 may have the function of a storage unit, and the transceiver 1430 may have the function of a Fig.13 The functions of the transceiver unit 1310 are shown in FIG.

[0348] Exemplarily, the communication device 1400 may be a first device, or a communication device applied to the first device or used in conjunction with the first device and capable of implementing the method executed by the first device, such as a chip, a chip system or a circuit. Fig.15 Description of the chip system shown.

[0349] Exemplarily, the communication device 1400 may be a location management function network element, or may be a communication device applied to a location management function network element or used in conjunction with a location management function network element and capable of implementing a method executed by a location management function network element, such as a chip, a chip system or a circuit. For details, see Fig.15 For example, the location management function network element may be the LMF in the above method embodiment.

[0350] As a design, the device 1400 is used to perform the above Figures 9 to 12 The steps or processes performed by the first device in the method embodiment are as follows: the transceiver 1430 is used to perform the operations related to the transmission and reception on the first device side in the above method embodiment; the processor 1410 is used to perform the above Figures 9 to 12 Operations related to processing on the first device side in the method embodiment.

[0351] As another design, the device 1400 is used to execute the above Figures 9 to 12 The steps or processes performed by the location management function network element in the method embodiment, the transceiver 1430 is used to perform the operations related to the transmission and reception of the location management function network element side in the above method embodiment, and the processor 1410 is used to perform the above Figures 9 to 12 The method embodiment includes operations related to processing on the location management function network element side.

[0352] Optionally, the processor 1410 is used to execute a computer program or instruction stored in the memory 1420 to implement relevant operations of the network element (such as the first device, such as the location management function network element, etc.) in the above method embodiments.

[0353] It should be understood that the processor mentioned in the embodiments of the present application can be the following devices or part of the circuit used for processing functions in the following devices: central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor, etc.

[0354] It should also be understood that the memory mentioned in the embodiments of the present application may be a volatile memory and / or a non-volatile memory. Among them, the non-volatile memory may be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory may be a random access memory (RAM). For example, RAM can be used as an external cache. By way of example and not limitation, RAM includes the following forms: static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM), and direct rambus RAM (DR RAM).

[0355] It should be noted that when the processor is a general-purpose processor, DSP, ASIC, FPGA or other programmable logic device, discrete gate or transistor logic device, discrete hardware component, the memory (storage module) can be integrated into the processor.

[0356] It should also be noted that the memory described herein is intended to include, but is not limited to, these and any other suitable types of memory.

[0357] In the embodiment of the present application, the above Figures 9 to 12 The method described above can be performed by the first device and the location management function network element, or can be performed by a chip, a chip system or a circuit of the first device and the location management function network element, and the chip, the chip system or the circuit can be installed in the first device and the location management function network element. Fig.15 The chip system in the first device and the location management function network element is described.

[0358] Fig.151 is a schematic diagram of a chip system 1500 provided in an embodiment of the present application. The chip system 1500 (or also referred to as a processing system) includes a logic circuit 1510 and an input / output interface 1520 .

[0359] Among them, the logic circuit 1510 can be a processing circuit in the chip system 1500. The logic circuit 1510 can be coupled to the storage unit and call the instructions in the storage unit so that the chip system 1500 can implement the methods and functions of each embodiment of the present application. The input / output interface 1520 can be an input / output circuit in the chip system 1500, outputting information processed by the chip system 1500, or inputting data or signaling information to be processed into the chip system 1500 for processing.

[0360] For example, if the first device is installed with the chip system 1500, the logic circuit 1510 is coupled to the input / output interface 1520, and the input / output interface 1520 can input the reference signal to the logic circuit 1510 for processing, such as the measurement result obtained by performing channel measurement on the reference signal.

[0361] For another example, if the location management function network element is installed with the chip system 1500, the logic circuit 1510 is coupled to the input / output interface 1520, and the input / output interface 1520 can input the measurement result from the first device to the logic circuit 1510 for processing.

[0362] As a solution, the chip system 1500 is used to implement the operations performed by a device (such as a first device, or a positioning device, such as a location management function network element, etc.) in the above method embodiments.

[0363] For example, the logic circuit 1510 is used to implement the processing-related operations performed by the device (such as the first device, or the positioning device, such as the location management function network element) in the above method embodiments; the input / output interface 1520 is used to implement the sending and / or receiving-related operations performed by the network element (such as the first device, or the positioning device, such as the location management function network element) in the above method embodiments.

[0364] An embodiment of the present application provides a computer-readable storage medium on which are stored computer instructions for implementing the methods executed by a device (such as a first device, or a positioning device, such as a location management function network element) in the above-mentioned method embodiments.

[0365] For example, when the computer program is executed by a computer, the computer can implement the method performed by a device (such as a first device, or a positioning device, such as a location management function network element) in each embodiment of the above method.

[0366] An embodiment of the present application provides a computer program product, comprising instructions, which, when executed by a computer, implement the methods performed by a device (such as a first device, or a positioning device, such as a location management function network element) in the above-mentioned method embodiments.

[0367] The present application embodiment provides a communication system, which includes the first device and / or location management function network element in each of the above embodiments. For example, the system includes Figures 9 to 11 The first device and / or location management function network element in the embodiment shown. For another example, the system includes Figures 9 to 11 The first device and / or location management function network element in the illustrated embodiment.

[0368] The explanation of the relevant contents and beneficial effects of any of the above-mentioned devices can be referred to the corresponding method embodiments provided above, which will not be repeated here.

[0369] To facilitate understanding of the above embodiments provided in this application, the following points are explained:

[0370] In this application, unless otherwise specified or there is a logical conflict, the terms and / or descriptions between different embodiments are consistent and can be referenced to each other, and the technical features in different embodiments can be combined to form new embodiments according to their internal logical relationships.

[0371] In the present application, "at least one" means one or more, and "plurality" means two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone, where A and B can be singular or plural. In the text description of the present application, the character " / " generally indicates that the associated objects before and after are in an "or" relationship. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b and c can mean: a, or b, or c, or a and b, or a and c, or b and c, or a, b and c. Where a, b and c can be single or multiple, respectively.

[0372] In the present application, "first", "second" and various numerical references are used to distinguish for the convenience of description and are not used to limit the scope of the embodiments of the present application. For example, different messages are distinguished, rather than used to describe a specific order or sequence. It should be understood that the objects described in this way can be interchanged where appropriate so as to be able to describe solutions other than the embodiments of the present application.

[0373] In the present application, the terms "comprises" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or apparatus comprising a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to these processes, methods, products or apparatuses.

[0374] In the present application, "used for indication" may include being used for direct indication and being used for indirect indication. When describing that a certain indication information is used to indicate A, it may include that the indication information directly indicates A or indirectly indicates A, but it does not mean that the indication information must carry A. Specifically, directly indicating information A means including the information A; implicitly indicating information A means indicating information A through the correspondence between information A and information B and directly indicating information B. Specifically, the correspondence between information A and information B may be predefined, pre-stored, pre-burned, or pre-configured.

[0375] It can be understood that some optional features in the embodiments of the present application may not depend on other features in some scenarios, and may also be combined with other features in some scenarios, without limitation.

[0376] It can also be understood that in some of the above embodiments, sending information is mentioned multiple times. For example, "network element A sends information A to network element B", which can be understood as the destination end of the information A or the intermediate network element in the transmission path between the destination end and the network element B, which may include directly or indirectly sending information to network element B. "Network element B receives information A from network element A", which can be understood as the source end of the information A or the intermediate network element in the transmission path between the source end and the source end is network element A, which may include directly or indirectly receiving information from network element A. The information may be subjected to necessary processing between the source end and the destination end of the information transmission, such as format changes, etc., but the destination end can understand the valid information from the source end. Similar expressions in this application can be understood similarly and will not be repeated here.

[0377] It can also be understood that in some of the above embodiments, the AI ​​model is mainly used as an AI model for positioning as an example for illustrative description. It can be understood that the above AI model can also be used for other purposes.

[0378] It can also be understood that the solutions in the various embodiments of the present application can be used in reasonable combination, and the explanations or descriptions of the various terms appearing in the embodiments can be mutually referenced or explained in the various embodiments, without limitation.

[0379] It can also be understood that in the above-mentioned various method embodiments, the methods and operations implemented by the first device or the positioning device can also be implemented by components (such as chips or circuits) that can be implemented by the first device or the positioning device, without limitation.

[0380] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0381] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0382] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0383] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0384] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0385] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0386] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A communication method, characterized in that: The method is performed by a first device or a chip or circuit of the first device, and includes: Receiving indication information from a location management function network element, where the indication information is used to indicate an artificial intelligence AI positioning function or an AI positioning model, where the AI ​​positioning function or the AI ​​positioning model belongs to a plurality of AI positioning functions or AI positioning models, and the plurality of AI positioning functions or AI positioning models correspond to a plurality of different measurement quantity sets, where the measurement quantity set includes one or more measurement quantities; A channel measurement result is sent to the location management function network element according to the indication information, and the measurement quantity corresponding to the channel measurement result corresponds to the AI ​​positioning function or AI positioning model indicated by the indication information.

2. The method according to claim 1, characterized in that The indication information is carried in a measurement request message from the location management function network element.

3. The method according to claim 1 or 2, characterized in that: The AI ​​positioning function or the AI ​​positioning model corresponds to one or more of the following measurement quantities: Line of sight LOS recognition results; Arrival time TOA estimation results; Arrival angle AOA estimation result; The LOS identification result corresponding to each path in the first path set; The delay corresponding to each path in the second path set; The amplitude corresponding to each path in the third path set; The phase corresponding to each path in the fourth path set; At least two of the first path set, the second path set, the third path set and the fourth path set are the same or different.

4. The method according to any one of claims 1 to 3, characterized in that The first device is an access network device, and the channel measurement result is obtained based on a first channel measurement, wherein the first channel measurement includes: measuring a sounding reference signal from a terminal device; or The first device is a terminal device, the channel measurement result is obtained based on a second channel measurement, and the second channel measurement includes: measuring a positioning reference signal or a channel state information reference signal from an access network device; or, The first device is a first terminal device, and the channel measurement result is obtained based on a third channel measurement, and the third channel measurement includes: measuring a side positioning reference signal from a second terminal device.

5. The method according to any one of claims 1 to 4, characterized in that The AI ​​positioning function or the AI ​​positioning model further corresponds to one of the following reporting methods: The measurement results of each diameter in the same measurement are reported independently; The measurement results of each diameter in the same measurement are reported in a differential manner.

6. The method according to claim 5, characterized in that The channel measurement result is included in the measurement report, and the measurement result of each path in the same measurement amount is reported in a differential manner, including: The measurement result of each path in the same measurement quantity in the same measurement report is reported in a differential manner.

7. The method according to any one of claims 1 to 6, characterized in that The AI ​​positioning function includes one or more AI positioning models.

8. A communication method, characterized in that: The method is performed by a location management function network element or a chip or circuit of the location management function network element, and includes: Sending indication information to the first device, where the indication information is used to indicate an artificial intelligence (AI) positioning function or an AI positioning model, where the AI ​​positioning function or the AI ​​positioning model belongs to a plurality of AI positioning functions or AI positioning models, and the plurality of AI positioning functions or AI positioning models correspond to a plurality of different measurement quantity sets, where the measurement quantity set includes one or more measurement quantities; A channel measurement result is received from the first device, where a measurement quantity corresponding to the channel measurement result corresponds to the AI ​​positioning function or the AI ​​positioning model indicated by the indication information.

9. The method according to claim 8, characterized in that The indication information is carried in a measurement request message from the location management function network element.

10. The method according to claim 8 or 9, characterized in that: The AI ​​positioning function or the AI ​​positioning model corresponds to any one of the following measurement quantities: Line of sight LOS recognition results; Arrival time TOA estimation results; Arrival angle AOA estimation result; The LOS identification result corresponding to each path in the first path set; The delay corresponding to each path in the second path set; The amplitude corresponding to each path in the third path set; The phase corresponding to each path in the fourth path set; At least two of the first path set, the second path set, the third path set and the fourth path set are the same or different.

11. The method according to any one of claims 8 to 10, characterized in that The first device is an access network device, and the channel measurement result is obtained based on a first channel measurement, wherein the first channel measurement includes: measuring a sounding reference signal from a terminal device; or The first device is a terminal device, the channel measurement result is obtained based on a second channel measurement, and the second channel measurement includes: measuring a positioning reference signal or a channel state information reference signal from an access network device; or, The first device is a first terminal device, and the channel measurement result is obtained based on a third channel measurement, and the third channel measurement includes: measuring a side positioning reference signal from a second terminal device.

12. The method according to any one of claims 8 to 11, characterized in that The AI ​​positioning function or the AI ​​positioning model further corresponds to one of the following reporting methods: The measurement results of each diameter in the same measurement are reported independently; The measurement results of each diameter in the same measurement are reported in a differential manner.

13. The method according to claim 12, characterized in that The channel measurement result is included in the measurement report, and the measurement result of each path in the same measurement amount is reported in a differential manner, including: The measurement result of each path in the same measurement quantity in the same measurement report is reported in a differential manner.

14. The method according to any one of claims 8 to 13, characterized in that The AI ​​positioning function includes one or more AI positioning models.

15. A communication device, characterized in that: Comprising means for performing the method of any one of claims 1 to 7 or claims 8 to 14.

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