Method for enabling training of artificial intelligence (AI) model for locating wireless device, related node

Abstract

A method performed by a location network node is disclosed enabling training of an artificial intelligence (AI) model for locating a wireless device. The method includes transmitting, with the positioning measurement node, a message indicating a channel response reporting format of a channel between the WD and the wireless network node. The method includes receiving a channel response report for a channel between the WD and the wireless network node from the positioning measurement node using the transmitted channel response format. The method includes receiving, from a WD to be positioned, a tag report indicating a location of the WD, where the tag report is associated with a channel response report.

Description

Technical Field

[0001] This disclosure relates to the field of wireless communications. Specifically, it relates to methods, location network nodes, location measurement nodes, and tag generation nodes that enable training of artificial intelligence (AI) models for locating wireless devices. Background Technology

[0002] Localization in dense multipath environments or NLOS channels, where non-line-of-sight (NLOS) paths are more numerous and dominant than line-of-sight (LOS) paths (such as in indoor factory scenarios), has always been a challenging problem. Because timing measurements from NLOS propagation channels deviate from the true first path time of arrival (TOA) on the ground, conventional localization algorithms sometimes fail to determine the accurate location or position of wireless devices within NLOS channels. As a result, conventional localization algorithms sometimes provide inaccurate localization estimates (e.g., incorrect coordinates), leading to non-negligible localization errors.

[0003] Positioning in NLOS channels needs improvement. Summary of the Invention

[0004] This invention discovers that AI / ML-based localization can be an effective method to improve the accuracy of localization estimation in NLOS-dominated scenarios.

[0005] AI-based localization mitigates localization errors in the NLOS channel by learning the relationship between LOS and NLOS TOA measurements, and can compensate for discrepancies (e.g., pre-compensation).

[0006] Therefore, there is a need for localization network nodes, localization measurement nodes, and methods that can train artificial intelligence (AI) models for locating wireless devices. This can mitigate, alleviate, or resolve existing shortcomings and improve localization accuracy, especially in NLOS scenarios.

[0007] A method executed by a location network node is disclosed, enabling the training of an artificial intelligence (AI) model for locating wireless devices. The method includes transmitting a message in a channel response report format indicative of the channel between the WD and the wireless network node to a location measurement node. The method also includes receiving a channel response report of the channel between the WD and the wireless network node from the location measurement node using the transmitted channel response format. Furthermore, the method includes receiving a tag report indicating the state of the WD from the WD to be located, wherein the tag report is associated with the channel response report and / or one or more location resources.

[0008] Furthermore, a location network node is provided. The location network node includes a memory circuitry, a processor circuitry, and a wireless interface, wherein the location network node is configured to perform any methods relating to a location network node according to this disclosure.

[0009] The advantage of this disclosure is that channel response information received from a first node (such as a positioning measurement node) and tag data from a second node (such as a tag generation node) can be received by the location network node and provided as inputs to train an AI model for locating a wireless device. A channel response report can be provided as input data to the AI ​​model, and a tag report serves as the expected output of the AI ​​model based on the channel response report input. The first and second nodes can be the same or different nodes. By associating the tag report with the channel response report and / or positioning resources, the tag report can be associated with a corresponding measurement report. Thus, pairs of input data and corresponding output data can be generated to train an AI model that will be used to determine and / or estimate the actual state of the WD based on the channel response report between the WD and the wireless network node. Associating the tag report with the channel response report also enables training the model in assisted AI / ML-based positioning, where the channel response report is provided by the wireless network node, which acts as a positioning measurement node unaware of the actual state of the WD. This provides training data that can improve the accuracy of the AI ​​model for locating the wireless device, especially in NLOS scenarios.

[0010] A method performed by a positioning measurement node is disclosed, enabling the training of an AI model for locating wireless devices. The method includes transmitting a message in a channel response report format indicating the channel between the WD and the wireless network node to the location network node. The method further includes transmitting a channel response report of the channel between the WD and the wireless network node to the location network node using the transmitted channel response report format. The channel response report may be associated with a tag report indicating the actual state of the WD.

[0011] Furthermore, a positioning measurement node is disclosed, which includes a memory circuit system, a processor circuit system, and a wireless interface. This positioning measurement node is configured to perform any of the methods disclosed herein related to positioning measurement nodes.

[0012] The advantage of this disclosure is that the positioning measurement node can provide channel response information of the channel between the WD and the wireless network node to the location network node. This enables the location network node to provide channel response reports as input for training an AI model for locating the wireless device. By associating the channel response reports with tag reports, pairs of input data and corresponding output data can be generated to train the AI ​​model, thereby determining the actual state of the WD based on the channel response reports between the WD and the wireless network node. Associating tag reports with channel response reports also enables training the model in assisted AI-based localization, where the channel response reports are provided by the wireless network node. This improves the accuracy of the AI ​​model used for locating the wireless device, especially in NLOS scenarios. Furthermore, the channel response size can be appropriately configured based on the capabilities of the positioning measurement node and the need to minimize signaling overhead. Attached Figure Description

[0013] The above and other features and advantages of this disclosure will become apparent to those skilled in the art from the following detailed description of examples of the disclosure with reference to the accompanying drawings, in which: Figure 1 This is a diagram illustrating an example wireless communication system including example network nodes and example wireless devices according to the present disclosure; Figures 2A to 2B This is a diagram illustrating an example wireless communication system for downlink and uplink positioning according to the present disclosure. Figure 3 This is a diagram illustrating an example technical solution for reducing the channel response report size using a moving search time window according to the present disclosure; Figure 4 This is a signaling diagram illustrating an example of signaling between a location network node, a wireless network node, and a wireless device for downlink data collection according to this disclosure; Figure 5 This is a signaling diagram illustrating an example of signaling between a location network node, a wireless network node, and a wireless device for uplink data collection according to this disclosure; Figure 6 This is a flowchart illustrating an example method performed in a location network node of a wireless communication system, according to the present disclosure, that enables the training of an AI model for locating wireless devices. Figure 7 This is a flowchart illustrating an example method performed in a positioning measurement node of a wireless communication system according to the present disclosure, enabling the training of an AI model for locating wireless devices. Figure 8 This is a flowchart illustrating an example method performed in a tag generation node of a wireless communication system according to the present disclosure, enabling the training of an AI model for locating wireless devices. Figure 9 This is a block diagram illustrating the location of network nodes according to an example of this disclosure; Figure 10 This is a block diagram illustrating the location of measurement nodes according to an example of this disclosure, and Figure 11 This is a block diagram illustrating the generation of nodes based on instance tags according to this disclosure. Detailed Implementation

[0014] Various examples and details are described below with reference to the accompanying drawings (where applicable). It should be noted that the drawings may or may not be drawn to scale, and throughout the drawings, elements with similar structures or functions are indicated by the same reference numerals. It should also be noted that the drawings are intended only to facilitate the description of examples. They are not intended as an exhaustive description of this disclosure or as a limitation on the scope of this disclosure. Furthermore, the illustrated examples need not possess all the aspects or advantages shown. Aspects or advantages described in connection with a particular example are not necessarily limited to that example and can be practiced in any other example, even if not so illustrated or if not so explicitly described.

[0015] The accompanying drawings are schematic and simplified for clarity, and they show only details that aid in understanding this disclosure, while other details have been omitted. Throughout this document, the same reference numerals are used for the same or corresponding parts.

[0016] Figure 1 This is a diagram illustrating an example wireless communication system 1 according to the present disclosure, including an example wireless network node 400 and an example wireless device 300.

[0017] As discussed in detail herein, this disclosure relates to a wireless communication system 1 that includes a cellular system (e.g., a 3GPP wireless communication system). The wireless communication system 1 includes one or more wireless devices 300, 300A (such as mobile wireless device 300 and / or positioning reference unit (PRU) 300A), and / or wireless network node 400, and / or location network node 600 (such as location management function (LMF)).

[0018] The wireless network node disclosed herein refers to a radio access network node operating in a radio access network, such as a base station, a transmit and receive point (TRP), an evolved Node B, an eNB, and a next-generation Node B (gNB) in NR. In one or more instances, the RAN node is a functional unit that can be distributed across several physical units. In uplink-based (UL) positioning, the wireless node is responsible for receiving the UL sounding reference signal (UL-SRS) transmitted from the WD and performing positioning measurements. The wireless network node thus acts as a positioning measurement node in the UL.

[0019] A wireless device can refer to a mobile device and / or a user equipment (UE). A wireless device can be considered an end user for mobile communications, such as a telephone, which connects to a wireless network node (e.g., a gNB) and communicates via the wireless network. In downlink-based (DL) positioning, the wireless device is responsible for receiving a positioning reference signal (PRS) transmitted from the wireless network node and performing positioning measurements. The WD thus acts as the positioning measurement node in the DL.

[0020] Wireless device 300 is configured to communicate with wireless network node 400 via wireless link (or wireless access link) 10. Wireless device 300 is also configured to communicate with other wireless devices via side link (SL) communication. In SL positioning, the positioning process between wireless devices is performed via PC5 link.

[0021] The core network (CN) nodes disclosed in this document refer to network nodes operating in the core network, such as in the evolved packet core network (EPC) and / or the 5G core network (5GC). Examples of CN nodes in the EPC include location management functions.

[0022] The positioning reference unit 300A can be considered a positioning measurement unit with a known (e.g., fixed) location. For example, the PRU 300A is a functional node for uplink (UL) - sounding reference signal (SRS) transmission, DL-PRS reception, and measurement, and is capable of providing precise location information through manual configuration, RAT-related, or RAT-independent methods (such as Global Positioning System (GPS)). The PRU 300A is configured to communicate with the wireless network node 400 via the wireless link (or wireless access link) 10A.

[0023] Location network node 600 can be viewed as a functional node in a 5G positioning architecture. In one or more instances, location network node 600 is a location management function (LMF). For example, location network node 600 receives measurement and assistance information from wireless network nodes and wireless devices to calculate the location of the wireless devices. In another instance, location network node 600 provides configuration to wireless network nodes and wireless devices. In some instances, an AI / ML model is trained in location network node 600, and subsequently, location network node 600 collects information data and constructs a training dataset for training the AI / ML model. In this disclosure, AI / ML models, AI models, and ML models are interchangeably used for machine learning models trained using artificial intelligence. In some instances, the ML model is trained in a separate node (such as a dedicated ML compute node) and connected to location network node 600 (such as an LMF) within the core network.

[0024] Figures 2A to 2B This is a diagram illustrating an example wireless communication system for downlink and uplink positioning according to the present disclosure.

[0025] Figure 2A The diagram illustrates DL-based positioning involving instance wireless device 300, instance wireless network node 400, instance PRU 300A, and instance location network node 600.

[0026] exist Figure 2A In this process, wireless network node 400 sends a downlink positioning reference signal (DL-PRS) to wireless device 300. Wireless device 300 receives the DL-PRS signal and performs positioning measurements, such as the DL-Time Difference of Arrival (DL-TDOA) and Reference Signal Timing Difference (RSTD) of the received signal, and the DL-Transmit Angle (AoD). The positioning measurement results (such as timing information) are reported back to location network node 600 via the LTE Positioning Protocol (LPP) for location determination. In other words, in DL, wireless device 300 acts as a positioning measurement node. Timing information can be reported back to the location network node in a channel response report (e.g., a CIR report). The difference between a channel response report such as a CIR report and a conventional positioning report is that timing information is reported for all arrival paths of the channel, rather than only for the first arrival path of the channel in a conventional positioning report.

[0027] Figure 2B The UL positioning of the instance wireless device 300, instance wireless network node 400, instance PRU 300A, and instance location network node 600 is shown.

[0028] exist Figure 2B In this process, wireless device 300 transmits an uplink sounding reference signal (UL-SRS) to wireless network node 400. Wireless network node 400 performs positioning measurements, such as measuring the timing of the received UL-SRS (e.g., relative time of arrival (RTOA)) and the angle of arrival (AoA) of the received UL-SRS, and reports the measurement results to location network node 600. Location network node 600 further calculates the estimated WD location (such as coordinates). In other words, in the UL, wireless network node 400 acts as a positioning measurement node.

[0029] UL-based positioning uses Time Difference of Arrival (TDOA) measurements, which rely on the time differences it takes for a measured signal to travel from a wireless device to multiple wireless network nodes. For DL-based positioning, TDOA measurements rely on the time differences it takes for a measured signal to travel from multiple wireless network nodes to the wireless device. By comparing these time differences, location network nodes can perform multilateral positioning of the wireless device. For example, to measure TDOA, the wireless device first calculates the channel response, such as the channel impulse response (CIR). The channel response includes information related to multipath characteristics caused by obstacles, signal reflection, and attenuation. By analyzing the channel response, the wireless device (WD) can estimate time delays (such as propagation delay, e.g., propagation time) and further calculate the TDOA. Channel response measurements can be normalized to provide power and time (e.g., delay) information, also known as power delay distribution (PDP).

[0030] In some instances, raw channel response measurements (such as unprocessed channel response measurements) can be used with a size It is represented by an N-dimensional matrix, where, Indicates the number of wireless network nodes used for a given location timing. This indicates the number of samples in the channel response, and This represents the wireless characteristic parameters of each channel response sample. We can assume it equals 3 to represent the delay, power, and phase information for each channel response sample. In some instances, such as indoor scenarios, The maximum can be 18, and The determination depends on the implementation method, such as the ability to locate and measure nodes. For example, It can be 256. In traditional positioning, determining the location of a wireless device involves identifying a first path by analyzing the channel response, extracting the corresponding timing information, and then calculating the WD's location estimate based on multiple timing information or other positioning measurements (such as angle information).

[0031] However, in AI-based localization, the AI ​​model directly learns the relationship between the channel response and the coordinates of the wireless device. The disclosed method simplifies the localization process and improves localization accuracy.

[0032] For example, AI-based localization operates in both deep and long directions (DL and UL). AI-based localization includes two subcategories, distinguished for example by the specific purpose of the AI ​​model: direct AI-based localization and assisted AI-based localization.

[0033] In direct AI-based localization, for example, the localization based on the AI ​​model directly outputs the coordinates of the WD (Warranty Root) and the model is trained based on ground truth labels of the coordinates of the WD / PRU (Placement Root) at least.

[0034] For example, in AI-assisted localization, the AI-based model does not directly output the coordinates of the ground truth (WD), but instead provides intermediate estimates (such as localization measurements), including TOA or information related to the LOS or NLOS state of the wireless channel. These intermediate estimates may help location network nodes calculate the coordinates of the WD. For example, in AI-assisted localization, the model output varies according to a specific function, which also leads to various types of tags in data collection. For example, when the model aims at NLOS mitigation, the tag generation entity provides the ground truth LOS probability or LOS indicator. For example, in other scenarios, when the model focuses on TOA estimation, the tag generation entity provides the ground truth range difference from the WD to the wireless network node.

[0035] AI-based positioning involves three steps: data collection, model training, and model deployment. This disclosure can be viewed as addressing the data collection aspect.

[0036] Data collection supports, for example, the development and training of AI models. Data collection is the process of gathering information and observations for training, validating, and testing AI models. For instance, in the context of AI-based positioning, location network nodes are responsible for data collection and gather information from positioning measurement nodes (which can be any of WD / PRU / wireless network nodes) to develop AI models specifically for positioning. The collected data may include raw measurements and / or features extracted from wireless reference signals.

[0037] Data collection can include labeling the collected data. For example, labeling ensures that each piece of information data is associated with its corresponding ground truth location (WD). This link between information data and accurate WD advantageously and effectively supports the training of AI models for achieving more precise positioning calculations.

[0038] In other words, for example, data collection is based on collaboration between location measurement nodes and location network nodes.

[0039] Location measurement nodes can be viewed as information-generating entities (WD / PRU / wireless network nodes). For example, location measurement nodes provide location measurements and generate the information data needed for AI model training. In some instances, location measurement nodes report information data over the air to location network nodes. For example, location network nodes collect information data and perform data analysis, post-processing, and model training.

[0040] It is understood that in NR positioning protocols, AI-based positioning relies on significant data collection regarding the magnitude and quantity of parameters. This requires location measurement nodes to report channel response measurements, such as CIR measurements, to location network nodes in channel response reports. For example, location network nodes store ground truth tag information associated with each channel response report (e.g., CIR measurement report) to perform, train, and update AI models. In some instances, channel response reports (e.g., CIR measurements) and corresponding tags are generated by location measurement nodes (e.g., depending on the signaling direction DL or UL, WD, PRU, or radio network node). This disclosure provides signaling that enables over-the-air reporting of channel response reports and associated tag reports used for training AI models to location network nodes.

[0041] However, reporting raw channel response (CIR) measurements can be considered to incur significant signaling overhead. For example, channel response measurements are performed by the WD in DL positioning and by the wireless network node in UL. A raw CIR measurement, for instance, covers the wireless channel of interest for a duration that depends on the deployment scenario (outdoor or indoor) and the delay spread of the environment. For example, in an indoor scenario, a raw CIR measurement might include 256x3 samples per WD-WLAN node link, recording the channel's delay, power, and phase information over a range span from 0 m to 624 m in FR1 with SCS = 30 kHz. This range is the equivalent distance / range for the delay information. For example, in FR2 with SCS = 120 kHz, the 256 samples in the raw CIR measurement only cover a range of up to 156 m. For example, when the CIR size is converted to information bits and each information element is represented by 8 bits as an instance, the CIR measurement has a size of 6144 bits (0.77 KB), and becomes even larger (3.85 KB) when considering the 5 WD-WLAN node links used for a single location event. The 8 bits here are just an example; other sizes, such as 16 and / or 32 bits, could also be applied with better granularity. Therefore, reporting such large packets for each location event is inefficient.

[0042] This disclosure addresses the signaling overhead problem by reducing report size without compromising positioning accuracy. This disclosure provides a wireless channel characteristic report that is more compact in size and / or can be tailored, for example, based on device capabilities.

[0043] Figure 3An example technique for reducing the size of channel response reports according to this disclosure is illustrated. According to this disclosure, an enhanced channel response report format (such as a CIR measurement report format) with flexible report sizes can be used to reduce signaling overhead. According to the example technique, a moving search window 20 is used to identify channels of interest. Reporting raw channel response measurements (e.g., CIR measurements) can potentially involve heavy signaling overhead. In this document, raw channel response measurements can be considered as the entire measurement performed by the locating measurement node, such as all... A sample of measurements. The raw channel response measurements may include channel information ranging from 0 m to 624 m in 3GPP Frequency Range 1 (FR1). However, not all channel information from 0 m to 624 m may be relevant to the location network node, such as for training AI models. For example, in an instance scenario where the WD is located approximately 500 m from the wireless network node, channel information from 0 m to 400 m does not provide any relevant information about the environment surrounding the WD. Therefore, including this portion of the channel response in the channel response report is unnecessary and incurs unnecessary signaling overhead. In this case, it is more efficient to report a subset of the raw channel response data that captures channel information from a narrower range (e.g., from 450 m to 550 m). This subset of the channel response is sufficient for the location network node to analyze the relevant channel characteristics and determine the location of the WD. To determine the narrower range in the channel response, the location measurement node (such as the WD in the DL or the wireless network node in the UL) may deploy a mobile search window 20, such as a mobile time window, in the time domain. The search window 20 may have The size of each sample, where . Figure 3 This is a schematic diagram illustrating the process of searching for the signal arrival area. The search window 20 moves (e.g., traverses) from the first measured delay sample to the last measured delay sample (e.g., a window timestamp from 1 to 256). During the movement, WD continuously calculates the sum of the measured power levels within the search window. The timestamp of the maximum power sum is provided by identifying the search window 20. WD is able to identify channels of interest. Using this method, WD then reports the search window timestamp. And from timestamps The rising has A subset of the channel response measurements with a sample size.

[0044] Figure 4A signaling diagram illustrating example signaling between wireless devices 300, 300A, wireless network node 400, and location network node 600 for DL-based data collection according to the present invention is shown. This DL-based data collection enables the training of an AI model for location WD. In the DL-based data collection, wireless network node 400 is the transmission point for transmitting location reference signals (such as DL location reference signals (PRS)). WDs 300, 300A measure the reference signals and thus act as location measurement nodes. Figure 4 The instance signaling shown can be used to train AI models in direct AI-based localization.

[0045] In one or more instances, location network node 600 transmits capability request 1001 to a location measurement node (such as WD 300, 300A), requesting WD 300, 300A to provide its ability to collect data to train an AI model for locating WD, such as its ability to provide channel response reports and / or tag reports.

[0046] In one or more instances, the WD 300, 300A provides location network node 600 with information 1002 indicating its ability to collect data for training AI models, such as its ability to provide channel response reports and / or tag reports.

[0047] Location network node 600 can send a request 1003 for a channel response report regarding the channel between wireless network node 400 and WD 300, 300A. This request can be sent to both wireless network node 400 and WD 300, 300A. In one or more instance methods, request 1003 can be forwarded by wireless network node 400 to WD 300, 300A. In another instance, request 1003 is sent directly from location network node 600 to WD 300, 300A (i.e., transparent to wireless network node 400).

[0048] Wireless network node 400 transmits reference signals, such as DL PRS 1004, to WD 300, 300A for periodic, non-periodic, or semi-static positioning.

[0049] Upon receiving a request, the WD 300, 300A measures the reference signal and performs positioning measurement 1005 and / or channel response measurement 1006.

[0050] In one or more instances, location network node 600 may send a request 1007 to WD 300, 300A for tag collection. Tags indicate the state of the WD (such as its actual state), such as the ground coordinates of the WD 300, 300A. Tags may be associated with channel response measurements, such as channel response resources used to measure the channel response. The state of the WD may include information indicating the current state of the WD (such as its condition). Information indicating the state of the WD may include one or more of the following: the WD's actual location (such as its ground coordinates), the WD's orientation, LOS / NLOS information, and actual delays (such as the WD's timing delay).

[0051] The WD 300 and 300A can transmit location and / or channel response reports, including tag reports such as tag information indicating the actual status of the WD, associated with channel response reports and / or channel response resources. By associating tag reports with channel response reports, the channel response reports can be provided as input to train an AI model for location, while the associated tag reports can be provided as the output of the AI ​​model. Thus, an AI model can be trained to determine the location of the wireless device based on its measured channel response.

[0052] Figure 5 A signaling diagram illustrating example signaling between wireless devices 300, 300A, wireless network node 400, and location network node 600 for UL-based data collection according to this disclosure is shown. This UL-based data collection enables the training of an AI model for locating a WD. In the UL-based data collection, WDs 300, 300A are transmission points for transmitting location reference signals (such as UL detection reference signals (SRS)). Wireless network node 400 measures the reference signals transmitted from WDs 300, 300A and thus acts as a location measurement node. Figure 5 The example signaling shown can be used to train AI models in assisted AI-based localization.

[0053] In one or more instances, location network node 600 transmits capability request 2001A to WD 300, 300A, requesting WD 300, 300A to provide its ability to collect data for training AI models used to locate WD, such as collecting tag information and / or providing tag reports.

[0054] In one or more instances, location network node 600 transmits capability request 2001B to wireless network node 400, requesting wireless network node 400 to provide its ability to collect data for training an AI model used to locate WD, such as collecting channel response information and / or providing channel response reports. In one or more instance methods, capability request 2001B may also request the wireless network node to provide its ability to collect tag information and / or provide tag reports, specifically tag information related to location measurements (such as LOS / NLOS information and actual delays (such as timing delays of WD)).

[0055] In one or more instances, WD 300, 300A provides location network node 600 with information 2002A instructing it to collect data for training AI models, such as collecting tag information and / or providing tag reports.

[0056] In one or more instances, wireless network node 400 provides location network node 600 with information 2002B instructing its ability to collect data for training an AI model, such as collecting channel response information and / or providing channel response reports. In one or more instance methods, information 2002B may also instruct the wireless network node to collect tag information and / or provide tag reports, specifically tag information related to location measurements (such as LOS / NLOS information and actual delays (such as timing delays in WD)).

[0057] Location network node 600 can send a request for UL reference signal resource allocation and tag information to wireless network node 400 2003.

[0058] Wireless network node 400 sends a request 2004 to WD 300, 300A for UL reference signal transmission and tag information. Request 2004 may include UL reference signal transmission configuration.

[0059] Upon receiving request 2004, WD 300, 300A transmits a reference signal 2005 for positioning, such as UL SRS. The reference signal may be transmitted in a dedicated resource (e.g., time and / or frequency resource). The dedicated resource may be referred to herein as the positioning resource.

[0060] The WD 300 and 300A also transmit a tag report 2006 containing information indicating the actual status of the WD 300 and 300A, such as their true ground coordinates. The tag report 2006 can be associated with location resources, such as resources used for transmissions to the UL SRS2005. By associating the tag report 2006 with location resources, the tag report can be associated with channel measurement reports provided to the location network node by different nodes, such as wireless network node 400.

[0061] In one or more example methods, wireless network node 400 performs positioning measurement 2007 on reference signal 2005 (such as UL SRS) transmitted by WD in positioning resources.

[0062] Location network node 600 sends a channel response report request 2008 to wireless network node 400.

[0063] Upon receiving a channel response report request 2008, wireless network node 400 performs a channel response measurement 2009 on the reference signal 2005 transmitted by WD 300, 300A.

[0064] Wireless network node 400 sends a channel response report 2010, including channel response measurement information, to location network node 600. The channel response report 2010 may be associated with a tag report 2006 transmitted by WD 300, 300A based on resources (such as location resources) used for transmitting reference signal 2005. In one or more example methods, the channel response report may include information indicating the location resources used for transmitting reference signal 2005. By associating the tag report 2006 with the channel response report 2010, the channel response report 2010 can be provided as input to train an AI model for location, while the associated tag report 2006 can be provided as the output of the AI ​​model. Thus, an AI model can be trained to determine the location of the wireless device based on its measured channel response.

[0065] Figure 6 A flowchart of an example method 100 performed by a location network node according to this disclosure is shown, which enables the training of an AI model for locating wireless devices. The location network node is an LMF such as those disclosed herein, such as... Figure 1 , Figures 2A to 2B , Figure 4 , Figure 5 and Figure 9 Location network node 600.

[0066] In one or more instance methods, the method includes receiving information from a positioning measurement node, such as a WD, instructing the positioning measurement node of its ability to collect data (such as AI training data) in S101. In one or more instance methods, receiving S101 includes receiving information from a tag generation node (such as a WD and / or a wireless network node) instructing the tag generation node of its ability to provide tag information for training an AI model.

[0067] As part of the data collection process, location measurement nodes and / or tag generation nodes provide their ability to collect data (such as input data for AI models) to location network nodes. In one or more example methods, information indicating the ability of a location measurement node to collect data includes information indicating the ability to perform channel response measurements. In one or more example methods, information indicating the ability of a tag generation node to collect data includes information indicating the ability to provide tag information associated with location resources and / or channel response measurements. Information indicating the ability to perform channel response measurements may indicate whether the location measurement node is capable of performing channel response measurements on a reference signal used for location (such as a DL-PRS or UL-SRS signal). In one or more example methods, information indicating the ability of a location measurement node to collect data includes information indicating the ability to report channel response data (such as a report of channel response measurements). In one or more example methods, information indicating the ability of a location measurement node may specify a preferred report index, such as a CIR report format index. The report index may represent the report size (such as the report's dimensions) and one or more measurement types (such as power, time (such as delay), and phase, among others).

[0068] Method 100 includes transmitting a message to the location measurement node, in step S102, indicating a channel response report format for the channel between the WD and the wireless network node. In one or more example methods, the location measurement node may select a channel response report format from a predetermined lookup table comprising a plurality of different channel response report formats, and may indicate the selected channel response report format to the location network node. The predetermined lookup table may be transmitted from the location network node to the location measurement node or may be hard-coded, such as being installed in the location measurement node during manufacturing or setup.

[0069] In one or more example methods, transmission S102 includes receiving from the positioning measurement node a message S102A indicating the channel response report format used by the positioning measurement node. In one or more example methods, the channel response report format used by the positioning node may be indicated by a message including an index corresponding to a specific channel response format indicated in a lookup table. In one or more example methods, the message indicating the channel response report format used by the positioning measurement node may include confirmation of a request from the location network node to use the specific channel response report format. In one or more example methods, such as when the positioning measurement node cannot provide the format requested from the location network node, the message indicating the channel response report format used by the positioning measurement node may include information indicating an alternative channel response report format, such as a less complex and / or simplified and / or smaller-sized channel response report format.

[0070] In one or more example methods, transmission S102 includes transmitting a message S102B to the positioning measurement node indicating the channel response report format (such as the CIR format) to be used by the positioning measurement node. The location network node (such as an LMF) and the positioning measurement node (such as a WD for DL ​​positioning or a wireless network node for UL positioning) can agree on the channel response format to be used. For example, the positioning measurement node can notify the location network node of the report format, such as CIR ReportFormat - NumberOfTRP, via an Information Element (IE). 、 CIR Report Format - Number of CIRSample and / or CIR Report Format - Measurement Type. In one or more instance methods, the location measurement node can report this information individually to the location network node.

[0071] In one or more instance methods, the channel response report format indicates an index associated with the channel response report format. In one or more instance methods, the location network node predefines a lookup table that can specify combinations of parameters to be reported. In such a case, the location measurement node can, for example, report only the combined index via the IE CIR report format index. The instance lookup table is described below. According to one or more instance lookup tables, the lookup table includes entries for an index (CIR report format index), the number of transmission points for which channel responses are to be reported (CIR report format - number of TRPs), the number of channel response samples to be reported (CIR report format - number of CIR samples), and the measurement type to be reported (CIR report format - measurement type). In one or more instances, the maximum number of TRPs to be reported can be 18, and the maximum number of samples to be reported can be 256.

[0072]

[0073] In one or more instance methods, a lookup table is defined in a specification such as the 3GPP specification, including, for example, the parameters to be reported and the range and / or options for each parameter. In one or more instance methods, when a location network node requests a location measurement node, the location network node specifically requests the location measurement node to provide a specific parameter with a specific value X, such as, for example, the number of transmission points or the number of samples to be reported. The location network node may, for example, request a measurement report with the number of transmission points TRP=6 and the number of channel response samples=100, etc.

[0074] In one or more instance methods, the channel response measurement report can report all available channel response measurements, which may be referred to herein as reporting the raw CIR measurements. In other words, locating the measurement node does not reduce the measurement report, and the report retains the data from the entire IE for the channel response report. In one or more instances, the maximum number of TRPs is assumed. And the maximum number of samples The IE used for channel response reporting (such as the CIR reporting IE) has a reserved data size of 18×256×3.

[0075] In one or more instance methods, the channel response report format indicates the number of transmission points to report the channel response. When the location measurement node is a WD (Wideway Device), the transmission point can be a wireless network node in a DL (Deep Node) location. When the location measurement node is a wireless network node, the transmission point can be a WD in a UL (Ultra-Low Node) location. In one or more instance methods, the location measurement node (such as a WD in a DL or a wireless network node in a UL) can be selected from a subset of available transmission points to report the channel response (such as CIR). For example, the location measurement node can report available transmission points. The subset ,in .

[0076] In one or more instance methods, the channel response report format indicates the number of samples to be reported for each transmission point. In one or more instance methods, the location measurement node may report a reduced number of samples. In one or more instance methods, the subset of reported samples may be determined by the size of a time window (such as a movement time window). In one or more instance methods, the location measurement node reports a window timestamp. and having, for example The size of the channel response report is reduced. In one or more instance methods, the positioning measurement node can select the corresponding Choose the percentage to reduce the size. For example, if you want to reduce the number of samples from a retained data size of 256 to a time window of 26, for example... This allows for a 90% reduction in the size of channel response report (such as CIR report) packets. In other words, by reducing the number of samples from the reserved data size of 256... The time window can reduce the packet size of the channel response report. Therefore, the original CIR measurement report can be considered... =0 and Special circumstances.

[0077] In one or more instance methods, the channel response report format indicates the type of channel information to be reported. The channel information type may include one or more of the following: time information associated with the channel response, power information associated with the channel response, and phase information associated with the channel response. In one or more instance methods, the location measurement node may report all or a subset of the channel information, such as time (e.g., delay), power, and / or phase information. In one or more instance methods, the location measurement node may report time, power, and phase. In one or more instance methods, the location measurement node may report time (e.g., delay) and power. In one or more instance methods, the location measurement node may report only time.

[0078] In one or more example methods, the channel response report format indicates the granularity of the channel information. In one or more example methods, the location measurement node can report time information (such as delay information), power information, and / or phase information at different granularity levels. In one or more example methods, the location measurement node can select from three different granularities, such as a first granularity for time information, a second granularity for power information, and / or a third granularity for phase information. These granularities can be indicated accordingly by the IE "CIR Timing Reporting Granularity Factor", the IE "CIR Power Reporting Granularity Factor", and the IE "CIR Phase Reporting Granularity Factor".

[0079] In one or more example methods, the method includes sending a request for a channel response report (S103) to the positioning measurement node regarding the channel between the WD and the wireless network node. In one or more example methods, such as when positioning is performed in a UL, the positioning measurement node is the wireless network node. In one or more example methods, such as when positioning is performed in a DL, the positioning measurement node is the WD.

[0080] In one or more example methods, the method includes sending an S104 request to a tag reporting node (such as a WD) for a tag report indicating the status of the WD. In one or more example methods, such as when positioning is performed in a DL, the positioning measurement node and the tag generating node are the same node, such as the WD. In one or more example methods, such as when positioning is performed in a UL, the positioning measurement node and the tag generating node are different nodes, wherein the positioning measurement node is a wireless network node and the tag generating node is the WD. In one or more example methods, the request for a tag report is provided together with a request for channel response measurement, such as a request for an SRS transmission sent from the wireless network node to the WD.

[0081] Method 100 includes receiving a channel response report (such as a CIR report) of the channel between the S106 WD and the radio network node from the positioning measurement node using a transmitted channel response report format (such as the channel response format transmitted in S102 and / or S102 and / or S102B). In other words, the channel response report can be reported according to the channel response format transmitted in S102 and / or S102 and / or S102B. For DL-based positioning, such as DL-based data collection, the channel response report can be received from the WD via the LTE Positioning Protocol (LPP). For UL-based positioning, such as UL-based data collection, the channel response report can be received from the radio network node via the NR Positioning Protocol A (NRPPa).

[0082] In one or more instance methods, the channel response report includes a subset of channel response measurement samples, such as the number of available samples. The number of A subset can be a subset of the entire set of samples measured by the positioning measurement node. In one or more instance methods, the subset includes one or more of the following: time information associated with the channel response, power information associated with the channel response, and phase information associated with the channel response.

[0083] In one or more instance methods, the channel response report includes a timestamp (such as a timestamp) indicating the timing of a first time parameter and / or power parameter and / or phase parameter in a subset of the channel measurement samples. The timing of the first time parameter can be indicated as absolute timing or relative to a reference timing in units of seconds / milliseconds or the number of time samples.

[0084] In one or more instance methods, the channel response report includes the size of a time window of a subset of the reported channel measurement samples, such as information indicating that size.

[0085] In one or more instance methods, the channel response report includes information indicating one or more resources (such as one or more positioning resources) that transmit reference signals for positioning. In one or more instance methods, resources may be provided explicitly and / or implicitly in the channel response report. This allows location network nodes to associate the channel response report with tag reports based on one or more resources (such as positioning resources).

[0086] In one or more example methods, the channel response report is associated with one or more location measurements. In one or more example methods, such as those used for DL-based data collection, the channel response report is associated with measurements from one or more transmission points, such as transmission points transmitting reference signals from location measurements. In other words, when the location measurement node is a WD (Wideband Controller), the channel response report may be associated with information associated with multiple wireless network nodes transmitting reference signals, for example, this information may be included. In one or more example methods, such as those used for UL-based data collection when the location measurement node is a wireless network node, the channel response report may include channel response measurements dedicated to a single WD-Wireless Network Node link. In this case, the IE CIR report format - TRP number equals 1.

[0087] Method 100 includes receiving a tag report indicating the status of the WD from a tag generation node (such as a WD or a wireless network node) in S108. The tag report may be associated with one or more channel response reports and / or one or more location resources. Location resources may be one or more time and / or frequency resources for transmitting reference signals used for positioning (such as a positioning reference signal (DL-PRS) in a DL or a detection reference signal (UL-SRS) in a UL). The association between the tag report and the channel response report and / or one or more location resources may be implicitly conveyed or conveyed by explicitly sending one or more resource IDs along with the tag report. In one or more example methods, the tag report is received from the tag generation node, such as the WD, via LPP. In one or more example methods, the tag report may be signaled using an “LPP location information delivery procedure” as defined in 3GPP TS 37.355 V17.3.0.

[0088] The status of a WD can include information indicating its current state (such as condition). Information indicating the status of a WD can include one or more of the following: the WD's actual location (such as its true ground coordinates), the WD's orientation, LOS / NLOS information, and actual delays (such as the WD's timing delay).

[0089] The type of label (such as the information included in the label report) can vary based on the capabilities of the AI ​​model. In one or more instance methods, the label report includes information indicating the ground truth (GT) coordinates of the WD (such as the WD for which localization training data is collected). The GT coordinates can be coordinates in the Global Cartesian System (GCS). In one or more instance methods, such as for direct AI / ML-based localization, the label generating node (such as the WD) provides its GT coordinates to the location network node. In one or more instance methods, for each channel response report, only one GT coordinate of the WD is provided in the label report.

[0090] In one or more instance methods, the tag report includes line-of-sight (LOS) or non-line-of-sight (NLOS) channel indications, such as information indicating whether the channel between the WD and the wireless network node is LOS or NLOS. In one or more instance methods, this information can be provided for training an AI model for assisted AI / ML localization, wherein the tag-generating node provides information specific to each link between the WD and the wireless network node.

[0091] In one or more instance methods, the tag report includes information indicating the time (such as delay, e.g., propagation delay) on the channel between the WD and the wireless network node. The time delay can be the time delay of the LOS path on the channel between the WD and the wireless network node. In one or more instance methods, this information can be provided for training an AI model for assisted AI / ML localization.

[0092] In one or more instance methods, the tag report includes information indicating the range of the channel between the WD and the wireless network node (such as the LOS distance). In one or more instance methods, this information can be provided for training an AI model for assisted AI / ML localization. In one or more instance methods, information indicating time delay can indicate the range.

[0093] In one or more instance methods, the tag report includes information indicating timing errors. Timing errors can be timing errors at the positioning measurement node and / or at the transmission point transmitting the reference signal used for positioning. In other words, timing errors can be WD timing errors and / or wireless network node timing errors. In one or more instance methods, this information can be provided from a specific WD (such as a PRU). In one or more instance methods, this information can be provided for training an AI model for assisted AI / ML positioning.

[0094] In one or more instance methods, the tag report includes information indicating the association between the tag report and the channel response report. This information can be used to map the tag report to the channel response report, such as mapping the expected output from an AI model to the input of an AI model. For UL data collection, the tag report and the channel response report can be received from different entities, such as from different nodes. For example, the tag report can be received from a WD (Wide Device Node), and the channel response report can be received from a wireless network node. In this case, the location network node can receive the tag report from a tag generation node (such as the WD), which has information that associates the tag report with a channel response report received from a location measurement node (such as the wireless network node).

[0095] In one or more instance methods, once the WD transmits a reference signal (such as a SRS) for positioning, a tag report is transmitted from the WD and received by the location network node. In this case, the WD implicitly provides the association between the tag report and the channel response report by informing the location network node of the association between the tag report and the SRS transmission (e.g., the resources of the SRS transmission). Thus, the location network node knows the association between the tag report and the corresponding channel response report from the SRS transmission.

[0096] In one or more instance methods, information indicating the association between the tag report and the channel response report may be explicitly provided in the tag report. In one or more instance methods, the tag report may include information indicating the location resources used for channel response measurements, such as the SRS resource ID or PRS resource ID associated with the tag report.

[0097] In one or more instance methods, the tag report includes information indicating the tag generation source, such as information indicating the method and / or technology used to generate the tag information. The tag generation source and / or tag generation node can be considered as the source and / or node generating the tag report. Tag information can be generated from different sources (such as from different nodes). In the context of direct AI / ML positioning, different types of WDs (such as mobile UEs and positioning reference units (PRUs)) can use different methods to obtain their location information, such as information indicating the actual state of the WD. For PRUs with fixed and known locations, the GTPRU coordinates should remain constant over time, and the uncertainty of this location is therefore negligible. However, for conventional mobile UEs whose locations change over time, Radio Access Technology (RAT) related methods (such as 3GPP-based DL Time Difference of Arrival (TDOA), Sidelink (SL) ranging, and / or Carrier Phase Positioning (CPP)) or RAT-independent methods (such as Global Navigation Satellite System (GNSS) Real-Time Kinematics (RTK)) are typically used to determine the GT coordinates. The quality of tag reports (such as the uncertainty in obtaining the actual location of the WD indicated in the tag report, such as the WD's GT coordinates) can be highly dependent on the method chosen to obtain the location information.

[0098] In one or more instance methods, the label generation node can thus provide information in the label report indicating the source of label generation. This allows location network nodes to assign different confidence levels and / or judgments to the label report, such as the information provided in the label report, thereby improving model training performance. In one or more instance methods, the label report may include a dedicated IE, such as an IE called "LabelSourceIndex," where the index value can correspond to a specific label generation source, as shown in the table below:

[0099] In one or more instance methods, the tag report includes information indicating tag quality (such as the quality of the location indicated by the WD). In one or more instance methods, the information indicating tag quality may be explicitly indicated in the tag report, for example, as the uncertainty of the WD coordinates in actual distances (such as in meters).

[0100] In one or more instance methods, the tag report includes information indicating a timestamp, such as a tag timestamp. A timestamp, such as a tag timestamp, could be a timestamp when the WD receives a DL-PRS used to perform channel response measurements, or a timestamp when the WD transmits a UL SRS for location measurement used by one or more radio network nodes to measure the channel response.

[0101] In one or more instance methods, the tag report includes information indicating a time window, such as a tag time window. The time window (such as a tag time window) can indicate the duration of tag validity, such as the maximum time a tag report is valid. If the tag generation node detects a change related to the reported tag information, the tag generation node can then transmit a new tag report before the time window expires.

[0102] In one or more instance methods, such as when performing data collection (such as location measurement) in DL, the location measurement node is WD.

[0103] In one or more instance methods, such as when performing data collection (such as location measurement) in UL, the location measurement node is a wireless network node.

[0104] In one or more instance methods, the method includes providing 110 channel response information and / or label reports for training an AI model for localizing WD. AI model training can be viewed as a supervised learning process that uses, for example, a neural network to learn the relationship between model inputs and desired model outputs. To train the AI ​​model for localization, channel response reports (such as CIR information data) can be provided as input to the AI ​​model, and label reports (such as corresponding labels) can be provided as the desired AI model output.

[0105] Figure 7 A flowchart of an example method 200 performed by a positioning measurement node according to this disclosure is shown, which enables the training of an AI model for locating wireless devices. The positioning measurement node is the positioning measurement node disclosed herein, such as... Figure 10 The positioning measurement node 700, such as when collecting data in DL. Figure 1 , Figures 2A to 2B , Figure 4 , Figure 5 Wireless devices 300, 300A, or when collecting data in UL. Figure 1 , Figures 2A to 2B , Figure 4 and Figure 5 The wireless network node 400. The positioning measurement node may also be referred to as a data collection node in this document, such as a data collection node used to collect input data for an AI model used to locate WD.

[0106] In one or more example methods, the method includes transmitting S201 information to a location network node instructing the positioning measurement node of its ability to collect data (such as AI training data). In one or more example methods, the transmission of S201 is performed in response to receiving a request from the location network node for the ability to perform data collection (such as the ability to provide tag information and / or channel response reports). The information instructing the positioning measurement node of its ability to collect data may instruct the positioning measurement node of its ability to provide channel response reports and / or tag reports.

[0107] Transmission S201 corresponds to in Figure 6 In method 100, the receiving step S101, performed by the location network node, Figure 4 1002 and Figure 5 2002B.

[0108] Method 200 includes transmitting a message in the format of a channel response report between the location network node and the wireless network node, instructing the WD to communicate with the wireless network node in S202.

[0109] In one or more instance methods, the channel response report format indicates (such as including information indicating the following) the number of transmission points to report channel responses.

[0110] In one or more instance methods, the channel response report format indicates (such as including information indicating the following) the number of samples to be reported for each transmission point.

[0111] In one or more instance methods, the channel response report format indicates (such as including information indicating the following) the type of channel information to be reported. In one or more instance methods, the channel information type includes one or more of time information associated with the channel response, power information associated with the channel response, and phase information associated with the channel response.

[0112] In one or more instance methods, the channel response report format indicates (such as including information indicating the following) the granularity of the channel information.

[0113] In one or more instance methods, the channel response report format indicator (such as including information indicating the following) is an index associated with the channel response report format.

[0114] In one or more example methods, transmitting S202 includes transmitting S202A to the location network node a message indicating the channel response report format used by the positioning measurement node. In one or more example methods, the positioning measurement node can select a channel response report format from a predetermined lookup table including multiple different channel response report formats, and can indicate the selected channel response report format to the location network node. The predetermined lookup table can be transmitted from the location network node to the positioning measurement node or can be hard-coded, such as being installed in the positioning measurement node during manufacturing or setup. In one or more example methods, the channel response report format used by the positioning node can be indicated by a message including an index corresponding to the specific channel response format indicated in the lookup table. Transmitting S202A corresponds to... Figure 6 The receiving S102A is performed by the location network node in method 100.

[0115] In one or more instance methods, transmitting S202 includes receiving S202B from the location network node a message indicating multiple channel response report formats that can be used by the positioning measurement node. In other words, the message may include information indicating multiple channel response report formats that can be used by the positioning measurement node. Receiving S202B corresponds to... Figure 6 The transmission S102B performed by the location network node in method 100. In other words, the message received in S202B corresponds to the message transmitted in S102B.

[0116] In one or more example methods, the method includes receiving, S203, a request from a location network node for a channel response report of the channel between the WD and the wireless network node. Receiving S203 corresponds to... Figure 6 The sending S103 is performed by the location network node in method 100.

[0117] In one or more instance methods, the method includes receiving, S204, a request from a location network node for a tag report indicating the status of the WD. Receiving S204 corresponds to... Figure 6 The sending S104 is performed by the location network node in method 100.

[0118] In one or more example methods, the method includes measuring a set of channel response measurement samples (S205). In one or more example methods, the set of channel response measurement samples is measured on a reference signal received from the transmission point, such as DL-PRS when the positioning measurement node is a WD, or UL-SRS when the positioning measurement node is a wireless network node.

[0119] In one or more instance methods, the method includes: determining a subset of a set of channel response measurement samples to be reported to the location network node in step S206. The subset of channel response measurement samples to be reported may be determined based on messages indicating multiple channel response reporting formats that can be used by the location measurement node, such as information indicating a subset of channel response measurement samples. In one or more instance methods, the subset of samples to be reported may be determined by the size of a time window (such as a movement time window). In one or more instance methods, the location measurement node reports a window timestamp. and having, for example, 18× A channel response report of size ×3. In one or more instance methods, the positioning measurement node can select the corresponding... To select the percentage reduction in size. For example, if If the sample size is 26, the packet size of the channel response report (e.g., CIR report) can be reduced by 90%. In other words, by reducing the number of samples from a reserved data size of 256 to a time window of 26, the packet size of the channel response report can be reduced by 256 / Therefore, the original CIR measurement report can be considered as... =0 and =256 is a special case.

[0120] In one or more instance methods, determining S206 includes determining a subset of S206A by detecting the maximum sum of power within a predetermined time window of the samples, such as based on the size of the predetermined time window.

[0121] To reduce signaling overhead, the location measurement node can report a subset of samples corresponding to the range of interest (ROI) of the location network node. The ROI can be a range narrower than the range measured by the location measurement node. To locate this narrower range in the channel response, the location measurement node can deploy a sample of size [size missing] in the time domain. The mobile search window, in which, < ,like Figure 3 As shown. The search window can traverse from the first delayed sample to the last delayed sample, such as a window timestamp from 1 to 256. Simultaneously, the positioning measurement node can continuously calculate the sum of the power levels of the reference signal measured within the time window. By identifying the timestamp that provides the maximum power sum within the time window, the positioning measurement node can identify the channel of interest. Using this method, the positioning measurement node only needs to report the window timestamp. and the number of samples from the window timestamp This is a subset of the channel responses, which reduces the signaling overhead of channel response reporting.

[0122] Method 200 includes transmitting a channel response report (such as a CIR report) of the channel between the S207WD and the wireless network node to the location network node using a transmitted channel response report format (such as the channel response format transmitted in S202 and / or S202 and / or S202B). The channel response report transmitted in S207 corresponds to the channel response report transmitted in S207. Figure 6 Method 100 of S106 Figure 5 The channel response report received by the location network node in 2010, and similar to Figure 4 1007.

[0123] In one or more instance methods, the channel response report includes information indicating a subset of the channel response measurement samples, such as the number of available samples. The number of A subset can be a subset of the entire set of samples measured by the positioning measurement node. In one or more instance methods, the subset includes one or more of the following: time information associated with the channel response, power information associated with the channel response, and phase information associated with the channel response.

[0124] In one or more instance methods, the channel response report includes a timestamp (such as a timestamp) indicating the timing of a first time parameter and / or power parameter and / or phase parameter in a subset of the channel measurement samples. The timing of the first time parameter can be indicated as absolute timing or relative to a reference timing.

[0125] In one or more instance methods, the channel response report includes the size of a time window of a subset of the reported channel measurement samples, such as information indicating that size.

[0126] In one or more example methods, the method includes transmitting a tag report indicating the status of the WD (Wide Device) to a location network node via S208, wherein the tag report is associated with a channel response report of the channel between the WD and the wireless network node. In other words, in one or more example methods, the location measurement node may correspond to the tag generating node. The status of the WD may include information indicating the current state of the WD (such as condition). The information indicating the status of the WD may include one or more of the WD's actual location (such as its true ground coordinates), the WD's orientation, LOS / NLOS information, and actual delays (such as the WD's timing delay). Transmitting S208 corresponds to... Figure 6 In method 100, the receiving step S108, performed by the location network node, Figure 5 In 2006, and similar to Figure 4 1007.

[0127] The type of label (such as the information included in the label report) can vary based on the capabilities of the AI ​​model. In one or more instance methods, the label report includes information indicating the ground truth (GT) coordinates of the WD (such as the WD for which localization training data is collected). The GT coordinates can be coordinates in the Global Cartesian System (GCS). In one or more instance methods, such as for direct AI / ML-based localization, the label generating node (such as the WD) provides its ground truth coordinates to the location network node. In one or more instance methods, for each channel response report, only one GT coordinate of the WD is provided in the label report.

[0128] In one or more instance methods, the tag report includes line-of-sight (LOS) or non-line-of-sight (NLOS) channel indications, such as information indicating whether the channel between the WD and the wireless network node is LOS or NLOS. In one or more instance methods, this information can be provided for training an AI model for assisted AI / ML localization, wherein the tag-generating node provides information specific to each link between the WD and the wireless network node.

[0129] In one or more instance methods, the tag report includes information indicating the time delay on the channel between the WD and the wireless network node. The time delay can be the time delay of the LOS path on the channel between the WD and the wireless network node. In one or more instance methods, this information can be provided for training an AI model for assisted AI / ML localization.

[0130] In one or more instance methods, the tag report includes information indicating the range of the channel between the WD and the wireless network node (such as the LOS distance). In one or more instance methods, this information can be provided for training an AI model for assisted AI / ML localization.

[0131] In one or more instance methods, the tag report includes information indicating timing errors. Timing errors can be timing errors at the positioning measurement node and / or at the transmission point transmitting the reference signal used for positioning. In other words, timing errors can be WD timing errors and / or wireless network node timing errors. In one or more instance methods, this information can be provided for training an AI model for assisted AI / ML positioning.

[0132] In one or more instance methods, the tag report includes information indicating the association between the tag report and the channel response report. In one or more instance methods, the tag report is transmitted from the WD and received by the location network node once the WD transmits a reference signal (such as SRS) for positioning. In this case, the association between the tag report and the channel response report is implicitly provided by the WD to the location network node by informing the location network node of the association between the tag report and the SRS transmission (e.g., the resources of the SRS transmission).

[0133] In one or more instance methods, information indicating the association between the tag report and the channel response report may be explicitly provided in the tag report. In one or more instance methods, the tag report may include information indicating the location resources used for channel response measurements, such as the SRS resource ID or PRS resource ID associated with the tag report.

[0134] In one or more instance methods, the tag report includes information indicating the tag generation source (such as the tag generation node).

[0135] In one or more instance methods, the tag generation node can provide information in the tag report indicating the source from which the tag was generated. In one or more instance methods, the tag report can include a dedicated IE, such as an IE called the "Tag Source Index," where index values ​​can correspond to a specific tag generation source.

[0136] In one or more instance methods, the tag report includes information indicating tag quality (such as the quality of the location indicated by the WD). In one or more instance methods, the information indicating tag quality may be explicitly indicated in the tag report, for example, as the uncertainty of the WD coordinates in actual distances (such as in meters).

[0137] In one or more instance methods, the tag report includes information indicating a timestamp, such as a tag timestamp. A timestamp, such as a tag timestamp, could be a timestamp when the WD receives a DL-PRS used to perform channel response measurements, or a timestamp when the WD transmits a UL SRS for location measurement used by one or more radio network nodes to measure the channel response.

[0138] In one or more instance methods, the label report includes information indicating a time window, such as a label time window. A time window (such as a label time window) can indicate the duration of label validity, such as the maximum time a label report is valid. If the label generating node detects a change related to the reported label information, the label generating node can then send a new label report before the time window expires.

[0139] The information included in a tag report may depend on the type of tag generation pattern that generates the tag report. A tag report may include one or more types of information disclosed herein. In other words, a tag report may be reported (e.g., may include information) based on information indicating the tag generation source (such as a tag generation node).

[0140] In one or more instance methods, such as when collecting data for training an AI model for assisted AI / ML localization, the label-generating node is a wireless network node.

[0141] In one or more instance methods, such as when collecting data for training a direct AI / ML-based localization AI model, the label generation node is a WD.

[0142] Figure 8 A flowchart of an example method 900 performed by a tag-generating node according to this disclosure is shown, which enables the training of an AI model for locating wireless devices. The tag-generating node is the tag-generating node disclosed herein, such as... Figure 11 The tag generation node 800, such as Figure 1 , Figures 2A to 2B , Figure 4 , Figure 5 Wireless devices 300, 300A, or Figure 1 , Figures 2A to 2B , Figure 4 and Figure 5 400 wireless network nodes.

[0143] In one or more example methods, the method includes transmitting S901 information to a location network node instructing the tag-generating node on its ability to collect data (such as AI training data), such as the ability to provide tag information for training an AI model. In one or more example methods, the information instructing the tag-generating node on its ability to collect data includes information instructing the ability to provide tag information associated with location resources and / or channel response measurements. In other words, the tag-generating node can indicate its ability to associate tag information (such as information indicating the actual location of the WD) with channel response reports. Transmitting S201 is similar to... Figure 6 The receiving S101 is performed by the location network node in method 100. In one or more instance methods, the transmission S901 is performed in response to receiving a request from the location network node for the ability to perform data collection (such as the ability to provide tag information).

[0144] In one or more instance methods, the method includes receiving, from a location network node, a request, S903, for a tag report indicating the status of the WD. Receiving S903 corresponds to... Figure 6The sending S104 performed by the location network node in method 100. In one or more instance methods, receiving S903 includes receiving a request for tag reporting from (such as via) a wireless network node, S903A. Receiving S903 corresponds to the sending S104 performed by the location network node in method 100.

[0145] In one or more example methods, the method includes transmitting a tag report indicating the location of the WD (Wide Device) to a location network node via S906. The tag report and a channel response report of the channel between the WD and the wireless network node are associated, and / or associated with location resources, such as resources for transmitting reference signals for measuring the channel response. In other words, in one or more example methods, the location measurement node may correspond to a tag generation node. Transmitting S906 corresponds to... Figure 6 The receiving S108 performed by the location network node in method 100 and Figure 5 The 2006, and similar to the transmission S108 performed by the positioning measurement node in method 200.

[0146] The type of label (such as information included in the label report) can vary based on the capabilities of the AI ​​model. In one or more instance methods, the label report includes information indicating the ground truth coordinates (GT coordinates) of the WD (such as the WD for which localization training data is collected). The GT coordinates can be coordinates in the GCS. In one or more instance methods, such as for direct AI / ML-based localization, the label generating node (such as the WD) provides its ground truth coordinates to the location network node. In one or more instance methods, for each channel response report, only one GT coordinate of the WD is provided in the label report.

[0147] In one or more instance methods, the tag report includes a LOS or NLOS channel indication, such as information indicating whether the channel between the WD and the wireless network node is LOS or NLOS. In one or more instance methods, this information can be provided for training an AI model for assisted AI / ML localization, wherein the tag-generating node provides information specific to each link between the WD and the wireless network node.

[0148] In one or more instance methods, the tag report includes information indicating the time delay on the channel between the WD and the wireless network node. This time delay may be the time delay of the LOS path on the channel between the WD and the wireless network node. In one or more instance methods, this information may be provided for training an AI model for assisted AI / ML localization.

[0149] In one or more instance methods, the tag report includes information indicating the range of the channel between the WD and the wireless network node (such as the LOS distance). In one or more instance methods, this information can be provided for training an AI model for assisted AI / ML localization.

[0150] In one or more instance methods, the tag report includes information indicating timing errors. Timing errors can be timing errors at the positioning measurement node and / or at the transmission point transmitting the reference signal used for positioning. In other words, timing errors can be WD timing errors and / or wireless network node timing errors. In one or more instance methods, this information can be provided for training an AI model for assisted AI / ML positioning.

[0151] In one or more instance methods, the tag report includes information indicating the association between the tag report and the channel response report. In one or more instance methods, the tag report is transmitted from the WD and received by the location network node once the WD transmits a reference signal (such as SRS) for positioning. In this case, the association between the tag report and the channel response report is implicitly provided by the WD to the location network node by informing the location network node of the association between the tag report and the SRS transmission (such as the resources of the SRS transmission).

[0152] In one or more instance methods, information indicating the association between the tag report and the channel response report may be explicitly provided in the tag report. In one or more instance methods, the tag report may include information indicating the location resources used for channel response measurements, such as the SRS resource ID or PRS resource ID associated with the tag report.

[0153] In one or more instance methods, the tag report includes information indicating the tag generation source (such as a tag generation node). In one or more instance methods, the tag generation node may provide information in the tag report indicating the source of tag generation. In one or more instance methods, the tag report may include a dedicated IE, such as an IE called a "tag source index," where index values ​​may correspond to a specific tag generation source.

[0154] In one or more instance methods, the label report includes information indicating label quality (such as the quality of the indicated location by the WD). In one or more instance methods, the information indicating label quality may be explicitly indicated in the label report, for example, as the uncertainty of the WD coordinates in actual distances (such as in meters). In one or more instances, quality refers to the quality of estimated measurement results (such as timing error estimates, time delay estimates, range estimates, etc.) associated with the label report.

[0155] In one or more instance methods, the tag report includes information indicating a timestamp, such as a tag timestamp. A timestamp, such as a tag timestamp, could be a timestamp when the WD receives a DL-PRS used to perform channel response measurements, or a timestamp when the WD transmits a UL SRS for location measurement used by one or more radio network nodes to measure the channel response.

[0156] In one or more instance methods, the label report includes information indicating a time window, such as a label time window. A time window (such as a label time window) can indicate the duration of label validity, such as the maximum time a label report is valid. If the label generating node detects changes related to the label information present in the report, the label generating node can then send a new label report before the time window expires.

[0157] The information included in the tag report may depend on the type of tag generation pattern that generates the tag report. The tag report may include one or more of the information disclosed herein. In other words, the tag report may be reported based on information indicating the tag generation source (such as the tag generation node), which may include information, for example.

[0158] In one or more instance methods, such as when collecting data for training an AI model for assisted AI / ML localization, the label-generating node is a wireless network node.

[0159] In one or more instance methods, such as when collecting data for training a direct AI / ML-based localization AI model, the label generation node is a WD.

[0160] Figure 9 A block diagram of an example location network node 600 according to the present disclosure is shown. The location network node 600 includes a memory circuitry 601, a processor circuitry 602, and an interface 603, such as a wired and / or wireless interface. The location network node 600 can be configured to perform... Figure 6 Any method disclosed herein. In other words, the location network node 600 can be configured to enable the training of an AI model for locating wireless devices.

[0161] Location network node 600 is configured to communicate with location measurement nodes such as location measurement node 700 and / or tag generation nodes such as tag generation node 800 using a wireless communication system.

[0162] In one or more instances, a location network node can be configured to communicate with a location measurement node and / or a tag generation node.

[0163] Interface 603 is configured to communicate via wireless communication systems such as 3GPP systems, such as 3GPP systems supporting one or more of the following and 3GPP systems operating in licensed or unlicensed frequency bands: Super 5G systems, New Radio (NR), Long Term Evolution (LTE), Narrowband IoT (NB-IoT) and Long Term Evolution-Enhanced Machine Type Communications (LTE-M)).

[0164] Location network node 600 is configured, for example, to transmit a channel response report in the form of an indication of the channel between the WD and the wireless network node to the location measurement node via interface 603.

[0165] Location network node 600 is configured to receive, for example, a channel response report of the channel between the WD and the wireless network node via interface 603 using the transmitted channel response report format.

[0166] Location network node 600 is configured to receive, for example, a tag report indicating the location of the WD from the tag generation node via interface 603, wherein the tag report is associated with a channel response report.

[0167] The processor circuitry 602 is optionally configured to perform operations in Figure 6 Any operation disclosed in the above (such as any one or more of S101, S102, S102A, S102B, S103, S104, S105, S106, S108, S110). The operation of the location network node 600 may be embodied in the form of an executable logic routine (e.g., a line of code, a software program, etc.) stored on a non-transitory computer-readable medium (e.g., memory circuitry 601) and executed by processor circuitry 602.

[0168] Furthermore, the operation of the location network node 600 can be viewed as a method configured to be performed by the location network node 600. Moreover, while the described functions and operations can be implemented in software, such functions can also be performed via dedicated hardware or firmware, or some combination of hardware, firmware, and / or software.

[0169] The memory circuit system 601 may be one or more of a buffer, flash memory, hard disk drive, removable media, volatile memory, non-volatile memory, random access memory (RAM), or other suitable devices. In a typical arrangement, the memory circuit system 601 may include non-volatile memory for long-term data storage and volatile memory used as system memory for the processor circuit system 602. The memory circuit system 601 may exchange data with the processor circuit system 602 via a data bus. Control lines and an address bus may also exist between the memory circuit system 601 and the processor circuit system 602. Figure 9 (Not shown in the image). The memory circuitry 601 is considered a non-transitory computer-readable medium.

[0170] The memory circuit system 601 can be configured to store information in a portion of the memory, such as information indicating channel response, information indicating channel response report format, information indicating tag report, and / or information indicating the ability of the positioning measurement node to collect AI training data.

[0171] Figure 10 A block diagram of a positioning measurement node 700 according to an example of this disclosure is shown. For DL-based data collection, such as DL-based positioning, the positioning measurement node 700 can be a WD, such as... Figure 1 , Figures 2A to 2B and Figure 4 The WD 300 and 300A. For UL-based data collection, such as UL-based positioning, the positioning measurement node 700 can be a wireless network node, such as... Figure 1 , Figures 2A to 2B and Figure 5 The location measurement node 400. The location measurement node may also be referred to herein as a data collection node, such as a data collection node for collecting input data to an AI model used for WD location. The location measurement node 700 includes a memory circuitry 701, a processor circuitry 702, and an interface 703, such as a wired interface and / or a wireless interface. The location measurement node 700 can be configured to perform… Figure 7 Any method disclosed herein. In other words, the positioning measurement node 700 can be configured to enable the training of an AI model for locating wireless devices.

[0172] The positioning measurement node 700 is configured to communicate with location network nodes (such as the location network node 600 disclosed herein) and / or transmission points that transmit reference signals for positioning using a wireless communication system.

[0173] The location measurement node 700 is configured to transmit (such as via interface 703) a channel response report format indicating the channel between the WD and the wireless network node to the location network node.

[0174] The location measurement node 700 is configured to transmit a channel response report (such as via interface 703) between the WD and the wireless network node to the location network node using the transmitted channel response report format.

[0175] Interface 703 is configured to communicate via wireless communication systems such as 3GPP systems, such as 3GPP systems supporting one or more of the following and 3GPP systems operating in licensed or unlicensed frequency bands: Super 5G systems, New Radio (NR), Long Term Evolution (LTE), Narrowband IoT (NB-IoT) and Long Term Evolution-Enhanced Machine Type Communications (LTE-M)).

[0176] The positioning measurement node 700 is optionally configured to perform Figure 7 Any operation disclosed in the above (such as any one or more of S201, S202, S202A, S202B, S203, S204, S205, S206, S206A, S207, S208). The operation of the positioning measurement node 700 may be embodied in the form of an executable logic routine (e.g., line of code, software program, etc.) stored on a non-transitory computer-readable medium (e.g., memory circuitry 701) and executed by processor circuitry 702.

[0177] Furthermore, the operation of the positioning measurement node 700 can be viewed as a method configured to be performed by the positioning measurement node 700. Moreover, although the described functions and operations can be implemented in software, such functions can also be performed via dedicated hardware or firmware, or some combination of hardware, firmware, and / or software.

[0178] The memory circuit system 701 may be one or more of a buffer, flash memory, hard disk drive, removable media, volatile memory, non-volatile memory, random access memory (RAM), or other suitable devices. In a typical arrangement, the memory circuit system 701 may include non-volatile memory for long-term data storage and volatile memory used as system memory for the processor circuit system 702. The memory circuit system 701 may exchange data with the processor circuit system 702 via a data bus. Control lines and an address bus may also exist between the memory circuit system 701 and the processor circuit system 702. Figure 10 (Not shown in the image). The memory circuitry 701 is considered a non-transitory computer-readable medium.

[0179] The memory circuit system 701 can be configured to store information in a portion of the memory, such as information indicating channel response, information indicating channel response report format, information indicating tag report, and / or information indicating the ability of the positioning measurement node to collect AI training data.

[0180] In this disclosure, the ability to locate a measurement node can be regarded as the ability to locate a measurement node, such as the ability to collect AI training data and / or, for example, provide label information for training AI models.

[0181] Examples of methods and products (location network nodes, location measurement nodes, and tag generation nodes) based on this disclosure are illustrated in the following projects: Project 1. A method executed by a location network node that enables training an artificial intelligence (AI) model for locating wireless devices, the method comprising: - Receive (S108) a tag report indicating the location of the WD from the tag generation node, wherein the tag report is associated with a channel response report and / or one or more location resources.

[0182] Project 2. Based on the method of Project 1, wherein the method includes: - The positioning measurement node transmits (S102) a message in the format of a channel response report indicating the channel between the WD and the wireless network node, and - Receive (S106) a channel response report from the positioning measurement node for the channel between the WD and the wireless network node using the transmitted channel response report format.

[0183] Item 3. According to the method of Item 2, wherein the transmission (S102) includes: - Receive (S102A) a message from the positioning measurement node indicating the channel response report format used by the positioning measurement node.

[0184] Item 4. According to the method of Item 2 or 3, wherein the transmission (S102) includes: - Transmit (S102B) a message to the positioning measurement node indicating the channel response report format to be used by the positioning measurement node.

[0185] Item 5. According to the method of any one of Items 2 to 4, wherein the channel response report format indicates one or more of the following: - The number of wireless network nodes to report channel responses, the number of samples to report for each transmission point, the type of channel information to report, the granularity of the channel information, and the index associated with the channel response report format.

[0186] Project 6. According to the method in Project 5, the channel information type includes one or more of the following: - Time information associated with the channel response, power information associated with the channel response, and phase information associated with the channel response.

[0187] Item 7. According to the method of any one of Items 2 to 6, wherein the channel response report includes one or more of the following: - A subset of channel response measurement samples, wherein the subset is a subset of the entire set of samples measured by the positioning measurement node, and the subset includes one or more of the following: information associated with the channel response, power information associated with the channel response, and phase information associated with the channel response. - A timestamp indicating the timing of the first time parameter, power parameter, and / or phase parameter in a subset of the channel measurement samples, and - The size of the time window for the subset of reported channel measurement samples.

[0188] Project 8. A method according to any one of the preceding projects, wherein the method includes: - Send a request (S103) to the positioning measurement node for a channel response report of the channel between the WD and the wireless network node, and - Send (S104) a request to the tag generation node for a tag report indicating the status of the WD.

[0189] Project 9. According to the method of any one of Projects 2 to 8, wherein the channel response report is associated with one or more of the positioning measurements.

[0190] Project 10. According to the method of any of the preceding projects, the label report includes one or more of the following: - Information indicating the actual ground coordinates of the WD. - Information indicating whether the channel between the WD and the wireless network node is line-of-sight (LOS) or non-line-of-sight (NLOS). - Information indicating the time delay on the channel between the WD and the wireless network node. - Information indicating the range of the channel between the WD and the wireless network node. - Information indicating timing error.

[0191] Project 11. According to the method of any of the preceding projects, the label report includes one or more of the following: - Information indicating the correlation between tag reports and channel response reports. - Information indicating the source of the tag generation. - Information indicating label quality, - Information indicating the timestamp of the tag, and - Information indicating the label's time window.

[0192] Project 12. Based on the method of Project 11, wherein label quality is associated with uncertainty in obtaining the location of the WD indicated in the label report.

[0193] Project 13. According to the method of Project 11 or 12, wherein the label report is reported based on the information of the node generated by the indicator label.

[0194] Project 14. According to the method of any of the preceding projects, wherein the tag report is associated with one or more channel response reports transmitted by the corresponding positioning measurement node.

[0195] Project 15. A method according to any one of the preceding projects, wherein the method includes: - Receive information from the positioning measurement node (S101) indicating the ability of the positioning measurement node to collect AI training data, and / or receive information from the label generation node (S101) indicating the ability of the label generation node to provide label information for training the AI ​​model.

[0196] Project 16. According to any one of Projects 2 to 15, the positioning measurement node is WD.

[0197] Project 17. According to any one of Projects 2 to 15, wherein the positioning measurement node is a wireless network node.

[0198] Project 18. According to any of the methods in the preceding projects, the tag generation node and the positioning measurement node are the same node.

[0199] Project 19. According to the method of any one of Projects 1 to 17, wherein the tag generation node is a node different from the positioning measurement node.

[0200] Project 20. A method performed by a positioning measurement node that enables training an artificial intelligence (AI) model for locating wireless devices, the method comprising: - A message in the format of a channel response report, indicating the channel between the WD and the wireless network node, is transmitted to the location network node (S202), and... - Transmit the channel response report between the WD and the wireless network node to the location network node using the transmitted channel response report format (S207).

[0201] Item 21. According to the method of Item 20, the channel response report includes one or more of the following: - A subset of channel response measurement samples, wherein the subset is a subset of the entire set of samples measured by the positioning measurement node, and the subset includes one or more of the following: information associated with the channel response, power information associated with the channel response, and phase information associated with the channel response. - A timestamp indicating the timing of the first time parameter, power parameter, and / or phase parameter in a subset of the channel measurement samples, and - The size of the time window for the subset of reported channel measurement samples.

[0202] Item 22. According to the method of Item 20 or 21, wherein the method includes: - A set of channel response measurement samples for measurement (S205), and - Determine (S206) a subset of the set of channel response measurement samples to be reported to the location network nodes.

[0203] Project 23. According to the method of Project 22, wherein determining (S206) includes determining (S206A) a subset by detecting the sum of the maximum power within a predetermined time window of the samples.

[0204] Item 24. The method according to any one of items 16 to 19, wherein the transmission (S202) includes: - Transmit (S202A) a message to the location network node indicating the channel response report format used by the positioning measurement node.

[0205] Item 25. The method according to any one of items 20 to 24, wherein the transmission (S202) includes: - Receive a message from the location network node (S202B) indicating the multiple channel response report formats that can be used by the positioning measurement node.

[0206] Item 26. According to the method of any one of Items 20 to 25, wherein the channel response report format indicates one or more of the following: - The number of transmission points to report channel responses, the number of samples to report for each transmission point, the type of channel information to report, the granularity of the channel information, and the index associated with the channel response report format.

[0207] Item 27. According to the method of Item 26, the channel information type includes one or more of the following: - Time information associated with the channel response, power information associated with the channel response, and phase information associated with the channel response.

[0208] Item 28. A method according to any one of Items 20 to 27, wherein the method includes: - Receive (S203) a request from the location network node for a channel response report between the WD and the wireless network node.

[0209] Item 29. The method according to any one of Items 20 to 28, wherein the method includes: - Transmit (S208) a tag report indicating the location of the WD to the location network node, wherein the tag report is associated with a channel response report of the channel between the WD and the wireless network node.

[0210] Project 30. According to the method of Project 29, the method includes: - Receive (S204) a request for a tag report indicating the status of the WD from the location network node.

[0211] Item 31. According to the method of any of Items 29 or 30, the label report includes one or more of the following: - Information indicating the actual ground coordinates of the WD to be located. - Information indicating whether the channel between the WD and the wireless network node is line-of-sight (LOS) or non-line-of-sight (NLOS). - Information indicating the channel delay between the WD and the wireless network node. - Information indicating the range of the channel between the WD and the wireless network node. - Information indicating timing error.

[0212] Item 32. According to the method of any one of Items 30 to 31, wherein the label report includes one or more of the following: - Information indicating the correlation between tag reports and channel response reports. - Information indicating the source of the tag generation. - Information indicating label quality, - Information indicating the timestamp of the tag, and - Information indicating the label's time window.

[0213] Item 33. The method according to any one of Items 20 to 32, wherein the method includes: - Transmit (S201) information to the location network node instructing the location measurement node on its ability to collect AI training data.

[0214] Project 34. According to any one of Projects 20 to 33, wherein the positioning measurement node is a wireless network node.

[0215] Item 35. According to the method of any one of Items 20 to 33, the positioning measurement node is WD.

[0216] Project 36. A method executed by a tag-generating node, enabling the training of an artificial intelligence (AI) model for locating wireless devices, the method comprising: - Transmit (S906) a tag report indicating the location of the WD to the location network node, wherein the tag report is associated with one or more location resources.

[0217] Item 37. According to the method of Item 36, the tag report and the channel response report of the channel between the WD and the wireless network node are associated.

[0218] Item 38. According to the method of Item 36 or 37, wherein the method includes: - Receive (S903) a request from the location network node for a tag report indicating the status of the WD.

[0219] Item 39. The method according to any one of Items 36 to 38, wherein the method includes: - Receive (S903A) a request from the wireless network node to provide a tag report to the location network node.

[0220] Item 40. According to the method of any one of Items 36 to 39, wherein the label report includes one or more of the following: - Information indicating the actual ground coordinates of the WD to be located. - Information indicating whether the channel between the WD and the wireless network node is line-of-sight (LOS) or non-line-of-sight (NLOS). - Information indicating the time delay on the channel between the WD and the wireless network node. - Information indicating the range of the channel between the WD and the wireless network node. - Information indicating timing error.

[0221] Item 41. According to the method of any one of Items 36 to 40, wherein the label report includes one or more of the following: - Indicates information about the association between the tag report and one or more location measurement nodes. - Information indicating the identification of the associated positioning measurement nodes, - Information indicating the source of the tag generation, and - Information indicating label quality - Information indicating the timestamp of the tag, and - Information indicating the label's time window.

[0222] Project 42. According to the method of Project 41, wherein label quality is associated with uncertainty when obtaining the location of WD indicated in the label report.

[0223] Project 43. According to the method of Project 41 or 42, the label report is reported based on the information of the node generated by the indicator label.

[0224] Item 44. The method of any one of Items 36 to 43, wherein the tag report is associated with one or more channel response reports transmitted by the corresponding positioning measurement node.

[0225] Item 45. The method according to any one of Items 36 to 44, wherein the method includes: - Transmit (S901) information to the location network node instructing the positioning measurement node to provide label information for training the AI ​​model.

[0226] Item 46. A location network node including a memory circuit system, a processor circuit system, and a wireless interface, wherein the location network node is configured to perform any of the methods according to any one of items 1 to 19.

[0227] Item 47. A positioning measurement node, comprising a memory circuit system, a processor circuit system, and a wireless interface, wherein the positioning measurement node is configured to perform any method according to any one of items 20 to 35.

[0228] Item 48. A tag generation node including a memory circuit system, a processor circuit system, and a wireless interface, wherein the wireless device is configured to perform any of the methods according to any one of items 36 to 45.

[0229] The use of the terms "first," "second," "third," and "fourth," "primary," "secondary," and "tertiary," etc., does not imply any particular order but is included to identify individual elements. Furthermore, the use of the terms "first," "second," "third," and "fourth," "primary," "secondary," and "tertiary," etc., does not indicate any order or importance but is used to distinguish one element from another. It should be noted that the terms "first," "second," "third," and "fourth," "primary," "secondary," and "tertiary," etc., are used solely for labelling purposes in this document and elsewhere and are not intended to indicate any particular spatial or temporal order. Moreover, the labeling of a first element does not imply the existence of a second element, and vice versa.

[0230] Understandable. Figures 1 to 9This includes circuit systems or operations shown in solid lines and circuit systems, components, features, or operations shown in dashed lines. The circuit systems or operations included in solid lines are those included in the broadest examples. The circuit systems, components, features, or operations included in dashed lines are instances that may be included in, or part of, the circuit systems, components, features, or operations of the solid-line instances, or other circuit systems, components, features, or operations that can be taken in addition to them. It should be understood that these operations do not need to be performed in the order presented. Furthermore, it should be understood that not all operations need to be performed. Instance operations can be performed in any order and in any combination. It should be understood that these operations do not need to be performed in the order presented. Circuit systems, components, features, or operations included in dashed lines can be considered optional.

[0231] Other operations not described in this document may be combined with instance operations. For example, one or more additional operations may be performed before, after, simultaneously with, or between any of the described operations.

[0232] The specific features discussed above as individual implementations can also be combined to implement a single implementation. Conversely, features described as a single implementation can also be implemented separately or in any suitable sub-combination in multiple implementations. Furthermore, while features may be described above as functioning in a specific combination, in some cases, one or more features from the claimed combination can be removed from the combination, and the combination can be claimed as any sub-combination or any variation of the sub-combination.

[0233] It should be noted that the word "including" does not necessarily exclude the presence of other elements or steps besides those listed.

[0234] It should be noted that the word "one" or "a" preceding the component does not preclude the existence of multiple such components.

[0235] It should be noted that the term "indication" can be considered as "associated with," "involved in," "describe," "represent," and / or "define." The terms "indication," "associated with," "involved in," "describe," "represent," and "define" can be used interchangeably. The term "indication" can be considered as indicating a relation. For example, weight data indicating weights may include one or more weight parameters.

[0236] It should be noted that the word "based on" can be considered as "according to" and / or "derived from". The terms "based on" and "according to" can be used interchangeably. For example, parameters determined "based on" a dataset can be considered as parameters determined "according to" a dataset. In other words, parameters can be the output of one or more functions that take a dataset as input.

[0237] Functions can represent the relationship between inputs and outputs, such as mathematical relationships, database relationships, hardware relationships, logical relationships, and / or other suitable relationships.

[0238] It should also be noted that any reference numerals in the drawings do not limit the scope of the claims, instances can be implemented at least in part by hardware and software, and several “apparatus”, “units” or “devices” can be represented by the same hardware item.

[0239] The degree language used herein, such as the terms “approximately,” “about,” “substantially,” and “basically”, as used herein, refers to a value, quantity, or characteristic that is close to the stated value, quantity, or characteristic while still performing the desired function or achieving the desired result. For example, the terms “approximately,” “about,” “substantially,” and “basically” can refer to a quantity that is less than or equal to 10%, less than or equal to 5%, less than or equal to 1%, less than or equal to 0.1%, and less than or equal to 0.01% of the stated quantity. If the stated quantity is 0 (e.g., none, not present), the above ranges can be specific ranges and not within a specific percentage of that value. For example, less than or equal to 10 wt. / vol.%, less than or equal to 5 wt. / vol.%, less than or equal to 1 wt. / vol.%, less than or equal to 0.1 wt. / vol.%, and less than or equal to 0.01 wt. / vol.%.

[0240] The various example methods, devices, nodes, and systems described herein are described within the general context of method steps or processes. In one aspect, these method steps or processes can be implemented by a computer program product contained in a computer-readable medium, including computer-executable instructions such as program code that are executed by a computer in a networked environment. Computer-readable media can include removable and non-removable storage devices, including but not limited to read-only memory (ROM), random access memory (RAM), compact discs (CDs), digital versatile discs (DVDs), etc. Typically, a program circuit system can include routines, programs, objects, components, data structures, etc., that perform a specified task or implement a particular abstract data type. The computer-executable instructions, associated data structures, and program circuit systems represent instances of program code for performing steps of the methods disclosed herein. A particular sequence of such executable instructions or associated data structures represents instances of corresponding actions for implementing the functions described in such steps or processes.

[0241] Although features have been shown and described, it will be understood that they are not intended to limit the claimed disclosure, and it will be apparent to those skilled in the art that various changes and modifications can be made without departing from the scope of the claimed disclosure. Therefore, the specification and drawings are to be regarded as illustrative rather than restrictive. The claimed disclosure is intended to cover all alternatives, modifications, and equivalents.

Claims

1. A method performed by a location network node, enabling the training of an artificial intelligence (AI) model for locating wireless devices, the method comprising: - The positioning measurement node transmits (S102) a message in the format of a channel response report indicating the channel between the WD and the wireless network node. - Receive (S106) from the positioning measurement node a channel response report of the channel between the WD and the wireless network node using the transmitted channel response report format, and - Receive (S108) a tag report indicating the location of the WD from the tag generation node, wherein the tag report is associated with the channel response report.

2. The method according to claim 1, wherein, The transmission (S102) includes: - Receive (S102A) a message from the positioning measurement node indicating the channel response report format used by the positioning measurement node, or - Transmit (S102B) a message to the positioning measurement node indicating the channel response report format to be used by the positioning measurement node.

3. The method according to claim 1 or 2, wherein, The channel response report format indicates one or more of the following: - The number of wireless network nodes to report channel responses, the number of samples to report for each transmission point, the type of channel information to report, the granularity of the channel information, and the index associated with the channel response report format.

4. The method according to claim 3, wherein, The channel information types include one or more of the following: - Time information associated with the channel response, power information associated with the channel response, and phase information associated with the channel response.

5. The method according to any one of the preceding claims, wherein, The channel response report includes one or more of the following: - A subset of channel response measurement samples, wherein the subset is a subset of the entire set of samples measured by the positioning measurement node, the subset including one or more of the following: information associated with the channel response, power information associated with the channel response, and phase information associated with the channel response. - A timestamp indicating the timing of the first time parameter, power parameter, and / or phase parameter in the subset of the channel measurement samples, and - The size of the time window for the subset of reported channel measurement samples.

6. The method according to any one of the preceding claims, wherein, The method includes: - Send a request (S103) to the positioning measurement node for a channel response report of the channel between the WD and the wireless network node, and - Send (S104) a request to the tag generation node for a tag report indicating the status of the WD.

7. The method according to any one of the preceding claims, wherein, The channel response report is associated with one or more of the positioning measurements.

8. The method according to any one of the preceding claims, wherein, The label report includes one or more of the following: - Information indicating the actual ground coordinates of the WD - Information indicating whether the channel between the WD and the wireless network node is line-of-sight (LOS) or non-line-of-sight (NLOS). - Information indicating the time delay on the channel between the WD and the wireless network node. - Information indicating the range of the channel between the WD and the wireless network node. -Information indicating timing error - Information indicating the association between the tag report and the channel response report. -Indicates information about the source of the tag generation. -Information indicating label quality -Information indicating the timestamp of the tag, and - Information indicating the label's time window.

9. The method according to claim 8, wherein, The label quality is associated with the uncertainty in obtaining the location of the WD indicated in the label report.

10. The method according to any one of claims 8 to 9, wherein, The tag report is based on information indicating the tag generation node.

11. The method according to any one of the preceding claims, wherein, The tag report is associated with one or more channel response reports transmitted by the corresponding positioning measurement node.

12. The method according to any one of the preceding claims, wherein, The method includes: - Receive information from the positioning measurement node (S101) indicating the ability of the positioning measurement node to collect AI training data, and / or receive information from the label generation node (S101) indicating the ability of the label generation node to provide label information for training the AI ​​model.

13. The method according to any one of the preceding claims, wherein, The positioning and measurement node is WD.

14. The method according to any one of claims 1 to 12, wherein, The positioning and measurement node is a wireless network node.

15. The method according to any one of the preceding claims, wherein, The tag generation node and the positioning measurement node are the same node.

16. The method according to any one of claims 1 to 14, wherein, The tag generation node is a different node from the positioning measurement node.

17. A method performed by a positioning measurement node, enabling the training of an artificial intelligence (AI) model for locating wireless devices, the method comprising: - A message in the format of a channel response report, indicating the channel between the WD and the wireless network node, is transmitted to the location network node (S202). - Transmit (S207) a channel response report of the channel between the WD and the wireless network node to the location network node using the transmitted channel response report format.

18. The method according to claim 17, wherein, The channel response report includes one or more of the following: - A subset of channel response measurement samples, wherein the subset is a subset of the entire set of samples measured by the positioning measurement node, the subset including one or more of the following: information associated with the channel response, power information associated with the channel response, and phase information associated with the channel response. - A timestamp indicating the timing of the first time parameter, power parameter, and / or phase parameter in the subset of the channel measurement samples, and - The size of the time window for the subset of reported channel measurement samples.

19. The method according to claim 17 or 18, wherein, The method includes: -A set of channel response measurement samples for measurement (S205), and - Determine (S206) a subset of the set of channel response measurement samples to be reported to the location network node.

20. The method according to claim 19, wherein, Determining (S206) includes determining (S206A) the subset by detecting the sum of the maximum power within a predetermined time window of the samples.

21. The method according to any one of claims 17 to 20, wherein, The transmission (S202) includes: - Transmit (S202A) a message to the location network node indicating the channel response report format used by the positioning measurement node.

22. The method according to any one of claims 17 to 21, wherein, The transmission (S202) includes: - Receive (S202B) a message from the location network node indicating multiple channel response report formats that can be used by the positioning measurement node.

23. The method according to any one of claims 17 to 22, wherein, The channel response report format indicates one or more of the following: - The number of transmission points to report channel responses, the number of samples to report for each transmission point, the type of channel information to report, the granularity of the channel information, and the index associated with the channel response report format.

24. The method according to claim 23, wherein, The channel information types include one or more of the following: - Time information associated with the channel response, power information associated with the channel response, and phase information associated with the channel response.

25. A method executed by a tag-generating node, enabling the training of an artificial intelligence (AI) model for locating wireless devices, the method comprising: - Transmit (S906) a tag report indicating the location of the WD to a location network node, wherein the tag report is associated with one or more location resources.

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