Wireless communication methods and communication devices

Abstract

Provided are wireless communication methods and communication devices. A method comprises: a first device measures a first reference signal to obtain a signal measurement result; and the first device sends first information to a second device, the first information comprising measurement information of some sampling points in the signal measurement result, the first information being used for training a first model, and the first model being used for terminal device positioning.

Description

Wireless communication methods and communication devices Technical Field

[0001] This application relates to the field of communication technology, and more specifically, to a wireless communication method and communication device. Background Technology

[0002] To improve the positioning accuracy of terminal devices, neural network models can be used for positioning. Signal measurement results can be used to train the model. If the device training the model is different from the device performing the signal measurements, the device performing the signal measurements needs to send its measurement results to the device training the model.

[0003] However, signal measurement results contain a large amount of data, and sending signal measurement results will cause excessive signaling overhead.

[0004] Summary of the Invention

[0005] This application provides a wireless communication method and a communication device. The various aspects covered by this application are described below.

[0006] In a first aspect, a wireless communication method is provided, comprising: a first device measuring a first reference signal to obtain a signal measurement result; the first device sending first information to a second device, the first information including measurement information of some sampling points in the signal measurement result, the first information being used to train a first model, the first model being used to locate a terminal device.

[0007] In a second aspect, a wireless communication method is provided, comprising: a second device receiving first information sent by a first device, the first information being determined by a signal measurement result obtained by the first device from measuring a first reference signal, the first information including measurement information of some sampling points in the signal measurement result, the first information being used to train a first model, and the first model being used to locate a terminal device.

[0008] Thirdly, a communication device is provided, the communication device being a first device, comprising: a measurement unit for measuring a first reference signal to obtain a signal measurement result; and a transmission unit for sending first information to a second device, the first information including measurement information of some sampling points in the signal measurement result, the first information being used to train a first model, the first model being used to locate a terminal device.

[0009] Fourthly, a communication device is provided, the communication device being a second device, comprising: a receiving unit, configured to receive first information sent by a first device, the first information being determined by a signal measurement result obtained by the first device from measuring a first reference signal, the first information including measurement information of some sampling points in the signal measurement result, the first information being used to train a first model, the first model being used to locate a terminal device.

[0010] Fifthly, a communication device is provided, which is a first device including a processor, a memory, and a communication interface. The memory is used to store one or more computer programs, and the processor is used to call the computer programs in the memory, causing the terminal device to execute some or all of the steps in the method of the first aspect.

[0011] In a sixth aspect, a communication device is provided, the communication device being a second device, comprising a processor, a memory, and a transceiver, wherein the memory is used to store one or more computer programs, and the processor is used to invoke the computer programs in the memory, causing the network device to perform some or all of the steps in the method of the second aspect.

[0012] Seventhly, embodiments of this application provide a communication system including the first device and / or the second device described above. In another possible design, the system may further include other devices that interact with the first device or the second device as provided in the embodiments of this application.

[0013] Eighthly, embodiments of this application provide a computer-readable storage medium storing a computer program that causes a communication device (e.g., a first device or a second device) to perform some or all of the steps in the methods described above.

[0014] Ninthly, embodiments of this application provide a computer program product, wherein the computer program product includes a non-transitory computer-readable storage medium storing a computer program operable to cause a communication device (e.g., a first device or a second device) to perform some or all of the steps of the methods described in the foregoing aspects. In some implementations, the computer program product may be a software installation package.

[0015] In a tenth aspect, embodiments of this application provide a chip including a memory and a processor, the processor being able to call and run a computer program from the memory to implement some or all of the steps described in the methods of the foregoing aspects.

[0016] The first device in this application can send measurement information of some sampling points in the signal measurement results to the second device instead of sending all the measurement information, thereby reducing signaling overhead. Furthermore, since some sampling points are determined based on the power values ​​corresponding to those sampling points, the accuracy of the selected sampling points can be guaranteed, avoiding the selection of sampling points containing only noise signals, which is beneficial for ensuring the accuracy of the model. Attached Figure Description

[0017] Figure 1 shows the wireless communication system 100 used in an embodiment of this application.

[0018] Figure 2 is a system architecture diagram of a positioning system applicable to embodiments of this application.

[0019] Figure 3 is a schematic diagram of neural network algorithms and traditional algorithms.

[0020] Figure 4 is a schematic flowchart of a wireless communication method provided in an embodiment of this application.

[0021] Figure 5 shows the waveforms of parameters related to CIR.

[0022] Figure 6 is an enlarged view of the first 50 points in the waveform shown in Figure 5.

[0023] Figure 7 is a schematic block diagram of a communication device provided in an embodiment of this application.

[0024] Figure 8 is a schematic block diagram of another communication device provided in an embodiment of this application.

[0025] Figure 9 is a schematic diagram of the structure of a device provided in an embodiment of this application. Detailed Implementation

[0026] The technical solutions in this application will now be described with reference to the accompanying drawings.

[0027] Figure 1 illustrates a wireless communication system 100 according to an embodiment of this application. The wireless communication system 100 may include a network device 110 and a terminal device 120. The network device 110 may be a device that communicates with the terminal device 120. The network device 110 may provide communication coverage for a specific geographical area and may communicate with the terminal device 120 located within that coverage area.

[0028] Figure 1 illustrates an exemplary network device and two terminals. Optionally, the wireless communication system 100 may include multiple network devices, and each network device may include other terminal devices within its coverage area. This application embodiment does not limit this.

[0029] Optionally, the wireless communication system 100 may also include other network entities such as a network controller and a mobility management entity, which is not limited in this embodiment.

[0030] It should be understood that the technical solutions of the embodiments of this application can be applied to various communication systems, such as: 5th generation (5G) systems or new radio (NR), long term evolution (LTE) systems, LTE frequency division duplex (FDD) systems, LTE time division duplex (TDD) systems, etc. The technical solutions provided in this application can also be applied to future communication systems, such as 6th generation mobile communication systems, satellite communication systems, and so on.

[0031] The terminal device in this application embodiment can also be referred to as user equipment (UE), access terminal, user unit, user station, mobile station, mobile station (MS), mobile terminal (MT), remote station, remote terminal, mobile device, user terminal, terminal, wireless communication device, user agent, or user device. The terminal device in this application embodiment can be a device that provides voice and / or data connectivity to a user, and can be used to connect people, objects, and machines, such as a handheld device with wireless connectivity, vehicle-mounted device, etc. The terminal devices in the embodiments of this application can be mobile phones, tablets, laptops, PDAs, mobile internet devices (MIDs), wearable devices, virtual reality (VR) devices, augmented reality (AR) devices, wireless terminals in industrial control, self-driving, remote medical surgery, smart grids, transportation safety, smart cities, and smart homes, etc. Optionally, the UE can act as a base station. For example, the UE can act as a scheduling entity, providing sidelink signals between UEs in V2X or D2D, etc. For example, cellular phones and cars communicate with each other using sidelink signals. Cellular phones and smart home devices communicate without relaying communication signals through a base station.

[0032] The network device in this application embodiment can be a device for communicating with a terminal device. This network device can also be called an access network device or a wireless access network device, such as a base station. In this application embodiment, the network device can refer to a radio access network (RAN) node (or device) that connects the terminal device to the wireless network. A base station can broadly encompass, or be replaced by, various names including: NodeB, evolved NodeB (eNB), next-generation NodeB (gNB), relay station, transmitting and receiving point (TRP), transmitting point (TP), master MeNB, auxiliary SeNB, multi-standard radio (MSR) node, home base station, network controller, access node, wireless node, access point (AP), transmission node, transceiver node, baseband unit (BBU), remote radio unit (RRU), active antenna unit (AAU), remote radio head (RRH), central unit (CU), distributed unit (DU), positioning node, etc. A base station can be a macro base station, micro base station, relay node, donor node, or similar entities, or combinations thereof. A base station can also refer to a communication module, modem, or chip installed within the aforementioned equipment or apparatus. A base station can also be a mobile switching center, or a device that performs base station functions in device-to-device (D2D), vehicle-to-everything (V2X), and machine-to-machine (M2M) communications, a network-side device in a 6G network, or a device performing base station functions in future communication systems. Base stations can support networks using the same or different access technologies. The embodiments of this application do not limit the specific technologies or device forms used in the network equipment.

[0033] Base stations can be fixed or mobile. For example, a helicopter or drone can be configured to act as a mobile base station, and one or more cells can move depending on the location of the mobile base station. In other examples, a helicopter or drone can be configured as a device to communicate with another base station.

[0034] In some deployments, the network device in this application embodiment may refer to a CU or a DU, or the network device may include both a CU and a DU. The gNB may also include an AAU.

[0035] Network devices and terminal devices can be deployed on land, including indoors or outdoors, handheld or vehicle-mounted; they can also be deployed on water; and they can also be deployed in the air on airplanes, balloons, and satellites. This application does not limit the scenario in which the network devices and terminal devices are located.

[0036] It should be understood that all or part of the functions of the communication device in this application can also be implemented by software functions running on hardware, or by virtualization functions instantiated on a platform (e.g., a cloud platform).

[0037] Positioning technology in communication systems

[0038] Referring to Figure 2, the communication system 100 may further include a positioning device 130. This positioning device 130 can be used to determine the location information of a terminal device. The positioning device 130 may be located in the core network. This positioning device 130 may sometimes be referred to as a positioning server or a location calculation unit. Taking an NR system as an example, the positioning device 130 may be a location management function (LMF). Taking other communication systems as examples, the positioning device 130 may be a location management unit (LMU), a location management center (LMC), or an evolved serving mobile location center (E-SMLC). It is understood that the positioning device 130 may also be other network elements, nodes, or devices used to determine the location information of terminal devices, such as network elements or nodes in future communication systems used to determine the location information of terminal devices. This application embodiment does not specifically limit the name of the positioning device.

[0039] The positioning in communication system 100 includes uplink positioning and downlink positioning. Some communication systems (such as NR systems) perform downlink positioning based on a positioning reference signal (PRS). The PRS, also known as the downlink positioning reference signal (DL-PRS), is a reference signal used for positioning functions. For example, during downlink positioning, terminal device 120 first measures the PRS transmitted by the serving cell and neighboring cells (or adjacent cells) and estimates the relevant positioning measurement information. Then, terminal device 120 reports the relevant positioning measurement information as the PRS measurement result to positioning device 130. Positioning device 130 calculates the location of terminal device 120 based on the positioning measurement information reported by terminal device 120, thereby obtaining the location information of terminal device 120.

[0040] Some communication systems (such as NR systems) perform uplink positioning based on sounding reference signals (SRS). For example, during uplink positioning, terminal device 120 sends an SRS. Base station 110 (the base station of the serving cell and the base stations of neighboring cells) can obtain measurement results based on the SRS sent by the terminal. The measurement results of the SRS can include relevant information about the positioning measurement. Then, base station 110 can send the relevant information about the positioning measurement to positioning device 130. Positioning device 130 can calculate the location of terminal device 120 based on the relevant information about the positioning measurement reported by base station 110, thereby obtaining the location information of terminal device 120.

[0041] The relevant information for the aforementioned positioning measurement may include one or more of the following: time information, distance information, power information, and angle information. More specifically, the relevant information for the positioning measurement may include one or more of the following: time difference of arrival (TDOA), angle difference of arrival (ADOA), reference signal receive power (RSRP), etc.

[0042] Location services in some communication systems (such as 5G) are designed to support industries and applications with high positioning accuracy requirements. Many industries and applications have high positioning accuracy needs, both in outdoor and indoor environments. For example, in location-based services and e-health, higher accuracy in detection equipment is crucial for new services and applications. For instance, on factory production lines, accurately positioning equipment and moving objects is essential, such as for forklifts or parts to be assembled. Similar needs exist in transportation and logistics, such as knowing the precise location of targets on railways, roads, and in scenarios using drones. In some road use cases, user equipment supporting V2X applications is also suitable for such needs. High positioning requirements are necessary to support availability when locating objects such as guiding vehicles (e.g., industrial equipment, drones) and objects involving safety-related functions.

[0043] The new wireless standards offer a variety of positioning technologies. Release 15 of the 3rd Generation Partnership Project (3GPP) released standards for positioning based on NR systems. In non-standalone (NSA) systems, positioning is mostly achieved using LTE technology. Release 16 of 3GPP significantly enhanced positioning support, providing a range of positioning methods, including downlink-based and uplink-based positioning. Release 17 of 3GPP introduced additional enhancements to reduce latency in latency-sensitive use cases such as remote control, improving positioning accuracy to 20-30 cm. Release 18 of 3GPP investigated further improvements in positioning accuracy, integrity, and power efficiency, explored sidelink positioning, and investigated solutions for positioning support for RedCap devices.

[0044] Traditional downlink and uplink positioning methods, such as those using Time Difference of Arrival (TDOA), Angle of Arrival (AOA), Angle of Departure (AOD), and Multiple Round Trip Time (multi-RTT), may not provide satisfactory performance in the presence of numerous non-line-of-sight (NLoS) errors. Traditional methods require a large amount of data to identify Loss and NLoS, resulting in high computational complexity and poor stability due to the need to identify Loss and NLoS based on location calculations. Furthermore, in industrial environments, traditional "RF fingerprinting" requires a database mapping RF measurement results to location, and constructing an accurate RF fingerprint map of a real-world environment is challenging. Additionally, the database needs to be updated regularly to adapt to constantly changing environments. Therefore, neural networks are being used in industry to improve positioning accuracy. The difference between neural network algorithms and traditional algorithms is shown in Figure 3.

[0045] Figure 3 illustrates the relationship between input data (e.g., wireless measurement data, or sensor data from vision, inertial, etc.) and output target values ​​(e.g., absolute position, relative offset, orientation, etc.). Traditional modeling methods implement domain-specific algorithms through manual design, while methods based on artificial intelligence (AI) or machine learning (ML) construct models and related parameters by learning relevant knowledge from large amounts of data, forming a mapping relationship between input and output.

[0046] The advantages of using AI / ML learning methods for localization are mainly threefold, which will be introduced below.

[0047] First, highly expressive neural networks can be used as general fitters to automatically extract task-relevant features. This characteristic allows AI / ML learning models to better adapt to various environments, especially in situations where manual modeling is difficult, such as regions with few features, complex dynamic environments, motion blur, and situations where precise initial calibration is impossible, thus exhibiting better robustness. Furthermore, AI / ML learning methods can connect abstract elements with human-understandable terms. For example, semantic labels in simultaneous localization and mapping (SLAM) are difficult to describe with a single, definitive mathematical equation.

[0048] Secondly, AI / ML allows space machine intelligent systems to extract experience from the past and more proactively and effectively utilize new sensor information. Traditional methods, designed to solve domain-specific problems, predefine all rules and algorithms before system deployment. However, this often impacts system accuracy when encountering undefined scenarios. AI / ML-based systems, on the other hand, can automatically discover new computational solutions in new scenarios by building general data-driven models and self-improving their models and parameters. A prime example is the ability to recover self-motion and depth from unlabeled video using novel view synthesis as a self-supervised signal. Furthermore, learning facilitates the construction of task-driven maps, further supporting more advanced robotic tasks such as path planning and decision-making.

[0049] Third, it can fully leverage the ever-increasing volume of data and computing power. Artificial intelligence and machine learning can generalize to large-scale data and application scenarios, and can automatically optimize the massive parameters within neural network models. Currently, several large datasets related to positioning have been released, such as the Oxford RobotCar dataset for autonomous vehicles, the Baidu Apollo dataset, and the Waymo dataset, all of which have collected a considerable amount of sensor data, as well as motion and semantic labels. Artificial intelligence learning methods can effectively utilize existing data and computing power to solve positioning challenges.

[0050] When conducting AI / ML localization research, it is necessary to define the methods for measuring signals and the model input format supported by the feedback signals. The input to the artificial intelligence model can include the measurement results of the signals, and the output can include localization-related parameters. For example, time-domain channel impulse response and power delay spectrum can be used as model inputs.

[0051] The positioning method involved in this application may include uplink positioning or downlink positioning. The aforementioned signal measurement results may include uplink signal measurement results or downlink signal measurement results. For example, a network device may send a downlink reference signal to a terminal device, and the terminal device may measure the downlink reference signal to obtain a signal measurement result. As another example, a terminal device may send an uplink reference signal to a network device, and the network device may measure the uplink reference signal to obtain a signal measurement result. The downlink reference signal may include, for example, one or more of the following: PRS, channel state information reference signal (CSI-RS). The uplink reference signal may include, for example, SRS.

[0052] Signal measurement results may include one or more of the following: channel impulse response (CIR), power delay profile (PDP), channel state information (CSI), etc.

[0053] If CIR or PDP is used as input to the model, then the input dimension of the model is N. TRP *N port *N t Among them, N TRP N is the number of TRPs. port N is the number of transmit / receive antenna port pairs. t It represents the number of samples in the continuous time domain.

[0054] Model training can be performed on any device. If the device used to train the model is not the same as the device used to perform signal measurements, the device performing the signal measurements needs to send the signal measurement results to the device used to train the model so that the device can train the model based on the signal measurement results.

[0055] For example, if the device training the model is a positioning device and the device performing signal measurements is a terminal device, then the terminal device needs to send the signal measurement results to the positioning device. Similarly, if the device training the model is a positioning device and the device performing signal measurements is a network device, then the network device needs to send the signal measurement results to the positioning device. Likewise, if the device training the model is a network device and the device performing signal measurements is a terminal device, then the terminal device needs to send the signal measurement results to the network device. And so on.

[0056] As can be seen from the above, the training process of the model involves the transmission of a large number of signal measurement results, leading to significant signaling overhead. For example, as mentioned above, if the model input is a CIR or PDP, and the model input dimension is N... TRP *N port *N t During the transmission of signal measurement results, N needs to be transmitted. t N samples, N t The large amount of data per sample results in significant signaling overhead.

[0057] Based on this, embodiments of this application provide a wireless communication method and communication device that reduce signaling overhead by transmitting only a portion of the sample data. The sample in this application can also be referred to as a sampling point. The sample data in this application can be understood as the measurement information of the sampling point.

[0058] The wireless communication method provided in the embodiments of this application will be described in detail below with reference to Figure 4. The method shown in Figure 4 includes steps S410 to S420, which will be described in detail below.

[0059] In step S410, the first device measures the first reference signal and obtains the signal measurement result.

[0060] The first device can be a terminal device or a network device; this application does not specifically limit this. If the first device is a terminal device, the first reference signal can be sent from the network device to the terminal device, and the first reference signal can be PRS or CSI-RS, etc. If the first device is a network device, the first reference signal can be sent from the terminal device to the network device, and the first reference signal can be SRS. In some embodiments, the first device can also be referred to as a measurement unit.

[0061] This application does not specifically limit the signal measurement results. As an example, the signal measurement results may include one or more of the following: CSI, CIR, PDP, DP. The signal measurement results may also be referred to as channel information. As another example, the signal measurement results may include one or more of the following: RSRP, RSRQ, SINR, etc. The signal measurement results in this application can be time-domain signal measurement results. Taking CIR as an example, the signal measurement results can be time-domain CIR. Taking PDP as an example, the signal measurement results are time-domain PDP.

[0062] The terminal device can measure the signal at a certain sampling period, which can be 1 / (Nf×Δf), where Δf is the subcarrier spacing and Nf is the number of points of the FFT transform.

[0063] In step S420, the first device sends first information to the second device.

[0064] In some embodiments, the second device may be a positioning device, a terminal device, or a network device. For example, if the first device is a terminal device, the second device may be a network device or a positioning device. As another example, if the first device is a network device, the second device may be a terminal device or a positioning device. Taking an NR system as an example, the positioning device may be an LMF (Local Mesh Filter). In other communication systems, the positioning device may be an LMU (Local Measurement Unit), LMC (Local Mesh Filter), or E-SMLC (Electronic-Small Module Filter).

[0065] It is understood that the positioning device can also be other network elements, nodes, or devices used to determine the location information of terminal devices. For example, it can be a network element or node in a future communication system used to determine the location information of terminal devices, or it can be a stand-alone positioning device specifically deployed for location calculation. This application does not specifically limit the name of the positioning device; for example, the positioning device can also be called a positioning server or a positioning calculation server.

[0066] In some embodiments, the first information may include measurement information of a portion of the sampling points. In some embodiments, the first information may include measurement information of a portion of the transformed sampling points obtained after transforming the signal measurement result. In the following description, the sampling points of the measurement result and the sampling points obtained after transforming the measurement result are collectively referred to as sampling points. For example, if the signal measurement result includes a time-domain signal measurement result, the first information may include measurement information of a portion of time points. Taking the signal measurement result as a time-domain CIR (TD CIR) as an example, the first information may include the CIR of a portion of the sampling points. Taking the signal measurement result as a time-domain PDP (TD PDP) as an example, the first information may include the PDP of a portion of the sampling points. In some implementations, after obtaining the CIR of a portion of the sampling points, the first device can obtain the PDP based on the CIR of the portion of the sampling points.

[0067] In some embodiments, a sampling point may also be referred to as a tap, and the measurement information of a portion of the sampling points can be understood as the amplitude values ​​of a portion of the taps. In some embodiments, a sampling point may also be referred to as a sample, such as a time-domain sample.

[0068] To improve the accuracy of signal acquisition, some sampling points can be determined based on the amplitude (e.g., power value) corresponding to each sampling point. The power value corresponding to a sampling point can be understood as the amplitude value corresponding to that sampling point. In some embodiments, some sampling points may include sampling points with power values ​​greater than or equal to a preset threshold. In some embodiments, some sampling points may include the sampling point with the highest power value. In some embodiments, some sampling points may be the top P strongest power sampling points. By selecting high-power sampling points as some sampling points, the accuracy of the selected sampling points can be improved, and the proportion of the signal can be increased.

[0069] In some embodiments, a subset of sampling points may include temporally consecutive sampling points, which simplifies the computational complexity of the first device. For example, a subset of sampling points may include the first M sampling points containing the highest power values. In some embodiments, a subset of sampling points may be scattered sampling points, and the first device may only need to report the first information corresponding to these scattered sampling points, which can further reduce the signaling overhead of the reporting.

[0070] For example, suppose the power values ​​of sampling points 10, 12, 20, and 23 are relatively high, while the power values ​​of other sampling points are relatively low (basically the power of noise). If some sampling points are continuous in time, then some sampling points can be sampling points 10 to 23; if some sampling points are scattered, then some sampling points can be sampling points 10, 12, 20, and 23.

[0071] The first device in this application can send measurement information of some sampling points in the signal measurement results to the second device instead of sending all the measurement information, thereby reducing signaling overhead. Furthermore, since some sampling points are determined based on the power values ​​corresponding to those sampling points, the accuracy of the selected sampling points can be guaranteed, avoiding the selection of sampling points containing only noise signals, which is beneficial for ensuring the accuracy of the model.

[0072] In some embodiments, some sampling points can be determined based on the coordinate values ​​of the sampling points in a first subspace of the first reference signal. After receiving the first reference signal, the first device can map the first reference signal into the first subspace. Here, the first reference signal can be a vector first reference signal. The first subspace can be a signal subspace or a noise subspace; this application embodiment does not specifically limit this.

[0073] The coordinates of a sampling point in the first subspace are related to the amplitude or power value projected onto the first subspace, or to the reciprocal of the amplitude or power value projected onto the first subspace. If the first subspace is a signal subspace, the larger the power value corresponding to the sampling point, the larger the absolute value of the coordinates projected onto the signal subspace; if the first subspace is a noise subspace, the larger the power value corresponding to the sampling point, the smaller the absolute value of the coordinates of the sampling point in the noise subspace.

[0074] In some embodiments, the first device can determine a portion of the sampling points based on the coordinate values ​​of the sampling points in the signal subspace; in some embodiments, the first device can determine a portion of the sampling points based on the coordinate values ​​of the sampling points in the noise subspace; in some embodiments, the first device can determine a portion of the sampling points based on the coordinate values ​​of the sampling points in both the signal subspace and the noise subspace.

[0075] In some embodiments, the first device may also send first indication information to the second device, which indicates the type of the first subspace. That is, the first device may indicate to the second device whether some sampling points are determined based on the signal subspace or the noise subspace. In some implementations, the first information may include the first indication information; for example, the first information and the first indication information may be carried in the same signaling. In other implementations, the first indication information is different from the first information, or in other words, the first indication information and the first information may be carried in different signaling.

[0076] In some embodiments, the first device may indicate the sequence number of a subset of sampling points to the second device. If the subset of sampling points are scattered sampling points, the first device may indicate the sequence number of each sampling point to the second device. If the subset of sampling points are consecutive sampling points, the first device may indicate the sequence number information of the segment in which the subset of sampling points are located to the second device. For example, the first device may indicate a start point and an end point, or a start point and a length, or a length and an end point, etc.

[0077] In some embodiments, the first information may further include one or more of the following: a first power ratio, a first time ratio, the ratio of the first power ratio to the first time ratio, and direction information of the first reference signal.

[0078] The first power ratio can be the ratio of the total power value corresponding to a subset of sampling points to the total power value corresponding to the signal measurement result. The total power value corresponding to a subset of sampling points can be the sum of the power values ​​corresponding to those sampling points. The total power value corresponding to the signal measurement result can be the sum of the power values ​​corresponding to all sampling points. The first power ratio can indicate the accuracy of the selected subset of sampling points, the accuracy of the signal, or the noise content of the signal. The larger the first power ratio, the higher the effective signal content and the lower the noise content of the selected sampling points, i.e., the higher the accuracy of the subset of sampling points; the smaller the first power ratio, the higher the noise content and the lower the effective signal content of the selected sampling points, i.e., the lower the accuracy of the subset of sampling points.

[0079] The first time ratio can be considered as the ratio of the time length corresponding to a subset of sampling points to the time length corresponding to the signal measurement result. The time length corresponding to the measurement result can be understood as the total measurement time. The first time ratio can be used to indicate the accuracy of the selected subset of sampling points. The smaller the first time ratio, the higher the accuracy of the subset of sampling points; the larger the first time ratio, the lower the accuracy of the subset of sampling points.

[0080] If the power contained in some sampling points accounts for the majority of the power of all sampling points, then some sampling points can reflect the characteristics of the original measurement results. By feeding back some sampling points, the characteristics of most sampling points can be transmitted with less signaling load.

[0081] In some possible implementations, the first device may notify the second device of a subset of the sampling points. For example, the first device may perform signal measurements and report a subset of sampling points upon request from the second device. The second device may instruct the first device whether to report the data at a fixed sampling point length or at a variable sampling point length. If reporting at a variable sampling point length, the first device may also report the length of a subset of the sampling points to the second device.

[0082] The first information may include one or more of the following:

[0083] 1) Signal strength at some sampling points, such as power and amplitude;

[0084] 2) The sequence number of some sampling points among all sampling points. When the partial sampling points are consecutive, the sequence number information of the segment where the partial sampling points are located can be notified, such as the sequence number being the start point and end point, or the start point and length, or the length and end point, etc.

[0085] 3) Channel impulse response;

[0086] 4) The signal obtained after transforming the frequency domain sampled signal;

[0087] 5) The signal obtained after transforming the time-domain sampled signal;

[0088] 6) Information related to the proportion of some sampling points among all sampling points.

[0089] The above information actually reflects the reliability of some of the reported sampling points. Neural networks have high requirements for data reliability during learning; if the input data is incorrect, it will skew the learning direction, resulting in a larger estimation error in the learned model. When generating the model, the reported proportion information can be used to determine whether to use the data for learning or discard it.

[0090] For example, the proportion of the length of a portion of the sampling points to the total length of all sampling points is 'a', which is the first-time ratio. A smaller value for 'a' indicates more concentrated data (i.e., data concentrated in a few points). For channel impulse response, more concentrated data indicates less severe channel dispersion. In extreme cases, a portion of the sampling points may be only one point, indicating that this channel impulse response is a line-of-sight (LoS) channel impulse response. When channel dispersion is not severe, the propagation environment is usually good. When 'a' is small, it can be considered that a portion of the sampling points can reflect the information of all sampling points, and the reliability of this portion of the sampling points is high.

[0091] For example, the ratio of the power of a portion of the sampling points to the sum of the power of all sampling points, denoted as b, can be considered as the normalized power, i.e., the first power ratio is b. When b is large, it indicates that the measured signal and noise are concentrated in a portion of the sampling points. Typically, the remaining points, excluding the portion of the sampling points, contain noise. When the power of the remaining points is small, it indicates low noise, suggesting that the noise in the portion of the sampling points is relatively low, and thus, higher reliability.

[0092] For example, proportional information can be a function of a, b, the length of a portion of the sampling points, and / or the length of all sampling points. For instance, a and b can be combined to indicate the reliability of the partial sampling, such as b / a or a / b; or b can be divided by the length of the partial sampling points to represent the reliability of the partial sampling points, i.e., the average normalized power of each point in the partial sampling points can also represent the reliability of the partial sampling points.

[0093] The direction information of the first reference signal can be represented by a first orthogonal vector group. In some implementations, the direction information of the first reference signal may include the amplitude values ​​of all vectors in the first orthogonal vector group. In some implementations, the direction information of the first reference signal may include the amplitude values ​​of some vectors in the first orthogonal vector group. For example, the direction information of the first reference signal may include the amplitude value of a first vector in the first orthogonal vector group, where the first vector is a vector with amplitude values, or in other words, the amplitude value of the first reference signal on the first vector is not zero. That is, the first device can only report information about vectors with amplitude values, thus reducing reporting overhead.

[0094] The first orthogonal vector group can be predefined by the protocol, or the first orthogonal vector group can be indicated to the first device by the second device.

[0095] In some embodiments, the first information is used to train and / or test the first model. For example, the input to the first model may include the first information, and the output of the first model may include parameters for localization. In some implementations, the input to the first model may include one or more of the following: measurement information of partial sampling points, the type of a first subspace, a first power ratio, a first time ratio, and direction information of a first reference signal. The measurement information may include CIR and / or PDP.

[0096] If the input to the first model includes a CIR, then each input value of the CIR is a complex number, meaning each input value contains two real values: {real part, imaginary part} or {amplitude, phase}. If the input to the first model is a PDP, then each input value of the PDP is the first real value.

[0097] In some embodiments, when training the first model, the second device may first filter the first information reported by the first device, and then use the filtered first information to train the first model. For example, if the first power of some sampling points in the first information is relatively small, the second device may discard the first information and not use it to train the first model, so as to avoid these information affecting the accuracy of the first model. Similarly, if the first time of some sampling points in the first information is relatively large, the second device may discard the first information and not use it to train the first model, so as to avoid these information affecting the accuracy of the first model.

[0098] Of course, in some embodiments, the second device may also input all the first information into the first model to improve the generalization ability of the first model.

[0099] The first model in this application embodiment can be any type of neural network model. For example, the first model can be an AI model or an ML model.

[0100] The following describes the calculation process of CIR, using the signal measurement result as an example.

[0101] Assume that the CIR should have L taps, each tap containing complex fading {c a,l} l and delay {τ l} l The reference signal (such as PRS or SRS) received at subcarrier k and receiving antenna port a is:

[0102] Where k = -N / 2, -N / 2+1, ..., N / 2-1, N is the number of subcarriers of the reference signal, Δ f For subcarrier spacing, s k For the signal on subcarrier (k+N / 2), W′ a [k] represents noise.

[0103] The measured frequency domain channel response (FDCR) is as follows:

[0104] in,

[0105] Assume N FFT >N,N FFT Δ d For the sampling rate, d l =τ l ·(N FFT Δ fIf ) represents the delay of the sampling period tap, then FDCR can be expressed as:

[0106] The FDCR samples are subjected to an inverse fast fourier transform (IFFT) to obtain the measured time-domain channel impulse response samples:

[0107] because Then there is

[0108] Where d = 0, 1, ..., N FFT -1, w a [d] is W a Inverse Fourier transform of [k].

[0109] for Its function waveform is shown in Figures 5 and 6. Figure 6 is a magnified view of the first 50 points. Wherein, N... FFT =4096, N=3267,d l =τ l ·(N FFT Δ f ), τ l =265ns.

[0110] As can be seen from Figures 5 and 6, there are higher amplitude values ​​at taps 33 and 34, while the amplitude values ​​at other taps are very low. In other words, the signals at taps 33 and 34 are valid, while the signals at other taps are noise.

[0111] The first device can retain the data of the first N_t samples and discard the data of the last N_FFT-N_t samples to obtain the truncated channel impulse response from the time-domain channel impulse response.

[0112] The method embodiments of this application have been described in detail above with reference to Figures 1 to 6. The apparatus embodiments of this application will be described in detail below with reference to Figures 7 to 9. It should be understood that the descriptions of the method embodiments correspond to the descriptions of the apparatus embodiments; therefore, any parts not described in detail can be referred to the preceding method embodiments.

[0113] Figure 7 is a schematic block diagram of a communication device provided in an embodiment of this application. The communication device 700 shown in Figure 7 can be any of the first devices described above. The communication device 700 may include a measurement unit 710 and a transmission unit 720.

[0114] The measurement unit 710 is used to measure the first reference signal and obtain the signal measurement result.

[0115] The transmitting unit 720 is used to transmit first information to the second device. The first information includes measurement information of some sampling points in the signal measurement results. The first information is used to train the first model, and the first model is used to locate the terminal device.

[0116] In some possible implementations, the partial sampling points are determined based on the corresponding power values ​​of the sampling points.

[0117] In some possible implementations, the partial sampling points are determined based on the coordinate values ​​of the sampling points in a first subspace of the first reference signal.

[0118] In some possible implementations, the first subspace includes a signal subspace and / or a noise subspace.

[0119] In some possible implementations, the sending unit is further configured to: send first indication information to the second device, the first indication information being used to indicate the type of the first subspace.

[0120] In some possible implementations, the partial sampling points include the sampling point with the highest power value and / or the sampling point with a power value greater than or equal to a preset threshold.

[0121] In some possible implementations, the partial sampling points include temporally continuous sampling points.

[0122] In some possible implementations, the first information may further include one or more of the following: a first power ratio, which is the ratio of the total power value corresponding to the partial sampling points to the total power value corresponding to the signal measurement result; a first time ratio, which is the ratio of the time length corresponding to the partial sampling points to the time length corresponding to the signal measurement result; the ratio of the first power ratio to the first time ratio; and the direction information of the first reference signal.

[0123] In some possible implementations, the direction information of the first reference signal is represented by a first set of orthogonal vectors.

[0124] In some possible implementations, the direction information of the first reference signal includes the amplitude value of the first vector in the first orthogonal vector group, wherein the first vector is a vector having an amplitude value.

[0125] In some possible implementations, the first orthogonal vector group is predefined by the protocol.

[0126] In some possible implementations, the first information includes one or more of the following: channel impulse response (CIR), power delay spectrum (PDP), and delay spectrum (DP).

[0127] In some possible implementations, the first device is a terminal device or a network device, and the second device is a positioning device.

[0128] In an optional embodiment, the transmitting unit 710 may be a transceiver 930, and the measuring unit 710 may be a processor 910. The communication device 700 may also include a memory 920, as shown in FIG9.

[0129] Figure 8 is a schematic block diagram of a communication device provided in an embodiment of this application. The communication device 800 shown in Figure 8 can be any of the second devices described above. The communication device 800 may include a receiving unit 810.

[0130] The receiving unit 810 is used to receive first information sent by the first device. The first information is determined by the signal measurement result obtained by the first device from measuring the first reference signal. The first information includes measurement information of some sampling points in the signal measurement result. The first information is used to train the first model. The first model is used to locate the terminal device.

[0131] In some possible implementations, the partial sampling points are determined based on the corresponding power values ​​of the sampling points.

[0132] In some possible implementations, the partial sampling points are determined based on the coordinate values ​​of the sampling points in a first subspace of the first reference signal.

[0133] In some possible implementations, the first subspace includes a signal subspace and / or a noise subspace.

[0134] In some possible implementations, the receiving unit is further configured to: receive first indication information sent by the first device, the first indication information being used to indicate the type of the first subspace.

[0135] In some possible implementations, the partial sampling points include the sampling point with the highest power value and / or the sampling point with a power value greater than or equal to a preset threshold.

[0136] In some possible implementations, the partial sampling points include temporally continuous sampling points.

[0137] In some possible implementations, the first information may further include one or more of the following: a first power ratio, which is the ratio of the total power value corresponding to the partial sampling points to the total power value corresponding to the signal measurement result; a first time ratio, which is the ratio of the time length corresponding to the partial sampling points to the time length corresponding to the signal measurement result; the ratio of the first power ratio to the first time ratio; and the direction information of the first reference signal.

[0138] In some possible implementations, the direction information of the first reference signal is represented by a first set of orthogonal vectors.

[0139] In some possible implementations, the direction information of the first reference signal includes the amplitude value of the first vector in the first orthogonal vector group, wherein the first vector is a vector having an amplitude value.

[0140] In some possible implementations, the first orthogonal vector group is predefined by the protocol.

[0141] In some possible implementations, the first information includes one or more of the following: channel impulse response (CIR), power delay spectrum (PDP), and delay spectrum (DP).

[0142] In some possible implementations, the first device is a terminal device or a network device, and the second device is a positioning device.

[0143] In an optional embodiment, the receiving unit 810 may be a transceiver 930. The communication device 800 may also include a processor 910 and a memory 920, as shown in FIG9.

[0144] Figure 9 is a schematic structural diagram of a communication device according to an embodiment of this application. The dashed lines in Figure 9 indicate that the unit or module is optional. This device 900 can be used to implement the methods described in the above method embodiments. Device 900 can be a chip, a first device, or a second device.

[0145] The apparatus 900 may include one or more processors 910. The processor 910 may support the apparatus 900 in implementing the methods described in the preceding method embodiments. The processor 910 may be a general-purpose processor or a special-purpose processor. For example, the processor may be a central processing unit (CPU). Alternatively, the processor may be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor.

[0146] The apparatus 900 may further include one or more memories 920. The memories 920 store a program that can be executed by the processor 910, causing the processor 910 to perform the methods described in the preceding method embodiments. The memories 920 may be independent of the processor 910 or integrated within the processor 910.

[0147] The device 900 may also include a transceiver 930. The processor 910 can communicate with other devices or chips via the transceiver 930. For example, the processor 910 can send and receive data with other devices or chips via the transceiver 930.

[0148] This application also provides a computer-readable storage medium for storing a program. This computer-readable storage medium can be applied to a first or second device provided in this application, and the program causes a computer to perform the methods executed by the first or second device in various embodiments of this application.

[0149] This application also provides a computer program product. The computer program product includes a program. The computer program product can be applied to a first device or a second device provided in this application embodiment, and the program causes a computer to perform the methods executed by the first device or the second device in various embodiments of this application.

[0150] This application also provides a computer program. This computer program can be applied to the first or second device provided in this application, and causes the computer to perform the methods executed by the first or second device in various embodiments of this application.

[0151] It should be understood that the terms "system" and "network" in this application can be used interchangeably. Furthermore, the terminology used in this application is only for explaining specific embodiments of the application and is not intended to limit the application. The terms "first," "second," "third," and "fourth," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish different objects, not to describe a specific order. In addition, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion.

[0152] In the embodiments of this application, the term "instruction" can be a direct instruction, an indirect instruction, or an indication of a relationship. For example, A instructing B can mean that A directly instructs B, such as B being able to obtain information through A; it can also mean that A indirectly instructs B, such as A instructing C, so B can obtain information through C; or it can mean that there is a relationship between A and B.

[0153] In the embodiments of this application, "B corresponding to A" means that B is associated with A, and B can be determined based on A. However, it should also be understood that determining B based on A does not mean that B is determined solely based on A; B can also be determined based on A and / or other information.

[0154] In the embodiments of this application, the term "correspondence" can indicate a direct or indirect correspondence between two things, or an association between two things, or a relationship such as instruction and being instructed, configuration and being configured.

[0155] In this application embodiment, "predefined" or "preconfigured" can be implemented by pre-storing corresponding codes, tables, or other means that can be used to indicate relevant information in the device (e.g., including terminal devices and network devices). This application does not limit the specific implementation method. For example, predefined can refer to what is defined in the protocol.

[0156] In this application embodiment, the "protocol" may refer to a standard protocol in the field of communication, such as the LTE protocol, the NR protocol, and related protocols applied to future communication systems. This application does not limit this.

[0157] In the embodiments of this application, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this document generally indicates that the preceding and following related objects have an "or" relationship.

[0158] In the various embodiments of this application, the order of the above-mentioned processes does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0159] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0160] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0161] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0162] In the above embodiments, implementation can be achieved entirely or partially through software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented entirely or partially in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can read or a data storage device such as a server or data center that integrates one or more available media. The available media may be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., digital video discs, DVDs) or semiconductor media (e.g., solid-state disks, SSDs), etc.

[0163] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A wireless communication method, characterized in that, include: The first device measures the first reference signal and obtains the signal measurement result; The first device sends first information to the second device. The first information includes measurement information of some sampling points in the signal measurement results. The first information is used to train the first model, and the model is used to locate the terminal device.

2. The method according to claim 1, characterized in that, The sampling points are determined based on the corresponding power values ​​of the sampling points.

3. The method according to claim 2, characterized in that, The partial sampling points are determined based on the coordinate values ​​of the sampling points in the first subspace of the first reference signal.

4. The method according to claim 3, characterized in that, The first subspace includes a signal subspace and / or a noise subspace.

5. The method according to claim 3 or 4, characterized in that, The method further includes: The first device sends a first indication message to the second device, the first indication message being used to indicate the type of the first subspace.

6. The method according to any one of claims 2-5, characterized in that, The sampling points include the sampling point with the highest power value and / or the sampling point with a power value greater than or equal to a preset threshold.

7. The method according to claim 6, characterized in that, The sampling points include sampling points that are continuous in time.

8. The method according to any one of claims 1-7, characterized in that, The first information also includes one or more of the following: The first power ratio is the ratio of the total power value corresponding to the partial sampling points to the total power value corresponding to the signal measurement result; The first time ratio is the ratio of the time length corresponding to the partial sampling points to the time length corresponding to the signal measurement result; The ratio of the first power ratio to the first time ratio; The direction information of the first reference signal.

9. The method according to claim 8, characterized in that, The direction information of the first reference signal is represented by a first orthogonal vector group.

10. The method according to claim 9, characterized in that, The direction information of the first reference signal includes the amplitude value of the first vector in the first orthogonal vector group, where the first vector is a vector with an amplitude value.

11. The method according to claim 9 or 10, characterized in that, The first orthogonal vector group is predefined by the protocol.

12. The method according to any one of claims 1-11, characterized in that, The first information includes one or more of the following: channel impulse response (CIR), power delay spectrum (PDP), and delay spectrum (DP).

13. The method according to any one of claims 1-12, characterized in that, The first device is a terminal device or a network device, and the second device is a positioning device.

14. A wireless communication method, characterized in that, include: The second device receives first information sent by the first device. The first information is determined by the signal measurement result obtained by the first device from the measurement of the first reference signal. The first information includes the measurement information of some sampling points in the signal measurement result. The first information is used to train the first model. The first model is used to locate the terminal device.

15. The method according to claim 14, characterized in that, The sampling points are determined based on the corresponding power values ​​of the sampling points.

16. The method according to claim 15, characterized in that, The partial sampling points are determined based on the coordinate values ​​of the sampling points in the first subspace of the first reference signal.

17. The method according to claim 16, characterized in that, The first subspace includes a signal subspace and / or a noise subspace.

18. The method according to claim 16 or 17, characterized in that, The method further includes: The second device receives first indication information sent by the first device, the first indication information being used to indicate the type of the first subspace.

19. The method according to any one of claims 16-18, characterized in that, The sampling points include the sampling point with the highest power value and / or the sampling point with a power value greater than or equal to a preset threshold.

20. The method according to claim 19, characterized in that, The sampling points include sampling points that are continuous in time.

21. The method according to any one of claims 14-20, characterized in that, The first information also includes one or more of the following: The first power ratio is the ratio of the total power value corresponding to the partial sampling points to the total power value corresponding to the signal measurement result. The ratio of rate values; The first time ratio is the ratio of the time length corresponding to the partial sampling points to the time length corresponding to the signal measurement result; The ratio of the first power ratio to the first time ratio; The direction information of the first reference signal.

22. The method according to claim 21, characterized in that, The direction information of the first reference signal is represented by a first orthogonal vector group.

23. The method according to claim 22, characterized in that, The direction information of the first reference signal includes the amplitude value of the first vector in the first orthogonal vector group, where the first vector is a vector with an amplitude value.

24. The method according to claim 22 or 23, characterized in that, The first orthogonal vector group is predefined by the protocol.

25. The method according to any one of claims 14-25, characterized in that, The first information includes one or more of the following: channel impulse response (CIR), power delay spectrum (PDP), and delay spectrum (DP).

26. The method according to any one of claims 14-25, characterized in that, The first device is a terminal device or a network device, and the second device is a positioning device.

27. A communication device, characterized in that, The communication device is a first device, comprising: The measurement unit is used to measure the first reference signal and obtain the signal measurement result; The transmitting unit is used to transmit first information to the second device. The first information includes measurement information of some sampling points in the signal measurement results. The first information is used to train the first model, and the first model is used to locate the terminal device.

28. The communication device according to claim 25, characterized in that, The sampling points are determined based on the corresponding power values ​​of the sampling points.

29. The communication device according to claim 28, characterized in that, The partial sampling points are determined based on the coordinate values ​​of the sampling points in the first subspace of the first reference signal.

30. The communication device according to claim 29, characterized in that, The first subspace includes a signal subspace and / or a noise subspace.

31. The communication device according to claim 29 or 30, characterized in that, The transmitting unit is further configured to: Send a first indication message to the second device, the first indication message being used to indicate the type of the first subspace.

32. The communication device according to any one of claims 28-31, characterized in that, The sampling points include the sampling point with the highest power value and / or the sampling point with a power value greater than or equal to a preset threshold.

33. The communication device according to claim 32, characterized in that, The sampling points include sampling points that are continuous in time.

34. The communication device according to any one of claims 27-33, characterized in that, The first information also includes one or more of the following: The first power ratio is the ratio of the total power value corresponding to the partial sampling points to the total power value corresponding to the signal measurement result; The first time ratio is the ratio of the time length corresponding to the partial sampling points to the time length corresponding to the signal measurement result; The ratio of the first power ratio to the first time ratio; The direction information of the first reference signal.

35. The communication device according to claim 34, characterized in that, The direction information of the first reference signal is represented by a first orthogonal vector group.

36. The communication device according to claim 35, characterized in that, The direction information of the first reference signal includes the amplitude value of the first vector in the first orthogonal vector group, where the first vector is a vector with an amplitude value.

37. The communication device according to claim 35 or 36, characterized in that, The first orthogonal vector group is predefined by the protocol.

38. The communication device according to any one of claims 27-37, characterized in that, The first information includes one or more of the following: channel impulse response (CIR), power delay spectrum (PDP), and delay spectrum (DP).

39. The communication device according to any one of claims 27-38, characterized in that, The first device is a terminal device or a network device, and the second device is a positioning device.

40. A communication device, characterized in that, The communication device is a second device, including: The receiving unit is configured to receive first information sent by the first device. The first information is determined by the signal measurement result obtained by the first device from measuring the first reference signal. The first information includes measurement information of some sampling points in the signal measurement result. The first information is used to train the first model, and the first model is used to locate the terminal device.

41. The communication device according to claim 40, characterized in that, The sampling points are determined based on the corresponding power values ​​of the sampling points.

42. The communication device according to claim 41, characterized in that, The partial sampling points are determined based on the coordinate values ​​of the sampling points in the first subspace of the first reference signal.

43. The communication device according to claim 42, characterized in that, The first subspace includes a signal subspace and / or a noise subspace.

44. The communication device according to claim 42 or 43, characterized in that, The receiving unit is also used for: Receive first indication information sent by the first device, the first indication information being used to indicate the type of the first subspace.

45. The communication device according to any one of claims 41-44, characterized in that, The sampling points include the sampling point with the highest power value and / or the sampling point with a power value greater than or equal to a preset threshold.

46. ​​The communication device according to claim 45, characterized in that, The sampling points include sampling points that are continuous in time.

47. The communication device according to any one of claims 40-46, characterized in that, The first information also includes one or more of the following: The first power ratio is the ratio of the total power value corresponding to the partial sampling points to the total power value corresponding to the signal measurement result; The first time ratio is the ratio of the time length corresponding to the partial sampling points to the time length corresponding to the signal measurement result; The ratio of the first power ratio to the first time ratio; The direction information of the first reference signal.

48. The communication device according to claim 47, characterized in that, The direction information of the first reference signal is represented by a first orthogonal vector group.

49. The communication device according to claim 48, characterized in that, The direction information of the first reference signal includes the amplitude value of the first vector in the first orthogonal vector group, where the first vector is a vector with an amplitude value.

50. The communication device according to claim 48 or 49, characterized in that, The first orthogonal vector group is predefined by the protocol.

51. The communication device according to any one of claims 40-50, characterized in that, The first information includes one or more of the following: channel impulse response (CIR), power delay spectrum (PDP), and delay spectrum (DP).

52. The communication device according to any one of claims 40-51, characterized in that, The first device is a terminal device or a network device, and the second device is a positioning device.

53. A communication device, characterized in that, The communication device is a first device, including a transceiver, a memory, and a processor. The memory is used to store a program, and the processor is used to call the program in the memory and control the transceiver to receive or send signals so that the terminal performs the method as described in any one of claims 1-13.

54. A communication device, characterized in that, The communication device is a second device, including a transceiver, a memory, and a processor. The memory is used to store programs, and the processor is used to call the programs in the memory and control the transceiver to receive or send signals so that the network device performs the method as described in any one of claims 14-26.

55. An apparatus, characterized in that, Includes a processor for calling a program from memory to cause the apparatus to perform the method as described in any one of claims 1-13 or 14-26.

56. A chip, characterized in that, Includes a processor for calling a program from memory, causing a device on which the chip is mounted to perform the method as described in any one of claims 1-13 or 14-26.

57. A computer-readable storage medium, characterized in that, It contains a program that causes a computer to perform the method as described in any one of claims 1-13 or 14-26.

58. A computer program product, characterized in that, Includes a program that causes a computer to perform the method as described in any one of claims 1-13 or 14-26.

59. A computer program, characterized in that, The computer program causes the computer to perform the method as described in any one of claims 1-13 or 14-26.

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