Wireless communication method, device and equipment

Abstract

The invention discloses a wireless communication method, device and equipment, and belongs to the field of communication, and the wireless communication method comprises the steps that first equipment receives first information from second equipment; wherein the first information is used for indicating at least one of the following items: a timed reporting granularity factor K1 and a minimum reporting number N1 of information units; the first device sends second information to the second device; the second information is used for carrying out a positioning function based on an AI model, and the second information comprises at least one of signal measurement information and position related information; wherein the signal measurement information comprises at least one of the following items: information of at least one measurement unit, quality information of at least one measurement unit, a timestamp associated with at least one measurement unit, and a first identifier associated with at least one measurement unit; wherein the at least one measurement unit is determined based on a timed reporting granularity factor K2 and / or a reporting number N2 of the information units, K2 is less than or equal to K1, and N2 is greater than or equal to N1.

Description

Technical Field

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

[0002] In New Radio (NR) systems, positioning functions can be implemented based on Artificial Intelligence (AI) models. However, the positioning accuracy of AI-based positioning functions disclosed in related technologies is not high. How to improve the positioning accuracy of AI-based positioning functions is a problem that needs to be solved. Summary of the Invention

[0003] This application provides a wireless communication method, apparatus, and device that can solve the problem of low positioning accuracy in AI model-based positioning functions.

[0004] Firstly, a wireless communication method is provided, comprising:

[0005] The first device receives first information from the second device; wherein the first information is used to indicate at least one of the following: periodically reporting granularity factor K1, and the minimum reporting quantity N1 of information units; wherein K1 is an integer and N1 is a positive integer;

[0006] The first device sends second information to the second device; wherein the second information is used for positioning based on an artificial intelligence (AI) model, and the second information includes at least one of the following: signal measurement information, location-related information;

[0007] The signal measurement information includes at least one of the following: information of at least one measurement unit, quality information of the at least one measurement unit, timestamp associated with the at least one measurement unit, and first identifier associated with the at least one measurement unit; the location-related information includes at least one of the following: location tag, quality information of the location tag, and timestamp associated with the location tag;

[0008] The information of the measurement unit includes at least one of the following: time delay information, power information, and phase information;

[0009] The at least one measurement unit is determined based on the number of timed reporting granularity factor K2 and / or information unit reporting N2, where K2 is less than or equal to K1, N2 is greater than or equal to N1, K2 is an integer, and N2 is a positive integer.

[0010] The first identifier is associated with the network environment information on the Radio Access Network (RAN) side.

[0011] Secondly, a wireless communication method is provided, including:

[0012] The second device sends first information to the first device; wherein the first information is used to indicate at least one of the following: periodically reporting granularity factor K1, and the minimum reporting quantity N1 of information units; wherein K1 is an integer and N1 is a positive integer;

[0013] The second device receives second information from the first device; wherein the second information is used for positioning based on an artificial intelligence (AI) model, and the second information includes at least one of the following: signal measurement information, location-related information;

[0014] The signal measurement information includes at least one of the following: information of at least one measurement unit, quality information of the at least one measurement unit, timestamp associated with the at least one measurement unit, and first identifier associated with the at least one measurement unit; the location-related information includes at least one of the following: location tag, quality information of the location tag, and timestamp associated with the location tag;

[0015] The information of the measurement unit includes at least one of the following: time delay information, power information, and phase information;

[0016] The at least one measurement unit is determined based on the number of timed reporting granularity factor K2 and / or information unit reporting N2, where K2 is less than or equal to K1, N2 is greater than or equal to N1, K2 is an integer, and N2 is a positive integer.

[0017] The first identifier is associated with the network environment information on the Radio Access Network (RAN) side.

[0018] Thirdly, a wireless communication device is provided, comprising:

[0019] A receiving module is configured to receive first information from a second device; wherein the first information is configured to indicate at least one of the following: a granularity factor K1 for periodic reporting, and a minimum reporting quantity N1 for information units; wherein K1 is an integer and N1 is a positive integer;

[0020] A sending module is used to send second information to the second device; wherein the second information is used for positioning based on an AI model, and the second information includes at least one of the following: signal measurement information, location-related information;

[0021] The signal measurement information includes at least one of the following: information of at least one measurement unit, quality information of the at least one measurement unit, timestamp associated with the at least one measurement unit, and first identifier associated with the at least one measurement unit; the location-related information includes at least one of the following: location tag, quality information of the location tag, and timestamp associated with the location tag;

[0022] The information of the measurement unit includes at least one of the following: time delay information, power information, and phase information;

[0023] The at least one measurement unit is determined based on the number of timed reporting granularity factor K2 and / or information unit reporting N2, where K2 is less than or equal to K1, N2 is greater than or equal to N1, K2 is an integer, and N2 is a positive integer.

[0024] The first identifier is associated with the network environment information on the RAN side.

[0025] Fourthly, a wireless communication device is provided, comprising:

[0026] A sending module is configured to send first information to a first device; wherein the first information is configured to indicate at least one of the following: a periodic reporting granularity factor K1, and a minimum reporting quantity N1 of information units; wherein K1 is an integer and N1 is a positive integer;

[0027] A receiving module is configured to receive second information from the first device; wherein the second information is used for positioning based on an AI model, and the second information includes at least one of the following: signal measurement information, location-related information;

[0028] The signal measurement information includes at least one of the following: information of at least one measurement unit, quality information of the at least one measurement unit, timestamp associated with the at least one measurement unit, and first identifier associated with the at least one measurement unit; the location-related information includes at least one of the following: location tag, quality information of the location tag, and timestamp associated with the location tag;

[0029] The information of the measurement unit includes at least one of the following: time delay information, power information, and phase information;

[0030] The at least one measurement unit is determined based on the number of timed reporting granularity factor K2 and / or information unit reporting N2, where K2 is less than or equal to K1, N2 is greater than or equal to N1, K2 is an integer, and N2 is a positive integer.

[0031] The first identifier is associated with the network environment information on the RAN side.

[0032] Fifthly, a wireless communication device is provided, the device being configured to perform the steps of the method described in the first aspect, or to implement the steps of the method described in the second aspect.

[0033] In a sixth aspect, a terminal is provided, the terminal including a processor and a memory, the memory storing a program or instructions executable on the processor, the program or instructions, when executed by the processor, implementing the steps of the method as described in the first aspect.

[0034] Seventhly, a terminal is provided, including a processor and a communication interface;

[0035] The communication interface is used to receive first information from the second device; wherein the first information is used to indicate at least one of the following: periodically reporting granularity factor K1, and the minimum reporting quantity N1 of information units; wherein K1 is an integer and N1 is a positive integer;

[0036] The communication interface is also used to send second information to the second device; wherein the second information is used for positioning based on an AI model, and the second information includes at least one of the following: signal measurement information, location-related information;

[0037] The signal measurement information includes at least one of the following: information of at least one measurement unit, quality information of the at least one measurement unit, timestamp associated with the at least one measurement unit, and first identifier associated with the at least one measurement unit; the location-related information includes at least one of the following: location tag, quality information of the location tag, and timestamp associated with the location tag;

[0038] The information of the measurement unit includes at least one of the following: time delay information, power information, and phase information;

[0039] The at least one measurement unit is determined based on the number of timed reporting granularity factor K2 and / or information unit reporting N2, where K2 is less than or equal to K1, N2 is greater than or equal to N1, K2 is an integer, and N2 is a positive integer.

[0040] The first identifier is associated with the network environment information on the Radio Access Network (RAN) side.

[0041] Eighthly, a network-side device is provided, the network-side device including a processor and a memory, the memory storing a program or instructions executable on the processor, the program or instructions, when executed by the processor, implementing the steps of the method as described in the second aspect.

[0042] Ninthly, a network-side device is provided, including a processor and a communication interface;

[0043] The communication interface is used to send first information to the first device; wherein the first information is used to indicate at least one of the following: periodically reporting granularity factor K1, and the minimum reporting quantity N1 of information units; wherein K1 is an integer and N1 is a positive integer;

[0044] The communication interface is also used to receive second information from the first device; wherein the second information is used for AI model-based positioning function, and the second information includes at least one of the following: signal measurement information, location-related information;

[0045] The signal measurement information includes at least one of the following: information of at least one measurement unit, quality information of the at least one measurement unit, timestamp associated with the at least one measurement unit, and first identifier associated with the at least one measurement unit; the location-related information includes at least one of the following: location tag, quality information of the location tag, and timestamp associated with the location tag;

[0046] The information of the measurement unit includes at least one of the following: time delay information, power information, and phase information;

[0047] The at least one measurement unit is determined based on the number of timed reporting granularity factor K2 and / or information unit reporting N2, where K2 is less than or equal to K1, N2 is greater than or equal to N1, K2 is an integer, and N2 is a positive integer.

[0048] The first identifier is associated with the network environment information on the Radio Access Network (RAN) side.

[0049] In a tenth aspect, a readable storage medium is provided, on which a program or instructions are stored, which, when executed by a processor, implement the steps of the method described in the first aspect, or implement the steps of the method described in the second aspect.

[0050] Eleventhly, a wireless communication system is provided, comprising: a terminal and a network-side device, wherein the terminal can be used to perform the steps of the method as described in the first aspect, and the network-side device can be used to perform the steps of the method as described in the second aspect.

[0051] In a twelfth aspect, a chip is provided, the chip including a processor and a communication interface coupled to the processor, the processor being configured to run programs or instructions to implement the method as described in the first aspect, or to implement the method as described in the second aspect.

[0052] In a thirteenth aspect, a computer program / program product is provided, which is stored in a storage medium and is executed by at least one processor to implement the steps of the wireless communication method as described in the first aspect, or to implement the steps of the wireless communication method as described in the second aspect.

[0053] In this embodiment, a first device receives first information from a second device; wherein the first information is used to indicate at least one of the following: a timed reporting granularity factor K1, and a minimum reporting quantity N1 of information units; the first device sends second information to the second device; wherein the second information is used to perform AI model-based positioning function, and the second information includes at least one of the following: signal measurement information, and location-related information; wherein the signal measurement information includes at least one of the following: information of at least one measurement unit, quality information of at least one measurement unit, a timestamp associated with at least one measurement unit, and a first identifier associated with at least one measurement unit; the location-related information includes at least one of the following: a location tag, quality information of the location tag, and a timestamp associated with the location tag; wherein at least one measurement unit is determined based on a timed reporting granularity factor K2 and / or a reporting quantity N2 of information units, where K2 is less than or equal to K1, and N2 is greater than or equal to N1; wherein the first identifier is associated with network environment information on the RAN side. Specifically, the first device can determine at least one measurement unit based on the timed reporting granularity factor K2 and / or the number of information units reported N2. By restricting K2 to be less than or equal to K1 and N2 to be greater than or equal to N1, the granularity of the delay information of the information units contained in each reported measurement unit and the number of information units contained therein meet the requirements of the AI ​​positioning model on the network side, thereby improving the positioning accuracy of the AI ​​model-based positioning function. For example, the smaller the timed reporting granularity factor K2, the smaller the granularity of the delay information of the information units, the higher the degree of freedom provided to the network side, and the higher the positioning accuracy of the AI ​​model-based positioning function based on the second information; and / or, the larger the number of information units reported N2, the more information units there are, and the higher the positioning accuracy of the AI ​​model-based positioning function based on the second information. Attached Figure Description

[0054] Figure 1 This is a schematic diagram of a communication system architecture provided in an embodiment of this application.

[0055] Figure 2 This is a schematic diagram of a neural network provided in this application.

[0056] Figure 3 This is a schematic diagram of a neuron provided in this application.

[0057] Figure 4 This is a schematic flowchart of a wireless communication method provided according to an embodiment of this application.

[0058] Figure 5 This is a schematic diagram of a channel sampling point and a channel path provided according to an embodiment of this application.

[0059] Figure 6This is a schematic diagram of signal measurement information provided according to an embodiment of this application.

[0060] Figures 7 to 14 These are schematic diagrams of channel sampling points provided according to embodiments of this application.

[0061] Figure 15 This is a schematic diagram of a first measuring window provided according to an embodiment of this application.

[0062] Figure 16 This is a schematic diagram of another first measurement window provided according to an embodiment of this application.

[0063] Figure 17 This is a schematic diagram of a second measuring window provided according to an embodiment of this application.

[0064] Figure 18 This is a schematic diagram of a first time interval provided according to an embodiment of this application.

[0065] Figure 19 This is a schematic diagram illustrating the acquisition of signal measurement information and location-related information according to an embodiment of this application.

[0066] Figure 20 This is a schematic diagram illustrating the reporting of signal measurement information and location-related information according to an embodiment of this application.

[0067] Figure 21 This is a schematic diagram illustrating another method for reporting signal measurement information and location-related information according to an embodiment of this application.

[0068] Figure 22 This is a schematic diagram illustrating another method for reporting signal measurement information and location-related information according to an embodiment of this application.

[0069] Figure 23 This is a schematic diagram illustrating another method of reporting signal measurement information and location-related information according to an embodiment of this application.

[0070] Figure 24 This is a schematic block diagram of a wireless communication device provided according to an embodiment of this application.

[0071] Figure 25 This is a schematic block diagram of another wireless communication device provided according to an embodiment of this application.

[0072] Figure 26 This is a schematic block diagram of a communication device provided according to an embodiment of this application.

[0073] Figure 27 This is a schematic diagram of the hardware structure of a terminal according to an embodiment of this application.

[0074] Figure 28 This is a schematic block diagram of a network-side device provided according to an embodiment of this application.

[0075] Figure 29 This is a schematic block diagram of a network-side device provided according to an embodiment of this application. Detailed Implementation

[0076] The technical solutions of the embodiments of this application will be clearly described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application are within the scope of protection of this application.

[0077] The terms "first," "second," etc., used in this application are used to distinguish similar objects and not to describe a specific order or sequence. It should be understood that such terms can be used interchangeably where appropriate so that embodiments of this application can be implemented in orders other than those illustrated or described herein, and the objects distinguished by "first" and "second" are generally of the same class, not limited in number; for example, the first object can be one or more. Furthermore, "or" in this application indicates at least one of the connected objects. For example, the scope of protection for "A or B" covers at least three scenarios: Scenario 1: including A but not B; Scenario 2: including B but not A; Scenario 3: including both A and B. In addition, the terms "A and / or B," "at least one of A and B," and "at least one of A or B" also cover at least the above three scenarios. The character " / " generally indicates that the preceding and following objects are in an "or" relationship.

[0078] The term "instruction" in this application can be either a direct instruction (or explicit instruction) or an indirect instruction (or implicit instruction). A direct instruction can be understood as one in which the sender explicitly informs the receiver of specific information, the operation to be performed, or the requested result, etc., in the instruction sent. An indirect instruction can be understood as one in which the receiver determines the corresponding information based on the instruction sent by the sender, or makes a judgment and determines the operation to be performed or the requested result, etc., based on the judgment result.

[0079] It is worth noting that the technologies described in this application are not limited to Long Term Evolution (LTE) / LTE-Advanced (LTE-A) systems, but can also be used in other wireless communication systems, such as Code Division Multiple Access (CDMA), Time Division Multiple Access (TDMA), Frequency Division Multiple Access (FDMA), Orthogonal Frequency Division Multiple Access (OFDMA), Single-carrier Frequency-Division Multiple Access (SC-FDMA), or other systems. The terms "system" and "network" in this application are often used interchangeably, and the described technologies can be used with the systems and radio technologies mentioned above, as well as with other systems and radio technologies. The following description describes New Radio (NR) systems for illustrative purposes, and the term NR is used in most of the following description; however, these technologies can also be applied to systems other than NR systems, such as 6th generation (6G) radio systems. th Generation 6G communication system.

[0080] Figure 1 This diagram illustrates a block diagram of a wireless communication system applicable to embodiments of this application. Specifically, the wireless communication system includes a terminal 11 and a network-side device 12.

[0081] Terminal 11 can be a mobile phone, tablet computer, laptop computer, notebook computer, personal digital assistant (PDA), handheld computer, netbook, ultra-mobile personal computer (UMPC), mobile internet device (MID), augmented reality (AR), virtual reality (VR) device, robot, wearable device, flight vehicle, vehicle user equipment (VUE), shipboard equipment, pedestrian user equipment (PUE), smart home device (home device with wireless communication function, such as refrigerator, television, washing machine or furniture, etc.), game console, personal computer (PC), ATM or self-service machine, etc. Wearable devices include: smartwatches, smart bracelets, smart earphones, smart glasses, smart jewelry (smart bracelets, smart chains, smart rings, smart necklaces, smart anklets, smart anklets, etc.), smart wristbands, smart clothing, etc. Among these, in-vehicle devices can also be referred to as in-vehicle terminals, in-vehicle controllers, in-vehicle modules, in-vehicle components, in-vehicle chips, or in-vehicle units, etc. It should be noted that the specific type of terminal 11 is not limited in the embodiments of this application.

[0082] Among them, network-side equipment 12 may include access network equipment or core network equipment.

[0083] Alternatively, access network equipment may also be referred to as Radio Access Network (RAN) equipment, radio access network function, or radio access network unit. Access network equipment may include base stations, wireless local area network (WLAN) access points (APs), or wireless Fidelity (WiFi) nodes, etc. The term "base station" can be referred to as Node B (NB), Evolved Node B (eNB), Next Generation Node B (gNB), New Radio Node B (NRNode B), Access Point, Relay Base Station (RBS), Serving Base Station (SBS), Base Transceiver Station (BTS), Radio Base Station, Radio Transceiver, Basic Service Set (BSS), Extended Service Set (ESS), Home Node B (HNB), Home Evolved Node B, Transmit / Receive Point (TRP), or any other suitable term in the relevant field, as long as the same technical effect is achieved. The term "base station" is not limited to specific technical terms. It should be noted that this application embodiment only uses a base station in an NR system as an example for description and does not limit the specific type of base station.

[0084] Optionally, core network equipment may also be referred to as core network nodes, core network functions, or core network elements, and includes, but is not limited to, at least one of the following: Mobility Management Entity (MME), Access and Mobility Management Function (AMF), Session Management Function (SMF), User Plane Function (UPF), Policy Control Function (PCF), Policy and Charging Rules Function (PCRF), Edge Application Server Discovery Function (EASDF), Unified Data Management (UDM), Unified Data Repository (UDR), Home Subscriber Server (HSS), Centralized network configuration (CNC), Network Repository Function (NRF), Network Exposure Function (NEF), and Local NEF. The core network equipment (NEF, or L-NEF) includes the following functions: Binding Support Function (BSF), Application Function (AF), Location Management Function (LMF), Gateway Mobile Location Centre (GMLC), and Network Data Analytics Function (NWDAF). It should be noted that this application only uses core network equipment in the NR system as an example and does not limit the specific type of core network equipment. If the name of the core network equipment mentioned in this application changes in subsequent protocol versions (e.g., 6G), it will still be within the scope of protection of this application.

[0085] Optionally, the core network equipment can be implemented by one or more functional modules in a single device, or by multiple devices working together; this application does not specifically limit this. It is understood that the aforementioned functional modules can be network elements in hardware devices, software functional modules running on dedicated hardware, or virtualized functional modules instantiated on a platform (e.g., a cloud platform).

[0086] To facilitate a better understanding of the embodiments of this application, artificial intelligence (AI) will be described.

[0087] Artificial intelligence (AI) has been widely applied in various fields. Integrating AI into wireless communication networks to significantly improve technical indicators such as throughput, latency, and user capacity is an important task for future wireless communication networks. AI modules can be implemented in various ways, such as neural networks, decision trees, support vector machines, and Bayesian classifiers. This application uses neural networks as an example for illustration, but does not limit the specific type of AI module.

[0088] A schematic diagram of a neural network can be shown as follows: Figure 2 As shown in the diagram. The neural network is composed of neurons, and a schematic diagram of a neuron is shown below. Figure 3 As shown in the diagram. Here, a1, a2, ..., aK are the inputs, w is the weight (multiplicative coefficient), b is the bias (additive coefficient), and σ(.) is the activation function. Common activation functions include Sigmoid, tanh, and Rectified Linear Unit (ReLU), etc.

[0089] The parameters of a neural network are optimized using gradient optimization algorithms. Gradient optimization algorithms are a class of algorithms that minimize or maximize an objective function (sometimes called a loss function), which is often a mathematical combination of model parameters and data. For example, given data X and its corresponding label Y, we construct a neural network model f(.). With the model, we can obtain the predicted output f(x) based on the input x, and calculate the difference between the predicted value and the true value (f(x) - Y), which is the loss function. Our goal is to find suitable W and b that minimize the value of the above loss function. The smaller the loss value, the closer our model is to the reality.

[0090] Most common optimization algorithms are based on the error back propagation (BP) algorithm. The basic idea of ​​the BP algorithm is that the learning process consists of two parts: forward propagation of the signal and backward propagation of the error. During forward propagation, the input sample is introduced from the input layer, processed layer by layer by the hidden layers, and then propagated to the output layer. If the actual output of the output layer does not match the expected output, the process transitions to the error back propagation stage. Error back propagation involves propagating the output error back to the input layer layer by layer through the hidden layers, distributing the error to all units in each layer, thus obtaining the error signal of each unit. This error signal serves as the basis for adjusting the weights of each unit. This process of adjusting the weights of each layer through forward and backward propagation is repeated continuously. This continuous adjustment of weights is similar to the learning and training process of a network. This process continues until the error of the network output is reduced to an acceptable level, or until the predetermined number of learning iterations is reached.

[0091] Common optimization algorithms include Gradient Descent, Stochastic Gradient Descent (SGD), mini-batch gradient descent, Momentum, Nesterov (specifically, stochastic gradient descent with momentum), Adaptive Gradient Descent (Adagrad), Adadelta, root mean square propagation (RMSprop), and Adaptive Moment Estimation (Adam). During error backpropagation, these algorithms calculate the gradient by taking the derivative / partial derivative of the error / loss obtained from the loss function with respect to the current neuron, adding the learning rate and the effects of previous gradients / derivatives / partial derivatives, and then propagating this gradient to the previous layer.

[0092] In practice, due to the relatively small size of real-time datasets, training neural networks directly on small datasets may lead to overfitting. Neural networks may achieve good convergence or inference accuracy on the training set, but poor convergence or inference accuracy on the validation or test set, a problem known as the generalization problem of neural networks. To improve generalization ability, a common approach is to pre-train neural networks on a large amount of offline collected data, and then fine-tune the parameters or structure of the pre-trained neural network using real-time collected data (fine-tuning) to adapt the neural network to the real-world environment. If fine-tuning only updates the parameters of the neural network, it can be considered a training process based on the parameters of the pre-trained neural network as initialization. During the fine-tuning stage, parameters of some layers can be frozen. Generally, parameters of layers closer to the input are frozen to retain coarse-grained features learned from large-scale datasets, while parameters of layers closer to the output are fine-tuned to adapt the network to fine-grained features of the real-world environment. The less data available during the fine-tuning stage, the more layers should be frozen, with only a small number of layers closer to the output being fine-tuned. If fine-tuning updates the structure of a neural network, it can fine-tune the structure of the last few layers of the neural network, such as adding an extra layer before the output layer, adjusting the number of neurons in the last few layers, etc. After the structure is changed, the parameters of the neural network can be further updated using the above parameter update methods.

[0093] Generalization of neural networks refers to the ability of a neural network to produce relatively accurate outputs on data not encountered during training (or learning). To address the generalization problem caused by variations in the wireless transmission environment and transceiver hardware implementation (such as the number of antennas and beam patterns), neural network-based wireless communication systems offer three solutions: 1) Training different neural networks under different conditions (such as different cells, different areas, different movement speeds, and different channel conditions), with each condition corresponding to a set of neural network parameters or structures. The parameters of the neural network are adjusted as the actual environment changes to ensure the accuracy of inference. 2) Training a neural network based on a mixed dataset under multiple conditions allows the network to adapt to various conditions, improving its robustness to environmental changes and avoiding frequent switching. 3) Fine-tuning: Re-collecting a set of data under new conditions and fine-tuning the parameters or structure of the original neural network. Each of these three modes has its advantages and disadvantages: The first approach performs well under different transmission conditions, but it requires storing multiple neural network parameters or structures and switching them as needed, which may lead to additional signaling overhead, model management complexity, and frequent switching issues; The second approach allows a single set of neural network parameters or structures to be applicable to multiple conditions, but it cannot achieve optimal performance under every condition; The third approach enables neural networks to be quickly adapted to various new scenarios, but it requires collecting new data and training the neural network model, and its performance is limited by several factors, such as the similarity between the pre-training dataset and the newly collected data, the scale of the new data, etc.

[0094] In machine learning and deep learning, a label (or ground truth label) typically refers to the identification or annotation of the true category or target value of a data sample. Labels are used to represent the information that a model should learn and predict given an input data sample. For example, in classification tasks, a label indicates which category a data sample belongs to. For instance, in image classification, each image sample has a label representing the category or probability of the object or scene contained in the image, such as "dog" or "cat," or the probability of belonging to "dog" or "cat."

[0095] Labels in object detection: Labels typically include the object's location information (bounding box) and category information. Each label identifies a target object in an image, including its location and category.

[0096] Labels for time series forecasting or regression tasks: Labels typically represent the continuous or real-valued objective to be predicted. For example, in a house price forecasting task, the label could be the predicted future house sales price.

[0097] Labels in sequence labeling: In natural language processing, labels in sequence labeling tasks are often used for tasks such as part-of-speech tagging and named entity recognition. Labels are used to represent the attributes or categories of each word or character in a text sequence.

[0098] Labels are a crucial component in supervised learning tasks, used to train machine learning models. Models learn patterns and regularities by comparing themselves to true labels in order to make predictions or classifications on unseen data. The quality and accuracy of the labels are critical to the model's performance.

[0099] To facilitate a better understanding of the embodiments of this application, the channel path and channel sampling points are explained.

[0100] Time-domain channel sampling points are observations of the channel obtained at a certain time granularity T.

[0101] While the LMF can recommend a k value to the UE, the choice of which k value to use for reporting channel path timing information (such as Reference Signal Time Difference (RSTD)) still depends on the UE. However, the UE needs to report the k used to the network side when reporting timing information. For channel path-based reporting, the choice of k value is related to the precision of the timing information (such as RSTD) reported by the terminal. The larger the k value, the coarser the granularity of the reported timing information. The current protocol supports k values ​​in the range of integers greater than or equal to 0 and less than or equal to 5. The k value corresponds to the minimum time interval T = 2 for reporting timing information of two channel paths. k ×T c T c It is the basic time unit of NR. For reporting methods based on channel sampling points, the k value selected by the terminal side may affect the accuracy of the AI ​​model-based positioning function on the LMF side.

[0102] LMF can request the UE to report additional channels besides the initial channel. However, the maximum number of additional channels that the terminal can support reporting depends on the terminal's capabilities (the terminal will tell the LMF the maximum number of additional channels it supports when reporting its capabilities). The actual number of channel channels reported depends on the terminal's implementation, but should not exceed the maximum number of channel channels the terminal supports reporting. LMF instructs the terminal to report additional channel channels. The number of additional channel channels reported by the terminal depends on the terminal's implementation, but should not exceed the maximum number of channel channels supported by the terminal's capabilities (e.g., 8 channels) or the maximum number of channel channels agreed upon in the protocol.

[0103] For channel path-based reporting, there may be situations where the number of additional channel paths detected by the terminal is less than the maximum, such as in wireless environments with few scatterers or sparse channel paths. Furthermore, the accuracy of channel path estimation algorithms varies among different UEs. Therefore, only the maximum number of additional channel paths reported by the terminal is limited; the actual number reported depends on the terminal implementation. For channel sampling point-based reporting, the number of channel sampling points detected by the terminal is independent of the wireless environment but may be related to factors such as the terminal's sampling rate, the number of Inverse Fast Fourier Transform (IFFT) points, and signal bandwidth. Therefore, LMF can specify the actual number of channel sampling points reported by the terminal to improve the performance of AI model-based positioning.

[0104] AI positioning refers to using an AI model to determine the location information of a terminal based on channel measurements (such as the channel delay spectrum, delay power spectrum, and time-domain channel impulse response of at least one TRP associated with the target terminal). For example, by inputting the channel measurements into the AI ​​model, the AI ​​model infers the terminal's location-related information. Location-related information includes at least one of the following: location coordinates, angle-related information (such as Angle of Arrival (AoA) and Angle of Departure (AoD)), delay-related information (such as Time of Arrival (TOA) and RSTD), distance-related information (such as the distance from the UE to the TRP), etc.

[0105] One method for determining channel sampling points is as follows: at the receiving antenna port a, the first sampling point... The reference symbols (positioning reference signals (PRS) or sounding reference signals (SRS)) received at each subcarrier are given by the following formula:

[0106]

[0107] Where k = -N / 2, -N / 2+1, ..., N / 2-1;

[0108] Where N represents the number of subcarriers carrying reference symbols (e.g., N = 3264); Δ f Indicates the subcarrier spacing (e.g., Δ). f =

[0109] 30kHz); s k Indicates the first Known PRS or SRS on each subcarrier; W a ′[k] represents the received noise.

[0110] The measured channel frequency response samples are shown below:

[0111]

[0112] in, For s k . conjugate.

[0113] Assumption: N FFT >N represents the window size for a single Fast Fourier Transform (FFT) (e.g., N0). FFT =4096); N FFT Δ f Indicates the sampling rate (e.g., 4096 × 30 kHz = 122.88 MHz); d l =τ l ·(N FFT Δ f ) represents the channel tap delay expressed in terms of the sampling period.

[0114] Then, the channel frequency response can be expressed as:

[0115]

[0116] By performing an IFFT on the frequency domain channel response sampling points, the measured channel impulse response (CIR) sampling points are obtained:

[0117]

[0118]

[0119] Where d = 0, 1, ..., N FFT -1, and w a [d] is W a IFFT of [k].

[0120] because The term, τ, indicates that a true channel tap can induce a time-domain (TD) response at a large number of measurement sampling points, exhibiting a large response near the true delay and attenuating for sampling points far from the true delay. For example, τ l =265ns, N=3264, and N FFT The actual channel delay when =4096.

[0121] Note that these time-domain or frequency-domain channel measurement sampling points are directly observable at the receiver or receiver unit. These channel sampling points can be further processed in the following ways.

[0122] By retaining only the first N t Sample points and discard the last N. FFT -N t Each sampling point obtains a truncated TDCIR from the TD CIR.

[0123] By retaining only the power information at the antenna port at each sampling grid point, the TD delay power spectrum (TD PDP) is obtained from the (truncated) TD CIR:

[0124]

[0125] By using N with the maximum power t The sampling point is set to a specific value, and the time-domain delay spectrum (TD DP) is obtained from the TD PDP of the sub-sampling point. The specific value can be a constant, such as 1, or the reference signal received power (RSRP) of the link.

[0126]

[0127] Channel path is an estimate of the channel response, such as the time-domain channel impulse response or channel frequency response, obtained by measuring a reference signal and further processed by a multipath extraction algorithm. Specifically, the result of a multipath extraction or estimation algorithm is an estimate of the actual propagation path of a signal in a real-world environment, including the channel path's delay, power, and phase, which respectively describe the changes in delay, power, and phase experienced by the wireless signal as it travels along that propagation path.

[0128] In addition, the current protocol supports channel path-based reporting, supporting the reporting of the first path and up to 8 additional paths. This allows the network side to confirm the true direct path from these 9 channel paths, such as selecting the Nth path as the direct path (Line of Sight, LOS). However, there are no constraints on how these channel paths are determined by the protocol, which depends on the terminal implementation.

[0129] It should be noted that for channel path-based reporting, the choice of k value is related to the precision of the timing information (such as RSTD) reported by the terminal. The larger the k value, the coarser the granularity of the reported timing information. The current protocol supports k values ​​in the range of integers greater than or equal to 0 and less than or equal to 5. The k value corresponds to the minimum time interval T = 2 for the timing information of the two reported channel paths. k ×T c T cIt is the basic time unit of NR. For the reporting method based on channel sampling points, the k value selected by the terminal may affect the accuracy of the AI ​​positioning model on the LMF side. In the embodiments of this application, the LMF needs to instruct or the protocol limits the rules for the terminal to determine the k value.

[0130] It should be noted that for channel path-based reporting, the number of additional paths detected by the terminal may be less than the maximum, for example, in wireless environments with few scatterers or sparse channel paths. Furthermore, the accuracy of channel path estimation algorithms varies among different UEs. Therefore, only the maximum number of additional paths reported by the terminal is limited; the actual number of reported paths depends on the terminal implementation. For channel sampling point-based reporting, the number of channel sampling points detected by the terminal is independent of the wireless environment but may be related to factors such as the terminal's sampling rate, IFFT points, and signal bandwidth. In this embodiment, the LMF can limit the actual number of channel sampling points reported by the terminal to improve the performance of AI-based positioning.

[0131] In this embodiment, during data acquisition, signal measurement information can be considered as AI model input or information related to channel measurements, and location-related information can be considered as AI model output or location-related information. The signal measurement information and location-related information of a data set should be associated with UEs at the same or similar locations to ensure pairing and improve model training performance. The acquired data can be used to train AI models or AI functions related to model supervision.

[0132] The wireless communication method provided in this application will be described in detail below with reference to the accompanying drawings and through some embodiments and application scenarios.

[0133] Figure 4 This is a schematic flowchart of a wireless communication method 200 according to an embodiment of this application, such as... Figure 4 As shown, the wireless communication method 200 may include at least some of the following:

[0134] S210, the second device sends first information to the first device; wherein, the first information is used to indicate at least one of the following: periodically reporting granularity factor K1, and the minimum reporting quantity N1 of information units; wherein, K1 is an integer and N1 is a positive integer;

[0135] S220, the first device receives the first information from the second device;

[0136] S230, the first device sends second information to the second device; wherein, the second information is used for positioning based on an AI model, and the second information includes at least one of the following: signal measurement information, location-related information;

[0137] The signal measurement information includes at least one of the following: information of at least one measurement unit, quality information of the at least one measurement unit, timestamp associated with the at least one measurement unit, and first identifier associated with the at least one measurement unit; the location-related information includes at least one of the following: location tag, quality information of the location tag, and timestamp associated with the location tag;

[0138] The information of the measurement unit includes at least one of the following: time delay information, power information, and phase information;

[0139] The at least one measurement unit is determined based on the number of timed reporting granularity factor K2 and / or information unit reporting N2, where K2 is less than or equal to K1, N2 is greater than or equal to N1, K2 is an integer, and N2 is a positive integer.

[0140] The first identifier is associated with the network environment information on the RAN side;

[0141] S240, the second device receives the second information from the first device.

[0142] It should be understood that Figure 4 The steps or operations of the wireless communication method 200 are illustrated, but these steps or operations are merely examples, and other operations may be performed in this application. Figure 4 Variations of various operations within it.

[0143] In this embodiment, the first device can determine at least one measurement unit based on the timed reporting granularity factor K2 and / or the number of information units reported N2. By restricting K2 to be less than or equal to K1 and N2 to be greater than or equal to N1, the granularity of the delay information of the information units contained in each reported measurement unit and the number of information units contained therein meet the requirements of the AI ​​positioning model on the network side, thereby improving the positioning accuracy of the AI ​​model-based positioning function. Specifically, for example, the smaller the timed reporting granularity factor K2, the smaller the granularity of the delay information of the information units, the higher the degree of freedom provided to the network side, and the higher the positioning accuracy of the AI ​​model-based positioning function based on the second information; and / or, the larger the number of information units reported N2, the more information units there are, and the higher the positioning accuracy of the AI ​​model-based positioning function based on the second information.

[0144] In this embodiment, at least one measurement unit is associated with a first identifier, which is associated with network environment information (such as beam information and / or antenna information) on the RAN side. For example, the network environment information is associated with the beam antenna information of at least one TRP. Specifically, the first device reports the network environment information of the first device to the second device, which facilitates the selection of the AI ​​model associated with the first identifier. This ensures that the network environment during AI model inference on the second device side is consistent with the network environment during AI model training, thereby guaranteeing the inference performance of the AI ​​model.

[0145] The AI-based positioning function described in this application embodiment can also be understood as: an AI-based positioning method, an AI or ML-based positioning method, or an AI or ML-based positioning function.

[0146] In this application embodiment, the AI ​​model-based positioning function includes at least one of the following:

[0147] The location information of the first device (such as a terminal) is inferred or predicted based on AI models;

[0148] Train or optimize the AI ​​model used to achieve localization functionality;

[0149] Monitor or determine the effectiveness of the AI ​​model used to achieve the positioning function;

[0150] Monitor or determine the inference performance of the AI ​​model used to achieve positioning functionality;

[0151] Monitor or determine the inference accuracy of the AI ​​model used to achieve positioning functionality.

[0152] In some embodiments, the second information includes the signal measurement information. In this case, information of at least one measurement unit in the signal measurement information (such as time delay information, power information, phase information, etc.) can be input into the AI ​​model to obtain the location information of the first device (such as a terminal).

[0153] For example, the terminal reports F measurement units, each of which is associated with a positioning reference signal resource; each measurement unit contains one of the following: time delay information of L information units, time delay information and power information of L information units, or time delay information, power information and phase information of L information units. It should be noted that the number of information units contained in each measurement unit can be the same or different.

[0154] Optionally, the quality information of at least one measurement unit in the signal measurement information can be used to filter the information of the measurement units input into the AI ​​model (such as time delay information, power information, phase information, etc.). For example, the information of the S1 measurement units with the best quality (such as time delay information, power information, phase information, etc.) is input into the AI ​​model to obtain the location information of the first device (such as a terminal). Optionally, during the AI ​​model training process, the second device performs weighted optimization based on the quality information of the measurement units to improve the inference performance of the model. Optionally, during the AI ​​model inference process, the second device judges the validity of the AI ​​model inference result based on the quality information of the measurement units.

[0155] Optionally, the timestamp associated with at least one measurement unit in the signal measurement information can be used to filter the information of the measurement units input into the AI ​​model (such as delay information, power information, phase information, etc.). For example, the information of the S2 most recent measurement units (such as delay information, power information, phase information, etc.) can be input into the AI ​​model to obtain the location information of the first device (such as a terminal). In this embodiment, the main purpose of the timestamp is to record the timestamp associated with the data; and to pair it with the location label to improve the accuracy of model training.

[0156] In some embodiments, the second information includes the location-related information. In this case, an AI model for achieving positioning functionality can be trained or optimized based on the location tags in the location-related information.

[0157] Optionally, the quality information of the location labels in the location-related information can be used to filter the location labels used to train or optimize the AI ​​model for localization. For example, the Q1 location labels with the best quality can be selected to train or optimize the location labels of the AI ​​model for localization.

[0158] Optionally, the timestamps associated with the location labels in the location-related information can be used to filter the location labels for training or optimizing AI models used to achieve localization. For example, the location labels of the most recent Q2 location labels can be selected for training or optimizing AI models used to achieve localization. In this embodiment, the main purpose of the timestamps is to record the timestamps associated with the location labels and to pair them with the measurement unit to improve the accuracy of model training.

[0159] The timestamp associated with the measurement unit described in the embodiments of this application can be understood as the timestamp associated with the measurement unit or the measurement time of the measurement unit.

[0160] In some embodiments, the type of measurement unit described in this application may include a combination of time delay information, power information, and phase information. For example, a time delay power spectrum may include time delay information and power information; a time delay spectrum may include time delay information; or a channel impulse response may include time delay information, power information, and phase information.

[0161] The timestamp associated with the location tag described in the embodiments of this application can be understood as the timestamp associated with the location tag or the acquisition time or measurement time of the location tag.

[0162] In some embodiments, the location tag described in this application can be understood as location coordinates or location-related information. The location-related information may include, but is not limited to, at least one of the following: RSTD, AOD, AOA, distance from UE to TRP, Direct Path (LOS) indication or Non-Direct Path (NLOS) indication, and propagation delay of the direct path from UE to TRP.

[0163] In some embodiments, the minimum number of information units N1 reported in the present application can also be referred to as the number of information units reported N1, and the present application does not limit this.

[0164] In some embodiments, the second information includes the signal measurement information and the location-related information. In this case, at least one of the following can be performed based on the signal measurement information and the location-related information:

[0165] Monitor or determine the effectiveness of the AI ​​model used to achieve the positioning function;

[0166] Monitor or determine the inference performance of the AI ​​model used to achieve positioning functionality;

[0167] Monitor or determine the inference accuracy of the AI ​​model used to achieve positioning functionality.

[0168] In this embodiment, a location tag can be associated with one quality information, or a location tag can be associated with multiple quality information; and / or, a location tag can be associated with one timestamp, or a location tag can be associated with multiple timestamps; and / or, multiple location tags can be associated with one timestamp, or multiple location tags can be associated with multiple timestamps.

[0169] In this embodiment, a measurement unit may be associated with one quality information, or a measurement unit may be associated with multiple quality information; and / or, a measurement unit may be associated with one timestamp, or a measurement unit may be associated with multiple timestamps; and / or, multiple measurement units may be associated with one timestamp, or multiple measurement units may be associated with multiple timestamps.

[0170] The signal measurement information described in this application embodiment can also be referred to as the first part of the data, and the location-related information described in this application embodiment can also be referred to as the second part of the data. This application embodiment does not limit this.

[0171] The AI ​​model described in this application embodiment may also be referred to as an AI unit, AI model / AI unit, machine learning (ML) model, ML unit, AI structure, AI function, AI characteristic, neural network, neural network function, neural network functionality, etc. Alternatively, the AI ​​model described in this application may also refer to a processing unit capable of implementing specific algorithms, formulas, processing flows, capabilities, etc. related to AI. Alternatively, the AI ​​model described in this application may be a processing method, algorithm, function, module, or unit for a specific dataset. Alternatively, the AI ​​model described in this application may be a processing method, algorithm, function, module, or unit running on AI / ML related hardware such as a graphics processing unit (GPU), neural processing unit (NPU), tensor processing unit (TPU), or application-specific integrated circuit (ASIC). This application does not specifically limit this. Optionally, the specific dataset includes data related to the AI ​​model input or data related to the AI ​​model output.

[0172] The identifier of the AI ​​model described in the embodiments of this application may be an AI unit identifier, an AI structure identifier, an AI parameter identifier, an AI algorithm identifier, or an identifier of a specific dataset associated with the AI ​​model described in this application, or an identifier of a specific scenario, environment, channel characteristics, or device related to the AI ​​model described in this application, or an identifier of a function, characteristic, capability, or module related to the AI ​​model described in this application. This application does not make any specific limitations on these.

[0173] In some embodiments, the first device is a terminal or an access network device; and / or, the second device is an access network device or a core network device. Optionally, the core network device can be an LMF (Local Multi-Functional Network) or other core network devices.

[0174] For example, the first device is a terminal, and the second device is an access network device or a core network device (such as an LMF).

[0175] For example, the first device is an access network device, and the second device is a core network device (such as an LMF).

[0176] For example, the first device is an access network device, and the second device is another access network device.

[0177] In some embodiments, the signal measurement information is acquired by the terminal, and the location-related information is acquired by the LMF; or, the signal measurement information is acquired by the access network device, and the location-related information is acquired by the LMF; or, the signal measurement information is acquired by the access network device, and the location-related information is acquired by the terminal.

[0178] In this embodiment of the application, channel information (such as delay information, power information, phase information, etc.) between the terminal and a TRP can be obtained through a measurement unit.

[0179] In some embodiments, the measuring unit is associated with at least one of the following:

[0180] The identifier of at least one reference signal resource, the identifier of at least one cell, the identifier of at least one reference signal, the identifier of at least one TRP, and the identifier of at least one set of reference signal resources.

[0181] In this embodiment, the measurement unit can be determined based on at least one of the following: the identifier of at least one reference signal resource, the identifier of at least one cell, the identifier of at least one reference signal, the identifier of at least one TRP, and the identifier of at least one reference signal resource set, thereby allowing for more flexible determination of the measurement unit.

[0182] For example, the measurement unit is associated with the identifier of at least one reference signal resource, including:

[0183] A measurement unit is obtained by measuring at least one reference signal resource.

[0184] For example, the measurement unit is associated with the identifier of at least one cell, including:

[0185] A measurement unit is obtained by measuring a reference signal associated with at least one cell.

[0186] For example, the measurement unit is associated with an identifier of at least one reference signal, including:

[0187] A measurement unit is obtained by measuring the reference signal of the TRP associated with at least one reference signal identifier.

[0188] For example, the measurement unit is associated with the identifier of at least one TRP, including:

[0189] A measurement unit is obtained by measuring a reference signal associated with at least one TRP.

[0190] For example, the measurement unit is associated with the identifier of at least one set of reference signal resources, including:

[0191] A measurement unit is obtained by measuring at least one set of reference signal resources.

[0192] For example, the first device measures a reference signal resource to obtain channel information (such as delay information, power information, phase information, etc.) between the terminal and a TRP.

[0193] The reference signals described in the embodiments of this application include, but are not limited to, at least one of the following:

[0194] Positioning reference signals (PRS), sounding reference signals (SRS), channel state information reference signals (CSI-RS), and synchronization signal blocks (SSB).

[0195] It should be noted that SSB can also be called synchronizationsignal / physical broadcast channel block (SS / PBCH block).

[0196] In some embodiments, the type of the information unit includes at least one of the following: channel sampling point, channel path.

[0197] For example, the several equally spaced channel sampling points and the two measured channel paths obtained by the first device (such as a terminal) can be as follows: Figure 5 As shown; where the sampling period T is related to the implementation of the first device (such as the terminal), it should not be less than the reciprocal of the bandwidth. For example, when the subcarrier spacing is 30kHz and the bandwidth is 100MHz, the sampling period T can be 1 / (30k*4096) seconds.

[0198] In the embodiments of this application, a measurement unit may be associated with one or more information units.

[0199] For example, signal measurement information can be as follows Figure 6 As shown, the signal measurement information includes information from S measurement units (such as time delay information, power information, phase information, etc.), and each measurement unit is associated with Z information units.

[0200] In the embodiments of this application, the information of each measurement unit (such as time delay information, power information, phase information, etc.) is determined based on the timing reporting granularity factor K2 and / or the reporting number N2 of information units; and / or, the number of information units associated with each measurement unit is determined based on the reporting number N2 of information units.

[0201] In some embodiments, the information unit described in this application can also be replaced with additional information units, wherein the additional information unit is an information unit other than the first channel path in terms of delay (e.g., the channel path with the minimum delay), or the additional information unit is an additional information unit other than the first channel sampling point in terms of delay (e.g., the channel sampling point with the minimum delay). Specifically, the first device determines the reporting quantity N2 of the additional information unit based on the minimum reporting quantity N1 of the additional information unit and / or the maximum reporting quantity N3 of the additional information unit and / or the maximum number of additional information units that the first device supports reporting. Specifically, a measurement unit contains N2+1 information units, such as the first channel path in terms of delay (e.g., the channel path with the minimum delay) or the first channel sampling point in terms of delay (e.g., the channel sampling point with the minimum delay), and an additional N2 paths or an additional N2 channel sampling points.

[0202] In some implementations, both the channel path and the channel sampling point described in this application embodiment may be called the channel path, but the methods for determining the channel path may differ. For example, the channel path described in this application embodiment is a path determined by a first method, while the channel sampling point described in this application embodiment is a path determined by a second method. Optionally, in this case, the first device reports not the type of information element, but the method for determining the information element.

[0203] In this application embodiment, no distinction is made in the reported IE name; or in other words, the channel sampling point is also regarded as the channel path, but it differs from the existing method of determining the channel path.

[0204] In some implementations, if the information element type is a channel path or a channel sampling point:

[0205] Latency information: If the first device is a UE, one measurement unit includes DL-RSTD of N2 or N2+1 channel paths, reference time such as the first detected path in time, downlink subframe boundary, etc.; if the first device is an access network device, one measurement unit includes: UL-RTOA of N2 or N2+1 channel paths reported by the access network device.

[0206] Power information: If the first device is a UE, a measurement unit includes DL-PRS-RSRPP (DL PRS reference signal received path power) for N2 or N2+1 channel paths; if the first device is an access network device, a measurement unit includes UL-SRS-RSRPP (UL SRS reference signal received path power) for N2 or N2+1 channel paths.

[0207] Phase information: If the first device is a UE, a measurement unit includes N2 or N2+1 channel paths of DL-RSCP (DL reference signal carrier phase (DL RSCP)) or DL-RSCPD (DL reference signal carrier phase difference (DL RSCPD)); or the DL-RSCP or DL-RSCPD of the first detected channel path in terms of delay; If the first device is an access network device, a measurement unit includes N2 or N2+1 channel paths of UL-RSCP or UL-RSCPD; or the UL-RSCP or UL-RSCPD of the first detected channel path in terms of delay.

[0208] In one scenario, a new IE is defined for the channel sampling point-based reporting method, which differs from the existing channel path-based reporting method.

[0209] In some implementations, if the type of the information element is a channel sampling point:

[0210] Latency information: If the first device is a UE, one measurement unit includes DL-RSTD with N2 or N2+1 channel sampling points, and the reference time includes at least one of the following: the first detected path in time, the first detected channel sampling point in time, and the downlink subframe boundary; if the first device is an access network device, one measurement unit includes: UL-RTOA with N2 or N2+1 channel sampling points reported by the access network device;

[0211] Power information: If the first device is a UE, a measurement unit includes N2 or N2+1 channel sampling points of DL-PRS-RSRSP (DL PRS reference signal received sample power); if the first device is an access network device, a measurement unit includes N2 or N2+1 channel sampling points of UL-SRS-RSRSP (UL SRS reference signal received sample power).

[0212] Phase information: If the first device is a UE, a measurement unit includes N2 or N2+1 channel sampling points of DL-RSCP (DL reference signal carrier phase (DL RSCP)) or DL-RSCPD (DL reference signal carrier phase difference (DL RSCPD)); or the DL-RSCP or DL-RSCPD of the first detected channel sampling point in terms of time delay; If the first device is an access network device, a measurement unit includes N2 or N2+1 channel sampling points of UL-RSCP or UL-RSCPD; or the UL-RSCP or UL-RSCPD of the first detected channel sampling point in terms of time delay.

[0213] In some embodiments, the signal measurement information may be associated with at least one of the following:

[0214] At least one area identifier, at least one cell list, at least one area identifier-cell list (AreaID-CellList), at least one TRP list, at least one positioning frequency layer, at least one cell identifier, at least one reference signal identifier, and at least one reference signal resource set identifier.

[0215] In this embodiment, signal measurement information can be determined based on at least one of the following: at least one area identifier, at least one cell list, at least one area identifier-cell list (AreaID-CellList), at least one TRP list, at least one positioning frequency layer, at least one cell identifier, at least one reference signal identifier, and at least one reference signal resource set identifier, thereby enabling more flexible determination of signal measurement information.

[0216] In some embodiments, the first information may be associated with at least one of the following:

[0217] At least one area identifier, at least one cell list, at least one area identifier-cell list (AreaID-CellList), at least one TRP list, at least one positioning frequency layer, at least one cell identifier, at least one reference signal identifier, and at least one reference signal resource set identifier.

[0218] In this embodiment, the scope of application of the configuration indicated by the first information can be determined based on at least one of the following: at least one area identifier, at least one cell list, at least one area identifier-cell list (AreaID-CellList), at least one TRP list, at least one positioning frequency layer, at least one cell identifier, at least one reference signal identifier, and at least one reference signal resource set identifier. For example, if a TRP is associated, the measurement reporting of all reference signal resources associated with that TRP will adopt the configuration or rules indicated by the first information, thereby allowing for more flexible determination of the first information.

[0219] The measurement unit described in this application embodiment may also be called or replaced by other names, such as signal measurement unit, information measurement unit, time domain information measurement unit, information measurement reporting unit, time domain channel measurement information, time domain channel measurement reporting information, time domain channel state information, etc., and this application embodiment does not limit it in this way.

[0220] The location label described in the embodiments of this application can also be referred to as or replaced by location coordinates.

[0221] In some embodiments, the first information further includes a maximum number N3 of information units to be reported;

[0222] Where N2 is less than or equal to N3, and N3 is a positive integer.

[0223] In some embodiments, the maximum number N3 of information units that can be reported can be agreed upon by the protocol.

[0224] For example, the signal measurement information obtained by the first device (such as a terminal) includes power information and time delay information of N2 equally spaced channel sampling points. Assume that at this time:

[0225] For example, if the timing reporting granularity factor K associated with the signal measurement information reported by the first device (such as a terminal) is 4, then the channel sampling points reported by the first device (such as a terminal) can be as follows: Figure 7 As shown.

[0226] For example, if the timing reporting granularity factor K associated with the signal measurement information reported by the first device (such as a terminal) is 5, then the timing granularity of the channel sampling points reported by the first device (such as the terminal) is 2. 5 ×T c =2T, the channel sampling points reported by the first device (such as the terminal) can be as follows Figure 8 As shown.

[0227] For example, if the timing reporting granularity factor K = 3 associated with the signal measurement information reported by the first device (such as a terminal), then the channel sampling points reported by the first device (such as a terminal) can be as follows: Figure 9 As shown.

[0228] It should be noted that the timing granularity of the channel sampling points is finer when the timing reporting granularity factor K=3. If the first device reports several channel sampling points with timing reporting granularity factor K=3, the second device can select several channel sampling points with timing reporting granularity factor K=4 from them.

[0229] For example, the larger the value of the timing reporting granularity factor k (e.g., when k=5), the coarser the timing granularity, and the more sensitive the channel sampling points reported by the first device (e.g., the terminal) are to timing deviations; for example, when k=5, there is no timing deviation. (The diagram shows...) Figure 10 As shown in the diagram, a timing deviation exists. Figure 11 As shown.

[0230] It should be noted that the larger the value of the timing reporting granularity factor k, the longer the time interval between adjacent channel sampling points. When there is a timing deviation, the difference between the reported channel sampling points and the actual channel sampling points is greater, which has a greater impact on the AI ​​positioning accuracy.

[0231] In some implementations, if the second device configures a timing reporting granularity factor k1 for the first device, and the first device believes that the timing deviation is large at this time, the first device can choose to use a timing reporting granularity factor smaller than k1 to reduce the impact of timing deviation on positioning performance.

[0232] In some embodiments, the wireless communication method 200 further includes:

[0233] The first device determines the timing reporting granularity factor K2 based on the timing reporting granularity factor K1; and / or,

[0234] The first device determines the reporting quantity N2 of the information unit based on the minimum reporting quantity N1 and / or the maximum reporting quantity N3 of the information unit.

[0235] For example, N2 is greater than or equal to N1, and / or N2 is less than or equal to N3.

[0236] In this embodiment, the first device can determine the timing reporting granularity factor K2 based on the timing reporting granularity factor K1, thereby more reasonably determining the timing reporting granularity factor K2; and / or, the first device can determine the reporting quantity N2 of the information unit based on the minimum reporting quantity N1 of the information unit and / or the maximum reporting quantity N3 of the information unit, thereby more reasonably determining the reporting quantity N2 of the information unit.

[0237] In some embodiments, the first information further includes at least one of the following: a candidate timing reporting granularity factor list and a candidate information unit reporting quantity list. Optionally, the candidate timing reporting granularity factor list includes at least one timing reporting granularity factor, and the first device can select a timing reporting granularity factor from the candidate timing reporting granularity factor list for reporting the measurement unit based on implementation. Optionally, the candidate information unit reporting quantity list includes at least one information unit reporting quantity, and the first device can select a reporting quantity of an information unit from the candidate information unit reporting quantity list for reporting the measurement unit based on implementation.

[0238] Optionally, the wireless communication method 200 further includes:

[0239] The first device determines the timing reporting granularity factor K2 based on the candidate timing reporting granularity factor list; and / or, the first device determines the reporting quantity N2 of the information unit based on the reporting quantity list of the candidate information units.

[0240] In this embodiment, the first device determines the timing reporting granularity factor K2 based on the candidate timing reporting granularity factor list, thereby more reasonably determining the timing reporting granularity factor K2; and / or, the first device determines the reporting quantity N2 of the information unit based on the reporting quantity list of the candidate information unit, thereby more reasonably determining the reporting quantity N2 of the information unit.

[0241] In this embodiment, the second device constrains the selection of the timing reporting granularity factor of the first device. If the second information is used for training the AI ​​model of the second device, it helps to reduce the training cost of the AI ​​model or improve the training accuracy of the AI ​​model. For example, it only needs to train an AI model separately or train an AI model together for a limited timing reporting granularity factor K2. If the second information is used for AI model inference of the second device (such as determining the location-related information of the terminal), it helps to adapt to the timing reporting granularity factor adapted to the AI ​​model of the second device, thereby improving the positioning accuracy of the AI ​​model.

[0242] In this embodiment, the selection of the number N2 of information units to be reported is constrained, which helps to ensure positioning accuracy or reduce reporting overhead.

[0243] In some embodiments, the wireless communication method 200 further includes:

[0244] The first device receives third information from the second device;

[0245] The third information includes, but is not limited to, at least one of the following:

[0246] The first indication information is used to indicate the timed reporting granularity factor K2;

[0247] The second instruction information is used to indicate the number N2 reported by the information unit;

[0248] The third instruction is used to instruct a reduction in the timing reporting granularity factor.

[0249] The fourth instruction is used to indicate the number of information units to be reported.

[0250] The fifth indication information is used to indicate the difference or ratio between the timed reporting granularity factor K2 and the timed reporting granularity factor K1;

[0251] The sixth indication information is used to indicate the difference or ratio between the reporting quantity N2 of the information unit and the minimum reporting quantity N1 of the information unit.

[0252] Optionally, when the third information includes the third indication information, the granularity or value of lowering the timing reporting granularity factor can be agreed upon by the protocol, or the granularity or value of lowering the timing reporting granularity factor can be implemented based on the first device, or the granularity or value of lowering the timing reporting granularity factor can be indicated by the second device.

[0253] In this embodiment, the second device instructs to lower the granularity or value of the timing reporting granularity factor, so that the second device can flexibly adjust the timing reporting granularity factor according to the current wireless environment, positioning accuracy, or the AI ​​model used, thereby improving the positioning accuracy of the AI ​​model.

[0254] Optionally, when the third information includes the fourth indication information, the value of the number of reports of the increased information unit can be agreed upon by the protocol, or the value of the number of reports of the increased information unit can be implemented based on the first device, or the value of the number of reports of the increased information unit can be indicated by the second device.

[0255] In this embodiment, the second device instructs to increase the number of information units reported, so that the second device can flexibly adjust the number of information units reported according to the current wireless environment, positioning accuracy, or the AI ​​model used, thereby improving the positioning accuracy of the AI ​​model.

[0256] It should be noted that after lowering the granularity factor of the timed reporting, the number of information units reported needs to be increased; otherwise, the positioning accuracy of the AI ​​model may be impaired.

[0257] For example, if the second device is pre-configured with multiple timed reporting granularity factors, the first device reports a timed reporting granularity factor smaller than the current timed reporting granularity factor. For instance, if the second device is configured with the following timed reporting granularity factors {0, 1, 2, 3, 4, 5}, and the current timed reporting granularity factor is 4, after receiving the third indication information, the first device adjusts the timed reporting granularity factor to 0, 1, 2, or 3.

[0258] For example, if the second device is pre-configured with multiple reporting quantities of information units, the first device reports a larger number of information units than the current reporting quantity. For instance, if the second device is configured with the following reporting quantities of information units {8, 16, 32}, and the current reporting quantity of information units is 8, after receiving the fourth indication information, the first device adjusts the reporting quantity of information units to 16 or 32.

[0259] In some implementations, if the first device reports channel measurement information according to a certain time-reported granularity factor k value, and the second device believes that the positioning accuracy is low because the time-reported granularity factor k value is too large, it can instruct the first device to lower the time-reported granularity factor k value.

[0260] In some embodiments, the wireless communication method 200 further includes:

[0261] The first device determines the minimum reporting quantity N1 of the information unit based on the timed reporting granularity factor K1 and the first correlation relationship; or, the first device determines the timed reporting granularity factor K1 based on the minimum reporting quantity N1 of the information unit and the first correlation relationship; wherein, the first correlation relationship is the correlation between the timed reporting granularity factor and the minimum reporting quantity of the information unit.

[0262] In this embodiment, the timed reporting granularity factor K1 is associated with the minimum reporting quantity N1 of the information unit, thereby reducing the signaling overhead of the second device instructing the timed reporting granularity factor K1 or the minimum reporting quantity N1 of the information unit, and ensuring the positioning accuracy of the AI ​​model-based positioning function.

[0263] For example, k1 = 5, N1 = 8; k1 = 4, N1 = 16; k1 = 3, N1 = 24. The purpose of this embodiment is to ensure that the time range of the channel sampling point reported by the first device, or the time range of the measurement window or timing window, does not decrease due to the decrease of the k value.

[0264] Optionally, in the first association relationship, a timed reporting granularity factor is associated with the minimum reporting quantity of one information unit, or a timed reporting granularity factor is associated with the minimum reporting quantity of at least two information units, or at least two timed reporting granularity factors are associated with the minimum reporting quantity of one information unit.

[0265] Optionally, the first association relationship can be agreed upon by a protocol, or the first association relationship can be configured by the network side.

[0266] In some embodiments, the wireless communication method 200 further includes:

[0267] The first device determines the reporting quantity N2 of the information unit based on the timed reporting granularity factor K2 and the second correlation relationship; or, the first device determines the timed reporting granularity factor K2 based on the reporting quantity N2 of the information unit and the second correlation relationship; wherein, the second correlation relationship is the correlation between the timed reporting granularity factor and the reporting quantity of the information unit.

[0268] In this embodiment, the timed reporting granularity factor K2 is associated with the number of information units reported N2, thereby reducing the signaling overhead of the first device in reporting the timed reporting granularity factor K2 or the number of information units reported N2, and ensuring the positioning accuracy of the AI ​​model-based positioning function.

[0269] For example, k2 = 5, N2 = 8; k2 = 4, N2 = 16; k2 = 3, N2 = 24. The purpose of this embodiment is to ensure that the time range of the channel sampling point reported by the first device, or the time range of the measurement window or timing window, does not decrease due to the decrease of the k value.

[0270] Optionally, in the second association, a timed reporting granularity factor is associated with the reporting quantity of one information unit, or a timed reporting granularity factor is associated with the reporting quantity of at least two information units, or at least two timed reporting granularity factors are associated with the reporting quantity of one information unit.

[0271] Optionally, the second association relationship can be agreed upon by a protocol, or the second association relationship can be configured by the network side.

[0272] For example, if the timing reporting granularity factor K2 associated with the signal measurement information reported by the first device (such as a terminal) is 4, in this case, to ensure the power of the reported channel sampling points, the channel sampling points reported by the first device (such as a terminal) can be as follows: Figure 12 As shown.

[0273] For example, if the timing reporting granularity factor K2 associated with the signal measurement information reported by the first device (such as a terminal) is 3, in this case, to ensure the power of the reported channel sampling points, the channel sampling points reported by the first device (such as a terminal) can be as follows: Figure 13 As shown.

[0274] For example, if the timing reporting granularity factor K2 associated with the signal measurement information reported by the first device (such as a terminal) is 4, in this case, to ensure the delay of the reported channel sampling points, the channel sampling points with the smallest delay among the first N2 = 8 are selected. The channel sampling points reported by the first device (such as a terminal) can be as follows: Figure 14 As shown.

[0275] In some embodiments, the first information further includes, but is not limited to, at least one of the following:

[0276] The seventh indication information is used to indicate the first time interval;

[0277] The eighth indication information is used to indicate the first distance;

[0278] The ninth instruction is used to indicate the second time interval;

[0279] The tenth indication information is used to indicate the second distance;

[0280] The eleventh instruction message is used to indicate the first measurement window;

[0281] The twelfth instruction is used to indicate the second measurement window.

[0282] Optionally, the time interval between the timestamp associated with the signal measurement information and the timestamp associated with the location-related information is less than the first time interval, or the time interval between the timestamp associated with the signal measurement information and the timestamp associated with the location-related information is less than or equal to the first time interval.

[0283] Optionally, the first time interval includes at least one time unit, wherein the time unit includes at least one of the following: Orthogonal frequency-division multiplexing (OFDM) symbol, time slot, subframe, half-frame, frame, second, millisecond, microsecond.

[0284] For example, the first time interval can be 1 slot, 5 slots, or 10 slots.

[0285] It should be noted that if the time interval between the timestamp associated with the signal measurement information and the timestamp associated with the location-related information is less than or equal to the first time interval, the signal measurement information and the location-related information can be considered associated, such as if they belong to the same data sample, or if they were obtained from the same or similar locations. For example, a single Information Elements (IEs) can contain both signal measurement information and its associated location-related information; or, the signal measurement information and the location-related information can be associated with the same data identifier (ID); such as IE1{Signal Measurement Information; Location-Related Information; Other Information}.

[0286] In this embodiment, after acquiring the first time interval, the terminal can determine the signal measurement information and its associated location-related information based on the first time interval. The signal measurement information and the location-related information belong to the same data sample, or the signal measurement information and the location-related information are obtained from the same or similar locations, thereby improving model performance when training the AI ​​model, or ensuring the reliability of the AI ​​model's inference results during AI model supervision.

[0287] Optionally, the distance between the location where the signal measurement information is acquired and the location where the location-related information is acquired is less than the first distance, or the distance between the location where the signal measurement information is acquired and the location where the location-related information is acquired is less than or equal to the first distance.

[0288] It should be noted that if the distance between the location where the signal measurement information is acquired and the location-related information is acquired is less than or equal to a first distance, the signal measurement information and the location-related information can be considered associated. This includes situations where the signal measurement information and the location-related information belong to the same data sample, or where they are obtained from the same or nearby locations. For example, an IE can simultaneously contain signal measurement information and its associated location-related information; or, the signal measurement information and the location-related information can be associated with the same data ID; such as IE1{Signal Measurement Information; Location-Related Information; Other Information}.

[0289] For example, the first distance can be 1m, 5m, or 10m.

[0290] In this embodiment, after acquiring the first distance, the terminal can determine the signal measurement information and its associated location-related information based on the first distance. The signal measurement information and the location-related information belong to the same data sample, or the signal measurement information and the location-related information are obtained at the same or similar locations, thereby improving model performance when training the AI ​​model, or ensuring the reliability of the AI ​​model's inference results during AI model supervision.

[0291] Optionally, if the time interval between the timestamps associated with at least two acquired signal measurement information is less than the second time interval, or if the time interval between the timestamps associated with at least two acquired signal measurement information is less than or equal to the second time interval, the at least two acquired signal measurement information belongs to the same data sample, or the at least two acquired signal measurement information is associated with the same data sample, or the at least two acquired signal measurement information was acquired at the same or similar locations; and / or, if the time interval between the timestamps associated with at least two acquired location-related information is less than the second time interval, or if the time interval between the timestamps associated with at least two acquired location-related information is less than or equal to the second time interval, the at least two acquired location-related information belongs to the same data sample, or the at least two acquired location-related information is associated with the same data sample, or the at least two acquired location-related information was acquired at the same or similar locations.

[0292] Optionally, if the number of times signal measurement information is acquired is U1, and U1 is an integer greater than 2, then the time interval between the timestamps associated with the at least U1 acquired signal measurement information can be the maximum time interval between the timestamps associated with the at least U1 acquired signal measurement information.

[0293] Optionally, if the number of times location-related information is obtained is U2, and U2 is an integer greater than 2, then the time interval between the timestamps associated with the location-related information obtained at least U2 times can be the maximum time interval between the timestamps associated with the location-related information obtained at least U2 times.

[0294] In this embodiment, after acquiring the second time interval, the terminal can determine at least two acquired signal measurement information based on the second time interval. The at least two acquired signal measurement information belong to the same data sample, or the at least two acquired signal measurement information are associated with the same data sample, or the at least two acquired signal measurement information are acquired at the same or similar locations. This can improve the performance of the AI ​​model during training or ensure the reliability of the inference results of the AI ​​model during AI model supervision.

[0295] In this embodiment, after acquiring the second time interval, the terminal can determine the location-related information acquired at least twice based on the second time interval. The location-related information acquired at least twice belongs to the same data sample, or the location-related information acquired at least twice is associated with the same data sample, or the location-related information acquired at least twice is acquired at the same or similar locations. This can improve the performance of the AI ​​model during training or ensure the reliability of the inference results of the AI ​​model during AI model supervision.

[0296] The timestamp associated with the signal measurement information described in this embodiment can be understood as the acquisition time or measurement time of the signal measurement information. Similarly, the timestamp associated with the location-related information described in this embodiment can be understood as the acquisition time or measurement time of the location-related information.

[0297] Optionally, the second time interval includes at least one time unit, wherein the time unit includes at least one of the following: symbol, time slot, subframe, half-frame, frame, second, millisecond, microsecond.

[0298] For example, the second time interval can be 1 slot, 5 slots, or 10 slots.

[0299] Optionally, if the distance between the acquisition locations of at least two acquired signal measurement information is less than the second distance, or if the distance between the acquisition locations of at least two acquired signal measurement information is less than or equal to the second distance, the at least two acquired signal measurement information belongs to the same data sample, or the at least two acquired signal measurement information is associated with the same data sample, or the at least two acquired signal measurement information was acquired at the same or similar locations; and / or, if the distance between the acquisition locations of at least two acquired location-related information is less than the second distance, or if the distance between the acquisition locations of at least two acquired location-related information is less than or equal to the second distance, the at least two acquired location-related information belongs to the same data sample, or the at least two acquired location-related information is associated with the same data sample, or the at least two acquired location-related information was acquired at the same or similar locations.

[0300] In this embodiment, after acquiring the second distance, the terminal can determine the signal measurement information acquired at least twice based on the second distance. The signal measurement information acquired at least twice belongs to the same data sample, or the signal measurement information acquired at least twice is associated with the same data sample, or the signal measurement information acquired at least twice is acquired at the same or similar locations. This can improve the performance of the AI ​​model when training it, or ensure the reliability of the inference results of the AI ​​model when supervising it.

[0301] In this embodiment, after obtaining the second distance, the terminal can determine the location-related information obtained at least twice based on the second distance. The location-related information obtained at least twice belongs to the same data sample, or the location-related information obtained at least twice is associated with the same data sample, or the location-related information obtained at least twice is obtained at the same or similar locations. This can improve the performance of the AI ​​model when training it, or ensure the reliability of the inference results of the AI ​​model when supervising it.

[0302] For example, the second distance can be 1m, 5m, or 10m.

[0303] Optionally, the signal measurement information and the location-related information are acquired within the same first measurement window.

[0304] In this embodiment, after acquiring the first measurement window, the terminal can determine the signal measurement information and its associated location-related information based on the first measurement window. The signal measurement information and the location-related information belong to the same data sample, or the signal measurement information and the location-related information are obtained at the same or similar locations, thereby improving model performance when training the AI ​​model, or ensuring the reliability of the AI ​​model's inference results during AI model supervision.

[0305] Optionally, if the signal measurement information acquired at least twice is acquired within the second measurement window, the signal measurement information acquired at least twice belongs to the same data sample, or the signal measurement information acquired at least twice is associated with the same data sample, or the signal measurement information acquired at least twice is acquired at the same or similar locations; and / or, if the location-related information acquired at least twice is acquired within the second measurement window, the location-related information acquired at least twice belongs to the same data sample, or the location-related information acquired at least twice is associated with the same data sample, or the location-related information acquired at least twice is acquired at the same or similar locations.

[0306] In this embodiment, after acquiring the second measurement window, the terminal can determine the signal measurement information acquired at least twice based on the second measurement window. The signal measurement information acquired at least twice belongs to the same data sample, or the signal measurement information acquired at least twice is associated with the same data sample, or the signal measurement information acquired at least twice is acquired at the same or similar locations. This can improve the performance of the AI ​​model during training or ensure the reliability of the inference results of the AI ​​model during AI model supervision.

[0307] In this embodiment, after acquiring the second measurement window, the terminal can determine the location-related information acquired at least twice based on the second measurement window. The location-related information acquired at least twice belongs to the same data sample, or the location-related information acquired at least twice is associated with the same data sample, or the location-related information acquired at least twice is acquired at the same or similar locations. This can improve the performance of the AI ​​model during training or ensure the reliability of the inference results of the AI ​​model during AI model supervision.

[0308] For example, such as Figure 15As shown, multiple measurement units acquire data in the m-th time slot, and location-related information is acquired in the m+t-th time slot. If t+1 is less than or equal to the length of the indicated first measurement window (acquired within the duration of the first measurement window), then the three measurement units and the location-related information are associated with the same data sample.

[0309] For example, such as Figure 16 As shown, multiple measurement units acquire data in the m-th and m+t-th time slots, and location-related information is acquired in the m+t+s-th time slot. If t+s+1 is less than or equal to the length of the indicated first measurement window (acquired within the duration of the first measurement window), then the four measurement units and the location-related information are associated with the same data sample.

[0310] For example, such as Figure 17 As shown, multiple measurement units acquire data in different time slots. If t+1 is less than or equal to the length of the indicated second measurement window (acquired within the duration of the second measurement window), then the multiple measurement units can be considered to be associated with the same data sample.

[0311] For example, such as Figure 18 As shown, the three measurement units obtain the data in the m-th time slot, and the location-related information is obtained in the m+t-th time slot. If t is less than or equal to the length of the indicated first time interval, then the three measurement units and the location-related information are associated with the same data sample.

[0312] In one scenario, there is no need to distinguish between the first and second measurement windows. Measurement units or location-related information located within a measurement window are associated with the same data sample or are considered to have been obtained from the same or similar locations.

[0313] Optionally, the first time interval shown can also be agreed upon by the protocol.

[0314] Optionally, the second time interval shown can also be agreed upon by the protocol.

[0315] Optionally, the first distance shown can also be agreed upon by the protocol.

[0316] Optionally, the second distance shown can also be agreed upon by the protocol.

[0317] In some embodiments, when the first information is used to request the signal measurement information and the location-related information, the first information includes, but is not limited to, at least one of the following:

[0318] The seventh indication information is used to indicate the first time interval;

[0319] The eighth indication information is used to indicate the first distance;

[0320] The ninth instruction is used to indicate the second time interval;

[0321] The tenth indication information is used to indicate the second distance;

[0322] The eleventh instruction message is used to indicate the first measurement window;

[0323] The twelfth instruction is used to indicate the second measurement window.

[0324] In some embodiments, the signal measurement information and the location-related information may be acquired by the same device, or they may be acquired by different devices.

[0325] In some implementations, both the signal measurement information and the location-related information are acquired by the terminal; or, the signal measurement information is acquired by the terminal and the location-related information is acquired by the LMF; or, the signal measurement information is acquired by the access network device and the location-related information is acquired by the LMF; or, the signal measurement information is acquired by the access network device and the location-related information is acquired by the terminal.

[0326] For example, such as Figure 19 As shown, UE1 obtains signal measurement information at location 1 and timestamp 1. After moving from location 1 to location 2, UE1 obtains location-related information at location 2 and timestamp 2.

[0327] In some embodiments, the wireless communication method 200 further includes:

[0328] The first device determines the information unit associated with each measurement unit in the at least one measurement unit based on a first power threshold;

[0329] Wherein, the power of the information unit associated with each measurement unit in the at least one measurement unit is greater than the first power threshold, or the power of the information unit associated with each measurement unit in the at least one measurement unit is greater than or equal to the first power threshold.

[0330] In this embodiment, the first device determines the information units associated with each measurement unit in at least one measurement unit based on a first power threshold, thereby filtering out information units with power greater than or equal to the first power threshold and discarding some invalid information units, which can reduce reporting overhead.

[0331] In some embodiments, the first power threshold is determined based on at least one of the following: the reference signal received power (RSRP) measured on the same reference signal resource, the power of the information unit with the smallest delay, and the power of the information unit with the largest power.

[0332] Optionally, the first power threshold is 1 / R or R times the RSRP measured on the same reference signal resource; or, the first power threshold is 1 / R or R times the power of the information unit with the smallest delay; or, the first power threshold is 1 / R or R times the power of the information unit with the largest power; where R is a positive number.

[0333] Optionally, R can be defined by a protocol, or R can be configured by the network side.

[0334] In some embodiments, the first power threshold is configured by the network side, or the first power threshold is agreed upon by the protocol.

[0335] In some embodiments, the wireless communication method 200 further includes:

[0336] The first device determines the time delay information of the at least one measurement unit based on a reference time; wherein, the time delay information of the at least one measurement unit includes the difference between the time delay of the at least one measurement unit and the reference time.

[0337] In this embodiment, the first device determines the delay information of at least one measurement unit based on the reference time, which can reduce the reporting overhead.

[0338] In some embodiments, the reference time is the timing information or delay information of the information unit with the smallest delay associated with the reference TRP; or, the reference time is the timing information or delay information of the information unit with the smallest delay associated with the reference cell; or, the reference time is the downlink subframe boundary of the reference TRP; or, the reference time is the downlink subframe boundary of the reference cell; or, the reference time is configured by the network side; or, the reference time is agreed upon by the protocol.

[0339] In this embodiment, the first device determines the delay information of at least one measurement unit based on a reference time. The reference time is the timing information or delay information of the information unit with the smallest delay associated with the reference TRP, or the timing information or delay information of the information unit with the smallest delay associated with the reference cell, or the downlink subframe boundary of the reference TRP, or the downlink subframe boundary of the reference cell, thereby reducing the complexity of data processing for the second device.

[0340] In some embodiments, before the first device receives the first information from the second device, the wireless communication method 200 further includes:

[0341] The first device sends capability information to the second device;

[0342] The capability information is used to indicate at least one of the following:

[0343] The first device supports the reporting of various information unit types;

[0344] The maximum number of information units that can be reported by a measurement unit associated with the first device;

[0345] The first device supports at least one timing reporting granularity factor in channel sampling point-based reporting;

[0346] The first device supports at least one timing reporting granularity factor in channel path-based reporting.

[0347] Optionally, the maximum number of information units reported by a measurement unit associated with the first device is related to the bandwidth of the reference signal associated with that measurement unit.

[0348] In this embodiment, the first device sends capability information to the second device, so that the second device can determine the first information based on the capability information.

[0349] In some embodiments, where the first device supports reporting information units of the types of channel sampling points and channel paths, the signal measurement information includes thirteenth indication information, wherein the thirteenth indication information is used to indicate the type of information unit associated with the at least one measurement unit. Thus, the second device can determine the type of information unit reported by the first device based on the thirteenth indication information.

[0350] In some embodiments, when the type of information unit to be reported by the first device is a channel sampling point or a channel path, the type of information unit associated with the at least one measurement unit defaults to the type of information unit to be reported by the first device. Therefore, the second device can determine, based on default rules, that the type of information unit reported by the first device is the type of information unit to be reported by the first device.

[0351] In some embodiments, the protocol specifies that the type of information unit reported by the first device can be determined based on an information field that determines whether the measurement units reported by the first device include delay information of the first information unit in terms of delay; or, the protocol specifies that the type of information unit reported by the first device can be determined based on an information field that determines whether the measurement units reported by the first device include a list of additional information units. Therefore, the second device can determine the type of information unit reported by the first device based on the protocol-defined information.

[0352] Optionally, if the measurement unit reported by the first device does not include an information field containing the delay information of the first information unit, or if the measurement unit reported by the first device does not include an information field containing a list of additional information units, the type of the information unit associated with the at least one measurement unit is a channel sampling point.

[0353] Optionally, if the measurement unit reported by the first device includes an information field containing delay information of the first information unit, or if the measurement unit reported by the first device includes an information field containing a list of additional information units, the type of the information unit associated with the at least one measurement unit is a channel path.

[0354] The type of information unit described in the embodiments of this application can also be referred to as or replaced by the type of measurement unit. For example, if the type of measurement unit is a channel sampling point, then the information units or additional information units (except for the first information unit in time) included in the measurement unit are all channel sampling points.

[0355] The type of information unit described in the embodiments of this application can also be referred to as or replaced by the type of signal measurement information. For example, if the type of signal measurement information is a channel sampling point, then the information units or additional information units (except for the first information unit in time) included in the signal measurement unit are all channel sampling points.

[0356] Optionally, the capability information is also used to indicate at least one of the following:

[0357] The first device supports the reporting of measurement unit types;

[0358] The first device supports the reporting of various types of signal measurement information.

[0359] In this embodiment, a first device receives first information from a second device; wherein the first information is used to indicate at least one of the following: a timed reporting granularity factor K1, and a minimum reporting quantity N1 of information units; the first device sends second information to the second device; wherein the second information is used to perform AI model-based positioning function, and the second information includes at least one of the following: signal measurement information, and location-related information; wherein the signal measurement information includes at least one of the following: information of at least one measurement unit, quality information of at least one measurement unit, a timestamp associated with at least one measurement unit, and a first identifier associated with at least one measurement unit; the location-related information includes at least one of the following: a location tag, quality information of the location tag, and a timestamp associated with the location tag; wherein at least one measurement unit is determined based on a timed reporting granularity factor K2 and / or a reporting quantity N2 of information units, where K2 is less than or equal to K1, and N2 is greater than or equal to N1; wherein the first identifier is associated with network environment information on the RAN side. Specifically, the first device can determine at least one measurement unit based on the timed reporting granularity factor K2 and / or the number of information units reported N2. By restricting K2 to be less than or equal to K1 and N2 to be greater than or equal to N1, the granularity of the delay information of the information units contained in each reported measurement unit and the number of information units contained therein meet the requirements of the AI ​​positioning model on the network side, thereby improving the positioning accuracy of the AI ​​model-based positioning function. For example, the smaller the timed reporting granularity factor K2, the smaller the granularity of the delay information of the information units, the higher the degree of freedom provided to the network side, and the higher the positioning accuracy of the AI ​​model-based positioning function based on the second information; and / or, the larger the number of information units reported N2, the more information units there are, and the higher the positioning accuracy of the AI ​​model-based positioning function based on the second information.

[0360] The technical solution of this application is described below through specific embodiments.

[0361] Example 1, taking the first device as the terminal and the second device as an LMF as an example, such as... Figure 20 As shown, Embodiment 1 may specifically include some or all of S1-1 to S1-4.

[0362] S1-1. The terminal sends capability information to the LMF;

[0363] The capability information is used to indicate at least one of the following:

[0364] The terminal supports the reporting of various information unit types;

[0365] The terminal supports the maximum number of information units that can be reported by a measurement unit associated with it.

[0366] The terminal supports at least one timing reporting granularity factor in channel sampling point-based reporting;

[0367] The terminal supports at least one timing reporting granularity factor in channel path-based reporting.

[0368] The information unit type includes at least one of the following: channel sampling point, channel path.

[0369] Optionally, the maximum number of information units reported by a measurement unit associated with the terminal is related to the bandwidth of the reference signal associated with that measurement unit.

[0370] The type of information unit described in this embodiment can also be referred to as or replaced by the type of measurement unit. For example, if the type of measurement unit is a channel sampling point, then the information units or additional information units included in the measurement unit are all channel sampling points.

[0371] The type of information unit described in this embodiment can also be referred to as or replaced by the type of signal measurement information. For example, if the type of signal measurement information is a channel sampling point, then the information units or additional information units (except for the first information unit in time) included in the signal measurement unit are all channel sampling points.

[0372] Optionally, the capability information is also used to indicate at least one of the following:

[0373] The terminal supports the reporting of various types of measurement units;

[0374] The terminal supports the reporting of various types of signal measurement information.

[0375] Optionally, S1-1 can also be as follows: Figure 21 Step 1 is shown.

[0376] S1-2. The LMF sends first information to the terminal, wherein the first information is used to indicate at least one of the following: periodically reporting granularity factor K1, and the minimum reporting number N1 of information units; wherein K1 is an integer and N1 is a positive integer.

[0377] Optionally, the first information can be carried by an LTE positioning protocol (LPP) message. For example, the LPP message can carry LPP Provide Assistance Data or LPP Request Location Information.

[0378] Optionally, S1-2 can also be as follows: Figure 21 Step 7 or step 8 are shown.

[0379] S1-3. The terminal performs downlink positioning reference signal (DL-PRS) measurement to obtain signal measurement information and / or location-related information; wherein, the signal measurement information includes at least one of the following: information of at least one measurement unit, quality information of the at least one measurement unit, timestamp associated with the at least one measurement unit, and a first identifier associated with the at least one measurement unit; the location-related information includes at least one of the following: location tag, quality information of the location tag, and timestamp associated with the location tag; wherein, the information of the measurement unit includes at least one of the following: delay information, power information, and phase information; wherein, the at least one measurement unit is determined based on the timing reporting granularity factor K2 and / or the reporting quantity N2 of information units, where K2 is less than or equal to K1, N2 is greater than or equal to N1, K2 is an integer, and N2 is a positive integer; wherein, the first identifier is associated with the network environment information on the RAN side.

[0380] Optionally, S1-3 can also be as follows: Figure 21 Step 9a is shown.

[0381] S1-4. The terminal sends second information to the LMF, wherein the second information is used for positioning based on the AI ​​model, and the second information includes at least one of the following: the signal measurement information, the location-related information.

[0382] Optionally, the second information can be carried by an LPP message. For example, an LPP message can carry LPP Provide Location Information.

[0383] Optionally, S1-4 can also be as follows: Figure 21 Step 10 is shown.

[0384] Example 2, taking gNB as the first device and LMF as the second device as an example, such as Figure 22 As shown, Embodiment 2 may specifically include some or all of S2-1 to S2-4.

[0385] S2-1.gNB sends configuration information to LMF;

[0386] The configuration information includes at least one of the following:

[0387] gNB supports the reporting of information unit types;

[0388] The maximum number of information units that can be reported by a measurement unit associated with a gNB;

[0389] gNB supports at least one timing reporting granularity factor in channel sampling point-based reporting;

[0390] gNB supports at least one timing reporting granularity factor in channel path-based reporting;

[0391] The information unit type includes at least one of the following: channel sampling point, channel path.

[0392] Optionally, the maximum number of information units reported by a measurement unit associated with the gNB is related to the bandwidth of the reference signal associated with that measurement unit.

[0393] The type of information unit described in this embodiment can also be referred to as or replaced by the type of measurement unit. For example, if the type of measurement unit is a channel sampling point, then the information units or additional information units included in the measurement unit are all channel sampling points.

[0394] The type of information unit described in this embodiment can also be referred to as or replaced by the type of signal measurement information. For example, if the type of signal measurement information is a channel sampling point, then the information units or additional information units (except for the first information unit in time) included in the signal measurement unit are all channel sampling points.

[0395] Optionally, the capability information is also used to indicate at least one of the following:

[0396] gNB supports the reporting of measurement unit types;

[0397] gNB supports the reporting of various types of signal measurement information.

[0398] Optionally, S2-1 can also be as follows: Figure 23 Step 1 is shown.

[0399] S2-2. The LMF sends a first message to the gNB, wherein the first message is used to indicate at least one of the following: periodically reporting granularity factor K1, and the minimum reporting number N1 of information units; wherein K1 is an integer and N1 is a positive integer.

[0400] Optionally, the first information can be carried by an NR positioning protocol a (NRPPa) message. For example, the NRPPa message can be carried by an NRPPa measurement request.

[0401] Optionally, S2-2 can also be as follows: Figure 23 Step 6 is shown.

[0402] The S2-3.gNB performs uplink probe reference signal (UL-SRS) measurements to obtain signal measurement information and / or location-related information. The signal measurement information includes at least one of the following: information of at least one measurement unit, quality information of at least one measurement unit, a timestamp associated with at least one measurement unit, and a first identifier associated with at least one measurement unit. The location-related information includes at least one of the following: a location tag, quality information of the location tag, and a timestamp associated with the location tag. At least one measurement unit is determined based on a timing reporting granularity factor K2 and / or the number of information units reported N2, where K2 is less than or equal to K1, and N2 is greater than or equal to N1. The first identifier is associated with network environment information on the RAN side.

[0403] Optionally, S2-3 can also be as follows: Figure 23 Step 7 is shown.

[0404] S2-4.gNB sends a second message to LMF, wherein the second message is used for AI model-based positioning function, and the second message includes at least one of the following: the signal measurement information, the location-related information.

[0405] Optionally, the second information can be carried by an NRPPa message. For example, an NRPPa message can be carried by an NRPPa measurement response.

[0406] Optionally, S2-4 can also be as follows: Figure 23 Step 8 is shown.

[0407] The wireless communication method provided in this application can be executed by a wireless communication device. This application uses an example of a wireless communication device executing the wireless communication method to illustrate the wireless communication device provided in this application.

[0408] This application provides a wireless communication device. As an example, the wireless communication device may be a communication equipment or a component within a communication equipment, such as a chip. The communication equipment may be a terminal, a network-side device, or a server, etc. Exemplarily, the terminal may include, but is not limited to, the type of terminal 11 listed above, and the network-side device may include, but is not limited to, the type of network-side device 12 listed above. This application does not impose specific limitations.

[0409] The wireless communication device includes a receiving module, a transmitting module, and a processing module. These modules can be implemented in software or hardware. When implemented in hardware, the processing module can be implemented by a processor. For example, the processor can include general-purpose processors, special-purpose processors, such as a Central Processing Unit (CPU), microprocessor, Digital Signal Processor (DSP), Artificial Intelligence (AI) processor, Graphics Processing Unit (GPU), Application Specific Integrated Circuit (ASIC), Network Processor (NP), Field Programmable Gate Array (FPGA), or other programmable logic devices, gate circuits, transistors, discrete hardware components, etc. The receiving and transmitting modules can be implemented by a communication interface, which can include one or more of the following: transceiver, pins, circuits, bus, radio frequency unit, etc.

[0410] For details, see Figure 24 When the wireless communication device is the first device or a component of the first device, the wireless communication device 300 includes:

[0411] The receiving module 301 is configured to receive first information from the second device; wherein the first information is configured to indicate at least one of the following: a granularity factor K1 for periodic reporting, and a minimum reporting quantity N1 for information units; wherein K1 is an integer and N1 is a positive integer;

[0412] The sending module 302 is used to send second information to the second device; wherein the second information is used for positioning function based on artificial intelligence AI model, and the second information includes at least one of the following: signal measurement information, location-related information;

[0413] The signal measurement information includes at least one of the following: information of at least one measurement unit, quality information of the at least one measurement unit, timestamp associated with the at least one measurement unit, and first identifier associated with the at least one measurement unit; the location-related information includes at least one of the following: location tag, quality information of the location tag, and timestamp associated with the location tag;

[0414] The information of the measurement unit includes at least one of the following: time delay information, power information, and phase information;

[0415] The at least one measurement unit is determined based on the number of timed reporting granularity factor K2 and / or information unit reporting N2, where K2 is less than or equal to K1, N2 is greater than or equal to N1, K2 is an integer, and N2 is a positive integer.

[0416] The first identifier is associated with the network environment information on the Radio Access Network (RAN) side.

[0417] In some embodiments, the first information further includes a maximum number N3 of information units to be reported;

[0418] Where N2 is less than or equal to N3, and N3 is a positive integer.

[0419] In some embodiments, the wireless communication device 300 further includes: a processing module 303;

[0420] The processing module 303 is used to determine the timed reporting granularity factor K2 based on the timed reporting granularity factor K1; and / or, the processing module 303 is used to determine the reporting quantity N2 of the information unit based on the minimum reporting quantity N1 of the information unit and / or the maximum reporting quantity N3 of the information unit.

[0421] In some embodiments, the first information further includes at least one of the following: a list of candidate timing reporting granularity factors, and a list of reporting quantities of candidate information units;

[0422] The wireless communication device 300 further includes: a processing module 303;

[0423] The processing module 303 is used to determine the timing reporting granularity factor K2 according to the candidate timing reporting granularity factor list; and / or, the processing module 303 is used to determine the reporting quantity N2 of the information unit according to the reporting quantity list of the candidate information units.

[0424] In some embodiments, the receiving module 301 is further configured to receive third information from the second device;

[0425] The third information includes at least one of the following:

[0426] The first indication information is used to indicate the timed reporting granularity factor K2;

[0427] The second instruction information is used to indicate the number N2 reported by the information unit;

[0428] The third instruction is used to instruct a reduction in the timing reporting granularity factor.

[0429] The fourth instruction is used to indicate the number of information units to be reported.

[0430] The fifth indication information is used to indicate the difference or ratio between the timed reporting granularity factor K2 and the timed reporting granularity factor K1;

[0431] The sixth indication information is used to indicate the difference or ratio between the reporting quantity N2 of the information unit and the minimum reporting quantity N1 of the information unit.

[0432] In some embodiments, the wireless communication device 300 further includes: a processing module 303;

[0433] The processing module 303 is used to determine the minimum reporting quantity N1 of the information unit based on the timed reporting granularity factor K1 and the first correlation relationship; or, the processing module 303 is used to determine the timed reporting granularity factor K1 based on the minimum reporting quantity N1 of the information unit and the first correlation relationship; wherein, the first correlation relationship is the correlation between the timed reporting granularity factor and the minimum reporting quantity of the information unit; or,

[0434] The processing module 303 is used to determine the reporting quantity N2 of the information unit based on the timed reporting granularity factor K2 and the second correlation relationship; or, the processing module 303 is used to determine the timed reporting granularity factor K2 based on the reporting quantity N2 of the information unit and the second correlation relationship; wherein, the second correlation relationship is the correlation between the timed reporting granularity factor and the reporting quantity of the information unit.

[0435] In some embodiments, the first information further includes at least one of the following:

[0436] The seventh indication information is used to indicate the first time interval;

[0437] The eighth indication information is used to indicate the first distance;

[0438] The ninth instruction is used to indicate the second time interval;

[0439] The tenth indication information is used to indicate the second distance;

[0440] The eleventh instruction message is used to indicate the first measurement window;

[0441] The twelfth instruction message is used to indicate the second measurement window;

[0442] Wherein, the time interval between the timestamp associated with the signal measurement information and the timestamp associated with the location-related information is less than the first time interval, or the time interval between the timestamp associated with the signal measurement information and the timestamp associated with the location-related information is less than or equal to the first time interval;

[0443] Wherein, the distance between the location where the signal measurement information is acquired and the location where the location-related information is acquired is less than the first distance, or the distance between the location where the signal measurement information is acquired and the location where the location-related information is acquired is less than or equal to the first distance;

[0444] Wherein, if the time interval between the timestamps associated with at least two acquired signal measurement information is less than the second time interval, or if the time interval between the timestamps associated with at least two acquired signal measurement information is less than or equal to the second time interval, the at least two acquired signal measurement information belongs to the same data sample, or the at least two acquired signal measurement information is associated with the same data sample, or the at least two acquired signal measurement information is acquired at the same or similar locations; and / or, if the time interval between the timestamps associated with at least two acquired location-related information is less than the second time interval, or if the time interval between the timestamps associated with at least two acquired location-related information is less than or equal to the second time interval, the at least two acquired location-related information belongs to the same data sample, or the at least two acquired location-related information is associated with the same data sample, or the at least two acquired location-related information is acquired at the same or similar locations;

[0445] Wherein, if the distance between the acquisition locations of at least two acquired signal measurement information is less than the second distance, or if the distance between the acquisition locations of at least two acquired signal measurement information is less than or equal to the second distance, the at least two acquired signal measurement information belongs to the same data sample, or the at least two acquired signal measurement information is associated with the same data sample, or the at least two acquired signal measurement information is acquired at the same or similar locations; and / or, if the distance between the acquisition locations of at least two acquired location-related information is less than the second distance, or if the distance between the acquisition locations of at least two acquired location-related information is less than or equal to the second distance, the at least two acquired location-related information belongs to the same data sample, or the at least two acquired location-related information is associated with the same data sample, or the at least two acquired location-related information is acquired at the same or similar locations;

[0446] The signal measurement information and the location-related information are acquired within the same first measurement window;

[0447] Specifically, if at least two signal measurement information acquisitions are both acquired within the second measurement window, the at least two acquired signal measurement information acquisitions belong to the same data sample, or the at least two acquired signal measurement information acquisitions are associated with the same data sample, or the at least two acquired signal measurement information acquisitions are acquired at the same or similar locations; and / or, if at least two location-related information acquisitions are both acquired within the second measurement window, the at least two acquired location-related information acquisitions belong to the same data sample, or the at least two acquired location-related information acquisitions are associated with the same data sample, or the at least two acquired location-related information acquisitions are acquired at the same or similar locations.

[0448] In some embodiments, the wireless communication device 300 further includes:

[0449] Processing module 303 is used to determine the information unit associated with each measurement unit in the at least one measurement unit according to a first power threshold;

[0450] Wherein, the power of the information unit associated with each measurement unit in the at least one measurement unit is greater than the first power threshold, or the power of the information unit associated with each measurement unit in the at least one measurement unit is greater than or equal to the first power threshold.

[0451] In some embodiments, the first power threshold is determined based on at least one of the following: the reference signal received power (RSRP) measured on the same reference signal resource, the power of the information unit with the smallest delay, and the power of the information unit with the largest power.

[0452] In some embodiments, the wireless communication device 300 further includes:

[0453] The processing module 303 is used to determine the time delay information of the at least one measurement unit based on the reference time; wherein, the time delay information of the at least one measurement unit includes the difference between the time delay of the at least one measurement unit and the reference time.

[0454] In some embodiments, the reference time is the timing information or delay information of the information unit with the smallest delay associated with the reference transmit / receive point (TRP); or, the reference time is the timing information or delay information of the information unit with the smallest delay associated with the reference cell; or, the reference time is the downlink subframe boundary of the reference TRP; or, the reference time is the downlink subframe boundary of the reference cell; or, the reference time is configured by the network side; or, the reference time is agreed upon by the protocol.

[0455] In some embodiments, before the wireless communication device 300 receives the first information from the second device, the transmitting module 302 is further configured to transmit capability information to the second device;

[0456] The capability information is used to indicate at least one of the following:

[0457] The wireless communication device 300 supports the types of information units to be reported;

[0458] The wireless communication device 300 supports the maximum number of information units reported by a measurement unit associated with it.

[0459] The wireless communication device 300 supports at least one timing reporting granularity factor in channel sampling point-based reporting.

[0460] The wireless communication device 300 supports at least one timing reporting granularity factor in channel path-based reporting.

[0461] The information unit type includes at least one of the following: channel sampling point, channel path.

[0462] In some embodiments, the maximum number of information units reported by a measurement unit associated with a wireless communication device 300 is associated with the bandwidth of the reference signal associated with that measurement unit.

[0463] In some embodiments, when the wireless communication device 300 supports reporting information units of the type of channel sampling point and channel path, the signal measurement information includes thirteenth indication information, wherein the thirteenth indication information is used to indicate the type of information unit associated with the at least one measurement unit;

[0464] or,

[0465] When the type of information unit supported by the wireless communication device 300 for reporting is a channel sampling point or a channel path, the type of information unit associated with the at least one measurement unit is by default the type of information unit supported by the wireless communication device 300 for reporting.

[0466] or,

[0467] The information field that allows the determination of the type of information unit reported by the wireless communication device 300 in the protocol to be based on whether the measurement unit reported by the wireless communication device 300 contains the delay information of the first information unit in terms of delay, or the information field that allows the determination of the type of information unit reported by the wireless communication device 300 in the protocol to be based on whether the measurement unit reported by the wireless communication device 300 contains a list of additional information units.

[0468] Wherein, if the measurement unit reported by the wireless communication device 300 does not include an information field containing delay information of the first information unit in terms of delay, or if the measurement unit reported by the wireless communication device 300 does not include an information field containing a list of additional information units, the type of the information unit associated with the at least one measurement unit is a channel sampling point; and / or,

[0469] In the case where the measurement unit reported by the wireless communication device 300 includes an information field containing delay information of the first information unit, or in the case where the measurement unit reported by the wireless communication device 300 includes an information field containing a list of additional information units, the type of the information unit associated with the at least one measurement unit is a channel path.

[0470] In some embodiments, the type of the information unit includes at least one of the following: channel sampling point, channel path.

[0471] In some embodiments, the measuring unit is associated with at least one of the following:

[0472] The identifier of at least one reference signal resource, the identifier of at least one cell, the identifier of at least one reference signal, the identifier of at least one TRP, and the identifier of at least one set of reference signal resources;

[0473] And / or,

[0474] The signal measurement information is associated with at least one of the following:

[0475] At least one area identifier, at least one cell list, at least one area identifier-cell list (AreaID-CellList), at least one TRP list, at least one positioning frequency layer, at least one cell identifier, at least one reference signal identifier, and at least one reference signal resource set identifier;

[0476] And / or,

[0477] The first information is associated with at least one of the following:

[0478] At least one area identifier, at least one cell list, at least one area identifier-cell list (AreaID-CellList), at least one TRP list, at least one positioning frequency layer, at least one cell identifier, at least one reference signal identifier, and at least one reference signal resource set identifier.

[0479] See Figure 25 When the wireless communication device is a second device or a component of a second device, the wireless communication device 400 includes:

[0480] The sending module 401 is used to send first information to the first device; wherein the first information is used to indicate at least one of the following: a timed reporting granularity factor K1, and a minimum reporting quantity N1 of information units; wherein K1 is an integer and N1 is a positive integer;

[0481] The receiving module 402 is configured to receive second information from the first device; wherein the second information is used for positioning based on an artificial intelligence (AI) model, and the second information includes at least one of the following: signal measurement information, location-related information;

[0482] The signal measurement information includes at least one of the following: information of at least one measurement unit, quality information of the at least one measurement unit, timestamp associated with the at least one measurement unit, and first identifier associated with the at least one measurement unit; the location-related information includes at least one of the following: location tag, quality information of the location tag, and timestamp associated with the location tag;

[0483] The information of the measurement unit includes at least one of the following: time delay information, power information, and phase information;

[0484] The at least one measurement unit is determined based on the number of timed reporting granularity factor K2 and / or information unit reporting N2, where K2 is less than or equal to K1, N2 is greater than or equal to N1, K2 is an integer, and N2 is a positive integer.

[0485] The first identifier is associated with the network environment information on the Radio Access Network (RAN) side.

[0486] In some embodiments, the first information further includes a maximum number N3 of information units to be reported;

[0487] Where N2 is less than or equal to N3, and N3 is a positive integer.

[0488] In some embodiments, the timed reporting granularity factor K2 is determined based on the timed reporting granularity factor K1; and / or,

[0489] The number of information units reported, N2, is determined based on the minimum number of information units reported, N1, and / or the maximum number of information units reported, N3.

[0490] In some embodiments, the first information further includes at least one of the following: a list of candidate timing reporting granularity factors, and a list of reporting quantities of candidate information units;

[0491] Wherein, the timed reporting granularity factor K2 is determined based on the candidate timed reporting granularity factor list; and / or, the reporting quantity N2 of the information unit is determined based on the reporting quantity list of the candidate information units.

[0492] In some embodiments, the sending module 401 is further configured to send third information to the first device;

[0493] The third information includes at least one of the following:

[0494] The first indication information is used to indicate the timed reporting granularity factor K2;

[0495] The second instruction information is used to indicate the number N2 reported by the information unit;

[0496] The third instruction is used to instruct a reduction in the timing reporting granularity factor.

[0497] The fourth instruction is used to indicate the number of information units to be reported.

[0498] The fifth indication information is used to indicate the difference or ratio between the timed reporting granularity factor K2 and the timed reporting granularity factor K1;

[0499] The sixth indication information is used to indicate the difference or ratio between the reporting quantity N2 of the information unit and the minimum reporting quantity N1 of the information unit.

[0500] In some embodiments, the minimum reporting quantity N1 of the information unit is determined based on the timed reporting granularity factor K1 and a first correlation relationship; or, the timed reporting granularity factor K1 is determined based on the minimum reporting quantity N1 of the information unit and a first correlation relationship; wherein, the first correlation relationship is the correlation between the timed reporting granularity factor and the minimum reporting quantity of the information unit; or,

[0501] The number N2 of information units reported is determined based on the timed reporting granularity factor K2 and the second correlation; or, the timed reporting granularity factor K2 is determined based on the number N2 of information units reported and the second correlation; wherein, the second correlation is the correlation between the timed reporting granularity factor and the number of information units reported.

[0502] In some embodiments, the first information further includes at least one of the following:

[0503] The seventh indication information is used to indicate the first time interval;

[0504] The eighth indication information is used to indicate the first distance;

[0505] The ninth instruction is used to indicate the second time interval;

[0506] The tenth indication information is used to indicate the second distance;

[0507] The eleventh instruction message is used to indicate the first measurement window;

[0508] The twelfth instruction message is used to indicate the second measurement window;

[0509] Wherein, the time interval between the timestamp associated with the signal measurement information and the timestamp associated with the location-related information is less than the first time interval, or the time interval between the timestamp associated with the signal measurement information and the timestamp associated with the location-related information is less than or equal to the first time interval;

[0510] Wherein, the distance between the location where the signal measurement information is acquired and the location where the location-related information is acquired is less than the first distance, or the distance between the location where the signal measurement information is acquired and the location where the location-related information is acquired is less than or equal to the first distance;

[0511] Wherein, if the time interval between the timestamps associated with at least two acquired signal measurement information is less than the second time interval, or if the time interval between the timestamps associated with at least two acquired signal measurement information is less than or equal to the second time interval, the at least two acquired signal measurement information belongs to the same data sample, or the at least two acquired signal measurement information is associated with the same data sample, or the at least two acquired signal measurement information is acquired at the same or similar locations; and / or, if the time interval between the timestamps associated with at least two acquired location-related information is less than the second time interval, or if the time interval between the timestamps associated with at least two acquired location-related information is less than or equal to the second time interval, the at least two acquired location-related information belongs to the same data sample, or the at least two acquired location-related information is associated with the same data sample, or the at least two acquired location-related information is acquired at the same or similar locations;

[0512] Wherein, if the distance between the acquisition locations of at least two acquired signal measurement information is less than the second distance, or if the distance between the acquisition locations of at least two acquired signal measurement information is less than or equal to the second distance, the at least two acquired signal measurement information belongs to the same data sample, or the at least two acquired signal measurement information is associated with the same data sample, or the at least two acquired signal measurement information is acquired at the same or similar locations; and / or, if the distance between the acquisition locations of at least two acquired location-related information is less than the second distance, or if the distance between the acquisition locations of at least two acquired location-related information is less than or equal to the second distance, the at least two acquired location-related information belongs to the same data sample, or the at least two acquired location-related information is associated with the same data sample, or the at least two acquired location-related information is acquired at the same or similar locations;

[0513] The signal measurement information and the location-related information are acquired within the same first measurement window;

[0514] Specifically, if at least two signal measurement information acquisitions are both acquired within the second measurement window, the at least two acquired signal measurement information acquisitions belong to the same data sample, or the at least two acquired signal measurement information acquisitions are associated with the same data sample, or the at least two acquired signal measurement information acquisitions are acquired at the same or similar locations; and / or, if at least two location-related information acquisitions are both acquired within the second measurement window, the at least two acquired location-related information acquisitions belong to the same data sample, or the at least two acquired location-related information acquisitions are associated with the same data sample, or the at least two acquired location-related information acquisitions are acquired at the same or similar locations.

[0515] In some embodiments, the information unit associated with each measurement unit in the at least one measurement unit is determined based on a first power threshold;

[0516] Wherein, the power of the information unit associated with each measurement unit in the at least one measurement unit is greater than the first power threshold, or the power of the information unit associated with each measurement unit in the at least one measurement unit is greater than or equal to the first power threshold.

[0517] In some embodiments, the delay information of the at least one measurement unit is determined based on a reference time; wherein the delay information of the at least one measurement unit includes the difference between the delay of the at least one measurement unit and the reference time.

[0518] In some embodiments, before the wireless communication device 400 sends the first information to the first device, the receiving module 402 is further configured to receive capability information from the first device;

[0519] The capability information is used to indicate at least one of the following:

[0520] The first device supports the reporting of various information unit types;

[0521] The maximum number of information units that can be reported by a measurement unit associated with the first device;

[0522] The first device supports at least one timing reporting granularity factor in channel sampling point-based reporting;

[0523] The first device supports at least one timing reporting granularity factor in channel path-based reporting;

[0524] The information unit type includes at least one of the following: channel sampling point, channel path.

[0525] In some embodiments, the maximum number of information units reported by a measurement unit supported by the first device is associated with the bandwidth of the reference signal associated with that measurement unit.

[0526] In some embodiments, when the type of information unit to be reported by the first device is a channel sampling point and a channel path, the signal measurement information includes a thirteenth indication information, wherein the thirteenth indication information is used to indicate the type of information unit associated with the at least one measurement unit;

[0527] or,

[0528] When the type of information unit that the first device supports reporting is a channel sampling point or a channel path, the type of information unit associated with the at least one measurement unit is by default the type of information unit that the first device supports reporting;

[0529] or,

[0530] The protocol stipulates that the type of information unit reported by the first device can be determined based on whether the measurement unit reported by the first device contains the delay information of the first information unit in terms of delay, or the protocol stipulates that the type of information unit reported by the first device can be determined based on whether the measurement unit reported by the first device contains a list of additional information units.

[0531] Wherein, if the measurement unit reported by the first device does not include an information field containing delay information of the first information unit, or if the measurement unit reported by the first device does not include an information field containing a list of additional information units, the type of the information unit associated with the at least one measurement unit is a channel sampling point; and / or,

[0532] In the case where the measurement unit reported by the first device includes an information field containing delay information of the first information unit, or in the case where the measurement unit reported by the first device includes an information field containing a list of additional information units, the type of the information unit associated with the at least one measurement unit is a channel path.

[0533] In some embodiments, the measuring unit is associated with at least one of the following:

[0534] The identifier of at least one reference signal resource, the identifier of at least one cell, the identifier of at least one reference signal, the identifier of at least one TRP, and the identifier of at least one set of reference signal resources;

[0535] And / or,

[0536] The signal measurement information is associated with at least one of the following:

[0537] At least one area identifier, at least one cell list, at least one area identifier-cell list (AreaID-CellList), at least one TRP list, at least one positioning frequency layer, at least one cell identifier, at least one reference signal identifier, and at least one reference signal resource set identifier;

[0538] And / or,

[0539] The first information is associated with at least one of the following:

[0540] At least one area identifier, at least one cell list, at least one area identifier-cell list (AreaID-CellList), at least one TRP list, at least one positioning frequency layer, at least one cell identifier, at least one reference signal identifier, and at least one reference signal resource set identifier.

[0541] Therefore, in this embodiment, the first device receives first information from the second device; wherein, the first information is used to indicate at least one of the following: a timed reporting granularity factor K1, and a minimum reporting quantity N1 of information units; the first device sends second information to the second device; wherein, the second information is used to perform a positioning function based on an AI model, and the second information includes at least one of the following: signal measurement information, and location-related information; wherein, the signal measurement information includes at least one of the following: information of at least one measurement unit, quality information of at least one measurement unit, a timestamp associated with at least one measurement unit, and a first identifier associated with at least one measurement unit; the location-related information includes at least one of the following: a location tag, quality information of the location tag, and a timestamp associated with the location tag; wherein, at least one measurement unit is determined based on a timed reporting granularity factor K2 and / or a reporting quantity N2 of information units, where K2 is less than or equal to K1, and N2 is greater than or equal to N1; wherein, the first identifier is associated with network environment information on the RAN side. Specifically, the first device can determine at least one measurement unit based on the timed reporting granularity factor K2 and / or the number of information units reported N2. By restricting K2 to be less than or equal to K1 and N2 to be greater than or equal to N1, the granularity of the delay information of the information units contained in each reported measurement unit and the number of information units contained therein meet the requirements of the AI ​​positioning model on the network side, thereby improving the positioning accuracy of the AI ​​model-based positioning function. For example, the smaller the timed reporting granularity factor K2, the smaller the granularity of the delay information of the information units, the higher the degree of freedom provided to the network side, and the higher the positioning accuracy of the AI ​​model-based positioning function based on the second information; and / or, the larger the number of information units reported N2, the more information units there are, and the higher the positioning accuracy of the AI ​​model-based positioning function based on the second information.

[0542] The wireless communication device provided in this application embodiment can achieve... Figures 4 to 23 The various processes implemented in the method embodiments achieve the same technical effect, and will not be described again here to avoid repetition.

[0543] like Figure 26 As shown in the figure, this application embodiment also provides a communication device 500, including a processor 501 and a memory 502, wherein the memory 502 stores a program or instructions that can be run on the processor 501.

[0544] For example, when the communication device 500 is the first device, the program or instruction executed by the processor 501 implements the various steps executed by the first device in the above wireless communication method embodiment and can achieve the same technical effect. To avoid repetition, it will not be described again here.

[0545] For example, when the communication device 500 is a second device, the program or instruction executed by the processor 501 implements the various steps executed by the second device in the above wireless communication method embodiment and can achieve the same technical effect. To avoid repetition, it will not be described again here.

[0546] This application embodiment also provides a terminal, including a processor and a communication interface, wherein the communication interface is coupled to the processor, and the processor is used to run programs or instructions to implement, for example... Figure 4 The steps in the method embodiment shown are illustrated. This terminal embodiment corresponds to the above-described terminal-side method embodiment. All implementation processes and methods of the above-described method embodiments can be applied to this terminal embodiment and achieve the same technical effect. The terminal can be... Figure 24 The wireless communication device 300 shown. Specifically, Figure 27 A schematic diagram of the hardware structure of a terminal to implement an embodiment of this application.

[0547] The terminal 600 includes, but is not limited to, at least some of the following components: radio frequency unit 601, network module 602, audio output unit 603, input unit 604, sensor 605, display unit 606, user input unit 607, interface unit 608, memory 609, and processor 610.

[0548] Those skilled in the art will understand that the terminal 600 may also include a power supply (such as a battery) for supplying power to various components. The power supply may be logically connected to the processor 610 through a power management system, thereby enabling functions such as managing charging, discharging, and power consumption through the power management system. Figure 27 The terminal structure shown does not constitute a limitation on the terminal. The terminal may include more or fewer components than shown, or combine certain components, or have different component arrangements, which will not be elaborated here.

[0549] It should be understood that, in this embodiment, the input unit 604 may include a graphics processor 6041 and a microphone 6042. The graphics processor 6041 processes image data of still images or videos obtained by an image capture device (such as a camera) in video capture mode or image capture mode. The display unit 606 may include a display panel 6061, which may be configured in the form of a liquid crystal display, an organic light-emitting diode, or the like. The user input unit 607 includes at least one of a touch panel 6071 and other input devices 6072. The touch panel 6071 is also called a touch screen. The touch panel 6071 may include two parts: a touch detection device and a touch controller. Other input devices 6072 may include, but are not limited to, a physical keyboard, function keys (such as volume control buttons, power buttons, etc.), a trackball, a mouse, and a joystick, which will not be described in detail here.

[0550] In this embodiment, after receiving downlink data from the network-side device, the radio frequency unit 601 can transmit it to the processor 610 for processing; in addition, the radio frequency unit 601 can send uplink data to the network-side device. Typically, the radio frequency unit 601 includes, but is not limited to, antennas, amplifiers, transceivers, couplers, low-noise amplifiers, duplexers, etc.

[0551] The memory 609 can be used to store software programs or instructions, as well as various data. The memory 609 may primarily include a first storage area for storing programs or instructions and a second storage area for storing data. The first storage area may store the operating system, application programs or instructions required for at least one function (such as sound playback, image playback, etc.). Furthermore, the memory 609 may include volatile memory or non-volatile memory. The non-volatile memory may be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. Volatile memory can be random access memory (RAM), static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDRSDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM), and direct memory bus RAM (DRRAM). The memory 609 in this embodiment includes, but is not limited to, these and any other suitable types of memory.

[0552] Processor 610 may include one or more processing units; optionally, processor 610 integrates an application processor and a modem processor, wherein the application processor mainly handles operations involving the operating system, user interface, and applications, and the modem processor mainly handles wireless communication signals, such as a baseband processor. It is understood that the aforementioned modem processor may also not be integrated into processor 610.

[0553] In some embodiments, the first device is a terminal;

[0554] The radio frequency unit 601 is used to receive first information from the second device; wherein the first information is used to indicate at least one of the following: periodically reporting granularity factor K1, and the minimum reporting number N1 of information units; wherein K1 is an integer and N1 is a positive integer;

[0555] The radio frequency unit 601 is further configured to send second information to the second device; wherein the second information is used for positioning based on an artificial intelligence (AI) model, and the second information includes at least one of the following: signal measurement information, location-related information;

[0556] The signal measurement information includes at least one of the following: information of at least one measurement unit, quality information of the at least one measurement unit, timestamp associated with the at least one measurement unit, and first identifier associated with the at least one measurement unit; the location-related information includes at least one of the following: location tag, quality information of the location tag, and timestamp associated with the location tag;

[0557] The information of the measurement unit includes at least one of the following: time delay information, power information, and phase information;

[0558] The at least one measurement unit is determined based on the number of timed reporting granularity factor K2 and / or information unit reporting N2, where K2 is less than or equal to K1, N2 is greater than or equal to N1, K2 is an integer, and N2 is a positive integer.

[0559] The first identifier is associated with the network environment information on the Radio Access Network (RAN) side.

[0560] Therefore, in this embodiment, the first device receives first information from the second device; wherein, the first information is used to indicate at least one of the following: a timed reporting granularity factor K1, and a minimum reporting quantity N1 of information units; the first device sends second information to the second device; wherein, the second information is used to perform a positioning function based on an AI model, and the second information includes at least one of the following: signal measurement information, and location-related information; wherein, the signal measurement information includes at least one of the following: information of at least one measurement unit, quality information of at least one measurement unit, a timestamp associated with at least one measurement unit, and a first identifier associated with at least one measurement unit; the location-related information includes at least one of the following: a location tag, quality information of the location tag, and a timestamp associated with the location tag; wherein, at least one measurement unit is determined based on a timed reporting granularity factor K2 and / or a reporting quantity N2 of information units, where K2 is less than or equal to K1, and N2 is greater than or equal to N1; wherein, the first identifier is associated with network environment information on the RAN side. Specifically, the first device can determine at least one measurement unit based on the timed reporting granularity factor K2 and / or the number of information units reported N2. By restricting K2 to be less than or equal to K1 and N2 to be greater than or equal to N1, the granularity of the delay information of the information units contained in each reported measurement unit and the number of information units contained therein meet the requirements of the AI ​​positioning model on the network side, thereby improving the positioning accuracy of the AI ​​model-based positioning function. For example, the smaller the timed reporting granularity factor K2, the smaller the granularity of the delay information of the information units, the higher the degree of freedom provided to the network side, and the higher the positioning accuracy of the AI ​​model-based positioning function based on the second information; and / or, the larger the number of information units reported N2, the more information units there are, and the higher the positioning accuracy of the AI ​​model-based positioning function based on the second information.

[0561] It is understood that the implementation process of each implementation method mentioned in this embodiment can refer to the relevant description of the method embodiment and achieve the same or corresponding technical effect. To avoid repetition, it will not be described again here.

[0562] This application embodiment also provides a network-side device, including a processor and a communication interface, wherein the communication interface is coupled to the processor, and the processor is used to run programs or instructions to implement, for example... Figure 4 The steps of the method embodiment shown are illustrated. This network-side device embodiment corresponds to the method embodiment executed by the first or second device described above. All implementation processes and methods of the above method embodiments can be applied to this network-side device embodiment and can achieve the same technical effect.

[0563] Specifically, embodiments of this application also provide a network-side device, which can be... Figure 24 The wireless communication device 300 shown or Figure 25The wireless communication device 400 is shown. (For example...) Figure 28 As shown, the network-side device 700 includes: an antenna 71, a radio frequency (RF) device 72, a baseband device 73, a processor 74, and a memory 75. The antenna 71 is connected to the RF device 72. In the uplink direction, the RF device 72 receives information through the antenna 71 and transmits the received information to the baseband device 73 for processing. In the downlink direction, the baseband device 73 processes the information to be transmitted and sends it to the RF device 72. The RF device 72 processes the received information and transmits it through the antenna 71.

[0564] The method executed by the first or second device in the above embodiments can be implemented in the baseband device 73, which includes a baseband processor.

[0565] The baseband device 73 may include, for example, at least one baseband board on which multiple chips are disposed, such as... Figure 28 As shown, one of the chips is, for example, a baseband processor, which is connected to the memory 75 via a bus interface to call the program in the memory 75 and execute the operation of the first or second device shown in the above method embodiment.

[0566] The network-side device may also include a network interface 76, such as a Common Public Radio Interface (CPRI).

[0567] Specifically, the network-side device 700 in this application embodiment further includes: instructions or programs stored in memory 75 and executable on processor 74, wherein processor 74 calls the instructions or programs in memory 75 to execute. Figure 24 or Figure 25 The methods executed by each module shown achieve the same technical effect, and to avoid repetition, they will not be described in detail here.

[0568] Specifically, embodiments of this application also provide a network-side device. For example... Figure 29 As shown, the network-side device 800 includes: a processor 801, a network interface 802, and a memory 803. This network-side device can be... Figure 24 The wireless communication device 300 shown or Figure 25 The wireless communication device 400 shown. The network interface 802 is, for example, a common public radio interface (CPRI).

[0569] Specifically, the network-side device 800 in this application embodiment further includes: instructions or programs stored in memory 803 and executable on processor 801, wherein processor 801 calls the instructions or programs in memory 803 to execute. Figure 24 or Figure 25 The methods executed by each module shown achieve the same technical effect, and to avoid repetition, they will not be described in detail here.

[0570] This application also provides a readable storage medium storing a program or instructions. When the program or instructions are executed by a processor, they implement the various processes of the above-described wireless communication method embodiments and achieve the same technical effects. To avoid repetition, they will not be described again here.

[0571] The processor is the processor in the first or second device described in the above embodiments. The readable storage medium includes computer-readable storage media, such as computer read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disk. In some examples, the readable storage medium may be a non-transient readable storage medium.

[0572] This application embodiment also provides a chip, which includes a processor and a communication interface. The communication interface is coupled to the processor. The processor is used to run programs or instructions to implement the various processes of the above-described wireless communication method embodiments and can achieve the same technical effect. To avoid repetition, it will not be described again here.

[0573] It should be understood that the chip mentioned in the embodiments of this application may also be referred to as a system-on-a-chip, system chip, chip system, or system-on-a-chip, etc.

[0574] This application also provides a computer program / program product, which is stored in a storage medium and executed by at least one processor to implement the various processes of the above-described wireless communication method embodiments, and can achieve the same technical effect. To avoid repetition, it will not be described again here.

[0575] This application also provides a wireless communication system, including a first device and a second device. The first device can be used to perform the steps performed by the first device in the wireless communication method described above, and the second device can be used to perform the steps performed by the second device in the wireless communication method described above.

[0576] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element. Furthermore, it should be noted that the scope of the methods and apparatuses in the embodiments of this application is not limited to performing functions in the order shown or discussed, but may also include performing functions substantially simultaneously or in the reverse order, depending on the functions involved. For example, the described methods may be performed in a different order than described, and various steps may be added, omitted, or combined. Additionally, features described with reference to certain examples may be combined in other examples.

[0577] From the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of computer software products plus necessary general-purpose hardware platforms, and of course, they can also be implemented by hardware. The computer software product is stored in a storage medium (such as ROM, RAM, magnetic disk, optical disk, etc.) and includes several instructions to cause the terminal or network-side device to execute the methods described in the various embodiments of this application.

[0578] The embodiments of this application have been described above with reference to the accompanying drawings. However, this application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other implementations under the guidance of this application without departing from the spirit and scope of the claims. All of these implementations are within the protection scope of this application.

Claims

1. A wireless communication method, characterized in that, include: The first device receives first information from the second device; wherein the first information is used to indicate at least one of the following: periodically reporting granularity factor K1, and the minimum reporting quantity N1 of information units; wherein K1 is an integer and N1 is a positive integer; The first device sends second information to the second device; wherein the second information is used for positioning based on an artificial intelligence (AI) model, and the second information includes at least one of the following: signal measurement information, location-related information; The signal measurement information includes at least one of the following: information of at least one measurement unit, quality information of the at least one measurement unit, timestamp associated with the at least one measurement unit, and first identifier associated with the at least one measurement unit; the location-related information includes at least one of the following: location tag, quality information of the location tag, and timestamp associated with the location tag; The information of the measurement unit includes at least one of the following: time delay information, power information, and phase information; The at least one measurement unit is determined based on the number of timed reporting granularity factor K2 and / or information unit reporting N2, where K2 is less than or equal to K1, N2 is greater than or equal to N1, K2 is an integer, and N2 is a positive integer. The first identifier is associated with the network environment information on the Radio Access Network (RAN) side.

2. The method according to claim 1, characterized in that, The first information also includes the maximum number of information units that can be reported, N3; Where N2 is less than or equal to N3, and N3 is a positive integer.

3. The method according to claim 1 or 2, characterized in that, The method further includes: The first device determines the timing reporting granularity factor K2 based on the timing reporting granularity factor K1; and / or, The first device determines the reporting quantity N2 of the information unit based on the minimum reporting quantity N1 and / or the maximum reporting quantity N3 of the information unit.

4. The method according to claim 1 or 2, characterized in that, The first information also includes at least one of the following: a list of candidate timed reporting granularity factors, and a list of the reporting quantities of candidate information units; The method further includes: The first device determines the timing reporting granularity factor K2 based on the candidate timing reporting granularity factor list; and / or, the first device determines the reporting quantity N2 of the information unit based on the reporting quantity list of the candidate information units.

5. The method according to claim 1 or 2, characterized in that, The method further includes: The first device receives third information from the second device; The third information includes at least one of the following: The first indication information is used to indicate the timed reporting granularity factor K2; The second instruction information is used to indicate the number N2 reported by the information unit; The third instruction is used to instruct a reduction in the timing reporting granularity factor. The fourth instruction is used to indicate the number of information units to be reported. The fifth indication information is used to indicate the difference or ratio between the timed reporting granularity factor K2 and the timed reporting granularity factor K1; The sixth indication information is used to indicate the difference or ratio between the reporting quantity N2 of the information unit and the minimum reporting quantity N1 of the information unit.

6. The method according to any one of claims 1 to 5, characterized in that, The method further includes: The first device determines the minimum reporting quantity N1 of the information unit based on the timed reporting granularity factor K1 and the first correlation relationship; or, the first device determines the timed reporting granularity factor K1 based on the minimum reporting quantity N1 of the information unit and the first correlation relationship; wherein, the first correlation relationship is the correlation between the timed reporting granularity factor and the minimum reporting quantity of the information unit; or, The first device determines the reporting quantity N2 of the information unit based on the timed reporting granularity factor K2 and the second correlation relationship; or, the first device determines the timed reporting granularity factor K2 based on the reporting quantity N2 of the information unit and the second correlation relationship; wherein, the second correlation relationship is the correlation between the timed reporting granularity factor and the reporting quantity of the information unit.

7. The method according to any one of claims 1 to 6, characterized in that, The method further includes: The first device determines the information unit associated with each measurement unit in the at least one measurement unit based on a first power threshold; Wherein, the power of the information unit associated with each measurement unit in the at least one measurement unit is greater than the first power threshold, or the power of the information unit associated with each measurement unit in the at least one measurement unit is greater than or equal to the first power threshold.

8. The method according to claim 7, characterized in that, The first power threshold is determined based on at least one of the following: the reference signal received power (RSRP) measured on the same reference signal resource, the power of the information unit with the smallest delay, and the power of the information unit with the largest power.

9. The method according to any one of claims 1 to 8, characterized in that, The method further includes: The first device determines the time delay information of the at least one measurement unit based on a reference time; wherein, the time delay information of the at least one measurement unit includes the difference between the time delay of the at least one measurement unit and the reference time.

10. The method according to claim 9, characterized in that, The reference time is the timing information or delay information of the information unit with the smallest delay associated with the reference transmit / receive point (TRP), or the reference time is the timing information or delay information of the information unit with the smallest delay associated with the reference cell, or the reference time is the downlink subframe boundary of the reference TRP, or the reference time is the downlink subframe boundary of the reference cell, or the reference time is configured by the network side, or the reference time is agreed upon by the protocol.

11. The method according to any one of claims 1 to 10, characterized in that, Before the first device receives the first information from the second device, the method further includes: The first device sends capability information to the second device; The capability information is used to indicate at least one of the following: The first device supports the reporting of various information unit types; The maximum number of information units that can be reported by a measurement unit associated with the first device; The first device supports at least one timing reporting granularity factor in channel sampling point-based reporting; The first device supports at least one timing reporting granularity factor in channel path-based reporting; The information unit type includes at least one of the following: channel sampling point, channel path.

12. The method according to claim 11, characterized in that, The maximum number of information units reported by a measurement unit associated with the first device is related to the bandwidth of the reference signal associated with that measurement unit.

13. The method according to claim 11 or 12, characterized in that, When the type of information unit that the first device supports reporting is channel sampling point and channel path, the signal measurement information includes thirteenth indication information, wherein the thirteenth indication information is used to indicate the type of information unit associated with the at least one measurement unit; or, When the type of information unit that the first device supports reporting is a channel sampling point or a channel path, the type of information unit associated with the at least one measurement unit is by default the type of information unit that the first device supports reporting; or, The protocol stipulates that the type of information unit reported by the first device can be determined based on whether the measurement unit reported by the first device contains the delay information of the first information unit in terms of delay, or the protocol stipulates that the type of information unit reported by the first device can be determined based on whether the measurement unit reported by the first device contains a list of additional information units. Wherein, if the measurement unit reported by the first device does not include an information field containing delay information of the first information unit, or if the measurement unit reported by the first device does not include an information field containing a list of additional information units, the type of the information unit associated with the at least one measurement unit is a channel sampling point; and / or, In the case where the measurement unit reported by the first device includes an information field containing delay information of the first information unit, or in the case where the measurement unit reported by the first device includes an information field containing a list of additional information units, the type of the information unit associated with the at least one measurement unit is a channel path.

14. The method according to any one of claims 1 to 13, characterized in that, The measurement unit is associated with at least one of the following: The identifier of at least one reference signal resource, the identifier of at least one cell, the identifier of at least one reference signal, the identifier of at least one TRP, and the identifier of at least one set of reference signal resources; And / or, The signal measurement information is associated with at least one of the following: At least one area identifier, at least one cell list, at least one area identifier-cell list (AreaID-CellList), at least one TRP list, at least one positioning frequency layer, at least one cell identifier, at least one reference signal identifier, and at least one reference signal resource set identifier; And / or, The first information is associated with at least one of the following: At least one area identifier, at least one cell list, at least one area identifier-cell list (AreaID-CellList), at least one TRP list, at least one positioning frequency layer, at least one cell identifier, at least one reference signal identifier, and at least one reference signal resource set identifier.

15. A wireless communication method, characterized in that, include: The second device sends first information to the first device; wherein the first information is used to indicate at least one of the following: periodically reporting granularity factor K1, and the minimum reporting quantity N1 of information units; wherein K1 is an integer and N1 is a positive integer; The second device receives second information from the first device; wherein the second information is used for positioning based on an artificial intelligence (AI) model, and the second information includes at least one of the following: signal measurement information, location-related information; The signal measurement information includes at least one of the following: information of at least one measurement unit, quality information of the at least one measurement unit, timestamp associated with the at least one measurement unit, and first identifier associated with the at least one measurement unit; the location-related information includes at least one of the following: location tag, quality information of the location tag, and timestamp associated with the location tag; The information of the measurement unit includes at least one of the following: time delay information, power information, and phase information; The at least one measurement unit is determined based on the number of timed reporting granularity factor K2 and / or information units N2, where K2 is less than or equal to K1, N2 is greater than or equal to N1, K2 is an integer, and N2 is a positive integer. The first identifier is associated with the network environment information on the Radio Access Network (RAN) side.

16. The method according to claim 15, characterized in that, The first information also includes the maximum number of information units that can be reported, N3; Where N2 is less than or equal to N3, and N3 is a positive integer.

17. The method according to claim 15 or 16, characterized in that, The timed reporting granularity factor K2 is determined based on the timed reporting granularity factor K1; and / or, The number of information units reported, N2, is determined based on the minimum number of information units reported, N1, and / or the maximum number of information units reported, N3.

18. The method according to claim 15 or 16, characterized in that, The first information also includes at least one of the following: a list of candidate timed reporting granularity factors, and a list of the reporting quantities of candidate information units; Wherein, the timed reporting granularity factor K2 is determined based on the candidate timed reporting granularity factor list; and / or, the reporting quantity N2 of the information unit is determined based on the reporting quantity list of the candidate information units.

19. The method according to claim 15 or 16, characterized in that, The method further includes: The second device sends a third message to the first device; The third information includes at least one of the following: The first indication information is used to indicate the timed reporting granularity factor K2; The second instruction information is used to indicate the number N2 reported by the information unit; The third instruction is used to instruct a reduction in the timing reporting granularity factor. The fourth instruction is used to indicate the number of information units to be reported. The fifth indication information is used to indicate the difference or ratio between the timed reporting granularity factor K2 and the timed reporting granularity factor K1; The sixth indication information is used to indicate the difference or ratio between the reporting quantity N2 of the information unit and the minimum reporting quantity N1 of the information unit.

20. The method according to any one of claims 15 to 19, characterized in that, The minimum reporting quantity N1 of the information unit is determined based on the timed reporting granularity factor K1 and the first correlation relationship; or, the timed reporting granularity factor K1 is determined based on the minimum reporting quantity N1 of the information unit and the first correlation relationship; wherein, the first correlation relationship is the correlation between the timed reporting granularity factor and the minimum reporting quantity of the information unit; or, The number N2 of information units reported is determined based on the timed reporting granularity factor K2 and the second correlation; or, the timed reporting granularity factor K2 is determined based on the number N2 of information units reported and the second correlation; wherein, the second correlation is the correlation between the timed reporting granularity factor and the number of information units reported.

21. The method according to any one of claims 15 to 20, characterized in that, The information unit associated with each measurement unit in the at least one measurement unit is determined based on a first power threshold; Wherein, the power of the information unit associated with each measurement unit in the at least one measurement unit is greater than the first power threshold, or the power of the information unit associated with each measurement unit in the at least one measurement unit is greater than or equal to the first power threshold.

22. The method according to any one of claims 15 to 21, characterized in that, The time delay information of the at least one measurement unit is determined based on a reference time; wherein, the time delay information of the at least one measurement unit includes the difference between the time delay of the at least one measurement unit and the reference time.

23. The method according to any one of claims 15 to 22, characterized in that, Before the second device sends the first information to the first device, the method further includes: The second device receives capability information from the first device; The capability information is used to indicate at least one of the following: The first device supports the reporting of various information unit types; The maximum number of information units that can be reported by a measurement unit associated with the first device; The first device supports at least one timing reporting granularity factor in channel sampling point-based reporting; The first device supports at least one timing reporting granularity factor in channel path-based reporting; The information unit type includes at least one of the following: channel sampling point, channel path.

24. A wireless communication device, characterized in that, include: A receiving module is configured to receive first information from a second device; wherein the first information is configured to indicate at least one of the following: a granularity factor K1 for periodic reporting, and a minimum reporting quantity N1 for information units; wherein K1 is an integer and N1 is a positive integer; A sending module is used to send second information to the second device; wherein the second information is used for positioning function based on artificial intelligence (AI) model, and the second information includes at least one of the following: signal measurement information, location-related information; The signal measurement information includes at least one of the following: information of at least one measurement unit, quality information of the at least one measurement unit, timestamp associated with the at least one measurement unit, and first identifier associated with the at least one measurement unit; the location-related information includes at least one of the following: location tag, quality information of the location tag, and timestamp associated with the location tag; The information of the measurement unit includes at least one of the following: time delay information, power information, and phase information; The at least one measurement unit is determined based on the number of timed reporting granularity factor K2 and / or information unit reporting N2, where K2 is less than or equal to K1, N2 is greater than or equal to N1, K2 is an integer, and N2 is a positive integer. The first identifier is associated with the network environment information on the Radio Access Network (RAN) side.

25. The apparatus according to claim 24, characterized in that, The first information also includes the maximum number of information units that can be reported, N3; Where N2 is less than or equal to N3, and N3 is a positive integer.

26. The apparatus according to claim 24 or 25, characterized in that, The first information also includes at least one of the following: a list of candidate timed reporting granularity factors, and a list of the reporting quantities of candidate information units; The wireless communication device further includes: The processing module is configured to determine the timing reporting granularity factor K2 based on the candidate timing reporting granularity factor list; and / or, determine the reporting quantity N2 of the information unit based on the reporting quantity list of the candidate information units.

27. The apparatus according to claim 24 or 25, characterized in that, The receiving module is also configured to receive third information from the second device; The third information includes at least one of the following: The first indication information is used to indicate the timed reporting granularity factor K2; The second instruction information is used to indicate the number N2 reported by the information unit; The third instruction is used to instruct a reduction in the timing reporting granularity factor. The fourth instruction is used to indicate the number of information units to be reported. The fifth indication information is used to indicate the difference or ratio between the timed reporting granularity factor K2 and the timed reporting granularity factor K1; The sixth indication information is used to indicate the difference or ratio between the reporting quantity N2 of the information unit and the minimum reporting quantity N1 of the information unit.

28. The apparatus according to any one of claims 24 to 27, characterized in that, The wireless communication device further includes: a processing module; The processing module is used to determine the minimum reporting quantity N1 of the information unit based on the timed reporting granularity factor K1 and the first correlation relationship; or, the processing module is used to determine the timed reporting granularity factor K1 based on the minimum reporting quantity N1 of the information unit and the first correlation relationship; wherein, the first correlation relationship is the correlation between the timed reporting granularity factor and the minimum reporting quantity of the information unit; or, The processing module is used to determine the reporting quantity N2 of the information unit based on the timed reporting granularity factor K2 and the second correlation relationship; or, the processing module is used to determine the timed reporting granularity factor K2 based on the reporting quantity N2 of the information unit and the second correlation relationship; wherein, the second correlation relationship is the correlation between the timed reporting granularity factor and the reporting quantity of the information unit.

29. The apparatus according to any one of claims 24 to 28, characterized in that, The wireless communication device further includes: a processing module; The processing module is used to determine the information unit associated with each measurement unit in the at least one measurement unit according to a first power threshold. Wherein, the power of the information unit associated with each measurement unit in the at least one measurement unit is greater than the first power threshold, or the power of the information unit associated with each measurement unit in the at least one measurement unit is greater than or equal to the first power threshold.

30. The apparatus according to any one of claims 24 to 29, characterized in that, The wireless communication device further includes: a processing module; The processing module is used to determine the time delay information of the at least one measurement unit based on the reference time; wherein, the time delay information of the at least one measurement unit includes the difference between the time delay of the at least one measurement unit and the reference time.

31. The apparatus according to any one of claims 24 to 30, characterized in that, Before the wireless communication device receives the first information from the second device, the transmitting module is further configured to transmit capability information to the second device; The capability information is used to indicate at least one of the following: The wireless communication device supports the types of information units that can be reported. The wireless communication device supports the maximum number of information units that can be reported by a measurement unit associated with it. The wireless communication device supports at least one timing reporting granularity factor in channel sampling point-based reporting; The wireless communication device supports at least one timing reporting granularity factor in channel path-based reporting. The information unit type includes at least one of the following: channel sampling point, channel path.

32. A wireless communication device, characterized in that, include: A sending module is configured to send first information to a first device; wherein the first information is configured to indicate at least one of the following: a periodic reporting granularity factor K1, and a minimum reporting quantity N1 of information units; wherein K1 is an integer and N1 is a positive integer; A receiving module is configured to receive second information from the first device; wherein the second information is used for positioning based on an artificial intelligence (AI) model, and the second information includes at least one of the following: signal measurement information and location-related information; The signal measurement information includes at least one of the following: information of at least one measurement unit, quality information of the at least one measurement unit, timestamp associated with the at least one measurement unit, and first identifier associated with the at least one measurement unit; the location-related information includes at least one of the following: location tag, quality information of the location tag, and timestamp associated with the location tag; The information of the measurement unit includes at least one of the following: time delay information, power information, and phase information; The at least one measurement unit is determined based on the number of timed reporting granularity factor K2 and / or information unit reporting N2, where K2 is less than or equal to K1, N2 is greater than or equal to N1, K2 is an integer, and N2 is a positive integer. The first identifier is associated with the network environment information on the Radio Access Network (RAN) side.

33. The apparatus according to claim 32, characterized in that, The first information also includes at least one of the following: a list of candidate timed reporting granularity factors, and a list of the reporting quantities of candidate information units; Wherein, the timed reporting granularity factor K2 is determined based on the candidate timed reporting granularity factor list; and / or, the reporting quantity N2 of the information unit is determined based on the reporting quantity list of the candidate information units.

34. The apparatus according to claim 32, characterized in that, The sending module is also used to send third information to the first device; The third information includes at least one of the following: The first indication information is used to indicate the timed reporting granularity factor K2; The second instruction information is used to indicate the number N2 reported by the information unit; The third instruction is used to instruct a reduction in the timing reporting granularity factor. The fourth instruction is used to indicate the number of information units to be reported. The fifth indication information is used to indicate the difference or ratio between the timed reporting granularity factor K2 and the timed reporting granularity factor K1; The sixth indication information is used to indicate the difference or ratio between the reporting quantity N2 of the information unit and the minimum reporting quantity N1 of the information unit.

35. The apparatus according to claim 32, characterized in that, The minimum reporting quantity N1 of the information unit is determined based on the timed reporting granularity factor K1 and the first correlation relationship; or, the timed reporting granularity factor K1 is determined based on the minimum reporting quantity N1 of the information unit and the first correlation relationship; wherein, the first correlation relationship is the correlation between the timed reporting granularity factor and the minimum reporting quantity of the information unit; or, The number N2 of information units reported is determined based on the timed reporting granularity factor K2 and the second correlation; or, the timed reporting granularity factor K2 is determined based on the number N2 of information units reported and the second correlation; wherein, the second correlation is the correlation between the timed reporting granularity factor and the number of information units reported.

36. The apparatus according to any one of claims 32 to 35, characterized in that, Before the wireless communication device sends the first information to the first device, the receiving module is further configured to receive capability information from the first device; The capability information is used to indicate at least one of the following: The first device supports the reporting of various information unit types; The maximum number of information units that can be reported by a measurement unit associated with the first device; The first device supports at least one timing reporting granularity factor in channel sampling point-based reporting; The first device supports at least one timing reporting granularity factor in channel path-based reporting; The information unit type includes at least one of the following: channel sampling point, channel path.

37. A terminal, characterized in that, It includes a processor and a memory, the memory storing a program or instructions that can run on the processor, the program or instructions being executed by the processor to implement the steps of the wireless communication method as described in any one of claims 1 to 14.

38. A network-side device, characterized in that, It includes a processor and a memory, the memory storing a program or instructions that can run on the processor, the program or instructions being executed by the processor to implement the steps of the wireless communication method as described in any one of claims 15 to 23.

Images