Wireless channel assessment method and system

Abstract

The application discloses a wireless channel evaluation method and system, which is used to solve the technical problem of low efficiency of wireless channel evaluation. In the wireless channel evaluation scheme, based on the reference signal receiving power measurement data of the beam space and the position information of the single grid, a plurality of single grids with similar channel paths are determined to form a clustering set; and the joint channel path solving is performed on the clustering set, thereby improving the accuracy of channel characterization. Since only the reference signal receiving power is used instead of the channel matrix, the required calculation complexity is very low. The wireless channel evaluation method provided by the application can quickly and accurately model the statistical characteristics of the wireless channel in the localized communication scene, thereby quickly evaluating the wireless channel quality and improving the network optimization efficiency.

Description

Technical Field

[0001] This application relates to the field of communication technology, and in particular to a wireless channel evaluation method and system. Background Technology

[0002] A wireless channel is a mathematical description of the communication environment between a signal transmitter and a signal receiver. The characteristics of the channel determine the effectiveness and accuracy of information transmission, playing a decisive role in communication quality. Channel modeling is a crucial step in 5G network optimization. An accurate channel model empowers network optimization algorithms, enabling them to accurately perceive the channel quality of each user in the network topology and provide optimization strategies to ultimately improve overall communication quality.

[0003] In the process of developing the existing technology, the inventors discovered that:

[0004] Existing channel models include deterministic channel models. While deterministic channel models (such as the WINNER channel model and the IMT-advanced channel model) can accurately characterize the digital features of the channel, they often have numerous parameters, complex structures, and require a large amount of computing and storage resources.

[0005] For localized communication scenarios, deterministic channel models require modeling the channel matrix, which involves high computational complexity, low efficiency in wireless channel evaluation, and difficulty in meeting the response requirements of network optimization tasks.

[0006] Therefore, a new wireless channel evaluation scheme is needed to solve the technical problem of low efficiency in wireless channel evaluation. Summary of the Invention

[0007] This application provides a new wireless channel evaluation scheme to solve the technical problem of low efficiency in wireless channel evaluation.

[0008] Specifically, a wireless channel evaluation method includes the following steps:

[0009] The antenna array transmits a reference signal according to a preset antenna gain and transmit power;

[0010] The received power of the reference signal is obtained by single-grid measurement at a preset location;

[0011] Establish the correspondence between the received power of the reference signal and a single grid;

[0012] Based on the correspondence between the received power of the reference signal and a single grid, several single grids with similar channel paths are identified and form a cluster set.

[0013] By performing joint channel path solving on the cluster set, the angular power spectrum statistical characteristics of the cluster set are obtained;

[0014] The quality of wireless channels is assessed based on the angular power spectrum statistical characteristics of clustered sets.

[0015] Furthermore, the reference signal received power includes SSB-RSRP data and CSI-RSRP data;

[0016] The reference signal received power is obtained by single-grid measurement at a preset location, specifically including:

[0017] SSB-RSRP data of the reference signal are obtained by single-grid measurement at a preset location;

[0018] Using a predictive model, predict the CSI-RSRP data of the reference signal corresponding to a single grid at a preset location;

[0019] The prediction model is characterized as follows:

[0020]

[0021] In the formula, ξ represents the position of a single grid cell. This represents the CSI-RSRP data of the reference signal corresponding to a single grid position, where e indicates that it follows a Gaussian distribution. The noise is denoted by f, which represents the Gaussian process regression function.

[0022] Furthermore, based on the correspondence between the received power of the reference signal and a single grid, several single grids with similar channel paths are identified, forming a cluster set, specifically including:

[0023] Based on the correspondence between the received power of the reference signal and a single grid, determine the beam ID and amplitude of the corresponding single grid.

[0024] Several single grid cells with the same beam ID and the highest amplitude are used as elements to form a coarse aggregate;

[0025] Determine the number of elements in the coarse aggregate;

[0026] When the number of elements in a coarse cluster does not exceed a preset threshold, the coarse cluster is converted into a cluster set.

[0027] When the number of elements in a coarse aggregate exceeds a preset threshold, the three-dimensional features of a single grid cell in the coarse aggregate are determined.

[0028] Based on the three-dimensional features of a single grid, an iterative self-organizing clustering algorithm is used to converge coarse clusters into fine clusters, which are then used as cluster sets.

[0029] Furthermore, the correspondence between the received power of the reference signal and a single grid is as follows:

[0030] y l =A l xl

[0031] Where l represents a single grid cell. M represents the reference signal received power of a single grid l. l This indicates the number of RSRP beams obtained from a single grid measurement. Let N represent the coefficient matrix, and let N represent the sectional fraction of the angle domain in three-dimensional space. Indicates the channel path, and x l It is a sparse vector.

[0032] Furthermore, joint channel path solving is performed on the cluster set to obtain the angular power spectrum statistical characteristics of the cluster set, specifically including:

[0033] enter

[0034] definition These are the initial parameters;

[0035] according to

[0036] Calculate sparse vectors Statistical properties of power spectrum as a cluster set.

[0037] This application also provides a wireless channel evaluation system.

[0038] Specifically, a wireless channel assessment system includes:

[0039] Antenna array, used to transmit reference signals according to preset antenna gain and transmit power;

[0040] A wireless channel evaluation device is used to measure the received power of a reference signal at a preset location using a single grid; it is also used to establish a correspondence between the received power of the reference signal and the single grid; and it is also used to determine several single grids with similar channel paths based on the correspondence between the received power of the reference signal and the single grid, forming a cluster set.

[0041] It is also used to perform joint channel path solving on cluster sets to obtain the angular power spectrum statistical characteristics of the cluster sets; and to perform quality assessment of wireless channels based on the angular power spectrum statistical characteristics of the cluster sets.

[0042] Furthermore, the reference signal received power includes SSB-RSRP data and CSI-RSRP data;

[0043] The wireless channel evaluation device is used to obtain the reference signal received power by single-grid measurement at a preset location, specifically including:

[0044] SSB-RSRP data of the reference signal are obtained by single-grid measurement at a preset location;

[0045] Using a predictive model, predict the CSI-RSRP data of the reference signal corresponding to a single grid at a preset location;

[0046] The prediction model is characterized as follows:

[0047]

[0048] In the formula, ξ represents the position of a single grid cell. This represents the CSI-RSRP data of the reference signal corresponding to a single grid position, where e indicates that it follows a Gaussian distribution. The noise is denoted by f, which represents the Gaussian process regression function.

[0049] Furthermore, the wireless channel evaluation device is used to determine several single grids with similar channel paths based on the correspondence between the received power of the reference signal and a single grid, forming a cluster set, specifically including:

[0050] Based on the correspondence between the received power of the reference signal and a single grid, determine the beam ID and amplitude of the corresponding single grid.

[0051] Several single grid cells with the same beam ID and the highest amplitude are used as elements to form a coarse aggregate;

[0052] Determine the number of elements in the coarse aggregate;

[0053] When the number of elements in a coarse cluster does not exceed a preset threshold, the coarse cluster is converted into a cluster set.

[0054] When the number of elements in a coarse aggregate exceeds a preset threshold, the three-dimensional features of a single grid cell in the coarse aggregate are determined.

[0055] Based on the three-dimensional features of a single grid, an iterative self-organizing clustering algorithm is used to converge coarse clusters into fine clusters, which are then used as cluster sets.

[0056] Furthermore, the correspondence between the received power of the reference signal and a single grid is as follows:

[0057] y l =A l x l

[0058] Where l represents a single grid cell. M represents the reference signal received power of a single grid l. l This indicates the number of RSRP beams obtained from a single grid measurement. Let N represent the coefficient matrix, and let N represent the sectional fraction of the angle domain in three-dimensional space. Indicates the channel path, and x l It is a sparse vector.

[0059] Furthermore, the wireless channel evaluation device is used to perform joint channel path solving on the cluster set to obtain the angular power spectrum statistical characteristics of the cluster set, specifically including:

[0060] enter

[0061] definition These are the initial parameters;

[0062] according to

[0063] Calculate sparse vectors Statistical properties of power spectrum as a cluster set.

[0064] The technical solution provided in this application has at least the following beneficial effects:

[0065] Based on reference signal received power measurement data in beamspace and the location information of individual grids, several individual grids with similar channel paths are identified and formed into a cluster set. Joint channel path solving is then performed on the cluster set, improving the accuracy of channel characterization. Since only the reference signal received power is used instead of the channel matrix, the required computational complexity is very low. The wireless channel evaluation method provided in this application can perform fast and accurate modeling of wireless channel statistical characteristics in localized communication scenarios, thereby enabling rapid evaluation of wireless channel quality and improving network optimization efficiency. Attached Figure Description

[0066] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:

[0067] Figure 1 A flowchart illustrating a wireless channel evaluation method provided in an embodiment of this application;

[0068] Figure 2 A schematic diagram of the reference signal received power in the beam domain provided in an embodiment of this application;

[0069] Figure 3 A schematic diagram of the main lobe and side lobes of coefficient matrix A provided in an embodiment of this application;

[0070] Figure 4 This is a schematic diagram of the structure of a wireless channel evaluation system provided in an embodiment of this application.

[0071] The reference numerals in the figure are as follows:

[0072] 100 Wireless Channel Evaluation System

[0073] 11-antenna array

[0074] 12. Wireless channel evaluation device. Detailed Implementation

[0075] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below in conjunction with specific embodiments and corresponding drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0076] Please refer to Figure 1 To address the technical problem of low efficiency in wireless channel assessment, this application provides a wireless channel assessment method, comprising the following steps:

[0077] S110: The antenna array transmits a reference signal according to the preset antenna gain and transmit power.

[0078] It is understood that the antenna array is installed on a base station for transmitting wireless signals. Typically, the antenna array consists of several identical antenna elements arranged according to a certain pattern. The antenna array has preset engineering parameters such as antenna gain, antenna spacing, and transmit power.

[0079] To ensure communication quality, base stations typically use antenna arrays to transmit reference signals to determine which specific frequency ranges within the base station's coverage area have better quality, and thus prioritize their allocation to user terminals.

[0080] Specifically, the antenna array transmits reference signals based on preset antenna gain and transmit power to provide a reference for the base station's resource scheduling.

[0081] S120: Obtain the reference signal received power by measuring a single grid at a preset position.

[0082] It should be noted that, in order to improve the accuracy of channel modeling, this application further subdivides the coverage area of ​​the base station. Specifically, this application divides the coverage area of ​​the base station into a grid. In the application scenario where the base station is a 5G base station, since the coverage radius of a 5G base station is approximately 100-300 meters, the grid division of the base station's coverage area in this application can be represented as: subdividing the base station's coverage area into several 10-meter by 10-meter square grids.

[0083] Based on the gridded division of the base station coverage area, an antenna array reference coordinate system can be established. Then, based on this reference coordinate system, the coordinates of any single grid can be determined as its positional attribute. Furthermore, the positional attribute of any single grid can be defined using preset position coordinates (utmx, utmy). The received power of the reference signal can be measured at the location of each single grid to characterize the wireless channel.

[0084] Furthermore, the reference signal received power includes SSB-RSRP data and CSI-RSRP data;

[0085] The reference signal received power is obtained by single-grid measurement at a preset location, specifically including:

[0086] SSB-RSRP data of the reference signal are obtained by single-grid measurement at a preset location;

[0087] Using a predictive model, predict the CSI-RSRP data of the reference signal corresponding to a single grid at a preset location;

[0088] The prediction model is characterized as follows:

[0089]

[0090] In the formula, ξ represents the position of a single grid cell. This represents the CSI-RSRP data of the reference signal corresponding to a single grid position, where e indicates that it follows a Gaussian distribution. The noise is denoted by f, which represents the Gaussian process regression function.

[0091] It should be noted that in real-world communication scenarios, the reference signal received power (RSRP) data includes both CSI-RSRP data and SSB-RSRP data. SSB-RSRP data can be measured at any single grid location, while CSI-RSRP data can only be measured at certain single grid locations.

[0092] To obtain CSI-RSRP data corresponding to a single grid at any location, this application employs a prediction model to predict the CSI-RSRP data of the reference signal corresponding to a single grid at any location. Specifically, the prediction model is a Gaussian process regression model.

[0093] The following describes the implementation process of using a predictive model to provide CSI-RSRP predictions for grids where CSI beams have not been measured:

[0094] Let the coordinates of a single grid cell (utmx, utmy) measured to CSI-RSRP be Ξ = [ξ1, ξ2, ... ξ]. l , …, ξ L ].in The corresponding CSI-RSRPs are respectively The training set is Learning ξ using a Gaussian process regression model l arrive Mapping relationship:

[0095]

[0096] Where e represents the independent variables that follow a Gaussian distribution. The noise is denoted by f, which is the Gaussian process regression function, and its covariance matrix is ​​the Gaussian kernel function.

[0097]

[0098] in These are the parameters to be learned.

[0099] Assume the position to be estimated is ξ * The RSRP value is The corresponding posterior probability is

[0100]

[0101] The mean and variance can be expressed as:

[0102] E(f(ξ * ))=K(ξ * ,Ξ)C -1 Y,

[0103] Cov(f(ξ * ))=K(ξ * ξ * )-K(ξ * Ξ)C -1 K(Ξ,ξ * ),

[0104]

[0105] Furthermore, matrix C is a function of the hyperparameter θ, and the marginal likelihood function is

[0106]

[0107] To obtain the optimal parameters, this application maximizes the likelihood function, that is, minimizes the following function:

[0108]

[0109] Wherein, the partial derivative of the i-th variable of the hyperparameter θ is

[0110]

[0111] Thus, for a single grid that can measure the CSI beam, a Gaussian process regression model is used to learn the mapping relationship between its position coordinates (utmx, utmy) and CSI-RSRP data;

[0112] For single grid cells where the CSI beam cannot be measured, their position coordinates are input into a learned Gaussian process regression model, and the learned Gaussian process regression model is used to predict their CSI-RSRP value.

[0113] S130: Establish the correspondence between the received power of the reference signal and a single grid.

[0114] It is understood that the channel environment of a wireless channel can be characterized by large-scale fading (path loss, shadowing fading) or small-scale fading. In a preferred embodiment provided in this application, large-scale fading is used to characterize the channel environment of an arbitrary grid.

[0115] Furthermore, to reduce the dimensionality complexity of the channel impulse response, this application considers the reference signal received power in the beam space. Based on the gridded division of the base station's coverage area, it is assumed that the channel matrix from the antenna array to the l-th grid is... The precoding matrix of the k-th beam is So if Figure 2 As shown, the reference signal received power from the k-th beam to the l-th grid can be expressed as:

[0116]

[0117] Where P represents the transmit power. Further expansion of rsrp l，k achievable

[0118]

[0119] By taking the expectation of time t on both sides of the above equation, we can obtain

[0120]

[0121] In the formula, N V N represents the total number of divisions of the vertical plane in the angular domain. H RSRP represents the total number of divisions of the horizontal plane in the angular domain. l,k Indicates the received power of the reference signal. Represents the coefficient matrix. This represents the angular power spectrum statistical characteristics of a wireless channel;

[0122] in,

[0123]

[0124]

[0125] The main lobe and side lobes of coefficient matrix A are as follows: Figure 3 As shown, the path between the antenna array and the grid can only exist at the angles corresponding to the main lobe and the side lobe.

[0126] Thus, this application establishes the statistical relationship between the received power of the low-dimensional reference signal and the angular power spectrum of the wireless channel. For any single grid, the correspondence between the received power of the reference signal and the single grid is as follows:

[0127] y l =A l x l Where l represents the raster number of a single raster. M represents the reference signal received power (RSRP) of a single grid l. l This indicates the number of RSRP beams obtained from a single grid measurement. Let N represent the coefficient matrix, and let N represent the sectional fraction of the angle domain in three-dimensional space. Indicates the channel path, and x l It is a sparse vector. Specifically, the sparse vector x l The number of non-zero elements does not exceed 10, and the number of corresponding channel paths does not exceed 10.

[0128] S140: Based on the correspondence between the received power of the reference signal and the single grid, determine several single grids with similar channel paths to form a cluster set.

[0129] Understandably, the inventors discovered that the channels of several adjacent single grids have similar characteristics. In order to more accurately characterize the real channel environment, this application forms a cluster set of several single grids with similar channel paths.

[0130] Furthermore, based on the correspondence between the received power of the reference signal and a single grid, several single grids with similar channel paths are identified, forming a cluster set, specifically including:

[0131] Based on the correspondence between the received power of the reference signal and a single grid, determine the beam ID and amplitude of the corresponding single grid.

[0132] Several single grid cells with the same beam ID and the highest amplitude are used as elements to form a coarse aggregate;

[0133] Determine the number of elements in the coarse aggregate;

[0134] When the number of elements in a coarse cluster does not exceed a preset threshold, the coarse cluster is converted into a cluster set.

[0135] When the number of elements in a coarse aggregate exceeds a preset threshold, the three-dimensional features of a single grid cell in the coarse aggregate are determined.

[0136] Based on the three-dimensional features of a single grid, an iterative self-organizing clustering algorithm is used to converge coarse clusters into fine clusters, which are then used as cluster sets.

[0137] It should be noted that, in specific application scenarios, the preset threshold is preferably 5. That is, if the number of individual grid cells in the coarse cluster is less than or equal to 5, the coarse cluster is converted into a cluster set; if the number of individual grid cells in the coarse cluster is greater than 5, the individual grid cells in that class are clustered again.

[0138] The clustering of individual lattices in the coarse clusters is as follows:

[0139] The three-dimensional features of individual graticules in the coarse cluster are determined as input data for the iterative self-organizing clustering algorithm ISODATA. This process continues until the individual graticules in the coarse cluster converge. The output is then a fine cluster consisting of the converged individual graticules, which serves as the cluster set.

[0140] Among them, the three-dimensional features of a single raster are represented by the position coordinates (utmx, utmy) and the strongest RSRP value of the single raster.

[0141] S150: Perform joint channel path solving on the cluster set to obtain the angular power spectrum statistical characteristics of the cluster set.

[0142] Understandably, the angular power spectrum is a statistical characteristic of channel fading at large scales and can be used to characterize the environment. Specifically, the angular power spectrum is a sparse vector whose dimension is the number of equal divisions of the angle. The positions of the non-zero elements correspond to the departure angles of the channel multipath, and the values ​​of the non-zero elements correspond to the channel gain of each path.

[0143] It should be noted that although step S130 has established the correspondence between the reference signal received power and a single grid, y l =A l x l However, this relationship applies to a single grid.

[0144] Based on the cluster set formed in step S140, in order to more accurately characterize the real channel environment, this application adopts the weighted non-negative orthogonal matching pursuit (WNOMP) method to jointly solve the channel path for the cluster set.

[0145] This is because the coefficient matrix A contains some columns with large amplitudes, which can affect the accuracy of finding non-zero elements. The weighted non-negative orthogonal matching pursuit method can introduce dynamic weights λ. k This reduces the impact of columns with large amplitude.

[0146] Furthermore, joint channel path solving is performed on the cluster set to obtain the angular power spectrum statistical characteristics of the cluster set, specifically including:

[0147] enter

[0148] definition These are the initial parameters;

[0149] according to

[0150] Calculate sparse vectors Statistical properties of power spectrum as a cluster set.

[0151] The calculation process is as follows:

[0152]

[0153] S160: Based on the angular power spectrum statistical characteristics of the wireless channel, perform a quality assessment of the wireless channel.

[0154] Understandably, based on the angular power spectrum statistical characteristics of the wireless channel, a channel quality assessment can be performed, generating a channel quality assessment result. After obtaining the channel quality assessment result, the base station can select an appropriate scheduling algorithm and downlink data block size to ensure that the user terminal obtains the best downlink performance in different wireless environments.

[0155] In summary, the wireless channel assessment method provided in this application, based on the reference signal received power (RSRP) measurement data in the beamspace and the location information of individual grids, identifies several individual grids with similar channel paths, forming a cluster set; and then performs joint channel path solving on the cluster set, improving the accuracy of channel characterization. Since only the reference signal received power is used instead of the channel matrix, the required computational complexity is very low. In localized communication scenarios, the wireless channel assessment method provided in this application can perform fast and accurate modeling of wireless channel statistical characteristics, thereby enabling rapid assessment of wireless channel quality and improving network optimization efficiency.

[0156] Please refer to Figure 4 To support wireless channel evaluation methods, this application also provides a wireless channel evaluation system 100, comprising:

[0157] Antenna array 11 is used to transmit reference signals according to preset antenna gain and transmit power;

[0158] The wireless channel evaluation device 12 is used to measure the received power of a reference signal at a preset location using a single grid; it is also used to establish a correspondence between the received power of the reference signal and the single grid; it is also used to determine several single grids with similar channel paths based on the correspondence between the received power of the reference signal and the single grid, forming a cluster set; it is also used to perform joint channel path solving on the cluster set to obtain the angular power spectrum statistical characteristics of the cluster set; and it is also used to evaluate the quality of the wireless channel based on the angular power spectrum statistical characteristics of the cluster set.

[0159] It is understood that the antenna array 11 is installed on a base station for transmitting wireless signals. Typically, the antenna array 11 consists of several identical antenna elements arranged according to a certain pattern. The antenna array 11 has preset engineering parameters such as antenna gain, antenna spacing, and transmit power.

[0160] To ensure communication quality, base stations typically use antenna array 11 to transmit reference signals to determine which specific frequency ranges within the base station's coverage area have better quality, and thus prioritize their allocation to user terminals.

[0161] Specifically, the antenna array 11 transmits reference signals according to preset antenna gain and transmission power to provide a reference for the scheduling resources of the base station.

[0162] The wireless channel evaluation device 12 obtains the reference signal received power by measuring a single grid at a preset location.

[0163] It should be noted that, in order to improve the accuracy of channel modeling, this application further subdivides the coverage area of ​​the base station. Specifically, this application divides the coverage area of ​​the base station into a grid. In the application scenario where the base station is a 5G base station, since the coverage radius of a 5G base station is approximately 100-300 meters, the grid division of the base station's coverage area in this application can be represented as: subdividing the base station's coverage area into several 10-meter by 10-meter square grids.

[0164] Based on the gridded division of the base station's coverage area, the wireless channel evaluation device 12 can establish a reference coordinate system for the antenna array 11. Then, based on the antenna array 11 reference coordinate system, the coordinates of any single grid can be determined as the positional attribute of that single grid. Furthermore, the wireless channel evaluation device 12 can define the positional attribute of any single grid using preset position coordinates (utmx, utmy). The received power of the reference signal can be measured at the location of each single grid to characterize the wireless channel.

[0165] Furthermore, the reference signal received power includes SSB-RSRP data and CSI-RSRP data;

[0166] The wireless channel evaluation device 12 is used to obtain the reference signal received power by single-grid measurement at a preset location, specifically including:

[0167] SSB-RSRP data of the reference signal are obtained by single-grid measurement at a preset location;

[0168] Using a predictive model, predict the CSI-RSRP data of the reference signal corresponding to a single grid at a preset location;

[0169] The prediction model is characterized as follows:

[0170]

[0171] In the formula, ξ represents the position of a single grid cell. This represents the CSI-RSRP data of the reference signal corresponding to a single grid position, where e indicates that it follows a Gaussian distribution. The noise is denoted by f, which represents the Gaussian process regression function.

[0172] It should be noted that in real communication scenarios, the reference signal received power (RSRP) data includes CSI-RSRP data and SSB-RSRP data. The wireless channel evaluation device 12 can measure SSB-RSRP data at any single grid location, but can only measure CSI-RSRP data at certain single grid locations.

[0173] To obtain the CSI-RSRP data corresponding to a single grid at any location, the wireless channel evaluation device 12 employs a prediction model to predict the CSI-RSRP data of the reference signal corresponding to a single grid at any location. Specifically, the prediction model is a Gaussian process regression model.

[0174] The following describes the implementation process of the wireless channel evaluation device 12 using a prediction model to provide CSI-RSRP prediction values ​​for grids where CSI beams have not been measured:

[0175] Let the coordinates of a single grid cell (utmx, utmy) measured to CSI-RSRP be Ξ = [ξ1, ξ2, ..., ξ]. l , …, ξ L ].in The corresponding CSI-RSRPs are respectively The training set is Learning ξ using a Gaussian process regression model l arrive Mapping relationship:

[0176]

[0177] Where e represents the independent variables that follow a Gaussian distribution. The noise is denoted by f, which is the Gaussian process regression function, and its covariance matrix is ​​the Gaussian kernel function.

[0178]

[0179] in These are the parameters to be learned.

[0180] Assume the position to be estimated is ξ * The RSRP value is The corresponding posterior probability is

[0181]

[0182] The mean and variance can be expressed as:

[0183] E(f(ξ * ))=K(ξ * ,Ξ)C -1 Y,

[0184] Cov(f(ξ * ))=K(ξ * ξ * )-K(ξ * ,Ξ)C -1 K(Ξ,ξ * ),

[0185]

[0186] Furthermore, matrix C is a function of the hyperparameter θ, and the marginal likelihood function is

[0187]

[0188] To obtain the optimal parameters, this application maximizes the likelihood function, that is, minimizes the following function:

[0189]

[0190] Wherein, the partial derivative of the i-th variable of the hyperparameter θ is

[0191]

[0192] In this way, the wireless channel evaluation device 12 uses a Gaussian process regression model to learn the mapping relationship between the location coordinates (utmx, utmy) and CSI-RSRP data for a single grid that can measure the CSI beam.

[0193] For a single grid where the CSI beam cannot be measured, the wireless channel evaluation device 12 inputs its location coordinates into a learned Gaussian process regression model and uses the learned Gaussian process regression model to predict its CSI-RSRP value.

[0194] The wireless channel evaluation device 12 then establishes the correspondence between the reference signal received power and a single grid.

[0195] It is understood that the channel environment of a wireless channel can be characterized by large-scale fading (path loss, shadowing fading) or small-scale fading. In a preferred embodiment provided in this application, the wireless channel evaluation device 12 uses large-scale fading to characterize the channel environment of an arbitrary grid.

[0196] Furthermore, to reduce the dimensionality complexity of the channel impulse response, this application considers the reference signal received power in the beam space. Based on the gridded division of the base station's coverage area, it is assumed that the channel matrix from the antenna array to the l-th grid is... The precoding matrix of the k-th beam is So if Figure 2 As shown, the reference signal received power from the k-th beam to the l-th grid can be expressed as:

[0197]

[0198] Where P represents the transmit power. Further expansion of rsrp l，k (t) can be obtained

[0199]

[0200] By taking the expectation of time t on both sides of the above equation, we can obtain

[0201]

[0202] In the formula, N V N represents the total number of divisions of the vertical plane in the angular domain. H RSRP represents the total number of divisions of the horizontal plane in the angular domain. l,k Indicates the received power of the reference signal. Represents the coefficient matrix. This represents the angular power spectrum statistical characteristics of a wireless channel;

[0203] in,

[0204]

[0205]

[0206] The main lobe and side lobes of coefficient matrix A are as follows: Figure 3 As shown, the path between the antenna array and the grid can only exist at the angles corresponding to the main lobe and the side lobe.

[0207] Thus, this application establishes the statistical relationship between the received power of the low-dimensional reference signal and the angular power spectrum of the wireless channel. For any single grid, the correspondence between the received power of the reference signal and the single grid is as follows:

[0208] y l =A l x l

[0209] Where l represents the raster number of a single raster. M represents the reference signal received power (RSRP) of a single grid l. l This indicates the number of RSRP beams obtained from a single grid measurement. Let N represent the coefficient matrix, and let N represent the sectional fraction of the angle domain in three-dimensional space. Indicates the channel path, and x l It is a sparse vector. Specifically, the sparse vector x l The number of non-zero elements does not exceed 10, and the number of corresponding channel paths does not exceed 10.

[0210] Then, the wireless channel evaluation device 12 determines several single grids with similar channel paths based on the correspondence between the reference signal received power and the single grid, forming a cluster set.

[0211] Understandably, the inventors discovered that the channels of several adjacent single grids have similar characteristics. In order to more accurately characterize the real channel environment, the wireless channel evaluation device 12 forms a cluster set of several single grids with similar channel paths.

[0212] Furthermore, the wireless channel evaluation device 12 is used to determine several single grids with similar channel paths based on the correspondence between the received power of the reference signal and the single grid, forming a cluster set, specifically including:

[0213] Based on the correspondence between the received power of the reference signal and a single grid, determine the beam ID and amplitude of the corresponding single grid.

[0214] Several single grid cells with the same beam ID and the highest amplitude are used as elements to form a coarse aggregate;

[0215] Determine the number of elements in the coarse aggregate;

[0216] When the number of elements in a coarse cluster does not exceed a preset threshold, the coarse cluster is converted into a cluster set.

[0217] When the number of elements in a coarse aggregate exceeds a preset threshold, the three-dimensional features of a single grid cell in the coarse aggregate are determined.

[0218] Based on the three-dimensional features of a single grid, an iterative self-organizing clustering algorithm is used to converge coarse clusters into fine clusters, which are then used as cluster sets.

[0219] It should be noted that, in specific application scenarios, the preset threshold is preferably 5. That is, if the number of individual grids in the coarse cluster is less than or equal to 5, the wireless channel evaluation device 12 will divide the coarse cluster into a cluster set; if the number of individual grids in the coarse cluster is greater than 5, the wireless channel evaluation device 12 will cluster the individual grids in that class again.

[0220] The wireless channel evaluation device 12 performs further clustering on the single grid cells in the coarse cluster, as follows:

[0221] The three-dimensional features of individual graticules in the coarse cluster are determined as input data for the iterative self-organizing clustering algorithm ISODATA. This process continues until the individual graticules in the coarse cluster converge. The output is then a fine cluster consisting of the converged individual graticules, which serves as the cluster set.

[0222] Among them, the three-dimensional features of a single raster are represented by the position coordinates (utmx, utmy) and the strongest RSRP value of the single raster.

[0223] Then, the wireless channel evaluation device 12 performs joint channel path solving on the cluster set to obtain the angular power spectrum statistical characteristics of the cluster set.

[0224] Understandably, the angular power spectrum is a statistical characteristic of channel fading at large scales and can be used to characterize the environment. Specifically, the angular power spectrum is a sparse vector whose dimension is the number of equal divisions of the angle. The positions of the non-zero elements correspond to the departure angles of the channel multipath, and the values ​​of the non-zero elements correspond to the channel gain of each path.

[0225] It should be noted that although the wireless channel evaluation device 12 has established the correspondence between the reference signal received power and a single grid in the above steps, l =A l x l However, this relationship applies to a single grid.

[0226] Based on the cluster set formed by the wireless channel evaluation device 12, in order to more accurately characterize the real channel environment, the wireless channel evaluation device 12 adopts the weighted non-negative orthogonal matching pursuit (WNOMP) method to jointly solve the channel path for the cluster set.

[0227] This is because the coefficient matrix A contains some columns with large amplitudes, which can affect the accuracy of finding non-zero elements. The weighted non-negative orthogonal matching pursuit method can introduce dynamic weights λ. k This reduces the impact of columns with large amplitude.

[0228] Furthermore, the wireless channel evaluation device 12 is used to perform joint channel path solving on the cluster set to obtain the angular power spectrum statistical characteristics of the cluster set, specifically including:

[0229] enter

[0230] definition These are the initial parameters;

[0231] according to

[0232] Calculate sparse vectors Statistical properties of power spectrum as a cluster set.

[0233] The calculation process is as follows:

[0234]

[0235] Finally, the wireless channel evaluation device 12 evaluates the quality of the wireless channel based on the angular power spectrum statistical characteristics of the wireless channel.

[0236] Understandably, the wireless channel evaluation device 12 can perform quality assessment on the wireless channel based on the angular power spectrum statistical characteristics of the wireless channel, and generate channel quality assessment results. After obtaining the channel quality assessment results, the base station can select an appropriate scheduling algorithm and downlink data block size to ensure that the user terminal obtains the best downlink performance in different wireless environments.

[0237] In summary, the wireless channel assessment system 100 provided in this application, based on the reference signal received power (RSRP) measurement data in the beamspace and the location information of individual grids, identifies several individual grids with similar channel paths, forming a cluster set; and performs joint channel path solving on the cluster set, improving the accuracy of channel characterization. Since only the reference signal received power is used instead of the channel matrix, the required computational complexity is very low. The wireless channel assessment method provided in this application can perform fast and accurate modeling of wireless channel statistical characteristics in localized communication scenarios, thereby enabling rapid assessment of wireless channel quality and improving network optimization efficiency.

[0238] It should be noted that 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 process, method, article, or apparatus. Unless otherwise specified, 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 said element.

[0239] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0240] The above description is merely an embodiment of this application and is not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. A wireless channel evaluation method, characterized in that, Includes the following steps: The antenna array transmits a reference signal according to a preset antenna gain and transmit power; The received power of the reference signal is obtained by single-grid measurement at a preset location; Establish the correspondence between the received power of the reference signal and a single grid; Based on the correspondence between the received power of the reference signal and a single grid, several single grids with similar channel paths are identified and form a cluster set. By performing joint channel path solving on the cluster set, the angular power spectrum statistical characteristics of the cluster set are obtained; The quality of the wireless channel is assessed based on the angular power spectrum statistical characteristics of the cluster set; The correspondence between the received power of the reference signal and a single grid is as follows: ; in Indicates a single grid. Represents a single grid Reference signal received power, Represents a single grid The number of RSRP beams obtained by measurement Represents the coefficient matrix. Represents the tangents of the angle domain in three-dimensional space. Indicates the channel path, and It is a sparse vector; Specifically, joint channel path solving is performed on the cluster set to obtain the angular power spectrum statistical characteristics of the cluster set, including: enter ; definition These are the initial parameters; according to ; Calculate sparse vectors , as the angular power spectrum statistical characteristics of the cluster set.

2. The wireless channel evaluation method as described in claim 1, characterized in that, The reference signal received power includes SSB-RSRP data and CSI-RSRP data; The reference signal received power is obtained by single-grid measurement at a preset location, specifically including: SSB-RSRP data of the reference signal are obtained by single-grid measurement at a preset location; Using a predictive model, predict the CSI-RSRP data of the reference signal corresponding to a single grid at a preset location; The prediction model is characterized as follows: ； In the formula, Indicates the position of a single grid cell. CSI-RSRP data representing the reference signal corresponding to a single grid position. Indicates that it follows a Gaussian distribution noise, This represents the Gaussian process regression function.

3. The wireless channel evaluation method as described in claim 1, characterized in that, Based on the correspondence between the received power of the reference signal and a single grid, several single grids with similar channel paths are identified, forming a cluster set, specifically including: Based on the correspondence between the received power of the reference signal and a single grid, determine the beam ID and amplitude of the corresponding single grid. Several single grid cells with the same beam ID and the highest amplitude are used as elements to form a coarse aggregate; Determine the number of elements in the coarse aggregate; When the number of elements in a coarse cluster does not exceed a preset threshold, the coarse cluster is converted into a cluster set. When the number of elements in a coarse aggregate exceeds a preset threshold, the three-dimensional features of a single grid cell in the coarse aggregate are determined. Based on the three-dimensional features of a single grid, an iterative self-organizing clustering algorithm is used to converge coarse clusters into fine clusters, which are then used as cluster sets.

4. A wireless channel evaluation system, characterized in that, include: Antenna array, used to transmit reference signals according to preset antenna gain and transmit power; A wireless channel evaluation device is used to measure the received power of a reference signal at a preset location using a single grid; it is also used to establish a correspondence between the received power of the reference signal and the single grid; based on the correspondence between the received power of the reference signal and the single grid, it is used to determine several single grids with similar channel paths, forming a cluster set; it is also used to perform joint channel path solving on the cluster set to obtain the angular power spectrum statistical characteristics of the cluster set; and it is also used to evaluate the quality of the wireless channel based on the angular power spectrum statistical characteristics of the cluster set. The correspondence between the received power of the reference signal and a single grid is as follows: ； in Indicates a single grid. Represents a single grid Reference signal received power, Represents a single grid The number of RSRP beams obtained by measurement Represents the coefficient matrix. Represents the tangents of the angle domain in three-dimensional space. Indicates the channel path, and It is a sparse vector; The wireless channel evaluation device is used to perform joint channel path solving on the cluster set to obtain the angular power spectrum statistical characteristics of the cluster set, specifically including: enter ; definition These are the initial parameters; according to ; Calculate sparse vectors , as the angular power spectrum statistical characteristics of the cluster set.

5. The wireless channel evaluation system as described in claim 4, characterized in that, The reference signal received power includes SSB-RSRP data and CSI-RSRP data; The wireless channel evaluation device is used to obtain the reference signal received power by single-grid measurement at a preset location, specifically including: SSB-RSRP data of the reference signal are obtained by single-grid measurement at a preset location; Using a predictive model, predict the CSI-RSRP data of the reference signal corresponding to a single grid at a preset location; The prediction model is characterized as follows: ; In the formula, Indicates the position of a single grid cell. CSI-RSRP data representing the reference signal corresponding to a single grid position. It indicates that it follows a Gaussian distribution. noise, This represents the Gaussian process regression function.

6. The wireless channel evaluation system as described in claim 4, characterized in that, The wireless channel evaluation device is used to determine several single grids with similar channel paths, forming a cluster set, based on the correspondence between the received power of the reference signal and a single grid. Specifically, it includes: Based on the correspondence between the received power of the reference signal and a single grid, determine the beam ID and amplitude of the corresponding single grid. Several single grid cells with the same beam ID and the highest amplitude are used as elements to form a coarse aggregate; Determine the number of elements in the coarse aggregate; When the number of elements in a coarse cluster does not exceed a preset threshold, the coarse cluster is converted into a cluster set. When the number of elements in a coarse aggregate exceeds a preset threshold, the three-dimensional features of a single grid cell in the coarse aggregate are determined. Based on the three-dimensional features of a single grid, an iterative self-organizing clustering algorithm is used to converge coarse clusters into fine clusters, which are then used as cluster sets.

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