A radio prediction analysis method and system

Abstract

The application relates to a radio prediction analysis method and system, and relates to the technical field of radio detection. In the method, geographical environment data of a target area and measured signal data of a monitoring station are first acquired, including field strength values, angles of arrival and multipath time delay parameters. By constructing a three-dimensional propagation environment model and performing ray tracing calculation, predicted and measured field strength values are compared to identify mismatched monitoring stations. For the mismatched stations, reverse ray tracing is performed based on the angles of arrival and the multipath time delay parameters to determine an environment area to be checked. Cluster analysis is performed on the area to be checked to determine a correction unit, environment parameters are corrected according to field strength deviation values, and the model is updated. Finally, the updated model is used to evaluate the performance of multiple candidate deployment schemes to select an optimal scheme. The technical scheme provided by the application can improve the accuracy of radio propagation detection.

Description

Technical Field

[0001] This application relates to the field of radio detection technology, specifically to a radio prediction and analysis method, system, medium, and product. Background Technology

[0002] With the continuous growth in demand for radio communications from fields such as broadcast television network planning, military communication deployment, public spectrum management, and wireless equipment manufacturing, the planning and deployment of radio stations has become increasingly important. To ensure the efficient and reliable operation of wireless equipment, accurate prediction of radio signal propagation characteristics is necessary during station planning. This is particularly crucial in complex terrain environments, where accurate propagation characteristic prediction is essential for optimizing station deployment.

[0003] Currently, commonly used radio propagation prediction methods are mainly based on ray tracing technology. This involves establishing a three-dimensional environmental model and simulating electromagnetic wave propagation to predict signal coverage. This method pre-sets the electromagnetic parameters of the environmental model and combines this with ray tracing algorithms to calculate the signal field strength distribution, providing a theoretical basis for developing station deployment plans.

[0004] However, in practical applications, it has been found that due to the numerous geographical elements in complex terrain environments and the differences in the electromagnetic properties of various land features, propagation predictions based solely on pre-set environmental models often deviate significantly from the actual situation. This prediction bias reduces the reliability of station planning schemes, increases the workload of subsequent adjustments and optimizations, and affects the deployment efficiency of communication systems. Therefore, improving the accuracy of radio propagation detection in complex environments, and thus optimizing station deployment schemes, is a pressing technical problem that needs to be solved. Summary of the Invention

[0005] This application provides a radio prediction analysis method, system, medium, and product that can improve the accuracy of radio propagation detection.

[0006] The first aspect of this application provides a radio prediction analysis method, comprising: The system acquires geographic environmental data of the target area and measured signal data from multiple monitoring stations. The measured signal data includes the measured field strength value, signal angle of arrival, and multipath delay spread parameters received by each monitoring station. A three-dimensional propagation environment model is constructed based on the geographic environment data, and ray tracing calculations are performed in the three-dimensional propagation environment model based on preset emission source parameters to obtain the predicted field strength value of each monitoring station. The predicted field strength value of each monitoring station is compared with the corresponding measured field strength value to determine the mismatched monitoring station whose field strength deviation value exceeds a preset threshold. For the mismatch monitoring station, the signal propagation direction is determined based on the signal arrival angle, and the propagation distance of the propagation path is determined according to the multipath delay spread parameter; Combining the propagation direction and the propagation distance, reverse ray tracing is performed starting from the location of the mismatch monitoring station. The intersection of the reverse ray with the geographical elements in the three-dimensional propagation environment model is determined as the area to be verified in the environment. Cluster analysis is performed on the environmental area to be verified to determine the environmental correction unit. The environmental parameters of the environmental correction unit are corrected according to the field strength deviation value, and the correction results are updated to the three-dimensional propagation environment model. Using the updated three-dimensional propagation environment model, ray tracing calculations are performed on multiple preset candidate station deployment schemes to obtain field strength distribution maps. Based on the field strength distribution maps, the preset candidate station deployment scheme with the best radio performance is determined as the target scheme.

[0007] By adopting the above technical solution, an initial three-dimensional propagation environment model is first constructed based on the geographic environmental data of the target area. This model is then compared and analyzed with measured signal data from multiple monitoring stations to promptly identify mismatched monitoring stations where the predicted field strength values ​​deviate significantly from the measured values. By analyzing the signal arrival angle and multipath delay spread parameters of the mismatched monitoring stations, the signal propagation direction and distance are determined. Reverse ray tracing technology can accurately locate the environmental areas requiring verification that cause prediction deviations. Furthermore, cluster analysis is used to determine environmental correction units, and environmental parameters are specifically corrected based on the field strength deviation values, achieving dynamic optimization and calibration of the propagation environment model. Finally, ray tracing calculations using the optimized propagation environment model improve the accuracy of radio propagation prediction.

[0008] Optionally, the signal arrival angle of the main path signal received by the mismatch monitoring station is obtained, and the components of the signal arrival angle in the horizontal and vertical planes are respectively used as the azimuth and elevation angles. Based on the azimuth and elevation angles, the propagation direction from the mismatch monitoring station to the transmission source is determined as the signal propagation direction. Multiple delay peaks are extracted from the multipath delay spread parameters, wherein each delay peak corresponds to a propagation path. Based on the delay difference between the delay peak corresponding to each propagation path and the earliest arrival delay peak, the additional propagation time of the propagation path relative to the shortest path is determined. Based on the additional propagation time and the propagation speed of electromagnetic waves in the current frequency band, the additional propagation distance of the propagation path relative to the shortest path is calculated, and the additional propagation distance is added to the shortest path distance to obtain the propagation distance of the corresponding propagation path.

[0009] Optionally, the electromagnetic wave propagation speed is determined according to the operating frequency in the preset emission source parameters; the relative propagation speed correction coefficient of the electromagnetic wave in different media is obtained according to the medium type of the region through which the propagation path passes in the three-dimensional propagation environment model; the additional propagation time is segmented according to the different medium regions through which the propagation path passes, and the additional propagation distance of the corresponding segment is calculated using the relative propagation speed correction coefficient of the corresponding medium for each segment; the additional propagation distances of all segments are summed to obtain the additional propagation distance of the propagation path relative to the shortest path.

[0010] Optionally, starting from the location of the mismatch monitoring station, a tracking ray is emitted in the opposite direction to the signal propagation direction; the effective search range of the tracking ray is determined according to the propagation distance, and the intersection points of the tracking ray with the building surface, terrain undulation surface, and vegetation cover surface in the three-dimensional propagation environment model are detected within the effective search range; the three-dimensional coordinates and geographic feature type of each intersection point are obtained; for each intersection point, the corresponding scale of the scope to be verified is determined according to the geographic feature type, and a spatial region corresponding to the scale of the scope to be verified is established with the three-dimensional coordinates of the intersection point as the center as the environmental verification area.

[0011] Optionally, the spatial distance between any two environmental areas to be verified is calculated; the environmental areas to be verified with a spatial distance less than a preset clustering radius are divided into the same candidate correction unit; the number of mismatch monitoring stations traced back to each candidate correction unit is obtained, and the number of mismatch monitoring stations is used as the environmental distortion degree of the corresponding candidate correction unit; and candidate correction units with environmental distortion degrees higher than a preset distortion threshold are selected as environmental correction units.

[0012] Optionally, for each of the environmental correction units, the average field strength deviation of all mismatch monitoring stations traced back to the environmental correction unit is obtained; an adjustment amount is determined based on the absolute value of the average field strength deviation, and the direction of environmental parameter adjustment is determined based on the positive or negative direction of the average field strength deviation; the environmental parameters of the environmental correction unit are adjusted according to the environmental parameter adjustment direction and the adjustment amount, the environmental parameters including building height parameters, surface roughness parameters, and medium electromagnetic property parameters; the adjusted environmental parameters are then updated to the position of the corresponding environmental correction unit in the three-dimensional propagation environment model.

[0013] Optionally, based on the field strength distribution map, areas with field strength higher than the receiving threshold value in each of the preset candidate station deployment schemes are extracted as effective coverage areas, and the coverage rate is obtained by calculating the ratio of the area of ​​the effective coverage area to the total area of ​​the target area; areas in each of the preset candidate station deployment schemes that simultaneously receive signals from multiple transmitters and whose signal strength difference is less than the protection ratio are extracted as interference areas, and the interference area ratio is obtained by calculating the ratio of the area of ​​the interference area to the area of ​​the effective coverage area; the spectrum utilization efficiency is calculated based on the unit spectrum bandwidth and the corresponding effective coverage area area in each of the preset candidate station deployment schemes; the coverage rate, interference area ratio, and spectrum utilization efficiency of each of the preset candidate station deployment schemes are weighted and calculated to obtain a radio performance evaluation value, and the preset candidate station deployment scheme with the highest radio performance evaluation value is selected as the target scheme.

[0014] In a second aspect, embodiments of this application provide a radio prediction analysis system, which includes: one or more processors and a memory; the memory is coupled to the one or more processors, and the memory is used to store computer program code, which includes computer instructions, and the one or more processors call the computer instructions to cause the radio prediction analysis system to perform the methods described in the first aspect and any possible implementation thereof.

[0015] Thirdly, embodiments of this application provide a computer-readable storage medium including instructions that, when executed on a radio prediction analysis system, cause the radio prediction analysis system to perform the method described in the first aspect and any possible implementation thereof.

[0016] Fourthly, embodiments of this application provide a computer program product containing instructions that, when the computer program product is run on a radio prediction analysis system, cause the radio prediction analysis system to perform the method described in the first aspect and any possible implementation thereof.

[0017] In summary, one or more technical solutions provided in this application have at least the following technical effects or advantages: By adopting the above technical solution, an initial three-dimensional propagation environment model is first constructed based on the geographic environmental data of the target area. This model is then compared and analyzed with measured signal data from multiple monitoring stations to promptly identify mismatched monitoring stations where the predicted field strength values ​​deviate significantly from the measured values. By analyzing the signal arrival angle and multipath delay spread parameters of the mismatched monitoring stations, the signal propagation direction and distance are determined. Reverse ray tracing technology can accurately locate the environmental areas requiring verification that cause prediction deviations. Furthermore, cluster analysis is used to determine environmental correction units, and environmental parameters are specifically corrected based on the field strength deviation values, achieving dynamic optimization and calibration of the propagation environment model. Finally, ray tracing calculations using the optimized propagation environment model improve the accuracy of radio propagation prediction. Attached Figure Description

[0018] Figure 1 This is a schematic flowchart of a radio prediction analysis method disclosed in an embodiment of this application; Figure 2 This is another schematic flowchart of a radio prediction analysis method disclosed in an embodiment of this application; Figure 3 This is a schematic diagram of the structure of a system provided in an embodiment of this application.

[0019] Explanation of reference numerals in the attached drawings: 301, Central Processing Unit; 302, Read-Only Memory; 303, Random Access Memory; 304, Bus; 305, Input / Output Interface; 306, Input Section; 307, Output Section; 308, Storage Section; 309, Communication Section; 310, Driver; 311, Removable Media. Detailed Implementation

[0020] To enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments.

[0021] In the description of the embodiments of this application, the words "for example" or "for instance" are used to indicate examples, illustrations, or explanations. Any embodiment or design that is described as "for example" or "for instance" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design options. Rather, the use of the words "for example" or "for instance" is intended to present the relevant concepts in a specific manner.

[0022] In the description of the embodiments of this application, the term "multiple" means two or more. For example, multiple systems means two or more systems, and multiple screen terminals means two or more screen terminals. Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the indicated technical features. Thus, a feature defined with "first" or "second" may explicitly or implicitly include one or more of that feature. The terms "comprising," "including," "having," and variations thereof all mean "including but not limited to," unless otherwise specifically emphasized.

[0023] This application provides a radio prediction analysis method, referring to... Figure 1 , Figure 1 This is a flowchart illustrating a radio prediction analysis method provided in an embodiment of this application. The method is applied to a system, which refers to a hardware and software integrated platform capable of executing a radio prediction analysis program. The system can execute a radio prediction analysis program, and the method includes steps 101 to 106, as follows: Step 101: Obtain geographic environmental data of the target area and measured signal data from multiple monitoring stations. The measured signal data includes the measured field strength value, signal arrival angle, and multipath delay spread parameters received by each monitoring station.

[0024] The target area refers to the specific geographical area where radio planning needs to be carried out, such as urban areas, mountainous regions, or designated sites. Geographic environmental data includes spatial information such as topographic elevation data, building distribution data, vegetation cover data, and surface material data. Monitoring stations are fixed measurement points deployed within the target area to collect signal data. Measured field strength values ​​represent the intensity of the electromagnetic wave signal received by the monitoring station, measured in dBm or dBμV / m. The signal arrival angle describes the direction in which the signal arrives at the receiving antenna, including the azimuth angle (0-360 degrees) in the horizontal plane and the elevation angle (-90 to 90 degrees) in the vertical plane. Multipath delay spread parameters reflect the time delay characteristics of the signal after reflection, diffraction, and other propagation paths during propagation, and are usually represented by a power delay profile.

[0025] Specifically, firstly, digital elevation model (DEM) data, 3D building model data, vegetation distribution layers, and land cover classification data for the target area are acquired through a geographic information system (GIS). These data need to meet certain accuracy requirements, such as a DEM resolution of at least 10 meters and building models including building outlines and height information. Then, multiple monitoring stations are deployed within the target area according to certain station placement principles (e.g., ensuring the distance between monitoring stations does not exceed 1 kilometer). Each monitoring station is equipped with a field strength meter, a signal direction measurement device, and a channel characteristic analyzer. For each monitoring station, the following data is recorded: the received signal level is measured using a field strength meter at a sampling interval of 1 second, and the average value is recorded for 5 minutes at each measurement point as the measured field strength value; the signal arrival direction is measured using a receiving device with a phased array antenna, and the azimuth and elevation angles are obtained through beam scanning; the channel impulse response is measured using a channel analyzer, and the power delay profile is obtained through Fourier transform to extract multipath delay spread parameters. All measurement data needs to be labeled with measurement time, environmental conditions, and other information, and stored in a database for subsequent analysis.

[0026] Step 102: Construct a three-dimensional propagation environment model based on geographical environment data, and perform ray tracing calculations in the three-dimensional propagation environment model based on preset emission source parameters to obtain the predicted field strength value of each monitoring station. Compare the predicted field strength value of each monitoring station with the corresponding measured field strength value to determine the mismatched monitoring stations whose field strength deviation value exceeds the preset threshold.

[0027] A three-dimensional propagation environment model is a digital representation of the electromagnetic wave propagation space, including the geometric shapes and electromagnetic properties of elements such as terrain, buildings, and vegetation. Preset transmitter parameters refer to technical specifications such as transmitter location coordinates, transmission power, antenna type, operating frequency, and polarization. Ray tracing calculation is a numerical calculation method based on geometric optics principles to simulate the propagation path of electromagnetic waves, covering propagation mechanisms such as direct, reflected, and diffracted waves. The predicted field strength value represents the theoretical signal strength value obtained through ray tracing calculation. The field strength deviation value represents the difference between the predicted and measured field strength values. Mismatch monitoring stations indicate the locations of measurement points where the field strength deviation value exceeds the allowable range.

[0028] Specifically, the geographic environment data is first imported into electromagnetic simulation software to establish a 3D model in a unified coordinate system. Terrain data is converted into an irregular triangular mesh structure, building data is converted into a polyhedral model, and vegetation areas are divided into voxel units with attenuation characteristics. Corresponding electromagnetic parameters are assigned to each type of feature; the dielectric constant of buildings is set to 4.0-j0.1, and the conductivity of the ground is set to 0.01 S / m. The location of the emission source is marked in the 3D model, and the operating frequency of the emission source is set to 900MHz, the transmission power to 40dBm, and the antenna gain to 12dBi. When performing ray tracing calculations, an adaptive resolution ray emission scheme is adopted, with an initial ray spacing angle of 1 degree, a maximum number of reflections set to 3, and a maximum number of diffractions set to 2. For each ray, various losses along its propagation path are calculated: the free space loss L is calculated using the formula L = 32.45 + 20log frequency value + 20log distance value, where the frequency value is in MHz and the distance value is in km; reflection loss is calculated using the Fresnel reflection coefficient; and diffraction loss is calculated using the unified diffraction theory method. At each monitoring station location, the power of all arriving rays is superimposed to obtain the predicted field strength value. The difference between the predicted and measured field strength values ​​is calculated; when the absolute value of the difference exceeds a preset threshold of 5 dB, the monitoring station is marked as a mismatch monitoring station. The location information and field strength deviation values ​​of all mismatch monitoring stations are recorded in a database for subsequent environmental parameter correction.

[0029] Step 103: For mismatch monitoring stations, determine the signal propagation direction based on the signal arrival angle, and determine the propagation distance of the propagation path based on the multipath delay spread parameter.

[0030] The direction of signal propagation is the direction of energy flow during the transmission of electromagnetic waves in space, determined by the azimuth and elevation angles when the signal reaches the receiving antenna. The azimuth angle represents the angle between the signal and true north in the horizontal plane, ranging from 0 to 360 degrees. The elevation angle represents the angle between the signal and the horizontal plane in the vertical plane, ranging from -90 to 90 degrees. The propagation path refers to the spatial trajectory of the electromagnetic wave from the transmitting source to the receiving point, including the direct path and multipath paths formed by reflection and diffraction. The propagation distance is the actual distance the signal travels along the propagation path from the transmitting source to the receiving point. The propagation distance of the direct path is equal to the straight-line distance between the transmitting source and the receiving point, while the propagation distance of the multipath path is greater than the straight-line distance.

[0031] Specifically, firstly, the signal arrival angle data measured by the mismatch monitoring station is read, and the azimuth angle α and elevation angle β values ​​are extracted. A direction vector is established based on a spherical coordinate system, with the components of the direction vector on the three coordinate axes as follows: x-component = cosβ·cosα, y-component = cosβ·sinα, z-component = sinβ. Normalizing this direction vector yields the standardized signal propagation direction. Then, the propagation distance is determined: the power delay profile data recorded by the monitoring station is read, and each delay peak τi and its corresponding power Pi are extracted. The delay data are sorted chronologically, with the earliest arrival delay τ1 as the benchmark. For each delay peak τi, the delay difference Δτi = τi - τ1 between it and τ1 is calculated. Based on the propagation speed c of electromagnetic waves in free space and the medium influence coefficient n in the current frequency band, the path length Li = c·τi / n for each propagation path is calculated. L1 corresponding to the earliest arriving signal is the shortest path distance, and the propagation distances of other paths are equal to Li. The propagation direction and propagation distance obtained through the above calculations will be used in the subsequent reverse ray tracing process.

[0032] Step 104: Based on the propagation direction and distance, perform reverse ray tracing starting from the location of the mismatch monitoring station, and determine the intersection of the reverse ray with the geographical elements in the three-dimensional propagation environment model as the area to be verified.

[0033] Reverse ray tracing is a technique for calculating the ray path from the receiving point in the opposite direction of signal propagation. The reverse ray is a calculated ray emitted from the location of the mismatch monitoring station towards the signal source. Geographic features in the 3D propagation environment model include spatial entities such as building surfaces, terrain undulations, and vegetation cover. The intersection point refers to the spatial coordinates of the point where the reverse ray intersects with the surface of a geographic feature. The environmental verification area refers to the spatial range centered on the intersection point where environmental parameters need to be checked and corrected.

[0034] Specifically, firstly, the starting position coordinates (x0, y0, z0) of the mismatch monitoring station are determined in the three-dimensional coordinate system. The propagation direction vector obtained in the previous step is inverted to obtain the direction vector (dx, dy, dz) of the reverse ray. The parametric equations of the reverse ray are expressed as: x = x0 + t·dx, y = y0 + t·dy, z = z0 + t·dz, where t is a parameter variable. Starting from t = 0, within the propagation distance L, the ray path is divided into several small step sizes Δt for iterative calculation. In each iteration step, the intersection test between the current ray position and each geographic feature in the three-dimensional environment model is calculated: for building surfaces, the ray-polygon intersection algorithm is used; for undulating terrain surfaces, the ray-triangular mesh intersection algorithm is used; for vegetation cover surfaces, the ray-voxel intersection algorithm is used. When an intersection is detected, the spatial coordinates (xi, yi, zi) of the intersection point and the corresponding geographic feature type are recorded. The scope to be verified is determined based on the type of geographic feature: a spherical area with a radius of 10 meters is used for building surfaces, a spherical area with a radius of 20 meters is used for undulating terrain, and a spherical area with a radius of 30 meters is used for vegetation cover. The coordinates of the intersection points and the corresponding scope information to be verified are stored in the database for subsequent environmental parameter correction. The reverse tracing calculation is terminated when the ray propagation distance reaches the set L value or the number of intersection points reaches the preset upper limit.

[0035] In one possible implementation, reverse ray tracing is performed from the location of the mismatch monitoring station, combining the propagation direction and propagation distance. The intersection of the reverse ray with geographical features in the three-dimensional propagation environment model is determined as the area to be verified. Specifically, this includes steps 1041-1043, as follows: Step 1041: Starting from the location of the mismatch monitoring station, emit a tracking ray in the opposite direction of the signal propagation direction.

[0036] The location of a mismatch monitoring station refers to the three-dimensional coordinates of a monitoring point where the predicted field strength value deviates from the measured field strength value by more than a threshold. The signal propagation direction is the electromagnetic wave energy propagation direction vector determined by the azimuth and elevation angles. The tracing ray refers to the digital ray representation used to calculate the path, containing the starting coordinates, direction vector, and propagation distance information. The reverse direction refers to the direction obtained by inverting the original propagation direction vector.

[0037] Specifically, the three-dimensional coordinate data (x0, y0, z0) of the mismatch monitoring station is first read as the starting point of the ray. The azimuth angle α and elevation angle β of the signal propagation direction are obtained and converted into direction vectors in a Cartesian coordinate system: forward propagation direction vector D = (cosβ·cosα, cosβ·sinα, sinβ). The direction vector is then calculated in reverse: reverse ray direction vector R = -D = (-cosβ·cosα, -cosβ·sinα, -sinβ). The parametric equations of the reverse ray are constructed: x = x0 + t·(-cosβ·cosα), y = y0 + t·(-cosβ·sinα), z = z0 + t·(-sinβ), where t is the ray propagation distance parameter. In the numerical calculation, an initial step size Δt = 0.1 meters is set for subsequent iterative tracking. The starting coordinates, direction vector, step size parameter, and current propagation distance t = 0 of the reverse ray are stored in the ray data structure as the initial state for ray tracing. This data will be used to perform subsequent ray propagation path calculations and intersection detection.

[0038] Step 1042: Determine the effective search range of the tracking ray based on the propagation distance, and detect the intersection points of the tracking ray with the building surface, terrain undulation surface and vegetation cover in the three-dimensional propagation environment model within the effective search range.

[0039] Propagation distance refers to the actual path length of an electromagnetic wave from its source to its receiver. Effective search range refers to the spatial area requiring intersection detection during reverse ray tracing. Building surface is the external outline of a building composed of polygonal patches. Terrain undulation is the change in ground elevation represented by a triangular mesh. Vegetation cover is the vegetation distribution area represented by a voxel array. Intersection location refers to the spatial coordinates of the point where the tracing ray intersects with a geographic feature.

[0040] Specifically, firstly, the maximum search range for ray tracing is determined based on the propagation distance L, and a spherical search space with a radius of L is constructed, centered on the mismatch monitoring station. The search space is divided into grid cells, with a grid size of 10 meters to accelerate spatial indexing. For each grid cell within the search space, an index table containing the geographic features within that cell is created. Iterative calculations are performed along the reverse ray direction: for the parametric equations x=x0+t·dx, y=y0+t·dy, z=z0+t·dz, starting from t=0, the t value is incremented by 0.1 meters. At each t value, the grid cell containing the current ray position is determined, and the geographic feature index table for that grid cell is read. Intersection detection is performed on the geographic features in the index table: for building surfaces, a ray-polygon intersection algorithm is used to calculate the intersection point between the ray equation and the polygon plane equation, and to determine whether the intersection point is inside the polygon; for terrain undulations, a ray-triangular mesh intersection algorithm is used to calculate the intersection point between the ray and each triangular facet; for vegetation cover, a ray-voxel intersection algorithm is used to detect whether the ray crosses the voxel boundary. Record the spatial coordinates (xi, yi, zi) and corresponding geographic feature types of all detected intersections. Stop iteration when the t-value reaches the propagation distance L or the number of detected intersections reaches a preset upper limit. Sort all intersection information according to the t-value in ascending order and store it in an intersection data table for subsequent environmental verification area delineation.

[0041] Step 1043: Obtain the three-dimensional coordinates and geographic feature type of each intersection location; for each intersection location, determine the corresponding scale of the scope to be verified based on the geographic feature type, and establish a spatial region with the three-dimensional coordinates of the intersection location as the center, corresponding to the scale of the scope to be verified, as the environmental verification area.

[0042] The three-dimensional coordinates of the intersection point are represented by the x, y, and z values ​​in a spatial rectangular coordinate system. Geographic feature types include three basic types: building surfaces, topographic relief surfaces, and vegetation cover surfaces. The scale of the area to be verified refers to the size of the environmental parameter inspection range corresponding to different geographic feature types. The environmental verification area refers to a specific scale spatial range centered on the intersection point, used for subsequent environmental parameter correction.

[0043] Specifically, the spatial coordinates (xi, yi, zi) and corresponding geographic feature type information of each intersection point are first read from the intersection data table. The scale of the area to be verified is set according to the geographic feature type: for building surface types, a spherical verification area with a radius of 10 meters is set, focusing on the building's height, material, and structural characteristics; for terrain undulation types, a spherical verification area with a radius of 20 meters is set, focusing on checking terrain slope, roughness, and surface cover characteristics; for vegetation cover types, a spherical verification area with a radius of 30 meters is set, focusing on analyzing vegetation height, density, and attenuation characteristics. For each intersection point, the following spatial region construction steps are performed: Establish a local coordinate system centered at the intersection point (xi, yi, zi); construct a spherical space S based on the corresponding verification region radius R: (x-xi)²+(y-yi)²+(z-zi)²≤R²; discretize the spherical space S into a set of grid points with a grid spacing of 1 meter; record the spatial coordinates and current environmental parameter values ​​of the geographic features to which each point belongs in the grid point set; store the boundary equations, grid point data, and environmental parameter information of each region to be verified in the database. Use spatial indexing technology to mark the overlap between adjacent regions to be verified, providing data support for subsequent cluster analysis. After completing the environmental verification region construction for all intersection points, a set of regions to be verified is formed, containing the spatial extent, geographic feature type, and current environmental parameter values ​​of each region.

[0044] Step 105: Perform cluster analysis on the environmental area to be verified, determine the environmental correction unit, correct the environmental parameters of the environmental correction unit according to the field strength deviation value, and update the correction results to the three-dimensional propagation environment model.

[0045] The environmental verification area refers to a specific spatial range centered on the intersection of rays. Cluster analysis is a data processing method that merges verification areas that are spatially close and have the same geographic feature type. The environmental correction unit is a larger continuous area formed after clustering. The field strength deviation value is the numerical difference between the predicted field strength and the measured field strength. Environmental parameter correction refers to the process of adjusting the electromagnetic characteristic parameters of geographic features based on the field strength deviation. The 3D propagation environment model update is a data update operation that writes the corrected parameters into the original model.

[0046] Specifically, spatial clustering calculations are first performed, using a density-based spatial clustering algorithm to process the areas to be verified. The clustering distance threshold is set to 1.5 times the scale of the verification range, and the density threshold is at least 3 grid points per cubic meter of space. Clustering is performed on the center points of all areas to be verified: the Euclidean distance between any two area center points is calculated, and areas with a distance less than the threshold and the same geographic feature type are grouped into the same category. For each clustering result, its corresponding multiple areas to be verified are merged to form an environmental correction unit, and the boundary range and geographic feature type of this unit are recorded. Environmental parameter correction is performed: the field strength deviation values ​​of the mismatch monitoring stations affecting this correction unit are read. For the field strength deviation value Di of each monitoring station i, the parameter correction amount is calculated based on the electromagnetic propagation loss model. The dielectric constant of the building surface is corrected: when Di is positive, the dielectric constant increases by 0.1×Di; when Di is negative, the dielectric constant decreases by 0.1×|Di|. Topographic relief surface correction for surface electrical conductivity: When Di is positive, the conductivity increases by 0.001 × DiS / m; when Di is negative, the conductivity decreases by 0.001 × |Di|S / m. Vegetation cover correction for attenuation coefficient: When Di is positive, the attenuation coefficient increases by 0.05 × DiB / m; when Di is negative, the attenuation coefficient decreases by 0.05 × |Di|dB / m. The average value of the corrected parameters at each grid point within each environmental correction unit is taken as the final correction result. The parameters of all correction units are sequentially updated and written to the corresponding positions in the 3D propagation environment model to complete the parameter update of the environment model.

[0047] In one possible implementation, cluster analysis is performed on the environmental area to be verified to determine environmental correction units, specifically including steps 1051-1052, as follows: Step 1051: Calculate the spatial distance between any two environmental regions to be verified; divide environmental regions to be verified with a spatial distance less than the preset clustering radius into the same candidate correction unit.

[0048] Spatial distance refers to the three-dimensional Euclidean distance between the center points of two environmental verification areas. The preset cluster radius is the distance threshold used to determine whether two areas belong to the same unit. Candidate correction units refer to the preliminary clustering results composed of multiple spatially similar environmental verification areas. An environmental verification area is a specific-scale spatial range centered on the intersection of rays.

[0049] Specifically, first, a spatial distance calculation matrix is ​​established, and the coordinates of the center points of all environmental regions to be checked are read, with a total of n regions. An n×n distance matrix D is constructed, where the matrix element Dij represents the distance between the center points of region i and region j. For any two regions i and j, their center point coordinates are (xi, yi, zi) and (xj, yj, zj), respectively, and the spatial distance Dij is calculated using the Euclidean distance formula. Each element in the distance matrix D is compared with a preset clustering radius R. When Dij is less than R, the connection relationship between region i and region j is marked in the connection matrix C, Cij=1; when Dij is greater than or equal to R, Cij=0. Candidate correction unit partitioning is performed based on the connection matrix C: a disjoint-set data structure is used to record the connection relationships between regions, initially each region forming its own set. All connection relationships marked as 1 in the connection matrix C are traversed, and connected regions are merged into the same set. The merging process uses path compression optimization to ensure that the time complexity of the search operation is O(α(n)), where α(n) is the inverse function of the Ackermann function. After traversal, each independent set becomes a candidate correction unit. Record the list of environmental regions to be verified contained in each candidate correction unit, and calculate the spatial extent of the unit: take the smallest bounding cube of all region coordinates within the unit as the boundary extent of the candidate correction unit. Store the candidate correction unit's number, the list of contained regions, and the boundary extent into a data structure for subsequent unit merging and parameter correction.

[0050] Step 1052: Obtain the number of mismatch monitoring stations traced back to each candidate correction unit, and use the number of mismatch monitoring stations as the environmental distortion of the corresponding candidate correction unit; select candidate correction units with environmental distortion higher than the preset distortion threshold as environmental correction units.

[0051] The number of mismatch monitoring stations refers to the total number of field strength anomaly measurement points that affect a candidate correction unit. Environmental distortion is a numerical indicator measuring the accuracy of environmental parameters of a candidate correction unit. The preset distortion threshold is a numerical standard for determining whether a candidate correction unit needs environmental parameter correction. The environmental correction unit is the spatial area ultimately determined to require parameter correction. Tracing refers to establishing the correlation between mismatch monitoring stations and candidate correction units through reverse ray tracing.

[0052] Specifically, firstly, an association table is established between candidate correction units and mismatch monitoring stations. For each mismatch monitoring station, its reverse ray tracing results are read, and the intersection information of the ray and geographic features is extracted. The candidate correction unit number to which each intersection belongs is checked, and a mapping relationship from monitoring station to candidate correction unit is established in the association table. The number of mismatch monitoring stations associated with each candidate correction unit is counted: the association table is traversed, the number of times each candidate correction unit appears is accumulated, and this value is recorded as the environmental distortion degree. A preset distortion degree threshold T is set, and the environmental distortion degree of all candidate correction units is filtered. When the environmental distortion degree Fi of candidate correction unit i is greater than the threshold T, the unit is marked as an environmental correction unit, and its number, boundary range, and list of associated mismatch monitoring stations are recorded; when the environmental distortion degree Fi is less than or equal to the threshold T, the candidate correction unit is removed from the correction list. An environmental correction unit data structure is established to store the spatial range of each correction unit, the list of environmental areas to be checked, the list of associated mismatch monitoring stations, and the environmental distortion degree value. Environmental correction units are sorted in descending order of environmental distortion degree, and areas with higher distortion degrees are processed first. The filtering results are written into the database for subsequent environmental parameter correction calculations.

[0053] In one possible implementation, the environmental parameters of the environmental correction unit are corrected based on the field strength deviation value, and the correction result is updated to the three-dimensional propagation environment model. Specifically, this includes steps 1053-1055, as follows: Step 1053: For each environmental correction unit, obtain the average field strength deviation of all mismatch monitoring stations traced back to the environmental correction unit.

[0054] An environmental correction unit refers to a spatial region that has been screened and determined to require parameter correction. A mismatch monitoring station refers to a measurement point where the deviation between the predicted and measured field strengths exceeds a threshold. Field strength deviation is the difference between the predicted and measured field strengths, expressed in dB. The mean field strength deviation is the arithmetic mean of the field strength deviations of multiple mismatch monitoring stations associated with the same environmental correction unit. The tracing relationship is the correspondence between environmental correction units and mismatch monitoring stations established through reverse ray tracing.

[0055] Specifically, firstly, the environmental correction unit data table is read to obtain the number of each correction unit and the list of associated mismatch monitoring stations. For environmental correction unit i, the set of associated mismatch monitoring stations Si is read. Each monitoring station j in set Si is traversed, and the predicted field strength value Pij and the measured field strength value Mij for that monitoring station are extracted. The field strength deviation value Dij = Pij - Mij is calculated. A field strength deviation array Di is established, storing the field strength deviation values ​​Dij of all monitoring stations associated with correction unit i into array Di. The mean is calculated: assuming the total number of monitoring stations associated with correction unit i is ni, the mean field strength deviation Ai = (Di1 + Di2 + ... + Dini) / ni is calculated. The mean field strength deviation Ai of each environmental correction unit is recorded in the correction unit attribute table. Simultaneously, the number of monitoring stations ni used to calculate the mean and the standard deviation σi of the field strength deviation for each monitoring station are recorded to evaluate the reliability of the mean. When the number of monitoring stations ni associated with a correction unit is less than 3, the mean calculation result is marked as low confidence. The average field strength deviation of all environmental correction units is calculated and written into the database as the basis for subsequent environmental parameter correction.

[0056] Step 1054: Determine the adjustment amount based on the absolute value of the mean field strength deviation, and determine the direction of environmental parameter adjustment based on the positive or negative direction of the mean field strength deviation.

[0057] The mean field strength deviation is the average of the field strength deviations of all mismatched monitoring stations associated with a specific environmental correction unit. The adjustment amount refers to the magnitude of environmental parameter correction determined based on the mean field strength deviation. The direction of environmental parameter adjustment indicates whether the parameter is increased or decreased, determined by the sign of the mean field strength deviation. A positive mean field strength deviation indicates that the predicted field strength is greater than the measured field strength, while a negative mean field strength indicates that the predicted field strength is less than the measured field strength. Environmental parameters include electromagnetic property parameters such as building dielectric constant, topographic conductivity, and vegetation attenuation coefficient.

[0058] Specifically, first, the mean field strength deviation Ai and the geographic feature type of each environmental correction unit are read. Based on the geographic feature type, the corresponding environmental parameter adjustment coefficients are selected: the adjustment coefficient k1 for the dielectric constant of building surfaces is set to 0.1, the adjustment coefficient k2 for the conductivity of terrain surfaces is set to 0.001, and the adjustment coefficient k3 for the vegetation attenuation coefficient is set to 0.05. For environmental correction unit i, the absolute value and sign of its mean field strength deviation Ai are obtained. The environmental parameter adjustment amount is calculated: when the geographic feature type is building, the adjustment amount ΔP = k1 × |Ai|; when the geographic feature type is terrain, the adjustment amount ΔP = k2 × |Ai|; when the geographic feature type is vegetation, the adjustment amount ΔP = k3 × |Ai|. The direction of environmental parameter adjustment is determined: when Ai is positive, it indicates that the predicted field strength is too high, and the environmental parameter needs to be reduced, with a final adjustment value of -ΔP; when Ai is negative, it indicates that the predicted field strength is too low, and the environmental parameter needs to be increased, with a final adjustment value of +ΔP. Record the parameter adjustment results for each environmental correction unit: geographic feature type, original parameter value, adjustment amount, adjustment direction, and final parameter value. Store the adjustment results in the database to update the environmental parameters in the 3D propagation environment model.

[0059] Step 1055: Adjust the environmental parameters of the environmental correction unit according to the adjustment direction and adjustment amount of the environmental parameters. The environmental parameters include building height parameters, surface roughness parameters and medium electromagnetic property parameters; update the adjusted environmental parameters to the position of the corresponding environmental correction unit in the three-dimensional propagation environment model.

[0060] The direction of environmental parameter adjustment refers to the corrective trend of increasing or decreasing the parameter. The adjustment amount is the specific numerical correction of the environmental parameter. Building height parameters describe the vertical height of the building. Surface roughness parameters are numerical indicators characterizing the degree of surface undulation. Medium electromagnetic property parameters include physical quantities describing electromagnetic propagation characteristics such as dielectric constant, conductivity, and loss tangent. A three-dimensional propagation environment model is a digital representation describing the space of electromagnetic wave propagation. An environmental correction unit is a specific spatial region that requires parameter correction.

[0061] Specifically, first, the geographic feature type and original environmental parameter values ​​of the environmental correction unit are read. For building type correction units, the building height h, dielectric constant εr, and loss tangent tanδ are read; for terrain type correction units, the surface roughness σh and electrical conductivity σ are read; for vegetation type correction units, the vegetation height hv and attenuation coefficient α are read. Then, parameter adjustment calculations are performed: for building parameter adjustments, when the adjustment direction is increasing, the new dielectric constant εr_new = εr + Δεr, and the new loss tangent tanδ_new = tanδ + Δtanδ; when the adjustment direction is decreasing, the new dielectric constant εr_new = εr - Δεr, and the new loss tangent tanδ_new = tanδ - Δtanδ. Terrain parameters are adjusted as follows: when the adjustment direction is increasing, the new surface roughness σh_new = σh + Δσh, and the new electrical conductivity σ_new = σ + Δσ; when the adjustment direction is decreasing, the new surface roughness σh_new = σh - Δσh, and the new electrical conductivity σ_new = σ - Δσ. Vegetation parameters are adjusted as follows: when the adjustment direction is increasing, the new attenuation coefficient α_new = α + Δα; when the adjustment direction is decreasing, the new attenuation coefficient α_new = α - Δα. The 3D environment model is updated by reading the spatial boundary coordinates of the environmental correction units and locating the corresponding areas in the model; writing the corrected environmental parameters into the corresponding data structures; updating the parameter index table in the model, and recording the parameter modification timestamp and reason. After updating the parameters of all environmental correction units, the updated 3D propagation environment model is saved.

[0062] Step 106: Use the updated 3D propagation environment model to perform ray tracing calculations on multiple preset candidate station deployment schemes to obtain the field strength distribution map, and determine the preset candidate station deployment scheme with the best radio performance as the target scheme based on the field strength distribution map.

[0063] Preset candidate station deployment schemes refer to different combinations of transmitter locations, antenna parameters, and operating parameters. Ray tracing calculation is a numerical calculation method that simulates the propagation path of electromagnetic waves. Field strength distribution maps represent the two-dimensional or three-dimensional distribution of signal strength at various points in space. Radio performance indicators include evaluation metrics such as field strength coverage, signal-to-noise ratio, and multipath interference. The target scheme is the optimal deployment scheme determined after comprehensive evaluation. The three-dimensional propagation environment model is a spatial model of electromagnetic wave propagation with parameters corrected.

[0064] Specifically, the process begins by reading parameters from multiple preset candidate station deployment schemes. Each scheme includes transmitter coordinates, antenna type, antenna height, transmit power, and operating frequency. For each deployment scheme, field strength calculations are performed: a transmission source is established in a 3D environment model, using a standard gain model for the antenna pattern; the target area is divided into grids with a grid spacing of 20 meters; ray tracing is performed on each receiving point, setting the maximum number of reflections to 3 and the maximum number of diffractions to 2; propagation losses for direct, reflected, and diffracted paths are calculated; and the field strength contributions from each path are superimposed to obtain the total field strength at the receiving point. A field strength distribution map is then generated: a field strength matrix is ​​established for each deployment scheme, with matrix elements representing the field strength value at the corresponding location; the field strength values ​​are mapped to color values ​​to generate a pseudo-color distribution map; and field strength statistics, including average field strength, coverage, and standard deviation, are calculated. Evaluation of scheme performance: Calculate the regional field strength coverage RC = number of grids with field strength exceeding the threshold / total number of grids; calculate the field strength uniformity index UI = 1 - field strength standard deviation / average field strength; calculate the comprehensive performance score S = 0.7 × RC + 0.3 × UI. Rank all schemes by performance score and select the scheme with the highest score as the target scheme. Record the detailed parameters and performance evaluation results of the target scheme, including transmitter location coordinates, antenna parameters, operating parameters, field strength distribution map, and values ​​of various performance indicators.

[0065] In one possible implementation, the optimal candidate station deployment scheme with the best radio performance is determined as the target scheme based on the field strength distribution map, specifically including steps 1061-1063, as follows: Step 1061: Based on the field strength distribution map, extract the areas with field strength higher than the reception threshold value in each preset candidate station deployment scheme as the effective coverage area, and calculate the coverage rate by the ratio of the area of ​​the effective coverage area to the total area of ​​the target area.

[0066] A field strength distribution map is a two-dimensional matrix representing the numerical distribution of signal strength at various points in space. The receive threshold refers to the minimum field strength required for a receiver to function properly. The effective coverage area refers to the continuous spatial range where the field strength value is higher than the receive threshold. The total area of ​​the target area is the complete area requiring radio planning. Coverage rate is the ratio of the effective coverage area to the total area of ​​the target area, used to evaluate signal coverage effectiveness. Preset candidate station deployment schemes are different combinations of transmitter locations and parameters.

[0067] Specifically, first, the field strength distribution data matrix F of each preset candidate station deployment scheme is read. A reception threshold value Eth is set, determined according to the service type, such as -95dBm for mobile communication services. Each element Fij in the field strength matrix F is traversed, creating a binarized matrix B. When Fij is greater than Eth, Bij is set to 1, indicating that the point is within the effective coverage area; when Fij is less than or equal to Eth, Bij is set to 0, indicating that the point is in a coverage blind zone. Connectivity analysis is performed: eight-neighbor connectivity is detected on the binarized matrix B; all connected components are numbered; isolated connected components with an area less than 100 square meters are removed, and their corresponding Bij values ​​are set to 0. The effective coverage area is calculated: the spatial resolution r of the field strength distribution map is read, and the actual area s = r × r of each grid is calculated; the total number of elements n with a value of 1 in the binarized matrix is ​​counted; the total effective coverage area S1 = n × s is calculated. The total area of ​​the target area is calculated: the boundary coordinates of the target area are read, and the total area S2 is calculated using the polygon area calculation formula. Calculate coverage: R = S1 / S2. Repeat the above calculation process for each deployment scheme to obtain the corresponding coverage value. Store the coverage calculation results of all schemes in a data table, recording the scheme number, effective coverage area, target area area, and coverage value.

[0068] Step 1062: Extract the areas in each preset candidate station deployment scheme that simultaneously receive signals from multiple transmission sources and whose signal strength difference is less than the protection ratio as interference areas, and calculate the ratio of the interference area area to the effective coverage area to obtain the interference area percentage.

[0069] Transmitted source signals refer to radio signals emitted by different transmitting stations. The protection ratio is the minimum required difference in strength between two signals to ensure communication quality. The interference area refers to the spatial range where multiple signals are received and the signal strength difference is less than the protection ratio. The effective coverage area is the region where the field strength is higher than the reception threshold. The interference area ratio is the ratio of the interference area area to the effective coverage area area. Preset candidate station deployment schemes are different combinations of transmitter locations and parameters.

[0070] Specifically, firstly, the field strength distribution matrix of all transmitters in the preset candidate station deployment scheme is read. Assuming the total number of transmitters is N, for any point P in space, the field strength value array E=[E1, E2, ..., EN] from each transmitter is obtained. A protection ratio threshold Rth is set; for mobile communication services, this is typically 9dB. Interference judgment is performed: for point P, the field strength array E is sorted in descending order to obtain E'; the maximum field strength value Emax and the second largest field strength value Esec are extracted; the field strength difference ΔE=Emax-Esec is calculated; when ΔE is less than Rth and Emax is greater than the reception threshold, point P is determined to be within the interference area. An interference marking matrix I is created; when point P is within the interference area, the corresponding element Iij is set to 1, otherwise it is set to 0. Connectivity analysis is performed: eight-neighborhood connectivity is detected on the interference marking matrix I; all connected components are numbered; isolated connected components with an area less than 50 square meters are removed. Calculate the interference area: Read the spatial resolution r of the field strength distribution map, calculate the actual area of ​​the grid s = r × r; count the total number of elements with a value of 1 in the interference marker matrix n1; calculate the total area of ​​the interference region S1 = n1 × s. Calculate the effective coverage area: Count the total number of grids with a field strength higher than the reception threshold n2; calculate the effective coverage area S2 = n2 × s. Calculate the proportion of the interference area: R = S1 / S2. Repeat the above calculation process for each deployment scheme to obtain the corresponding proportion of the interference area. Store the calculation results of all schemes in a data table, recording the scheme number, interference area, effective coverage area, and interference area proportion.

[0071] Step 1063: Calculate the spectrum utilization efficiency based on the unit spectrum bandwidth and the area of ​​the corresponding effective coverage area in each preset candidate station deployment scheme.

[0072] Unit spectrum bandwidth refers to the bandwidth of frequency resources occupied by each transmitter, measured in MHz. Effective coverage area refers to the area where the field strength is higher than the reception threshold, measured in square kilometers. Spectrum utilization efficiency is the amount of traffic that can be supported per square kilometer within a unit bandwidth. Preset candidate station deployment schemes are different combinations of transmitter locations and parameters. Total bandwidth resources are the sum of the spectrum bandwidth occupied by all transmitters.

[0073] Specifically, first, the parameters of the preset candidate station deployment scheme are read, including the channel bandwidth B and modulation scheme of each transmitter. For a deployment scheme with a total of N transmitters, the total bandwidth resource BT = B1 + B2 + ... + BN is calculated. The modulation scheme of each transmitter is read, and the spectral efficiency η is determined: η = 2 bps / Hz for QPSK modulation, η = 4 bps / Hz for 16QAM modulation, and η = 6 bps / Hz for 64QAM modulation. The channel capacity Ci = Bi × ηi for each transmitter is calculated. Area division is performed: the target area is divided into multiple sub-regions according to the field strength distribution; the dominant transmitter is determined within each sub-region, i.e., the transmitter providing the strongest signal; the area Si of each sub-region and the corresponding dominant transmitter number are recorded. The regional spectral efficiency is calculated: for sub-region i, its spectral efficiency SEi = Ci / (Bi × Si); the total spectral utilization efficiency SE = (C1 + C2 + ... + CN) / (BT × ST), where ST is the total area of ​​the effective coverage area. Calculate the correction factor: Based on the proportion of the interference area p, calculate the correction factor k = 1 - p; the final spectrum utilization efficiency SEf = SE × k. Repeat the calculation process for each deployment scheme to obtain the corresponding spectrum utilization efficiency value. Store the calculation results in a data table, recording the scheme number, total bandwidth resources, effective coverage area, and spectrum utilization efficiency.

[0074] Step 1064: Perform weighted calculations on the coverage, interference area ratio, and spectrum utilization efficiency of each preset candidate station deployment scheme to obtain the radio performance evaluation value, and select the preset candidate station deployment scheme with the highest radio performance evaluation value as the target scheme.

[0075] Coverage rate is the ratio of the effective coverage area to the total area of ​​the target area. Interference area ratio is the ratio of the interference area to the effective coverage area. Spectrum utilization efficiency represents the amount of traffic supported per square kilometer of area within a unit bandwidth. Weighted calculation is a comprehensive calculation by assigning weight coefficients to different evaluation indicators. Radio performance evaluation value is a comprehensive score calculated by weighting multiple performance indicators. The target solution is the deployment solution with the highest performance evaluation value.

[0076] Specifically, firstly, the performance index data of each preset candidate station deployment scheme are read, including coverage rate (RC), interference area percentage (RI), and spectrum utilization efficiency (SE). Data normalization is performed: for coverage rate, the normalized value NRC = RC / RCmax, where RCmax is the maximum coverage rate among all schemes; for interference area percentage, the normalized value NRI = 1 - RI / RImax, where RImax is the maximum interference area percentage among all schemes; for spectrum utilization efficiency, the normalized value NSE = SE / SEmax, where SEmax is the maximum spectrum utilization efficiency among all schemes. Weighting coefficients are set: coverage rate weight w1 = 0.4, reflecting coverage requirements; interference area percentage weight w2 = 0.3, reflecting communication quality requirements; spectrum utilization efficiency weight w3 = 0.3, reflecting frequency resource utilization requirements. Weighted calculation is performed: for scheme i, its radio performance evaluation value Pi = w1 × NRCi + w2 × NRIi + w3 × NSEi is calculated. All scheme performance evaluation values ​​are sorted in descending order, and the scheme with the highest evaluation value is selected as the target scheme. Record complete information about the target scheme: scheme number, transmitter location coordinates, transmit power, antenna parameters, operating frequency, coverage, interference area proportion, spectrum utilization efficiency, and performance evaluation values. Store the target scheme's field strength distribution map, interference distribution map, and evaluation indicators in a database for subsequent network planning and optimization.

[0077] In the above embodiments, a basic propagation path analysis framework was implemented using signal arrival angle and multipath delay spread parameters. To further improve the accuracy of propagation path identification and reduce the impact of medium changes on propagation distance calculation, this application also provides a radio prediction analysis method. This method identifies the arrival angle characteristics of the main path signal, analyzes the multipath delay distribution pattern, and performs medium correction for propagation speed, enabling the system to more accurately handle path reconstruction needs in complex propagation environments. The following section combines... Figure 2 Another radio prediction analysis method in the embodiments of this application is described below: Please see Figure 2 This is a flowchart illustrating a radio prediction analysis method in an embodiment of this application.

[0078] Step 201: Obtain the signal arrival angle of the main path signal received by the mismatch monitoring station, take the components of the signal arrival angle in the horizontal and vertical planes as the azimuth and elevation angles respectively, and determine the propagation direction from the mismatch monitoring station to the transmission source as the signal propagation direction based on the azimuth and elevation angles.

[0079] The dominant ray refers to the ray with the shortest propagation path or the strongest signal strength. The angle of arrival is the angle between the ray and the reference coordinate system when the ray reaches the receiving point. The azimuth is the angle between the signal propagation direction on the horizontal plane and true north, ranging from 0 to 360 degrees. The elevation angle is the angle between the signal propagation direction and the horizontal plane, positive (upward), ranging from -90 to 90 degrees. The propagation direction is the spatial vector of the ray's propagation, uniquely determined by the azimuth and elevation angles. The transmitting source is the location of the transmitting antenna.

[0080] Specifically, the signal measurement data from the mismatch monitoring station is first read, including the power spectrum and angle of arrival spectrum of the received signal. Signal principal path extraction is performed: peak detection is performed on the power spectrum, and the delay point with the strongest signal intensity is marked; the angle of arrival information corresponding to this delay is read. A spherical coordinate system is established: the monitoring station is the origin; the north is the 0-degree azimuth reference; the ground plane is the 0-degree elevation reference. The angle of arrival is decomposed: the signal angle of arrival θ is read; the azimuth α = arctan(sinθ × cosφ / cosθ), where φ is the Earth curvature correction angle; the elevation angle β = arcsin(sinθ × sinφ). Coordinate transformation is performed: the spherical coordinates (1, α, β) are converted to rectangular coordinates (x, y, z); x = cosβ × cosα, y = cosβ × sinα, z = sinβ. The propagation direction vector is constructed: starting from the coordinates of the monitoring station; the unit vector (-x, -y, -z) is used as the direction, pointing towards the source; the three components of the propagation direction vector are recorded. The calculation results are stored in a data structure containing: monitoring station number, main path signal strength, azimuth angle, elevation angle, and propagation direction vector. This data is used for subsequent reverse ray tracing calculations.

[0081] Step 202: Extract multiple delay peaks from the multipath delay spread parameters, where each delay peak corresponds to a propagation path; determine the additional propagation time of the propagation path relative to the shortest path based on the delay difference between the delay peak corresponding to each propagation path and the earliest arriving delay peak.

[0082] The delay peak is the local maximum value of signal power in the power delay spectrum. The propagation path is the spatial trajectory of the electromagnetic wave from the source to the receiver. The earliest arrival at the delay peak corresponds to the path with the shortest propagation distance. The delay difference is the difference in propagation time for each propagation path relative to the shortest path. Additional propagation time is the extra propagation time caused by path curvature or reflection / diffraction.

[0083] Specifically, first, the power delay spectrum data P(τ) measured by the mismatch monitoring station is read. Peak detection is performed: the detection threshold Pth is set to 10dB above the noise floor; local maxima search is performed on P(τ); when the power of a maximum point exceeds Pth, it is marked as a valid peak; the time delay τi and power Pi of each peak are recorded. The detected peaks are sorted in ascending order of time delay: the peak with the smallest time delay is defined as τ0, corresponding to the shortest propagation path; the remaining peaks are recorded as τ1, τ2, etc. Relative time delay is calculated: for each peak, the time delay difference Δτi = τi - τ0 relative to τ0 is calculated. The time delay difference is converted into spatial distance: the additional propagation distance ΔLi = c × Δτi is calculated, where c is the speed of light. A path data structure is established: a unique number is assigned to each propagation path; the peak power, absolute time delay, relative time delay, and additional propagation distance corresponding to the path are recorded. Perform data filtering: remove paths with power below 20dB of the strongest peak value; remove paths with relative delay greater than 2 microseconds; remove paths with an additional propagation distance greater than 1 kilometer. Store the filtered valid path information in a database: path number, peak power, delay parameter, and spatial distance parameter. This data is used for subsequent propagation path reconstruction.

[0084] Step 203: Calculate the additional propagation distance of the propagation path relative to the shortest path based on the additional propagation time and the propagation speed of electromagnetic waves in the current frequency band, and add the additional propagation distance to the shortest path distance to obtain the propagation distance of the corresponding propagation path.

[0085] Additional propagation time is the difference in propagation time between each propagation path and the shortest path. Electromagnetic wave propagation speed is the rate at which an electromagnetic wave propagates within a specific frequency band and medium. Additional propagation distance is the extra propagation path caused by path curvature or reflection / diffraction. The shortest path distance is the straight-line distance from the transmitter to the receiver. Propagation distance is the actual distance an electromagnetic wave travels along a specific path from the transmitter to the receiver. The propagation path is the spatial trajectory of an electromagnetic wave from the transmitter to the receiver.

[0086] Specifically, first, calculate the propagation speed v of the electromagnetic wave in the current medium. Read the relative permittivity εr of the propagation medium; calculate the actual propagation speed v, which is equal to the speed of light in vacuum c divided by the square root of the permittivity εr. Read the coordinate information of the transmitting and receiving points: transmitting source coordinates (x1, y1, z1), receiving point coordinates (x2, y2, z2). Calculate the shortest path distance L0: square the distance differences between the transmitting and receiving points on the three coordinate axes, add them together, sum them to obtain the square of the shortest path distance, and finally take the square root to obtain L0. Perform distance calculation for each propagation path: read the extra propagation time Δt; calculate the extra propagation distance ΔL = v × Δt; calculate the total propagation distance L = L0 + ΔL. Establish a path distance data table: path number, extra propagation time, extra propagation distance, total propagation distance. Perform data verification: check if the total propagation distance of all paths is greater than the shortest path distance; check if the extra propagation distance is within a reasonable range (usually not exceeding 50% of the shortest path distance); mark paths that do not meet the verification conditions. The verified path distance data is stored in a data structure: each path's distance parameters are recorded in order of path number; the coordinates of the transmitter, receiver, and medium parameters are also recorded. This data is used for subsequent path reconstruction and field strength calculation.

[0087] In one possible implementation, the additional propagation distance of the propagation path relative to the shortest path is calculated based on the additional propagation time and the propagation speed of the electromagnetic wave in the current frequency band, specifically including steps 2031-2033, as follows: Step 2031: Determine the corresponding electromagnetic wave propagation speed based on the operating frequency in the preset emission source parameters.

[0088] The preset transmitter parameters are a set of operating parameters for the transmitting equipment, including parameters such as transmit power, operating frequency, and antenna gain. The operating frequency is the carrier frequency at which the transmitter operates, measured in MHz or GHz. The speed of electromagnetic wave propagation is the rate at which electromagnetic waves propagate in a specific medium, influenced by the properties of the medium. The relative permittivity of the medium is the coefficient that influences the speed of electromagnetic wave propagation. The relative permeability is the coefficient that influences the magnetic properties of the medium on the propagation of electromagnetic waves.

[0089] Specifically, first, the operating frequency f in the preset emission source parameters is read. The speed constant of light in a vacuum is set to c = 3 × 10⁻⁶. 8m / s. Read the electromagnetic parameters of the propagation medium: relative permittivity εr and relative permeability μr. For air, εr≈1, μr≈1. Calculate the propagation speed of the electromagnetic wave in the current frequency band and medium: v=c / (εr×μr). Correct for the influence of medium loss: Read the medium loss tangent tanδ; calculate the correction coefficient k=1-0.5×tanδ²; the corrected propagation speed v'=v×k. Perform dispersion correction: when the operating frequency exceeds 1GHz, medium dispersion needs to be considered; read the medium frequency dispersion curve data; obtain the dispersion coefficient kd from the table based on the operating frequency; the final propagation speed vf=v'×kd. Establish a frequency-velocity correspondence table: record the operating frequency, medium parameters, and propagation speed data; store the calculation results in a data structure, including frequency values, medium parameters, correction coefficients at each level, and the final propagation speed. These data are used for subsequent propagation delay and path distance calculations.

[0090] Step 2032: Based on the medium type of the region through which the propagation path passes in the three-dimensional propagation environment model, obtain the correction coefficient for the relative propagation speed of electromagnetic waves in different media.

[0091] Medium type refers to different propagation media such as air, building materials, and vegetation. The relative propagation speed correction factor is the ratio of the propagation speed of various media relative to the propagation speed in air. A medium region is a continuous spatial range with the same electromagnetic properties. Propagation speed is the rate at which an electromagnetic wave propagates in a specific medium.

[0092] Specifically, first, the spatial mesh data of the 3D propagation environment model is read, with the mesh size set to 1 meter. A medium parameter database is established: air medium correction coefficient k1=1.0; concrete medium correction coefficient k2=0.45; glass medium correction coefficient k3=0.67; metal medium correction coefficient k4=0; vegetation medium correction coefficient k5=0.82. Path segmentation is performed: the propagation path is divided into multiple sub-paths according to the medium boundaries; the starting coordinates (xs, ys, zs) and ending coordinates (xe, ye, ze) of each sub-path segment are recorded. Sub-path medium is determined: for each sub-path segment, the medium type identifier of the passing meshes is read; the number of meshes occupied by each type of medium is counted; the medium type with the most occurrences is selected as the dominant medium for that segment. Path segment correction is calculated: the correction coefficient ki of the dominant medium is read; the sub-path length Li is calculated; the corrected equivalent propagation distance Lei=Li / ki is calculated. Accumulate the results across all sub-paths: calculate the total equivalent propagation distance Le = Le1 + Le2 + ... + Len; calculate the overall correction factor K = L / Le, where L is the actual total path length. Record the correction results: path number, number of segments, medium type of each segment, correction factor for each segment, and overall correction factor. Store the calculation results in a data structure, including spatial coordinates, medium parameters, and correction factors. This data is used for subsequent propagation delay calculations.

[0093] Step 2033: Divide the extra propagation time into segments according to the different medium regions traversed by the propagation path, and calculate the extra propagation distance for each segment using the relative propagation speed correction coefficient of the corresponding medium; sum up the extra propagation distances of all segments to obtain the extra propagation distance of the propagation path relative to the shortest path.

[0094] Additional propagation time is the time difference between the propagation path and the shortest path. The propagation path is the spatial trajectory of an electromagnetic wave from its source to its receiver. A medium region is a continuous spatial area with the same electromagnetic properties. The relative propagation speed correction factor is the ratio of the propagation speeds of various media relative to air. A segment is a sub-segment of the path divided according to the medium's boundary. Additional propagation distance is the extra distance traveled due to path curvature or diffraction caused by reflection.

[0095] Specifically, first, the additional propagation duration ΔT and the spatial trajectory data of the propagation path are read. Path segmentation is performed: the coordinates of the intersection points between the propagation path and the medium boundary are identified; the path is divided into n sub-segments, each located within a single medium region; the starting coordinates (xi1, yi1, zi1) and ending coordinates (xi2, yi2, zi2) of each segment are recorded. Segment duration is calculated: based on the geometric characteristics of the propagation path, the proportion pi of each segment in the total duration is calculated; the propagation duration ΔTi = ΔT × pi corresponding to each segment is calculated. Medium parameters are read: the correction coefficient ki of the medium in which each segment of the path is located is obtained; the correction coefficient k = 1.0 for air, and less than 1.0 for other media. Segment distance is calculated: the speed of light in vacuum c = 3 × 10⁻⁶. 8 m / s; Calculate the additional propagation distance ΔLi = c × ΔTi × ki for each segment. Perform distance accumulation: Calculate the total additional propagation distance ΔL = ΔL1 + ΔL2 + ... + ΔLn. Establish a segmented data table: Record the sequence number, medium type, correction factor, duration percentage, and additional distance for each segment; record the total additional distance after accumulation. Verify the calculation results: Check if the additional distance for each segment is positive; check if the total additional distance is less than twice the shortest path distance; check the consistency between the geometric dimensions of each segment and the calculated distance. Store the verified data in a data structure: path number, number of segments, parameters of each segment, and total additional distance. This data is used for subsequent path reconstruction and field strength calculation.

[0096] The following describes a radio prediction analysis system according to an embodiment of the present invention from the perspective of hardware processing. Please refer to [link / reference needed]. Figure 3 This is a schematic diagram of the structure of a radio prediction analysis system according to an embodiment of this application.

[0097] It should be noted that, Figure 3 The structure of the radio prediction analysis system shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of the present invention.

[0098] like Figure 3 As shown, a radio prediction analysis system includes a central processing unit (CPU) 301, which can perform various appropriate actions and processes according to a program stored in read-only memory (ROM) 302 or a program loaded from storage portion 308 into random access memory (RAM) 303, such as performing the methods in the above embodiments. The RAM 303 also stores various programs and data required for system operation. The CPU 301, ROM 302, and RAM 303 are interconnected via a bus 304. An input / output (I / O) interface 305 is also connected to the bus 304.

[0099] The following components are connected to I / O interface 305: input section 306 including audio input devices, push-button switches, etc.; output section 307 including liquid crystal display (LCD) and audio output devices, indicator lights, etc.; storage section 308 including hard disks, etc.; and communication section 309 including network interface cards such as LAN (Local Area Network) cards, modems, etc. Communication section 309 performs communication processing via a network such as the Internet. Drive 310 is also connected to I / O interface 305 as needed. Removable media 311, such as disks, optical disks, magneto-optical disks, semiconductor memories, etc., are installed on drive 310 as needed so that computer programs read from them can be installed into storage section 308 as needed.

[0100] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing computer programs for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 309, and / or installed from removable medium 311. When the computer program is executed by central processing unit (CPU) 301, it performs the various functions defined in the present invention.

[0101] It should be noted that specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), flash memory, optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this invention, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0102] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. Each block in a flowchart or block diagram may represent a module, segment, or portion of code, which contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those shown in the drawings.

[0103] Specifically, a radio prediction analysis system according to this embodiment includes a processor and a memory. The memory stores a computer program, and when the computer program is executed by the processor, it implements a radio prediction analysis method provided in the above embodiment.

[0104] In another aspect, the present invention also provides a computer-readable storage medium, which may be included in a radio predictive analysis system described in the above embodiments; or it may exist independently and not incorporated into the radio predictive analysis system. The storage medium carries one or more computer programs that, when executed by a processor of the radio predictive analysis system, enable the radio predictive analysis system to implement the radio predictive analysis method based on encrypted data transmission of the Internet of Things provided in the above embodiments.

Claims

1. A radio prediction analysis method, characterized in that, The method includes: The system acquires geographic environmental data of the target area and measured signal data from multiple monitoring stations. The measured signal data includes the measured field strength value, signal angle of arrival, and multipath delay spread parameters received by each monitoring station. A three-dimensional propagation environment model is constructed based on the geographic environment data, and ray tracing calculations are performed in the three-dimensional propagation environment model based on preset emission source parameters to obtain the predicted field strength value of each monitoring station. The predicted field strength value of each monitoring station is compared with the corresponding measured field strength value to determine the mismatched monitoring station whose field strength deviation value exceeds a preset threshold. For the mismatch monitoring station, the signal propagation direction is determined based on the signal arrival angle, and the propagation distance of the propagation path is determined according to the multipath delay spread parameter, including: The signal arrival angle of the main path signal received by the mismatch monitoring station is obtained, and the components of the signal arrival angle in the horizontal and vertical planes are respectively used as the azimuth and elevation angles. Based on the azimuth and elevation angles, the propagation direction from the mismatch monitoring station to the transmission source is determined as the signal propagation direction. Multiple delay peaks are extracted from the multipath delay spread parameters, wherein each delay peak corresponds to a propagation path; Based on the delay difference between the peak delay corresponding to each propagation path and the earliest arrival delay peak, the additional propagation time of the propagation path relative to the shortest path is determined. The additional propagation distance of the propagation path relative to the shortest path is calculated based on the additional propagation time and the propagation speed of electromagnetic waves in the current frequency band, including: The corresponding electromagnetic wave propagation speed is determined based on the operating frequency in the preset emission source parameters. Based on the medium type of the region through which the propagation path passes in the three-dimensional propagation environment model, the relative propagation speed correction coefficient of electromagnetic waves in different media is obtained. The additional propagation time is divided into segments according to the different medium regions traversed by the propagation path, and the additional propagation distance of each segment is calculated using the relative propagation speed correction coefficient of the corresponding medium. The additional propagation distance of the propagation path relative to the shortest path is obtained by summing the additional propagation distance of all segments; The additional propagation distance is added to the shortest path distance to obtain the propagation distance of the corresponding propagation path; Combining the propagation direction and the propagation distance, reverse ray tracing is performed starting from the location of the mismatch monitoring station, and the intersection of the reverse ray with the geographical elements in the three-dimensional propagation environment model is determined as the environmental verification area; Cluster analysis is performed on the environmental area to be verified to determine the environmental correction unit. The environmental parameters of the environmental correction unit are corrected according to the field strength deviation value, and the correction results are updated to the three-dimensional propagation environment model. Using the updated three-dimensional propagation environment model, ray tracing calculations are performed on multiple preset candidate station deployment schemes to obtain field strength distribution maps. Based on the field strength distribution maps, the preset candidate station deployment scheme with the best radio performance is determined as the target scheme.

2. The method according to claim 1, characterized in that, The step of combining the propagation direction and the propagation distance to perform reverse ray tracing from the location of the mismatch monitoring station, and determining the intersection of the reverse ray with the geographical features in the three-dimensional propagation environment model as the environmental verification area, includes: Starting from the location of the mismatch monitoring station, a tracking ray is emitted in the opposite direction to the signal propagation direction; The effective search range of the tracking ray is determined based on the propagation distance, and the intersection points of the tracking ray with the building surface, terrain undulation surface and vegetation cover surface in the three-dimensional propagation environment model are detected within the effective search range. Obtain the three-dimensional coordinates and geographic feature type of each intersection point; For each intersection location, the corresponding scale of the scope to be verified is determined according to the geographic feature type, and a spatial region corresponding to the scale of the scope to be verified is established with the three-dimensional coordinates of the intersection location as the center as the environmental verification area.

3. The method according to claim 1, characterized in that, The step of performing cluster analysis on the environmental area to be verified to determine environmental correction units includes: Calculate the spatial distance between any two environmental areas to be verified; The environmental areas to be checked with a spatial distance smaller than the preset clustering radius are divided into the same candidate correction unit; Obtain the number of mismatch monitoring stations traced back to each candidate correction unit, and use the number of mismatch monitoring stations as the environmental distortion of the corresponding candidate correction unit; Candidate correction units whose environmental distortion is higher than a preset distortion threshold are selected as environmental correction units.

4. The method according to claim 1, characterized in that, The step of correcting the environmental parameters of the environmental correction unit based on the field strength deviation value and updating the correction result to the three-dimensional propagation environment model includes: For each of the environmental correction units, the average field strength deviation of all mismatch monitoring stations traced back to the environmental correction unit is obtained; The adjustment amount is determined based on the absolute value of the average field strength deviation, and the direction of environmental parameter adjustment is determined based on the positive or negative direction of the average field strength deviation. The environmental parameters of the environmental correction unit are adjusted according to the adjustment direction and the adjustment amount of the environmental parameters. The environmental parameters include building height parameters, surface roughness parameters, and medium electromagnetic property parameters. The adjusted environmental parameters are updated to the corresponding environmental correction unit positions in the three-dimensional propagation environment model.

5. The method according to claim 1, characterized in that, The step of determining the optimal radio performance of a preset candidate station deployment scheme based on the field strength distribution map as the target scheme includes: Based on the field strength distribution map, areas with field strength higher than the reception threshold in each of the preset candidate station deployment schemes are extracted as effective coverage areas, and the coverage rate is obtained by calculating the ratio of the area of ​​the effective coverage area to the total area of ​​the target area. The region in each of the preset candidate station deployment schemes that simultaneously receives signals from multiple transmission sources and whose signal strength difference is less than the protection ratio is extracted as the interference region, and the ratio of the area of ​​the interference region to the area of ​​the effective coverage area is calculated to obtain the interference region proportion. Calculate the spectrum utilization efficiency based on the unit spectrum bandwidth and the area of ​​the corresponding effective coverage area in each of the preset candidate station deployment schemes. The coverage, interference area ratio, and spectrum utilization efficiency of each preset candidate station deployment scheme are weighted and calculated to obtain a radio performance evaluation value. The preset candidate station deployment scheme with the highest radio performance evaluation value is selected as the target scheme.

6. A radio prediction analysis system, characterized in that, The radio prediction analysis system includes: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code including computer instructions, and the one or more processors call the computer instructions to cause the radio prediction analysis system to perform the method as described in any one of claims 1-5.

7. A computer-readable storage medium comprising instructions, characterized in that, When the instructions are executed on the radio predictive analysis system, the radio predictive analysis system performs the method as described in any one of claims 1-5.

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