Base station coverage partition calculation method in wireless network optimization

Abstract

The invention discloses a base station coverage partition calculation method in wireless network optimization, and relates to the technical field of wireless communication networks, and the method comprises the steps: obtaining at least two first single-frequency-band cells corresponding to at least two frequency bands in a to-be-optimized region, and precisely locking a multi-frequency-band optimization object; for each frequency band, if a first single-frequency-band cell of the frequency band meets a first conflict condition, integrating the first single-frequency-band cell into a first region set in a preset first processing mode, eliminating single-frequency-band coverage conflicts, and improving single-frequency-band partition precision and resource efficiency; and if the first region set meets a preset second conflict condition, integrating the first region set into a second region set by using a second processing mode, thereby eliminating the cross-band coverage conflict, and finally improving the accuracy of network optimization in the multi-band coexistence scene.

Description

Technical Field

[0001] The present application relates to the technical field of wireless communication networks, and in particular to a method for calculating base station coverage zones in wireless network optimization. Background Art

[0002] In the field of wireless communications, wireless network cell coverage zones, formed by base stations, are used to enable refined monitoring of regional network indicators and are a crucial foundation for network optimization. Currently, wireless network cell coverage zones typically use a unified rule to divide coverage areas. This results in a disconnect between the actual coverage of each base station and each frequency band. Especially in scenarios where multiple frequency bands coexist, a single zone logic struggles to adapt to the actual signal distribution across different frequency bands, making network optimization based on these zones inaccurate.

[0003] Therefore, new methods and new ideas are urgently needed to break through the bottleneck of traditional single optimization routines and solve the problem of insufficient accuracy of network optimization in multi-band coexistence scenarios.

[0004] The above content is only used to assist in understanding the technical solution of this application and does not mean that the above content is recognized as prior art. Summary of the Invention The main purpose of this application is to provide a base station coverage partition calculation method, device and computer-readable storage medium in wireless network optimization, aiming to improve the accuracy of network optimization in multi-band coexistence scenarios.

[0005] To achieve the above objectives, the present application proposes a method for calculating base station coverage zones in wireless network optimization, the method comprising: Acquire at least two first single-frequency-band cells corresponding to at least two frequency bands in the area to be optimized; For each frequency band, if the first single-frequency-band cells corresponding to the frequency band meet a preset first conflict condition, calling a preset first processing method to integrate the first single-frequency-band cells into a first area set, where the first area set includes mutually non-overlapping second single-frequency-band cells; If the first area sets corresponding to the frequency bands meet the preset second conflict conditions, the preset second processing method is called to integrate the first area sets into a second area set, wherein the second area set includes non-overlapping third single-band cells and / or multi-band cells, wherein the third single-band cell is a cell that belongs only to a single frequency band, and the multi-band cell is a cell that belongs to at least two frequency bands at the same time.

[0006] In addition, to achieve the above-mentioned purpose, the present application also provides a base station coverage partition calculation device in wireless network optimization, wherein the base station coverage partition calculation device in wireless network optimization includes a memory, a processor, and a base station coverage partition calculation device program in wireless network optimization stored on the memory and runnable on the processor. When the base station coverage partition calculation device program in wireless network optimization is executed by the processor, the steps of the base station coverage partition calculation device method in wireless network optimization are implemented.

[0007] In addition, to achieve the above-mentioned purpose, the present application also provides a storage medium, which is a computer-readable storage medium, and the computer-readable storage medium stores a base station coverage partition calculation device program in wireless network optimization. When the base station coverage partition calculation device program in wireless network optimization is executed by the processor, the steps of the above-mentioned base station coverage partition calculation device method in wireless network optimization are implemented.

[0008] One or more technical solutions proposed in this application have at least the following technical effects: by obtaining at least two first single-band cells corresponding to at least two frequency bands in the area to be optimized, accurate locking of network optimization targets for multi-band coexistence is achieved, avoiding omission of key frequency bands or cells, clarifying initial boundaries for subsequent frequency band division and cross-band conflict processing, and reducing data redundant operations in irrelevant areas; for each frequency band, if the first single-band cells corresponding to the frequency band meet a preset first conflict condition, a preset first processing method is invoked to integrate the first single-band cells into a first area set, thereby eliminating coverage conflicts within the single frequency band, reducing co-frequency signal interference and unnecessary switching, and improving the accuracy of single-band coverage partitioning and resource utilization efficiency; if the first area sets corresponding to the frequency bands meet a preset second conflict condition, a preset second processing method is invoked to integrate the first area sets into a second area set, thereby eliminating cross-band coverage conflicts, distinguishing frequency band coverage attributes, retaining the value of multi-band collaboration, and providing a structured and feasible regional basis for multi-band collaborative optimization, thereby improving the accuracy of network optimization in multi-band coexistence scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0010] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0011] Figure 1This is a flow chart of a first embodiment of a method for calculating base station coverage zones in wireless network optimization of this application; Figure 2 A schematic diagram of the starting grid corresponding to the minimum longitude and latitude in the lower left corner and the ending grid corresponding to the maximum longitude and latitude in the upper right corner involved in this application; Figure 3 A schematic diagram of the spatial overlap between the selected candidate grids and the area to be optimized involved in this application; Figure 4 A schematic diagram of the latitude and longitude of the lower left corner of the grid after conversion involved in this application; Figure 5 This is a schematic diagram of the point P0 with the smallest longitude and latitude in the grid center point set involved in this application as the starting point; Figure 6 A schematic diagram of generating a convex polygon involved in this application; Figure 7 This is a schematic diagram of the same frequency band inclusion relationship involved in this application; Figure 8 A schematic diagram of the intersection relationship of the same frequency band involved in this application; Figure 9 A schematic diagram of the cross-band intersection relationship involved in this application; Figure 10 This is a structural diagram of a base station coverage partition calculation device in wireless network optimization involved in an embodiment of the present application.

[0012] The purpose, features and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0013] It should be understood that the specific embodiments described herein are merely used to explain the technical solutions of the present application and are not intended to limit the present application.

[0014] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0015] Current methods for zoning outdoor wireless network cell coverage primarily rely on the latitude and longitude of industrial cells, azimuth angles, and preset zoning outlines, which present significant limitations. First, they fail to consider the differences in propagation characteristics of signals in different frequency bands. A single zoning method cannot truly reflect the actual coverage area of ​​each frequency band. Furthermore, they place high demands on the accuracy of parameters such as base station latitude and longitude and altitude, making it difficult to guarantee data accuracy in various cities and regions, resulting in insufficient zoning accuracy. Second, they rely on manual maintenance and updates, making it impossible to respond in real time to changes in frequency resources and dynamic adjustments to network loads. Consequently, coverage zoning lags, impacting frequency optimization and resource balancing.

[0016] The present application provides a solution for accurately locking in network optimization targets for multi-band coexistence by obtaining at least two first single-band cells corresponding to at least two frequency bands in an area to be optimized, thereby avoiding missing key frequency bands or cells, clarifying initial boundaries for subsequent frequency band division and cross-band conflict processing, and reducing data redundancy calculations in irrelevant areas. For each frequency band, if the first single-band cells corresponding to the frequency band meet a preset first conflict condition, a preset first processing method is invoked to integrate the first single-band cells into a first area set, thereby eliminating coverage conflicts within a single frequency band, reducing co-frequency signal interference and unnecessary switching, and improving the accuracy of single-band coverage partitioning and resource utilization efficiency. If the first area sets corresponding to the frequency bands meet a preset second conflict condition, a preset second processing method is invoked to integrate the first area sets into a second area set. Multi-band cells associate multiple frequency bands and corresponding cells, thereby eliminating cross-band coverage conflicts, distinguishing frequency band coverage attributes, retaining the value of multi-band collaboration, and providing a structured and feasible regional basis for multi-band collaborative optimization, thereby improving the accuracy of network optimization in multi-band coexistence scenarios.

[0017] It should be noted that the execution subject of this embodiment can be a computing service device with data processing, network communication, and program execution capabilities, such as a tablet computer, personal computer, mobile phone, database system, etc., or a device capable of performing the aforementioned functions, such as a base station coverage zone calculation device used in wireless network optimization. This embodiment and the following embodiments will be described below using a base station coverage zone calculation device used in wireless network optimization as an example.

[0018] Based on this, the embodiment of the present application provides a base station coverage partition calculation method in wireless network optimization, referring to Figure 1 , Figure 1 This is a flowchart of the first embodiment of the base station coverage partition calculation method in wireless network optimization of this application.

[0019] In this embodiment, the base station coverage partition calculation method in wireless network optimization includes steps S10-S30: Step S10: obtaining at least two first single-frequency-band cells corresponding to at least two frequency bands in the area to be optimized; In this embodiment, the area to be optimized refers to a specific geographical range for performing logical partitioning adjustment of outdoor wireless network base station coverage, and the range must meet the core condition of including at least two first single-band cells corresponding to at least two frequency bands. For example, the area to be optimized includes X-band cells and Y-band cells, and the X-band cells include cell A and cell A1, and the Y-band cells include cell B and cell B1.

[0020] Optionally, step S10 includes determining the source type of the area to be optimized, wherein the source type includes a pre-stored multi-band scene area and an externally imported multi-band area; if it is a pre-stored multi-band scene area, the first area data corresponding to the area to be optimized is called from a preset database; if it is an externally imported multi-band area, the second area data corresponding to the area to be optimized imported by the front-line maintenance personnel through the interactive interface is received, wherein the first area data and the second area data both contain a sequence of area contour points and cell association information corresponding to the multi-band.

[0021] Furthermore, it should be noted that a pre-stored multi-band scenario area refers to a fixed geographic area pre-stored in the database, confirmed through a preliminary network survey to contain at least two cells with different frequency bands, and associated with a specific scenario type. An externally imported multi-band area refers to a temporary geographic area manually drawn or uploaded by frontline maintenance personnel through an interactive interface and confirmed to contain multi-band cells through real-time verification. Area outline point sequences are stored in the WKT (Well-Known Text) format.

[0022] Optionally, when conventional wireless network optimization is required, the system automatically retrieves a list of pre-stored areas from a preset database (such as a MySQL (MySQL Database Management System) database); the system filters the pre-stored areas based on multi-band cell association information, retaining only areas that "contain at least two cells of different frequency bands" and synchronizes them to the subsequent optimization area geographic gridding step; the pre-stored areas have been verified for multi-band attributes in advance, and repeated verification can be skipped to improve optimization efficiency.

[0023] Optionally, front-line maintenance personnel upload regional data through the interactive interface; the system automatically associates the base station MR (Measurement Report) data with the industrial parameter data, extracts the frequency band information of all cells in the imported area, and determines whether it contains at least two different frequency bands. For example, if a "new residential area" is imported and the system verifies that it only contains 3.5GHz cells, it will prompt "Multi-band cell areas need to be supplemented, otherwise subsequent frequency band coverage division cannot be carried out"; after verification, the system receives the second area data corresponding to the area and marks it as an area to be optimized; if the external imported area has a single frequency band, it needs to be verified to ensure that it meets the premise of multi-band optimization to avoid the subsequent multi-band coverage range division technical solution from being unable to be implemented.

[0024] Step S20: For each frequency band, if the first single-frequency-band cells corresponding to the frequency band meet a preset first conflict condition, calling a preset first processing method to integrate the first single-frequency-band cells into a first area set, where the first area set includes mutually non-overlapping second single-frequency-band cells; In this embodiment, for each frequency band, which refers to each frequency band within the area to be optimized, frequency band X or frequency band Y, the preset first conflict condition is that there is a spatial intersection between the first single-frequency-band cells. The preset first processing method is to divide the first single-frequency-band cells with the spatial intersection into mutually non-intersecting second single-frequency-band cells. For example, the coverage area of ​​cell A with a frequency band of 1.8 GHz overlaps with the coverage area of ​​cell B (the intersection area is greater than 0), or cell A completely contains cell B (the coverage area of ​​cell B is less than that of cell A, and the convex hull point set of cell B is within cell A). If cell A contains cell B, B is merged into A. B is no longer treated as an independent area. For example, the convex hull point set of A absorbs the point set of B, and the coverage area of ​​A is recalculated. If only an intersection relationship exists (no inclusion), the smaller area B is retained and becomes the second single-band cell. The intersection is subtracted from the larger area A. If A is divided into multiple sub-areas, forming the second single-band cell, the sub-areas need to be added to the to-be-processed set. Otherwise, the point set and area of ​​A are updated to obtain the first area set, which contains the mutually non-intersecting second single-band cells.

[0025] Optionally, the first area set is a set of non-overlapping coverage areas generated after conflict processing of the first single-band cell, and each area only contains the signal of this frequency band. For example, in the 1.8GHz frequency band, the coverage areas of cells A and B have no overlap after processing, and together constitute the first area set, thereby solving the resource waste caused by overlapping cell coverage within the frequency band and improving resource utilization within the frequency band.

[0026] Step S30: If each first area set corresponding to each frequency band meets a preset second conflict condition, calling a preset second processing method to integrate each first area set into a second area set, wherein the second area set includes mutually non-overlapping third single-band cells and / or multi-band cells, wherein the third single-band cell is a cell belonging to only a single frequency band, and the multi-band cell is a cell belonging to at least two frequency bands at the same time; In this embodiment, if there is an intersection between the second single-band cells of different frequency bands of each base station, the multi-band conflict processing logic is triggered to determine whether the preset second conflict condition is met. The preset second processing method is to divide the second single-band cells with intersection into non-intersecting third single-band cells and / or multi-band cells.

[0027] Optionally, if region A of frequency band X and region B of frequency band Y only intersect (do not include each other), the intersection region is subtracted from each of A and B, with the intersection region being region C. If multiple subregions are generated after subtracting the intersection, each subregion is added to the corresponding frequency band's pending set. If region A of frequency band X contains region B of frequency band Y, region B is no longer considered an independent region, and region A is subtracted from the intersection region. If subregions are generated from region A, they are used as a third single-band cell. Intersection region C is designated as a "multi-band XY cell" and added to the multi-band pending set, with associated frequency bands X and Y and their corresponding cells (e.g., cell A for the 1.8 GHz band and cell B for the 2.6 GHz band).

[0028] Optionally, after multi-band conflict processing, a set of non-overlapping coverage areas is generated, namely the second area set. The non-overlapping coverage area set includes two types of areas: a third single-band cell (such as area A of band X minus the intersection, an independent area without overlap) and a multi-band cell (such as the intersection area C, associated bands X, Y and corresponding cells, marked as "multi-band XY cell"). By splitting and generating mixed areas, the resource conflict problem caused by the traditional method of ignoring multi-band overlap is solved, and precise multi-band coverage is achieved.

[0029] In this embodiment, by obtaining at least two first single-band cells corresponding to at least two frequency bands in the area to be optimized, the multi-band optimization object is accurately locked; for each frequency band, if its first single-band cell meets the first conflict condition, it is integrated into a first area set using a preset first processing method to eliminate single-band coverage conflicts and improve single-band partitioning accuracy and resource efficiency; if the first area set meets the second conflict condition, it is integrated into a second area set using a preset second processing method to eliminate cross-band coverage conflicts, and ultimately improve the accuracy of network optimization in a multi-band coexistence scenario.

[0030] Based on the first embodiment of the present application, in the second embodiment of the present application, the same or similar contents as those in the above-mentioned embodiment 1 can be referred to the above introduction and will not be repeated hereafter. On this basis, before step S10, it also includes: Step B40, performing geographic rasterization processing on the area to be optimized using a preset raster accuracy and a preset raster algorithm, and generating a raster list table for the area to be optimized; In this embodiment, the preset grid accuracy refers to the spatial resolution of the grid, which can be set to 20 meters × 20 meters or dynamically adjusted according to optimization requirements. It is used to determine the size of the geographic grid to ensure that the granularity of subsequent data processing is adapted to different scenarios. The preset grid algorithm uses an algorithm including but not limited to quadtree partitioning or regular grid partitioning, such as a regular grid partitioning algorithm, which divides the geographic scope of the area to be optimized into equal-sized grids row by row / column starting from the upper left corner latitude and longitude according to the preset accuracy, discretizes the geographic space of the area to be optimized into regular grid units, and provides a unified spatial carrier for subsequent association of cell measurement data. The grid list table records information such as the unique identifier of each grid (such as the grid number), the geographic scope of the grid (upper left and lower right latitude and longitude), and the identifier of the area to be optimized, which is used for subsequent association of cell measurement data to form a spatial-measurement data correspondence.

[0031] Optionally, read the preset grid accuracy (such as 20 meters × 20 meters) and the preset grid algorithm (such as the regular grid division algorithm), calculate the required number and distribution of grids according to the geographical scope (extreme longitude and latitude of the area to be optimized), and determine the boundary coordinates of each grid; use the preset grid algorithm to cut the geographical space according to the longitude and latitude of the upper left corner of the area to be optimized according to the accuracy, generate regular grid cells, and mark the spatial position of each grid; traverse all grids, record the grid number, geographical scope, ID (Identifier) ​​of the area to be optimized, and other information to form a grid list table, which can convert the continuous geographical space into discrete grid cells, and provide a unified spatial reference for the subsequent correlation of multi-band cell measurement data.

[0032] Step B50, obtaining the cell measurement data matched with the grid list table, and converting the cell measurement data into rasterized data using a preset grid algorithm; In this embodiment, cell measurement data refers to data containing information such as the serving cell's unique identifier (ECI, Evolved Universal Terrestrial Radio Access Network) and frequency band, and the longitude and latitude of the measurement point, reflecting the signal characteristics of cells at different geographic locations. A preset gridding algorithm is reused to ensure consistency in the spatial division rules of the geographic grid and the data grid, enabling precise matching of measurement data with the geographic grid. The gridded data includes, but is not limited to, the cell's unique identifier (ECI), frequency band, grid unique identifier, the grid's top-left and bottom-right longitude and latitude, and key measurement indicators from the MR data. This creates a "geographic grid - cell frequency band - measurement data" association, linking the cell measurement data with the geographic grid and providing spatialized data for subsequent frequency band coverage analysis.

[0033] Step B60: grouping and converting the rasterized data according to different frequency bands to obtain a grid center point set of a first single-frequency-band cell, and generating the first single-frequency-band cell based on the grid center point set; In this embodiment, the rasterized data grouping and conversion processing refers to grouping the rasterized data first by frequency band and then by cell unique identifier ECI to obtain a sub-data set of "single frequency band - single cell"; wherein, the conversion processing refers to extracting the coordinates of the grid center point from each sub-data set, such as the average value of the upper left longitude and latitude and longitude and the lower right longitude and longitude of the grid, to form a structured point set; the grid center point set refers to the center point coordinate set of all grids corresponding to each "single frequency band - single cell"; the preset scanning method includes but is not limited to the Graham scanning method (Graham's scan, an algorithm for calculating the convex hull of a plane point set), by performing convex hull calculation on the grid center point set to generate the minimum convex polygon that can surround all center points as the coverage area of ​​the first single frequency band cell.

[0034] Optionally, the first single-band cell refers to a geographical area generated by a preset scanning method, representing the actual coverage of a single cell in a certain frequency band, represented by a polygonal boundary point sequence, and including information such as a unique regional identifier and a boundary longitude and latitude point sequence.

[0035] Optionally, step S30 also includes step B70, which generates a logical coverage partition cell relationship result set as a basis for performing network optimization steps in a multi-band coexistence scenario, wherein the logical coverage partition result includes the spatial information of each multi-band cell coverage area and the corresponding frequency band information.

[0036] Optionally, based on the second area set, a structured data set organized according to a preset data structure is used to record the spatial range, associated frequency band and corresponding cell of each logical coverage partition, which is the core basis for subsequent network optimization in multi-band coexistence scenarios.

[0037] Optionally, the second area set includes information such as a convex hull point set, associated frequency bands, associated cells, and area of ​​each area, and the preset data structure is defined as a hierarchical relationship and field requirements of Partition-Area-Point.

[0038] Optionally, traverse each coverage area in the second area set, extract information one by one according to the data structure fields to realize the field mapping of regional data and data structure; encapsulate the mapped fields into structured data according to the hierarchical relationship of the data structure, and obtain the encapsulation result according to the Partition-Area-Point hierarchy; output the logical coverage partition cell relationship result set, wherein the result set is output in a compatible format, such as JSON, database table, and the logical coverage partition cell relationship result set contains at least spatial information, frequency band information and cell association information, so as to optimize switching parameters and avoid frequent switching between frequency bands.

[0039] In this embodiment, the region is rasterized using a preset grid accuracy and algorithm to generate a grid list table, converting the abstract region into a standard computable grid, laying the foundation for data association. Cell measurement data is matched and converted into rasterized data containing frequency bands, binding the discrete data to the grid. The first single-band cell grid center point set is obtained by grouping by frequency band, and the first single-band cell is generated using a preset scanning method. This provides a basis for multi-band optimization, avoids confusion of frequency band attributes, and improves optimization accuracy.

[0040] Based on the above embodiments of the present application, in the third embodiment of the present application, the same or similar contents as those in the above embodiment 1 can be referred to the above introduction and will not be described in detail later. On this basis, step B40 includes: Step B401, parsing the regional contour point sequence and extracting the longitude and latitude coordinates of all contour points; In this embodiment, the regional contour point sequence refers to the set of boundary point coordinates of the area to be optimized, the regional contour point sequence and the corresponding multi-band cell association information, a geometric parsing library based on the OGC (Open Geospatial Consortium) standard, or a custom string segmentation algorithm, which is used to extract coordinate points in WKT.

[0041] Step B402, traverse the longitude and latitude coordinates of all contour points to determine the minimum longitude and latitude of the lower left corner and the maximum longitude and latitude of the upper right corner; In this embodiment, the longitude and latitude coordinates of the contour points are the coordinates of the boundary points of the area to be optimized; the minimum longitude and latitude of the lower left corner is: The point with the smallest longitude and latitude among all contour points is the starting reference point for geographic rasterization, where: Longitude, representing longitude, Latitude, representing latitude; the maximum longitude and latitude in the upper right corner: It is the point with the largest longitude and latitude among all contour points. It is used to determine the diagonal vertices of the circumscribed rectangle and used for the subsequent rasterization starting traversal, so as to ensure that the subsequent rasterization range strictly covers the area to be optimized, and solve the problem of grid omission / redundancy caused by extreme value calculation errors in traditional methods.

[0042] Step B403, based on the preset grid accuracy and the preset grid algorithm, calculate the starting grid corresponding to the minimum longitude and latitude of the lower left corner and the ending grid corresponding to the maximum longitude and latitude of the upper right corner, wherein the longitude difference and latitude difference corresponding to the grid accuracy of 20 meters are calculated. , latitude difference The grid algorithm is the latitude and longitude algorithm of the lower left point of the 20-meter grid corresponding to any spatial point in the area to be optimized: Among them, X is the longitude of any spatial point in the area to be optimized, Y is the latitude of any spatial point in the area to be optimized, [ ] is rounded down, and the longitude and latitude of the lower left corner of the starting grid are , the latitude and longitude of the lower left corner of the ending grid is

[0043] In this embodiment, if Figure 2 As shown, Figure 2 This is a schematic diagram of the starting grid corresponding to the minimum longitude and latitude in the lower left corner and the ending grid corresponding to the maximum longitude and latitude in the upper right corner involved in this application. The x-axis represents longitude and the y-axis represents latitude. Figure 2 middle, is the lower left corner, The longitude and latitude differences corresponding to the upper right corner point and the grid accuracy is 20 meters, where the longitude difference , latitude difference , is a quantitative standard of grid size, which determines the spatial resolution of geographic grid, such as Figure 2 In the example, the grid side length is 20 units, where the coordinate axis scale is 0→20→40→60; the budget formula is , calculate the longitude and latitude of the lower left point of the 20-meter grid corresponding to the longitude and latitude (X, Y) of any spatial point. The core is to round down ([ ]) to achieve coordinate alignment. For example, the point (20.0001, 10.0001) is aligned to (20, 10) after calculation according to the formula to ensure that the upper right grid of the optimization area is covered. The row and column range of the grid traversal is determined by the longitude and latitude of the lower left of the starting and ending grids, ensuring that the grid generated by the subsequent traversal strictly wraps the polygon, solving the problem of the grid range being out of line with the target area in the traditional method.

[0044] Step B404: From the starting grid to the ending grid, the longitude difference is incremented along the longitude direction. , each incremental latitude difference in the latitude direction All candidate rasters are generated by traversing, and the rasters that overlap with the area to be optimized are screened out to form a raster list table.

[0045] In this embodiment, Figure 3 As shown, Figure 3 This is a schematic diagram of the spatial overlap between the candidate grids selected for this application and the area to be optimized. The longitude direction is as follows: Increment ( Figure 3 Horizontal axis 0→20→40→60), latitude direction press Increment ( Figure 3The vertical axis is 0→20→40→60), and the grid segmentation is traversed with a precision of 20 meters; from the lower left of the starting grid (20,10) in step A203 to the upper right of the ending grid (60,60), covering Figure 3 The row and column range of the grid corresponding to the area to be optimized (horizontal axis 20 / 40 / 60, vertical axis 10 / 30 / 50).

[0046] Optionally, generate all grids covering the "start→end" range, with the lower left latitude and longitude of each grid being (20+20*i,10+20*j), where i and j are traversal indices, e.g. i=0, j=0 corresponds to (20,10), * represents multiplication, used to calculate the product of step length and index), and determine whether the candidate grid is consistent with the target grid. Figure 3 The polygons (i.e. the area to be optimized) intersect, and the intersecting grids are retained ( Figure 3 medium grey raster, overlapping with polygon boundaries / interiors), filtering non-intersecting rasters ( Figure 3 The white grid in the middle has no intersection with the polygon), and the filtered intersecting grids are sorted according to the preset format to output the optimized regional grid list table. The preset format includes but is not limited to the region type, region ID, grid ID, center longitude and latitude, etc., to ensure that the subsequent cell measurement data only matches the valid grids and avoids interference from invalid grids.

[0047] In this embodiment, by parsing the sequence of regional contour points, the longitude and latitude of all contour points are extracted, and the abstract boundary of the area to be optimized is converted into computable spatial coordinates; these coordinates are traversed to determine the minimum longitude and latitude in the lower left and the maximum longitude and latitude in the upper right, and the circumscribed rectangle of the area is framed; according to the preset grid accuracy and algorithm, the starting grid corresponding to the lower left and the ending grid corresponding to the upper right are calculated, and the geographic coordinate boundary is converted into a standardized grid boundary; from the starting to the ending grid, candidate grids are generated by traversing according to the longitude difference and latitude difference, and the grids overlapping with the regional space are screened out to form a list table, which not only solves the problem of invalid grids occupying resources, but also provides a standard spatial carrier for the subsequent optimization, ensuring multi-band optimization of precise geographic raster data.

[0048] Based on the above content of the present application, in the fourth embodiment of the present application, the same or similar content as the above embodiment 1 can be referred to the above introduction and will not be repeated hereafter. On this basis, in step B50, it also includes: Step B501: For the longitude and latitude interval between the start grid and the end grid in the grid list table, obtain cell measurement data of each sampling point in the longitude and latitude interval, wherein the cell measurement data includes the longitude and latitude coordinates of each sampling point; In this embodiment, the rectangular spatial range defined by the starting and ending grids; the geographic sampling points recorded in the cell measurement data, including information such as latitude and longitude, serving cell ECI, and frequency band, are basic data reflecting cell signal characteristics; relying on grid boundaries to clearly define the spatial screening range; providing a precise data source for rasterized data conversion, achieving precise binding of the spatial range of the area to be optimized with the cell measurement data, avoiding the inefficiency of global data traversal, reducing the amount of data subsequently processed, and improving the efficiency of multi-band coverage analysis.

[0049] Step B502: Calling a preset grid algorithm to convert the latitude and longitude coordinates of each sampling point to obtain the converted latitude and longitude of the lower left corner of the grid to which it belongs; In this embodiment, a grid coordinate conversion algorithm is reused, the latitude and longitude of the selected sampling point are input, and the latitude and longitude of the lower left corner of the grid to which the sampling point belongs are output as the core index of the subsequent matching grid list table. This achieves accurate association of cell measurement data with geographic grids and provides core support for the subsequent statistical compilation of grid lists by cell and frequency band.

[0050] Alternatively, as Figure 4 As shown, Figure 4 This is a schematic diagram of the latitude and longitude of the lower left corner of the grid after conversion involved in this application. Figure 4 The middle dots are sampling points, and the black boxes are 20-meter grid accuracy. Figure 4 The black box in the middle is a 20-meter precision grid, and the dots are MR sampling points. After conversion, all dots are aligned to the latitude and longitude of the lower left corner of the black box grid to which they belong, verifying the accuracy of the "data-space" association. This solves the problem of random distribution of sampling points in traditional wireless network optimization and the inability to accurately bind to the grid, and provides an accurate spatial index for statistical grid lists grouped by cell and frequency band.

[0051] Step B503 , the converted longitude and latitude of the lower left corner of the grid to which it belongs are associated and matched with the grid identifier of the grid in the grid list table to form rasterized data.

[0052] In this embodiment, the latitude and longitude of the lower left corner of the converted grid are the grid boundary coordinates after the sampling points are aligned; the grid identifier is the unique ID of each valid grid in the grid list table; and the rasterized data is structured data that integrates the cell measurement data and the grid spatial information.

[0053] Optionally, Figure 4 As shown, the black boxes are grids, the dots are sampling points and the 20-meter grid accuracy is used as an example. Figure 4There are 15 black square grids and 15 dot sampling points in the figure. After matching, all the dots are associated with the grid ID and spatial information of the corresponding black squares, forming 10 rasterized data, realizing the three-dimensional association of "cell measurement data - grid space - frequency band attributes", providing direct data support for grouping by frequency band and cell, and solving the problem of traditional data dispersion and lack of spatial association.

[0054] In this embodiment, based on the longitude and latitude interval from the start to the end grid, the cell measurement data of each sampling point in the interval is determined, and the valid data in the area is accurately screened; the preset grid algorithm is called to convert the longitude and latitude of the sampling point to obtain the lower left longitude and latitude of the grid to which it belongs, so that the discrete coordinates are aligned with the standard grid boundary; the converted lower left longitude and latitude are associated with the grid identifier to form rasterized data, and a structured association of "cell measurement data - geographic grid - frequency band attributes" is constructed, which solves the problem that traditional data has no spatial attributes and is difficult to support frequency band coverage analysis, and ensures that multi-band optimization is carried out based on precise space-data association.

[0055] Based on the above content of the present application, in the fifth embodiment of the present application, the same or similar content as the above embodiment 1 can be referred to the above introduction, and no further details will be given later. On this basis, the rasterized data includes frequency band information and cell identification, and step B60 includes: Step B601: grouping the rasterized data according to the combination of frequency band information and cell identifier to obtain a corresponding joint group, wherein the joint group includes all rasterized data corresponding to the same frequency band and the same cell; In this embodiment, rasterized data refers to structured data that integrates cell identification, frequency band, and raster spatial information. The frequency band and cell identification joint group uses (frequency band value, ECI value) as a unique association key, and aggregates all rasterized data corresponding to the key to form a data set. For example, the 30 rasterized data corresponding to "1.8 GHz frequency band + ECI = 1001" constitute a joint group, realizing "single frequency band - single cell" data isolation, ensuring that the coverage area constructed by the subsequent Graham scanning method only reflects the signal distribution of a single cell under a single frequency band.

[0056] Step B602: extract the latitude and longitude of the upper left corner and the latitude and longitude of the lower right corner corresponding to each grid in each joint group, and calculate the coordinates of the center point of each grid in the joint group; In this embodiment, the longitude and latitude of the four corners of the grid are the longitude and latitude of the upper left corner recorded in the rasterized data. and the latitude and longitude of the lower right corner , defining the spatial extent of the grid. The center point is calculated using the unified rule of the longitude and latitude of the four corners of the grid. The longitude is the average of the upper left and lower right longitudes. The formula is:

[0057] The same applies to latitude. Ensure that the center point is the geometric center of the grid. Summarize the calculated center point coordinates to form a grid center point set corresponding to the joint group. Calculate the center point using a unified formula to ensure the standardization of grid spatial information within a single-band cell, avoid manual calculation errors, and improve the accuracy of subsequent coverage area generation.

[0058] Step B603: Aggregate the center point coordinates of all grids in the same joint group to form a grid center point set of the first single-band cell.

[0059] In this embodiment, the joint group refers to a set of rasterized data aggregated with (frequency band, ECI) as a unique identifier; a point set is formed by summarizing the coordinates of the center points of all grids in the same joint group.

[0060] Optionally, select a single joint group (e.g., (1.8GHz, 1001)), where each rasterized data item in this group carries the center point coordinates (in latitude and longitude format, such as (30.0, 20.0)). Traverse all rasterized data items within the joint group, extract the center point coordinates for each item, and store them in a list. If duplicate grids exist, as if the same grid has been matched multiple times, remove the duplicate coordinates. Based on the grid range, verify that the coordinates are within the area to be optimized, eliminating outliers that are miscalculated and fall outside the area. This converts the discrete spatial information of a single-band cell into a structured point set, resolving the pain point that scattered data cannot support coverage area calculations.

[0061] In this embodiment, rasterized data is grouped by frequency band and cell identifier to form a "frequency band-cell" joint group, thereby achieving structured classification of scattered data; the latitude and longitude of the upper left and lower right grids of each group are extracted, and the center point is calculated using a preset formula to convert the two-dimensional range of the grid into a standardized single point; the center points of the same joint group are aggregated to form a set of grid center points of a single-band cell, and discrete points are integrated to characterize its coverage trend, providing structured input for the subsequent scanning method to generate a continuous coverage area, ensuring that the coverage area fits the actual signal distribution, and solving the problem of traditional reliance on base station parameter estimation being out of touch with reality.

[0062] Based on any of the above embodiments of the present application, in the sixth embodiment of the present application, the same or similar contents as those in the first embodiment can be referred to above and will not be described in detail. On this basis, in step B60, it also includes: Step C610: Select the point with the smallest longitude and latitude in the grid center point set as the starting point, and calculate the polar angle between the starting point and other center points in the grid center point set; In this embodiment, Figure 5 As shown, Figure 5The schematic diagram of the point P0 with the smallest longitude and the smallest latitude in the grid center point set involved in this application as the starting point is input, and the single-band cell grid center point set is input. The single-band cell grid center point set contains the longitude and longitude of the center points of all grids of the band-cell; the point with the smallest longitude in the set, or the smallest latitude if the longitudes are the same, is selected as the reference point for the Graham scan, such as Figure 5 The starting point is P0; the polar angle θi is the polar angle of point Pi relative to P0, which is calculated using the following formula: Among them, arctan is the inverse tangent function, which reflects the directional characteristics of Pi relative to P0.

[0063] Optionally, traverse the set of center points and initialize the extreme values , where +∞ is positive infinity, if ,renew 、 ;like and ,renew ;final Ensure that it is the "lower left point" of the collection, adapting to the counterclockwise sorting logic of Graham scan.

[0064] Step C612, sorting the polar angles in ascending order to obtain the ascending grid center points; In this embodiment, a set of polar angles and corresponding center point coordinates are input; a list of center points in ascending order of polar angles and distances from the same polar angle is output, providing a counterclockwise ordered grid center point set for subsequent Graham scan method to construct a convex hull.

[0065] Alternatively, if the polar angles of the two grid center points are equal, that is, they are collinear with the starting point P0, then they are sorted in ascending order of distance to P0, where the distance calculation formula is:

[0066] Here, d is the distance. It should be noted that points with a short distance are given priority to avoid missing inner points in the convex hull calculation, which would result in a larger coverage area.

[0067] Step C613, determining the positional relationship corresponding to the center points of the ascending grids, and screening out the convex polygon boundary point set that meets the preset stacking conditions in the positional relationship; In this embodiment, the first two points after polar angle sorting (the starting point P0 and the point with the smallest polar angle) are ) into the stack, where Graham scan requires at least 2 points to start convex hull construction); starting from the third point (index i=2), process each grid center point in turn : Let the top element of the stack be A (the last point), and the next element of the stack be B (the second last point); vector (from B to A), vector (From B to C, C is the current point ), cross product formula: If the cross product ≤ 0: exist In the clockwise direction or collinear, A is a "concave point" (destroying the counterclockwise winding of the convex hull), pop the top of the stack A, and repeat the judgment of the new top of the stack until the cross product is greater than 0 or there is only one point left in the stack; if the cross product is greater than 0: exist The counterclockwise direction of Push the points into the stack. After the traversal is complete, the points in the stack form a convex hull boundary in counterclockwise order. Because the polar angle sorting already ensures wraparound, no additional closure processing is required. Therefore, dynamic cross product filtering is performed to retain only the convex hull vertices that wrap around counterclockwise, excluding internal points and concave points, to generate a minimum convex polygon that truly reflects the signal coverage of a single-band cell.

[0068] like Figure 6 As shown, Figure 6 As a schematic diagram of generating a convex polygon involved in this application, a set of points to be processed is set: P0 (20, 20); P2 (30, 10); P3 (50, 15); P9 (35, 12); P8 (25, 25); P7 (22, 30); P6 (35, 35); P5 (45, 32); P4 (55, 25); with P0 as the origin, sort the points from small to large according to the polar angle (the angle rotated counterclockwise from the positive direction of the x-axis). If the polar angles are the same, the point with the farthest distance is retained. The order after sorting is: P0→P2→P9→P3→P4→P5→P6→P7→P8 (only non-starting points are processed, and the starting point is initialized separately); the starting point and the point with the smallest polar angle are pushed in: stack = [P0(20,20),P2(30,10)]; use the stack to store the convex hull vertices, and use the cross product to determine the direction of the three points: cross product > 0: counterclockwise direction, the current point is pushed into the stack; cross product ≤ 0: clockwise direction, the top of the stack is popped out, and the judgment is repeated to form a convex polygon that surrounds all points.

[0069] Step C614: sequentially connect adjacent points in the convex polygon boundary point set and close the first and last points to obtain a convex polygon as the first single-band cell; In this embodiment, a convex hull boundary point set is input and arranged in counterclockwise order; a closed convex polygon, i.e., a sequence of longitude and latitude points, is output to represent the actual coverage range of a single-band cell.

[0070] Optionally, Figure 6As shown, the convex hull vertex sequence is traversed, and the i-th vertex and the i+1-th vertex are connected in sequence: P0→P2→P3→P4→P5→P6→P7. This step uses the counterclockwise order of the convex hull vertices to ensure that the polyline always extends in the direction of "surrounding all grid points" to avoid crossing or sinking. The last vertex (P7) of the sequence is connected to the starting vertex (P0): P7→P0 is the minimum convex polygon after connection, which truly reflects the signal coverage range of the single-band cell, avoids introducing additional "sinks" or "redundant boundaries", ensures that the coverage range is consistent with the grid point distribution of the actual MR data, and improves the accuracy of multi-band coverage partitioning.

[0071] Optionally, after generating the closed convex polygon, the area of ​​the single-band cell (convex polygon) is calculated using a preset area calculation formula. The preset area calculation formula is: Where S is the area of ​​the single-band cell; n is the number of vertices of the convex polygon; is the longitude of the i-th vertex; is the latitude of the i-th vertex. Ensure that the polygons are connected end to end. Otherwise, the cumulative sum will not converge and the area calculation will be wrong. For example, taking a 3-vertex triangle as an example: The area calculation formula is: Where S is the area.

[0072] In this embodiment, the point with the smallest longitude and latitude in the grid center point set is selected as the starting point, and the polar angle between it and other points is calculated using a formula to unify the Graham scan benchmark and accurately characterize the directional characteristics; the polar angles are arranged in a preset manner to obtain a counterclockwise ordered sequence of center points; the position relationship is determined by the vector cross product, and the convex hull vertices that meet the stacking conditions are screened to remove concave and redundant points; the convex polygon (single-band cell coverage area) formed by connecting the convex hull points fits the actual signal, solves the problem of disconnection between traditional base station parameter estimation, and conforms to the GIS (Geographic Information System: Geographic Information System) format, providing a computational carrier for subsequent conflict detection and ensuring accurate coverage zoning.

[0073] Based on any of the above embodiments of the present application, in the seventh embodiment of the present application, the same or similar contents as those in the first embodiment can be referred to above and will not be described in detail. On this basis, before step S20, the following is also included: Step D80: Grouping the first single-band cells according to the frequency band dimension to obtain a first single-band cell set corresponding to each frequency band; Optionally, by grouping the scattered single-cell coverage areas by frequency band, a structured data set is provided for subsequent multi-cell coverage conflict detection in the same frequency band. This is a key prerequisite for achieving hierarchical optimization. Through structured clustering in the frequency band dimension, aggregate management of coverage areas within a single frequency band is achieved, which not only provides an accurate data set for subsequent conflict detection, but also supports the implementation of the entire multi-band optimization solution through hierarchical logic.

[0074] Step D90: For each frequency band, detecting whether a first area pair in the corresponding first single-frequency-band cell set has an intersection, wherein the first area pair is any two first single-frequency-band cells in the first single-frequency-band cell set; Optionally, the existence of an intersection in an area pair means that there is an intersection between two single-band cells in the area pair, and any two different single-band cells in the first single-band cell set are the first area pair; the intersection is that there is spatial overlap between the convex polygon boundaries of the two areas, wherein the intersection includes a partially overlapping correlation relationship and a completely contained inclusion relationship, and the judgment condition is that the intersection area is greater than 0 or the boundaries intersect.

[0075] Optionally, by traversing all area pairs and detecting spatial intersections, cell pairs with coverage conflicts within a single frequency band are identified, providing an accurate list of conflicting objects for subsequent conflict area integration. This is a prerequisite for optimizing coverage partitions within a single frequency band, thereby avoiding the problem of traditional methods missing conflicts in adjacent areas, ensuring that all coverage overlaps within a single frequency band are identified, and improving the integrity of coverage partitions.

[0076] Step D100: If at least one first area pair has an intersection, determining whether each first single-band cell in the first single-band cell set meets a first conflict condition; Step D110: If there is no intersection between the first area pairs, it is determined that the first single-band cells in the first single-band cell set do not meet the first conflict condition.

[0077] Optionally, if there is at least one conflicting first area pair in the first area pair set, which has an intersection relationship or an inclusion relationship, it is determined that the first single-frequency band cell meets the preset first conflict condition; if all area pairs in the first area pair set have no intersection and no inclusion relationship, it is determined that the first single-frequency band cell does not meet the preset first conflict condition, thereby achieving accurate conflict judgment of the first single-frequency band cell and providing a basis for subsequent resource allocation.

[0078] In this embodiment, the coverage areas of each first single-band cell are clustered according to the frequency band to obtain a first single-band cell set, thereby realizing isolation and hierarchical processing of data in the same frequency band; all first area pairs in the set are traversed to detect whether there is an intersection, thereby realizing full coverage detection of conflicts within a single frequency band; if there is an intersection, it is determined that the single-band conflict conditions are met; if there is no intersection, it is determined that it does not meet the conditions, and the conflict processing is directly skipped to avoid redundant calculations, reduce the amount of subsequent multi-band optimization data, improve overall efficiency, and solve the problem of resource waste in the traditional unified processing regardless of whether there is a conflict.

[0079] Based on any of the above embodiments of the present application, in the eighth embodiment of the present application, the same or similar contents as those in the first embodiment can be referred to above and will not be described in detail. On this basis, the steps of step S20 further include: Step B201: For each frequency band, for a first target single-frequency-band cell in a first single-frequency-band cell set, a portion of the first target single-frequency-band cell that does not intersect with other first single-frequency-band cells in the first single-frequency-band cell set is divided into a second single-frequency-band cell, wherein the first target single-frequency-band cell does not intersect with any other first single-frequency-band cells in the first single-frequency-band cell set, or intersects with at least one other first single-frequency-band cell in the first single-frequency-band cell set. Step B202: For any first single-band cell that has an intersection with other first single-band cells in the first single-band cell set, divide the intersection into second single-band cells to obtain a first area set including the second single-band cells.

[0080] Optionally, the first target single-frequency band cell has no intersection with other first single-frequency band cells in the first single-frequency band cell set, or has an intersection with at least one other first single-frequency band cell in the first single-frequency band cell set. For each frequency band, when processing the first target single-frequency band cell in the first single-frequency band cell set, the core is divided around the non-intersection of coverage within the single frequency band.

[0081] Optionally, for the non-overlapping portion of the first target single-band cell, regardless of whether the first target single-band cell has no overlap with all other first single-band cells in the first single-band cell set, or only overlaps with some other first single-band cells, the area that does not overlap with any other first single-band cells is directly divided into the second single-band cell. This area does not need to participate in conflict resolution and is the basic effective coverage area within the single band, ensuring coverage integrity and avoiding coverage loss due to excessive processing.

[0082] For the first target single-band cell that has an intersection with other first single-band cells in the first single-band cell set: the overlapping part with other first single-band cells needs to be divided into a second single-band cell separately; during the division process, it is necessary to avoid duplication with the aforementioned non-intersecting part, and ensure that the intersection part does not generate a new intersection with any other second single-band cell after division, so as to eliminate signal interference in the intersection area within the same frequency band, reduce invalid switching, and ensure signal stability.

[0083] Finally, all the second single-band cells obtained by division are integrated to form the first area set. All areas in this set pass the division verification and meet the requirement that there is no intersection between any two areas in a single frequency band. This not only integrates all effective coverage areas in a single frequency band, but also provides standardized basic coverage area input for subsequent multi-band conflict processing, ensuring the logical connection closed loop between single-band optimization and multi-band optimization.

[0084] Optionally, when it is detected that the intersection is a containment relationship, the first region pairs corresponding to the containment relationship are processed by removing the smaller ones and retaining the larger ones to obtain a first temporary region set; Optionally, the intersection includes relationships and intersection relationships. The preset second processing method includes a method of removing small and retaining large areas or an area-graded intersection area subtraction processing method. For the inclusion relationship conflict of single-band cells, the elimination of redundant coverage within a single band is achieved through a merging strategy of removing small and retaining large areas. This is a core step in the optimization of single-band coverage zoning, where the inclusion relationship is that the coverage area of ​​a certain cell is completely included in the coverage area of ​​another cell.

[0085] Alternatively, as Figure 7 As shown, Figure 7 This is a schematic diagram of the same-frequency band inclusion relationship involved in this application. For the first area pair (A, B) within a single frequency band, where A represents area A and B represents area B, SA>SB, where SA is the area of ​​A and SB is the area of ​​B, a convex polygon inclusion test is performed, such as calling the contains method of the GIS library, to verify whether all vertices of B are within the convex polygon of A and that the boundaries do not exceed; We can get B=C, where C is the intersection area, C is

[0086] Among them, A and B are the coverage areas of two cells in a single frequency band, and C is the spatial intersection area of ​​A and B. is the geographic coordinate point, where is the longitude, is latitude, and ∩ is the set intersection operation. The spatial intersection of A and B is extracted to define the scope of the conflicting area. When B is contained by A, the intersection C is equivalent to B. Because area A is larger, the larger area A is retained, and the contained area B is removed. In other words, if B is within area A, the terminal in area B can be covered by area A. Retaining area A avoids frequent handoffs between A and B within the same frequency band. For example, if the terminal is connected to both A and B within area B, this would result in wasted handoffs and reduces unnecessary handoffs.

[0087] Optionally, when it is detected that the intersection is in an intersecting relationship, the first region pairs corresponding to the intersecting relationship are processed by subtracting the intersecting regions according to area classification to obtain a second temporary region set; Alternatively, as Figure 8 As shown, Figure 8 This is a schematic diagram of the intersection relationship of the same frequency band involved in this application. The intersection relationship is that within the same frequency band, areas A and B have spatial intersection, but do not contain each other, then the smaller coverage area B remains unchanged; the larger coverage area A is subtracted from the intersection area C; if A is split into multiple sub-areas after deduction, the sub-areas need to be added to the set to be processed; otherwise, the boundary and area of ​​A are updated to achieve precise optimization of the intersection area within a single frequency band.

[0088] Optionally, the larger coverage area A minus the intersection area C is used to obtain a new area A′, which is expressed as: For example, call a GIS geometry library (such as Shapely) to verify that the convex polygons of A and B intersects (intersect) is true (there is an intersection), and contains is false (they do not contain each other); the area of ​​the intersection area C SC>0, excluding invalid intersections such as boundary tangency; calculate the area of ​​the convex polygons of A and B, where SA>SB, mark the larger area as A and the smaller area as B, and use the geometry library to find the intersection polygon C of A and B (the vertex sequence is Cpoints (points)); if A is not split after deducting C (still a single connected area), then update the boundary of A to A′points=Apoints\Cpoints (remove the intersection part) and recalculate the area SA′.

[0089] Optionally, the first temporary area set and the second temporary area set are used as new single-band cell sets, and the following steps are repeatedly performed: detecting whether there is a new intersection in the new single-band cell set; if so, performing small-removal and large-retention processing on the area pairs corresponding to the new inclusion relationship or performing area-graded intersection area deduction processing on the area pairs corresponding to the new intersection relationship to obtain a temporary area set corresponding to the intersection; until it is detected that all areas in the new single-band cell set have no intersection; merging the final temporary area sets to obtain the first area set.

[0090] Optionally, coverage areas within a single frequency band are processed dynamically. Initial processing removes smaller areas from coverage relationships and retains larger areas, and deducts the intersection of intersections from the coverage areas. This can change the area's shape, for example, by splitting a large area into sub-areas, creating new spatial intersections, such as overlap between sub-areas and other areas. If processing is performed only once, secondary conflicts may remain, making it impossible to ensure that coverage areas within the same frequency band do not overlap.

[0091] Optionally, input a first temporary area set and a second temporary area set, wherein the first temporary area set is the result after processing the inclusion relationship: the included small areas are removed, and the merged large areas are retained; the second temporary area set is the result after processing the intersection relationship: the large area is subtracted from the intersection, and the sub-areas are added to be processed, and the two sets are merged to form a new single-band cell set as the object of the next round of conflict detection.

[0092] Optionally, all pairs of regions within the new spatial intersection are detected, wherein all pairs of regions within the new spatial intersection include sub-regions newly added after the initial processing and original non-conflicting regions; new inclusion relationships are detected, such as a sub-region being included in another region; new intersection relationships, such as a sub-region overlapping with other regions.

[0093] Optionally, reuse the aforementioned geometry detection logic to traverse all region pairs and mark conflicting pairs. If the relationship is a containment one, the "remove small and retain large" approach is still applied: that is, the contained small regions are removed, while the large regions are retained. If the relationship is an intersection one, the "leveled area reduction" approach is still applied: the large regions are subtracted from the intersection, the small regions are retained, and the split sub-regions are added for processing. The conflicting small regions or the original large regions are removed, and the new regions or sub-regions after the subtraction are added. An updated temporary region set is generated as input for the next iteration until there are no new conflicts.

[0094] Optionally, the final temporary area set is all the valid coverage areas remaining after iterative conflict processing. These areas have passed the global iterative verification and meet the requirement that there is no intersection between any two areas in a single frequency band. The temporary area sets generated in all iterative rounds are integrated to ensure that all valid coverage areas in a single frequency band are included, ensuring the logical closed loop of layered optimization of the entire solution from single frequency band to multi-frequency band.

[0095] In this embodiment, for each frequency band, for the first target single-frequency-band cell in the first single-frequency-band cell set, the portion of the first target single-frequency-band cell that does not intersect with other first single-frequency-band cells in the first single-frequency-band cell set is divided into a second single-frequency-band cell. For any first single-frequency-band cell that intersects with other first single-frequency-band cells in the first single-frequency-band cell set, the intersecting portion is divided into a second single-frequency-band cell, thereby obtaining a first area set including each second single-frequency-band cell. After integration and optimization, a conflict-free coverage area is obtained, providing standardized input for multi-frequency-band conflict processing.

[0096] Based on any of the above embodiments of the present application, in the ninth embodiment of the present application, the same or similar contents as those in the first embodiment can be referred to above and will not be described in detail. On this basis, step S30 includes: Step B301: For each second target single-band cell in each first area set, a portion of the second target single-band cell that does not intersect with other second single-band cells is divided into a third single-band cell, where the second target single-band cell does not intersect with any other second single-band cell, or intersects with at least one other second single-band cell. Step B302: For any second single-band cell that intersects with other second single-band cells, divide the intersecting part into multi-band cells to obtain a second area set including third single-band cells and / or multi-band cells.

[0097] Optionally, if the second target single-band cell has no intersection with all other second single-band cells of different frequency bands, the complete area of ​​the second target single-band cell is the non-intersection part, and the complete area is directly divided into the third single-band cell without additional processing, ensuring that the optimized effective coverage within the single band is not lost and retaining the conflict-free basic coverage area.

[0098] Optionally, if the second target single-band cell only intersects with some other second single-band cells of different frequency bands, it is necessary to extract the second target single-band cell through geometric calculation, and the area that does not overlap with any other cells of different frequency bands, and divide this area into the third single-band cell to avoid erroneous deletion of non-conflicting coverage due to subsequent intersection processing.

[0099] Optionally, the second single-band cells that intersect with other second single-band cells originate from the first area set, so the other second single-band cells belong to different frequency bands, that is, the intersection is a cross-band intersection, which requires targeted processing to avoid cross-band interference.

[0100] Optionally, if the cross-band intersection is an inclusion relationship (e.g., cell A of frequency band X completely includes cell B of frequency band Y, and A has a larger area): the intersection part is the included cell B, and the included cell B is divided into multi-band cells (associated with the X and Y dual bands and the corresponding cell IDs); at the same time, a difference operation is performed on the included cell A (subtracting the intersection part B), and the remaining area is obtained as the third single-band cell (retaining the X band attribute), and the original included cell B is removed to eliminate cross-band redundant coverage, and the frequency band association relationship of the intersection is recorded through the multi-band cell; if the cross-band intersection is an intersection Relationship (for example, cell C of frequency band M and cell D of frequency band N partially overlap and do not include each other): directly extract the intersection area C∩D of the two, and divide the intersection area C∩D into multi-band cells (associated with the M and N dual bands and the corresponding cell IDs); the area obtained after deducting the intersection of the larger cell C (if it is split into sub-areas, all of them are included) is used as the third single-band cell (retaining the M band attributes), and the smaller cell D is completely retained as the third single-band cell (retaining the N band attributes). This not only eliminates the intersection conflict, but also retains the effective coverage of each single band and the multi-band synergy potential of the intersection area.

[0101] Optionally, there is a second intersection of the second area pair, wherein the second intersection includes a relationship or an intersection relationship, and the second area pair is any two second single-band cells of different frequency bands; Optionally, the second area pair refers to selecting two areas belonging to different frequency bands from the first area set (coverage areas without conflict in a single frequency band), and is recorded as 、 ,satisfy The frequency band and The second intersection includes two relationships: one is the inclusion relationship, that is, The convex polygon completely contains (or vice versa), that is, Convex polygons are verified by calling the contains method The convex polygon result is true; the second is the intersection relationship, that is, and The convex polygons of partially overlap (do not contain each other), that is, The convex polygon is verified by calling the intersects method The convex polygon result of is true and has no containment relationship.

[0102] Optionally, first traverse all regional combinations of different frequency bands in the first region set (such as X band and Y band, X band and Z band, etc.) to generate a second region pair list, such as ; Then perform geometric relationship verification, including calling the contains method of the Shapely library to verify the relationship Is it fully included? (or vice versa); the intersection relationship detection calls the intersects method. If the two regions intersect and there is no containment relationship, it is determined to be an intersection relationship; if A of the X frequency band and B of the Y frequency band have an intersection relationship, their intersection area C is defined as

[0103] like Figure 9 As shown, Figure 9 This is a schematic diagram of the cross-band intersection relationship involved in this application. The intersection C is a multi-band XY cell, where A and B are the coverage areas of two different frequency band cells in a single frequency band, area A is the X band, area B is the Y band, and area C is the XY band. C is the spatial intersection area of ​​A and B, and the dotted arrows correspond to the divided areas; wherein ∩ is a set intersection operation, that is, the second area pair (A, B) of the detected intersection relationship, and its intersection C will subsequently be processed as a multi-band XY cell.

[0104] Optionally, when it is detected that the second intersection is in an inclusion relationship, the second area pair in the inclusion relationship is processed by removing small areas and retaining large areas to obtain a third temporary area set, wherein the third temporary area set includes a third single-frequency-band cell; Optionally, the third single-band cell is a single-band cell that retains a large area. Suppose the second area pair is (R_main, R_sub), where R_main (main) completely contains R_sub (sub) (for example, B of the Y band contains A of the X band), and the area satisfies that the area of ​​R_main is greater than the area of ​​R_sub, and the area is calculated based on the aforementioned convex polygon area formula.

[0105] Optionally, first retain the large area, remove the small area, remove R_sub from the first area set, and retain R_main, where R_main is the third single-band cell. This is because the large area has better coverage and avoids redundancy in the same-frequency switching. Perform a difference set operation to correct the large area, because R_sub is completely included, and the intersection C=R_main∩R_sub=R_sub.

[0106] Therefore, the new boundary of R_main is R_main'=R_main-C=R_main-R_sub. This step is achieved through Shapely's difference method to resolve cross-band inclusion conflicts.

[0107] Optionally, when it is detected that the second intersection is in an intersection relationship, the second area pairs corresponding to the intersection relationship are processed according to an area-graded intersection area deduction processing method to obtain a fourth temporary area set, wherein the fourth temporary area set includes the third single-band cell and the multi-band cell; Optionally, let the second region pair be (R_main, R_sub), satisfying that R_main and R_sub intersect (do not contain each other), and the area of ​​R_main is greater than or equal to the area of ​​R_sub (R_main is the main region, R_sub is the sub-region).

[0108] Optionally, first calculate the intersection area C, C = R_main ∩ R_sub. This step is extracted using Shapely's intersection method. If C is empty, skip it to ensure a valid intersection. Then, subtract the intersection from the main area to obtain R_main' = R_main-C, which is used as the third single-band cell. If R_main' is a single connected area (such as a Polygon), directly update the boundary of R_main to R_main' and retain the original frequency band (such as the X band). If R_main' is split into multiple sub-areas (such as a MultiPolygon), split into R_main,1, R_main,2, etc., as the third single-band cell, all belong to the original frequency band and are added to the fourth temporary set. Then the sub-area is retained, R_sub (such as the Y band) remains unchanged, and is directly added to the fourth temporary set; finally, a mixed area is generated, the intersection C is extracted, and it is marked as a multi-band mixed area. The associated frequency bands record the dual frequency bands (such as the frequency band of R_main + the frequency band of R_sub, that is, X+Y), and the associated cells record the corresponding cell IDs (such as the cell ID of R_main + the cell ID of R_sub), and the mixed area is added to the fourth temporary set as a multi-band cell.

[0109] Optionally, the third temporary area set and the fourth temporary area set are used as a new set including a third single-band cell and / or multi-band cell, and the following steps are repeatedly performed: detect whether there is a new intersection in the new set including the third single-band cell and / or multi-band cell; if so, perform small-removal and large-retention processing on the area pairs corresponding to the new inclusion relationship or perform area-graded intersection area deduction processing on the area pairs corresponding to the new intersection relationship to obtain temporary area sets corresponding to the intersection; until it is detected that all areas in the new set including the third single-band cell and / or multi-band cell have no intersection; merge the final temporary area sets to obtain a second area set.

[0110] Optionally, the main area is split into sub-areas after deducting the intersection. As the third single-band cell, the sub-area generates a new intersection with other cross-band areas. Therefore, cyclic detection processing is required to ensure that all cross-band conflicts are completely resolved.

[0111] Optionally, merge the temporary sets, merge the third temporary set (the result of processing the inclusion relationship) and the fourth temporary set (the result of processing the intersection relationship) to form a new set to be processed (including corrected single-band regions, mixed regions, and split sub-regions); detect new conflicts, traverse all cross-band regions pairs in the new set, repeat geometric verification, and identify new inclusion or intersection relationships; repeat the processing. If it is an inclusion relationship, reuse the logic of keeping the larger and removing the smaller to correct the regions and update the temporary set; if it is an intersection relationship, reuse the logic of subtracting the intersection and generating the mixed region to correct the regions and update the temporary set; the termination condition of the iteration is when there is no intersection between all cross-band regions pairs in the new set, the iteration ends. Therefore, after the iterative processing, there must be no intersection between cross-band regions, avoiding the loss of coverage ability caused by simple "eliminating overlap" and ensuring the convergence of the algorithm. Optionally, after the iteration ends, the final temporary region set contains two types of regions: one is the third single-band cell, such as A' in the X band and B in the Y band (the cross-band overlap has been stripped and there is no conflict within the single band); the other is the multi-band cell, such as C in X+Y (associated with dual bands and corresponding cells for multi-band collaborative optimization). Thus, through iterative processing, it is ensured that there is no intersection between cross-band regions pairwise.

[0112] Optionally, encapsulate according to a preset data structure (such as List<MultiBandRegion>). Each region contains polygon (a set of longitude and latitude boundary points, a Shapely geometric object, such as Polygon or MultiPolygon), bands (a list of associated frequency bands, such as ["X"] representing a single band, ["X","Y"] representing a mixed region), and cell_ids (a list of associated cell IDs, such as ["CI_1001"] or ["CI_1001","CI_2001"]).

[0113] In this embodiment, for the second target single-band cells in each first region set, the part of the second target single-band cells that has no intersection with other second single-band cells is divided into third single-band cells; for any second single-band cell that has an intersection with other second single-band cells, the intersection part is divided into multi-band cells, obtaining a second region set containing third single-band cells and / or multi-band cells, generating a structured optimization result, and solving the problem of the disconnection between traditional zoning and frequency bands and cell attributes.

[0114] In addition, the present application also provides a base station coverage zoning calculation device in wireless network optimization. Please refer to Figure 10 , Figure 10 which is a schematic structural diagram of the base station coverage zoning calculation device in wireless network optimization involved in the solution of the embodiment of the present application. The device in the embodiment of the present application can specifically be a device that runs the base station coverage zoning calculation method in wireless network optimization locally.

[0115] The present application provides a base station coverage partition calculation device for wireless network optimization, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the base station coverage partition calculation device method for wireless network optimization in the above-mentioned embodiment.

[0116] Reference below Figure 10 , which shows a schematic diagram of the structure of a base station coverage zone calculation device suitable for implementing the wireless network optimization in the embodiments of the present application. The base station coverage zone calculation device in the wireless network optimization in the embodiments of the present application may include, but is not limited to, mobile terminals such as mobile phones, laptops, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), in-vehicle terminals (such as in-vehicle navigation terminals), and fixed terminals such as digital TVs and desktop computers. Figure 10 The base station coverage partition calculation device in the wireless network optimization shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0117] like Figure 10As shown, the base station coverage zone calculation device for wireless network optimization may include a processing device 1001 (e.g., a central processing unit, graphics processing unit, etc.), which can perform various appropriate actions and processes based on programs stored in a read-only memory (ROM) 1002 or programs loaded from a storage device 1003 into a random access memory (RAM) 1004. RAM 1004 also stores various programs and data required for the operation of the base station coverage zone calculation device for wireless network optimization. Processing device 1001, ROM 1002, and RAM 1004 are interconnected via a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Typically, the following devices may be connected to I / O interface 1006: input device 1007 including, for example, a touchscreen, touchpad, keyboard, mouse, image sensor, microphone, accelerometer, gyroscope, etc.; output device 1008 including, for example, a liquid crystal display (LCD), speaker, vibrator, etc.; storage device 1003 including, for example, a magnetic tape, hard disk, etc.; and communication device 1009. Communication device 1009 may allow the base station coverage zoning calculation device for wireless network optimization to communicate wirelessly or wired with other devices to exchange data. Although the figure shows a base station coverage zoning calculation device for wireless network optimization with various devices, it should be understood that implementation or presence of all illustrated devices is not required. More or fewer devices may alternatively be implemented or present.

[0118] In particular, according to the embodiments disclosed in the present application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, the embodiments disclosed in the present application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program comprising program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network via a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0119] The base station coverage zone calculation device for wireless network optimization provided in this application utilizes the base station coverage zone calculation method for wireless network optimization described in the aforementioned embodiment, thereby resolving the technical issue of low efficiency in base station coverage zone calculation devices for wireless network optimization. Compared to the prior art, the base station coverage zone calculation device for wireless network optimization provided in this application achieves the same beneficial effects as the base station coverage zone calculation method for wireless network optimization described in the aforementioned embodiment. Other technical features of the base station coverage zone calculation device for wireless network optimization are the same as those disclosed in the aforementioned embodiment and are not further elaborated upon here.

[0120] In addition, the present application provides a computer-readable storage medium. The computer-readable storage medium stores a base station coverage partition calculation program in wireless network optimization, which, when executed by a processor, implements the steps of the base station coverage partition calculation method in wireless network optimization.

[0121] It should be noted that, in this document, the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or system comprising a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or system. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or system comprising the element.

[0122] The serial numbers of the above embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.

[0123] Through the description of the above embodiments, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus the necessary general hardware platform. Of course, they can also be implemented by hardware, but in many cases the former is a better embodiment. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product. The computer software product is stored in a computer-readable storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes a number of instructions for enabling a device (which can be a mobile phone, computer, server, or network device, etc.) to execute the methods described in each embodiment of the present application.

[0124] The above are only preferred embodiments of the present application and do not limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present application.

Claims

1. A method for calculating base station coverage zones in wireless network optimization, characterized in that: The method comprises: Acquire at least two first single-frequency-band cells corresponding to at least two frequency bands in the area to be optimized; For each frequency band, if the first single-frequency-band cells corresponding to the frequency band meet a preset first conflict condition, calling a preset first processing method to integrate the first single-frequency-band cells into a first area set, where the first area set includes mutually non-overlapping second single-frequency-band cells; If the first area sets corresponding to each frequency band meet the preset second conflict condition, the preset second processing method is called to integrate the first area sets into a second area set, wherein the second area set includes non-overlapping third single-band cells and / or multi-band cells, wherein the third single-band cell is a cell that belongs only to a single frequency band, and the multi-band cell is a cell that belongs to at least two frequency bands at the same time.

2. The method for calculating base station coverage zones in wireless network optimization according to claim 1, wherein: Before the step of obtaining at least two first single-frequency-band cells corresponding to at least two frequency bands in the area to be optimized, the method further includes: Performing geographic rasterization processing on the area to be optimized by using a preset raster precision and a preset raster algorithm to generate a raster list table for the area to be optimized; Acquire cell measurement data matched by the grid list table, and convert the cell measurement data into rasterized data using the preset grid algorithm; The rasterized data is grouped and converted according to different frequency bands to obtain a grid center point set of the first single-frequency-band cell, and the first single-frequency-band cell is generated according to the grid center point set.

3. The method for calculating base station coverage zones in wireless network optimization according to claim 2, wherein: The step of obtaining the cell measurement data matched with the grid list table and converting the cell measurement data into rasterized data using the preset grid algorithm includes: For the longitude and latitude interval between the start grid and the end grid in the grid list table, obtaining cell measurement data of each sampling point in the longitude and latitude interval, wherein the cell measurement data includes the longitude and latitude coordinates of each sampling point; Calling the preset grid algorithm to convert the latitude and longitude coordinates of each sampling point to obtain the converted latitude and longitude of the lower left corner of the grid to which it belongs; The converted longitude and latitude of the lower left corner of the grid to which it belongs are associated and matched with the grid identifier of the grid in the grid list table to form the rasterized data.

4. The method for calculating base station coverage zones in wireless network optimization according to claim 3, wherein: The rasterized data includes frequency band information and cell identifiers, and the step of grouping and converting the rasterized data according to different frequency bands to obtain a set of grid center points of the first single-band cell includes: Grouping the rasterized data according to a combination of the frequency band information and the cell identifier to obtain a corresponding joint group, wherein the joint group includes all rasterized data corresponding to the same frequency band and the same cell; Extracting the latitude and longitude of the upper left corner and the latitude and longitude of the lower right corner corresponding to each grid in each of the combined groups, and calculating the coordinates of the center point of each grid in the combined group; Aggregate the center point coordinates of all grids in the same joint group to form a grid center point set of the first single-band cell.

5. The method for calculating base station coverage zones in wireless network optimization according to claim 4, wherein: The step of generating the first single-band cell according to the grid center point set includes: Selecting the point with the smallest longitude and the smallest latitude in the grid center point set as the starting point, and calculating the polar angle between the starting point and other center points in the grid center point set; Sorting the polar angles in ascending order to obtain ascending grid center points; Determine the positional relationship corresponding to the center points of the ascending grid, and filter out the convex polygon boundary point set that meets the preset stacking conditions in the positional relationship; Adjacent points in the convex polygon boundary point set are sequentially connected and the first and last points are closed to obtain a convex polygon as the first single-band cell.

6. The method for calculating base station coverage zones in wireless network optimization according to claim 5, wherein: Before the step of calling the preset first processing method to integrate the first single-band cells into a first area set, the method further includes: Grouping the first single-frequency-band cells according to the frequency band dimension to obtain a first single-frequency-band cell set corresponding to each frequency band; For each frequency band, detecting whether a first area pair in the corresponding first single-frequency-band cell set has an intersection, wherein the first area pair is any two first single-frequency-band cells in the first single-frequency-band cell set; If at least one of the first area pairs has an intersection, determining that each of the first single-band cells in the first single-band cell set meets the first conflict condition; If there is no intersection between the first area pairs, it is determined that the first single-band cells in the first single-band cell set do not meet the first conflict condition.

7. The method for calculating base station coverage zones in wireless network optimization according to claim 6, wherein: The step of calling the preset first processing method to integrate the first single-frequency-band cells into a first area set includes: For each frequency band, for a first target single-frequency band cell in the first single-frequency band cell set, dividing a portion of the first target single-frequency band cell that does not intersect with other first single-frequency band cells in the first single-frequency band cell set as a second single-frequency band cell, wherein the first target single-frequency band cell has no intersection with any other first single-frequency band cells in the first single-frequency band cell set, or has an intersection with at least one other first single-frequency band cell in the first single-frequency band cell set; For any first single-band cell that has an intersection with other first single-band cells in the first single-band cell set, the intersection is divided into second single-band cells to obtain the first area set including each second single-band cell.

8. The method for calculating base station coverage zones in wireless network optimization according to claim 7, wherein: The second conflict condition is that at least two of the second single-frequency-band cells in each of the first area sets intersect, and the step of calling the preset second processing method to integrate the first area sets into the second area set includes: For each second target single-frequency band cell in the first area set, dividing a portion of the second target single-frequency band cell that does not intersect with other second single-frequency band cells as the third single-frequency band cell, wherein the second target single-frequency band cell does not intersect with any other second single-frequency band cells, or intersects with at least one other second single-frequency band cell; For any second single-band cell that has an intersection with other second single-band cells, the intersection is divided into the multi-band cells to obtain the second area set including the third single-band cell and / or the multi-band cell.

9. A base station coverage partition calculation device in wireless network optimization, characterized in that: The base station coverage partition calculation device in wireless network optimization includes a memory, a processor, and a base station coverage partition calculation program in wireless network optimization stored on the memory and executable on the processor. When the processor executes the base station coverage partition calculation program in wireless network optimization, the steps of the base station coverage partition calculation method in wireless network optimization as described in any one of claims 1 to 8 are implemented.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a base station coverage partition calculation program in wireless network optimization, and when the base station coverage partition calculation program in wireless network optimization is executed by a processor, the steps of the base station coverage partition calculation method in wireless network optimization according to any one of claims 1 to 8 are implemented.

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