Optimization method and device for overlapping coverage problem, electronic equipment and storage medium

Abstract

The invention provides an optimization method and device for an overlapping coverage problem, electronic equipment and a computer readable storage medium, and relates to the technical field of communication network optimization. The optimization method comprises the following steps: rasterizing measurement report statistics MRO data of all terminals in a preset area to obtain a plurality of pieces of MRO data covering grids; determining an overlapping coverage area based on the MRO data of the plurality of coverage grids and a clustering algorithm; determining a high-interference cell of the overlapping coverage area based on the MRO data of all terminals in the overlapping coverage area; and the high-interference cells in the overlapping coverage area are optimized, so that the overlapping coverage problem is optimized. The problems of incomplete positioning and optimization, low accuracy and low efficiency of the overlapping coverage problem in the prior art are at least solved. The method is suitable for coverage problem positioning and scene optimization.

Description

Technical Field

[0001] The present invention relates to the technical field of communication network optimization, and in particular to an optimization method, device, electronic device and computer-readable storage medium for overlapping coverage problems. Background Art

[0002] The optimization of mobile wireless network topology structure includes two processes: positioning of mobile wireless network topology structure problems and problem optimization. Mobile wireless network topology structure problems include weak coverage problem, over-coverage problem and overlapping coverage problem.

[0003] In order to solve the overlapping coverage problem, the existing technology of locating the topology structure problem of mobile wireless network is often based on the engineering parameters of base stations and the number of sector switching, and a number of network structure feature data are calculated to match the abnormal identification model to find the network problem. The optimization of the topology structure problem of mobile wireless network in the existing technology focuses on solving the weak coverage area in the network to meet the requirements of continuous coverage.

[0004] Therefore, the optimization of the mobile wireless network topology structure for overlapping coverage problems in the prior art has the following problems: (1) only the number of switching is considered, and the number of switching is strictly related to the integrity and accuracy of the definition of the neighboring area of ​​the wireless network base station, and the positioning of the mobile wireless network topology structure problem is not comprehensive; (2) the accuracy of the anomaly recognition model cannot be guaranteed, and the positioning accuracy of the mobile wireless network topology structure problem is not high; (3) The optimization of the mobile wireless network topology structure problem is mainly based on the continuous coverage requirement, and the network interference problem of the mobile communication principle is not considered, which will result in a situation where there is coverage but the service cannot be used; (4) The generated reorganization plan that meets the continuous coverage requirement only considers the network coverage of the base station downlink, and the network coverage of the mobile terminal uplink cannot be guaranteed.

[0005] In summary, the existing technologies for problem location and optimization of overlapping coverage problems have the problems of incomplete problem location and optimization, low accuracy and low efficiency. Summary of the invention

[0006] The technical problem to be solved by the present invention is to provide a method, device, electronic device and computer-readable storage medium for optimizing the overlapping coverage problem in view of the above-mentioned shortcomings of the prior art. The method can comprehensively and accurately locate the overlapping coverage problem, improve the reliability of the optimization direction of the overlapping coverage problem, reduce the time and labor costs caused by invalid positioning, and improve the accuracy and efficiency of optimizing the overlapping coverage problem.

[0007] In a first aspect, the present invention provides a method for optimizing the overlapping coverage problem, comprising: rasterizing the measurement report statistics MRO data of all terminals in a preset area to obtain MRO data of several coverage grids; determining the overlapping coverage area based on the MRO data of the several coverage grids and a clustering algorithm; determining the high-interference cells in the overlapping coverage area based on the MRO data of all terminals in the overlapping coverage area; and optimizing the high-interference cells in the overlapping coverage area to optimize the overlapping coverage problem.

[0008] Preferably, the measurement report statistics MRO data of all terminals in the preset area are rasterized to obtain MRO data of several covering grids, specifically including: filling in the longitude and latitude of the MRO data of all terminals in the preset area based on the fingerprint library algorithm; rasterizing the preset area to obtain several covering grids; based on the longitude and latitude, mapping the MRO data of all terminals in the preset area with several covering grids to obtain MRO data of several covering grids.

[0009] Preferably, the determining of the overlapping coverage area based on the MRO data of several covering grids and the clustering algorithm specifically includes: calculating the overlapping coverage ratio of several covering grids based on the MRO data of several covering grids; determining the overlapping coverage grid based on the overlapping coverage ratio, wherein the overlapping coverage grid is used to characterize the covering grid whose number of MRO data is greater than a first threshold and whose overlapping coverage ratio is greater than a second threshold; clustering the overlapping coverage grids based on the clustering algorithm to obtain the overlapping coverage area.

[0010] Preferably, the method of determining high-interference cells in the overlapping coverage area based on the MRO data of all terminals in the overlapping coverage area specifically includes: determining each service cell connected to all terminals in the overlapping coverage area based on the MRO data of all terminals in the overlapping coverage area; calculating the interference matrix of each service cell, wherein the interference matrix is ​​used to characterize the set of uplink interference amounts of all terminals connected to the current service cell to other service cells; and determining high-interference cells in the overlapping coverage area based on the interference matrix of each service cell.

[0011] Preferably, the MRO data includes power headroom report PHR information, reference signal received power RSRP of the connected service cell, and power configuration, and the calculation of the interference matrix of each service cell specifically includes: calculating the interference matrix of each service cell according to formula (1):

[0012] N a =(23-PHR)-(R s Power-RSRP) (1), Among them, N a represents the ath element of the interference matrix, N aIt is used to characterize the uplink interference of the ath terminal connected to the current serving cell to other serving cells, R s Power represents the power configuration of the ath terminal connected to the current serving cell, RSRP represents the RSRP of the current serving cell, and PHR represents the PHR information of the ath terminal connected to the current serving cell.

[0013] Preferably, after determining the high-interference cells in the overlapping coverage area based on the MRO data of all terminals in the overlapping coverage area, and before optimizing the high-interference cells in the overlapping coverage area to optimize the overlapping coverage problem, the optimization method for the overlapping coverage problem also includes: visually presenting each service cell and at least one of the following: an overlapping coverage grid, an overlapping coverage area.

[0014] Preferably, the optimization of high-interference cells in the overlapping coverage area to optimize the overlapping coverage problem specifically includes: determining the optimal electronic downtilt of the high-interference cells based on the antenna feed tilt optimization model; optimizing the high-interference cells in the overlapping coverage area based on the optimal electronic downtilt of the high-interference cells to optimize the overlapping coverage problem.

[0015] Preferably, the antenna feed tilt optimization model includes:

[0016] Average propagation coverage fitting model tan(m+e-θ / 2)=H / D,

[0017] Rolling optimization and correction strategy

[0018] Where m represents mechanical downtilt, e represents electronic downtilt, θ represents vertical beam width, H represents antenna height, D represents coverage distance, and ε represents the vertical beam width. j represents the correction factor of the jth optimization, e j represents the j-th optimized electronic downdip, e represents the upper and lower boundaries of the electron downdip fluctuation, ε t It represents the correction factor of the current optimization action t, and t-1 represents the previous optimization action.

[0019] In a second aspect, the present invention also provides an optimization device for the overlapping coverage problem, including a rasterization module, a first determination module, a second determination module and an optimization module. The rasterization module is used to rasterize the measurement report statistics MRO data of all terminals in a preset area to obtain MRO data of several covering grids. The first determination module is connected to the rasterization module and is used to determine the overlapping coverage area based on the MRO data of several covering grids and a clustering algorithm. The second determination module is connected to the first determination module and is used to determine the high interference cell in the overlapping coverage area based on the MRO data of all terminals in the overlapping coverage area. The optimization module is connected to the second determination module and is used to optimize the high interference cell in the overlapping coverage area to optimize the overlapping coverage problem.

[0020] In a third aspect, the present invention further provides an electronic device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor is configured to run the computer program to implement the optimization method for the overlapping coverage problem provided in the first aspect.

[0021] In a fourth aspect, the present invention further provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the optimization method for the overlapping coverage problem provided in the first aspect above is implemented.

[0022] The present invention provides an optimization method, device, electronic device and computer-readable storage medium for overlapping coverage problems. By using the MRO data of all terminals in the overlapping coverage area, it can more accurately and in real time identify all service cells involved in the overlapping coverage area, and then accurately determine the high-interference cells in the overlapping coverage area according to all service cells involved in the coverage area. Compared with the prior art that is limited to determining the high-interference cells in the overlapping coverage area among all service cells in the coverage planning of the overlapping coverage area, it can take into account interference factors in a larger range, and reduce the dependence on theoretical models or static configurations, so as to achieve real-time and accurate determination of high-interference cells; after accurately determining the high-interference cells, it can be optimized in a targeted manner, clarify the optimization direction, and improve the accuracy and efficiency of optimizing the overlapping coverage problem. Therefore, the present invention can realize comprehensive and accurate positioning of overlapping coverage problems, improve the reliability of the optimization direction of overlapping coverage problems, reduce the time and labor costs caused by invalid positioning, and improve the accuracy and efficiency of optimizing the overlapping coverage problem. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 This is a flow chart of an optimization method for overlapping coverage problem according to Embodiment 1 of the present invention;

[0024] Figure 2 This is an example diagram of mapping the MRO data of all terminals in a preset area with a plurality of coverage grids in Embodiment 1 of the present invention;

[0025] Figure 3 This is an example diagram of determining the serving cells connected to all terminals in the overlapping coverage area in Embodiment 1 of the present invention;

[0026] Figure 4 This is an example diagram of calculating the interference matrix of each serving cell in Embodiment 1 of the present invention;

[0027] Figure 5 This is an example diagram of determining the optimal electronic downtilt of a high-interference cell in Embodiment 1 of the present invention;

[0028] Figure 6 This is an example diagram of visually presenting overlapping coverage grids in Embodiment 1 of the present invention;

[0029] Figure 7 This is an example diagram of visually presenting overlapping coverage areas in Embodiment 1 of the present invention;

[0030] Figure 8 This is a flow chart of an optimization method for overlapping coverage problem according to Embodiment 2 of the present invention;

[0031] Fig. 9 It is a structural schematic diagram of an optimization device for overlapping coverage problem according to embodiment 3 of the present invention. DETAILED DESCRIPTION

[0032] In order to enable those skilled in the art to better understand the technical solution of the present invention, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings.

[0033] It should be understood that the specific embodiments and drawings described herein are only used to explain the present invention rather than to limit the present invention.

[0034] It can be understood that, in the absence of conflict, the various embodiments of the present invention and the various features in the embodiments can be combined with each other.

[0035] It can be understood that, for the convenience of description, the drawings of the present invention only show the parts related to the present invention, while the parts irrelevant to the present invention are not shown in the drawings.

[0036] It can be understood that each unit and module involved in the embodiments of the present invention may correspond to only one physical structure, or may be composed of multiple physical structures, or multiple units and modules may be integrated into one physical structure.

[0037] It can be understood that, without conflict, the functions and steps marked in the flowcharts and block diagrams of the present invention may occur in an order different from that marked in the drawings.

[0038] It is understood that the flowcharts and block diagrams of the present invention illustrate the possible architectures, functions, and operations of the systems, devices, equipment, and methods according to the various embodiments of the present invention. Each box in the flowchart or block diagram may represent a unit, module, program segment, or code, which contains executable instructions for implementing the specified functions. Moreover, each box or combination of boxes in the block diagram and flowchart may be implemented by a hardware-based system that implements the specified functions, or may be implemented by a combination of hardware and computer instructions.

[0039] It can be understood that the units and modules involved in the embodiments of the present invention can be implemented by software or hardware. For example, the units and modules can be located in a processor.

[0040] Embodiment 1:

[0041] like Figure 1 As shown, this embodiment provides an optimization method for the overlapping coverage problem. The optimization method for the overlapping coverage problem includes:

[0042] S101, rasterizing the measurement report statistics MRO data of all terminals in a preset area to obtain MRO data covering a plurality of grids.

[0043] Specifically, the MRO data includes power headroom report PHR information, reference signal received power RSRP of the connected service cell, and power configuration.

[0044] Specifically, S101: rasterizing the measurement report statistics MRO data of all terminals in a preset area to obtain MRO data covering a plurality of grids, including steps S1011 to S1013:

[0045] S1011, based on the fingerprint library algorithm, fill in the longitude and latitude of the MRO data of all terminals in the preset area.

[0046] In this embodiment, the preset area includes but is not limited to provinces, cities, and administrative regions. Taking the preset area as a province as an example, based on the fingerprint library algorithm, the longitude and latitude of the MRO (Measurement Report Object) data of all terminals in the preset area are filled in, specifically including: ① Collecting MR (Measurement Report) data and MDT (Minimization Drive Test) data throughout the province, and structuring the MR data and MDT data to obtain MRO data. ② Based on the MRO data and the fingerprint library algorithm, train the RF (Random Forest) model and verify the overall average positioning accuracy of the MRO data. ③ When the RF model is tuned to the first preset positioning accuracy, it can be used for real-time MRO data positioning, that is, based on the tuned RF model, fill in the longitude and latitude of the MRO data of all terminals in the preset area. Compared with the traditional MR positioning method, the fingerprint library algorithm performs better in complex environments (such as places with tall buildings in cities) and can complete MRO positioning faster and more effectively. Therefore, this embodiment uses the fingerprint library algorithm to fill in the longitude and latitude of the MRO data of all terminals in the preset area, thereby improving the accuracy of the longitude and latitude of the MRO data, and thereby improving the accuracy of subsequent MRO data mapping to the corresponding coverage grid.

[0047] It should be noted that this embodiment implements the training of the RF model through spark tasks. The RF model can be trained using MRO data of different precisions to improve the positioning accuracy of the RF model for the MRO data. The MRO data for training the RF model can be of the following two types: ① Distinguish between outdoor and indoor MRO data (distinguished according to the displacement and the building database of the moving party); ② Distinguish between high, medium and low MRO data of three different precision levels, and try to use high-precision MRO data to train the RF model. When the amount of data is insufficient, use medium-precision and low-precision MRO data to train the RF model. In addition, it is also preferred to use outdoor high-precision MRO data. After the RF model is tuned to the second preset positioning accuracy, consider adding indoor high-precision MRO data to mix and train the RF model.

[0048] High-precision MRO data usually refers to MRO data with an accuracy within a few meters, and is often used in communication business scenarios with high requirements for positioning accuracy. Medium-precision MRO data usually has an accuracy between 10 and 50 meters and is suitable for communication business scenarios with general positioning requirements. Low-precision MRO data usually has an accuracy of more than 100 meters and is suitable for communication business scenarios with relatively low positioning requirements.

[0049] S1012, rasterizing the preset area to obtain a plurality of coverage grids.

[0050] In this embodiment, a preset area is rasterized with a preset grid size to obtain a plurality of coverage grids, wherein the preset grid size includes but is not limited to: 50 meters * 50 meters. In addition, this embodiment also assigns a coding value to each coverage grid, and the coding value can be used to assign different colors to each coverage grid according to the coding value during subsequent visualization, so as to intuitively identify the coverage situation.

[0051] S1013, based on the longitude and latitude, mapping the MRO data of all terminals in the preset area with a plurality of coverage grids to obtain the MRO data of the plurality of coverage grids.

[0052] In this embodiment, due to the huge amount of MRO data, it is difficult for traditional databases to achieve fast query and fast mapping to corresponding coverage grids. Therefore, based on longitude and latitude, the MRO data of all terminals in the preset area are mapped to several coverage grids, such as Figure 2 As shown, it specifically includes: ① Designing a row key structure for MRO data in the distributed database postgresql, and numbering the MRO data. ② Define a coverage grid table in postgresql to record the code value and geographic location information of each coverage grid. ③ Traditional distributed databases do not directly support spatial indexes. This embodiment can use postgresql to map the MRO data and its corresponding coverage grid based on the longitude and latitude of the MRO data and the geographic location information of each coverage grid to generate an XZ2T index for the MRO data, which can efficiently manage the MRO data and ensure better query efficiency for subsequent MRO data. ④ Combine the XZ2T index, the number of the MRO data and the code value of the corresponding coverage grid as the storage key, and then store the storage key and the MRO data in a distributed cluster with multiple backups and security.

[0053] S102, determining overlapping coverage areas based on MRO data of a plurality of coverage grids and a clustering algorithm.

[0054] Specifically, S102: based on the MRO data of a plurality of coverage grids and a clustering algorithm, determining the overlapping coverage area includes steps S1021 to S1023:

[0055] S1021, calculating the overlapping coverage ratio of the plurality of coverage grids based on the MRO data of the plurality of coverage grids.

[0056] In this embodiment, based on the MRO data of each coverage grid, the number of MRO data points and the total number of MRO data points that meet the overlapping coverage conditions in each coverage grid are counted to obtain the overlapping coverage of each coverage grid. The overlapping coverage condition refers to the service cell level value ≥-105dbm and |3 or more neighboring cell levels-service cell level |≤6dbm. The proportion of the number of MRO data points that meet the overlapping coverage condition to the total number of MRO data points is calculated to obtain the overlapping coverage rate of each coverage grid, where the level value usually refers to the strength of the received signal, which can be RSRP (Reference Signal Receiving Power) or RSSI (Received Signal Strength Indicator).

[0057] It should be noted that the number of bytes carried by different modulation methods varies greatly. BPSK (Binary Phase Shift Keying) carries 1 byte, QPSK (Quadrature Phase Shift Keying) carries 2 bytes, 16QAM (Quadrature Amplitude Modulation) carries 4 bytes, 64QAM carries 6 bytes, and 256QAM carries 8 bytes. Under different modulation methods, the bandwidth requirements for transmitting the same size of data vary greatly. The higher the modulation method, the less bandwidth is required, and the higher the spectrum efficiency. Signal noise affects the accuracy of the receiver's decision. The higher the modulation order, the higher the requirement for the signal-to-noise ratio. Therefore, the level of the signal-to-noise ratio directly affects the modulation and demodulation efficiency and affects the spectrum efficiency.

[0058] In summary, overlapping coverage will cause co-channel interference on the wireless side and reduce the signal to interference plus noise ratio (SINR) of the mobile network. SINR is positively correlated with channel quality (Channel Quality Indication, CQI). CQI determines the mapping of the modulation method. Therefore, overlapping coverage has a great impact on the quality of the wireless network and the spectrum efficiency.

[0059] As shown in Table 1, from the analysis of the number of overlapping neighboring cells, it can be seen that as the number of strong interfering neighboring cells increases, the proportion of low-order modulation becomes higher and higher, indicating that the higher the overlapping coverage, the worse the signal-to-noise ratio, and the interference increases from small to large: there are 3 strong interfering neighboring cells < there are 4 strong interfering neighboring cells < there are 5 strong interfering neighboring cells...

[0060] Table 1 Analysis of the number of overlapping neighboring areas

[0061]

[0062]

[0063] S1022: Determine an overlapping coverage grid based on the overlapping coverage ratio, wherein the overlapping coverage grid is used to represent a coverage grid in which the number of MRO data is greater than a first threshold and the overlapping coverage ratio is greater than a second threshold.

[0064] In this embodiment, taking the first threshold value as 3 and the second threshold value as 20% as an example, it is determined whether the number of MRO data points (i.e., the number of MRO data) of each coverage grid is greater than 3, and whether the overlapping coverage rate of each coverage grid is greater than 20%. If the number of MRO data points of the current coverage grid is greater than 3, and the overlapping coverage rate is greater than 20%, it is determined that the current coverage grid is an overlapping coverage grid.

[0065] S1023, clustering the overlapping coverage grids based on a clustering algorithm to obtain an overlapping coverage area.

[0066] In this embodiment, the clustering algorithm includes but is not limited to the DBSCAN (Density-Based Spatial Clustering of Applications with Noise) algorithm. Taking the DBSCAN algorithm as an example, based on the clustering algorithm, the overlapping coverage grid is clustered to obtain the overlapping coverage area, which specifically includes: ① first select any point, and then find all points whose distance from the current point is ≤eps. If the number of data points within eps from the current point is <min_samples, the current point is marked as noise. If the number of data points within eps is >min_samples, the current point is marked as a core sample and is assigned a new cluster label, where eps = 100 meters and min_samples = 500. ② Then visit all neighboring points of the current point (that is, all points within eps from the current point). If all neighboring points have not been assigned a cluster, the new cluster label just assigned is assigned to the neighboring points that have not been assigned a cluster. If the neighboring point is a core sample, visit its neighboring points in turn, and so on, the cluster gradually increases until there are no more core samples within the eps distance of the cluster. ③ Select another point that has not been visited and repeat ①-③.

[0067] It should be noted that this embodiment uses Python programming to implement clustering of overlapping grids.

[0068] S103: Determine a high-interference cell in the overlapping coverage area based on the MRO data of all terminals in the overlapping coverage area.

[0069] In this embodiment, when coverage planning is performed for a preset area, it is usually accompanied by planning of the main service cell and the neighboring cell, such as: deploying the main service cell a1 and the neighboring cell a2 in area A to achieve communication coverage of area A, and deploying the main service cell b1 and the neighboring cell b2 in area B to achieve communication coverage of area B. The prior art usually determines the high-interference cells in the overlapping coverage area based on all the service cells covered in the overlapping coverage area (that is, only the number of switching is considered, and the number of switching is strictly related to the integrity and accuracy of the neighboring cell definition during coverage planning), but often ignores the interference of the service cells covered in the adjacent area of ​​the overlapping coverage area to the overlapping coverage area. In other words, the coverage range of the service cells covered in the adjacent area can not only achieve communication coverage of the adjacent area, but also achieve communication coverage of part of the area or even all of the area in the overlapping coverage area, resulting in the terminal whose coordinate position is in the overlapping coverage area but the connected service cell is in the adjacent area causing interference to the overlapping coverage area. Figure 3 As shown, the overlapping coverage areas are areas B, C, E, D, E, and F. During coverage planning, the coverage area of ​​service cell a1 is area A. Since the coverage range of service cell a1 involves areas B, C, E, D, E, and F, service cell a1 will interfere with the overlapping coverage areas.

[0070] Specifically, S103: based on the MRO data of all terminals in the overlapping coverage area, determining the high-interference cell in the overlapping coverage area, including steps S1031-S1032:

[0071] S1031: Determine serving cells to which all terminals in the overlapping coverage area are connected based on the MRO data of all terminals in the overlapping coverage area.

[0072] S1032: Calculate the interference matrix of each serving cell, where the interference matrix is ​​used to represent the set of uplink interference amounts of all terminals connected to the current serving cell to other serving cells.

[0073] Specifically, S1032: calculating the interference matrix of each serving cell, including: calculating the interference matrix of each serving cell according to formula (1):

[0074] N a =(23-PHR)-(R s Power-RSRP) (1), Among them, N a represents the ath element of the interference matrix, N a It is used to characterize the uplink interference of the ath terminal connected to the current serving cell to other serving cells, R sPower represents the power configuration of the ath terminal connected to the current serving cell, RSRP represents the RSRP of the current serving cell, and PHR represents the PHR information of the ath terminal connected to the current serving cell.

[0075] S1033: Determine high-interference cells in the overlapping coverage area based on the interference matrix of each serving cell.

[0076] In this embodiment, the MRO data of the terminals connected to each service cell are counted, and the interference matrix of each service cell is calculated according to the MRO data of the terminals connected to each service cell. Figure 4 As shown, the interference matrix of each service cell is calculated, specifically including: ① calculating the transmission power T of the terminal connected to each service cell through the PHR (Power Headroom Report) information of the terminal connected to each service cell x Power≈(23-PHR)≈(23-2)≈21. ②Measure the RSRP value of each serving cell (i.e. Figure 4 CellA RSRP: -100dBm or CellB RSRP: -103dBm), and calculate the path loss PL of each serving cell according to the RSRP value and power configuration of each serving cell. s Power-RSRP. ③ According to the transmission power T of the terminal connected to each service cell x Power and the path loss PL of each serving cell, and calculate the uplink interference N of the terminal connected to each serving cell a =T x ④ Repeat the above steps ①-③ to calculate the uplink interference amount of all terminals connected to each service cell to form an interference matrix of each service cell, wherein forming the interference matrix of each service cell includes but is not limited to summing up the uplink interference amount of all terminals connected to each service cell N = ΣN a .

[0077] It should be noted that forming the interference matrix of each service cell also includes: calculating the interference coefficient σ=∑N of all terminals connected to each service cell a / N; Calculate the interference matrix of each service cell according to the interference coefficient and uplink interference amount of all terminals connected to each service cell.

[0078] In addition to determining the high-interference cells in the overlapping coverage area through the interference matrix of each service cell, this embodiment can also determine the high-interference cells in the overlapping coverage area by calculating the interference contribution of each service cell and based on the interference contribution of each service cell. Calculating the interference contribution of each service cell specifically includes: ① Based on the MRO data of all terminals in the overlapping coverage area, counting the sampling points of each service cell as the main service cell and the sampling points of each service cell as the neighboring cell in the overlapping coverage cell list, where the overlapping coverage cell list represents the service cells connected to all terminals in the overlapping coverage area. ② According to the formula:

[0079] Calculate the interference contribution of each serving cell.

[0080] The service cell connected to the terminal is usually the main service cell in the area where the terminal is located. When the communication quality of the main service cell in the area where the terminal is located is poor, the service cell connected to the terminal will be switched to a neighboring cell.

[0081] Since the interference between service cells is usually caused by the same frequency of the service cells, this embodiment can also help determine the service cells with frequency overlap based on the carrier frequency and bandwidth used by each service cell after calculating the interference matrix or interference contribution of each service cell and before determining the high-interference cells in the overlapping coverage area, and then update the interference matrix or interference contribution of each service cell. For example: the interference matrix or interference contribution of the service cell with frequency overlap is not updated, and the interference matrix or interference contribution of the service cell without frequency overlap is updated to 0.

[0082] S104, optimizing high-interference cells in the overlapping coverage area to optimize the overlapping coverage problem.

[0083] Specifically, S104: optimizing the high-interference cells in the overlapping coverage area to optimize the overlapping coverage problem, including steps S1041-S1042:

[0084] S1041: Determine the optimal electronic downtilt of the high-interference cell based on the antenna feed tilt optimization model.

[0085] Specifically, the antenna feed tilt optimization model includes:

[0086] Average propagation coverage fitting model tan(m+e-θ / 2)=H / D,

[0087] Rolling optimization and correction strategy

[0088] Where m represents mechanical downtilt, e represents electronic downtilt, θ represents vertical beam width, H represents antenna height, D represents coverage distance, and ε represents the vertical beam width. j represents the correction factor of the jth optimization, ej represents the j-th optimized electronic downdip, e represents the upper and lower boundaries of the electron downdip fluctuation, ε t It represents the correction factor of the current optimization action t, and t-1 represents the previous optimization action.

[0089] In this embodiment, based on the antenna feed tilt optimization model, the optimal electronic downtilt of the high-interference cell is determined, specifically including: ① According to the average propagation coverage fitting model, the first optimized electronic downtilt of the high-interference cell is determined. ② Based on the j-th optimized electronic downtilt, the electronic downtilt of the high-interference cell is modified, where j=1,...,N, and N represents the optimization threshold. After modifying the electronic downtilt of the high-interference cell based on the j-th optimized electronic downtilt, if the overlapping coverage problem is still not solved, or the first optimized electronic downtilt is not suitable for the high-interference cell, it is determined that the base station operating parameter is wrong. ③ The rolling optimization correction strategy is triggered by the base station operating parameter error event, and the electronic downtilt of the high-interference cell is traversed and optimized based on the rolling optimization correction strategy and the average propagation coverage fitting model. Based on the rolling optimization correction strategy and the average propagation coverage fitting model, the electronic downtilt of the high-interference cell is traversed and optimized, including: before solving the electronic downtilt of the high-interference cell each time, read the existing engineering parameters (i.e. mechanical downtilt, electronic downtilt, vertical beam width and antenna height), store the mechanical electronic downtilt, set the electronic downtilt action constraints, the actual electronic downtilt constraints and the cell problem type to perform the operation action constraints. The average propagation coverage fitting model of the base station is solved by the least squares method, and the distance between the farthest coverage point and the theoretical farthest coverage point is compared. The point with the smallest distance is selected as the fitting switching point, and the fitting switching threshold is solved (the actual main coverage distance in the fitting curve is determined by the switching threshold and hysteresis, but the actual switching threshold may be due to the delay and waiting counter. The average value of MR switching does not match the switching parameter setting, so it is necessary to calculate the fitting switching threshold). When solving, the farthest coverage point is formed by solving the theoretical farthest coverage distance after the action and the fitting switching threshold, and the coverage curve is constructed with the point with the largest RSRP in the original fitting curve. The grid whose distance from the grid sampling point to the base station is less than the farthest coverage distance is corrected according to the new fitting curve, and the sampling point whose distance from the previous sampling point to the base station is less than the distance of the maximum RSRP point maintains the original coverage. The comprehensive indicators of weak coverage ratio and overlapping coverage ratio of sampling points in the farthest coverage area are statistically calculated. Figure 5As shown, the electronic downtilt with the smallest comprehensive index is selected as the optimal electronic downtilt for the high-interference cell. This embodiment uses the average propagation coverage fitting model to more scientifically and reasonably evaluate the network coverage status; uses the rolling optimization correction strategy to enable network operators to dynamically adjust and optimize the downtilt angle according to real-time data, and quickly respond to user feedback and network changes; through a series of optimization adjustments, the stability of the network during high-load periods can be improved, the reliability and availability of the overall network can be enhanced, and the signal interference fluctuations caused by environmental changes (such as user movement and weather factors) can be effectively responded to, and the adaptability of the network can be improved.

[0090] It should be noted that e is obtained by integrating and updating the preset adjustment boundary and the upper and lower boundaries of each optimization action. When the MRO data is incomplete, the optimization is performed again after the MRO data is completed.

[0091] S1042, based on the optimal electronic downtilt of the high-interference cell, optimizing the high-interference cell in the overlapping coverage area to optimize the overlapping coverage problem.

[0092] Optionally, after S103: determining the high-interference cell in the overlapping coverage area based on the MRO data of all terminals in the overlapping coverage area, and before S104: optimizing the high-interference cell in the overlapping coverage area to optimize the overlapping coverage problem, the optimization method for the overlapping coverage problem further includes:

[0093] S105, visually presenting each service cell and at least one of the following: an overlapping coverage grid and an overlapping coverage area.

[0094] In this embodiment, by developing the mapview tool, the visualization of overlapping grids and overlapping areas is realized in different color coding methods, such as Figure 6 and Figure 7 As shown, green grids represent coverage grids with excellent signal strength, red grids represent overlapping coverage grids, and blue grids represent coverage grids with good signal strength. The depth of the color indicates the severity of the overlapping coverage problem. In addition, through the mapview tool, line drawing and thematic analysis can be performed on individual cells, concentrated coverage grids, and TOP grids, solving the problem of no grip for overlapping coverage analysis.

[0095] The present embodiment provides a method for optimizing the overlapping coverage problem. By utilizing the MRO data of all terminals in the overlapping coverage area, all service cells whose coverage ranges involve the overlapping coverage area can be more accurately and in real time identified, and then the high-interference cells in the overlapping coverage area can be accurately determined based on all the service cells involved in the coverage range. Compared with the prior art which is limited to determining the high-interference cells in the overlapping coverage area among all the service cells in the coverage planning of the overlapping coverage area, interference factors in a wider range can be taken into account, and the dependence on theoretical models or static configurations can be reduced, thereby achieving real-time and accurate determination of high-interference cells. After accurately determining the high-interference cells, targeted optimization can be performed, the optimization direction can be clarified, the accuracy and efficiency of optimizing the overlapping coverage problem can be improved, the overlapping coverage problem can be comprehensively and accurately positioned, the reliability of the optimization direction of the overlapping coverage problem can be improved, the time and labor costs caused by invalid positioning can be reduced, and the accuracy and efficiency of optimizing the overlapping coverage problem can be improved.

[0096] Embodiment 2:

[0097] like Figure 8 As shown, this embodiment provides an optimization method for the overlapping coverage problem. The optimization method for the overlapping coverage problem includes:

[0098] S201, based on the fingerprint library algorithm, fill in the longitude and latitude of the MRO data of all terminals in the preset area; rasterize the preset area to obtain a number of coverage grids; based on the longitude and latitude, map the MRO data of all terminals in the preset area with the several coverage grids to obtain the MRO data of the several coverage grids; determine the overlapping coverage area based on the MRO data of the several coverage grids and the clustering algorithm.

[0099] S202, based on the MRO data of all terminals in the overlapping coverage area, determine the service cells connected to all terminals in the overlapping coverage area; calculate the interference matrix of each service cell, where the interference matrix is ​​used to characterize the set of uplink interference amounts of all terminals connected to the current service cell to other service cells; based on the interference matrix of each service cell, determine the high-interference cells in the overlapping coverage area.

[0100] In this embodiment, the high interference cell is Figure 8 High contribution cells in the .

[0101] S203, visually presenting each service cell and at least one of the following: an overlapping coverage grid and an overlapping coverage area.

[0102] S204, based on the antenna feed tilt optimization model, determine the optimal electronic downtilt of the high-interference cell, where the antenna feed tilt optimization model includes an average propagation coverage fitting model and a rolling optimization correction strategy; based on the optimal electronic downtilt of the high-interference cell, optimize the high-interference cell in the overlapping coverage area to optimize the overlapping coverage problem.

[0103] In this embodiment, the antenna feed tilt optimization model is Figure 8 The AI ​​antenna feed optimization model in the above example is the average propagation coverage fitting model. Figure 8 The antenna feed angle optimization model in the rolling optimization correction strategy is Figure 8 Coverage fitting and model traversal in .

[0104] The present embodiment provides a method for optimizing the overlapping coverage problem. By utilizing the MRO data of all terminals in the overlapping coverage area, all service cells whose coverage ranges involve the overlapping coverage area can be more accurately and in real time identified, and then the high-interference cells in the overlapping coverage area can be accurately determined based on all the service cells involved in the coverage range. Compared with the prior art which is limited to determining the high-interference cells in the overlapping coverage area among all the service cells in the coverage planning of the overlapping coverage area, interference factors in a wider range can be taken into account, and the dependence on theoretical models or static configurations can be reduced, thereby achieving real-time and accurate determination of high-interference cells. After accurately determining the high-interference cells, targeted optimization can be performed, the optimization direction can be clarified, the accuracy and efficiency of optimizing the overlapping coverage problem can be improved, the overlapping coverage problem can be comprehensively and accurately positioned, the reliability of the optimization direction of the overlapping coverage problem can be improved, the time and labor costs caused by invalid positioning can be reduced, and the accuracy and efficiency of optimizing the overlapping coverage problem can be improved.

[0105] Embodiment 3:

[0106] like Fig. 9 As shown, this embodiment provides an optimization device for the overlapping coverage problem, including a rasterization module 31, a first determination module 32, a second determination module 33 and an optimization module 34. The rasterization module 31 is used to rasterize the measurement report statistics MRO data of all terminals in a preset area to obtain MRO data of several covering grids. The first determination module 32 is connected to the rasterization module 31, and is used to determine the overlapping coverage area based on the MRO data of several covering grids and a clustering algorithm. The second determination module 33 is connected to the first determination module 32, and is used to determine the high interference cell in the overlapping coverage area based on the MRO data of all terminals in the overlapping coverage area. The optimization module 34 is connected to the second determination module 33, and is used to optimize the high interference cell in the overlapping coverage area to optimize the overlapping coverage problem.

[0107] Specifically, the rasterization module 31 includes: a filling unit 311, a rasterization unit 312 and a mapping unit 313. The filling unit 311 is used to fill the longitude and latitude of the MRO data of all terminals in the preset area based on the fingerprint library algorithm. The rasterization unit 312 is used to rasterize the preset area to obtain a number of covering grids. The mapping unit 313 is used to map the MRO data of all terminals in the preset area with a number of covering grids based on the longitude and latitude to obtain the MRO data of the several covering grids.

[0108] Specifically, the first determination module 32 includes: a first calculation unit 321, a first determination unit 322 and a clustering unit 323, the first calculation unit 321 is used to calculate the overlapping coverage rate of several covering grids based on the MRO data of the several covering grids, the first determination unit 322 is used to determine the overlapping coverage grid based on the overlapping coverage rate, wherein the overlapping coverage grid is used to characterize the covering grid whose number of MRO data is greater than a first threshold and whose overlapping coverage rate is greater than a second threshold, and the clustering unit 323 is used to cluster the overlapping coverage grids based on a clustering algorithm to obtain the overlapping coverage area.

[0109] Specifically, the second determination module 33 includes: a second determination unit 331, a second calculation unit 332 and a third determination unit 333. The second determination unit 331 is used to determine the service cells connected to all terminals in the overlapping coverage area based on the MRO data of all terminals in the overlapping coverage area. The second calculation unit 332 is used to calculate the interference matrix of each service cell, wherein the interference matrix is ​​used to characterize the set of uplink interference amounts of all terminals connected to the current service cell to other service cells. The third determination unit 333 is used to determine the high-interference cells in the overlapping coverage area based on the interference matrix of each service cell.

[0110] Specifically, the second calculation unit 332 includes: a calculation subunit, configured to calculate the interference matrix of each serving cell according to formula (1):

[0111] N a =(23-PHR)-(R s Power-RSRP) (1), Among them, N a represents the ath element of the interference matrix, N a It is used to characterize the uplink interference of the ath terminal connected to the current serving cell to other serving cells, R s Power represents the power configuration of the ath terminal connected to the current serving cell, RSRP represents the RSRP of the current serving cell, and PHR represents the PHR information of the ath terminal connected to the current serving cell.

[0112] Optionally, the optimization device for the overlapping coverage problem further includes: a visualization module 35, which is used to visualize each service cell and at least one of the following: an overlapping coverage grid and an overlapping coverage area.

[0113] Specifically, the optimization module 34 includes: a fourth determination unit 341 and an optimization unit 342, the fourth determination unit 341 is used to determine the optimal electronic downtilt of the high-interference cell based on the antenna feed tilt optimization model, and the optimization unit 342 is used to optimize the high-interference cell in the overlapping coverage area based on the optimal electronic downtilt of the high-interference cell to optimize the overlapping coverage problem.

[0114] It can be understood that the above-mentioned optimization device for the overlapping coverage problem executes the optimization method for the overlapping coverage problem corresponding to the embodiment 1 provided above. Therefore, the beneficial effects that can be achieved can refer to the beneficial effects of the scheme corresponding to the optimization method for the overlapping coverage problem in the above embodiment 1, which will not be repeated here.

[0115] Embodiment 4:

[0116] This embodiment also provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and the processor is configured to run the computer program to implement the optimization method for the overlapping coverage problem in the above-mentioned embodiment 1 or embodiment 2.

[0117] Embodiment 5:

[0118] This embodiment further provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the optimization method for the overlapping coverage problem in the above-mentioned embodiment 1 or embodiment 2 is implemented.

[0119] It is to be understood that the above embodiments are merely exemplary embodiments used to illustrate the principles of the present invention, but the present invention is not limited thereto. For those of ordinary skill in the art, various modifications and improvements can be made without departing from the spirit and essence of the present invention, and these modifications and improvements are also considered to be within the scope of protection of the present invention.

Claims

1. A method for optimizing overlapping coverage problems, characterized in that: include: The measurement report statistics MRO data of all terminals in the preset area are rasterized to obtain MRO data covering several grids; Based on the MRO data of several coverage grids and clustering algorithm, the overlapping coverage area is determined; Based on the MRO data of all terminals in the overlapping coverage area, determine the high-interference cells in the overlapping coverage area; Optimize the high-interference cells in the overlapping coverage area to optimize the overlapping coverage problem.

2. The optimization method for overlapping coverage problem according to claim 1, characterized in that: The step of rasterizing the measurement report statistics MRO data of all terminals in the preset area to obtain MRO data covering a plurality of grids specifically includes: Based on the fingerprint library algorithm, fill in the latitude and longitude of the MRO data of all terminals in the preset area; Rasterize the preset area to obtain a number of coverage grids; Based on the longitude and latitude, the MRO data of all terminals in the preset area are mapped with a plurality of coverage grids to obtain the MRO data of the plurality of coverage grids.

3. The optimization method for overlapping coverage problem according to claim 1, characterized in that: The method of determining overlapping coverage areas based on the MRO data of a plurality of coverage grids and a clustering algorithm specifically includes: Based on the MRO data of several coverage grids, the overlapping coverage ratio of several coverage grids is calculated; Based on the overlapping coverage ratio, determining an overlapping coverage grid, wherein the overlapping coverage grid is used to represent a coverage grid in which the amount of MRO data is greater than a first threshold and the overlapping coverage ratio is greater than a second threshold; Based on the clustering algorithm, the overlapping coverage grids are clustered to obtain the overlapping coverage area.

4. The optimization method for the overlapping coverage problem according to claim 3 is characterized in that: The determining of the high-interference cell in the overlapping coverage area based on the MRO data of all terminals in the overlapping coverage area specifically includes: Determine, based on the MRO data of all terminals in the overlapping coverage area, each serving cell to which all terminals in the overlapping coverage area are connected; Calculate the interference matrix of each serving cell, where the interference matrix is ​​used to represent the set of uplink interference amounts of all terminals connected to the current serving cell to other serving cells; Based on the interference matrix of each serving cell, the high-interference cells in the overlapping coverage area are determined.

5. The optimization method for overlapping coverage problem according to claim 4, characterized in that: The MRO data includes power headroom report PHR information, reference signal received power RSRP of the connected serving cell, and power configuration, The calculating of the interference matrix of each serving cell specifically includes: According to formula (1), the interference matrix of each service cell is calculated: N a =(23-PHR)-(R s Power-RSRP)(1), where n a represents the ath element of the interference matrix, N a It is used to characterize the uplink interference of the ath terminal connected to the current serving cell to other serving cells, R s Power represents the power configuration of the ath terminal connected to the current serving cell, RSRP represents the RSRP of the current serving cell, and PHR represents the PHR information of the ath terminal connected to the current serving cell.

6. The optimization method for overlapping coverage problem according to claim 4, characterized in that: After determining the high-interference cell in the overlapping coverage area based on the MRO data of all terminals in the overlapping coverage area, and before optimizing the high-interference cell in the overlapping coverage area to optimize the overlapping coverage problem, the method further includes: The service cells are visualized and at least one of the following: overlapping coverage grids, overlapping coverage areas.

7. The optimization method for overlapping coverage problem according to claim 1, characterized in that: The optimizing of the high-interference cells in the overlapping coverage area to optimize the overlapping coverage problem specifically includes: Determine the optimal electronic downtilt for high-interference cells based on the antenna feed tilt optimization model; Based on the optimal electronic downtilt of the high-interference cells, the high-interference cells in the overlapping coverage area are optimized to optimize the overlapping coverage problem.

8. The optimization method for overlapping coverage problem according to claim 7, characterized in that: Antenna tilt optimization models include: Average propagation coverage fitting model tan(m+e-θ / 2)=H / D, Rolling optimization correction strategy Where m represents mechanical downtilt, e represents electronic downtilt, θ represents vertical beam width, H represents antenna height, D represents coverage distance, and ε represents the vertical beam width. j represents the correction factor of the jth optimization, e j represents the j-th optimized electronic downdip, e represents the upper and lower boundaries of the electron downdip fluctuation, ε t It represents the correction factor of the current optimization action t, and t-1 represents the previous optimization action.

9. An optimization device for overlapping coverage problem, characterized in that: It includes a rasterization module, a first determination module, a second determination module and an optimization module, The gridding module is used to grid the measurement report statistics MRO data of all terminals in the preset area to obtain MRO data covering several grids. The first determination module is connected to the rasterization module and is used to determine the overlapping coverage area based on the MRO data of several coverage grids and the clustering algorithm. The second determination module is connected to the first determination module and is used to determine the high interference cell in the overlapping coverage area based on the MRO data of all terminals in the overlapping coverage area. The optimization module is connected to the second determination module and is used to optimize the high-interference cells in the overlapping coverage area to optimize the overlapping coverage problem.

10. An electronic device, characterized in that: The method comprises a memory and a processor, wherein the memory stores a computer program, and the processor is configured to run the computer program to implement an optimization method for overlapping coverage problems as described in any one of claims 1 to 8.

11. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the optimization method for overlapping coverage problem according to any one of claims 1 to 8 is implemented.

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