Wireless network base station planning method, device, equipment, medium and program product

Abstract

The present application discloses a method, device, equipment, medium and program product for planning a wireless network base station, and relates to the field of network communication. The method comprises: obtaining a plurality of discretely distributed areas to be planned; calculating a first distance from the center of gravity of each area to be planned to the farthest point of the area to be planned; taking the center of gravity as a reference point, determining the area where a station can be deployed corresponding to the area to be planned according to the first distance; determining a distance weight according to the degree to which any point in each area where a station can be deployed is close to the edge, performing channel modeling based on the initial position of the base station, determining the coverage rate corresponding to the area where a station can be deployed, associating the distance weight and the coverage rate, and obtaining a joint evaluation index of the area where a station can be deployed; taking the sum of the joint evaluation indexes of all areas where a station can be deployed as the maximum as the goal, using a first preset planning algorithm to plan the base station positions in each area where a station can be deployed, and obtaining the target positions of the base stations in each area to be planned. The overall utilization efficiency of base station resources can be improved.

Description

Technical Field

[0001] The present application belongs to the field of network communications, and in particular, relates to a method, device, equipment, medium and program product for planning a wireless network base station. Background Art

[0002] With the rapid development of wireless communication technology, the complexity of network planning is increasing. In traditional wireless network planning methods, base station site selection mainly relies on the experience of designers. This method is not only time-consuming and labor-intensive, but also often requires repeated manual adjustments, which is costly and difficult to meet the increasingly complex, efficient and accurate planning needs.

[0003] Based on this, the related technology provides a solution for base station layout based on site planning algorithm. When the site planning algorithm is performing base station layout, the base station will be first arranged in the center of the planned area, and then the base stations will be added in the edge areas to meet the planning conditions. However, this layout method easily leads to overload of central base stations, low resource utilization of edge base stations, and unbalanced resource allocation. Summary of the invention

[0004] The embodiments of the present application provide a method, apparatus, device, medium and program product for planning a wireless network base station, which effectively solves the problems of excessive load on the central base station and waste of edge base station resources, and improves the overall utilization efficiency of base station resources.

[0005] In a first aspect, the present application provides a method for planning a wireless network base station, the method comprising:

[0006] Obtain multiple discretely distributed areas to be planned;

[0007] For each area to be planned, a first distance from the center of gravity of the area to be planned to the farthest point of the area to be planned is calculated; taking the center of gravity as a reference point, a station-laying area corresponding to the area to be planned is determined according to the first distance;

[0008] For each area where a station can be deployed, the following operations are performed: Determine the distance weight according to the degree to which any point in the area where a station can be deployed is close to the edge;

[0009] For each area where a station can be deployed, the following operations are performed: channel modeling is performed based on the initial location of the base station to determine the coverage rate corresponding to the area where a station can be deployed;

[0010] For each area where a station can be deployed, the following are performed: associating the distance weight and coverage rate of the area where a station can be deployed to obtain a joint evaluation index of the area where a station can be deployed, wherein the joint evaluation index indicates that the evaluation index of the central base station is lower than that of the edge base station;

[0011] With the goal of maximizing the sum of joint evaluation indicators of all deployable areas, the first preset planning algorithm is used to plan the base station positions in each deployable area to obtain the target positions of the base stations in each area to be planned.

[0012] In some embodiments of the present application, taking the center of gravity as a reference point, determining a deployable station area corresponding to the area to be planned according to the first distance includes:

[0013] A target circular area is determined with the center of gravity as the circle point and the first distance as the radius, and the target circular area is used as the station deployable area corresponding to the area to be planned.

[0014] In some embodiments of the present application, the distance weight is determined according to the degree to which any point in the deployable station area is close to the edge, including:

[0015] Calculate the distance from any point in the stationable area to the center of gravity to obtain the second distance;

[0016] The ratio of the second distance to the radius of the deployable area is calculated, and the ratio is used as the distance weight.

[0017] In some embodiments of the present application, the distance weight and coverage rate of the deployable site area are associated to obtain a joint evaluation index of the deployable site area, including:

[0018] The product of distance weight and coverage rate is calculated and used as a joint evaluation index for the area where stations can be deployed.

[0019] In some embodiments of the present application, the first preset planning algorithm is used to plan the base station positions in each deployable area with the goal of maximizing the sum of the joint evaluation indicators of all deployable areas, and the target positions of the base stations in each area to be planned are obtained, including:

[0020] The first preset planning algorithm is used to plan the base station positions in each deployable area. When the maximum value of the sum of the joint evaluation indicators of all deployable areas meets the first convergence condition, the base station positions in each corresponding deployable area are determined as the target base station positions in each area to be planned.

[0021] When the maximum value of the sum of the joint evaluation indicators of all deployable areas does not meet the first convergence condition, the initial position of the base station in each deployable area is updated, and the channel modeling based on the initial position of the base station is returned to determine the coverage rate corresponding to the deployable area.

[0022] In some embodiments of the present application, with the goal of maximizing the sum of the joint evaluation indicators of all deployable sites, a first preset planning algorithm is used to plan the base station positions in each deployable site area, and after obtaining the target positions of the base stations in each to-be-planned area, the method further includes:

[0023] For each base station, perform the following: perform channel modeling geometry calculation according to the base station target position to obtain the target transmission path;

[0024] For each base station, the following are performed: channel modeling electromagnetic calculations are performed according to the target transmission path and the initial parameters of the base station to obtain the evaluation indicators of the base station;

[0025] With the goal that the evaluation indicators of the base stations in all the areas to be planned meet the second convergence condition, the base station parameters are planned using the second preset planning algorithm to obtain the target parameters of the base stations in each area to be planned.

[0026] In some embodiments of the present application, channel modeling geometry calculation is performed according to the target position of the base station to obtain the target transmission path, including:

[0027] By taking the target end of the base station antenna as an omnidirectional antenna and the location of the target end as a particle, the target transmission path is determined according to the spatial relationship between the triangular surface element in the scene and the location of the target end. The target end is the receiving end or the transmitting end.

[0028] In some embodiments of the present application, electromagnetic calculations for channel modeling are performed according to the target transmission path and the initial parameters of the base station to obtain evaluation indicators of the base station, including:

[0029] According to the target transmission path, the real radiation pattern of the base station antenna and the radiation energy difference in each direction between the omnidirectional antenna, the signal on the target transmission path is corrected to obtain the evaluation index of the base station. The real radiation pattern of the antenna is determined based on the initial parameters of the base station.

[0030] In some embodiments of the present application, the evaluation indicators of base stations in all areas to be planned meet the second convergence condition as a goal, and the base station parameters are planned using the second preset planning algorithm to obtain the target parameters of the base stations in each area to be planned, including:

[0031] The base station parameters are planned by using the second preset planning algorithm. When the evaluation indicators of the base stations in all the areas to be planned meet the second convergence condition, the base station parameters corresponding to the conditions that meet the second convergence condition are used as the target parameters of the base stations in each area to be planned.

[0032] When the evaluation indicators of all base stations in the area to be planned do not meet the second convergence condition, the initial parameters of the base stations are updated, and the channel modeling electromagnetic calculation is performed for each base station according to the target transmission path and the initial parameters of the base station to obtain the evaluation indicators of the base stations.

[0033] In a second aspect, the present application provides a planning device for a wireless network base station, the device comprising:

[0034] An acquisition module, used for acquiring a plurality of discretely distributed areas to be planned;

[0035] A first determination module is used to calculate, for each area to be planned, a first distance from the center of gravity of the area to be planned to the farthest point of the area to be planned; taking the center of gravity as a reference point, determining a station-deployable area corresponding to the area to be planned according to the first distance;

[0036] The second determination module is used to respectively perform, for each station deployable area: determining a distance weight according to the degree to which any point in the station deployable area is close to the edge;

[0037] The third determination module is used to respectively perform, for each area where a station can be deployed: performing channel modeling based on an initial position of the base station to determine a coverage rate corresponding to the area where a station can be deployed;

[0038] The association module is used to perform, for each deployable station area, the following operations: associating the distance weight and coverage rate of the deployable station area to obtain a joint evaluation index of the deployable station area, wherein the joint evaluation index indicates that the evaluation index of the central base station is lower than that of the edge base station;

[0039] The first planning module is used to plan the base station locations in each deployable area with the goal of maximizing the sum of joint evaluation indicators of all deployable areas, using a first preset planning algorithm to obtain the target location of the base station in each area to be planned.

[0040] In a third aspect, an embodiment of the present application provides a planning device for a wireless network base station, the device comprising: a processor and a memory storing computer program instructions;

[0041] When the processor executes the computer program instructions, the method for planning a wireless network base station in any of the above embodiments is implemented.

[0042] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium having computer program instructions stored thereon. When the computer program instructions are executed by a processor, a method for planning a wireless network base station according to any of the above embodiments is implemented.

[0043] In a fifth aspect, an embodiment of the present application provides a computer program product. When instructions in the computer program product are executed by a processor of an electronic device, the electronic device executes the method for planning a wireless network base station of any of the above embodiments.

[0044] According to the planning method, device, equipment, medium and program product of the wireless network base station in the embodiment of the present application, the distance weight and coverage are associated as a joint evaluation indicator. The joint evaluation indicator indicates that the evaluation indicator of the central base station is lower than that of the edge base station. The base station positions in each deployable area are planned according to the joint evaluation indicator to finally obtain the target positions of the base stations in each area to be planned, which effectively solves the problems of excessive load on the central base station and waste of edge base station resources, and improves the overall utilization efficiency of base station resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the technical solution of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0046] Figure 1 A schematic diagram of a flow chart of a method for planning a wireless network base station provided in an embodiment of the present application;

[0047] Figure 2 Another schematic diagram of a flow chart of a method for planning a wireless network base station provided in an embodiment of the present application;

[0048] Figure 3 A schematic diagram of another flow chart of a method for planning a wireless network base station provided in an embodiment of the present application;

[0049] Figure 4 A schematic diagram of the structure of a planning device for a wireless network base station provided in an embodiment of the present application;

[0050] Figure 5 Another structural schematic diagram of a planning device for a wireless network base station provided in an embodiment of the present application;

[0051] Figure 6 A schematic diagram of the structure of a planning device for a wireless network base station provided in an embodiment of the present application. DETAILED DESCRIPTION

[0052] The features and exemplary embodiments of various aspects of the present application will be described in detail below. In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain the present application, rather than to limit the present application. For those skilled in the art, the present application can be implemented without the need for some of these specific details. The following description of the embodiments is only to provide a better understanding of the present application by illustrating the examples of the present application.

[0053] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the statement "include..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

[0054] With the rapid development of wireless communication technology, the complexity of network planning is increasing. In traditional wireless network planning methods, base station site selection mainly relies on the experience of designers. This method is not only time-consuming and labor-intensive, but also often requires repeated manual adjustments, which is costly and difficult to meet the increasingly complex, efficient and accurate planning needs.

[0055] Based on this, the related technology provides a solution for base station layout based on site planning algorithm. When the site planning algorithm is performing base station layout, the base station will be first arranged in the center of the planned area, and then the base stations will be added in the edge areas to meet the planning conditions. However, this layout method easily leads to overload of central base stations, low resource utilization of edge base stations, and unbalanced resource allocation.

[0056] In order to solve the above technical problems, the embodiments of the present application provide a planning method, device, equipment, medium and program product for a wireless network base station, which effectively solves the problems of excessive load on the central base station and waste of edge base station resources, and improves the overall utilization efficiency of base station resources.

[0057] Figure 1 A flowchart of a method for planning a wireless network base station provided in an embodiment of the present application is shown below in combination with Figure 1 A method for planning a wireless network base station according to an embodiment of the present application is introduced, and the method comprises the following steps:

[0058] S110, obtaining a plurality of discretely distributed areas to be planned;

[0059] S120, for each area to be planned, calculating a first distance from the centroid of the area to be planned to the farthest point of the area to be planned; taking the centroid as a reference point, determining a station deployable area corresponding to the area to be planned according to the first distance;

[0060] S130, for each area where a station can be deployed, respectively executing: determining a distance weight according to the degree to which any point in the area where a station can be deployed is close to the edge;

[0061] S140, for each area where a station can be deployed, respectively executing: performing channel modeling based on an initial position of a base station to determine a coverage rate corresponding to the area where a station can be deployed;

[0062] S150, for each deployable area, respectively performing: associating the distance weight and coverage rate of the deployable area to obtain a joint evaluation index of the deployable area, wherein the joint evaluation index indicates that the evaluation index of the central base station is lower than that of the edge base station;

[0063] S160, with the goal of maximizing the sum of joint evaluation indicators of all deployable areas, a first preset planning algorithm is used to plan the base station locations in each deployable area to obtain the target locations of the base stations in each area to be planned.

[0064] According to the planning method of the wireless network base station in the embodiment of the present application, the distance weight and the coverage rate are associated as a joint evaluation index. The joint evaluation index indicates that the evaluation index of the central base station is lower than that of the edge base station. The base station positions in each deployable area are planned according to the joint evaluation index to finally obtain the target positions of the base stations in each area to be planned, which effectively solves the problems of excessive load on the central base station and waste of edge base station resources, and improves the overall utilization efficiency of base station resources.

[0065] Regarding the above S110, the area to be planned is a discrete area, which can be recorded as S1, S2, S3, ... S n .

[0066] Regarding the above S120, in some embodiments of the present application, taking the center of gravity as a reference point, determining the deployable station area corresponding to the area to be planned according to the first distance includes:

[0067] A target circular area is determined with the center of gravity as the circle point and the first distance as the radius, and the target circular area is used as the station deployable area corresponding to the area to be planned.

[0068] The first distance from the center of gravity of each area to be planned to the farthest point of the area to be planned is recorded as D1, D2, D3, ... D n , with the center of gravity as the point and the first distance as the radius D i Determine the target circular area and use the target circular area as the station deployment area corresponding to the area to be planned.

[0069] Regarding the above S130, in some embodiments of the present application, the distance weight is determined according to the degree to which any point in the deployable station area is close to the edge, including:

[0070] Calculate the distance from any point in the stationable area to the center of gravity to obtain the second distance;

[0071] The ratio of the second distance to the radius of the deployable area is calculated, and the ratio is used as the distance weight.

[0072] Specifically, the distance weight Q i The setting needs to ensure that the location close to the edge of the deployable area has a higher weight, guiding the base station layout to expand to the edge area, thereby avoiding the load imbalance problem caused by the concentration of base stations in the central location.

[0073] In the embodiment of the present application, the distance weight can be set as: , where d i It represents the distance from any point in the stationable area to the center of gravity, that is, the first distance, D i Indicates the radius of the area where stations can be deployed.

[0074] Regarding the above S140, channel modeling is performed based on the initial position of the base station. Specifically, statistical channel modeling or lightweight deterministic channel modeling can be performed based on the initial position of the base station, wherein the statistical channel modeling method includes but is not limited to the commonly used channel models such as the Hata model, COST231-Hata model, Walfisch-Ikegami model, SUI model, and Lee model, and the lightweight deterministic channel modeling method includes but is not limited to the free space loss model, the PEL model, and the lightweight ray tracing model (only considering direct, diffraction, and transmission mechanisms). Performing statistical channel modeling or lightweight deterministic channel modeling based on the initial position of the base station can obtain the coverage rate P corresponding to each deployable area. i .

[0075] Regarding the above S150, in some embodiments of the present application, the distance weight and coverage rate of the deployable site area are associated to obtain a joint evaluation index of the deployable site area, including:

[0076] The product of distance weight and coverage rate is calculated and used as a joint evaluation index for the area where stations can be deployed.

[0077] The distance weight Q i and coverage P i The product of is used as the joint evaluation index of the deployable base station area, which can ensure that the evaluation index of the central base station is lower than that of the edge base station.

[0078] Regarding the above S160, in some embodiments of the present application, the first preset planning algorithm is used to plan the base station positions in each deployable area with the goal of maximizing the sum of the joint evaluation indicators of all deployable areas, and the base station target positions in each to-be-planned area are obtained, including:

[0079] The first preset planning algorithm is used to plan the base station positions in each deployable area. When the maximum value of the sum of the joint evaluation indicators of all deployable areas meets the first convergence condition, the base station positions in each corresponding deployable area are determined as the target base station positions in each area to be planned.

[0080] When the maximum value of the sum of the joint evaluation indicators of all deployable areas does not meet the first convergence condition, the initial position of the base station in each deployable area is updated, and the channel modeling based on the initial position of the base station is returned to determine the coverage rate corresponding to the deployable area.

[0081] The first preset planning algorithm includes but is not limited to particle swarm optimization algorithm and simulated annealing algorithm. The first convergence condition can be that the maximum value of the joint evaluation index remains unchanged in multiple iterations. After each iteration generates the base station position, the first distance d is calculated based on the distance between the base station position and the center of gravity. i , the first distance d i Substitute the value of the joint evaluation index into the joint evaluation index formula to calculate. When the maximum value of the joint evaluation index remains unchanged during multiple iterations, it means that the joint evaluation index has converged. The base station position at this time is used as the target position of the base station in each area to be planned. When the maximum value of the joint evaluation index does not remain unchanged during multiple iterations, it means that the joint evaluation index has not converged. Continue to update the position, use the updated base station position as the initial position of the base station, continue to perform channel modeling based on the initial position of the base station, and determine the coverage rate corresponding to the area where the station can be deployed until the joint evaluation index converges.

[0082] Based on the wireless network base station planning method provided by the embodiment of the present application, in the site planning stage, a wireless network planning method based on statistical channel modeling or lightweight deterministic channel modeling is applied. In this process, the radiation pattern of the base station antenna is coupled to improve the prediction accuracy and planning effect. With the help of an intelligent iterative algorithm, the optimal location of the base station can be quickly determined with the optimal combined effect of distance weight and coverage as the optimization goal.

[0083] In addition to site planning, this application also involves base station parameter planning. Traditional wireless network planning methods, like site planning, mainly rely on the experience of designers for base station parameter planning. This method is not only time-consuming and labor-intensive, but also often requires repeated manual adjustments, which is costly and difficult to cope with the increasingly complex, efficient and accurate planning needs.

[0084] Existing wireless network planning methods use intelligent planning algorithms to automatically adjust and optimize station parameter configurations through multiple rounds of iterative convergence. Although existing planning methods have improved planning efficiency and accuracy to a certain extent compared to traditional methods, they still have some limitations.

[0085] Existing wireless network planning methods are mainly divided into two categories: wireless network planning methods based on statistical channel modeling and wireless network planning methods based on deterministic channel modeling.

[0086] Although the former has a fast planning speed, its applicable frequency and scenario range is limited, and the planning accuracy is relatively low. Specifically, the wireless network planning method based on statistical channel modeling is usually based on historical data and statistical analysis, and can provide valuable predictions under specific frequencies or scenarios. This method has a high planning rate. However, when facing new frequency bands or complex environments, its prediction ability cannot be guaranteed. This frequency and scenario limitation makes it difficult for statistical channel modeling to meet the needs of the growing high-frequency bands and increasingly complex application scenarios. In addition, this method often does not fully consider channel propagation characteristics such as multipath effects and shadow fading. Therefore, the prediction results of the wireless network planning method based on statistical channel modeling may deviate from the actual situation to a certain extent, and its planning results can only be used for guidance, and multiple rounds of network optimization are required in the future.

[0087] Although the latter can provide more accurate prediction results, its modeling process is complex and consumes a lot of computing resources. Specifically, the wireless network planning method based on deterministic channel modeling can provide high-precision predictions by simulating the signal propagation characteristics in the environment in detail, and its planning results are more reliable. However, this method has high computational complexity, requires a lot of computing resources and a long processing time. In the case of large-scale network planning, rapid deployment or relatively tight resources, this high computational complexity and high resource demand may become a bottleneck for practical applications.

[0088] Therefore, existing wireless network planning solutions have their own advantages and disadvantages, and it is difficult to take into account both planning efficiency and accuracy at the same time.

[0089] Figure 2 Another schematic diagram of a flow chart of a method for planning a wireless network base station provided in an embodiment of the present application;

[0090] In order to solve the above technical problems, combined Figure 2 In some embodiments of the present application, with the goal of maximizing the sum of the joint evaluation indicators of all deployable sites, a first preset planning algorithm is used to plan the base station locations in each deployable site area, and after obtaining the target locations of the base stations in each to-be-planned area, the planning method for the wireless network base station further includes the following steps:

[0091] S210, for each base station, respectively executing: performing channel modeling geometry calculation according to the base station target position to obtain a target transmission path;

[0092] S220, for each base station, respectively executing: performing electromagnetic calculation of channel modeling according to the target transmission path and the initial parameters of the base station to obtain an evaluation index of the base station;

[0093] S230, taking the evaluation indicators of the base stations in all the areas to be planned as meeting the second convergence condition as the goal, adopting the second preset planning algorithm to plan the base station parameters, and obtaining the target parameters of the base stations in each area to be planned.

[0094] Among them, deterministic channel modeling geometric calculation can be performed according to the target position of the base station to obtain the target transmission path, and deterministic channel modeling electromagnetic calculation can be performed according to the target transmission path and the initial parameters of the base station to obtain the evaluation index of the base station. The evaluation index of the base station can be coverage, capacity, etc. The second preset planning algorithm includes but is not limited to particle swarm optimization algorithm, simulated annealing algorithm, genetic algorithm and other intelligent iterative optimization algorithms, which can search for the optimal base station parameters through multiple rounds of iterations. The second convergence condition can be as large as the maximum number of iterations or the evaluation index of the base station reaches the preset value.

[0095] In the embodiment of the present application, the electromagnetic-geometric decoupling calculation of the deterministic channel modeling is performed. After the base station site is determined, the basic geometric relationship in the scene will not be changed when planning the base station azimuth, downtilt angle, power and other parameters, that is, the geometric calculation results will not change, and only the changes in the electromagnetic simulation results caused by the changes in the antenna radiation pattern due to the changes in the station parameters need to be considered. With the support of the decoupling capabilities of geometry and electromagnetic calculations, the evaluation indicators (such as coverage indicators and capacity indicators) in the iterative optimization process are calculated, and the second preset planning algorithm is used to find the optimal solution through multiple rounds of iterative convergence to complete the multi-objective station parameter optimization, which can take into account both accuracy and planning efficiency and quickly lock the base station parameters.

[0096] Regarding the above S210, in some embodiments of the present application, performing channel modeling geometry calculation according to the target position of the base station to obtain the target transmission path includes:

[0097] By taking the target end of the base station antenna as an omnidirectional antenna and the location of the target end as a particle, the target transmission path is determined according to the spatial relationship between the triangular surface element in the scene and the location of the target end. The target end is the receiving end or the transmitting end.

[0098] Regarding the above S220, in some embodiments of the present application, channel modeling electromagnetic calculation is performed according to the target transmission path and the initial parameters of the base station to obtain evaluation indicators of the base station, including:

[0099] According to the target transmission path, the real radiation pattern of the base station antenna and the radiation energy difference in each direction between the omnidirectional antenna, the signal on the target transmission path is corrected to obtain the evaluation index of the base station. The real radiation pattern of the antenna is determined based on the initial parameters of the base station.

[0100] Regarding the above S230, in some embodiments of the present application, the evaluation indicators of the base stations in all the areas to be planned meet the second convergence condition as a goal, and the base station parameters are planned using the second preset planning algorithm to obtain the target parameters of the base stations in each area to be planned, including:

[0101] The base station parameters are planned by using the second preset planning algorithm. When the evaluation indicators of the base stations in all the areas to be planned meet the second convergence condition, the base station parameters corresponding to the conditions that meet the second convergence condition are used as the target parameters of the base stations in each area to be planned.

[0102] When the evaluation indicators of all base stations in the area to be planned do not meet the second convergence condition, the initial parameters of the base stations are updated, and the channel modeling electromagnetic calculation is performed for each base station according to the target transmission path and the initial parameters of the base station to obtain the evaluation indicators of the base stations.

[0103] Figure 3 Another flowchart of the method for planning a wireless network base station provided in the embodiment of the present application is shown below in combination with Figure 3 The whole process of the planning method of the wireless network base station provided in the embodiment of the present application is briefly introduced, including the following steps:

[0104] S301, determining the center of gravity of the discrete area to be planned and determining the area where stations can be deployed;

[0105] S302, setting distance weight;

[0106] S303, statistical channel modeling or lightweight channel modeling;

[0107] S304, calculating the coverage rate of each discrete area;

[0108] S305, associating coverage and distance weight, and calculating a joint evaluation index;

[0109] S306, determining whether the maximum value of the joint evaluation index remains unchanged in multiple iterations, if yes, executing S307, if no, executing S308;

[0110] S307, determining the base station location;

[0111] S308, updating the base station location;

[0112] S309, deterministic channel modeling geometry calculation;

[0113] S310, Deterministic Channel Modeling Electromagnetic Computing;

[0114] S311, calculating evaluation indicators;

[0115] S312, determine whether the evaluation index converges, if so, execute S313, if not, execute S314;

[0116] S313, determining base station parameters;

[0117] S314, update base station parameters.

[0118] The planning method for wireless network base stations provided in the embodiment of the present application introduces the concept of "distance weight" in the site planning stage, and optimally sets the combined effect of distance weight and coverage as the optimization goal of intelligent iteration, thereby achieving a more balanced and effective base station layout while ensuring that coverage requirements are met; in the station parameter planning stage, based on the electromagnetic geometry-decoupling method, it is possible to achieve rapid locking of station parameters under deterministic channel model prediction, thereby improving network planning efficiency while improving the accuracy of planning results.

[0119] Figure 4 A schematic diagram of a structure of a wireless network base station planning device provided in an embodiment of the present application, in combination with Figure 4 The present invention provides a wireless network base station planning device, which includes:

[0120] An acquisition module 401 is used to acquire a plurality of discretely distributed areas to be planned;

[0121] The first determination module 402 is used to calculate, for each area to be planned, a first distance from the center of gravity of the area to be planned to the farthest point of the area to be planned; taking the center of gravity as a reference point, determining a station deployable area corresponding to the area to be planned according to the first distance;

[0122] The second determination module 403 is used to respectively perform, for each station deployable area: determining a distance weight according to the degree to which any point in the station deployable area is close to the edge;

[0123] The third determination module 404 is used to respectively perform, for each area where a station can be deployed: performing channel modeling based on the initial position of the base station to determine the coverage rate corresponding to the area where a station can be deployed;

[0124] The association module 405 is used to perform, for each deployable station area, respectively: associating the distance weight and coverage rate of the deployable station area to obtain a joint evaluation index of the deployable station area, wherein the joint evaluation index indicates that the evaluation index of the central base station is lower than that of the edge base station;

[0125] The first planning module 406 is used to plan the base station locations in each deployable area using a first preset planning algorithm with the goal of maximizing the sum of joint evaluation indicators of all deployable areas, and obtain the target location of the base station in each area to be planned.

[0126] In some embodiments of the present application, the first determining module 402 is specifically configured to:

[0127] A target circular area is determined with the center of gravity as the circle point and the first distance as the radius, and the target circular area is used as the station deployable area corresponding to the area to be planned.

[0128] In some embodiments of the present application, the second determining module 403 is specifically configured to:

[0129] Calculate the distance from any point in the stationable area to the center of gravity to obtain the second distance;

[0130] The ratio of the second distance to the radius of the deployable area is calculated, and the ratio is used as the distance weight.

[0131] In some embodiments of the present application, the association module 405 is specifically used to:

[0132] The product of distance weight and coverage rate is calculated and used as a joint evaluation index for the area where stations can be deployed.

[0133] In some embodiments of the present application, the first planning module 406 is specifically configured to:

[0134] The first preset planning algorithm is used to plan the base station positions in each deployable area. When the maximum value of the sum of the joint evaluation indicators of all deployable areas meets the first convergence condition, the base station positions in each corresponding deployable area are determined as the target base station positions in each area to be planned.

[0135] When the maximum value of the sum of the joint evaluation indicators of all deployable areas does not meet the first convergence condition, the initial position of the base station in each deployable area is updated, and the channel modeling based on the initial position of the base station is returned to determine the coverage rate corresponding to the deployable area.

[0136] Figure 5 Another structural schematic diagram of a planning device for a wireless network base station provided in an embodiment of the present application;

[0137] In some embodiments of the present application, Figure 5 , the planning device of the wireless network base station in the embodiment of the present application further includes:

[0138] The geometric calculation module 501 is used to plan the base station positions in each deployable area by using a first preset planning algorithm with the goal of maximizing the sum of the joint evaluation indicators of all deployable areas, and after obtaining the target positions of the base stations in each area to be planned, for each base station, respectively perform the following: perform channel modeling geometric calculation according to the target position of the base station to obtain a target transmission path;

[0139] The electromagnetic calculation module 502 is used to perform, for each base station, the following: performing electromagnetic calculations for channel modeling according to the target transmission path and the initial parameters of the base station to obtain evaluation indicators of the base station;

[0140] The second planning module 503 is used to plan the base station parameters by using the second preset planning algorithm with the evaluation indicators of the base stations in all the areas to be planned meeting the second convergence condition as the goal, so as to obtain the target parameters of the base stations in each area to be planned.

[0141] In some embodiments of the present application, the geometry calculation module 501 is specifically used to:

[0142] By taking the target end of the base station antenna as an omnidirectional antenna and the location of the target end as a particle, the target transmission path is determined according to the spatial relationship between the triangular surface element in the scene and the location of the target end. The target end is the receiving end or the transmitting end.

[0143] In some embodiments of the present application, the electromagnetic calculation module 502 is specifically used to:

[0144] According to the target transmission path, the real radiation pattern of the base station antenna and the radiation energy difference in each direction between the omnidirectional antenna, the signal on the target transmission path is corrected to obtain the evaluation index of the base station. The real radiation pattern of the antenna is determined based on the initial parameters of the base station.

[0145] In some embodiments of the present application, the second planning module 503 is specifically used to:

[0146] The base station parameters are planned by using the second preset planning algorithm. When the evaluation indicators of the base stations in all the areas to be planned meet the second convergence condition, the base station parameters corresponding to the conditions that meet the second convergence condition are used as the target parameters of the base stations in each area to be planned.

[0147] When the evaluation indicators of all base stations in the area to be planned do not meet the second convergence condition, the initial parameters of the base stations are updated, and the channel modeling electromagnetic calculation is performed for each base station according to the target transmission path and the initial parameters of the base station to obtain the evaluation indicators of the base stations.

[0148] According to the planning device of the wireless network base station in the embodiment of the present application, the distance weight and the coverage rate are associated as a joint evaluation index. The joint evaluation index indicates that the evaluation index of the central base station is lower than that of the edge base station. The base station positions in each deployable area are planned according to the joint evaluation index to finally obtain the target positions of the base stations in each area to be planned, which effectively solves the problems of excessive load on the central base station and waste of edge base station resources, and improves the overall utilization efficiency of base station resources.

[0149] Figure 6A schematic diagram of the structure of a planning device for a wireless network base station provided in an embodiment of the present application;

[0150] The planning device for a wireless network base station may include a processor 601 and a memory 602 storing computer program instructions.

[0151] Specifically, the processor 601 may include a central processing unit (CPU), or an application specific integrated circuit (ASIC), or may be configured to implement one or more integrated circuits of the embodiments of the present application.

[0152] The memory 602 may include a large capacity memory for data or instructions. By way of example and not limitation, the memory 602 may include a hard disk drive (HDD), a floppy disk drive, a flash memory, an optical disk, a magneto-optical disk, a magnetic tape, or a universal serial bus (USB) drive or a combination of two or more of these. In appropriate cases, the memory 602 may include a removable or non-removable (or fixed) medium. In appropriate cases, the memory 602 may be inside or outside the integrated gateway disaster recovery device. In a specific embodiment, the memory 602 is a non-volatile solid-state memory.

[0153] The memory may include read-only memory (ROM), random access memory (RAM), magnetic disk storage media devices, optical storage media devices, flash memory devices, electrical, optical or other physical / tangible memory storage devices. Thus, typically, the memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., memory devices) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the method according to an aspect of the present disclosure.

[0154] The processor 601 implements the method for planning a wireless network base station in the above embodiment by reading and executing the computer program instructions stored in the memory 602 .

[0155] In one example, the planning device of the wireless network base station may further include a communication interface 603 and a bus 610. Figure 6 As shown, the processor 601, the memory 602, and the communication interface 603 are connected via a bus 610 and communicate with each other.

[0156] The communication interface 603 is mainly used to implement communication between various modules, devices, units and / or equipment in the embodiments of the present application.

[0157] Bus 610 includes hardware, software or both, and the components of the determination device of the base station configuration parameters are coupled to each other. For example, but not limitation, the bus may include an accelerated graphics port (AGP) or other graphics bus, an enhanced industrial standard architecture (EISA) bus, a front-end bus (FSB), a hypertransport (HT) interconnection, an industrial standard architecture (ISA) bus, an infinite bandwidth interconnection, a low pin count (LPC) bus, a memory bus, a microchannel architecture (MCA) bus, a peripheral component interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a serial advanced technology attachment (SATA) bus, a video electronics standard association local (VLB) bus or other suitable bus or a combination of two or more of these. Where appropriate, bus 610 may include one or more buses. Although the present application embodiment describes and shows a specific bus, the present application considers any suitable bus or interconnection.

[0158] The abnormal access object identification device executes the abnormal access object identification method in the embodiment of the present application, thereby achieving Figure 1 , Figure 2 , Figure 3 A planning method for wireless network base stations.

[0159] In addition, in combination with the wireless network base station planning method in the above embodiment, the embodiment of the present application can provide a computer storage medium for implementation. The computer storage medium stores computer program instructions; when the computer program instructions are executed by the processor, any one of the wireless network base station planning methods in the above embodiment is implemented.

[0160] In combination with the wireless network base station planning method in the above embodiments, an embodiment of the present application further provides a computer program product. When the instructions in the computer program product are executed by a processor of an electronic device, the electronic device executes the wireless network base station planning method in any of the above embodiments.

[0161] It should be clear that the present application is not limited to the specific configuration and processing described above and shown in the figures. For the sake of simplicity, a detailed description of the known method is omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of the present application is not limited to the specific steps described and shown, and those skilled in the art can make various changes, modifications and additions, or change the order between the steps after understanding the spirit of the present application.

[0162] The functional blocks shown in the structural block diagram described above can be implemented as hardware, software, firmware or a combination thereof. When implemented in hardware, it can be, for example, an electronic circuit, an application-specific integrated circuit (ASIC), appropriate firmware, a plug-in, a function card, etc. When implemented in software, the elements of the present application are programs or code segments used to perform the required tasks. The program or code segment can be stored in a machine-readable medium, or transmitted on a transmission medium or a communication link by a data signal carried in a carrier. "Machine-readable medium" may include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROMs, flash memories, erasable ROMs (EROMs), floppy disks, CD-ROMs, optical disks, hard disks, optical fiber media, radio frequency (RF) links, etc. The code segment can be downloaded via a computer network such as the Internet, an intranet, etc.

[0163] It should also be noted that the exemplary embodiments mentioned in this application describe some methods or systems based on a series of steps or devices. However, this application is not limited to the order of the above steps, that is, the steps can be performed in the order mentioned in the embodiment, or in a different order from the embodiment, or several steps can be performed simultaneously.

[0164] Aspects of the present disclosure are described above with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present disclosure. It should be understood that each box in the flowchart and / or block diagram and the combination of each box in the flowchart and / or block diagram can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device to produce a machine so that these instructions executed by the processor of the computer or other programmable data processing device enable the implementation of the functions / actions specified in one or more boxes of the flowchart and / or block diagram. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor, or a field programmable logic circuit. It can also be understood that each box in the block diagram and / or flowchart and the combination of boxes in the block diagram and / or flowchart can also be implemented by dedicated hardware that performs the specified function or action, or can be implemented by a combination of dedicated hardware and computer instructions.

[0165] The above is only a specific implementation of the present application. Those skilled in the art can clearly understand that for the convenience and simplicity of description, the specific working processes of the systems, modules and units described above can refer to the corresponding processes in the aforementioned method embodiments, and will not be repeated here. It should be understood that the protection scope of the present application is not limited to this. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed in this application, and these modifications or replacements should be included in the protection scope of this application.

Claims

1. A method for planning a wireless network base station, characterized in that: The method comprises: Obtain multiple discretely distributed areas to be planned; For each area to be planned, calculate a first distance from the center of gravity of the area to be planned to the farthest point of the area to be planned; determine a target circular area with the center of gravity as a circle point and the first distance as a radius, and use the target circular area as a station-deployable area corresponding to the area to be planned; For each area where a station can be deployed, respectively: calculating the distance from the base station planned in the area where a station can be deployed to the center of gravity to obtain a second distance; calculating the ratio of the second distance to the radius of the area where a station can be deployed, and using the ratio as the distance weight of the base station; For each area where base stations can be deployed, the following operations are performed: channel modeling is performed based on the initial location of the base station to determine the corresponding coverage of the base station; For each area where a station can be deployed, respectively: calculating the product of the distance weight and the coverage rate, and using the product as a joint evaluation index of the base station, wherein the joint evaluation index indicates that the evaluation index of the central base station is lower than that of the edge base station; With the goal of maximizing the joint evaluation index of all base stations in the deployable area, the first preset planning algorithm is used to plan the base station positions in each deployable area to obtain the target positions of the base stations in each area to be planned; The goal is to maximize the joint evaluation index of all base stations in the deployable area, and to use a first preset planning algorithm to plan the base station positions in each deployable area to obtain the target positions of the base stations in each area to be planned, including: The first preset planning algorithm is used to plan the base station positions in each deployable area, and when the maximum value of the joint evaluation index of all base stations in the deployable area remains unchanged in multiple iterations, the corresponding base station positions in each deployable area are determined as the base station target positions in each area to be planned; When the maximum value of the joint evaluation index of all base stations in the deployable area does not remain unchanged during multiple iterations, the initial position of each base station in the deployable area is updated, and the calculation of the distance from the planned base station in the deployable area to the center of gravity is returned to obtain a second distance.

2. The method according to claim 1, characterized in that After the joint evaluation index of all base stations in the deployable area is maximized and the first preset planning algorithm is used to plan the base station positions in each deployable area to obtain the target positions of the base stations in each area to be planned, the method further includes: For each base station, perform the following: perform channel modeling geometry calculation according to the base station target position to obtain the target transmission path; For each base station, respectively executing: performing electromagnetic calculation of channel modeling according to the target transmission path and the initial parameters of the base station to obtain an evaluation index of the base station; With the goal that the evaluation indicators of all base stations in the area to be planned meet the second convergence condition, the base station parameters are planned using the second preset planning algorithm to obtain the target parameters of the base stations in each area to be planned, wherein the second convergence condition is that the maximum number of iterations is reached or the evaluation indicator of the base station reaches a preset value.

3. The method according to claim 2, characterized in that The performing channel modeling geometric calculation according to the target position of the base station to obtain the target transmission path includes: By taking the target end of the base station antenna as an omnidirectional antenna and the location of the target end as a particle, the target transmission path is determined according to the spatial relationship between the triangular surface element in the scene and the location of the target end, and the target end is a receiving end or a transmitting end.

4. The method according to claim 3, characterized in that The performing electromagnetic calculation of channel modeling according to the target transmission path and the initial parameters of the base station to obtain the evaluation index of the base station includes: According to the target transmission path, the real radiation pattern of the base station antenna and the radiation energy difference in each direction between the omnidirectional antenna, the signal on the target transmission path is corrected to obtain the evaluation index of the base station. The real radiation pattern of the antenna is determined based on the initial parameters of the base station.

5. The method according to claim 2, characterized in that: The method of planning base station parameters by using a second preset planning algorithm with the evaluation index of all base stations in the area to be planned satisfying the second convergence condition as a goal, and obtaining target parameters of base stations in each area to be planned, includes: The second preset planning algorithm is used to plan the base station parameters. When the evaluation indicators of the base stations in all the areas to be planned meet the second convergence condition, the base station parameters corresponding to the second convergence condition are used as the target parameters of the base stations in each area to be planned. When the evaluation indicators of all base stations in the area to be planned do not meet the second convergence condition, the initial parameters of the base stations are updated, and the channel modeling electromagnetic calculation is performed for each base station according to the target transmission path and the initial parameters of the base station to obtain the evaluation indicators of the base stations.

6. A wireless network base station planning device, characterized in that: The device comprises: An acquisition module, used for acquiring a plurality of discretely distributed areas to be planned; A first determination module is used to calculate, for each area to be planned, a first distance from the center of gravity of the area to be planned to the farthest point of the area to be planned; determine a target circular area with the center of gravity as a circle point and the first distance as a radius, and use the target circular area as a station-deployable area corresponding to the area to be planned; The second determination module is used to respectively perform, for each deployable station area: calculating the distance from the base station planned in the deployable station area to the center of gravity to obtain a second distance; calculating the ratio of the second distance to the radius of the deployable station area, and using the ratio as the distance weight of the base station; The third determination module is used to respectively perform, for each area where a base station can be deployed: performing channel modeling based on an initial position of the base station to determine a coverage rate corresponding to the base station; An association module is used to respectively perform, for each deployable station area: calculating the product of the distance weight and the coverage rate, and using the product as a joint evaluation index of the base station, wherein the joint evaluation index indicates that the evaluation index of the central base station is lower than that of the edge base station; The first planning module is used to plan the base station positions in each deployable area by using a first preset planning algorithm with the goal of maximizing the joint evaluation index of all base stations in the deployable area, so as to obtain the target position of the base station in each area to be planned; Wherein, the first planning module is specifically used for: The first preset planning algorithm is used to plan the base station positions in each deployable area, and when the maximum value of the joint evaluation index of all base stations in the deployable area remains unchanged in multiple iterations, the corresponding base station positions in each deployable area are determined as the base station target positions in each area to be planned; When the maximum value of the joint evaluation index of all base stations in the deployable area does not remain unchanged during multiple iterations, the initial position of each base station in the deployable area is updated, and the calculation of the distance from the planned base station in the deployable area to the center of gravity is returned to obtain a second distance.

7. A wireless network base station planning device, characterized in that: The device comprises: a processor and a memory storing computer program instructions; When the processor executes the computer program instructions, the method for planning a wireless network base station according to any one of claims 1 to 5 is implemented.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer program instructions, and when the computer program instructions are executed by a processor, the method for planning a wireless network base station according to any one of claims 1 to 5 is implemented.

9. A computer program product, characterized in that When the instructions in the computer program product are executed by a processor of an electronic device, the electronic device executes the method for planning a wireless network base station as described in any one of claims 1 to 5.

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