Method, apparatus and device for planning wireless network base stations, and medium and program product

Abstract

The present application relates to the field of network communications. Disclosed are a method, apparatus and device for planning wireless network base stations, and a medium and a program product. The method for planning wireless network base stations comprises: acquiring a plurality of discretely distributed areas to be planned; calculating a first distance from the centroid of each area to be planned to the farthest point thereof; by taking the centroid as a reference point and on the basis of the first distance, determining a station-deployable area corresponding to each area to be planned; determining a distance weight on the basis of the degree of proximity of any point within each station-deployable area to the edge thereof, performing channel modeling on the basis of initial base station positions, determining a coverage rate corresponding to each station-deployable area, and associating the distance weight with the coverage rate, so as to obtain a joint evaluation indicator of each station-deployable area; and with the objective of maximizing the sum of the joint evaluation indicators of all the station-deployable areas, using a first preset planning algorithm to plan base station positions in the station-deployable areas, so as to obtain target base station positions in the areas to be planned.

Description

Planning methods, devices, equipment, media, and software products for wireless network base stations

[0001] Cross-references to related applications

[0002] This application claims priority to Chinese Patent Application No. 202411525456.X, filed on October 29, 2024, entitled “Planning Method, Apparatus, Device, Medium and Program Product for Wireless Network Base Stations”, the entire contents of which are incorporated herein by reference. Technical Field

[0003] This application belongs to the field of network communication, and in particular relates to a planning method, apparatus, equipment, medium and program product for a wireless network base station. Background Technology

[0004] With the rapid development of wireless communication technology, network planning is becoming increasingly complex. 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, resulting in high costs and difficulty in meeting the increasingly complex, efficient, and accurate planning requirements.

[0005] Based on this, related technologies have provided a scheme for base station layout based on site planning algorithms. When laying out base stations, these algorithms first place base stations in the center of the area to be planned, and then supplement them in the peripheral areas to meet the planning requirements. However, this layout method can easily lead to overloaded central base stations, while peripheral base stations suffer from low resource utilization and uneven resource allocation. Summary of the Invention

[0006] This application provides a method, apparatus, equipment, medium, and program product for planning wireless network base stations, which effectively solves the problems of excessive load on central base stations and waste of resources on edge base stations, and improves the overall utilization efficiency of base station resources.

[0007] In a first aspect, embodiments of this application provide a method for planning a wireless network base station, the method comprising:

[0008] Obtain multiple discretely distributed regions to be planned;

[0009] For each area to be planned, calculate the first distance from the centroid of the area to the farthest point in the area; using the centroid as a reference point, determine the site deployment area for the corresponding area to be planned based on the first distance.

[0010] For each deployable area, perform the following: determine the distance weight based on how close any point within the deployable area is to the edge;

[0011] For each deployable base station area, perform the following steps: perform channel modeling based on the initial location of the base station to determine the coverage rate corresponding to the deployable base station area;

[0012] For each deployable base station area, the following steps are performed: the distance weight and coverage of the deployable base station area are associated to obtain a joint evaluation index for the deployable base station area. The joint evaluation index indicates that the evaluation index of the central base station is lower than that of the edge base station.

[0013] With the goal of maximizing the sum of joint evaluation indicators for all deployable areas, the first preset planning algorithm is used to plan the base station locations in each deployable area, thereby obtaining the target base station locations in each area to be planned.

[0014] In some embodiments of this application, the deployable area for the corresponding planned area is determined based on a first distance, using the center of gravity as a reference point, including:

[0015] The target circular area is determined with the center of gravity as the center and the first distance as the radius. The target circular area is used as the station placement area corresponding to the area to be planned.

[0016] In some embodiments of this application, distance weights are determined based on the degree to which any point within the deployable area is close to the edge, including:

[0017] Calculate the distance from any point within the deployable area to the centroid to obtain the second distance;

[0018] Calculate the ratio of the second distance to the radius of the area where stations can be deployed, and use this ratio as the distance weight.

[0019] In some embodiments of this application, distance weights and coverage rates of deployable areas are correlated to obtain joint evaluation metrics for deployable areas, including:

[0020] Calculate the product of distance weight and coverage rate, and use the product as a joint evaluation index for the area where stations can be deployed.

[0021] In some embodiments of this application, with the goal of maximizing the sum of joint evaluation indicators for all deployable areas, a first preset planning algorithm is used to plan the base station locations in each deployable area, resulting in the target base station locations in each area to be planned, including:

[0022] The base station locations in each deployable area are planned using the first preset planning algorithm. When the maximum value of the sum of the joint evaluation indicators of all deployable areas satisfies the first convergence condition, the base station locations in each deployable area are determined as the base station target locations in each area to be planned.

[0023] If the maximum sum of the joint evaluation metrics for all deployable areas does not meet the first convergence condition, update the initial location of the base station for each deployable area, return to perform channel modeling based on the initial location of the base station, and determine the coverage corresponding to the deployable area.

[0024] In some embodiments of this application, after planning the base station locations in each deployable area using a first preset planning algorithm with the objective of maximizing the sum of joint evaluation indicators for all deployable areas, and obtaining the target base station locations in each area to be planned, the wireless network base station planning method further includes:

[0025] For each base station, perform the following steps: Perform channel modeling geometric calculations based on the target location of the base station to obtain the target transmission path;

[0026] For each base station, the following steps are performed: electromagnetic calculations for channel modeling are performed based on the target transmission path and the initial parameters of the base station to obtain the evaluation index of the base station;

[0027] With the goal of satisfying the second convergence condition for the evaluation indicators of base stations in all areas to be planned, the second preset planning algorithm is used to plan the base station parameters to obtain the target parameters of base stations in each area to be planned.

[0028] In some embodiments of this application, channel modeling geometric calculations are performed based on the target location of the base station to obtain the target transmission path, including:

[0029] By taking the target end of the base station antenna as an omnidirectional antenna and the location of the target end as a mass point, the target transmission path is determined based on the spatial relationship between the triangular surface elements in the scene and the position of the target end. The target end is either the receiving end or the transmitting end.

[0030] In some embodiments of this application, channel modeling electromagnetic calculations are performed based on the target transmission path and initial parameters of the base station to obtain evaluation metrics for the base station, including:

[0031] Based on the target transmission path, the difference in radiated energy in each direction between the actual radiation pattern of the base station antenna and the omnidirectional antenna, the signal on the target transmission path is corrected to obtain the evaluation index of the base station. The actual radiation pattern of the antenna is determined based on the initial parameters of the base station.

[0032] In some embodiments of this application, with the goal of ensuring that the evaluation indicators of base stations in all areas to be planned meet the second convergence condition, a second preset planning algorithm is used to plan the base station parameters to obtain the target parameters of base stations in each area to be planned, including:

[0033] The base station parameters are planned using the second preset planning algorithm. If the evaluation index of the base stations in all areas to be planned meets 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.

[0034] If the evaluation metrics of base stations in all areas to be planned do not meet the second convergence condition, update the initial parameters of the base stations, and return to perform channel modeling electromagnetic calculations for each base station based on the target transmission path and the initial parameters of the base stations to obtain the evaluation metrics of the base stations.

[0035] Secondly, embodiments of this application provide a planning device for a wireless network base station, the planning device for the wireless network base station comprising:

[0036] The acquisition module is used to acquire multiple discretely distributed regions to be planned.

[0037] The first determination module is used to calculate the first distance from the centroid of the planned area to the farthest point of the planned area for each planned area; and to determine the station deployment area of ​​the corresponding planned area based on the first distance, using the centroid as a reference point.

[0038] The second determination module is used to perform the following for each deployable area: determine the distance weight based on the degree to which any point in the deployable area is close to the edge;

[0039] The third determination module is used to perform the following for each deployable area: perform channel modeling based on the initial location of the base station, and determine the coverage corresponding to the deployable area;

[0040] The association module is used to perform the following for each deployable area: associate the distance weight and coverage of the deployable area to obtain the joint evaluation index of the deployable area. The joint evaluation index indicates that the evaluation index of the central base station is lower than that of the edge base station.

[0041] The first planning module is used to plan the base station locations in each deployable area with the goal of maximizing the sum of the joint evaluation indicators of all deployable areas, and to obtain the target base station locations in each area to be planned.

[0042] Thirdly, embodiments of this application provide a planning device for a wireless network base station, the planning device for a wireless network base station including: a processor and a memory storing computer program instructions;

[0043] The processor executes computer program instructions to implement the wireless network base station planning method of any of the above embodiments.

[0044] Fourthly, embodiments of this application provide a computer-readable storage medium storing computer program instructions, which, when executed by a processor, implement the wireless network base station planning method of any of the above embodiments.

[0045] Fifthly, embodiments of this application provide a computer program product, wherein instructions in the computer program product, when executed by a processor of an electronic device, cause the electronic device to perform the wireless network base station planning method of any of the above embodiments.

[0046] According to the wireless network base station planning method, apparatus, device, medium and program product of the present application embodiment, distance weight and coverage 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 locations in each deployable area are planned according to the joint evaluation index, and the target locations of base stations in each planned area are finally obtained. This effectively solves the problems of excessive load on the central base station and waste of resources of the edge base station, and improves the overall utilization efficiency of base station resources. Attached Figure Description

[0047] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments of this application will be briefly introduced below. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0048] Figure 1 is a flowchart illustrating a wireless network base station planning method provided in an embodiment of this application;

[0049] Figure 2 is another flowchart illustrating the planning method for a wireless network base station provided in an embodiment of this application;

[0050] Figure 3 is a schematic flowchart of another wireless network base station planning method provided in an embodiment of this application;

[0051] Figure 4 is a schematic diagram of a planning device for a wireless network base station provided in an embodiment of this application;

[0052] Figure 5 is a schematic diagram of another structure of the planning device for a wireless network base station provided in an embodiment of this application;

[0053] Figure 6 is a schematic diagram of the planning equipment for a wireless network base station provided in an embodiment of this application. Detailed Implementation

[0054] The features and exemplary embodiments of various aspects of this application will be described in detail below. To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain this application and not to limit it. For those skilled in the art, this application can be implemented without some of these specific details. The following description of the embodiments is merely to provide a better understanding of this application by illustrating examples.

[0055] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising..." does not exclude the presence of additional identical elements in the process, method, article, or apparatus that includes said element.

[0056] With the rapid development of wireless communication technology, network planning is becoming increasingly complex. 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, resulting in high costs and difficulty in meeting the increasingly complex, efficient, and accurate planning requirements.

[0057] Based on this, related technologies have provided a scheme for base station layout based on site planning algorithms. When laying out base stations, these algorithms first place base stations in the center of the area to be planned, and then supplement them in the peripheral areas to meet the planning requirements. However, this layout method can easily lead to overloaded central base stations, while peripheral base stations suffer from low resource utilization and uneven resource allocation.

[0058] To address the aforementioned technical problems, this application provides a planning method, apparatus, equipment, medium, and program product for wireless network base stations, which effectively solves the problems of excessive load on central base stations and resource waste at edge base stations, thereby improving the overall utilization efficiency of base station resources.

[0059] Figure 1 is a flowchart illustrating a wireless network base station planning method according to an embodiment of this application. The wireless network base station planning method of this application, as described below with reference to Figure 1, includes the following steps S110-S160:

[0060] S110, obtain multiple discretely distributed regions to be planned;

[0061] S120, For each area to be planned, calculate the first distance from the centroid of the area to the farthest point of the area; using the centroid as a reference point, determine the station deployment area of ​​the corresponding area to be planned based on the first distance;

[0062] S130, for each deployable area, perform the following: determine the distance weight based on how close any point in the deployable area is to the edge;

[0063] S140, for each deployable area, perform the following: perform channel modeling based on the initial location of the base station to determine the coverage rate corresponding to the deployable area;

[0064] S150, for each deployable base station area, perform the following: associate the distance weight and coverage of the deployable base station area to obtain the joint evaluation index of the deployable base 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;

[0065] S160, with the goal of maximizing the sum of the joint evaluation indicators of all deployable areas, the first preset planning algorithm is used to plan the base station locations in each deployable area, thereby obtaining the target base station locations in each area to be planned.

[0066] According to the wireless network base station planning method of this application embodiment, distance weight and coverage 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. Based on the joint evaluation index, the base station locations in each deployable area are planned to finally obtain the target locations of base stations in each planned area. This effectively solves the problems of excessive load on the central base station and waste of resources on the edge base station, and improves the overall utilization efficiency of base station resources.

[0067] Regarding S110 above, the area to be planned is a discrete region, which can be denoted as S1, S2, S3, ... S n .

[0068] Regarding the above-mentioned S120, in some embodiments of this application, the site deployment area corresponding to the area to be planned is determined based on the first distance, using the center of gravity as a reference point, including:

[0069] The target circular area is determined with the center of gravity as the center and the first distance as the radius. The target circular area is used as the station placement area corresponding to the area to be planned.

[0070] The first distance from the centroid of each area to be planned to the farthest point of that area is denoted as D1, D2, D3, ... D n With the center of gravity as the center and the first distance as the radius Di Determine the target circular area, and use the target circular area as the site deployment area for the corresponding area to be planned.

[0071] Regarding S130 above, in some embodiments of this application, the distance weight is determined based on the degree to which any point within the deployable area is close to the edge, including:

[0072] Calculate the distance from any point within the deployable area to the centroid to obtain the second distance;

[0073] Calculate the ratio of the second distance to the radius of the area where stations can be deployed, and use this ratio as the distance weight.

[0074] Specifically, the distance weight Q i The settings need to ensure that locations near the edge of the deployable area have higher weights, guiding the base station layout to expand towards the edge areas, thereby avoiding the load imbalance problem caused by base stations being concentrated in the center.

[0075] In this embodiment of the application, the distance weight can be set as follows: Where d i D represents the distance from any point within the stationable area to the centroid, also known as the second distance. i This indicates the radius of the area where stations can be deployed.

[0076] Regarding S140 above, channel modeling is performed based on the initial location of the base station. Specifically, statistical channel modeling or lightweight deterministic channel modeling can be performed based on the initial location of the base station. Statistical channel modeling methods include, but are not limited to, commonly used channel models such as the Hata model, COST231-Hata model, Walfisch-Ikegami model, SUI model, and Lee model. Lightweight deterministic channel modeling methods include, but are not limited to, free space loss model, PEL model, and lightweight ray tracing model (considering only direct, diffraction, and transmission mechanisms). Statistical channel modeling or lightweight deterministic channel modeling based on the initial location of the base station can obtain the coverage rate P corresponding to each deployable area. i .

[0077] Regarding S150 above, in some embodiments of this application, the distance weight and coverage of the deployable area are correlated to obtain a joint evaluation index for the deployable area, including:

[0078] Calculate the product of distance weight and coverage rate, and use the product as a joint evaluation index for the area where stations can be deployed.

[0079] Distance weight Q i and coverage P i The product of these factors, used as a joint evaluation metric for deployable base stations, ensures that the evaluation metrics for central base stations are lower than those for edge base stations.

[0080] Regarding the above S160, in some embodiments of this application, 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, obtaining the target base station locations in each area to be planned, including:

[0081] The base station locations in each deployable area are planned using the first preset planning algorithm. When the maximum value of the sum of the joint evaluation indicators of all deployable areas satisfies the first convergence condition, the base station locations in each deployable area are determined as the base station target locations in each area to be planned.

[0082] If the maximum sum of the joint evaluation metrics for all deployable areas does not meet the first convergence condition, update the initial location of the base station for each deployable area, return to perform channel modeling based on the initial location of the base station, and determine the coverage corresponding to the deployable area.

[0083] The first pre-defined planning algorithm includes, but is not limited to, particle swarm optimization and simulated annealing algorithms. The first convergence condition can be that the maximum value of the joint evaluation index remains constant across multiple iterations. After generating the base station location in each iteration, the second distance d is calculated based on the distance between the base station location and the centroid. i , the second distance d i The value of the joint evaluation index is calculated by substituting it into the joint evaluation index formula. When the maximum value of the joint evaluation index remains unchanged in multiple iterations, it indicates that the joint evaluation index has converged. The base station location at this time is taken as the target location of the base station in each area to be planned. When the maximum value of the joint evaluation index does not remain unchanged in multiple iterations, it indicates that the joint evaluation index has not converged. The location is updated again, and the updated base station location is taken as the initial location of the base station. Channel modeling based on the initial location of the base station is continued to determine the coverage corresponding to the deployable area until the joint evaluation index converges.

[0084] Based on the wireless network base station planning method provided in this application, a wireless network planning method based on statistical channel modeling or lightweight deterministic channel modeling is applied during the site planning stage. In this process, the radiation pattern of the base station antenna is coupled to improve prediction accuracy and planning effectiveness. By employing an intelligent iterative algorithm, with the optimization objective of achieving the optimal joint effect of distance weight and coverage, the best location for the base station can be quickly determined.

[0085] In addition to site planning, this application also involves site parameter planning. Traditional wireless network planning methods, like site planning, rely mainly 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 meet the increasingly complex, efficient and accurate planning needs.

[0086] Existing wireless network planning methods employ intelligent planning algorithms, automatically adjusting and optimizing site parameter configurations through multiple rounds of iterative convergence. While these methods have improved planning efficiency and accuracy to some extent compared to traditional methods, they still possess certain limitations.

[0087] 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.

[0088] While the former (statistical channel modeling) offers fast planning speed, its applicable frequency and scenario range is limited, and its planning accuracy is relatively low. Specifically, wireless network planning methods based on statistical channel modeling typically rely on historical data and statistical analysis, providing valuable predictions for specific frequencies or scenarios, and thus boasting a high planning speed. However, its predictive capability cannot be guaranteed when facing new frequency bands or complex environments. This limitation in frequency and scenario makes statistical channel modeling difficult to meet the demands of increasingly high-frequency bands and more complex application scenarios. Furthermore, this method often fails to fully consider channel propagation characteristics such as multipath effects and shadowing fading. Therefore, the prediction results of wireless network planning methods based on statistical channel modeling may deviate somewhat from the actual situation, and their planning results can only be used for guidance; subsequent rounds of network optimization are still required.

[0089] While the latter method offers more accurate predictions, its modeling process is complex and computationally intensive. Specifically, the deterministic channel modeling-based wireless network planning method can provide high-precision predictions by simulating signal propagation characteristics in the environment in detail, resulting in more reliable planning results. However, this method is computationally complex, requiring substantial computing resources and significant processing time. In large-scale network planning, scenarios requiring rapid deployment, or situations with relatively limited resources, this high computational complexity and resource requirements can become a bottleneck for practical applications.

[0090] Therefore, existing wireless network planning schemes each have their advantages and disadvantages, making it difficult to simultaneously balance planning efficiency and accuracy.

[0091] Figure 2 is another flowchart illustrating the planning method for a wireless network base station provided in an embodiment of this application;

[0092] To address the aforementioned technical problems, referring to Figure 2, in some embodiments of this application, after planning the base station locations in each deployable area using a first preset planning algorithm with the objective of maximizing the sum of joint evaluation indicators for all deployable areas, and obtaining the target base station locations in each area to be planned, the wireless network base station planning method further includes the following steps S210-S230:

[0093] S210, for each base station, perform the following separately: perform channel modeling geometric calculations based on the target location of the base station to obtain the target transmission path;

[0094] S220, for each base station, performs the following: electromagnetic calculations for channel modeling based on the target transmission path and the initial parameters of the base station, to obtain the evaluation index of the base station;

[0095] S230, with the goal of ensuring that the evaluation indicators of base stations in all areas to be planned meet the second convergence condition, the second preset planning algorithm is used to plan the base station parameters to obtain the target parameters of base stations in each area to be planned.

[0096] Specifically, deterministic channel modeling geometric calculations can be performed based on the target location of the base station to obtain the target transmission path, and deterministic channel modeling electromagnetic calculations can be performed based on 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, intelligent iterative optimization algorithms such as particle swarm optimization algorithm, simulated annealing algorithm, and genetic algorithm, which can find the optimal base station parameters through multiple iterations. The second convergence condition can be reaching the maximum number of iterations or the evaluation index of the base station reaching a preset value.

[0097] In this embodiment, the electromagnetic-geometric calculations of deterministic channel modeling are decoupled. After the base station site is determined, the basic geometric relationships within the scenario are not changed when planning parameters such as the base station azimuth, downtilt angle, and power. That is, the geometric calculation results remain unchanged; only the changes in electromagnetic simulation results caused by changes in the antenna radiation pattern due to changes in station parameters need to be considered. With the support of the decoupling capability of geometric and electromagnetic calculations, the evaluation indicators (such as coverage indicators and capacity indicators) in the iterative optimization process are calculated. Using a second preset planning algorithm, the optimal solution is found through multiple rounds of iterative convergence, completing the optimization of multi-objective station parameters. This approach can simultaneously ensure accuracy and planning efficiency, and quickly lock in the base station parameters.

[0098] Regarding the above-mentioned S210, in some embodiments of this application, channel modeling geometric calculations are performed based on the target location of the base station to obtain the target transmission path, including:

[0099] By taking the target end of the base station antenna as an omnidirectional antenna and the location of the target end as a mass point, the target transmission path is determined based on the spatial relationship between the triangular surface elements in the scene and the position of the target end. The target end is either the receiving end or the transmitting end.

[0100] Regarding the above-mentioned S220, in some embodiments of this application, channel modeling electromagnetic calculations are performed based on the target transmission path and the initial parameters of the base station to obtain the evaluation indicators of the base station, including:

[0101] Based on the target transmission path, the difference in radiated energy in each direction between the actual radiation pattern of the base station antenna and the omnidirectional antenna, the signal on the target transmission path is corrected to obtain the evaluation index of the base station. The actual radiation pattern of the antenna is determined based on the initial parameters of the base station.

[0102] Regarding the above S230, in some embodiments of this application, with the objective that the evaluation indicators of base stations in all areas to be planned satisfy the second convergence condition, a second preset planning algorithm is used to plan the base station parameters to obtain the target parameters of base stations in each area to be planned, including:

[0103] The base station parameters are planned using the second preset planning algorithm. If the evaluation index of the base stations in all areas to be planned meets 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.

[0104] If the evaluation metrics of base stations in all areas to be planned do not meet the second convergence condition, update the initial parameters of the base stations, and return to perform channel modeling electromagnetic calculations for each base station based on the target transmission path and the initial parameters of the base stations to obtain the evaluation metrics of the base stations.

[0105] Figure 3 is a schematic flowchart of another wireless network base station planning method provided in the embodiments of this application. The entire process of the wireless network base station planning method provided in the embodiments of this application is briefly described below with reference to Figure 3, including the following steps S301-S314:

[0106] S301, Determine the centroid of the discrete area to be planned, and determine the area where stations can be deployed;

[0107] S302, Set distance weight;

[0108] S303, statistical channel modeling or lightweight channel modeling;

[0109] S304, calculate the coverage rate of each discrete region;

[0110] S305, Associated coverage and distance weights, calculate joint evaluation metrics;

[0111] S306, determine whether the maximum value of the joint evaluation index remains unchanged in multiple iterations. If so, execute S307; otherwise, execute S308.

[0112] S307, Determine the location of the base station;

[0113] S308, Update base station location;

[0114] S309, Deterministic Channel Modeling Geometric Calculation;

[0115] S310, Electromagnetic computation for deterministic channel modeling;

[0116] S311, Calculate the evaluation indicators;

[0117] S312, determine whether the evaluation index has converged. If yes, proceed to S313; otherwise, proceed to S314.

[0118] S313, Determine base station parameters;

[0119] S314, Update base station parameters.

[0120] The wireless network base station planning method provided in this application introduces the concept of "distance weight" in the site planning stage, and sets the optimal combined effect of distance weight and coverage as the optimization target of intelligent iteration, so as to achieve a more balanced and effective base station layout while ensuring that coverage requirements are met. In the site parameter planning stage, based on the electromagnetic geometry-decoupling method, the site parameters can be quickly locked under the deterministic channel model prediction, which improves the efficiency of network planning and the accuracy of planning results.

[0121] Figure 4 is a schematic diagram of a wireless network base station planning device provided in an embodiment of this application. The wireless network base station planning device provided in this application is described below with reference to Figure 4. The wireless network base station planning device includes:

[0122] The acquisition module 401 is used to acquire multiple discretely distributed regions to be planned;

[0123] The first determining module 402 is used to calculate the first distance from the centroid of the planned area to the farthest point of the planned area for each planned area; and to determine the station deployment area of ​​the corresponding planned area based on the first distance, using the centroid as a reference point.

[0124] The second determining module 403 is used to perform the following for each deployable area: determine the distance weight based on the degree to which any point in the deployable area is close to the edge;

[0125] The third determining module 404 is used to perform the following for each deployable area: perform channel modeling based on the initial location of the base station, and determine the coverage rate corresponding to the deployable area;

[0126] The association module 405 is used to perform the following for each deployable area: associate the distance weight and coverage of the deployable area to obtain a joint evaluation index for 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;

[0127] The first planning module 406 is used to plan the base station locations in each deployable area with the goal of maximizing the sum of the joint evaluation indicators of all deployable areas, and to obtain the base station target locations in each area to be planned.

[0128] In some embodiments of this application, the first determining module 402 is specifically used for:

[0129] The target circular area is determined with the center of gravity as the center and the first distance as the radius. The target circular area is used as the station placement area corresponding to the area to be planned.

[0130] In some embodiments of this application, the second determining module 403 is specifically used for:

[0131] Calculate the distance from any point within the deployable area to the centroid to obtain the second distance;

[0132] Calculate the ratio of the second distance to the radius of the area where stations can be deployed, and use this ratio as the distance weight.

[0133] In some embodiments of this application, the association module 405 is specifically used for:

[0134] Calculate the product of distance weight and coverage rate, and use the product as a joint evaluation index for the area where stations can be deployed.

[0135] In some embodiments of this application, the first planning module 406 is specifically used for:

[0136] The base station locations in each deployable area are planned using the first preset planning algorithm. When the maximum value of the sum of the joint evaluation indicators of all deployable areas satisfies the first convergence condition, the base station locations in each deployable area are determined as the base station target locations in each area to be planned.

[0137] If the maximum sum of the joint evaluation metrics for all deployable areas does not meet the first convergence condition, update the initial location of the base station for each deployable area, return to perform channel modeling based on the initial location of the base station, and determine the coverage corresponding to the deployable area.

[0138] Figure 5 is a schematic diagram of another structure of the planning device for a wireless network base station provided in an embodiment of this application;

[0139] In some embodiments of this application, referring to FIG5, the planning device for a wireless network base station in this application embodiment further includes:

[0140] The geometric calculation module 501 is used to plan the base station locations in each deployable area with the goal of maximizing the sum of the joint evaluation indicators of all deployable areas. After obtaining the target base station locations in each area to be planned, for each base station, the following is performed: channel modeling geometric calculation is performed based on the target base station location to obtain the target transmission path.

[0141] The electromagnetic calculation module 502 is used to perform electromagnetic calculations for channel modeling based on the target transmission path and the initial parameters of the base station for each base station, so as to obtain the evaluation index of the base station.

[0142] The second planning module 503 is used to plan the base station parameters using a second preset planning algorithm with the goal of satisfying the second convergence condition for the evaluation indicators of base stations in all areas to be planned, so as to obtain the target parameters of base stations in each area to be planned.

[0143] In some embodiments of this application, the geometric calculation module 501 is specifically used for:

[0144] By taking the target end of the base station antenna as an omnidirectional antenna and the location of the target end as a mass point, the target transmission path is determined based on the spatial relationship between the triangular surface elements in the scene and the position of the target end. The target end is either the receiving end or the transmitting end.

[0145] In some embodiments of this application, the electromagnetic calculation module 502 is specifically used for:

[0146] Based on the target transmission path, the difference in radiated energy in each direction between the actual radiation pattern of the base station antenna and the omnidirectional antenna, the signal on the target transmission path is corrected to obtain the evaluation index of the base station. The actual radiation pattern of the antenna is determined based on the initial parameters of the base station.

[0147] In some embodiments of this application, the second planning module 503 is specifically used for:

[0148] The base station parameters are planned using the second preset planning algorithm. If the evaluation index of the base stations in all areas to be planned meets 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.

[0149] If the evaluation metrics of base stations in all areas to be planned do not meet the second convergence condition, update the initial parameters of the base stations, and return to perform channel modeling electromagnetic calculations for each base station based on the target transmission path and the initial parameters of the base stations to obtain the evaluation metrics of the base stations.

[0150] According to the wireless network base station planning device of this application embodiment, distance weight and coverage 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 locations in each deployable area are planned according to the joint evaluation index, and the target locations of base stations in each planned area are finally obtained. This effectively solves the problems of excessive load on the central base station and waste of resources on the edge base station, and improves the overall utilization efficiency of base station resources.

[0151] Figure 6 is a schematic diagram of the structure of the planning equipment for the wireless network base station provided in an embodiment of this application;

[0152] The planning equipment for a wireless network base station may include a processor 601 and a memory 602 storing computer program instructions.

[0153] Specifically, the processor 601 may include a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits that can be configured to implement the embodiments of this application.

[0154] Memory 602 may include mass storage for data or instructions. For example, and not limitingly, memory 602 may include a hard disk drive (HDD), floppy disk drive, flash memory, optical disk, magneto-optical disk, magnetic tape, or Universal Serial Bus (USB) drive, or a combination of two or more of these. Where appropriate, memory 602 may include removable or non-removable (or fixed) media. Where appropriate, memory 602 may be internal or external to the integrated gateway disaster recovery device. In a particular embodiment, memory 602 is non-volatile solid-state memory.

[0155] Memory may include read-only memory (ROM), random access memory (RAM), disk storage media devices, optical storage media devices, flash memory devices, and electrical, optical, or other physical / tangible memory storage devices. Therefore, typically, 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 methods according to one aspect of this disclosure.

[0156] The processor 601 implements the wireless network base station planning method in the above embodiments by reading and executing computer program instructions stored in the memory 602.

[0157] In one example, the planning equipment for a wireless network base station may also include a communication interface 603 and a bus 610. As shown in Figure 6, the processor 601, memory 602, and communication interface 603 are connected via the bus 610 and communicate with each other.

[0158] The communication interface 603 is mainly used to realize communication between various modules, devices, units and / or equipment in the embodiments of this application.

[0159] Bus 610 includes hardware, software, or both, that couples components of a planned device for a wireless network base station together. For example, and not limitingly, the bus may include an Accelerated Graphics Port (AGP) or other graphics bus, an Enhanced Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), HyperTransport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an Infinite Bandwidth Interconnect, 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 Standards Association Local (VLB) bus, or other suitable buses, or combinations of two or more of these. Where appropriate, bus 610 may include one or more buses. Although specific buses are described and illustrated in embodiments of this application, any suitable bus or interconnect is contemplated herein.

[0160] The planning device for the wireless network base station executes the planning method for the wireless network base station in the embodiments of this application, thereby realizing the planning method for the wireless network base station shown in Figures 1, 2, and 3.

[0161] Furthermore, in conjunction with the wireless network base station planning method in the above embodiments, this application embodiment can provide a computer storage medium for implementation. The computer storage medium stores computer program instructions; when these computer program instructions are executed by a processor, they implement any of the wireless network base station planning methods in the above embodiments.

[0162] In conjunction with the wireless network base station planning method in the above embodiments, this application also provides a computer program product. When the instructions in the computer program product are executed by the processor of an electronic device, the electronic device executes the wireless network base station planning method of any of the above embodiments.

[0163] It should be clarified that this application is not limited to the specific configurations and processes described above and shown in the figures. For the sake of brevity, detailed descriptions of known methods are omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of this application is not limited to the specific steps described and shown. Those skilled in the art can make various changes, modifications, and additions, or change the order of steps, after understanding the spirit of this application.

[0164] The functional blocks shown in the above-described structural diagram can be implemented as hardware, software, firmware, or a combination thereof. When implemented in hardware, they can be, for example, electronic circuits, application-specific integrated circuits (ASICs), appropriate firmware, plug-ins, function cards, etc. When implemented in software, the elements of this application are programs or code segments used to perform the required tasks. Programs or code segments can be stored on a machine-readable medium or transmitted over a transmission medium or communication link via data signals carried on a carrier wave. "Machine-readable medium" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, fiber optic media, radio frequency (RF) links, etc. Code segments can be downloaded via computer networks such as the Internet, intranets, etc.

[0165] It should also be noted that the exemplary embodiments mentioned in this application describe methods or systems based on a series of steps or apparatus. 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 embodiments, or in a different order, or several steps can be performed simultaneously.

[0166] The aspects of this disclosure have been described above with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this disclosure. It should be understood that each block in the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, 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 apparatus to produce a machine such that these instructions, executable via the processor of the computer or other programmable data processing apparatus, enable the implementation of the functions / actions specified in one or more blocks of the flowchart illustrations and / or block diagrams. 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 is also understood that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can also be implemented by special-purpose hardware performing the specified functions or actions, or can be implemented by a combination of special-purpose hardware and computer instructions.

[0167] The above description is merely a specific implementation of this application. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, modules, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here. It should be understood that the protection scope of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the protection scope of this application.

Claims

1. A method for planning wireless network base stations, the method comprising: Obtain multiple discretely distributed regions to be planned; For each region to be planned, calculate the first distance from the centroid of the region to the farthest point in the region. Using the center of gravity as a reference point, the possible station deployment area corresponding to the area to be planned is determined according to the first distance; For each deployable area, the following steps are performed: determine the distance weight based on how close any point within the deployable area is to the edge; For each deployable base station area, the following steps are performed: Channel modeling is performed based on the initial location of the base station to determine the coverage rate corresponding to the deployable base station area; For each deployable base station area, the following steps are performed: associating the distance weight of the deployable base station area with the coverage rate to obtain a joint evaluation index for the deployable base 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; With the goal of maximizing the sum of joint evaluation indicators for all deployable areas, the first preset planning algorithm is used to plan the base station locations in each deployable area, thereby obtaining the target base station locations in each area to be planned.

2. The method according to claim 1, wherein, The step of determining the site deployment area corresponding to the planned area based on the first distance, using the center of gravity as a reference point, includes: Using the center of gravity as the center point and the first distance as the radius, a target circular area is determined, and the target circular area is used as the station deployment area corresponding to the area to be planned.

3. The method according to claim 2, wherein, The step of determining the distance weight based on the proximity of any point within the deployable area to the edge includes: Calculate the distance from any point within the deployable station area to the centroid to obtain the second distance; Calculate the ratio of the second distance to the radius of the area where the station can be deployed, and use the ratio as the distance weight.

4. The method according to claim 1, wherein, The distance weight of the deployable area and the coverage rate are associated to obtain a joint evaluation index for the deployable area, including: Calculate the product of the distance weight and the coverage rate, and use the product as a joint evaluation index for the area where stations can be deployed.

5. The method according to claim 1, wherein, The goal is to maximize the sum of joint evaluation indicators for all deployable areas. A first preset planning algorithm is used to plan the base station locations in each deployable area, resulting in the target base station locations in each area to be planned, including: The first preset planning algorithm is used to plan the base station locations in each deployable area. When the maximum value of the sum of the joint evaluation indicators of all deployable areas satisfies the first convergence condition, the base station locations in each deployable area are determined as the base station target locations in each planned area. If the maximum value of the sum of the joint evaluation metrics of all deployable areas does not meet the first convergence condition, update the initial location of the base station in each deployable area, return to perform channel modeling based on the initial location of the base station, and determine the coverage corresponding to the deployable area.

6. The method according to any one of claims 1 to 5, after the method plans the base station locations in each deployable area using a first preset planning algorithm with the objective of maximizing the sum of joint evaluation indicators of all deployable areas, and obtains the target base station locations in each area to be planned, the method further includes: For each base station, perform the following steps: Perform channel modeling geometric calculations based on the target location of the base station to obtain the target transmission path; For each base station, the following steps are performed: electromagnetic calculations for channel modeling are performed based on the target transmission path and the initial parameters of the base station to obtain the evaluation index of the base station; With the goal of satisfying the second convergence condition for the evaluation indicators of base stations in all areas to be planned, the second preset planning algorithm is used to plan the base station parameters to obtain the target parameters of base stations in each area to be planned.

7. The method according to claim 6, wherein, The step of performing channel modeling and geometric calculations based on the target location 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 mass point, the target transmission path is determined according to the spatial relationship between the triangular surface element in the scene and the position of the target end, where the target end is either a receiver or a transmitter.

8. The method according to claim 7, wherein, The step of performing channel modeling electromagnetic calculations based on the target transmission path and initial base station parameters to obtain base station evaluation metrics includes: Based on the target transmission path, the difference in radiated energy in each direction between the actual radiation pattern of the base station antenna and the omnidirectional antenna, the signal on the target transmission path is corrected to obtain the evaluation index of the base station. The actual radiation pattern of the antenna is determined based on the initial parameters of the base station.

9. The method according to claim 6, wherein, The goal is to satisfy the second convergence condition for the evaluation indicators of base stations in all areas to be planned. A second preset planning algorithm is used to plan the base station parameters, resulting in target parameters for base stations in each area to be planned, including: The base station parameters are planned using the second preset planning algorithm. If the evaluation index of the base station in all areas to be planned meets the second convergence condition, the base station parameters corresponding to the second convergence condition are used as the target parameters of the base station in each area to be planned. If the evaluation metrics of base stations in all areas to be planned do not meet the second convergence condition, update the initial parameters of the base stations, and return to perform channel modeling electromagnetic calculations for each base station based on the target transmission path and the initial parameters of the base stations to obtain the evaluation metrics of the base stations.

10. A planning device for a wireless network base station, the device comprising: The acquisition module is used to acquire multiple discretely distributed regions to be planned. The first determining module is used to calculate, for each region to be planned, the first distance from the centroid of the region to the farthest point of the region to be planned. Using the center of gravity as a reference point, the possible station deployment area corresponding to the area to be planned is determined according to the first distance; The second determining module is used to perform the following for each deployable area: determining the distance weight based on the degree to which any point in the deployable area is close to the edge; The third determining module is used to perform the following for each deployable area: perform channel modeling based on the initial location of the base station, and determine the coverage rate corresponding to the deployable area; The association module is used to perform the following for each deployable base station area: associate the distance weight of the deployable base station area with the coverage rate to obtain a joint evaluation index for the deployable base 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. The first planning module is used to plan the base station locations in each deployable area with the goal of maximizing the sum of the joint evaluation indicators of all deployable areas, and to obtain the target base station locations in each area to be planned.

11. A planning device for a wireless network base station, the device comprising: Processor and memory storing computer program instructions; When the processor executes the computer program instructions, it implements the wireless network base station planning method as described in any one of claims 1 to 9.

12. A computer-readable storage medium storing computer program instructions that, when executed by a processor, constitute a planning method for a wireless network base station as described in any one of claims 1 to 9.

13. A computer program product, wherein instructions in the computer program product, when executed by a processor of an electronic device, cause the electronic device to perform the wireless network base station planning method as described in any one of claims 1 to 9.

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