Base station site selection method and device, storage medium and program product

Abstract

The invention provides a base station site selection method and device, a storage medium and a program product, relates to the technical field of communication, can perform comprehensive quantitative evaluation on the adaptability of an air route and a communication resource to realize more effective base station site selection, and comprises the steps of obtaining signal information of an established base station and air route information of an unmanned aerial vehicle; determining at least one candidate site based on the signal information of the established base station and the route information of the unmanned aerial vehicle; determining a base station site selection scheme based on the at least one candidate site; wherein the evaluation index of the base station site selection scheme is greater than or equal to a first threshold value; the evaluation indexes are used for evaluating the station building cost and the signal coverage rate.

Description

Technical Field

[0001] This application relates to the field of communication technologies, and in particular, to a method, device, storage medium, and program product for base station site selection. Background Art

[0002] With the rapid development of unmanned aerial vehicle (UAV) technology, its applications in the low-altitude field are becoming increasingly widespread, deeply covering many important fields such as logistics transportation, environmental monitoring, and disaster assessment.

[0003] When a UAV is flying, stable communication and sensing support are crucial, which are necessary conditions for it to complete tasks safely and efficiently. In this way, the adaptability of the flight path and communication and sensing resources becomes one of the key factors affecting the flight performance and mission success rate of the UAV. However, traditional base station site selection methods often ignore the complex relationship between communication and sensing resources and the flight path, resulting in situations where the UAV is prone to communication interruption and falling into a sensing blind area during actual flight. Summary of the Invention

[0004] This application provides a method, device, storage medium, and program product for base station site selection, which can comprehensively quantify and evaluate the adaptability of the flight path and communication and sensing resources, so as to achieve more effective base station site selection.

[0005] In a first aspect, this application provides a method for base station site selection. The method includes: obtaining signal information of existing base stations and flight path information of UAVs; determining at least one candidate site based on the signal information of existing base stations and the flight path information of UAVs; determining a base station site selection plan based on at least one candidate site; where the evaluation index of the base station site selection plan is greater than or equal to a first threshold; the evaluation index is used to evaluate the construction cost and signal coverage rate.

[0006] It can be understood that traditional base station site selection plans do not consider the adaptability problem between the communication and sensing resources of the base station and the UAV flight path. This application makes full use of the signal information of existing base stations and the UAV flight path information to evaluate those candidate sites that have construction conditions but have not been built. On this basis, the optimal base station site selection plan is determined by comprehensively considering the construction cost and signal coverage rate, successfully filling the gap in the traditional base station site selection plan in terms of considering air communication, and improving the service quality and efficiency of air transportation and mobile communication.

[0007] A possible implementation manner, where the route information of the UAV includes the flight path of the UAV; based on the signal information of the existing base stations and the route information of the UAV, determining at least one candidate site, including: dividing the flight path of the UAV into multiple flight segments; for each flight segment among the multiple flight segments, determining the base station signal strength in the airspace where each flight segment is located based on the signal information of the existing base stations; based on the base station signal strength in the airspace where each flight segment is located and the minimum signal strength required by the UAV on each flight segment, determining M target areas that do not meet the communication requirements of the UAV; one target area includes one flight segment; M is an integer greater than or equal to 1; determining at least one candidate site according to the M target areas.

[0008] Another possible implementation manner, determining at least one candidate site according to the M target areas, including: performing a clustering operation on the M target areas to obtain X clustering centers; where the clustering center is a point where the local density in the clustering cluster is greater than or equal to a second threshold, and / or the clustering center is a point where the clustering distance is greater than or equal to a third threshold; N is an integer greater than or equal to 1 and less than or equal to M; determining at least one candidate site according to the positions of the X clustering centers.

[0009] Another possible implementation manner, the distance between the candidate site and the X clustering centers is less than or equal to a preset distance.

[0010] Another possible implementation manner, determining a base station site selection scheme based on at least one candidate site, including: determining at least one candidate base station site selection scheme based on at least one candidate site; the candidate base station site selection scheme includes one or more selected sites; where the selected site is any one of at least one candidate site; for each candidate base station site selection scheme among at least one candidate base station site selection scheme, calculating the evaluation index of each candidate base station site selection scheme respectively; determining the base station site selection scheme based on the evaluation index of each candidate base station site selection scheme.

[0011] Another possible implementation manner, determining at least one candidate base station site selection scheme based on at least one candidate site, including: using a genetic algorithm to determine at least one candidate base station site selection scheme based on at least one candidate site.

[0012] Another possible implementation manner, the evaluation index is determined based on the weighted sum of the site construction cost index and the coverage rate index.

[0013] Another possible implementation manner, the base station site selection scheme includes one or more selected base stations; the site construction cost index is determined based on the following parameters: the number of selected base stations included in the base station site selection scheme, the number of at least one candidate base station.

[0014] Another possible implementation manner, the base station site selection scheme includes one or more selected base stations; the coverage rate index is determined based on the following parameters: the number of target areas that can be covered by one or more selected base stations, and the total number of target areas; wherein, the target area is an area where the base station signal strength of the existing base stations cannot meet the communication requirements of the unmanned aerial vehicle.

[0015] Another possible implementation manner, the signal information of the existing base stations includes at least one of the following: signal strength, coverage range, signal frequency band.

[0016] Another possible implementation manner, the route information of the unmanned aerial vehicle includes at least one of the following: take-off point, landing point, flight path, communication requirement, sensing frequency, sensing delay.

[0017] In a second aspect, the present application provides a base station site selection device, which includes: an acquisition module and a processing module. Among them, the acquisition module is used to: acquire the signal information of the existing base stations and the route information of the unmanned aerial vehicle; the processing module is used to: determine at least one candidate site based on the signal information of the existing base stations and the route information of the unmanned aerial vehicle; determine a base station site selection scheme based on at least one candidate site; wherein, the evaluation index of the base station site selection scheme is greater than or equal to a first threshold; the evaluation index is used to evaluate the construction cost and signal coverage rate.

[0018] A possible implementation manner, the route information of the unmanned aerial vehicle includes the flight path of the unmanned aerial vehicle; specifically, the processing module is used to: divide the flight path of the unmanned aerial vehicle into multiple flight segments; for each flight segment among the multiple flight segments, determine the base station signal strength in the airspace where each flight segment is located based on the signal information of the existing base stations; based on the base station signal strength in the airspace where each flight segment is located and the minimum signal strength required by the unmanned aerial vehicle on each flight segment, determine M target areas that do not meet the communication requirements of the unmanned aerial vehicle; one target area includes one flight segment; M is an integer greater than or equal to 1; determine at least one candidate site according to the M target areas.

[0019] Another possible implementation manner, specifically, the processing module is used to: perform a clustering operation on the M target areas to obtain X clustering centers; wherein, the clustering center is a point where the local density in the clustering cluster is greater than or equal to a second threshold, and / or, the clustering center is a point where the clustering distance is greater than or equal to a third threshold; N is an integer greater than or equal to 1 and less than or equal to M; determine at least one candidate site according to the positions of the X clustering centers.

[0020] Another possible implementation manner, the distance between the candidate site and the X clustering centers is less than or equal to a preset distance.

[0021] Another possible implementation manner, the processing module is specifically configured to: determine at least one candidate base station site selection scheme based on at least one candidate site; the candidate base station site selection scheme includes one or more selected sites; wherein, the selected site is any one of the at least one candidate site; for each candidate base station site selection scheme among the at least one candidate base station site selection scheme, calculate the evaluation index of each candidate base station site selection scheme respectively; and determine the base station site selection scheme based on the evaluation index of each candidate base station site selection scheme.

[0022] Another possible implementation manner, the processing module is specifically configured to: adopt a genetic algorithm to determine at least one candidate base station site selection scheme based on at least one candidate site.

[0023] Another possible implementation manner, the evaluation index is determined based on the weighted sum of the site construction cost index and the coverage rate index.

[0024] Another possible implementation manner, the base station site selection scheme includes one or more selected base stations; the site construction cost index is determined based on the following parameters: the number of selected base stations included in the base station site selection scheme, and the number of at least one candidate base station.

[0025] Another possible implementation manner, the base station site selection scheme includes one or more selected base stations; the coverage rate index is determined based on the following parameters: the number of target areas that can be covered by one or more selected base stations, and the total number of target areas; wherein, the target area is an area where the base station signal strength of the existing base station cannot meet the communication requirements of the unmanned aerial vehicle.

[0026] Another possible implementation manner, the signal information of the existing base station includes at least one of the following: signal strength, coverage range, and signal frequency band.

[0027] Another possible implementation manner, the route information of the unmanned aerial vehicle includes at least one of the following: take-off point, landing point, flight path, communication requirement, sensing frequency, and sensing delay.

[0028] In a third aspect, the present application provides an electronic device, which includes: a processor and a memory; the memory stores instructions executable by the processor; when the processor is configured to execute the instructions, the electronic device implements the method of the first aspect above.

[0029] In a fourth aspect, the present application provides a chip system, which is applied to the base station site selection device; the chip system includes one or more interface circuits and one or more processors. The interface circuits and the processors are interconnected through lines; the interface circuits are used to receive signals from the memory of the base station site selection device and send signals to the processor of the base station site selection device, and the signals include software instructions stored in the memory. When the processor executes the software instructions, the electronic device executes the method of the first aspect above.

[0030] Fifth aspect, the present application provides a readable storage medium, which includes: software instructions; when the software instructions run on an electronic device, the electronic device is enabled to implement the method of the first aspect above.

[0031] Sixth aspect, the present application provides a computer program product, when the computer program product runs on an electronic device, the electronic device is enabled to execute the steps of the related method described in the first aspect above, so as to implement the method of the first aspect.

[0032] For the beneficial effects of the second to sixth aspects above, refer to the corresponding descriptions of the first aspect, and will not be elaborated here. Description of the Drawings

[0033] Figure 1 It is a schematic flowchart of a base station site selection method provided by the present application;

[0034] Figure 2 It is a schematic flowchart of another base station site selection method provided by the present application;

[0035] Figure 3 It is a schematic flowchart of yet another base station site selection method provided by the present application;

[0036] Figure 4 It is a schematic flowchart of yet another base station site selection method provided by the present application;

[0037] Figure 5 It is a schematic diagram of the composition of a base station site selection device provided by the present application;

[0038] Figure 6 It is a schematic diagram of the composition of an electronic device provided by the present application. Detailed Embodiments

[0039] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.

[0040] It should be noted that in the embodiments of the present application, words such as "exemplarily" or "for example" are used to represent examples, illustrations or explanations. Any embodiment or design solution described as "exemplarily" or "for example" in the embodiments of the present application should not be construed as being more preferred or having more advantages than other embodiments or design solutions. Exactly speaking, using words such as "exemplarily" or "for example" is intended to present relevant concepts in a specific manner.

[0041] To facilitate a clear description of the technical solutions of the embodiments of the present application, in the embodiments of the present application, terms such as "first" and "second" are used to distinguish identical or similar items with basically the same functions and roles. Those skilled in the art can understand that terms such as "first" and "second" do not limit the quantity and execution order.

[0042] With the rapid development of unmanned aerial vehicle (UAV) technology, its applications in the low-altitude field are becoming increasingly widespread, covering important fields such as logistics transportation, environmental monitoring, and disaster assessment. UAV flight requires stable communication and sensing support to ensure safe and efficient task completion. Therefore, the adaptability of flight paths and communication and sensing resources has become one of the key factors affecting flight performance and mission success rate. Traditional base station site selection methods ignore the complex relationship between communication and sensing resources and flight paths, resulting in problems such as possible communication interruptions and sensing blind spots during UAV flight. Therefore, it is necessary to comprehensively quantify and evaluate the adaptability of flight paths and communication and sensing resources to optimize base station site selection.

[0043] In terms of existing technical solutions, integrated sensing and communication (ISAC) technology has demonstrated dual advantages in the fields of wireless communication and environmental sensing. It realizes integrated fusion from multiple dimensions including hardware, spectrum, algorithms, and software, strongly supporting the development of the low-altitude economy. Especially in the UAV scenario, its key technologies include integrated waveform design, beamforming technology, UAV swarm cooperative interference management, and UAV swarm resource allocation and trajectory planning. At the same time, regarding the issue of communication base station site selection, a large amount of research has been carried out in the academic and industrial communities. Factors such as communication coverage, capacity, and quality need to be comprehensively considered. With the goal of the optimal cost or the largest coverage rate, it can be regarded as a coverage problem when constructing a model. For example, the basic model of the set coverage problem is widely used in traditional multi-base station site selection, and many scholars have carried out optimization research based on heuristic algorithms and so on.

[0044] However, in terms of integrated sensing and communication technology, in an environment with limited resources, it is still a difficult problem to allocate resources and plan trajectories for UAV swarms to achieve the optimal performance balance. In terms of communication environment modeling and communication quality evaluation, there is insufficient research on 5G complex communication scenarios and the estimation of communication path loss in low-altitude cellular mobile networks. Empirical models are mostly used and the errors are relatively large. When evaluating signal quality, the comprehensive influence of multiple factors is considered less, and it is difficult to give a comprehensive evaluation standard.

[0045] Based on this, the embodiments of the present application provide a base station site selection method, which makes full use of the signal information of existing base stations and the flight path information of unmanned aerial vehicles (UAVs) to evaluate candidate sites that have construction conditions but have not been built yet. On the one hand, by establishing refined evaluation criteria, the evaluation error is reduced. On the other hand, the optimal base station site selection scheme determined by comprehensively weighing the construction cost and signal coverage can not only ensure efficient communication services but also reasonably control costs. In summary, the base station site selection method provided by the present application can fill the gap in considering aerial communication in traditional base station site selection schemes and improve the service quality and efficiency of air transportation and mobile communication.

[0046] The base station site selection method provided by the embodiments of the present application can be executed by an electronic device.

[0047] Exemplarily, the electronic device can be a server. For example, a single server, or a server cluster composed of multiple servers. In some embodiments, the server cluster can also be a distributed cluster.

[0048] Exemplarily, the electronic device can be a terminal device. For example, a mobile phone, a tablet computer, a desktop computer, a laptop computer, a handheld computer, a notebook computer, an ultra-mobile personal computer (UMPC), a netbook, a cellular phone, a personal digital assistant (PDA), an augmented reality (AR) / virtual reality (VR) device, etc. The embodiments of the present application do not impose special restrictions on the specific form of the terminal device.

[0049] Figure 1 It is a schematic flow chart of a base station site selection method provided by the embodiments of the present application. As Figure 1 shown, the base station site selection method provided by the present application specifically includes the following steps:

[0050] S101. Obtain the signal information of existing base stations and the flight path information of UAVs.

[0051] In some embodiments, the signal information of existing base stations includes at least one of the following: signal strength, coverage range, signal frequency band.

[0052] In some embodiments, the flight path information of UAVs includes at least one of the following: take-off point, landing point, flight path, communication requirement, sensing frequency, sensing delay.

[0053] Exemplarily, the signal information of the existing base stations can be obtained in the following ways: testing with professional equipment or software, such as using a signal tester; contacting the local operator to obtain the signal information of the existing base stations.

[0054] Exemplarily, the route information of the unmanned aerial vehicles (UAVs) in the airspace can be collected in the following ways: obtained by monitoring with a radar system; obtained based on the UAV operation information provided by the cooperating UAV manufacturers.

[0055] S102. Determine at least one candidate site based on the signal information of the existing base stations and the route information of the UAVs.

[0056] S103. Determine a base station site selection plan based on at least one candidate site.

[0057] Among them, the evaluation index of the base station site selection plan is greater than or equal to the first threshold; the evaluation index is used to evaluate the construction cost and signal coverage rate.

[0058] The base station site selection method provided by the present invention matches and analyzes the flight routes of UAVs with communication and sensing resources, realizes the collaborative optimization of base station site selection and resource allocation, and significantly improves the utilization efficiency of low-altitude network resources.

[0059] In some embodiments, the route information of the UAVs includes the flight path of the UAVs. As Figure 2 shown, step S102 can be implemented as steps S1021 to S1024:

[0060] S1021. Divide the flight path of the UAVs into multiple flight segments.

[0061] Exemplarily, the low-altitude airspace of the city is divided into multiple small areas, and each area is called a signal grid; the flight path of the UAVs is divided according to the signal grid to form multiple small segments, and each small segment is called a flight segment.

[0062] Exemplarily, the size of the signal grid is determined according to the signal coverage range of the existing base stations and the accuracy of the flight path of the UAVs.

[0063] For example, if the signal strength of a single base station is stable within 300 meters in height, that is, the signal coverage range is 300 meters, the upper limit of the height is set to 300 meters when dividing the signal grid.

[0064] Exemplarily, the accuracy of the flight path of the UAVs is affected by the environmental complexity, that is, the higher the environmental complexity, the higher the accuracy requirement for the flight path of the UAVs. Therefore, in the vertical direction, it can be divided into two layers. For example, the first layer (0 - 30 meters) has a higher environmental complexity, and the signal grid can be divided smaller (such as 10 meters × 10 meters), and the second layer (30 - 300 meters) has a lower environmental complexity, and the signal grid can be appropriately enlarged (such as 50 meters × 50 meters).

[0065] Exemplarily, each signal grid is marked and monitored for its corresponding signal strength, signal-to-noise ratio, time delay, and route demand information.

[0066] It can be understood that this dynamic signal grid division mechanism improves the accuracy, efficiency, and adaptability of base station site selection evaluation by dividing the geographical space into dynamically adjustable grid cells and monitoring real-time signal parameters (such as signal strength, signal-to-noise ratio, time delay, environmental interference, etc.).

[0067] S1022. For each flight segment among multiple flight segments, determine the base station signal strength in the airspace where each flight segment is located based on the signal information of the existing base stations.

[0068] Exemplarily, determining the base station signal strength in the airspace where each flight segment is located based on the signal information of the existing base stations can be implemented as follows:

[0069] A1. Determine the signal strength of each existing base station in the airspace where each flight segment is located based on the signal information of the existing base stations.

[0070] A2. Calculate the average value of the signal strengths in the airspace where each flight segment is located as the base station signal strength in the airspace where each flight segment is located.

[0071] S1023. Based on the base station signal strength in the airspace where each flight segment is located and the minimum signal strength required by the unmanned aerial vehicle (UAV) on each flight segment, determine M target areas that do not meet the UAV communication requirements.

[0072] Wherein, one target area includes one flight segment; M is an integer greater than or equal to 1.

[0073] Exemplarily, if the base station signal strength in the airspace where a certain flight segment is located is lower than the minimum signal strength required by the UAV on that flight segment, then the signal grid where that flight segment is located is a target area.

[0074] Exemplarily, step S1023 further includes: marking the target areas and determining the signal strength difference (i.e., the difference between the base station signal strength in the airspace where the flight segment is located and the minimum signal strength required by the UAV on that flight segment).

[0075] S1024. Determine at least one candidate site according to the M target areas.

[0076] In some embodiments, step S1024 can be implemented as follows:

[0077] B1. Perform a clustering operation on the M target areas to obtain X clustering centers.

[0078] Among them, the clustering center is a point where the local density in the clustering cluster is greater than or equal to the second threshold, and / or the clustering center is a point where the clustering distance is greater than or equal to the third threshold; N is an integer greater than or equal to 1 and less than or equal to M.

[0079] Exemplarily, the M target regions can be represented as the set P = {P 1 , P 2 , …, P M}.

[0080] Exemplarily, step A1 can be implemented as the following steps A11 - A13:

[0081] B11. For any P i , P j ∈ P, i, j ∈ M, calculate the distance d and between them as d ij .

[0082] Exemplarily, d ij satisfies the following formula (I):

[0083]

[0084] B12. For any P i , calculate its local density ρ i and clustering distance σ i .

[0085] Exemplarily, ρ i satisfies the following formula (II):

[0086]

[0087] Among them, d ij is the distance that does not satisfy the distance between the grid center and other grid centers that do not satisfy, d c is the distance threshold.

[0088] Exemplarily, d c = d [λh] .

[0089] Among them, the array d = {d ij , 0 < i < j < M} and d ij in the array d is arranged in descending order, h is the total length of the array d, and λ is a coefficient less than 1.

[0090] Exemplarily, λ is 0.7.

[0091] Exemplarily, σ i satisfies the following formula (III):

[0092]

[0093] where d ij is the distance between the grid center that does not meet the requirements and other grid centers that do not meet the requirements.

[0094] B13. Select the local density ρ according to the decision diagram i greater than or equal to the second threshold and the clustering distance σ i greater than or equal to the third threshold as the clustering center.

[0095] Exemplarily, the horizontal axis of the decision diagram is the local density, the vertical axis is the clustering distance, and the clustering center is the point located in the upper right corner of the decision diagram.

[0096] B2. Determine at least one candidate site according to the positions of the X clustering centers.

[0097] In some embodiments, the distance between the candidate site and the X clustering centers is less than or equal to a preset distance.

[0098] Exemplarily, on the premise of knowing the position information of multiple sites available for construction, the sites that meet the following conditions are screened out from these buildable sites: the distance between the site and at least one of the given X clustering centers is less than or equal to the preset distance threshold, and the screened buildable sites that meet the conditions are determined as candidate sites.

[0099] The present invention proposes a base station site selection method based on clustering. This method is based on the decision diagram method of local density and clustering distance, and dynamically selects clustering centers from the set of grids where the signal does not meet the requirements, which can reduce the number of redundant base stations and thus reduce the cost of deploying base stations.

[0100] In some embodiments, as Figure 3 shown, step S103 can be implemented as steps S1031 to S1033:

[0101] S1031. Determine at least one candidate base station site selection scheme based on at least one candidate site.

[0102] In some embodiments, the candidate base station site selection scheme includes one or more selected sites; wherein, the selected site is any one of at least one candidate site.

[0103] In some embodiments, the site construction cost index is determined based on the following parameters: the number of selected base stations included in the base station site selection scheme, the number of at least one candidate base station.

[0104] In some embodiments, the coverage rate index is determined based on the following parameters: the number of target areas that can be covered by one or more selected base stations, the total number of target areas; wherein, the target area is the area where the base station signal strength of the existing base stations cannot meet the communication requirements of the unmanned aerial vehicle.

[0105] In some embodiments, step S1031 may be implemented as: using a genetic algorithm, based on at least one candidate site, determining at least one candidate base station site selection scheme.

[0106] S1032. For each candidate base station site selection scheme among the at least one candidate base station site selection scheme, calculate the evaluation index of each candidate base station site selection scheme respectively.

[0107] S1033. Based on the evaluation indexes of each candidate base station site selection scheme, determine the base station site selection scheme.

[0108] In some embodiments, the evaluation index is determined based on the weighted sum of the site construction cost index and the coverage rate index.

[0109] Exemplarily, the evaluation index satisfies the following formula (IV):

[0110] f = w 1 f 1 + w 2 f 2 Formula (IV)

[0111] Wherein, w 1 is the cost index weight, f 1 is the site construction cost index, w 2 is the coverage rate index weight, f 2 is the coverage rate index.

[0112] Exemplarily, the site construction cost index satisfies the following formula (V):

[0113]

[0114] Wherein, N is the number of candidate base stations, N 0 is the number of selected sites.

[0115] Exemplarily, the coverage rate index satisfies the following formula (VI):

[0116]

[0117] Wherein, M is the number of target areas, M 0 is the number of areas in the target areas covered by the selected sites.

[0118] Exemplarily, determining whether a target area is covered by a selected site can be determined based on the following steps:

[0119] C1. Define the coverage rule.

[0120] Exemplarily, the candidate site set is The target area set is Among them, N is the number of candidate sites, and M is the number of target areas.

[0121] The coverage range of the selected site can be expressed as a circle with the site coordinates (x i , y i , z i ) as the center and R as the radius. Therefore, the base station s i is represented as s i = (x i , y i , z i , R), i ∈ N.

[0122] The center point of the target area can be expressed as

[0123] Exemplarily, denote the event that the center point p j of the target area is covered by the base station s i as r ij , and the corresponding occurrence probability is P(r ij ), and P(r ij ) satisfies the following distribution rule:

[0124]

[0125] C2. Calculate the Euclidean distance d(s i , p j ) between the center point coordinates of the target area and the coordinates of the selected site.

[0126] Exemplarily, d(s i , p j ) satisfies the following formula (VII):

[0127]

[0128] C3. Based on the calculation results, obtain M 0 .

[0129] Exemplarily, if the Euclidean distance between the center point coordinates of the target area and the coordinates of any selected site is less than or equal to R, it is considered that the target area can be covered, and the value of M 0 is incremented by 1; if the Euclidean distances between the center point coordinates of the target area and the coordinates of all selected sites are greater than R, it is considered that the target area cannot be covered, and the value of M 0 does not increase.

[0130] The present invention proposes a base station site selection evaluation method based on multi-objective optimization, constructs a comprehensive evaluation model of coverage rate and construction cost through a weighted index method, and introduces a genetic algorithm to achieve global optimization of candidate solutions. Compared with single-index evaluation, this method has obvious advantages in terms of efficiency improvement, cost control, and solution robustness.

[0131] The base station site selection method of the present application will be introduced below with a specific embodiment.

[0132] As Figure 4 shown, the base station site selection method provided by the embodiment of the present application includes the following steps:

[0133] S201. Obtain the signal information of the existing base stations and the route information of the unmanned aerial vehicle (UAV).

[0134] S202. Divide the signal grid, segment the route of the UAV to obtain a plurality of navigation sections, and each navigation section is located within a signal grid.

[0135] S203. Calculate the average signal strength within each signal grid.

[0136] S204. Confirm the required signal strength threshold within each signal grid according to the navigation section of the UAV.

[0137] S205. Determine whether the average signal strength within each signal grid meets the required signal strength threshold of the UAV.

[0138] Specifically, if the average signal strength within the signal grid does not meet the required signal strength threshold of the UAV, it is marked as a signal non - meeting grid, and the set of the center points of the signal non - meeting grids can be expressed as P = {P 1 , P 2 , …, P M}, and then step S206 is executed; if all meet the required signal strength threshold of the UAV, step S208 is executed.

[0139] S206. Cluster the signal non - meeting grids.

[0140] Specifically, for the center point P i of the signal non - meeting grid, calculate the local density and the clustering distance to obtain the corresponding (ρ i , σ i ) combination, select the center point of the signal non - meeting grid with relatively large local density and clustering distance as the clustering center, and divide the remaining center points of the signal non - meeting grids into the cluster where the nearest clustering center is located to complete the clustering process.

[0141] S207. Use the site selection algorithm to determine the base station site.

[0142] Specifically, select the sites closer to the clustering center as candidate sites, and all candidate sites form a candidate site set; evaluate each candidate base station site selection scheme in the set; generate new candidate base station site selection schemes by combining mutation, evolution, and selection operations in the genetic algorithm and evaluate them; finally, select the candidate base station site selection scheme with the highest evaluation index value as the optimal base station site selection scheme.

[0143] Exemplarily, the pseudocode of the above site selection algorithm is shown in Table 1:

[0144] Table 1 Pseudocode of the Base Station Site Selection Method

[0145]

[0146]

[0147] S208. Generate an evaluation report and a site selection scheme.

[0148] Specifically, the evaluation report and the site selection scheme include the existing signal quality situation, the grid areas that do not meet the signal requirements, the clustering results, the new base station locations, the estimated construction costs, etc.

[0149] Exemplarily, the signal quality situation can be presented by a signal quality heat map.

[0150] The above mainly introduces the solution of the embodiments of the present disclosure from the perspective of the method. It can be understood that in order to implement the above functions, the base station site selection device includes at least one of the corresponding hardware structures and software modules for executing each function. Those skilled in the art should easily realize that, combined with the units and algorithm steps of each example described in the embodiments disclosed herein, the embodiments of the present disclosure can be implemented in the form of hardware or a combination of hardware and computer software. Whether a certain function is executed in the way of hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the embodiments of the present disclosure.

[0151] The embodiments of the present disclosure can divide the functional modules of the base station site selection device according to the above method embodiments. For example, each functional module can be divided corresponding to each function, or two or more functions can be integrated into one functional module. The above integrated module can be implemented in the form of hardware or software. It should be noted that the division of modules in the embodiments of the present disclosure is illustrative, only a logical function division, and there can be other division methods in actual implementation. The following takes the example of dividing each functional module corresponding to each function for illustration.

[0152] For example,Figure 5 This is a schematic diagram of the composition of a base station site selection device provided by an embodiment of the present application. As Figure 5 shown, the base station site selection device 400 includes: an acquisition module 401 and a processing module 402. Among them, the acquisition module 401 is used to: acquire the signal information of existing base stations and the route information of the drone; the processing module 402 is used to: determine at least one candidate site based on the signal information of existing base stations and the route information of the drone; determine a base station site selection plan based on at least one candidate site; wherein, the evaluation index of the base station site selection plan is greater than or equal to a first threshold; the evaluation index is used to evaluate the construction cost and signal coverage.

[0153] A possible implementation manner is that the route information of the drone includes the flight path of the drone; the processing module 402 is specifically used to: divide the flight path of the drone into multiple flight segments; for each flight segment among the multiple flight segments, determine the base station signal strength in the airspace where each flight segment is located based on the signal information of existing base stations; based on the base station signal strength in the airspace where each flight segment is located and the minimum signal strength required by the drone on each flight segment, determine M target areas that do not meet the communication requirements of the drone; one target area includes one flight segment; M is an integer greater than or equal to 1; determine at least one candidate site according to the M target areas.

[0154] Another possible implementation manner is that the processing module 402 is specifically used to: perform a clustering operation on the M target areas to obtain X clustering centers; wherein, the clustering center is a point where the local density in the clustering cluster is greater than or equal to a second threshold, and / or, the clustering center is a point where the clustering distance is greater than or equal to a third threshold; N is an integer greater than or equal to 1 and less than or equal to M; determine at least one candidate site according to the positions of the X clustering centers.

[0155] Another possible implementation manner is that the distance between the candidate site and the X clustering centers is less than or equal to a preset distance.

[0156] Another possible implementation manner is that the processing module 402 is specifically used to: determine at least one candidate base station site selection plan based on at least one candidate site; the candidate base station site selection plan includes one or more selected sites; wherein, the selected site is any one of at least one candidate site; for each candidate base station site selection plan among at least one candidate base station site selection plan, calculate the evaluation index of each candidate base station site selection plan respectively; determine the base station site selection plan based on the evaluation index of each candidate base station site selection plan.

[0157] Another possible implementation manner is that the processing module 402 is specifically used to: use a genetic algorithm to determine at least one candidate base station site selection plan based on at least one candidate site.

[0158] Another possible implementation manner is that the evaluation index is determined based on the weighted sum of the site construction cost index and the coverage rate index.

[0159] Another possible implementation manner is that the base station site selection scheme includes one or more selected base stations; the site construction cost index is determined based on the following parameters: the number of selected base stations included in the base station site selection scheme, and the number of at least one candidate base station.

[0160] Another possible implementation manner is that the base station site selection scheme includes one or more selected base stations; the coverage rate index is determined based on the following parameters: the number of target areas that can be covered by one or more selected base stations, and the total number of target areas; wherein, the target area is an area where the base station signal strength of the existing base stations cannot meet the communication requirements of the unmanned aerial vehicle.

[0161] Another possible implementation manner is that the signal information of the existing base stations includes at least one of the following: signal strength, coverage range, and signal frequency band.

[0162] Another possible implementation manner is that the route information of the unmanned aerial vehicle includes at least one of the following: take-off point, landing point, flight path, communication requirement, sensing frequency, and sensing delay.

[0163] In the case of implementing the functions of the above integrated modules in the form of hardware, the embodiments of the present disclosure provide a possible structure of the electronic device involved in the above embodiments. As Figure 6 shown, the electronic device 500 includes: a processor 502, and a bus 504. Optionally, the electronic device 500 may further include a memory 501; optionally, the electronic device 500 may further include a communication interface 503.

[0164] The processor 502 may be used to implement or execute various exemplary logical blocks, modules, and circuits described in conjunction with the embodiments of the present application. The processor 502 may be a central processing unit, a general-purpose processor, a digital signal processor, an application-specific integrated circuit, a field-programmable gate array, or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It may implement or execute various exemplary logical blocks, modules, and circuits described in conjunction with the embodiments of the present disclosure. The processor 502 may also be a combination of computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0165] The communication interface 503 is used to connect to other devices through a communication network. The communication network may be an Ethernet, a radio access network, a wireless local area network (WLAN), etc.

[0166] The memory 501 can be a read-only memory (ROM) or other types of static storage devices that can store static information and instructions, a random access memory (RAM) or other types of dynamic storage devices that can store information and instructions, or can also be an electrically erasable programmable read-only memory (EEPROM), a magnetic disk storage medium or other magnetic storage devices, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto.

[0167] As a possible implementation, the memory 501 can exist independently of the processor 502. The memory 501 can be connected to the processor 502 through the bus 504 for storing instructions or program code. When the processor 502 calls and executes the instructions or program code stored in the memory 501, the base station site selection method provided in the embodiments of the present application can be implemented. In another possible implementation, the memory 501 can also be integrated with the processor 502.

[0168] The bus 504 can be an extended industry standard architecture (EISA) bus, etc. The bus 504 can be divided into an address bus, a data bus, a control bus, etc. For the sake of convenience of representation, Figure 6 only a thick line is used to represent it in the figure, but it does not mean that there is only one bus or one type of bus.

[0169] In an exemplary embodiment, the embodiments of the present application also provide a readable storage medium, on which program instructions are stored; when the program instructions are executed by an electronic device, the electronic device is enabled to implement the method described in the foregoing embodiments. The readable storage medium can be a non-transitory readable storage medium. For example, the non-transitory readable storage medium can be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, and an optical data storage device, etc.

[0170] In an exemplary embodiment, the embodiments of the present application also provide a computer program product. When the computer program product runs on an electronic device, the electronic device is enabled to execute the above-related method steps to implement the base station site selection method in the above embodiments.

[0171] The above are only the specific implementation manners of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions within the technical scope disclosed in the present application should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A base station site selection method, characterized in that: The method comprises: Obtain signal information of established base stations and route information of drones; Determine at least one candidate site based on the signal information of the established base station and the route information of the UAV; Based on the at least one candidate site, a base station site selection plan is determined; wherein an evaluation index of the base station site selection plan is greater than or equal to a first threshold; and the evaluation index is used to evaluate site construction cost and signal coverage.

2. The method according to claim 1, characterized in that: The route information of the UAV includes a flight path of the UAV; and determining at least one candidate site based on the signal information of the established base station and the route information of the UAV includes: Dividing the flight path of the drone into a plurality of flight segments; For each of the multiple flight segments, determine the base station signal strength in the airspace where each flight segment is located based on the signal information of the established base station; Based on the base station signal strength in the airspace where each flight segment is located and the minimum signal strength required by the UAV on each flight segment, M target areas that do not meet the communication requirements of the UAV are determined; one target area includes one flight segment; M is an integer greater than or equal to 1; The at least one candidate site is determined according to the M target areas.

3. The method according to claim 2, characterized in that The determining, according to the M target areas, the at least one candidate site includes: Performing a clustering operation on the M target areas to obtain N cluster centers; wherein the cluster centers are points in the cluster clusters whose local density is greater than or equal to a second threshold, and / or the cluster centers are points whose cluster distance is greater than or equal to a third threshold; and N is an integer greater than or equal to 1 and less than or equal to M; The at least one candidate site is determined according to the positions of the N cluster centers.

4. The method according to claim 3, characterized in that The distance between the candidate site and the N cluster centers is less than or equal to a preset distance.

5. The method according to claim 1, characterized in that: The determining of a base station site selection scheme based on the at least one candidate site includes: Based on the at least one candidate site, determine at least one candidate base station site selection scheme; the candidate base station site selection scheme includes one or more selected sites; wherein the selected site is any one of the at least one candidate site; For each candidate base station site selection scheme in the at least one candidate base station site selection scheme, respectively calculating an evaluation index of each candidate base station site selection scheme; The base station site selection scheme is determined based on the evaluation index of each candidate base station site selection scheme.

6. The method according to claim 5, characterized in that The determining, based on the at least one candidate site, at least one candidate base station site selection scheme comprises: A genetic algorithm is used to determine a site selection scheme for the at least one candidate base station based on the at least one candidate site.

7. The method according to claim 1, characterized in that The evaluation index is determined based on the weighted sum of the site construction cost index and the coverage index.

8. The method according to claim 7, characterized in that The base station site selection plan includes one or more selected base stations; The site construction cost indicator is determined based on the following parameters: the number of selected base stations included in the base station site selection plan and the number of the at least one candidate base station.

9. The method according to claim 7, characterized in that: The base station site selection plan includes one or more selected base stations; The coverage index is determined based on the following parameters: the number of target areas that can be covered by the one or more selected base stations and the total number of target areas; wherein the target area is an area where the base station signal strength of the established base station cannot meet the communication needs of the drone.

10. The method according to claim 1, characterized in that The signal information of the established base station includes at least one of the following: Signal strength, coverage, and signal frequency band.

11. The method according to claim 1, characterized in that: The route information of the UAV includes at least one of the following: Take-off point, landing point, flight path, communication requirements, perception frequency, and perception delay.

12. An electronic device, characterized in that: The electronic device comprises: a processor and a memory; The memory stores instructions executable by the processor; When the processor is configured to execute the instructions, the electronic device implements the method according to any one of claims 1 to 11.

13. A readable storage medium, characterized in that: The readable storage medium includes: software instructions; When the software instructions are executed in an electronic device, the electronic device implements the method according to any one of claims 1 to 11.

14. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is run on an electronic device, the electronic device is enabled to execute the method according to any one of claims 1 to 11.

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