Cost optimization unmanned aerial vehicle base station deployment method based on an improved genetic algorithm

Abstract

The invention discloses a cost optimization unmanned aerial vehicle base station deployment method based on an improved genetic algorithm, and mainly solves the problem that the unmanned aerial vehicle base station deployment cost is difficult to optimize in the prior art. The realization method comprises the following steps: 1) establishing a ground wireless communication coverage model of the unmanned aerial vehicle base station; 2) calculating the maximum coverage radius and the optimal hovering height of the unmanned aerial vehicle base station in the unmanned aerial vehicle base station ground wireless communication coverage model scene; 3) deploying the unmanned aerial vehicle base stations at the optimal hovering height, enabling the deployment problem to be reduced from three-dimensional dimensionality to a two-dimensional plane, establishing an unmanned aerial vehicle base station deployment optimization model taking unmanned aerial vehicle base station deployment number optimization as a target, and solving the model to obtain an optimal chromosome; 4) converting the optimal chromosome into a corresponding unmanned aerial vehicle base station coordinate set to obtain an optimal unmanned aerial vehicle base station deployment scheme, reducing the complexity of the deployment problem, improving the solution accuracy, and being applicable to communication network deployment planning, temporary communication network construction and disaster area emergency communication.

Description

technical field [0001] The invention belongs to the field of communication technology, and in particular relates to a cost-optimized UAV base station deployment method, which can be used for communication network deployment planning, temporary communication network construction, and emergency communication in disaster areas. Background technique [0002] With the rapid development of UAVs in recent years, UAV low-altitude platforms equipped with base stations have attracted increasing attention. Due to its advantages of high mobility, flexible deployment, and lower cost than other communication facilities, the communication network deployment of UAV base stations has increasingly become a research hotspot in the field of communication. The number and location of mobile base stations are of great significance. [0003] The earliest development of drones originated from military needs. Compared with manned aircraft, drones have been widely used in national ecological environm...

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Problems solved by technology

[0008] The purpose of the present invention is to address the deficiencies of the above-mentioned prior art, and propose a cost-optimized UAV base station deployment method based on an improved genetic algorithm to solve the problem that the prior art is difficult to optimize the deployment cost of the UAV base station. The optimal deployment scheme under the condition of meeting the communication needs of users in a given target area

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