Mobile Communication Network Site Planning Research Based on Simulated Annealing Algorithm Optimization Model

Abstract

With the development of 5G network, it becomes a hot topic to reasonably plan the siting of communication base stations in the weak coverage area of 5G network. In this paper, we take improving the coverage of service volume and reducing the cost of building base stations in the weak coverage area as the target of siting, and select base station sites among 2500×2500 points in a given area under ideal conditions and actual conditions, respectively, and use the less time-complex clustering method to cluster all weak coverage points. In order to improve the feasibility of the model in practical applications, we try to develop the base station site selection scheme that benefits the most for the 5G construction company by setting up a multi-objective planning model based on multiple constraints. On this basis, the conditions of the multi-objective planning model are changed and optimized to obtain a new multi-objective planning model based on the requirement that the communication coverage of base stations is fan-shaped in real life, and the simulated annealing optimization algorithm based on greedy thinking is used to optimize and solve the listed multi-objective planning model to obtain a new station site plan.