Research on Location Decision Optimization of Communication Station Based on Simulated Annealing Particle Swarm Optimization

Abstract

With the fast expansion of communication technology, the location of base stations becomes more and more complex. In this paper, aiming at the existing problems of base station location, the address and type of base station are planned scientifically and the regional clustering is carried out. We solve the location problem of base stations with innovative optimization algorithms. In order to make the newly-built base station meet 90% of the total traffic of weak coverage points, we set up a biobjective programming model with cost and traffic as the objective function, and constraints such as the threshold between base stations and the coverage range of base stations. Secondly, the effective coverage area of the base station and the changes in the Angle between the main direction of the sector are simplified, which is equivalent to six kinds of circular coverage, and the new coverage area of the base station is calculated. Then, according to the new coverage area, the objective function and constraints are changed to reconstruct the biobjective programming model, and the biobjective programming function is transformed into a single objective programming function.Monte Carlo simulation is used to obtain the initial solution of the objective function.