Research on Location Selection Model of Base Station based on Improved Genetic Algorithm

Abstract

With the increase in the number of users accessing the 5G network in the future, how to choose the location of 5G base stations to ensure effective network coverage of the service area, so as to provide reliable communication and transmission services, is a key issue to be considered. By establishing an improved genetic algorithm model, the site planning problem is solved. According to the circular coverage area of the base station, the coverage requirement and the minimum cost optimization goal are completed. First, denoising according to business volume, and finally get 35,915 weak coverage points. The sum of the cost of setting up macro base stations and micro base stations is the optimization goal, and the coverage rate of the weak coverage point is more than 90%, is set as the constraint condition. At the same time, the lethal factor is set in the selection process, and the individuals who do not meet the threshold conditions of the original base station are deleted. The improved operator is adopted in the crossover link and mutation link, which speeds up the running speed of the algorithm and ensures the population diversity and the accuracy of the results. Finally, 689 macro base stations and 269 micro base stations are established, with a coverage rate of 93.51% and an optimal cost solution of 7159. By visualizing the results on the coordinate map, it can be clearly seen that most of the weak coverage points have been covered, which shows that the improved genetic algorithm shows fast convergence speed and good optimal value, and verifies the effectiveness of the model.