Improved Particle Swarm Optimization Algorithm And Its Application And Research In Base Station Optimization Location

With the advent of4G era, the three operators have access to TD-LTE license. It needs to build a lot of new TD-LTE base stations, base station optimization siting such issues become an important research. In order to use the smallest base station construction costs, to get the best quality of service of communication, some scholars have proposed the use of automatic planning algorithm to obtain the optimal design. However, the base station siting considerations, such as optimization of traffic areas, coverage and cost issues, the current optimization search algorithm to solve it is not a good candidate for a large number of solutions, the optimization process is complex, multimodal search space and other problems.PSO algorithm originated in the study of group behavior of birds, is a nonlinear function for continuous optimization of artificial intelligence algorithms, as a swarm intelligence-based optimization algorithm, PSO algorithm can be used to solve a variety of non-linear, non-differentiable and multimodal complex optimization problems. But there PSO algorithm easily fall into local minima, late slow convergence and poor accuracy flaws. For PSO algorithm search accuracy is not high, easy to fall into local minimum deficiencies Overall, this paper presents an improved PSO algorithm, and applied TD-LTE base station siting in optimization. The main work and innovation of this paper is as follows:(1) This paper presents an improved PSO algorithm easy to implement, the effect is obvious. Improved mainly two aspects:on the one hand, particle swarm particle with a weighted average of individual extreme alternative type of particle velocity update individual extreme; hand, by reference to the two non-linear decreasing function of the inertia weight adjustments. So that the particles can be easily moved to the optimal position faster, stronger global optimization capability.(2) Were used in this article Sphere, Griewank, Rastrigrin and Ackley function simulation tests on four benchmark functions through simulation to verify the convergence of the global optimization algorithm to improve the ability of this article.(3) In this paper, improved PSO algorithm is applied to a city in the Pearl River Delta TD-LTE base station siting in the optimization. The simulation results and applications show that the improved PSO algorithm has higher convergence speed and global optimization capability, this paper improved PSO algorithm can provide a reasonable base station deployment scenarios.(4) ArcGIS platform based on PSO algorithm is applied to the improved TD-LTE base stations to optimize the site in order to show a more intuitive screen optimized distribution station after deployment.