Particle swarm optimization for base station placement in mobile communication

The tremendous growth in the demand for mobile services results in an explosion in base station (BS) density and network complexity, making the conventional manual planning processes highly inefficient. In this paper, we give some novel adaptation to the recent bio-inspired optimization approach, Particle Swarm Optimization (PSO), to form a suitable algorithm for the base station placement problem. Considering the two most important factors simultaneously, coverage and economy efficiency, we can get a Pareto optimal set by using the Divided Range Multiobjective Particle Swarm Optimization (DRMPSO) which is performed in distributed computing. The Pareto optimal set is a set of solutions which are optimal with respect to constrained conditions and non-inferior to each other. The simulation results show that the proposed approach is efficient and effective, especially for large-scale network design.