A Novel Network Planning Algorithm of Three-Dimensional Dense Networks Based on Adaptive Variable-Length Particle Swarm Optimization

Small base stations (SBSs) deployed in hotspots are formed into dense networks to improve network coverage and system capacity. However, the deployment of SBSs becomes a great challenge owing to the high density of small cells and the uneven distribution of traffic. In this paper, we propose a three-dimensional (3D) dense network planning method to deploy SBSs in hotspots. First, considering the propagation characteristics of 3D indoor deployment environment and the hybrid distribution of traffic, we estimate the network dimension to obtain the approximate number of SBSs that need to cover the entire area and meet the rate requirements of all users in a given space. Then, we formulate network planning as an optimization problem with the objective of minimizing the number of SBSs while satisfying both coverage and capacity constraints. Finally, in order to solve the optimization problem, we propose an adaptive variable-length particle swarm optimization (AVLPSO) algorithm. Simulation results indicate that compared with the traditional algorithms, the proposed algorithm can significantly achieve higher service ratio and reduce the costs of deployment.