Toward the Energy-Saving Optimization of WLAN Deployment in Real 3-D Environment: A Hybrid Swarm Intelligent Method
Peng Liu, Qian Hu, Kezhong Jin, Guanding Yu, Zhenzhou Tang
Abstract
The deployment of access points (APs) imposes a great impact on the performance of wireless local area networks (WLANs). Although there have been plenty of works on the optimal AP deployment (OAD), however, the issue remains open that how to deploy APs energy-savingly in 3-D environments while considering some practical demands. Therefore, this article investigates the OAD with the objective of minimizing the total AP transmission power while guaranteeing the effective coverage by jointly optimizing the transmission power and location of each AP. Different from existing works, our article fully considers not only real 3-D environments with various obstacles but also the differentiated coverage demand and the restrictions on AP locations. To solve this NP-hard optimization problem, this article first proposes a novel hybrid swarm intelligence optimization algorithm, named PSO-Lévy-DFOA. The computational results on 16 benchmark functions and comprehensive comparisons with other algorithms demonstrate the superior global convergence performance of PSO-Lévy-DFOA. The proposed PSO-Lévy-DFOA-based OAD method is then applied to WLAN planning in a two-story building. It has been shown that the total AP transmission power can be considerably reduced compared to the current deployment while still fulfilling the effective coverage.