Soft computing methods for WiMax Network Planning on 3D Geographical Information Systems

In this paper, we present an application of soft computing methods for the problem of WiMax Network Planning on 3D Geographical Information Systems (3D GIS) that optimizes both performance of the network (Coverage and Quality-of-Service) and investment costs (the number of base stations and sectors). A pre-processing procedure using latest results of parallel Random Forest classification algorithm to determine valid positions of base stations on a terrain of 3D GIS is proposed. Based upon those positions, we design a generalized mathematical model taking into account 3D obstacles in path loss calculation process. In order to generate optimal solutions of the model, a hybrid algorithm between greedy BTP and improved Particle Swarm Optimization incorporated with parallel computing is presented. Experimental validation of the proposed method in comparison with other relevant ones is performed.