Optimal placement of mobile antenna in an urban area using evolutionary multiobjective optimization


The optimized placements of mobile antennas (MA) in an existing high traffic urban area are identified using evolutionary multiobjective optimization algorithms (EMOA). The design parameters such as (x, y) coordinates, transmitting power, height, and tilt are considered. The objectives are coverage and cost where as the inequality constraints are handover, traffic demand, and overlap. Modified NSGA-II (MNSGA-II) is preferred to improve the non dominated solutions. A detailed study is performed about physical and geometrical structure of propagation environment. Four different case studies are performed. The simulation results reveal that Hata-Okumura path loss model is more suited. MNSGA-II is able to determine optimal MA parameters for multiobjective case studies.