Coverage Optimization for UAV Base Stations using Simulated Annealing
Nicholas Hao Zheng Lim, Ying Loong Lee, Mau‐Luen Tham, Yoong Choon Chang, Allyson Gek Hong Sim, Donghong Qin
Abstract
Conventional terrestrial base stations (BSs) are prone to natural disasters and they are not flexible to cater to the sudden surge in the number of users in various locations within their coverage area. Therefore, unmanned aerial vehicle (UAV)-carried BSs (UAV-BSs) have been proposed to overcome this problem, thanks to their advantages in flexible UAV-BS placement and simple deployment. However, the positioning of the UAV-BSs for maximum coverage with satisfactory received data rate is a challenging task. Therefore, the objective of this study is to develop a UAV-BS placement scheme which maximizes the communication coverage. To this end, we formulate the UAVBS placement optimization problem to maximize the coverage of multiple UAV-BSs in a given area, while taking into account the collision avoidance between the UAV-BSs. Then, an artificial intelligence technique known as simulated annealing is used to develop an algorithm to solve the optimization problem. Simulation results have shown that the proposed algorithm outperforms static UAV-BS placement in terms of quality of service and throughput.