Efficient Coronavirus Herd Immunity Optimizer for the UAV Base Stations Placement Problem

ABSTRACT

This paper proposes an improved version of the Coronavirus Herd Immunity Optimizer (CHIO) algorithm, called RFDB-CHIO, for solving the Unmanned Aerial vehicle carried Base Stations (UAV-BSs) placement problem in 5G networks. The proposed RFDB-CHIO is based on the integration of the Roulette Fitness Distance Balance (RFDB) selection mechanism into the original CHIO algorithm. RFDB-CHIO is validated in terms of user coverage and mean coverage radius under 16 scenarios with different numbers of drones and users. The simulation results demonstrated that RFDB-CHIO obtained better results than CHIO, Whale optimization algorithm (WOA), and Grey Wolf Optimization (GWO) algorithms. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.