A 3D Placement of Unmanned Aerial Vehicle Base Station Based on Multi-Population Genetic Algorithm for Maximizing Users with Different QoS Requirements

Unmanned aerial vehicle mounted base stations (UAV - BSs) can provide wireless cellular service to ground users in a variety of scenarios. The efficient deployment of such UAV-BSs while optimizing the coverage area is one of the key challenges. This work investigates the 3D UAV -BS placement that maximizes the numbers of covered users with different Quality-of-Service (QoS) requirements using the minimum power. In this paper, we first highlight the properties of the 3D placement problem and we model the problem as a multiple concentric circles placement problem with the objective of maximizing the numbers of covered users. We decouple the UAV-BS deployment problem in the vertical and horizontal dimensions without any loss of optimality, after some mathematical manipulations, we formulate a Mixed Integer Second Order Cone Problem (MISOCP) and propose an improved Multi-Population Genetic Algorithm (MPGA) for horizontal dimensions placement problem. Numerical simulations are presented showing that improved MPGA can obtain better performance compare to Standard Genetic Algorithm (SGA) in this problem.