UAV base-station design method and optimization for urban environment communication with 5G cellular network

Abstract

During unexpected or temporary events, base transceiver stations (BTSs), also known as base stations (BSs), may be unable to fully meet the flexibility and resilience requirements of upcoming cellular networks. A promising solution to this issue is to serve the cellular networks with low-altitude unmanned aerial vehicle base stations (UAV-BSs), which can assist terrestrial stations in increasing networks’ capacity and coverage. This paper proposes a network planning method for the fast deployment of fifth-generation (5G) cellular networks using a metaheuristic algorithm. This approach aims to determine the minimum number of UAV-BSs that can cover an area the size of a stadium while considering cell capacity, coverage constraints, the system’s spectral efficiency, and the battery life of the UAVs being utilized. We have formulated an optimization problem approach to capture the practical aspects and satisfy the above conditions simultaneously. We have detailed the implementation of a metaheuristic algorithm based on particle swarm optimization (PSO) that finds optimal locations for the UAV-BSs that satisfy all the stadium constraints among various subareas with different user densities. This approach was compared to a genetic algorithm (GA) using the same simulation parameters during performance evaluation. The simulation results indicate that the proposed approach effectively finds the minimum number of UAV-BSs and their 3-D placement so that all users are served based on their traffic requirements. The results also indicate that the quality-of-service (QoS) targets desired for the network are reached in each scenario.