Deployable Base Stations for Mission Critical Communications

Abstract: Uninterrupted network connectivity is vital for real-time and mission-critical communication networks. The failure of Base Stations due to unforeseen circumstances such as natural disasters or emergencies can affect the coverage and capacity provided by terrestrial communication networks. The use of Unmanned Aerial Vehicles (UAVs) or drones in cellular networks is an upcoming area of research interest in 5G where the public sector and the communication service providers are fervently discussing it. The drones can be rapidly deployed to bridge the gaps in coverage or capacity of the network due to unforeseen circumstances. This thesis explores drone base stations' use for a simple hexagonal cell deployment scenario where the deployable base stations replace two failed macro base stations to improve the mean network capacity. Simulations show that the introduction of the deployable base stations indeed helps improve mean network capacity in case of one or multiple macro base station fail. The Genetic Algorithm is used to achieve Pareto optimality between downlink and uplink capacity of the simulated network. The simulation results show that introducing deployable nodes in a network can improve the network's capacity while also giving near-optimal transmit power values.