Mechanical Energy Minimization UAV-Mounted Base Station Path Plan for Public Safety Communication

Abstract

The increasing number of situations in which wireless communication networks are damaged due to natural disasters has motivated researchers to utilize unmanned aerial vehicles (UAVs) to deliver fast and efficacious backup communication in post-disaster scenarios. UAVs are a logical option for public safety cellular networks due to their key features such as agility, mobility, flexibility, and adaptable altitude. There are exciting situations; for example, California and Turkey wildfires and UAVs can be integral to cellular networks beyond 5G as the technology rises and new efficient Scenarios are developed. In this paper, we investigate the use of a powered Feeder UAV to charge the batteries of UAVBSs, after which a UAV Relay can deliver backhaul connectivity to one of the UAVBSs, all UAVBSs can have hybrid FSO/RF link connections, and all UAVBSs has been designed within a disaster zone providing network coverage to users based on the latency-free communication. We compare a path planning design that uses ACO and Metropolis-hasting algorithms to find the optimal trajectory with the least propulsion energy required for the Feeder UAV to visit all UAVBSs, UAV relay, and return to a docking station that serves as a physical location where the Feeder UAV charges. In calculating the energy consumption, we consider both the hovering and the hardware of the Feeder UAV. According to simulation results, our proposed ACO design outperforms the proposed Metropolis-hasting design and the approach in the literature by up to 12 % and 48 %, respectively.