2018/05/26 by Aaron M. French, French, Aaron, Mohammad Mozaffari +5
Engineering · Computer Science · #UAV Applications and Optimization #Distributed Control Multi-Agent Systems #Opportunistic and Delay-Tolerant Networks
paper · pdf · doi:10.48550/arxiv.1805.10424
In this paper, a software-based simulator for the deployment of base\nstation-equipped unmanned aerial vehicles (UAVs) in a cellular network is\nproposed. To this end, the Google Earth Engine platform and its included image\nprocessing functions are used to collect geospatial data and to identify\nobstacles that can disrupt the line-of-sight (LoS) communications between UAVs\nand ground users. Given such geographical information, three environment-aware\noptimal UAV deployment scenarios are investigated using the developed\nsimulator. In the first scenario, the positions of UAVs are optimized such that\nthe number of ground users covered by UAVs is maximized. In the second\nscenario, the minimum number of UAVs needed to provide full coverage for all\nground users is determined. Finally, given the load requirements of the ground\nusers, the total flight time (i.e., energy) that the UAVs need to completely\nserve the ground users is minimized. Simulation results using a real area of\nthe Virginia Tech campus show that the proposed environment-aware drone\ndeployment framework with Google Earth input significantly enhances the network\nperformance in terms of coverage and energy consumption, compared to classical\ndeployment approaches that do not exploit geographical information. In\nparticular, the results show that the proposed approach yields a coverage\nenhancement by a factor of 2, and a 65% improvement in energy-efficiency. The\nresults have also shown the existence of an optimal number of drones that leads\nto a maximum wireless coverage performance.\n