  In this paper, a software-based simulator for the deployment of base
station-equipped unmanned aerial vehicles (UAVs) in a cellular network is
proposed. To this end, the Google Earth Engine platform and its included image
processing functions are used to collect geospatial data and to identify
obstacles that can disrupt the line-of-sight (LoS) communications between UAVs
and ground users. Given such geographical information, three environment-aware
optimal UAV deployment scenarios are investigated using the developed
simulator. In the first scenario, the positions of UAVs are optimized such that
the number of ground users covered by UAVs is maximized. In the second
scenario, the minimum number of UAVs needed to provide full coverage for all
ground users is determined. Finally, given the load requirements of the ground
users, the total flight time (i.e., energy) that the UAVs need to completely
serve the ground users is minimized. Simulation results using a real area of
the Virginia Tech campus show that the proposed environment-aware drone
deployment framework with Google Earth input significantly enhances the network
performance in terms of coverage and energy consumption, compared to classical
deployment approaches that do not exploit geographical information. In
particular, the results show that the proposed approach yields a coverage
enhancement by a factor of 2, and a 65% improvement in energy-efficiency. The
results have also shown the existence of an optimal number of drones that leads
to a maximum wireless coverage performance.
