4,201 research outputs found
Efficient Deployment of Multiple Unmanned Aerial Vehicles for Optimal Wireless Coverage
In this paper, the efficient deployment of multiple unmanned aerial vehicles
(UAVs) with directional antennas acting as wireless base stations that provide
coverage for ground users is analyzed. First, the downlink coverage probability
for UAVs as a function of the altitude and the antenna gain is derived. Next,
using circle packing theory, the three-dimensional locations of the UAVs is
determined in a way that the total coverage area is maximized while maximizing
the coverage lifetime of the UAVs. Our results show that, in order to mitigate
interference, the altitude of the UAVs must be properly adjusted based on the
beamwidth of the directional antenna as well as coverage requirements.
Furthermore, the minimum number of UAVs needed to guarantee a target coverage
probability for a given geographical area is determined. Numerical results
evaluate the various tradeoffs involved in various UAV deployment scenarios.Comment: Accepted in the IEEE Communications Letter
Deployment Strategies of Multiple Aerial BSs for User Coverage and Power Efficiency Maximization
Unmanned aerial vehicle (UAV) based aerial base stations (BSs) can provide
rapid communication services to ground users and are thus promising for future
communication systems. In this paper, we consider a scenario where no
functional terrestrial BSs are available and the aim is deploying multiple
aerial BSs to cover a maximum number of users within a certain target area. To
this end, we first propose a naive successive deployment method, which converts
the non-convex constraints in the involved optimization into a combination of
linear constraints through geometrical relaxation. Then we investigate a
deployment method based on K-means clustering. The method divides the target
area into K convex subareas, where within each subarea, a mixed integer
non-linear problem (MINLP) is solved. An iterative power efficient technique is
further proposed to improve coverage probability with reduced power. Finally,
we propose a robust technique for compensating the loss of coverage probability
in the existence of inaccurate user location information (ULI). Our simulation
results show that, the proposed techniques achieve an up to 30% higher coverage
probability when users are not distributed uniformly. In addition, the proposed
simultaneous deployment techniques, especially the one using iterative
algorithm improve power-efficiency by up to 15% compared to the benchmark
circle packing theory
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