Distributed UAV placement optimization for cooperative line-of-sight MIMO communications

S Hanna, H Yan, D Cabric - ICASSP 2019-2019 IEEE …, 2019 - ieeexplore.ieee.org
ICASSP 2019-2019 IEEE International Conference on Acoustics …, 2019ieeexplore.ieee.org
Cooperative communication using unmanned aerial vehicles (UAVs) is a promising
technology for infrastructureless wireless networks. One of the key challenges in UAV based
communications is the backhaul throughput. In this paper, we propose optimization of the
UAV swarm positions to achieve a high mulitplexing gain in line-of-sight (LoS) MIMO back-
haul. We develop two distributed algorithms to position the UAVs such that each UAV moves
a minimal distance to realize the highest capacity LoS MIMO channel. The first approach …
Cooperative communication using unmanned aerial vehicles (UAVs) is a promising technology for infrastructureless wireless networks. One of the key challenges in UAV based communications is the backhaul throughput. In this paper, we propose optimization of the UAV swarm positions to achieve a high mulitplexing gain in line-of-sight (LoS) MIMO back-haul. We develop two distributed algorithms to position the UAVs such that each UAV moves a minimal distance to realize the highest capacity LoS MIMO channel. The first approach uses iterative gradient descent (GD) and the second uses iterative brute force (BF). Simulations show that both algorithms can achieve up to 6 times higher capacity compared to the approach relying on random UAV placement, earlier proposed in the literature. BF has the advantage of not requiring any location information, while GD is less sensitive to errors in motion.
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