@inproceedings{f5bbd360308e4ec6ab54966e684aa52c,
title = "Leveraging Antenna Orientation to Optimize Network Performance of Fleets of UAVs",
abstract = "In this paper, we investigate the problem of optimizing the network performance of a fleet of unmanned aerial vehicles (UAVs) in static positions. More precisely, we allow each UAV to change its orientation in order to improve the quality of communication with its neighbours. This form of controlled mobility takes advantage of the effective radiation pattern of each UAV. We build a decentralized scheme based on the hill climbing optimization approach without a priori knowledge of the antennas radiation patterns. Then, we propose a simulation framework, based on ns-3, allowing to evaluate the gain in network performance. We provide results in several deployment scenarios involving different rate adaptation algorithms and network sizes.",
keywords = "802.11, antenna, drone, mobility, ns-3, rate adaptation, simulation, simulator, uav, wlan",
author = "R{\'e}my Gr{\"u}nblatt and Lassous, \{Isabelle Gu{\'e}rin\} and Olivier Simonin",
note = "Publisher Copyright: {\textcopyright} 2020 ACM.; 23rd ACM International Conference on Modelling, Analysis, and Simulation of Wireless and Mobile Systems, MSWiM 2020 ; Conference date: 16-11-2020 Through 20-11-2020",
year = "2020",
month = nov,
day = "16",
doi = "10.1145/3416010.3423225",
language = "English",
series = "MSWiM 2020 - Proceedings of the 23rd International ACM Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems",
publisher = "Association for Computing Machinery, Inc",
pages = "253--260",
booktitle = "MSWiM 2020 - Proceedings of the 23rd International ACM Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems",
}