Sambo, Y.A. , Klaine, P.V. , Nadas, J.P.B. and Imran, M.A. (2019) Energy Minimization UAV Trajectory Design for Delay-Tolerant Emergency Communication. In: 53rd IEEE International Conference on Communications Workshops (ICC Workshops): Intelligent Wireless Emergency Communications Networks: Theory and Applications, Shanghai, China, 20-24 May 2019, ISBN 9781728123745 (doi: 10.1109/ICCW.2019.8757127)
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Abstract
The increasing cases of wireless communication networks being partly (or even fully) destroyed after the occurrence of natural disasters has made researchers focus on the use of Unmanned Aerial Vehicles (UAVs) to provide quick and efficient backup communication in post-disaster scenarios. However, the performance of UAVs in the provisioning of wireless coverage is known to be constrained by their battery life, which limits their flight times. In this paper, we explore the use of a single UAV to provide backhaul connectivity to truck-mounted Base Stations (BSs) that have been deployed within a disaster zone to provide network coverage to users based on the principle of delay-tolerant communications. We propose a trajectory design that uses genetic algorithm to find the trajectory with the least energy requirement for the UAV to visit all the BSs and return to a central node that acts as a gateway to the core network. Our trajectory design takes into account both the straight-and-level flight and banked-level turns of the UAV in computing the energy requirement. Simulation results show that our proposed design outperforms two approaches in the literature by up to 14% and 40%.
| Item Type: | Conference Proceedings |
|---|---|
| Status: | Published |
| Refereed: | Yes |
| Glasgow Author(s) Enlighten ID: | Sambo, Dr Yusuf and Imran, Professor Muhammad and Valente Klaine, Mr Paulo |
| Authors: | Sambo, Y.A., Klaine, P.V., Nadas, J.P.B., and Imran, M.A. |
| College/School: | College of Science and Engineering College of Science and Engineering > School of Engineering > Systems Power and Energy |
| ISSN: | 2474-9133 |
| ISBN: | 9781728123745 |
| Copyright Holders: | Copyright © 2019 IEEE |
| Publisher Policy: | Reproduced in accordance with the copyright policy of the publisher |
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