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UAV Trajectory Optimization in a Post-Disaster Area Using Dual Energy-Aware Bandits †

Over the past few years, with the rapid increase in the number of natural disasters, the need to provide smart emergency wireless communication services has become crucial. Unmanned aerial Vehicles (UAVs) have gained much attention as promising candidates due to their unprecedented capabilities and...

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Autores principales: Amrallah, Amr, Mohamed, Ehab Mahmoud, Tran, Gia Khanh, Sakaguchi, Kei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9919222/
https://www.ncbi.nlm.nih.gov/pubmed/36772443
http://dx.doi.org/10.3390/s23031402
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author Amrallah, Amr
Mohamed, Ehab Mahmoud
Tran, Gia Khanh
Sakaguchi, Kei
author_facet Amrallah, Amr
Mohamed, Ehab Mahmoud
Tran, Gia Khanh
Sakaguchi, Kei
author_sort Amrallah, Amr
collection PubMed
description Over the past few years, with the rapid increase in the number of natural disasters, the need to provide smart emergency wireless communication services has become crucial. Unmanned aerial Vehicles (UAVs) have gained much attention as promising candidates due to their unprecedented capabilities and broad flexibility. In this paper, we investigate a UAV-based emergency wireless communication network for a post-disaster area. Our optimization problem aims to optimize the UAV’s flight trajectory to maximize the number of visited ground users during the flight period. Then, a dual cost-aware multi-armed bandit algorithm is adopted to tackle this problem under the limited available energy for both the UAV and ground users. Simulation results show that the proposed algorithm could solve the optimization problem and maximize the achievable throughput under these energy constraints.
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spelling pubmed-99192222023-02-12 UAV Trajectory Optimization in a Post-Disaster Area Using Dual Energy-Aware Bandits † Amrallah, Amr Mohamed, Ehab Mahmoud Tran, Gia Khanh Sakaguchi, Kei Sensors (Basel) Article Over the past few years, with the rapid increase in the number of natural disasters, the need to provide smart emergency wireless communication services has become crucial. Unmanned aerial Vehicles (UAVs) have gained much attention as promising candidates due to their unprecedented capabilities and broad flexibility. In this paper, we investigate a UAV-based emergency wireless communication network for a post-disaster area. Our optimization problem aims to optimize the UAV’s flight trajectory to maximize the number of visited ground users during the flight period. Then, a dual cost-aware multi-armed bandit algorithm is adopted to tackle this problem under the limited available energy for both the UAV and ground users. Simulation results show that the proposed algorithm could solve the optimization problem and maximize the achievable throughput under these energy constraints. MDPI 2023-01-26 /pmc/articles/PMC9919222/ /pubmed/36772443 http://dx.doi.org/10.3390/s23031402 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Amrallah, Amr
Mohamed, Ehab Mahmoud
Tran, Gia Khanh
Sakaguchi, Kei
UAV Trajectory Optimization in a Post-Disaster Area Using Dual Energy-Aware Bandits †
title UAV Trajectory Optimization in a Post-Disaster Area Using Dual Energy-Aware Bandits †
title_full UAV Trajectory Optimization in a Post-Disaster Area Using Dual Energy-Aware Bandits †
title_fullStr UAV Trajectory Optimization in a Post-Disaster Area Using Dual Energy-Aware Bandits †
title_full_unstemmed UAV Trajectory Optimization in a Post-Disaster Area Using Dual Energy-Aware Bandits †
title_short UAV Trajectory Optimization in a Post-Disaster Area Using Dual Energy-Aware Bandits †
title_sort uav trajectory optimization in a post-disaster area using dual energy-aware bandits †
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9919222/
https://www.ncbi.nlm.nih.gov/pubmed/36772443
http://dx.doi.org/10.3390/s23031402
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