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Joint Resource Management and Trajectory Optimization for UAV-Enabled Maritime Network
Due to the lack of places to employ communication infrastructures, there are many coverage blind zones in maritime communication networks. Benefiting from the high flexibility and maneuverability, unmanned aerial vehicles (UAVs) have been proposed as a promising method to provide broadband maritime...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9781414/ https://www.ncbi.nlm.nih.gov/pubmed/36560131 http://dx.doi.org/10.3390/s22249763 |
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author | Yu, Guanding Ding, Xin Liu, Shengli |
author_facet | Yu, Guanding Ding, Xin Liu, Shengli |
author_sort | Yu, Guanding |
collection | PubMed |
description | Due to the lack of places to employ communication infrastructures, there are many coverage blind zones in maritime communication networks. Benefiting from the high flexibility and maneuverability, unmanned aerial vehicles (UAVs) have been proposed as a promising method to provide broadband maritime coverage for these blind zones. In this paper, a multi-UAV-enabled maritime communication model is proposed, where UAVs are deployed to provide the transmission service for maritime users. To improve the performance of the maritime communication systems, an optimization problem is formulated to maximize the minimum average throughput among all users by jointly optimizing the user association, power allocation, and UAV trajectory. To derive the solutions with a low computational complexity, we decompose this problem into three subproblems, namely user association optimization, power allocation optimization, and UAV trajectory optimization. Then, a joint iterative algorithm is developed to achieve the solutions based on the successive convex approximation and interior-point methods. Extensive simulation results validate the effectiveness of the proposed algorithm and demonstrate that UAVs can be used to enhance the maritime coverage. |
format | Online Article Text |
id | pubmed-9781414 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-97814142022-12-24 Joint Resource Management and Trajectory Optimization for UAV-Enabled Maritime Network Yu, Guanding Ding, Xin Liu, Shengli Sensors (Basel) Article Due to the lack of places to employ communication infrastructures, there are many coverage blind zones in maritime communication networks. Benefiting from the high flexibility and maneuverability, unmanned aerial vehicles (UAVs) have been proposed as a promising method to provide broadband maritime coverage for these blind zones. In this paper, a multi-UAV-enabled maritime communication model is proposed, where UAVs are deployed to provide the transmission service for maritime users. To improve the performance of the maritime communication systems, an optimization problem is formulated to maximize the minimum average throughput among all users by jointly optimizing the user association, power allocation, and UAV trajectory. To derive the solutions with a low computational complexity, we decompose this problem into three subproblems, namely user association optimization, power allocation optimization, and UAV trajectory optimization. Then, a joint iterative algorithm is developed to achieve the solutions based on the successive convex approximation and interior-point methods. Extensive simulation results validate the effectiveness of the proposed algorithm and demonstrate that UAVs can be used to enhance the maritime coverage. MDPI 2022-12-13 /pmc/articles/PMC9781414/ /pubmed/36560131 http://dx.doi.org/10.3390/s22249763 Text en © 2022 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 Yu, Guanding Ding, Xin Liu, Shengli Joint Resource Management and Trajectory Optimization for UAV-Enabled Maritime Network |
title | Joint Resource Management and Trajectory Optimization for UAV-Enabled Maritime Network |
title_full | Joint Resource Management and Trajectory Optimization for UAV-Enabled Maritime Network |
title_fullStr | Joint Resource Management and Trajectory Optimization for UAV-Enabled Maritime Network |
title_full_unstemmed | Joint Resource Management and Trajectory Optimization for UAV-Enabled Maritime Network |
title_short | Joint Resource Management and Trajectory Optimization for UAV-Enabled Maritime Network |
title_sort | joint resource management and trajectory optimization for uav-enabled maritime network |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9781414/ https://www.ncbi.nlm.nih.gov/pubmed/36560131 http://dx.doi.org/10.3390/s22249763 |
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