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A Channel Rendezvous Algorithm for Multi-Unmanned Aerial Vehicle Networks Based on Average Consensus
Realizing the distributed adaptive network construction of multi-UAV networks is an urgent challenge, as they lack a reliable common control channel and can only maintain a limited sensing range in crowded electromagnetic environments. Multi-unmanned aerial vehicle (UAV) networks are gaining popular...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10575011/ https://www.ncbi.nlm.nih.gov/pubmed/37836906 http://dx.doi.org/10.3390/s23198076 |
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author | Wang, Yunlu Zhang, Bo Qin, Shan Peng, Jinlin |
author_facet | Wang, Yunlu Zhang, Bo Qin, Shan Peng, Jinlin |
author_sort | Wang, Yunlu |
collection | PubMed |
description | Realizing the distributed adaptive network construction of multi-UAV networks is an urgent challenge, as they lack a reliable common control channel and can only maintain a limited sensing range in crowded electromagnetic environments. Multi-unmanned aerial vehicle (UAV) networks are gaining popularity in many fields. In order to address these issues, this paper proposes a multi-UAV network channel rendezvous algorithm based on average consistency. The goal of the algorithm is to adjust the communication channels of each UAV to converge on the same channel, since the communication link of the multi-UAV network is broken due to interference. The proposed memory-based average consistency (MAC) algorithm utilizes the network adjacency matrix as prior information. Furthermore, for the case where the adjacency matrix is unknown, this paper also proposes the Multi-Radio Average Consensus (MRAC) algorithm, which achieves a beneficial trade-off between rendezvous performance and hardware cost. Simulation results demonstrate that the proposed MAC and MRAC algorithms provide superior network convergence time and scalability in networks of different densities. Finally, a hardware simulation platform based on a multi-UAV network was designed using a software-defined radio platform, and experimental simulations were performed to prove the effectiveness of the MAC algorithm in a real environment. |
format | Online Article Text |
id | pubmed-10575011 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-105750112023-10-14 A Channel Rendezvous Algorithm for Multi-Unmanned Aerial Vehicle Networks Based on Average Consensus Wang, Yunlu Zhang, Bo Qin, Shan Peng, Jinlin Sensors (Basel) Article Realizing the distributed adaptive network construction of multi-UAV networks is an urgent challenge, as they lack a reliable common control channel and can only maintain a limited sensing range in crowded electromagnetic environments. Multi-unmanned aerial vehicle (UAV) networks are gaining popularity in many fields. In order to address these issues, this paper proposes a multi-UAV network channel rendezvous algorithm based on average consistency. The goal of the algorithm is to adjust the communication channels of each UAV to converge on the same channel, since the communication link of the multi-UAV network is broken due to interference. The proposed memory-based average consistency (MAC) algorithm utilizes the network adjacency matrix as prior information. Furthermore, for the case where the adjacency matrix is unknown, this paper also proposes the Multi-Radio Average Consensus (MRAC) algorithm, which achieves a beneficial trade-off between rendezvous performance and hardware cost. Simulation results demonstrate that the proposed MAC and MRAC algorithms provide superior network convergence time and scalability in networks of different densities. Finally, a hardware simulation platform based on a multi-UAV network was designed using a software-defined radio platform, and experimental simulations were performed to prove the effectiveness of the MAC algorithm in a real environment. MDPI 2023-09-25 /pmc/articles/PMC10575011/ /pubmed/37836906 http://dx.doi.org/10.3390/s23198076 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 Wang, Yunlu Zhang, Bo Qin, Shan Peng, Jinlin A Channel Rendezvous Algorithm for Multi-Unmanned Aerial Vehicle Networks Based on Average Consensus |
title | A Channel Rendezvous Algorithm for Multi-Unmanned Aerial Vehicle Networks Based on Average Consensus |
title_full | A Channel Rendezvous Algorithm for Multi-Unmanned Aerial Vehicle Networks Based on Average Consensus |
title_fullStr | A Channel Rendezvous Algorithm for Multi-Unmanned Aerial Vehicle Networks Based on Average Consensus |
title_full_unstemmed | A Channel Rendezvous Algorithm for Multi-Unmanned Aerial Vehicle Networks Based on Average Consensus |
title_short | A Channel Rendezvous Algorithm for Multi-Unmanned Aerial Vehicle Networks Based on Average Consensus |
title_sort | channel rendezvous algorithm for multi-unmanned aerial vehicle networks based on average consensus |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10575011/ https://www.ncbi.nlm.nih.gov/pubmed/37836906 http://dx.doi.org/10.3390/s23198076 |
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