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Modeling and Performance Analysis of Opportunistic Link Selection for UAV Communication
In anticipation of wide implementation of 5G technologies, the scarcity of spectrum resources for the unmanned aerial vehicles (UAVs) communication remains one of the major challenges in arranging safe drone operations. Dynamic spectrum management among multiple UAVs as a tool that is able to addres...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7828490/ https://www.ncbi.nlm.nih.gov/pubmed/33451017 http://dx.doi.org/10.3390/s21020534 |
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author | Xu, Zhengjia Petrunin, Ivan Tsourdos, Antonios |
author_facet | Xu, Zhengjia Petrunin, Ivan Tsourdos, Antonios |
author_sort | Xu, Zhengjia |
collection | PubMed |
description | In anticipation of wide implementation of 5G technologies, the scarcity of spectrum resources for the unmanned aerial vehicles (UAVs) communication remains one of the major challenges in arranging safe drone operations. Dynamic spectrum management among multiple UAVs as a tool that is able to address this issue, requires integrated solutions with considerations of heterogeneous link types and support of the multi-UAV operations. This paper proposes a synthesized resource allocation and opportunistic link selection (RA-OLS) scheme for the air-to-ground (A2G) UAV communication with dynamic link selections. The link opportunities using link hopping sequences (LHSs) are allocated in the GCSs for alleviating the internal collisions within the UAV network, offloading the on-board computations in the spectrum processing function, and avoiding the contention in the air. In this context, exclusive technical solutions are proposed to form the prototype system. A sub-optimal allocation method based on the greedy algorithm is presented for addressing the resource allocation problem. A mathematical model of the RA-OLS throughput with above propositions is formulated for the spectrum dense and scarce environments. An interference factor is introduced to measure the protection effects on the primary users. The proposed throughput model approximates the simulated communication under requirements of small errors in the spectrum dense environment and the spectrum scarce environment, where the sensitivity analysis is implemented. The proposed RA-OLS outperforms the static communication scheme in terms of the utilization rate by over 50% in case when multiple links are available. It also enables the collaborative communication when the spectral resources are in scarcity. The impacts from diverse parameters on the RA-OLS communication performance are analyzed. |
format | Online Article Text |
id | pubmed-7828490 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-78284902021-01-25 Modeling and Performance Analysis of Opportunistic Link Selection for UAV Communication Xu, Zhengjia Petrunin, Ivan Tsourdos, Antonios Sensors (Basel) Article In anticipation of wide implementation of 5G technologies, the scarcity of spectrum resources for the unmanned aerial vehicles (UAVs) communication remains one of the major challenges in arranging safe drone operations. Dynamic spectrum management among multiple UAVs as a tool that is able to address this issue, requires integrated solutions with considerations of heterogeneous link types and support of the multi-UAV operations. This paper proposes a synthesized resource allocation and opportunistic link selection (RA-OLS) scheme for the air-to-ground (A2G) UAV communication with dynamic link selections. The link opportunities using link hopping sequences (LHSs) are allocated in the GCSs for alleviating the internal collisions within the UAV network, offloading the on-board computations in the spectrum processing function, and avoiding the contention in the air. In this context, exclusive technical solutions are proposed to form the prototype system. A sub-optimal allocation method based on the greedy algorithm is presented for addressing the resource allocation problem. A mathematical model of the RA-OLS throughput with above propositions is formulated for the spectrum dense and scarce environments. An interference factor is introduced to measure the protection effects on the primary users. The proposed throughput model approximates the simulated communication under requirements of small errors in the spectrum dense environment and the spectrum scarce environment, where the sensitivity analysis is implemented. The proposed RA-OLS outperforms the static communication scheme in terms of the utilization rate by over 50% in case when multiple links are available. It also enables the collaborative communication when the spectral resources are in scarcity. The impacts from diverse parameters on the RA-OLS communication performance are analyzed. MDPI 2021-01-13 /pmc/articles/PMC7828490/ /pubmed/33451017 http://dx.doi.org/10.3390/s21020534 Text en © 2021 by the authors. 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 (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Xu, Zhengjia Petrunin, Ivan Tsourdos, Antonios Modeling and Performance Analysis of Opportunistic Link Selection for UAV Communication |
title | Modeling and Performance Analysis of Opportunistic Link Selection for UAV Communication |
title_full | Modeling and Performance Analysis of Opportunistic Link Selection for UAV Communication |
title_fullStr | Modeling and Performance Analysis of Opportunistic Link Selection for UAV Communication |
title_full_unstemmed | Modeling and Performance Analysis of Opportunistic Link Selection for UAV Communication |
title_short | Modeling and Performance Analysis of Opportunistic Link Selection for UAV Communication |
title_sort | modeling and performance analysis of opportunistic link selection for uav communication |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7828490/ https://www.ncbi.nlm.nih.gov/pubmed/33451017 http://dx.doi.org/10.3390/s21020534 |
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