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Power Control and Clustering-Based Interference Management for UAV-Assisted Networks
Unmanned Aerial Vehicle (UAV) has been widely used in various applications of wireless network. A system of UAVs has the function of collecting data, offloading traffic for ground Base Stations (BSs) and illuminating coverage holes. However, inter-UAV interference is easily introduced because of the...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7411894/ https://www.ncbi.nlm.nih.gov/pubmed/32664405 http://dx.doi.org/10.3390/s20143864 |
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author | Zhang, Jinxi Chuai, Gang Gao, Weidong |
author_facet | Zhang, Jinxi Chuai, Gang Gao, Weidong |
author_sort | Zhang, Jinxi |
collection | PubMed |
description | Unmanned Aerial Vehicle (UAV) has been widely used in various applications of wireless network. A system of UAVs has the function of collecting data, offloading traffic for ground Base Stations (BSs) and illuminating coverage holes. However, inter-UAV interference is easily introduced because of the huge number of LoS paths in the air-to-ground channel. In this paper, we propose an interference management framework for UAV-assisted networks, consisting of two main modules: power control and UAV clustering. The power control is executed first to adjust the power levels of UAVs. We model the problem of power control for UAV networks as a non-cooperative game which is proved to be an exact potential game and the Nash equilibrium is reached. Next, to further improve system user rate, coordinated multi-point (CoMP) technique is implemented. The cooperative UAV sets are established to serve users and thus transforming the interfering links into useful links. Affinity propagation is applied to build clusters of UAVs based on the interference strength. Simulation results show that the proposed algorithm integrating power control with CoMP can effectively reduce the interference and improve system sum-rate, compared to Non-CoMP scenario. The law of cluster formation is also obtained where the average cluster size and the number of clusters are affected by inter-UAV distance. |
format | Online Article Text |
id | pubmed-7411894 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-74118942020-08-25 Power Control and Clustering-Based Interference Management for UAV-Assisted Networks Zhang, Jinxi Chuai, Gang Gao, Weidong Sensors (Basel) Article Unmanned Aerial Vehicle (UAV) has been widely used in various applications of wireless network. A system of UAVs has the function of collecting data, offloading traffic for ground Base Stations (BSs) and illuminating coverage holes. However, inter-UAV interference is easily introduced because of the huge number of LoS paths in the air-to-ground channel. In this paper, we propose an interference management framework for UAV-assisted networks, consisting of two main modules: power control and UAV clustering. The power control is executed first to adjust the power levels of UAVs. We model the problem of power control for UAV networks as a non-cooperative game which is proved to be an exact potential game and the Nash equilibrium is reached. Next, to further improve system user rate, coordinated multi-point (CoMP) technique is implemented. The cooperative UAV sets are established to serve users and thus transforming the interfering links into useful links. Affinity propagation is applied to build clusters of UAVs based on the interference strength. Simulation results show that the proposed algorithm integrating power control with CoMP can effectively reduce the interference and improve system sum-rate, compared to Non-CoMP scenario. The law of cluster formation is also obtained where the average cluster size and the number of clusters are affected by inter-UAV distance. MDPI 2020-07-10 /pmc/articles/PMC7411894/ /pubmed/32664405 http://dx.doi.org/10.3390/s20143864 Text en © 2020 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 Zhang, Jinxi Chuai, Gang Gao, Weidong Power Control and Clustering-Based Interference Management for UAV-Assisted Networks |
title | Power Control and Clustering-Based Interference Management for UAV-Assisted Networks |
title_full | Power Control and Clustering-Based Interference Management for UAV-Assisted Networks |
title_fullStr | Power Control and Clustering-Based Interference Management for UAV-Assisted Networks |
title_full_unstemmed | Power Control and Clustering-Based Interference Management for UAV-Assisted Networks |
title_short | Power Control and Clustering-Based Interference Management for UAV-Assisted Networks |
title_sort | power control and clustering-based interference management for uav-assisted networks |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7411894/ https://www.ncbi.nlm.nih.gov/pubmed/32664405 http://dx.doi.org/10.3390/s20143864 |
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