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...
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doaj-dd8dca0893304759847f903a75064d372020-11-25T03:43:28ZengMDPI AGSensors1424-82202020-07-01203864386410.3390/s20143864Power Control and Clustering-Based Interference Management for UAV-Assisted NetworksJinxi Zhang0Gang Chuai1Weidong Gao2School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100000, ChinaSchool of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100000, ChinaSchool of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100000, ChinaUnmanned 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.https://www.mdpi.com/1424-8220/20/14/3864UAV communicationcoordinate multi-point (CoMP)potential gameaffinity propagation |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Jinxi Zhang Gang Chuai Weidong Gao |
spellingShingle |
Jinxi Zhang Gang Chuai Weidong Gao Power Control and Clustering-Based Interference Management for UAV-Assisted Networks Sensors UAV communication coordinate multi-point (CoMP) potential game affinity propagation |
author_facet |
Jinxi Zhang Gang Chuai Weidong Gao |
author_sort |
Jinxi Zhang |
title |
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_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_sort |
power control and clustering-based interference management for uav-assisted networks |
publisher |
MDPI AG |
series |
Sensors |
issn |
1424-8220 |
publishDate |
2020-07-01 |
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. |
topic |
UAV communication coordinate multi-point (CoMP) potential game affinity propagation |
url |
https://www.mdpi.com/1424-8220/20/14/3864 |
work_keys_str_mv |
AT jinxizhang powercontrolandclusteringbasedinterferencemanagementforuavassistednetworks AT gangchuai powercontrolandclusteringbasedinterferencemanagementforuavassistednetworks AT weidonggao powercontrolandclusteringbasedinterferencemanagementforuavassistednetworks |
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1724519688936882176 |