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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Main Authors: Jinxi Zhang, Gang Chuai, Weidong Gao
Format: Article
Language:English
Published: MDPI AG 2020-07-01
Series:Sensors
Subjects:
Online Access:https://www.mdpi.com/1424-8220/20/14/3864
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spelling 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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