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基于功率控制和聚类的无人机辅助网络干扰管理

Power Control and Clustering-Based Interference Management for UAV-Assisted Networks.

作者信息

Zhang Jinxi, Chuai Gang, Gao Weidong

机构信息

School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100000, China.

出版信息

Sensors (Basel). 2020 Jul 10;20(14):3864. doi: 10.3390/s20143864.

Abstract

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.

摘要

无人机(UAV)已在无线网络的各种应用中得到广泛使用。无人机系统具有数据收集、为地面基站(BS)卸载流量以及消除覆盖空洞的功能。然而,由于空对地信道中存在大量视距(LoS)路径,无人机之间很容易产生干扰。在本文中,我们提出了一种用于无人机辅助网络的干扰管理框架,该框架由两个主要模块组成:功率控制和无人机聚类。首先执行功率控制以调整无人机的功率水平。我们将无人机网络的功率控制问题建模为一个非合作博弈,该博弈被证明是一个精确势博弈并且能达到纳什均衡。接下来,为了进一步提高系统用户速率,实施了协作多点(CoMP)技术。建立协作无人机集来为用户服务,从而将干扰链路转化为有用链路。基于干扰强度,应用亲和传播算法来构建无人机集群。仿真结果表明,与非CoMP场景相比,所提出的将功率控制与CoMP相结合的算法能够有效降低干扰并提高系统总速率。还得出了集群形成规律,其中平均集群大小和集群数量受无人机间距离的影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/019a/7411894/cf4fd5c088c8/sensors-20-03864-g001.jpg

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