Coverage Optimization for UAV-Aided Internet of Things with Partial Channel Knowledge

作     者：Xuanxuan Wang Wei Feng Yunfei Chen Ning Ge 

作者机构：Beijing National Research Center for Infor-mation Science and Technology(BNRist)Department of Electronic Engi-neeringTsinghua UniversityBeijing 100084China School of Engineeringthe University of WarwickCoventryCV47ALUK 

出 版 物：《Journal of Communications and Information Networks》 (通信与信息网络学报（英文）)

年 卷 期：2018年第3卷第4期

页      面：55-63页

学科分类：0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 

基　　金：Beijing Natural science Foundation(No.L172041) the National Science Foundation of China(Nos.61701457,61771286,91638205,61671478 and 61621091) 

主　　题：block coordinate descent coverage optimization IoT UAVs 

摘      要：Due to the high maneuverability of unmanned aerial vehicles(UAVs),they have been widely deployed to boost the performance of Internet of Things(IoT).In this paper,to promote the coverage performance of UAV-aided IoT communications,we maximize the minimum average rate of the IoT devices by jointly optimizing the resource allocation strategy and the UAV ***,to depict the practical propagation environment,we take the composite channel model including both the small-scale and the large-scale channel fading into *** to the difficulty in acquiring the random small-scale channel fading,we assume that only the large-scale channel sate information is *** this basis,we formulate an optimization problem,which is not convex and challenging to ***,an efficient iterative algorithm is proposed using block coordinate descent and successive convex optimization ***,simulation results are presented to demonstrate the significant performance gain of the proposed scheme over existing ones.