Multi-Antenna UAV Data Harvesting:Joint Trajectory and Communication Optimization

作     者：Jingwei Zhang Yong Zeng Rui Zhang Jingwei Zhang;Yong Zeng;Rui Zhang

作者机构：Department of Electrical and Computer EngineeringNational University of SingaporeSingapore National Mobile Communications Research LaboratorySoutheast UniversityNanjingChina.Purple Mountain LaboratoriesNanjingChina 

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

年 卷 期：2020年第5卷第1期

页      面：86-99页

核心收录：

学科分类：0810[工学-信息与通信工程] 0808[工学-电气工程] 0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 0839[工学-网络空间安全] 0804[工学-仪器科学与技术] 080402[工学-测试计量技术及仪器] 082503[工学-航空宇航制造工程] 0825[工学-航空宇航科学与技术] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：wireless sensor network multi-antenna unmannedaerialvehicle(UAV) ratemaximization trajectoryoptimization 

摘      要：Unmanned aerial vehicle(UAV)-enabled communication is a promising technology to extend coverage and enhance throughput for traditional terres-trial wireless communication systems.In this paper,we consider a UAV-enabled wireless sensor network,where a multi-antenna UAV is dispatched to collect data from a group of sensor nodes(SNs).The objective is to maximize the minimum data collection rate from all SNs via jointly optimizing their transmission scheduling and power allocations as well as the trajectory of the UAV,subject to the practical constraints on the maximum transmit power of the SNs and the maximum speed of the UAV.The formulated optimization problem is challenging to solve as it involves non-convex constraints and discrete-value variables.To draw useful insight,we first consider the special case of the formulated problem by ignoring the UAV speed constraint and optimally solve it based on the Lagrange duality method.It is shown that for this relaxed problem,the UAV should hover above a finite number of optimal locations with different durations in general.Next,we address the general case of the formulated problem where the UAV speed constraint is considered and propose a traveling salesman problem-based trajec-tory initialization,where the UAV sequentially visits the locations obtained in the relaxed problem with minimumflying time.Given this initial trajectory,we thenfind the corresponding transmission scheduling and power alloca-tions of the SNs and further optimize the UAV trajectory by applying the block coordinate descent and successive convex approximation techniques.Finally,numerical results are provided to illustrate the spectrum and energy efficiency gains of the proposed scheme for multi-antenna UAV data harvesting,as compared to benchmark schemes.