Online Computation Offloading and Trajectory Scheduling for UAV-Enabled Wireless Powered Mobile Edge Computing

作     者：Han Hu Xiang Zhou Qun Wang Rose Qingyang Hu Han Hu;Xiang Zhou;Qun Wang;Rose Qingyang Hu

作者机构：The Jiangsu Key Laboratory of Wireless CommunicationsNanjing University of Posts and TelecommunicationsNanjing 210003China The Engineering Research Center of Health Service System Based on Ubiquitous Wireless NetworksMinistry of EducationNanjing University of Posts and TelecommunicationsNanjing 210003China The Department of Electrical and Computer EngineeringUtah State UniversityLoganUTUSA. 

出 版 物：《China Communications》 (中国通信（英文版）)

年 卷 期：2022年第19卷第4期

页      面：257-273页

核心收录：

学科分类：080904[工学-电磁场与微波技术] 0810[工学-信息与通信工程] 080802[工学-电力系统及其自动化] 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] 080402[工学-测试计量技术及仪器] 0804[工学-仪器科学与技术] 082503[工学-航空宇航制造工程] 081001[工学-通信与信息系统] 0825[工学-航空宇航科学与技术] 

基　　金：supported in part by the U.S. National Science Foundation under Grant CNS-2007995 in part by the National Natural Science Foundation of China under Grant 92067201,62171231 in part by Jiangsu Provincial Key Research and Development Program under Grant BE2020084-1 

主　　题：energy efficiency mobile edge computing UAV-enabled wireless power transfer trajectorys cheduling 

摘      要：The unmanned aerial vehicle(UAV)-enabled mobile edge computing(MEC) architecture is expected to be a powerful technique to facilitate 5 G and beyond ubiquitous wireless connectivity and diverse vertical applications and services, anytime and anywhere. Wireless power transfer(WPT) is another promising technology to prolong the operation time of low-power wireless devices in the era of Internet of Things(IoT). However, the integration of WPT and UAV-enabled MEC systems is far from being well studied, especially in dynamic environments. In order to tackle this issue, this paper aims to investigate the stochastic computation offloading and trajectory scheduling for the UAV-enabled wireless powered MEC system. A UAV offers both RF wireless power transmission and computation services for IoT devices. Considering the stochastic task arrivals and random channel conditions, a long-term average energyefficiency(EE) minimization problem is *** to non-convexity and the time domain coupling of the variables in the formulated problem, a lowcomplexity online computation offloading and trajectory scheduling algorithm(OCOTSA) is proposed by exploiting Lyapunov optimization. Simulation results verify that there exists a balance between EE and the service delay, and demonstrate that the system EE performance obtained by the proposed scheme outperforms other benchmark schemes.