期刊
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
卷 18, 期 10, 页码 4738-4752出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TWC.2019.2928539
关键词
UAV; mobile edge computing; resource scheduling; bandwidth allocation; trajectory optimization
资金
- U.K. Engineering and Physical Sciences Research Council (EPSRC) [EP/K015893/1]
- Natural Science Foundation of China [61620106011, 61572389]
- EPSRC [EP/K015893/1] Funding Source: UKRI
In this paper, we study an unmanned aerial vehicle (UAV)-assisted mobile edge computing (MEC) architecture, in which a UAV roaming around the area may serve as a computing server to help user equipment (UEs) compute their tasks or act as a relay for further offloading their computation tasks to the access point (AP). We aim to minimize the weighted sum energy consumption of the UAV and UEs subject to the task constraints, the information-causality constraints, the bandwidth allocation constraints and the UAV's trajectory constraints. The required optimization is nonconvex, and an alternating optimization algorithm is proposed to jointly optimize the computation resource scheduling, bandwidth allocation, and the UAV's trajectory in an iterative fashion. The numerical results demonstrate that significant performance gain is obtained over conventional methods. Also, the advantages of the proposed algorithm are more prominent when handling computation-intensive latency-critical tasks.
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