Joint User Scheduling and UAV Trajectory Design on Completion Time Minimization for UAV-Aided Data Collection

被引:30
|
作者
Yuan, Xiaopeng [1 ,2 ]
Hu, Yulin [1 ,2 ]
Zhang, Jian [1 ]
Schmeink, Anke [2 ]
机构
[1] Wuhan Univ, Sch Elect Informat, Wuhan 430072, Peoples R China
[2] Rhein Westfal TH Aachen, Chair Informat Theory & Data Analyt, D-52074 Aachen, Germany
基金
中国国家自然科学基金;
关键词
Trajectory; Autonomous aerial vehicles; Task analysis; Data collection; Minimization; Wireless networks; Iterative methods; Unmanned aerial vehicle (UAV); trajectory design; user scheduling; data collection; completion time minimization; successive-hover-fly (SHF) structure; WIRELESS POWER TRANSFER; COMMUNICATION DESIGN; OPTIMIZATION; PLACEMENT; NETWORKS; INTERNET; IOT;
D O I
10.1109/TWC.2022.3222067
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
We consider an unmanned aerial vehicle (UAV) assisting data collection from multiple sensor nodes (SNs). We provide a completion time minimization design via jointly deciding the UAV trajectory and the SN assignment scheme. In particular, we first characterize the fundamental features of the joint optimal solution to the formulated problem. On the one hand, the optimal UAV trajectory is proved following a successive-hover-fly (SHF) structure. Namely, in an optimal solution, the UAV successively visits multiple hovering points and performs hovering with designated duration, while the maximum speed is achieved during the whole flying period between each two hovering points. On the other hand, the optimal SN assignment is characterized to follow a segment-based scheme. Based on the two characterizations, we are motivated to implement SHF structure with turning points in trajectory design and reasonably assume each segment in SHF structure having constant SN assignment. Afterwards, we relax the binary constraints for SN assignments and establish a convex approximation for the reformulated problem, which enables an iterative algorithm. A suboptimal joint solution is obtained via iteratively optimizing the completion time. A realization strategy is also provided for the relaxed solution while assuring the completion of data collection tasks. Finally, the proposed solution is validated and evaluated through numerical results. Both a low complexity and an accurate task completion guarantee of our proposed solution are observed in comparison with the benchmarks.
引用
收藏
页码:3884 / 3898
页数:15
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