UAV Trajectory Design on Completion Time Minimization of WPT Task in UAV-Enabled Multi-User Network

Xiaopeng Yuan, Guodong Sun, Yulin Hu, Lihua Wu, Hao Wang, A. Schmeink
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引用次数: 2

Abstract

In this paper, we study a UAV-enabled wireless sensor network (WSN), where a UAV is dispatched to charge multiple sensors deployed on the ground floor via the wireless power transfer (WPT) technique. A probabilistic line-of-sight (PLoS) channel model and a practical nonlinear energy harvesting (EH) model are considered in the characterization of the harvested energy by sensors. Focusing on a WPT task where a minimum energy budget is required by each sensor, we formulate a UAV trajectory optimization problem minimizing the corresponding completion time. To simplify the analysis, we reformulate the completion time minimization problem via inserting a successive-hover-and-fly (SHF) structure into UAV trajectory without loss of optimality. Afterwards, we proved the convexity in the LoS probability and nonlinear harvested power with respect to a higher-order power of a horizontal distance. Based on the proved convexity, we construct a convex approximation for the harvested energy at each sensor and propose an iterative solution for iteratively reducing the completion time until a convergence to a suboptimal point. At last, the simulation results are presented to confirm the convergence of the proposed algorithm and reveal the benefits in adopting the more practical PLoS model.
多用户网络中WPT任务完成时间最小化的无人机轨迹设计
本文研究了一种支持无人机的无线传感器网络(WSN),其中一架无人机通过无线电力传输(WPT)技术向部署在底层的多个传感器充电。考虑了概率视距(PLoS)通道模型和实际的非线性能量收集(EH)模型来表征传感器收集的能量。针对每个传感器所需能量预算最小的WPT任务,提出了一个最小化相应完成时间的无人机轨迹优化问题。为了简化分析,我们通过在无人机轨迹中插入连续悬停飞行(SHF)结构来重新表述完成时间最小化问题,而不会失去最优性。然后,我们证明了LoS概率和非线性收获功率相对于水平距离的高阶幂的凸性。基于已证明的凸性,我们构造了每个传感器收集能量的凸近似,并提出了迭代解决方案,迭代地减少完成时间,直到收敛到次优点。最后给出了仿真结果,验证了所提算法的收敛性,并揭示了采用更实用的PLoS模型的好处。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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