[论文解读] Energy Minimization for Wireless Communication with Rotary-Wing UAV

Yong Zeng, Jie Xu+1 more|arXiv (Cornell University)|Apr 6, 2018

UAV Applications and Optimization参考文献 24被引用 75

一句话总结

本论文通过对推进能量建模、建立联合轨迹与调度优化，并通过飞行-悬停-通信与路径离散化方法求解，提出一个能源最小化的旋翼无人机支持的无线通信框架。

ABSTRACT

This paper studies unmanned aerial vehicle (UAV) enabled wireless communication, where a rotarywing UAV is dispatched to send/collect data to/from multiple ground nodes (GNs). We aim to minimize the total UAV energy consumption, including both propulsion energy and communication related energy, while satisfying the communication throughput requirement of each GN. To this end, we first derive an analytical propulsion power consumption model for rotary-wing UAVs, and then formulate the energy minimization problem by jointly optimizing the UAV trajectory and communication time allocation among GNs, as well as the total mission completion time. The problem is difficult to be optimally solved, as it is non-convex and involves infinitely many variables over time. To tackle this problem, we first consider the simple fly-hover-communicate design, where the UAV successively visits a set of hovering locations and communicates with one corresponding GN when hovering at each location. For this design, we propose an efficient algorithm to optimize the hovering locations and durations, as well as the flying trajectory connecting these hovering locations, by leveraging the travelling salesman problem (TSP) and convex optimization techniques. Next, we consider the general case where the UAV communicates also when flying. We propose a new path discretization method to transform the original problem into a discretized equivalent with a finite number of optimization variables, for which we obtain a locally optimal solution by applying the successive convex approximation (SCA) technique. Numerical results show the significant performance gains of the proposed designs over benchmark schemes, in achieving energy-efficient communication with rotary-wing UAVs.

研究动机与目标

• 最小化包括推进能量和通信能量在内的无人机总能耗。
• 确保每个地面节点达到其目标信息吞吐量。
• 理解旋翼无人机在飞行与悬停/通信能量之间的权衡。
• 探索适用于简单与一般 UAV 通信协议的可行解法。
• 在带有旋翼动力学的 TDMA 下，提供能效轨迹设计的洞察与算法。

提出的方法

• 推导一个分析性推进功率模型，适用于旋翼无人机，涵盖叶片轮廓、感应功率和寄生功率分量。
• 在轨迹、时间分配和任务时间上，结合吞吐约束，建立一个非凸的能量最小化问题 (P1)。
• 采用 fly-hover-communicate 协议，将 (P1) 降维为有限变量问题，并通过基于 TSP 的排序与凸优化求解。
• 引入路径离散化方法，将时域连续问题转化为适用于逐次凸近似 (SCA) 的有限变量形式。
• 证明收敛到满足 KKT 条件的局部最优解。
• 给出单个和多个 GN 情况的渐近/启发式洞见，包括 MR/MÉ 常数和最优行进速度。

实验结果

研究问题

• RQ1 在满足各 GN 吞吐要求的同时，如何将无人机总能量（推进能量加通信能量）降至最低？
• RQ2 在旋翼推进动力学约束下，针对能量优化，UAV 轨迹与 TDMA 调度的高效算法是什么？
• RQ3 如何利用 fly-hover-communicate 和路径离散化方法获得可处理且近似优化的解？
• RQ4 在数据采集/中继场景中，旋翼无人机的飞行能量与悬停/通信能量之间的权衡是什么？
• RQ5 在多 GN 情况下，访问顺序与悬停位置如何影响总能耗？

主要发现

• 旋翼无人机的推进能量包括叶片轮廓、感应和寄生分量；悬停并不总是能量最优。
• 对于单个 GN，存在在前往最优悬停点与悬停发送之间的最优平衡，由 MR 速度和一维 D_tr 权衡决定。
• 对于多个 GN，通过选择合适的悬停位置和访问顺序来最小化能量，转化为类似 TSP 的问题，并对航路点放置进行凸优化。
• 结合路径离散化与 SCA 的方法，在不预先设定任务时间的情况下，得到一般 (P1) 问题的局部最优解。
• 数值结果显示，与基准相比，所提出的 fly-hover-communicate 与路径离散化设计在能量上有显著节省。