[论文解读] Trajectory Optimization for Completion Time Minimization in UAV-Enabled Multicasting

Yong Zeng, Xiaoli Xu+1 more|arXiv (Cornell University)|Aug 22, 2017

UAV Applications and Optimization参考文献 29被引用 15

一句话总结

本文提出了一种针对无人机（UAV）多播通信的优化轨迹设计，结合随机线性网络编码（RLNC），以最小化任务完成时间。通过推导文件恢复成功率的下界，问题被重新表述为仅需满足与地面终端的最小连接时间约束，从而可通过凸优化和线性规划实现分段线性轨迹的最优设计。

ABSTRACT

This paper studies an unmanned aerial vehicle (UAV)-enabled multicasting system, where a UAV is dispatched to disseminate a common file to a number of geographically distributed ground terminals (GTs). Our objective is to design the UAV trajectory to minimize its mission completion time, while ensuring that each GT is able to successfully recover the file with a high probability required. We consider the use of practical random linear network coding (RLNC) for UAV multicasting, so that each GT is able to recover the file as long as it receives a sufficiently large number of coded packets. However, the formulated UAV trajectory optimization problem is non-convex and difficult to be directly solved. To tackle this issue, we first derive an analytical lower bound for the success probability of each GT's file recovery. Based on this result, we then reformulate the problem into a more tractable form, where the UAV trajectory only needs to be designed to meet a set of constraints each on the minimum connection time with a GT, during which their distance is below a designed threshold. We show that the optimal UAV trajectory only needs to constitute connected line segments, thus it can be obtained by determining first the optimal set of waypoints and then UAV speed along the lines connecting the waypoints. We propose practical schemes for the waypoints design based on a novel concept of virtual base station (VBS) placement and by applying convex optimization techniques. Furthermore, for given set of waypoints, we obtain the optimal UAV speed over the resulting path efficiently by solving a linear programming (LP) problem. Numerical results show that the proposed UAV-enabled multicasting with optimized trajectory design achieves significant performance gains as compared to benchmark schemes.

研究动机与目标

• 解决在向分布式地面终端多播时，最小化无人机任务完成时间的挑战。
• 通过实际的随机线性网络编码（RLNC）确保每个地面终端的高成功率文件恢复。
• 通过解析重构，克服原始轨迹优化问题的非凸性。
• 设计仅由路径点之间直线段连接而成的分段线性无人机轨迹。
• 利用线性规划高效计算轨迹沿线的最优无人机速度。

提出的方法

• 推导使用RLNC时，每个地面终端文件恢复成功率的解析下界。
• 将原始非凸问题重构为仅含每个地面终端最小连接时间约束的可处理形式。
• 证明最优无人机轨迹仅由关键路径点之间的直线段组成。
• 引入虚拟基站（VBS）概念，通过凸优化指导最优路径点的放置。
• 建立并求解线性规划（LP）问题，以确定分段路径上的最优无人机速度。
• 利用连接地面终端集合发生变化的关键时间点，将轨迹划分为多个段。

实验结果

研究问题

• RQ1 如何优化无人机轨迹，以在确保通过RLNC实现可靠文件传输的同时，最小化任务完成时间？
• RQ2 无人机与地面站之间的距离、连接时间与文件恢复成功率之间的解析关系是什么？
• RQ3 非凸轨迹优化问题能否被重构为凸或可处理的形式？
• RQ4 在给定约束条件下，最优无人机轨迹的结构形式是什么？
• RQ5 如何高效计算分段路径上最优无人机速度？

主要发现

• 最优无人机轨迹仅由路径点之间的连接线段构成，支持高效计算。
• 与基准方案相比，所提方法在完成时间减少方面实现了显著性能提升。
• 使用虚拟基站（VBS）可实现有效且通过凸优化优化的路径点布局，提升覆盖效果。
• 线性规划被证明可高效计算给定路径点下轨迹沿线的最优无人机速度。
• 引入最小连接时间约束的重构问题可确保所有地面终端均实现高成功率文件恢复。
• 该轨迹优化框架具有鲁棒性和可扩展性，因其将原始非凸问题简化为一系列凸和线性子问题。