[论文解读] Throughput Maximization for UAV-Enabled Wireless Powered Communication Networks

Lifeng Xie, Jie Xu+1 more|arXiv (Cornell University)|Jan 14, 2018

Energy Harvesting in Wireless Networks参考文献 35被引用 16

一句话总结

本文提出一种由无人机（UAV）支持的无线能量传输通信网络（WPCN），通过联合优化UAV轨迹与无线资源分配，最大化上行链路公共吞吐量。通过利用UAV移动性，使其在用户上方悬停以实现高效的下行链路能量传输和上行链路通信，该方案显著优于传统固定接入点（AP）的WPCN，尤其在解决‘双重近-远’公平性问题方面表现突出。

ABSTRACT

This paper studies an unmanned aerial vehicle (UAV)-enabled wireless powered communication network (WPCN), in which a UAV is dispatched as a mobile access point (AP) to serve a set of ground users periodically. The UAV employs the radio frequency (RF) wireless power transfer (WPT) to charge the users in the downlink, and the users use the harvested RF energy to send independent information to the UAV in the uplink. Unlike the conventional WPCN with fixed APs, the UAV-enabled WPCN can exploit the mobility of the UAV via trajectory design, jointly with the wireless resource allocation optimization, to maximize the system throughput. In particular, we aim to maximize the uplink common (minimum) throughput among all ground users over a finite UAV's flight period, subject to its maximum speed constraint and the users' energy neutrality constraints. The resulted problem is non-convex and thus difficult to be solved optimally. To tackle this challenge, we first consider an ideal case without the UAV's maximum speed constraint, and obtain the optimal solution to the relaxed problem. The optimal solution shows that the UAV should successively hover above a finite number of ground locations for downlink WPT, as well as above each of the ground users for uplink communication. Next, we consider the general problem with the UAV's maximum speed constraint. Based on the above multi-location-hovering solution, we first propose an efficient successive hover-and-fly trajectory design, jointly with the downlink and uplink wireless resource allocation, and then propose a locally optimal solution by applying the techniques of alternating optimization and successive convex programming (SCP). Numerical results show that the proposed UAV-enabled WPCN achieves significant throughput gains over the conventional WPCN with fixed-location AP.

研究动机与目标

• 为解决传统WPCN中固定AP导致的‘双重近-远’问题，即远距离用户能量采集效率低且上行链路发射功率高。
• 通过轨迹优化实现UAV的动态定位，利用其移动性提升能量传输效率与通信公平性。
• 在有限飞行周期内，最大化所有地面用户中最小（公共）上行链路吞吐量。
• 在UAV速度与用户能量中性约束条件下，联合优化UAV轨迹、下行链路无线功率传输（WPT）与上行链路无线信息传输（WIT）资源分配。

提出的方法

• 基于无约束情况下的最优多位置悬停解，提出一种连续悬停-飞行轨迹设计。
• 采用交替优化与连续凸逼近（Successive Convex Programming, SCP）方法，求解具有UAV速度与能量中性约束的非凸优化问题。
• 利用一阶泰勒近似将下行链路与上行链路速率表达式中的非凸项转化为凸形式。
• 将UAV轨迹建模为在地面用户及中间航点上方的悬停阶段序列，以平衡能量采集与信息传输。
• 实施两阶段优化：首先，推导无速度限制下的最优轨迹；其次，通过迭代优化将该轨迹适配至速度约束条件。
• 整合下行链路功率与时间分配，以及上行链路传输调度，以最大化系统公平性与吞吐量。

实验结果

研究问题

• RQ1 如何利用UAV移动性提升WPCN中的能量采集效率与上行链路吞吐量？
• RQ2 在具有能量中性约束的WPCN中，服务多个地面用户的UAV最优轨迹结构为何种形式？
• RQ3 UAV速度约束的引入如何影响最优轨迹与系统性能？
• RQ4 基于SCP的方法能否有效求解UAV轨迹与资源分配的联合非凸优化问题？
• RQ5 所提出的UAV-enabled WPCN在公平性与吞吐量方面，相较于传统固定AP WPCN的性能提升程度如何？

主要发现

• 无速度约束下的最优轨迹由UAV依次在有限个地面位置及各用户上方悬停构成，可最大化能量传输与上行链路吞吐量。
• 所提出的基于SCP优化的连续悬停-飞行轨迹设计，在UAV速度约束下仍能实现高性能表现。
• 数值结果表明，与传统固定AP的WPCN相比，该方案在吞吐量方面有显著增益，尤其在解决双重近-远公平性问题方面优势明显。
• 即使固定AP处于最优位置，UAV-enabled WPCN仍能实现比其更高的公共吞吐量。
• 所提方法收敛迅速，可获得具有强实际可行性的局部最优解。