[论文解读] 3D Trajectory Optimization in Rician Fading for UAV-Enabled Data Harvesting

Changsheng You, Rui Zhang|arXiv (Cornell University)|Jan 14, 2019

UAV Applications and Optimization参考文献 36被引用 11

一句话总结

该论文提出了一种用于瑞利衰落信道中无人机（UAV）数据采集的三维轨迹优化框架，其中通过逻辑斯蒂函数近似有效衰落功率以处理非凸性问题。该方法采用块坐标下降法结合连续凸逼近（Successive Convex Approximation, SCA），联合优化无人机调度、水平轨迹和垂直轨迹，相较于仅考虑视 Line-of-Sight（LoS）的模型，在真实衰落条件下实现了更优的数据采集速率。

ABSTRACT

In this paper, we consider a UAV-enabled WSN where a flying UAV is employed to collect data from multiple sensor nodes (SNs). Our objective is to maximize the minimum average data collection rate from all SNs subject to a prescribed reliability constraint for each SN by jointly optimizing the UAV communication scheduling and three-dimensional (3D) trajectory. Different from the existing works that assume the simplified line-of-sight (LoS) UAV-ground channels, we consider the more practically accurate angle-dependent Rician fading channels between the UAV and SNs with the Rician factors determined by the corresponding UAV-SN elevation angles. However, the formulated optimization problem is intractable due to the lack of a closed-form expression for a key parameter termed effective fading power that characterizes the achievable rate given the reliability requirement in terms of outage probability. To tackle this difficulty, we first approximate the parameter by a logistic ('S' shape) function with respect to the 3D UAV trajectory by using the data regression method. Then the original problem is reformulated to an approximate form, which, however, is still challenging to solve due to its non-convexity. As such, we further propose an efficient algorithm to derive its suboptimal solution by using the block coordinate descent technique, which iteratively optimizes the communication scheduling, the UAV's horizontal trajectory, and its vertical trajectory. The latter two subproblems are shown to be non-convex, while locally optimal solutions are obtained for them by using the successive convex approximation technique. Last, extensive numerical results are provided to evaluate the performance of the proposed algorithm and draw new insights on the 3D UAV trajectory under the Rician fading as compared to conventional LoS channel models.

研究动机与目标

• 在可靠性约束下，最大化无人机辅助无线传感器网络（UAV-enabled WSN）中所有传感器节点的最小平均数据采集速率。
• 解决由于缺乏有效衰落功率的闭式表达式而导致的瑞利衰落信道中三维轨迹优化的不可解性问题。
• 将瑞利因子建模为无人机-传感器节点（UAV-SN）仰角的函数，以反映真实城市/郊区传播条件。
• 开发一种可处理的算法，联合优化无人机通信调度、水平轨迹与垂直飞行剖面。
• 在实际衰落环境中，展示三维轨迹设计相较于传统二维LoS-only模型在性能上的提升。

提出的方法

• 通过数据回归方法，利用逻辑斯蒂（S形）函数近似瑞利衰落信道中的有效衰落功率，从而实现可处理的优化。
• 将原始的非凸问题重新表述为便于迭代优化的近似形式。
• 应用块坐标下降法，迭代优化三个子问题：通信调度、水平轨迹与垂直轨迹。
• 使用连续凸逼近（SCA）方法，局部求解非凸的水平与垂直轨迹子问题。
• 通过SCA推导出速率表达式的凸下界，确保算法收敛至次优解。
• 基于LoS分量函数关于高度的凹性，对速率约束进行凸松弛处理。

实验结果

研究问题

• RQ1 在瑞利衰落信道下，与仅考虑二维LoS-only模型相比，三维轨迹优化如何提升无人机辅助无线传感器网络中的数据采集速率？
• RQ2 逻辑斯蒂函数能否准确地将有效衰落功率近似为无人机-传感器节点仰角的函数？
• RQ3 在实际衰落条件下，垂直飞行剖面对链路可靠性与数据速率有何影响？
• RQ4 所提出的算法在多传感器场景下如何平衡数据采集的公平性与系统吞吐量？
• RQ5 在真实衰落环境中，轨迹复杂度、计算成本与性能增益之间的关键权衡是什么？

主要发现

• 所提算法在城市类环境中（存在显著多径衰落）相比传统二维LoS-only轨迹设计，实现了更高的最小平均数据采集速率。
• 三维轨迹设计通过高度调节实现更好的链路质量控制，显著提升了传感器节点之间的公平性。
• 有效衰落功率的逻辑斯蒂逼近与实测信道数据高度吻合，支持精确且高效的优化。
• 与固定高度设计相比，垂直轨迹优化在遮挡概率较高的区域带来了显著的性能增益。
• 连续凸逼近方法收敛稳定，所得次优解具有出色的实用性能。
• 数值结果证实，瑞利衰落模型相比理想LoS模型能提供更保守且更真实的性能预测。