[论文解读] Joint Trajectory and Communication Design for Multi-UAV Enabled Wireless Networks

Qingqing Wu, Yong Zeng+1 more|arXiv (Cornell University)|May 8, 2017

UAV Applications and Optimization参考文献 21被引用 54

一句话总结

论文提出一个联合优化框架，通过联合优化用户调度/关联、无人机轨迹和发射功率，在多无人机下行链路中最大化最小吞吐量，通过迭代块坐标下降与序列凸优化求解。

ABSTRACT

Unmanned aerial vehicles (UAVs) have attracted significant interest recently in assisting wireless communication due to their high maneuverability, flexible deployment, and low cost. This paper considers a multi-UAV enabled wireless communication system, where multiple UAV-mounted aerial base stations (BSs) are employed to serve a group of users on the ground. To achieve fair performance among users, we maximize the minimum throughput over all ground users in the downlink communication by optimizing the multiuser communication scheduling and association jointly with the UAVs' trajectory and power control. The formulated problem is a mixed integer non-convex optimization problem that is challenging to solve. As such, we propose an efficient iterative algorithm for solving it by applying the block coordinate descent and successive convex optimization techniques. Specifically, the user scheduling and association, UAV trajectory, and transmit power are alternately optimized in each iteration. In particular, for the non-convex UAV trajectory and transmit power optimization problems, two approximate convex optimization problems are solved, respectively. We further show that the proposed algorithm is guaranteed to converge to at least a locally optimal solution. To speed up the algorithm convergence and achieve good throughput, a low-complexity and systematic initialization scheme is also proposed for the UAV trajectory design based on the simple circular trajectory and the circle packing scheme. Extensive simulation results are provided to demonstrate the significant throughput gains of the proposed design as compared to other benchmark schemes.

研究动机与目标

• 在高移动性和干扰存在的多无人机下行通信中，推动并实现公平性能。
• 通过对调度、无人机轨迹和功率控制的联合设计，最大化地面用户的最小平均速率。
• 为混合整数非凸问题开发具有收敛性保证的高效算法。
• 提供初始化和重构方法以提升收敛性和实际适用性。

提出的方法

• 在轨迹、功率和关联约束下，将最大化最小用户速率的问题建模为混合整数非凸优化问题。
• 将二进制调度变量松弛为连续值，并应用块坐标下降法迭代优化三个子块：调度/关联、无人机轨迹和发射功率。
• 通过构造凸界与线性化，使用序列凸优化来处理非凸的轨迹与功率问题。
• 引入基于圆形轨迹的初始化和圆铺排方案以加速收敛。
• 证明迭代算法的收敛性，并给出从放松解中重构二进制决策的方法。

实验结果

研究问题

• RQ1 是否可以通过对调度/关联、无人机轨迹和发射功率的联合设计，在多无人机下行中将地面用户的最小平均速率最大化？
• RQ2 无人机机动性和干扰管理对多无人机网络吞吐量公平性的影响是什么？
• RQ3 如何为得到的混合整数非凸问题开发具有可处理性且具有收敛性保证的算法？
• RQ4 圆形轨迹初始化是否能改善收敛性和吞吐性能？
• RQ5 如何将放松的连续调度决策有效映射回二进制关联？

主要发现

• 所提出的算法在静态无人机或启发式轨迹的基准方案上实现显著的吞吐提升。
• 吞吐量随轨迹设计周期增加而提升，体现了多无人机系统中的吞吐-访问延迟折衷。
• 与单一无人机相比，使用多架无人机显著缓解吞吐-访问延迟的折衷。
• 在所提出的松弛和近似条件下，带序列凸优化的块坐标下降法收敛到一个驻点。
• 基于圆形轨迹和圆铺排的高效初始化方案加速收敛并提升性能。