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Joint Trajectory and Communication Design for Multi-UAV Enabled Wireless Networks

机译:多无人机无线联合弹道与通信设计   网络

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摘要

Unmanned aerial vehicles (UAVs) have attracted significant interest recentlyin assisting wireless communication due to their high maneuverability, flexibledeployment, and low cost. This paper considers a multi-UAV enabled wirelesscommunication system, where multiple UAV-mounted aerial base stations (BSs) areemployed to serve a group of users on the ground. To achieve fair performanceamong users, we maximize the minimum throughput over all ground users in thedownlink communication by optimizing the multiuser communication scheduling andassociation jointly with the UAVs' trajectory and power control. The formulatedproblem is a mixed integer non-convex optimization problem that is challengingto solve. As such, we propose an efficient iterative algorithm for solving itby applying the block coordinate descent and successive convex optimizationtechniques. 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, twoapproximate convex optimization problems are solved, respectively. We furthershow that the proposed algorithm is guaranteed to converge to at least alocally optimal solution. To speed up the algorithm convergence and achievegood throughput, a low-complexity and systematic initialization scheme is alsoproposed for the UAV trajectory design based on the simple circular trajectoryand the circle packing scheme. Extensive simulation results are provided todemonstrate the significant throughput gains of the proposed design as comparedto other benchmark schemes.
机译:由于无人飞行器的高机动性,灵活的部署和低成本,近来在协助无线通信方面引起了广泛的兴趣。本文考虑了启用多UAV的无线通信系统,其中使用多个安装有UAV的空中基站(BS)为地面上的一组用户提供服务。为了在用户之间实现公平的性能,我们通过优化多用户通信的调度和关联以及无人机的轨迹和功率控制,使下行通信中的所有地面用户的最小吞吐量最大化。公式化问题是一个混合整数非凸优化问题,需要解决。因此,我们提出了一种有效的迭代算法,通过应用块坐标下降法和连续凸优化技术来解决该问题。具体而言,在每次迭代中交替优化用户调度和关联,UAV轨迹和发射功率。特别是针对非凸型无人机的航迹和发射功率优化问题,分别解决了两个近似的凸优化问题。我们进一步表明,所提出的算法可以保证至少收敛到局部最优解。为了加快算法的收敛速度并获得良好的吞吐量,还提出了一种基于简单圆形轨迹和圆形填充方案的低复杂度,系统的初始化方案。提供了广泛的仿真结果,以证明与其他基准方案相比,所提出设计的吞吐量显着提高。

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