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Trajectory Optimization in UAV-Assisted Cellular Networks under Mission Duration Constraint

机译:任务持续时间约束下的无人机辅助蜂窝网络的轨迹优化

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In this paper, we address the problem of finding the optimal trajectory for an unmanned aerial vehicle (UAV) for improving the wireless coverage of a terrestrial cellular network. In particular, we consider a UAV that is tasked to travel from one point to another within a given time constraint, and it can also simultaneously assist the cellular network by providing wireless coverage during its mission. Considering an interference limited downlink of a cellular network, we formulate an optimization problem for maximizing the proportional-fair (PF) data rate of the cellular network and explore dynamic programming (DP) technique for finding the optimum UAV trajectory. We also explore the optimal UAV trajectories associated with maximum sum-rate and 5th percentile spectral efficiency (5pSE) rate and compare the capacity and coverage performance of the three approaches. Numerical simulations show that the maximum sum-rate trajectory provides the best per user capacity whereas, the optimal PF trajectory yields higher coverage probability than the other two trajectories. The optimal trajectories are generally infeasible to follow exactly as the UAVs can not take sharp turns due to kinematic constraints. Hence, we generate smooth trajectories using Bezier curve.
机译:在本文中,我们解决了寻找无人空中车辆(UAV)的最佳轨迹的问题,用于改善地面蜂窝网络的无线覆盖。特别地,我们考虑一个任务以在给定的时间约束内从一个点到另一个点的UAV,并且它还可以通过在其任务期间提供无线覆盖来同时辅助蜂窝网络。考虑到蜂窝网络的干扰有限的下行链路,我们制定了用于最大化蜂窝网络的比例公平(PF)数据速率的优化问题,并探索用于找到最佳UAV轨迹的动态编程(DP)技术。我们还探讨了最佳的UAV轨迹,与最大总和率和第5百分位谱效率(5PSE)速率相关,并比较了三种方法的容量和覆盖性能。数值模拟表明,最大和速率轨迹提供了每个用户容量的最佳速度,而最佳PF轨迹产生比其他两个轨迹更高的覆盖概率。最佳轨迹通常是不可行的,因为由于对运动约束而言,无人机不能急剧转弯。因此,我们使用Bezier曲线产生平滑的轨迹。

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