Trajectory Optimization for Cellular-Connected UAVs with Disconnectivity Constraint
Trajectory Optimization for Cellular-Connected UAVs with Disconnectivity Constraint
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DOI：
10.1109/iccw.2018.8403623
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发表时间：
2018-05
期刊：
影响因子：
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通讯作者：
E. Bulut;Ismail Güvenç
中科院分区：
文献类型：
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作者：
E. Bulut;Ismail Güvenç
最近，由于无人机的功能增强和制造成本降低，无人机的受欢迎程度越来越高。许多军事和民用应用涉及无人机用于从监视到搜索和救援的用例/任务。然而，尽管具有优势，无人机通常需要几乎无处不在的网络连接才能成功完成任务，这是一项具有挑战性的任务。本文研究了具有断开时间约束的元胞连接无人机的轨迹优化问题。也就是说，具有从起始位置飞行到最终位置的任务的无人机需要找到一条路径，在此过程中，它不会在给定的时间限制内通过该区域的一个地面基站（GBS）失去蜂窝连接。针对该问题难以最优求解的特点，提出了一种基于动态规划的多项式近似求解方法。在仿真中，我们证明了所提出的方法可以以非常低的计算成本获得接近最优的结果，并且可以通过在近似中添加更多粒度来提高其精度。
The popularity of unmanned aerial vehicles (UAVs) has been increasing recently thanks to their enhanced functionalities and decreasing manufacturing costs. Many military and civilian applications involve UAVs for usecases/missions ranging from surveillance to search and rescue. However, despite their advantages, UAVs typically require near ubiquitous network connectivity for a successful fulfillment of their missions, which is a challenging task to achieve. In this paper, we study the trajectory optimization for cellular- connected UAVs with a disconnection duration constraint. That is, the UAV with the mission of flying from a start location to a final location needs to find a path during which it does not lose its cellular connection via one of the ground base stations (GBS) in the area more than a given time constraint. As the problem is difficult to be solved optimally, we propose a dynamic programming based approximate solution within polynomial time. In simulations, we show that the proposed approach can achieve close-to-optimal results with remarkably low computation costs and its accuracy could be increased by adding more granularity to the approximation.