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Trajectory Optimization for Cellular-Connected UAVs with Disconnectivity Constraint

机译：断开连接约束的蜂窝连接过滤器的轨迹优化

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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.
机译：无人驾驶飞行器（无人机）的普及最近一直在增加，这归功于其增强的功能和降低制造成本。许多军事和民用申请涉及UAV用于USECASE / Missions，从监测到搜救来搜索和救援。然而，尽管他们的优势，无人机通常需要在普遍存在的网络连接附近成功实现他们的任务，这是一个具有挑战性的任务。在本文中，我们研究了具有断开持续时间约束的蜂窝连接的无人机的轨迹优化。也就是说，与最终位置的起始位置飞行的使命需要找到一条路径，在此期间它不会在该区域中的一个以上的地面基站（GBS）失去其蜂窝连接，而不是给定时间约束。由于问题难以最佳地解决，因此我们提出了一种基于多项式时间内的近似解的动态编程。在仿真中，我们表明，所提出的方法可以通过显着低计算成本实现近乎最佳结果，并且通过向近似增加更多粒度来增加其准确性。

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