This paper studies a rechargeable unmanned aerial vehicle (UAV) assisted wireless network, where a UAV is dispatched to disseminate information to a group of ground terminals (GTs) and returns to a recharging station (RS) before the on-board battery is depleted. The central aim is to design a UAV trajectory with the minimum total time duration, including the flight and recharging time, by optimizing the flying velocity, transmit power and hovering positions jointly. A flow-based mathematical programming formulation is proposed to provide optimal for joint optimization of flying and recharging time. Furthermore, to attack the curse of dimensionality for optimal decision making, a two-step method is proposed. In the first step, the UAV hovering positions is fixed and initialize a feasible trajectory design by solving a travelling salesman problem with energy constraints (TSPE) problem. In the second step, for the given initial trajectory, the time consumption for each sub-tour is minimized by optimizing the flying velocity, transmit power and hovering positions jointly. Numerical results show that the proposed method outperforms state of art techniques and reduces the aggregate time duration in an efficient way.
翻译:本文研究的是可再充电的无人驾驶飞行器辅助无线网络,无人驾驶飞行器被派遣向一组地面终端(GTs)传播信息,并在机载电池用完之前返回充电站(RS),中心目标是通过优化飞行速度、传输动力和悬浮位置共同优化飞行速度、传输动力和充电时间,设计具有最低总时间的无人驾驶飞行器轨迹,包括飞行和充电时间。提议采用流动数学编程方式,为联合优化飞行和再充电时间提供最佳的优化。此外,为了打击空间的诅咒,建议采用两步法,首先确定无人驾驶飞行器悬浮位置,并启动可行的轨迹设计,在能源限制(TSPE)问题下解决流动销售人员问题。第二步是,通过优化飞行速度、传输动力和悬浮位置联合优化,使每个子卫星的消耗时间最小化。数字结果显示,拟议方法超越了艺术技术的状态,并高效地缩短了总时间。