In this paper, we consider a cellular-connected unmanned aerial vehicle (UAV) with an information collection and transmission mission for multiple ground targets. Specifically, the UAV is required to collect a fixed amount of information of each target by hovering at a pre-determined location (via e.g., photography/videography/sensing), and transmit all the collected information to the cellular network during its flight. We aim to jointly optimize the UAV's trajectory and the information collection order of the ground targets to minimize the mission completion time. The formulated problem is NP-hard due to the need of visiting the information collection locations for all targets; moreover, the UAV's trajectories over different time durations are coupled in non-convex constraints for ensuring information transmission completion. To handle this difficult problem, we first propose a structured communication protocol between the UAV and the cellular network, which decouples the UAV's trajectory designs in different time durations. Then, under the proposed protocol, we establish an equivalent graph-based model for the considered problem, and devise a low-complexity algorithm for finding an approximate solution by exploiting the problem structure and leveraging graph theory. Numerical results show that our proposed design achieves efficient information collection and transmission, and outperforms various benchmark schemes.

翻译：在本文中,我们考虑的是一种与蜂窝相连的无人驾驶飞行器(无人驾驶飞行器),该飞行器为多个地面目标收集和传播信息,具体而言,无人驾驶飞行器需要通过在预定地点(如摄影/摄影/摄影/遥感)徘徊,收集每个目标的固定数量的信息,并在飞行期间将收集到的所有信息传送到蜂窝网络;我们的目标是共同优化无人驾驶飞行器的轨迹和地面目标的信息收集顺序,以尽量减少任务完成时间;由于需要访问所有目标的信息收集地点,因此形成的问题很硬;此外,无人驾驶飞行器在不同时间段的轨迹中收集固定数量的信息,同时受到非凝固的限制,以确保信息传输完成。为了处理这一难题,我们首先提议在无人驾驶飞行器和移动网络之间订立结构有序的通信协议,将无人驾驶飞行器的轨迹设计在不同的时间段内进行分解。然后,根据拟议的议定书,我们为所考虑的问题建立一个等量的图形模型,并设计一种低复杂性算法,通过利用高效的问题结构和利用基准数据模型,以及利用各种基准数据采集,从而显示我们所提出的结果。