Trajectory Design for UAV-Based Internet-of-Things Data Collection: A Deep Reinforcement Learning Approach. (arXiv:2107.11015v1 [cs.IT] CROSS LISTED)

In this paper, we investigate an unmanned aerial vehicle (UAV)-assisted
Internet-of-Things (IoT) system in a sophisticated three-dimensional (3D)
environment, where the UAV's trajectory is optimized to efficiently collect
data from multiple IoT ground nodes. Unlike existing approaches focusing only
on a simplified two-dimensional scenario and the availability of perfect
channel state information (CSI), this paper considers a practical 3D urban
environment with imperfect CSI, where the UAV's trajectory is designed to
minimize data collection completion time subject to practical throughput …

arxiv data data collection design internet learning reinforcement learning