Research Article
Joint User Scheduling and UAV Height Control for Smart Wearable Device Charging Network
@INPROCEEDINGS{10.1007/978-3-031-65123-6_31, author={Hongjing Ji and Xiaojie Wang and Zhaolong Ning}, title={Joint User Scheduling and UAV Height Control for Smart Wearable Device Charging Network}, proceedings={Quality, Reliability, Security and Robustness in Heterogeneous Systems. 19th EAI International Conference, QShine 2023, Shenzhen, China, October 8 -- 9, 2023, Proceedings, Part II}, proceedings_a={QSHINE PART 2}, year={2024}, month={8}, keywords={Wearable networks wireless power transfer (WPT) user scheduling UAV altitude control constrained deep reinforcement learning}, doi={10.1007/978-3-031-65123-6_31} }- Hongjing Ji
Xiaojie Wang
Zhaolong Ning
Year: 2024
Joint User Scheduling and UAV Height Control for Smart Wearable Device Charging Network
QSHINE PART 2
Springer
DOI: 10.1007/978-3-031-65123-6_31
Abstract
This paper studies the user device time slot scheduling and Unmanned Aerial Vehicle (UAV) height control problem in the UAV-assisted smart wearable charging network. In contrast to traditional studies that only consider UAVs to serve user devices at a fixed height and ignore the flexibility and mobility of UAVs. We consider the UAV coverage and limited battery energy constraints as well as the charging demand of wearable devices; aiming to maximize network throughput. Specifically, first we formulate the problem as a Constrained Markov Decision Process (CMDP), and then propose a Proximal Policy Optimization (PPO)-CMDP algorithm for solving the formulated problem based on the Lagrangian original pairwise strategy optimization. Finally, the results from simulation evaluations show that our proposed algorithm can learn the mobility policy of UAV and the time slot scheduling policy of wearable devices to maximize the throughput of the achieved network while ensuring that the power of the UAV satisfies the constraint, and outperforms the baseline scheme.
