Research Article
Beacon in the Air: Optimizing Data Delivery for Wireless Energy Powered UAVs
@INPROCEEDINGS{10.1007/978-3-030-32388-2_15, author={Huajian Jin and Jiangming Jin and Yang Zhang}, title={Beacon in the Air: Optimizing Data Delivery for Wireless Energy Powered UAVs}, proceedings={Machine Learning and Intelligent Communications. 4th International Conference, MLICOM 2019, Nanjing, China, August 24--25, 2019, Proceedings}, proceedings_a={MLICOM}, year={2019}, month={10}, keywords={Unmanned Aerial Vehicle Wireless energy harvesting Markov decision process}, doi={10.1007/978-3-030-32388-2_15} }- Huajian Jin
Jiangming Jin
Yang Zhang
Year: 2019
Beacon in the Air: Optimizing Data Delivery for Wireless Energy Powered UAVs
MLICOM
Springer
DOI: 10.1007/978-3-030-32388-2_15
Abstract
UAV-aided Internet of Things (IoT) systems enable IoT devices to relay up-to-date information to base stations with UAVs, which extends the IoT network coverage and improves data transmission efficiency. To achieve a perpetual UAV data delivery system, simultaneous wireless data and power transfer (SWIPT) is employed for energy-constrained UAVs to harvest energy from wireless chargers to support data sensing and transmission from IoT devices (e.g., sensors) deployed at different locations. In this paper, the design objective is to pursue the optimal energy charging policy for each UAV considering the system states of location, the queue length and energy storage. We formulate and solve a Markov decision process for the UAV data delivery to optimally take the actions of energy charging, and data delivery to base stations. The performance evaluation shows that the proposed MDP scheme outperforms baseline schemes in terms of lower expected overall cost and high energy efficiency.