English

Energy optimization for Full-Duplex Wireless-Powered IoT Networks using Rotary-Wing UAV with Multiple Antennas

Systems and Control 2023-07-06 v1 Systems and Control Signal Processing

Abstract

In this paper, we propose a novel design for the rotary-wing unmanned aerial vehicle (UAV)-enabled full-duplex (FD) wireless-powered Internet of Things (IoT) networks. In this network, the UAV is equipped with an antenna array, and the KK IoT sensors, which are distributed randomly, use single-antenna to communicate. By sending the energy, the UAV as a hybrid access point, charges the sensors and collects information from them. Then, to manage the time and optimize the energy, the sensors are divided into N groups, so that the UAV equipped with multi-input multi-output (MIMO) technology can serve the sensors in a group, during the total time TT. We provide a simple implementation of the wireless power transfer protocol in the sensors by using the time division multiple access (TDMA) scheme to receive information from the users. In other words, the sensors of each group receive energy from the UAV, when it hovers over the sensors of the previous group, and also when the UAV flies over the previous group to the current group. The sensors of each group send their information to the UAV, when the UAV is hovering over their group. Under these assumptions, we formulate two optimization problems: a sum throughput maximization problem, and a total time minimization problem. Numerical results show that our proposed optimal network provides better performance than the existing networks. In fact, our novel design can serve more sensors at the cost of using more antennas compared to that of the conventional networks.

Keywords

Cite

@article{arxiv.2307.02302,
  title  = {Energy optimization for Full-Duplex Wireless-Powered IoT Networks using Rotary-Wing UAV with Multiple Antennas},
  author = {Leyla Fathollahi and Mahmood Mohassel Feghhi and Mahmoud Atashbar},
  journal= {arXiv preprint arXiv:2307.02302},
  year   = {2023}
}

Comments

24 pages, 9 figures, Submitted for possible journal publication

R2 v1 2026-06-28T11:22:43.258Z