Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/26729
Title: Energy Minimization for UAV-Enabled Wireless Power Transfer and Relay Networks
Authors: He, Z
Ji, Y
Wang, K
Xu, W
Shen, H
Wang, N
You, X
Keywords: trajectory;autonomous aerial vehicles;wireless communication;optimization;Internet of Things;relay networks;quality of service
Issue Date: 31-May-2023
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Citation: He, Z. et al. (2023) 'Energy Minimization for UAV-Enabled Wireless Power Transfer and Relay Networks', IEEE Internet of Things Journal, 10 (21), pp. 19141 - 19152. doi: 10.1109/jiot.2023.3281584.
Abstract: In this article, we consider an unmanned aerial vehicle (UAV)-enabled wireless power transfer (WPT) and relay communication network consisting of a base station (BS), a UAV, and multiple ground users. The UAV acts as both a wireless power transmission source and an uplink communication relay. Specifically, an entire transmission period of the considered system is divided into two stages. In the first stage, the UAV transfers the power to the ground users along a well-optimized flight trajectory and meanwhile, the users transmit data to the UAV using the harvested energy. Subsequently, in the second stage, the UAV flies to the vicinity of the BS and forwards the data to the BS. For the purpose of minimizing the energy consumed by the UAV, we jointly optimize the time durations of the two stages, the UAV’s transmit powers for WPT and data forwarding, as well as its flight trajectory, subject to the constraints of the Quality of Service (QoS), the information forwarding, the energy causality, and the mobility of the UAV. The involved optimization problem is nonconvex and highly intractable. To this end, we propose an efficient alternating algorithm to iteratively solve the two subproblems with respect to the time durations of the two stages and the UAV’s transmit powers and trajectory, respectively. The first subproblem has a closed-form optimal solution and the second subproblem is handled by addressing a surrogate convex problem based on the technique of successive convex approximation. Finally, the simulation results confirm the superiority of our proposed algorithm.
URI: https://bura.brunel.ac.uk/handle/2438/26729
DOI: https://doi.org/10.1109/jiot.2023.3281584
Other Identifiers: ORCID iD: Zhenyao He https://orcid.org/0000-0002-4655-7635
ORCID iD: Yukuan Ji https://orcid.org/0000-0002-6925-2471
ORCID iD: Kezhi Wang https://orcid.org/0000-0001-8602-0800
ORCID iD: Wei Xu https://orcid.org/0000-0001-9341-8382
ORCID iD: Hong Shen https://orcid.org/0000-0002-2788-0349
ORCID iD: Ning Wang https://orcid.org/0000-0001-9403-3417
ORCID iD: Xiaohu You https://orcid.org/0000-0002-0809-8511
Appears in Collections:Dept of Computer Science Research Papers

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