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Multi-Objective Optimization for UAV-Assisted Wireless Powered IoT Networks Based on Extended DDPG Algorithm

Yu, Y; Tang, J; Huang, J; Zhang, X; So, DKC; Wong, KK; (2021) Multi-Objective Optimization for UAV-Assisted Wireless Powered IoT Networks Based on Extended DDPG Algorithm. IEEE Transactions on Communications 10.1109/TCOMM.2021.3089476. Green open access

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Abstract

This paper studies an unmanned aerial vehicle (UAV)-assisted wireless powered IoT network, where a rotary-wing UAV adopts fly-hover-communicate protocol to successively visit IoT devices in demand. During the hovering periods, the UAV works on full-duplex mode to simultaneously collect data from the target device and charge other devices within its coverage. Practical propulsion power consumption model and non-linear energy harvesting model are taken into account. We formulate a multi-objective optimization problem to jointly optimize three objectives: maximization of sum data rate, maximization of total harvested energy and minimization of UAV’s energy consumption over a particular mission period. These three objectives are in conflict with each other partly and weight parameters are given to describe associated importance. Since IoT devices keep gathering information from the physical surrounding environment and their requirements to upload data change dynamically, online path planning of the UAV is required. In this paper, we apply deep reinforcement learning algorithm to achieve online decision. An extended deep deterministic policy gradient (DDPG) algorithm is proposed to learn control policies of UAV over multiple objectives. While training, the agent learns to produce optimal policies under given weights conditions on the basis of achieving timely data collection according to the requirement priority and avoiding devices’ data overflow. The verification results show that the proposed MODDPG (multi-objective DDPG) algorithm achieves joint optimization of three objectives and optimal policies can be adjusted according to weight parameters among optimization objectives.

Type: Article
Title: Multi-Objective Optimization for UAV-Assisted Wireless Powered IoT Networks Based on Extended DDPG Algorithm
Open access status: An open access version is available from UCL Discovery
DOI: 10.1109/TCOMM.2021.3089476
Publisher version: https://doi.org/10.1109/TCOMM.2021.3089476
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Internet of Things (IoT), wireless power transfer (WPT), unmanned aerial vehicle (UAV), multi-objective optimization (MOO), deep deterministic policy gradient (DDPG)
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Electronic and Electrical Eng
URI: https://discovery.ucl.ac.uk/id/eprint/10133705
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