Weighted Harvest-Then-Transmit: UAV-Enabled Wireless Powered Communication Networks

Abstract

This paper proposes an unmanned aerial vehicle (UAV)-enabled wireless-powered communication network (WPCN), which consists of a hybrid access point (H-AP), a UAV, and nodes. The H-AP broadcasts energy to all nodes, and the nodes harvest and use the energy for information transmission. However, far-apart nodes from the H-AP hardly harvest the energy and they require more energy for the same throughput as near-apart nodes due to distance-dependent signal attenuation, which is called the doubly near–far problem. To overcome the doubly near–far problem, we propose a weighted harvest-then-transmit protocol. In the proposed protocol, we consider that the channel power gain changes according to the location of nodes, whereas it has remained constant in most conventional WPCNs. The UAV acts as a mobile H-AP, where the UAV performs weighted energy transfer and receives information to/from all encountering far-apart nodes with the better channel power gain. For the UAV, we consider the flight path optimization by implementing a regression algorithm in terms of energy efficiency. Under these considerations, we aim to maximize the sum-throughput of all nodes based on the weighted harvest-then-transmit protocol, by using convex optimization techniques. The optimal time allocation is investigated for far-apart nodes and near-apart nodes sequentially, to solve the doubly near–far problem. Simulation results show that the proposed UAV-enabled WPCN outperforms the conventional WPCN with a fixed H-AP in terms of the sum-throughput maximization.

Keywords

• Convex optimization
• doubly-near-far problem
• sum-throughput maximization
• unmanned aerial vehicle
• UAV-enabled wireless-powered communication networks
• weighted harvest-then-transmit