Distributed and Optimal Resource Allocation for Power Beacon-Assisted Wireless-Powered Communications

TL;DR

This paper develops distributed algorithms for optimal resource allocation in a wireless-powered communication network with a power beacon, addressing both cooperative and non-cooperative scenarios to maximize throughput.

Contribution

It introduces novel water-filling and auction-based distributed algorithms for resource allocation in PB-assisted wireless-powered networks, considering cooperation and self-interest.

Findings

Algorithms converge successfully in simulations.

System parameters significantly affect throughput.

Proposed methods outperform baseline approaches.

Abstract

In this paper, we investigate optimal resource allocation in a power beacon-assisted wireless-powered communication network (PB-WPCN), which consists of a set of hybrid access point (AP)-source pairs and a power beacon (PB). Each source, which has no embedded power supply, first harvests energy from its associated AP and/or the PB in the downlink (DL) and then uses the harvested energy to transmit information to its AP in the uplink (UL). We consider both cooperative and non-cooperative scenarios based on whether the PB is cooperative with the APs or not. For the cooperative scenario, we formulate a social welfare maximization problem to maximize the weighted sum-throughput of all AP-source pairs, which is subsequently solved by a water-filling based distributed algorithm. In the non-cooperative scenario, all the APs and the PB are assumed to be rational and self-interested such that incentives from each AP are needed for the PB to provide wireless charging service. We then formulate an auction game and propose an auction based distributed algorithm by considering the PB as the auctioneer and the APs as the bidders. Finally, numerical results are performed to validate the convergence of both the proposed algorithms and demonstrate the impacts of various system parameters.