Robust Beamforming Design and Time Allocation for IRS-assisted Wireless Powered Communication Networks

TL;DR

This paper proposes a novel IRS-assisted wireless powered communication network architecture that optimizes energy and information transfer under imperfect channel information, using advanced optimization techniques to improve power efficiency for IoT devices.

Contribution

It introduces a joint optimization framework for IRS-assisted WPCN considering imperfect CSI and non-linear energy harvesting, employing alternating optimization and DC programming techniques.

Findings

Significant reduction in HAP transmit energy compared to benchmarks.

Effective joint optimization of time, beamforming, and IRS reflection coefficients.

Validation through numerical simulations demonstrating improved performance.

Abstract

In this paper, a novel intelligent reflecting surface (IRS)-assisted wireless powered communication network (WPCN) architecture is proposed for power-constrained Internet-of-Things (IoT) smart devices, where IRS is exploited to improve the performance of WPCN under imperfect channel state information (CSI). We formulate a hybrid access point (HAP) transmit energy minimization problem by jointly optimizing time allocation, HAP energy beamforming, receiving beamforming, user transmit power allocation, IRS energy reflection coefficient and information reflection coefficient under the imperfect CSI and non-linear energy harvesting model. On account of the high coupling of optimization variables, the formulated problem is a non-convex optimization problem that is difficult to solve directly. To address the above-mentioned challenging problem, alternating optimization (AO) technique is applied to decouple the optimization variables to solve the problem. Specifically, through AO, time allocation, HAP energy beamforming, receiving beamforming, user transmit power allocation, IRS energy reflection coefficient and information reflection coefficient are divided into three sub-problems to be solved alternately. The difference-of-convex (DC) programming is used to solve the non-convex rank-one constraint in solving IRS energy reflection coefficient and information reflection coefficient. Numerical simulations verify the superiority of the proposed optimization algorithm in decreasing HAP transmit energy compared with other benchmark schemes.