Joint Active and Passive Beamforming Optimization for Intelligent Reflecting Surface Assisted SWIPT Under QoS Constraints

TLDR

Intelligent reflecting surfaces (IRS) are a revolutionary technology that uses massive low‑cost passive elements with adjustable phase shifts to achieve high passive beamforming gains, thereby enhancing spectrum and energy efficiency in wireless networks, especially for RF‑based wireless power transfer. This paper investigates an IRS‑assisted simultaneous wireless information and power transfer (SWIPT) system and seeks to minimize the access point’s transmit power by jointly optimizing its precoders and the IRS phase shifts while satisfying SINR constraints for information users and energy harvesting constraints for energy users. To address the resulting non‑convex optimization, the authors transform the QoS constraints and propose an efficient iterative penalty‑based algorithm, and further develop a parallel phase‑shift optimization that exploits the short‑range coverage of IRSs to reduce computational complexity. Simulation results demonstrate that deploying multiple IRSs significantly improves SWIPT performance, with the proposed algorithms outperforming benchmark schemes and revealing the impact of IRS on transmitter/receiver design.

Abstract

Intelligent reflecting surface (IRS) is a new and revolutionizing technology for achieving spectrum and energy efficient wireless networks. By leveraging massive low-cost passive elements that are able to reflect radio-frequency (RF) signals with adjustable phase shifts, IRS can achieve high passive beamforming gains, which are particularly appealing for improving the efficiency of RF-based wireless power transfer. Motivated by the above, we study in this paper an IRS-assisted simultaneous wireless information and power transfer (SWIPT) system. Specifically, a set of IRSs are deployed to assist in the information/power transfer from a multi-antenna access point (AP) to multiple single-antenna information users (IUs) and energy users (EUs), respectively. We aim to minimize the transmit power at the AP via jointly optimizing its transmit precoders and the reflect phase shifts at all IRSs, subject to the quality-of-service (QoS) constraints at all users, namely, the individual signal-to-interference-plus-noise ratio (SINR) constraints at IUs and the energy harvesting constraints at EUs. However, this optimization problem is non-convex with intricately coupled variables, for which the existing alternating optimization approach is shown to be inefficient as the number of QoS constraints increases. To tackle this challenge, we first apply proper transformations on the QoS constraints and then propose an efficient iterative algorithm by applying the penalty-based optimization method. Moreover, by exploiting the short-range coverage of IRS, we further propose a more computationally efficient algorithm by optimizing the phase shifts at all IRSs in parallel. Simulation results demonstrate the effectiveness of employing multiple IRSs for enhancing the performance of SWIPT systems as well as the significant performance gains achieved by our proposed algorithms over benchmark schemes. The impact of IRS on the transmitter/receiver design for SWIPT is also unveiled.