Secrecy Sum-Rate Maximization for Active IRS-Assisted MIMO-OFDM SWIPT System
Xingxiang Peng, Peiran Wu, Junhui Zhao, Minghua Xia

TL;DR
This paper explores the use of active IRS in MIMO-OFDM SWIPT systems to enhance secrecy sum-rate by leveraging active beamforming and artificial noise, outperforming passive IRS and non-IRS setups especially under low power or blocked links.
Contribution
It introduces a novel active IRS-assisted MIMO-OFDM SWIPT system model and proposes algorithms for maximizing secrecy sum-rate considering practical constraints.
Findings
Active IRS outperforms passive IRS and non-IRS systems in secrecy sum-rate.
Increasing the active IRS power budget significantly improves secrecy performance.
The proposed algorithms effectively optimize system parameters for enhanced security.
Abstract
The propagation loss of RF signals is a significant issue in simultaneous wireless information and power transfer (SWIPT) systems. Additionally, ensuring information security is crucial due to the broadcasting nature of wireless channels. To address these challenges, we exploit the potential of active intelligent reflecting surface (IRS) in a multiple-input and multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) SWIPT system. The active IRS provides better beamforming gain than the passive IRS, reducing the "double-fading" effect. Moreover, the noise introduced at the active IRS can be used as artificial noise (AN) to jam eavesdroppers. This paper formulates a secrecy sum-rate maximization problem related to precoding matrices, power splitting (PS) ratios, and the IRS matrix. Since the problem is highly non-convex, we propose a block coordinate descent (BCD)-based…
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