Phase Shift Matrix Optimization for IRS-Aided Legitimate Monitoring

Abstract

This paper studies wireless covert monitoring technologies, where multiple legitimate monitors (LMs) make use of intelligent reflecting surface (IRS) to sustainably intercept information sent from a suspicious transmitter (ST) to a suspicious receiver (SR). In particular, we propose an IRS-aided active monitoring scheme aligning with the regular two-phase transmissions between the ST and SR. In the pilot-transmission (PT) phase, LMs adopt a pilot spoofing strategy, where LMs control an IRS to reflect pilot signals sent by the SR, leading the ST's channel estimation towards LMs' direction. In the data-transmission (DT) phase, the IRS is controlled to reflect the ST's signals in a way that the LMs' received signal-to-noise ratios (SNR) are optimized, while helping maintain the SR's received SNR beyond a certain threshold to achieve sustainable monitoring. We formulate a phase-shift-matrix optimization problem over PT and DT phases. The minorization-maximization (MM) algorithm was applied to deal with the non-convex optimization such that we can efficiently obtain the optimized phase-shift matrices. Simulation results presented demonstrate the SNR gain improvement and monitoring range expansion introduced by our proposed scheme over the traditional passive monitoring approach.