Minimum-SNR Maximization for Robust IRS-assisted Legitimate Monitoring System

This paper focuses on the distributed intelligent reflecting surface (IRS) assisted legitimate monitoring system to improve the availability of monitoring nodes, so that the legitimate monitors (LMs) can stably and sustainably conduct covert monitoring on both sides of suspicious communication. Our active monitoring scheme is consistent with the conventional dual-stage transmissions between suspicious transmitter (ST) and suspicious receiver (SR). Firstly, in the process of SR sending pilot to ST (PT stage), LMs control the phase shifts of IRSs and reflect the signal sent by SR to ST for pilot spoofing, resulting in the deviation of ST's channel estimation, and the suspicious information is leaked to the IRSs during data transmission (DT) stage. Considering that non-sudden factors in the real scene will destroy some monitoring parties resulting in monitoring interruption and system robustness damage, LMs control the IRSs' phase shifts to maximize the received SNR of the monitoring party with the worst channel quality in the DT stage. The above process can be equivalent to the joint optimization of IRSs' phase shift over PT and DT stages. The unit module constraint leads to the non convexity of problems, so Majorization-Minimization (MM) algorithm and Alternating Direction Method of Multipliers (ADMM) algorithm are used to solve them alternately. Both algorithms can guarantee at least convergence to the local optimal solution. Numerical results show that our minimum-SNR maximization scheme is superior to other benchmark schemes. It is also confirmed that the distributed IRSs system is better than the centralized IRS system.