Covert Surveillance via Proactive Eavesdropping Under Channel Uncertainty

Surveillance performance is studied for a wireless eavesdropping system, where full-duplex legitimate monitor eavesdrops suspicious user's link with artificial noise (AN) assistance. Different from the existing works, receiver assumed to be capable of detecting presence AN. Once such detects AN, user will stop transmission, which can therefore degrade surveillance performance. Hence, improve performance, AN should transmitted covertly low detection probability. Under these assumptions, an optimization problem formulated maximize under covert constraint. Then, based on ability at receiver, novel scheme proposed solve using iterative search. Moreover, we investigate impact both suspicious-transmitter-to-suspicious-receiver and monitor-to-suspicious-receiver links uncertainties Simulations are performed verify analyses. We show that uncertainty in enhance while