Intelligent Reflecting Surface-Aided Covert Ambient Backscatter Communication

This paper presents a covert ambient backscatter communication (AmBC) system aided by the intelligent reflecting surface (IRS), where an IRS is used as a beamformer to help Tag for covert AmBC. Technically, we derive the expression of the Kullback-Leibler (KL) divergence to measure the detection performance of the warden. To fight against the warden's detection, we propose a joint IRS's beamforming and Tag's reflection coefficient optimization scheme to maximize the covert AmBC rate subject to a key constraint metric of the KL divergence. To solve the non-convex problem, we formulate it as Fractional Programming (FP) for the linear iterations, and use the Majorization-Minimization (MM) algorithm to obtain the optimal parameters of IRS and Tag. Moreover, we investigate the covert performance with the imperfect channel state information of the warden's link (WCSI) with Tag and IRS. Numerical results show the covert performance of the system, and illustrate the superiority of the IRS's assistance to the covert backscatter efficiency. The simulations also show that the channel estimated error of Tag-Willie link has a negative impact on the covert backscatter efficiency, while the channel estimated errors of IRS-Willie link have the positive influence on the contrary.