Binary Intelligent Reflecting Surfaces Assisted OFDM Systems

Abstract

Intelligent reflecting surfaces (IRSs) enhance the performance of wireless systems by reflecting the incoming signals towards a desired user, especially in the mmWave bands. However, this requires optimizing the discrete reflection coefficients of the IRS elements, which crucially depends on the availability of accurate channel state information (CSI) of all links in the system. Further, in wideband systems employing orthogonal frequency division multiplexing (OFDM), a given IRS configuration cannot be simultaneously optimal for all the subcarriers, and hence the phase optimization is not straightforward. In this paper, we propose a novel IRS phase configuration scheme in OFDM systems by first leveraging the sparsity of the channel in the angular domain to estimate the CSI using simultaneous orthogonal matching pursuit (SOMP) algorithm, and then devising a novel and computationally efficient binary IRS phase configuration algorithm using majorization-minimization (MM). Simulation results illustrate the efficacy of the approach in comparison with the state-of-the-art.