IRS-Aided Communications With Finite-Alphabet Inputs: Analysis and Design

This letter analyzes the ergodic mutual information (EMI) of an intelligent reflecting surface (IRS)-aided communication system with finite-alphabet inputs relying on statistical channel state information. For the sake of unveiling important system design insights, asymptotic analyses are performed to the EMI in the regime of high signal-to-noise ratio (SNR). It is found that the EMI converges to some constant in the high-SNR regime and the rate of convergence is determined by the diversity order and the array gain. On this basis, two efficient algorithms are proposed to design the phase shifts of the IRS in order to improve the array gain as well as the EMI. All the analytical results are verified through computer simulations.