Phase Shift Optimization on Intelligent Reflecting Surface with Hardware Impairment

Intelligent Reflecting Surface (IRS), consisting of low-cost passive reflective elements (PEs), is envisioned as a rev-olutionary technology for fifth-generation (5G) and beyond wireless communication networks. By optimizing the phase shift of passive reflective elements, communication performance such as wireless coverage, energy efficiency, and capacity can be improved. However, the performance of an IRS can be degraded due to inherent hardware impairment (HWI) in the PEs. In this paper, we investigate the problem of phase shift optimization in the presence of inherent hardware impairment (HWI) appearing at PEs, which is modeled as uniformly distributed random phase shift errors (PSEs). Specifically, we formulate an optimization problem that aims to maximize the downlink data rate while considering the impact of PSEs. Since the resulting optimization problem is non-convex, we transform it into a semidefinite programming (SDP) problem that can be solved efficiently. Considering the randomness of PSEs, we derive the expectation of the objective function to further facilitate the optimization procedure. Numerical results demonstrate the effectiveness of the proposed optimization method and show that PSEs degrade the data rates of IRS-assisted communication systems.