Beamforming and Performance Evaluation for Intelligent Reflecting Surface Aided Wireless System with Hardware Impairments

Intelligent reflecting surface (IRS) can effectively control the wavefront of the impinging signals and has emerged as a cost-effective promising solution to improve the spectrum and energy efficiency of wireless systems. Most existing researches on IRS assume that the hardware operations are perfect. However, both physical transceiver and IRS suffer from inevitable hardware impairments in practice, which leads to severe system performance degradation and increases the complexity of beamforming optimization. Consequently, the existing researches on IRS, including channel estimation, beamforming optimization, spectrum and energy efficiency analysis, etc., cannot directly apply to the case of hardware impairments. In this paper, by taking hardware impairments into consideration, we conduct the joint transmit and reflect beamforming optimization and reevaluate the system performance. First, we characterize the closed-form estimators of direct and cascade channels in both cases of single-user and multi-user and analyze the impact of hardware impairments on channel estimation accuracy. Then, the optimal transmit beamforming solution is derived, and a gradient descent method-based algorithm is also proposed to optimize the reflect beamforming. Moreover, we analyze the three types of asymptotic channel capacities with respect to the transmit power, the antenna number, and the reflecting element number. Finally, in terms of the system energy consumption, we analyze the power scaling law and the energy efficiency. To the best of our knowledge, it is the first research comprehensively evaluating the impact of hardware impairments on IRS-assisted wireless systems.