Channel Modeling for IRS-Assisted MIMO Systems to Analyze the Effects of Nonlinear Distortions in Wireless Environments

B5G networks are envisioned to meet higher spectral efficiencies through advanced transmission technologies. Consequently, it is important to comprehend the typical propagation characteristics of wireless communication medium that experience multipath effects, fading, shadowing, and nonlinear distortions. Most of these challenging issues arise under non-line of sight conditions concerning the propagation medium, which deteriorates the quality of the signal received due to uncontrollable channel variations. The recent advances in Intelligent Reflecting Surface (IRS), enable a dynamically alterable wireless environment to achieve flexible reconfigurable channels. The deployment of IRS can evidently bypass the obstacles through smart reflections and shall mitigate channel fading impairments. Motivated by the potentials of the IRS, this paper investigates the performance of IRS-assisted multi-input-multi-output (MIMO) systems to analyze the effect of nonlinear distortions and system adaptation over IID and non-IID Gaussian channel variations. The simulations show the distortion levels with the help of power spectral density for correlated or uncorrelated channel conditions. Furthermore, Monte Carlo simulations are performed to understand the behavior of the wireless system through the analysis of bit error rate (BER) vs signal-to-noise ratio (SNR), Ergodic Channel capacity vs SNR in the presence of IID-Gaussian/ non-IID Gaussian and in-band nonlinear distortions. Additionally, in realistic channel conditions, it is observed that the effect of increasing the number of IRS elements increases the BER performance of ~8dB in both IID and non-IID Gaussian variations. Finally, improvement in the performance of ergodic capacity of 5 bps/Hz has been observed at a fixed SNR of 5dB.