Impact of Channel Correlation and Hardware Impairments on Large Intelligent Surfaces-Aided Communication Systems

Abstract

Large Intelligent Surfaces (LIS) are promising in terms of what they can offer to 6G and beyond communication networks. As such, they have recently attracted considerable attention in the research community. This technique allows the operators to control the environment in a strategic way so as to improve the communication system performance. This work studies the effect of hardware impairments (HWIs) on the LIS-Aided wireless communication system under correlated channel conditions. In specific, we look at the impact on the system performance. We also give a deterministic approximation function of the average bit error rate (ABER) for a large number of reflectors and a tight approximation of the outage probability (OP). Extensive Monte Carlo simulations are provided to verify the analytical results, which show that the system performance saturates at a high signal-to-noise ratio (SNR) due to the HWIs. Moreover, this degradation is exacerbated when the channels demonstrate strong correlation conditions. However, the HWIs have a dominant effect and the correlation impact diminishes with a larger number of reflectors.