Analytical Framework for IRS-NOMA With Hardware Impairment and Diversity Over Fading Encompassing Exponential and Hypergeometric Functions

Abstract

With the unprecedented growth of wireless devices and data-intensive applications across diverse communication domains, there is an increasing demand for enhanced spectral efficiency, wider coverage, and efficient power utilization. In this context, intelligent reflecting surfaces (IRS) and non-orthogonal multiple access (NOMA) have emerged as promising technologies to enhance coverage, capacity, and user fairness. While a large body of literature exists on their individual and joint performance, the development of a unified and generalized analytical framework remains largely unexplored for IRS-NOMA systems. To address these gaps, this work investigates an IRS NOMA system with receiver diversity under a generalized fading environment characterized by exponential and confluent hypergeometric functions, namely, kappa - & micro;/shadowed, extended eta - & micro;, and Beaulieu-Xie/shadowed distributions. The proposed framework improves both spectral efficiency and signal-to-noise ratio. Recognizing that ideal transceiver hardware is not available in practice, the analysis is extended to account for inherent hardware impairments, offering insights into the performance of realistic communication setups. Closed-form analytical expressions are derived for several key performance metrics, including the amount of fading, channel quality estimation index, rate outage probability, channel capacity under optimal rate adaptation, and channel inversion with fixed rate schemes. Additionally, asymptotic analysis is provided for both low-and high-power regimes to yield deeper insights into system behavior. The derived analytical results are validated through Monte-Carlo simulations, which demonstrate an excellent match with theoretical predictions, confirming their accuracy and practical relevance.