Performance Analysis of IRS-Assisted NOMA Under Practical SIC Impairments

Non-Orthogonal Multiple Access (NOMA) with Intelligent Reflecting Surfaces (IRS) forms an integral part of the new technologies that will provide significant benefits through increased efficiency in frequency usage, improved connection quality and an increase in fairness to all users extending into the implementation of future 6 G networks. This paper will provide extensive information regarding the performance evaluation of a downlink intelligent reflecting surface-assisted non-orthogonal multiple access (IRS-ANOMA) system operating under ideal (perfect) as well as non ideal (imperfect) successive interference cancellation (SIC) environments. The primary methods of evaluating the IRSANOMA systems performance are presented using Monte Carlo simulation techniques each simulation determines three performance metrics: the total achievable sum rate, energy efficiency (EE) and probability of outage, using realistic Rayleigh fading channel conditions. Two imperfect SIC scenarios with residual interference coefficients$\rho=0.01$and$\rho=0.1$are examined to capture practical decoder limitations. The simulation results also demonstrate that the IRS-ANOMA system improves performance, especially concerning both data rate (throughput) and reliability. Furthermore, optimized IRS phase configuration effectively maximizes the reflected signal power while reducing the required transmit power, leading to substantial improvements in energy efficiency. These results confirm the potential of IRS-ANOMA as an efficient and robust multiple access framework for next-generation wireless networks.