Fairness optimization in RIS-FAS NOMA networks under practical impairments

For future wireless networks beyond 5G (B5G), integrating and dynamically reconfiguring advanced technologies is crucial for achieving high spectral efficiency and ensuring massive user connectivity. This work proposes a practical and improved millimeter-wave non-orthogonal multiple access (NOMA) framework that synergistically integrates a reconfigurable intelligent surface (RIS) with fluid antenna system (FAS) receivers. The port selection diversity of FAS is utilized to enhance signal reception and aid interference suppression during successive interference cancellation (SIC). A central contribution is the development of a max–min fairness-based power allocation (PA) algorithm designed to equalize the ergodic capacities of NOMA users by maximizing the minimum achievable signal-to-interference-plus-noise ratio (SINR) under imperfect SIC conditions, ensuring a fair and balanced rate distribution. Crucially, three major practical impairment sources, such as the combined impact of channel state information (CSI) with bounded estimation error, finite-resolution RIS phase-shift quantization, and residual interference due to imperfect SIC with configurable error levels are explicitly modeled and analyzed. Simulation results evaluate the system performance across various transmit power and FAS port numbers, conclusively demonstrating that the RIS-FAS integration yields substantial gains in ergodic capacity, successfully balances spectral efficiency with user fairness, and highlights the critical trade-offs necessary for realistic networks.