Simultaneously Transmitting and Reflecting RIS Aided NOMA with Randomly Deployed Users

Abstract

To achieve 360 coverage, we investigate a simulta-neous transmitting and reflecting reconfigurable intelligent surfaces (STAR-RIS) aided downlink non-orthogonal multiple access (NOMA) network with randomly deployed users. For different scenarios, we first derive two STAR- RIS-aided channel models, namely the central limit model and the curve fitting model. More specifically, the central limit model fits the scenarios with numerous RIS elements while the curve fitting model can be extended to multi-cell scenarios. The analytical results reveal that 1) the central limit model has closed-form expressions calculated as the error functions, and 2) the curve fitting model can be closely modeled as a Gamma distribution. We then derive the closed-form outage probability expressions for the NOMA users. Numerical results indicate that 1) the two channel models match the simulation results well in low signal-to-noise-ratio (SNR) regions and perform as boundaries in high SNR regions, 2) the central limit model performs as an upper bound of the simulation results, while a lower bound can be obtained by the curve fitting model, and 3) the both users in the NOMA pair have no error floor.