Performance Analysis of IRS-Assisted NOMA Underlay CRN with Dynamic IRS Allocation

We analyze the performance of an intelligent reflecting surface (IRS)-assisted non-orthogonal multiple access (NOMA) underlay communication. IRS is particularly well-suited for underlay cognitive radio networks, as it helps limit transmit power to ensure the primary user’s interference threshold is not exceeded. In this study, a secondary base station transmits information to two secondary users: a near user (NU) and a far user (FU). We propose a dynamic IRS allocation approach where, during each transmission interval, the number of selected IRS elements is based on the channel between BS to IRS, IRS to NU, and IRS to FU. This paper analyzes the outage probability, outage floor, and sum-throughput, demonstrating that the proposed approach outperforms the conventional analysis, with a sum-throughput improvement of 65%,74%,80% for increasing IRS elements 4,8,16. Monte Carlo simulations verify the analytical expressions.