To analyze and enhance the performance of IRS-aided NOMA and OMA wireless networks by deriving channel statistics and evaluating outage probability, ergodic rate, and diversity order under Nakagami-m fading conditions.
Intelligent Reflecting Surfaces (IRS) have emerged as a promising technology to enhance wireless communication by dynamically reconfiguring the propagation environment. This paper investigates the performance of IRS-aided downlink and uplink networks under Non-Orthogonal Multiple Access (NOMA) and Orthogonal Multiple Access (OMA) schemes. The primary objective is to improve coverage, outage probability, ergodic rate, and diversity order by deploying IRS to assist cell-edge users in communication with the base station. New channel statistics are derived for the base station-IRS-user device (BS-IRS-UD) link under Nakagami-m fading, enabling a detailed performance analysis. Closed-form expressions for outage probability and ergodic rate are obtained, followed by asymptotic approximations to determine diversity order and high-SNR slope. Results demonstrate that IRS significantly improves system performance compared to full-duplex decode-and-forward relay (FDR)-aided networks, especially in the high-SNR regime. The study further highlights that diversity order depends on the number of IRS reflecting elements and fading parameters, whereas the high-SNR slope remains independent of these factors. Simulation results validate the theoretical analysis, confirming the advantages of IRS in optimizing NOMA and OMA networks. This work provides valuable insights into IRS deployment strategies for next-generation wireless communication systems.
Keywords: Intelligent Reflecting Surface (IRS), Non-Orthogonal Multiple Access (NOMA), Orthogonal Multiple Access (OMA), Outage Probability, Ergodic Rate, Diversity Order, High-SNR Slope, Wireless Communication, Nakagami-m Fading, Full-Duplex Relay.
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