Open Access

ARTICLE

NOMA with Adaptive Transmit Power Using Intelligent Reflecting Surfaces

Raed Alhamad^1,*, Hatem Boujemaa²

1 Information Technology Department, Saudi Electronic University, Riaydh, Saudi Arabia
2 University of Carthage, SUPCOM-COSIM, Ariana, 2083, Tunisia

* Corresponding Author: Raed Alhamad. Email:

Computer Systems Science and Engineering 2023, 45(2), 2059-2070. https://doi.org/10.32604/csse.2023.032610

Received 23 May 2022; Accepted 24 June 2022; Issue published 03 November 2022

Abstract

In this article, we use Intelligent Reflecting Surfaces (IRS) to improve the throughput of Non Orthogonal Multiple Access (NOMA) with Adaptive Transmit Power (ATP). The results are valid for Cognitive Radio Networks (CRN) where secondary source adapts its power to generate low interference at primary receiver. In all previous studies, IRS were implemented with fixed transmit power and previous results are not valid when the power of the secondary source is adaptive. In CRN, secondary nodes are allowed to transmit over the same band as primary users since they adapt their power to minimize the generated interference. Each NOMA user has a subset of dedicated reflectors. At any NOMA user, all IRS reflections have the same phase. CRN-NOMA using IRS offers 7, 13, 20 dB gain vs. CRN-NOMA without IRS for N = 8, 16, 32 reflectors. We also evaluate the effects of primary interference. The results are valid for any number of NOMA users, Quadrature Amplitude Modulation (QAM) and Rayleigh channels.

---

Keywords

---