Open Access

ARTICLE

Throughput Enhancement for NOMA Systems Using Intelligent Reflecting Surfaces

Raed Alhamad^1,*, Hatem Boujemaa²

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

* Corresponding Author: Raed Alhamad. Email:

Computers, Materials & Continua 2022, 73(3), 5233-5244. https://doi.org/10.32604/cmc.2022.030793

Received 01 April 2022; Accepted 29 May 2022; Issue published 28 July 2022

Abstract

In this article, we optimize the powers associated to Non Orthogonal Multiple Access (NOMA) users, sensing and harvesting duration for Cognitive Radio Networks (CRN). The secondary source harvests energy from node A signal. Then, it senses the channel to detect primary source. Then, the secondary source transmits a signal that is reflected by Intelligent Reflecting Surfaces (IRS) so that all reflections have a zero phase at any user. A set Ii of reflectors are associated to user Ui. The use of M = Mi = 512, 256, 128, 64, 32, 16, 8 reflectors per user offers 45, 42, 39, 36, 33, 30, 27 dB gain vs. the absence of IRS. We also suggest the use of IRS in energy harvesting. The use P = 8 reflectors for energy harvesting and M = Mi = 8 reflectors per user for data communications offers 7 and 38 dB gain vs. one IRS M = Mi = 8 and the absence of IRS. The use of P = 16 reflectors for energy harvesting and M = Mi = 8 reflectors per user for data communications offers 9 and 42 dB gain vs. one IRS M = Mi = 8 and the absence of IRS.

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Keywords

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