Intelligent Reflecting Surfaces (IRS)-Enhanced Cooperative NOMA: A Contemporary Review

The integration of intelligent reflecting surfaces (IRS) into cooperative non-orthogonal multiple access (NOMA) systems revolutionizes wireless networks by enhancing signal strength, mitigating interference, and optimizing spectral efficiency. The cooperative NOMA (CNOMA) framework, empowered by IRS...

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Main Authors: Sanjeev Sharma, Amit Kumar Mishra, M. Hemant Kumar, Kuntal Deka, Vimal Bhatia
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
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Online Access:https://ieeexplore.ieee.org/document/10535492/
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author Sanjeev Sharma
Amit Kumar Mishra
M. Hemant Kumar
Kuntal Deka
Vimal Bhatia
author_facet Sanjeev Sharma
Amit Kumar Mishra
M. Hemant Kumar
Kuntal Deka
Vimal Bhatia
author_sort Sanjeev Sharma
collection DOAJ
description The integration of intelligent reflecting surfaces (IRS) into cooperative non-orthogonal multiple access (NOMA) systems revolutionizes wireless networks by enhancing signal strength, mitigating interference, and optimizing spectral efficiency. The cooperative NOMA (CNOMA) framework, empowered by IRS technology, further promises enhanced performance, robustness, and scalability for next-generation wireless networks as compared to NOMA only systems. This paper explores the synergy between IRS and NOMA to leverage cooperative techniques for superior wireless system design. Fundamental principles, technological advancements, and potential applications of IRS-assisted CNOMA systems are discussed, highlighting existing works. Both underlay and overlay NOMA principles are examined in conjunction with IRS in the paper. Spatial modulation-aided CNOMA is explored for multiple-input multiple-output (MIMO) systems, along with its advantages and practical challenges. Additionally, the paper discusses fundamental principles and technological advancements of IRS-assisted CNOMA systems, emphasizing solutions to potential challenges and the role of machine learning (ML)/deep learning (DL) in resource optimization like transmit power and IRS phase settings. Simulation results are presented to highlight the benefits of IRS-aided CNOMA system design. Finally, the paper outlines future directions and potential research topics in IRS-aided CNOMA.
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issn 2169-3536
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publishDate 2024-01-01
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spelling doaj-art-bf60c072e31846ffb0a55abb044363f22025-08-20T03:31:23ZengIEEEIEEE Access2169-35362024-01-0112821688219110.1109/ACCESS.2024.340393110535492Intelligent Reflecting Surfaces (IRS)-Enhanced Cooperative NOMA: A Contemporary ReviewSanjeev Sharma0https://orcid.org/0000-0001-7488-1064Amit Kumar Mishra1https://orcid.org/0000-0001-6631-1539M. Hemant Kumar2https://orcid.org/0000-0001-9976-186XKuntal Deka3https://orcid.org/0000-0002-8782-1682Vimal Bhatia4https://orcid.org/0000-0001-5148-6643IIT (BHU) Varanasi, Varanasi, IndiaNational Spectrum Centre, Aberystwyth University, Aberystwyth, U.K.ICS, Hyderabad, IndiaIIT Guwahati, Guwahati, IndiaIIT Indore, Indore, IndiaThe integration of intelligent reflecting surfaces (IRS) into cooperative non-orthogonal multiple access (NOMA) systems revolutionizes wireless networks by enhancing signal strength, mitigating interference, and optimizing spectral efficiency. The cooperative NOMA (CNOMA) framework, empowered by IRS technology, further promises enhanced performance, robustness, and scalability for next-generation wireless networks as compared to NOMA only systems. This paper explores the synergy between IRS and NOMA to leverage cooperative techniques for superior wireless system design. Fundamental principles, technological advancements, and potential applications of IRS-assisted CNOMA systems are discussed, highlighting existing works. Both underlay and overlay NOMA principles are examined in conjunction with IRS in the paper. Spatial modulation-aided CNOMA is explored for multiple-input multiple-output (MIMO) systems, along with its advantages and practical challenges. Additionally, the paper discusses fundamental principles and technological advancements of IRS-assisted CNOMA systems, emphasizing solutions to potential challenges and the role of machine learning (ML)/deep learning (DL) in resource optimization like transmit power and IRS phase settings. Simulation results are presented to highlight the benefits of IRS-aided CNOMA system design. Finally, the paper outlines future directions and potential research topics in IRS-aided CNOMA.https://ieeexplore.ieee.org/document/10535492/Intelligent reflecting surfaces (IRS)cooperative-NOMA (CNOMA)bit error performance5G and beyondmachine learningMIMO
spellingShingle Sanjeev Sharma
Amit Kumar Mishra
M. Hemant Kumar
Kuntal Deka
Vimal Bhatia
Intelligent Reflecting Surfaces (IRS)-Enhanced Cooperative NOMA: A Contemporary Review
IEEE Access
Intelligent reflecting surfaces (IRS)
cooperative-NOMA (CNOMA)
bit error performance
5G and beyond
machine learning
MIMO
title Intelligent Reflecting Surfaces (IRS)-Enhanced Cooperative NOMA: A Contemporary Review
title_full Intelligent Reflecting Surfaces (IRS)-Enhanced Cooperative NOMA: A Contemporary Review
title_fullStr Intelligent Reflecting Surfaces (IRS)-Enhanced Cooperative NOMA: A Contemporary Review
title_full_unstemmed Intelligent Reflecting Surfaces (IRS)-Enhanced Cooperative NOMA: A Contemporary Review
title_short Intelligent Reflecting Surfaces (IRS)-Enhanced Cooperative NOMA: A Contemporary Review
title_sort intelligent reflecting surfaces irs enhanced cooperative noma a contemporary review
topic Intelligent reflecting surfaces (IRS)
cooperative-NOMA (CNOMA)
bit error performance
5G and beyond
machine learning
MIMO
url https://ieeexplore.ieee.org/document/10535492/
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AT amitkumarmishra intelligentreflectingsurfacesirsenhancedcooperativenomaacontemporaryreview
AT mhemantkumar intelligentreflectingsurfacesirsenhancedcooperativenomaacontemporaryreview
AT kuntaldeka intelligentreflectingsurfacesirsenhancedcooperativenomaacontemporaryreview
AT vimalbhatia intelligentreflectingsurfacesirsenhancedcooperativenomaacontemporaryreview