IRS-enabled NOMA communication systems: A network architecture primer with future trends and challenges Article Swipe
YOU?
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· 2023
· Open Access
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· DOI: https://doi.org/10.1016/j.dcan.2023.09.002
Non-Orthogonal Multiple Access (NOMA) has already proven to be an effective multiple access scheme for 5th Generation (5G) wireless networks. It provides improved performance in terms of system throughput, spectral efficiency, fairness, and energy efficiency (EE). However, in conventional NOMA networks, performance degradation still exists because of the stochastic behavior of wireless channels. To combat this challenge, the concept of Intelligent Reflecting Surface (IRS) has risen to prominence as a low-cost intelligent solution for Beyond 5G (B5G) networks. In this paper, a modeling primer based on the integration of these two cutting-edge technologies, i.e., IRS and NOMA, for B5G wireless networks is presented. An in-depth comparative analysis of IRS-assisted Power Domain (PD)-NOMA networks is provided through 3-fold investigations. First, a primer is presented on the system architecture of IRS-enabled multiple-configuration PD-NOMA systems, and parallels are drawn with conventional network configurations, i.e., conventional NOMA, Orthogonal Multiple Access (OMA), and IRS-assisted OMA networks. Followed by this, a comparative analysis of these network configurations is showcased in terms of significant performance metrics, namely, individual users' achievable rate, sum rate, ergodic rate, EE, and outage probability. Moreover, for multi-antenna IRS-enabled NOMA networks, we exploit the active Beamforming (BF) technique by employing a greedy algorithm using a state-of-the-art branch-reduce-and-bound (BRB) method. The optimality of the BRB algorithm is presented by comparing it with benchmark BF techniques, i.e., minimum-mean-square-error, zero-forcing-BF, and maximum-ratio-transmission. Furthermore, we present an outlook on future envisioned NOMA networks, aided by IRSs, i.e., with a variety of potential applications for 6G wireless networks. This work presents a generic performance assessment toolkit for wireless networks, focusing on IRS-assisted NOMA networks. This comparative analysis provides a solid foundation for the development of future IRS-enabled, energy-efficient wireless communication systems.
Related Topics
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1016/j.dcan.2023.09.002
- OA Status
- diamond
- Cited By
- 29
- References
- 222
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4386776943
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4386776943Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1016/j.dcan.2023.09.002Digital Object Identifier
- Title
-
IRS-enabled NOMA communication systems: A network architecture primer with future trends and challengesWork title
- Type
-
articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2023Year of publication
- Publication date
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2023-09-15Full publication date if available
- Authors
-
Haleema Sadia, Ahmad Kamal Hassan, Ziaul Haq Abbas, Ghulam Abbas, Muhammad Waqas, Zhu HanList of authors in order
- Landing page
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https://doi.org/10.1016/j.dcan.2023.09.002Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
-
diamondOpen access status per OpenAlex
- OA URL
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https://doi.org/10.1016/j.dcan.2023.09.002Direct OA link when available
- Concepts
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Noma, Computer science, Wireless network, Beamforming, Wireless, Channel state information, Ergodic theory, Spectral efficiency, Benchmark (surveying), Computer network, Throughput, Telecommunications, Mathematics, Telecommunications link, Geography, Geodesy, Mathematical analysisTop concepts (fields/topics) attached by OpenAlex
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29Total citation count in OpenAlex
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2025: 9, 2024: 17, 2023: 3Per-year citation counts (last 5 years)
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222Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| corresponding_institution_ids | https://openalex.org/I5400463 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/7 |
| sustainable_development_goals[0].score | 0.8899999856948853 |
| sustainable_development_goals[0].display_name | Affordable and clean energy |
| citation_normalized_percentile.value | 0.95350371 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |