Author Identifier

Muhammad Waqas: https://orcid.org/0000-0003-0814-7544

Document Type

Journal Article

Publication Title

Digital Communications and Networks

Volume

10

Issue

5

Publisher

Elsevier

School

School of Engineering

RAS ID

62430

Funders

Higher Education Commission of Pakistan (20-14560/NRPU/R&D/HEC/2021)

Comments

Sadia, H., Hassan, A. K., Abbas, Z. H., Abbas, G., Waqas, M., & Han, Z. (2023). IRS-enabled NOMA communication systems: A network architecture primer with future trends and challenges. Digital Communications and Networks, 10(5). https://doi.org/10.1016/j.dcan.2023.09.002

Abstract

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.

DOI

10.1016/j.dcan.2023.09.002

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

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