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Energy-Efficient IRS-Aided NOMA Beamforming for 6G Wireless Communications
Ihsan, Asim1; Wen Chen1; Asif, Muhammad2; Khan, Wali Ullah3; Wu, Qingqing4,5; Li, Jun6
2022-09-27
Source PublicationIEEE Transactions on Green Communications and Networking
ISSN2473-2400
Volume6Issue:4Pages:1945-1956
Abstract

This manuscript presents an energy-efficient alternating optimization framework based on intelligent reflective surfaces (IRS) aided non-orthogonal multiple access beamforming (NOMA-BF) system for 6G wireless communications. Specifically, this work proposes a centralized IRS-enabled design for the NOMA-BF system to optimize the active beamforming and power allocation coefficient (PAC) of users at the transmitter in the first stage and passive beamforming at IRS in the 2nd stage to maximize the energy efficiency (EE) of the network. However, an increment in the number of supportable users with the NOMA-BF system will lead to NOMA user interference and inter-cluster interference (ICI). To mitigate the effect of ICI, first zero-forcing beamforming along with efficient user clustering algorithm is exploited and then NOMA user interference is tackled efficiently through a proposed iterative algorithm that computes PAC of NOMA user through simplified closed-form expression under the required system constraints. In the 2nd stage, the problem of passive beamforming is solved through a technique based on difference-of-convex (DC) programming and successive convex approximation (SCA). Simulation results demonstrate that the proposed alternating framework for energy-efficient IRS-assisted NOMA-BF system can achieve convergence within a few iterations and provide efficient performance in terms of EE of the system with low complexity.

Keyword6g Centralized Irs Design Energy Efficiency Maximization Interference Management Noma Beamforming Design Resource Allocation
DOI10.1109/TGCN.2022.3209617
URLView the original
Language英語English
Scopus ID2-s2.0-85139448149
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Document TypeJournal article
CollectionTHE STATE KEY LABORATORY OF INTERNET OF THINGS FOR SMART CITY (UNIVERSITY OF MACAU)
Affiliation1.Shanghai Jiao Tong University, Department of Information and Communication Engineering, Shanghai, 200240, China
2.Shenzhen University, Guangdong Key Laboratory of Intelligent Information Processing, College of Electronics and Information Engineering, Shenzhen, 518000, China
3.University of Luxembourg, Interdisciplinary Centre for Security, Reliability and Trust, Luxembourg City, 1855, Luxembourg
4.University of Macau, State Key Laboratory of Internet of Things for Smart City, Macao
5.Guangdong-Macau Joint Laboratory for Advanced and Intelligent Computing, Guangzhou, China
6.Nanjing University of Science and Technology, School of Electronic and Optical Engineering, Nanjing, 210094, China
Recommended Citation
GB/T 7714
Ihsan, Asim,Wen Chen,Asif, Muhammad,et al. Energy-Efficient IRS-Aided NOMA Beamforming for 6G Wireless Communications[J]. IEEE Transactions on Green Communications and Networking, 2022, 6(4), 1945-1956.
APA Ihsan, Asim., Wen Chen., Asif, Muhammad., Khan, Wali Ullah., Wu, Qingqing., & Li, Jun (2022). Energy-Efficient IRS-Aided NOMA Beamforming for 6G Wireless Communications. IEEE Transactions on Green Communications and Networking, 6(4), 1945-1956.
MLA Ihsan, Asim,et al."Energy-Efficient IRS-Aided NOMA Beamforming for 6G Wireless Communications".IEEE Transactions on Green Communications and Networking 6.4(2022):1945-1956.
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