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Abstract
The integration of large intelligent surfaces (LIS) with non-orthogonal multiple access (NOMA) networks has emerged as a promising solution to enhance the capacity and coverage of wireless communication systems. In this study, we analyse the performance of a NOMA network with the assistance of LIS. We propose a system model where a base station (BS) equipped with a LIS serves multiple users. The LIS consists of many passive elements that can influence the wireless channel by adjusting the reflection coefficients. We consider a downlink scenario where the BS transmits to multiple users simultaneously using NOMA, and the LIS helps to improve the signal quality and coverage. We additionally evaluate the efficiency of the suggested LIS-assisted NOMA network. In addition, we evaluate the efficiency of the LIS-assisted NOMA network in comparison to conventional NOMA systems that do not utilize LISs. The findings indicate that the LIS has a notable impact on enhancing the system's performance in terms of diversity gain, probability of error, and pairwise error probability (PEP). Moreover, the suggested LIS-assisted NOMA network is shown to be superior to conventional NOMA systems through comparison. These findings offer useful insights into the performance analysis of LIS-assisted NOMA networks. They also serve as inspiration and motivation for future research and development in this new subject, with the potential to revolutionize wireless communication systems.
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1 VIT–AP University, School of Electronics Engineering, Amaravati, India (GRID:grid.513382.e) (ISNI:0000 0004 7667 4992)
2 VIT–AP University, School of Computer Science and Engineering, Amaravati, India (GRID:grid.513382.e) (ISNI:0000 0004 7667 4992)
3 Vellore Institute of Technology, School of Electrical Engineering, Vellore, India (GRID:grid.412813.d) (ISNI:0000 0001 0687 4946)
4 Bapatla Engineering College, Department of ECE, Bapatla, India (GRID:grid.411114.0) (ISNI:0000 0000 9211 2181)
5 King Saud University, Department of Chemistry, College of Science, Riyadh, Kingdom of Saudi Arabia (GRID:grid.56302.32) (ISNI:0000 0004 1773 5396)
6 Hawassa University, Department of Electrical and Computer Engineering, Hawassa 05, Ethiopia (GRID:grid.192268.6) (ISNI:0000 0000 8953 2273); Zhejiang University, Center for Renewable Energy and Microgrids, Huanjiang Laboratory, Zhuji, China (GRID:grid.13402.34) (ISNI:0000 0004 1759 700X); Western Caspian University, Department of Technical Sciences, Baku, Azerbaijan (GRID:grid.442905.e) (ISNI:0000 0004 0435 8106)