A Robust Adaptive NOMA Architecture for High-reliability 6G Indoor Li-Fi Communication System

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Authors: Zainab Hassan Mazher Fakhr Al-Deen, Marwa Jaleel Mohsin
Cited by: 1

Abstract

With enormous growth of mobile data traffic, urgent need for high-speed and high-density indoor access, and to overcome the Radio Frequency (RF) spectrum crunch in wireless communication networks, Light Fidelity (Li-Fi) system concatenated with non-orthogonal multiple access (NOMA) technology and represented in this paper.In the next generation of 6G optical networks, for the purpose of verifying fairness between users and maximizing spectral efficiency (SE), a novel dynamic Li-Fi-NOMA system was proposed.The system utilized low-complexity adaptive power allocation APA concatenated with an adaptive modulation and coding scheme (AMC).The APA-based gain ratio power allocation (GRPA) algorithm with the adynamic mechanism of modulation coding based on channel condition improved the Signal-to-Interference-plus-Noise Ratio (SINR) levels.Various modulation schemes, such as 16-QAM, 8PSK, 4-QAM, and continuous phase modulation (CPM), were utilized based on APA stage decision for cell-edge users.Large-scale room design (10×6×3.5 m) was simulated with a 4-LED array distributed over a realistic channel condition involving line-of-sight (LOS) and non-line-of-sight (NLOS) models.Furthermore, different values of signal-to-noise-ratio SNR (0-20 dB) were subjected to test the proposed system performance.As results showed the proposed system exhibits superior performance compared with state-of -art, with high-throughput indoor optical wireless networks achieving ~ 150 Mbps with SE of ~7 bits/s/Hz and maintaining a low latency approximate of 1.4 ms.Moreover, at high SNR of 20 dB, the system reaches BER of

Fields of Study & Subjects

Advanced Wireless Communication Technologies PAPR reduction in OFDM Advanced Wireless Communication Techniques

Publication details

Journal / source
International journal of intelligent engineering and systems
Publisher
The Intelligent Networks and Systems Society
Volume
19
Issue
3
Pages
677–696
Publication date
17 February 2026