{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,22]],"date-time":"2026-04-22T01:46:17Z","timestamp":1776822377582,"version":"3.51.2"},"reference-count":40,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2022,4,4]],"date-time":"2022-04-04T00:00:00Z","timestamp":1649030400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Due to the growing number of users, power, and spectral effectiveness, most communication systems are complex and difficult to implement on a large scale. Artificial Intelligence (AI) has played an outstanding role in the implementation of theoretical systems in the real world, with less complexity achieving better results. In this direction, we compare the Non-Orthogonal Multiple Access (NOMA) technique for a multiuser Visible Light Communication (VLC) system with Successive Interference Cancellation (SIC) for two types of detectors: (1) the deep learning-based system and (2) the traditional maximum likelihood (ML) decoder-based system. For multiplexing, we compare the variations of novel Orbital Angular Momentum (OAM) multiplexing and Orthogonal Frequency Division Multiplexing (OFDM) with Index Modulation (IM). In this article, we implement OFDM-IM and OAM-IM for four users for the Gaussian fading MIMO Line-of-Sight (LoS) and Non-Line-of-Sight (NLoS) VLC channels. The suggested systems\u2019 bit error rate (BER) performances are compared in simulations for a wide range of Signal-to-Noise Ratios (SNRs), which shows that deep learning-based systems outperform the ML-based system for both users to ensure better decoding at the receiver end, especially at higher SNR values. The detection error is lower in a deep learning-based system at around 20% and around 30% for low SNR and high SNR values, respectively.<\/jats:p>","DOI":"10.3390\/s22072771","type":"journal-article","created":{"date-parts":[[2022,4,4]],"date-time":"2022-04-04T09:49:41Z","timestamp":1649065781000},"page":"2771","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Deep Learning-Based Next-Generation Waveform for Multiuser VLC Systems"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8838-9457","authenticated-orcid":false,"given":"Hafiz M.","family":"Asif","sequence":"first","affiliation":[{"name":"Department of Electrical and Computer Engineering, Sultan Qaboos University, Muscat 123, Oman"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0666-7696","authenticated-orcid":false,"given":"Affan","family":"Affan","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, University of Louisville, Louisville, KY 40292, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7690-8168","authenticated-orcid":false,"given":"Naser","family":"Tarhuni","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, Sultan Qaboos University, Muscat 123, Oman"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kaamran","family":"Raahemifar","sequence":"additional","affiliation":[{"name":"Data Science and Artificial Intelligence Program, College of Information Sciences and Technology (IST), Penn State University, State College, PA 16801, USA"},{"name":"Faculty of Science, School of Optometry and Vision Science, University of Waterloo, 200 University Ave. W, Waterloo, ON N2L 3G1, Canada"},{"name":"Department of Chemical Engineering, Faculty of Engineering, University of Waterloo, 200 University Ave. W, Waterloo, ON N2L 3G1, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,4,4]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"302","DOI":"10.23919\/JCIN.2020.9200893","article-title":"Challenges and Prospects of Machine Learning in Visible Light Communication","volume":"5","author":"Chi","year":"2020","journal-title":"J. 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