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Vertical Cavity Surface Emitting Laser Performance Maturing through Machine Learning for High-Yield Optical Wireless Network

The high-yield optical wireless network (OWN) is a promising framework to strengthen 5G and 6G mobility. In addition, high direction and narrow bandwidth-based laser beams are enormously noteworthy for high data transmission over standard optical fibers. Therefore, in this paper, the performance of...

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Autores principales: Armghan, Ammar, Aliqab, Khaled, Ali, Farman, Alenezi, Fayadh, Alsharari, Meshari
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9781996/
https://www.ncbi.nlm.nih.gov/pubmed/36557431
http://dx.doi.org/10.3390/mi13122132
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author Armghan, Ammar
Aliqab, Khaled
Ali, Farman
Alenezi, Fayadh
Alsharari, Meshari
author_facet Armghan, Ammar
Aliqab, Khaled
Ali, Farman
Alenezi, Fayadh
Alsharari, Meshari
author_sort Armghan, Ammar
collection PubMed
description The high-yield optical wireless network (OWN) is a promising framework to strengthen 5G and 6G mobility. In addition, high direction and narrow bandwidth-based laser beams are enormously noteworthy for high data transmission over standard optical fibers. Therefore, in this paper, the performance of a vertical cavity surface emitting laser (VCSEL) is evaluated using the machine learning (ML) technique, aiming to purify the optical beam and enable OWN to support high-speed, multi-user data transmission. The ML technique is applied on a designed VCSEL array to optimize paths for DC injection, AC signal modulation, and multiple-user transmission. The mathematical model of VCSEL narrow beam, OWN, and energy loss through nonlinear interference in an optical wireless network is studied. In addition, the mathematical model is then affirmed with a simulation model following the bit error rate (BER), the laser power, the current, and the fiber-length performance matrices. The results estimations declare that the presented methodology offers a narrow beam of VCSEL, mitigating nonlinear interference in OWN and increasing energy efficiency.
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spelling pubmed-97819962022-12-24 Vertical Cavity Surface Emitting Laser Performance Maturing through Machine Learning for High-Yield Optical Wireless Network Armghan, Ammar Aliqab, Khaled Ali, Farman Alenezi, Fayadh Alsharari, Meshari Micromachines (Basel) Article The high-yield optical wireless network (OWN) is a promising framework to strengthen 5G and 6G mobility. In addition, high direction and narrow bandwidth-based laser beams are enormously noteworthy for high data transmission over standard optical fibers. Therefore, in this paper, the performance of a vertical cavity surface emitting laser (VCSEL) is evaluated using the machine learning (ML) technique, aiming to purify the optical beam and enable OWN to support high-speed, multi-user data transmission. The ML technique is applied on a designed VCSEL array to optimize paths for DC injection, AC signal modulation, and multiple-user transmission. The mathematical model of VCSEL narrow beam, OWN, and energy loss through nonlinear interference in an optical wireless network is studied. In addition, the mathematical model is then affirmed with a simulation model following the bit error rate (BER), the laser power, the current, and the fiber-length performance matrices. The results estimations declare that the presented methodology offers a narrow beam of VCSEL, mitigating nonlinear interference in OWN and increasing energy efficiency. MDPI 2022-12-01 /pmc/articles/PMC9781996/ /pubmed/36557431 http://dx.doi.org/10.3390/mi13122132 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Armghan, Ammar
Aliqab, Khaled
Ali, Farman
Alenezi, Fayadh
Alsharari, Meshari
Vertical Cavity Surface Emitting Laser Performance Maturing through Machine Learning for High-Yield Optical Wireless Network
title Vertical Cavity Surface Emitting Laser Performance Maturing through Machine Learning for High-Yield Optical Wireless Network
title_full Vertical Cavity Surface Emitting Laser Performance Maturing through Machine Learning for High-Yield Optical Wireless Network
title_fullStr Vertical Cavity Surface Emitting Laser Performance Maturing through Machine Learning for High-Yield Optical Wireless Network
title_full_unstemmed Vertical Cavity Surface Emitting Laser Performance Maturing through Machine Learning for High-Yield Optical Wireless Network
title_short Vertical Cavity Surface Emitting Laser Performance Maturing through Machine Learning for High-Yield Optical Wireless Network
title_sort vertical cavity surface emitting laser performance maturing through machine learning for high-yield optical wireless network
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9781996/
https://www.ncbi.nlm.nih.gov/pubmed/36557431
http://dx.doi.org/10.3390/mi13122132
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