Cargando…
Optical Encoding Model Based on Orbital Angular Momentum Powered by Machine Learning
Based on orbital angular momentum (OAM) properties of Laguerre–Gaussian beams LG([Formula: see text]), a robust optical encoding model for efficient data transmission applications is designed. This paper presents an optical encoding model based on an intensity profile generated by a coherent superpo...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10007020/ https://www.ncbi.nlm.nih.gov/pubmed/36904967 http://dx.doi.org/10.3390/s23052755 |
_version_ | 1784905415083950080 |
---|---|
author | Lamilla, Erick Sacarelo, Christian Alvarez-Alvarado, Manuel S. Pazmino, Arturo Iza, Peter |
author_facet | Lamilla, Erick Sacarelo, Christian Alvarez-Alvarado, Manuel S. Pazmino, Arturo Iza, Peter |
author_sort | Lamilla, Erick |
collection | PubMed |
description | Based on orbital angular momentum (OAM) properties of Laguerre–Gaussian beams LG([Formula: see text]), a robust optical encoding model for efficient data transmission applications is designed. This paper presents an optical encoding model based on an intensity profile generated by a coherent superposition of two OAM-carrying Laguerre–Gaussian modes and a machine learning detection method. In the encoding process, the intensity profile for data encoding is generated based on the selection of p and ℓ indices, while the decoding process is performed using a support vector machine (SVM) algorithm. Two different decoding models based on an SVM algorithm are tested to verify the robustness of the optical encoding model, finding a BER [Formula: see text] for [Formula: see text] dB of signal-to-noise ratio in one of the SVM models. |
format | Online Article Text |
id | pubmed-10007020 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-100070202023-03-12 Optical Encoding Model Based on Orbital Angular Momentum Powered by Machine Learning Lamilla, Erick Sacarelo, Christian Alvarez-Alvarado, Manuel S. Pazmino, Arturo Iza, Peter Sensors (Basel) Communication Based on orbital angular momentum (OAM) properties of Laguerre–Gaussian beams LG([Formula: see text]), a robust optical encoding model for efficient data transmission applications is designed. This paper presents an optical encoding model based on an intensity profile generated by a coherent superposition of two OAM-carrying Laguerre–Gaussian modes and a machine learning detection method. In the encoding process, the intensity profile for data encoding is generated based on the selection of p and ℓ indices, while the decoding process is performed using a support vector machine (SVM) algorithm. Two different decoding models based on an SVM algorithm are tested to verify the robustness of the optical encoding model, finding a BER [Formula: see text] for [Formula: see text] dB of signal-to-noise ratio in one of the SVM models. MDPI 2023-03-02 /pmc/articles/PMC10007020/ /pubmed/36904967 http://dx.doi.org/10.3390/s23052755 Text en © 2023 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 | Communication Lamilla, Erick Sacarelo, Christian Alvarez-Alvarado, Manuel S. Pazmino, Arturo Iza, Peter Optical Encoding Model Based on Orbital Angular Momentum Powered by Machine Learning |
title | Optical Encoding Model Based on Orbital Angular Momentum Powered by Machine Learning |
title_full | Optical Encoding Model Based on Orbital Angular Momentum Powered by Machine Learning |
title_fullStr | Optical Encoding Model Based on Orbital Angular Momentum Powered by Machine Learning |
title_full_unstemmed | Optical Encoding Model Based on Orbital Angular Momentum Powered by Machine Learning |
title_short | Optical Encoding Model Based on Orbital Angular Momentum Powered by Machine Learning |
title_sort | optical encoding model based on orbital angular momentum powered by machine learning |
topic | Communication |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10007020/ https://www.ncbi.nlm.nih.gov/pubmed/36904967 http://dx.doi.org/10.3390/s23052755 |
work_keys_str_mv | AT lamillaerick opticalencodingmodelbasedonorbitalangularmomentumpoweredbymachinelearning AT sacarelochristian opticalencodingmodelbasedonorbitalangularmomentumpoweredbymachinelearning AT alvarezalvaradomanuels opticalencodingmodelbasedonorbitalangularmomentumpoweredbymachinelearning AT pazminoarturo opticalencodingmodelbasedonorbitalangularmomentumpoweredbymachinelearning AT izapeter opticalencodingmodelbasedonorbitalangularmomentumpoweredbymachinelearning |