Mitigation of Distortions in Radio Over Fiber Systems Using Machine Learning
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| Format: | Artículo científico |
| Language: | en |
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Corporación Universitaria de la Costa
2021
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| _version_ | 1876483555942465536 |
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| author | Diego Fernando Torres Vahos |
| author_facet | Diego Fernando Torres Vahos |
| contents | Mitigation of Distortions in Radio Over Fiber Systems Using Machine Learning Diego Fernando Torres Vahos Alejandro Escobar Pérez Cristian Alexis Diaz Rodríguez Jhon James Granada Torres Ingeniería Radio Radio over fiber over fiber Machine learning The ever-growing number of users connected to internet via mobile devices has driven to increase the research in the paradigm of hybrid optical networks called Radio-over-Fiber. These networks take advantages of the bandwidth given by the optical fiber and the mobility given by wireless transmissions, avoiding the bottleneck of optical-to-electrical conversion interfaces. However, the chromatic dispersion of the optical fiber generates distortions in the radiofrequency signals optically modulated, limiting the reach of transmission. 2021 artículo científico 0122-6517 https://www.redalyc.org/articulo.oa?id=497779340020 en http://www.redalyc.org/revista.oa?id=4977 INGE CUC application/pdf Corporación Universitaria de la Costa INGE CUC (Colombia) Num.2 Vol.17 |
| format | Artículo científico |
| id | redalyc_497779340020 |
| institution | Redalyc |
| language | en |
| publishDate | 2021 |
| publisher | Corporación Universitaria de la Costa |
| spellingShingle | Mitigation of Distortions in Radio Over Fiber Systems Using Machine Learning Diego Fernando Torres Vahos Ingeniería Radio Radio over fiber over fiber Machine learning Mitigation of Distortions in Radio Over Fiber Systems Using Machine Learning Diego Fernando Torres Vahos Alejandro Escobar Pérez Cristian Alexis Diaz Rodríguez Jhon James Granada Torres Ingeniería Radio Radio over fiber over fiber Machine learning The ever-growing number of users connected to internet via mobile devices has driven to increase the research in the paradigm of hybrid optical networks called Radio-over-Fiber. These networks take advantages of the bandwidth given by the optical fiber and the mobility given by wireless transmissions, avoiding the bottleneck of optical-to-electrical conversion interfaces. However, the chromatic dispersion of the optical fiber generates distortions in the radiofrequency signals optically modulated, limiting the reach of transmission. 2021 artículo científico 0122-6517 https://www.redalyc.org/articulo.oa?id=497779340020 en http://www.redalyc.org/revista.oa?id=4977 INGE CUC application/pdf Corporación Universitaria de la Costa INGE CUC (Colombia) Num.2 Vol.17 |
| title | Mitigation of Distortions in Radio Over Fiber Systems Using Machine Learning |
| topic | Ingeniería Radio Radio over fiber over fiber Machine learning |
| url | https://www.redalyc.org/articulo.oa?id=497779340020 |