Modulation Format Recognition Using Artificial Neural Networks for the Next Generation Optical Networks
Transmission systems that use advanced complex modulation schemes have been driving the growth of optical communication networks for nearly a decade. In fact, the adoption of advanced modulation schemes and digital coherent systems has led researchers and industry communities to develop new strategi...
- Autores:
- Tipo de recurso:
- Book
- Fecha de publicación:
- 2021
- Institución:
- Universidad de Bogotá Jorge Tadeo Lozano
- Repositorio:
- Expeditio: repositorio UTadeo
- Idioma:
- eng
- OAI Identifier:
- oai:expeditiorepositorio.utadeo.edu.co:20.500.12010/16832
- Acceso en línea:
- https://www.intechopen.com/books/advanced-applications-for-artificial-neural-networks/modulation-format-recognition-using-artificial-neural-networks-for-the-next-generation-optical-netwo
http://hdl.handle.net/20.500.12010/16832
- Palabra clave:
- Ingeniería de software
Redes neuronales artificiales
Redes ópticas
Reconocimiento de formato de modulación
- Rights
- License
- Abierto (Texto Completo)
| Summary: | Transmission systems that use advanced complex modulation schemes have been driving the growth of optical communication networks for nearly a decade. In fact, the adoption of advanced modulation schemes and digital coherent systems has led researchers and industry communities to develop new strategies for network diagnosis and management. A prior knowledge of modulation formats and symbol rates of all received optical signals is needed. Our approach of modulation formats identification is based on artificial neural networks (ANNs) in conjunction with different features extraction approaches. Unlike the existing techniques, our ANN-based pattern recognition algorithm facilitates the modulation format classification with higher accuracies. |
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