OCATA: A deep-learning-based digital twin for the optical time domain
The development of digital twins to represent the optical transport network might enable multiple applications for network operation, including automation and fault management. In this work, we propose a deep-learning-based digital twin for the optical time domain, named OCATA. OCATA is based on the...
| Autores: | , , , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2023 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/386988 |
| Acceso en línea: | https://hdl.handle.net/2117/386988 https://dx.doi.org/10.1364/JOCN.477341 |
| Access Level: | acceso abierto |
| Palabra clave: | Deep learning Optical fiber communication Digital twins (Computer simulation) Deep neural network modeling Disaggregated-proprietary optical network scenarios DNN-based models Fault management Network operation OCATA Optical filtering Optical links Optical time domain Optical transport network Real-time applications Aprenentatge profund Comunicació per fibra òptica Rèpliques digitals (Simulació per ordinador) Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Telecomunicació òptica |
| Sumario: | The development of digital twins to represent the optical transport network might enable multiple applications for network operation, including automation and fault management. In this work, we propose a deep-learning-based digital twin for the optical time domain, named OCATA. OCATA is based on the concatenation of deep neural network (DNN) modeling of optical links and nodes, which facilitates representing lightpaths. The DNNs model linear and nonlinear noise, as well as optical filtering. Additional DNN-based models are proposed to extract useful lightpath metrics, such as lightpath length, number of optical links, and nonlinear fiber parameters. OCATA exhibits low complexity, thus making it ideal for real-time applications. Illustrative results for the application of OCATA to disaggregated and mixed disaggregated-proprietary optical network scenarios reveal remarkable accuracy. |
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