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Proceedings Paper

Application of machine learning methods in provisioning of DWDM channels
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Paper Abstract

Complexity and size of modern optic-fiber networks start to challenge the traditional methods of managing them and yet majority of telecommunication companies still report rapid growth of their optical networks. One of essential problems in managing optic-fiber networks is calculating the Quality of Transmission (QoT) of given path in network. The unit responsible for this task is Optical Performance Unit (OPU) which communicates with Network Management System (NMS). OPU's task is to determine whether it is possible to transmit signal through a given path. Modern OPUs are still operating based on traditional algorithms e.g. these systems take into consideration known physics rules and information about the network parameters, calculating transmission losses for each path. Main parameter that determines the OPUs result is Optical Signal to Noise Ratio (OSNR). However, measuring its value from NMS level is often not practical. An alternative solution to this problem might prove the application of Machine Learning (ML) algorithms for the estimation of OSNR. In this contribution an application of Artificial Neural Network (ANN) to an evaluation of OSNR in an optical Dense Wavelength Division Multiplexing (DWDM) network is investigated.

Paper Details

Date Published: 13 September 2019
PDF: 5 pages
Proc. SPIE 11204, 14th Conference on Integrated Optics: Sensors, Sensing Structures, and Methods, 1120407 (13 September 2019); doi: 10.1117/12.2536656
Show Author Affiliations
Piotr Paziewski, Warsaw Univ. of Technology (Poland)
Sławomir Sujecki, Wroclaw Univ. of Science and Technology (Poland)
Stanisław Kozdrowski, Warsaw Univ. of Technology (Poland)

Published in SPIE Proceedings Vol. 11204:
14th Conference on Integrated Optics: Sensors, Sensing Structures, and Methods
Przemyslaw Struk; Tadeusz Pustelny, Editor(s)

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