International Symposium on Telecommunication (IST)

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QoT Estimation of a Commercial DWDM Transmission System Using Artificial Neural Network and Its Feature Importance Analysis

Authors :

Mojtaba Amani¹ Changiz Ghobadi² Javad Nourinia³ Mehdi Habibi⁴

1- Department of computer and electrical engineering, Urmia University 2- Department of computer and electrical engineering, Urmia University 3- Department of computer and electrical engineering, Urmia University 4- Transmission and Fiber Optic Group, Telecommunication Infrastructure Company

Keywords :

neural network،quality of transmission (QoT)،signal-to-noise ratio (SNR)،dense wavelength-division multiplexing (DWDM)،feature importance

Abstract :

In this paper, we proposed an artificial neural network (ANN) architecture to estimate the optical signal-to-noise ratio (OSNR) of an in-use commercial dense wavelength-division multiplexing (DWDM) system. The model yields a very close estimation of the values the optical spectrum analyzer measured during periodical maintenance measurements (mean absolute error is less than 0.04 for OSNR values in dB). Since our model is based on periodic measurements, it represents an updated network state. Furthermore, to investigate the compliance of the ANN model with previous theoretical studies, we have examined the importance of the features. The results imply that complex and accurate models like the ANN model for in-use commercial systems do not necessarily behave as the theoretical analyses suggest. This is due to the complex nature of quality of transmission (QoT) analysis in optical systems and other factors such as equipment aging and errors not included in the theoretical studies. Feature importance analysis could help in simplifying the models based on network specifications by removing features with low impacts while maintaining the required estimation accuracy.