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Performance estimation of super combined DWDM system employing machine learning

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Abstract

In this work, a 32-channel DWDM system has been evaluated by employing modified duobinary return to zero (MDRZ) and differential phase shift keying (DPSK) modulation techniques at alternate channels. Performance of the system has been evaluated in terms of gain, noise figure, optical signal-to-noise ratio (OSNR), quality- factor (Q-factor) and noise figure (NF). The DPSK modulated channels result in higher values of gain, OSNR and Q-factor with low noise figure values as compared to MDRZ channels. The reduction in FWM components have been reported in case of DPSK modulated channels and by employing erbium-ytterbium doped fiber amplifier (EYDFA). Further, Machine Learning (ML) techniques have been applied for gain spectrum and performance estimation. Levenberg–Marquardt's (LM) provides best fit as compared to other ANN models in case of gain spectrum estimation. The k-nearest neighbors (KNN) and support vector machine (SVM) algorithms have been tested for impairments analysis and performance estimation based on root mean square error (RMSE) and coefficient of determination (R2) as performance indicators. The best-performing model for gain, OSNR, Q-factor and NF are ANN-LM, KNN fine tree, KNN fine tree and SVM cubic, respectively.

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Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.

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Authors and Affiliations

  1. Amity School of Engineering and Technology, Amity University, Noida, Uttar Pradesh, India

    Sanmukh Kaur

  2. Ambedkar DSEU Shakarpur Campus-I, Delhi, 110092, India

    Anurupa Lubana

Authors
  1. Sanmukh Kaur
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  2. Anurupa Lubana
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Contributions

All authors have contributed to the design of the proposed configuration. Anurupa performs the whole simulation work and prepares the manuscript. SK analysed, investigated, and supervised the findings of this work and contributes to the editing of the manuscript.

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Correspondence to Anurupa Lubana.

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Kaur, S., Lubana, A. Performance estimation of super combined DWDM system employing machine learning. J Opt (2024). https://doi.org/10.1007/s12596-024-01770-9

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