Fast Single-Mode Fiber Nonlinearity Monitoring

An Experimental Comparison Between Split-Step and Nonlinear Fourier Transform-Based Methods

Journal Article (2023)
Author(s)

P.B.J. de Koster (TU Delft - Team Sander Wahls)

Olaf Schulz (Christian-Albrechts-Universität zu Kiel)

Jonas Koch (Christian-Albrechts-Universität zu Kiel, Rohde and Schwarz)

Stephan Pachnicke (Christian-Albrechts-Universität zu Kiel)

S. Wahls (Karlsruhe Institut für Technologie, TU Delft - Team Michel Verhaegen)

Research Group
Team Sander Wahls
Copyright
© 2023 P.B.J. de Koster, Olaf Schulz, Jonas Koch, Stephan Pachnicke, S. Wahls
DOI related publication
https://doi.org/10.1109/JPHOT.2023.3322635
More Info
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Publication Year
2023
Language
English
Copyright
© 2023 P.B.J. de Koster, Olaf Schulz, Jonas Koch, Stephan Pachnicke, S. Wahls
Research Group
Team Sander Wahls
Issue number
6
Volume number
15
Reuse Rights

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Abstract

We experimentally investigate the problem of monitoring the Kerr-nonlinearity coefficient $\gamma$ from transmitted and received data for a single-mode fiber link of 1600 km length. We compare the accuracy and speed of three different approaches. First, a standard split-step Fourier method is used to predict the output at various $\gamma$ values, which are then compared to the measured output. Second, a recently proposed nonlinear Fourier transform (NFT)-based method, which matches solitonic eigenvalues in the transmitted and received signals for various $\gamma$ values. Third, a novel fast version of the NFT-based method, which only matches the highest few eigenvalues. Although the NFT-based methods do not scale with link length, we demonstrate that the SSFM-based method is significantly faster than the basic NFT-based method for the considered link of 1600 km, and outperforms even the faster version. However, for a simulated link of 8000 km, the fast NFT-based method is shown to be faster than the SSMF-based method, although at the cost of a small loss in accuracy.