Time-Domain Volterra-Based Digital Backpropagation for Coherent Optical Systems

We propose a novel closed-form time-domain (TD) Volterra series nonlinear equalizer (VSNE) for the mitigation of Kerr-related distortions in polarization-multiplexed (PM) coherent optical transmission systems. The proposed TD-VSNE is obtained from the inverse Fourier analysis of a frequency-domain V...

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Bibliographic Details
Published in:Journal of lightwave technology 2015-08, Vol.33 (15), p.3170-3181
Main Authors: Guiomar, Fernando Pedro, Batalha Amado, Sofia, Sanches Martins, Celestino, Nolasco Pinto, Armando
Format: Article
Language:English
Subjects:
Approximation algorithms
Approximation methods
Coherent detection
Complexity theory
digital signal processing
Equalizers
Mathematical model
nonlinear equalization
Nonlinear optics
optical communication systems
Optical polarization
Volterra series
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Summary:We propose a novel closed-form time-domain (TD) Volterra series nonlinear equalizer (VSNE) for the mitigation of Kerr-related distortions in polarization-multiplexed (PM) coherent optical transmission systems. The proposed TD-VSNE is obtained from the inverse Fourier analysis of a frequency-domain VSNE based on a frequency-flat approximation. Employing novel TD approximations, we demonstrate the equivalency between the VSNE algorithms formulated in time and frequency domains. In order to enhance the computational efficiency, we insert a power weighting time window in the TD-VSNE, yielding the weighted VSNE (W-VSNE) algorithm. We demonstrate that the convergence of the W-VSNE to its maximum performance is much faster than that of the TD-VSNE, thus requiring fewer parallel filters. Through numerical simulation of a 224-Gb/s PM-16QAM optical channel, we compare the performance/complexity tradeoff of the W-VSNE with the well-known split-step Fourier method (SSFM) and with the computationally optimized weighted SSFM (W-SSFM). Enabled by the use of fewer iterations and only two parallel W-VSNE filters, we demonstrate a reduction of up to ~45% on computational effort and ~70% on latency, in comparison with the W-SSFM.
ISSN:0733-8724
1558-2213
DOI:10.1109/JLT.2015.2435520