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Fully-blind Neural Network Based Equalization for Severe Nonlinear Distortions in 112 Gbit/s Passive Optical Networks

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arxiv 2401.09579 v1 pith:JWUMOBNB submitted 2024-01-17 eess.SP cs.LG

Vincent Lauinger , Patrick Matalla , Jonas Ney , Norbert Wehn , Sebastian Randel , Laurent Schmalen This is my paper · ORCID
classification eess.SPcs.LG
keywords networksfully-blindneuralopticalpassiveanalyzechaincomplexity
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We demonstrate and evaluate a fully-blind digital signal processing (DSP) chain for 100G passive optical networks (PONs), and analyze different equalizer topologies based on neural networks with low hardware complexity.

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  1. Recent Advances on Machine Learning-aided DSP for Short-reach and Long-haul Optical Communications

    eess.SP 2024-11 unverdicted novelty 1.0 of 10

    A mini-review of the authors' prior work on VAE-based blind equalization, FPGA-implemented CNN equalizers, and spiking neural network equalizers for optical communications.

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