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Domain Adaptation: the Key Enabler of Neural Network Equalizers in Coherent Optical Systems

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arxiv 2202.12689 v1 pith:3EM4LFYG submitted 2022-02-25 eess.SP cs.LG

classification eess.SPcs.LG
keywords adaptationapproachdomainequalizersneuralcalibratingcoherentdata
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We introduce the domain adaptation and randomization approach for calibrating neural network-based equalizers for real transmissions, using synthetic data. The approach renders up to 99\% training process reduction, which we demonstrate in three experimental setups.

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