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Experimental Study of Deep Neural Network Equalizers Performance in Optical Links

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arxiv 2106.13133 v1 pith:EIW6NJPA submitted 2021-06-24 eess.SP

Pedro J. Freire , Yevhenii Osadchuk , Bernhard Spinnler , Wolfgang Schairer , Antonio Napoli , Nelson Costa , Jaroslaw E. Prilepsky , Sergei K. Turitsyn This is my paper · ORCID
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keywords equalizerapproacheschannelconvolutional-recurrentdeepdemonstratedp-16qamequalizers
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We propose a convolutional-recurrent channel equalizer and experimentally demonstrate 1dB Q-factor improvement both in single-channel and 96 x WDM, DP-16QAM transmission over 450km of TWC fiber. The new equalizer outperforms previous NN-based approaches and a 3-steps-per-span DBP.

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