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Experimental Study of Deep Neural Network Equalizers Performance in Optical Links

Pedro J. Freire, Yevhenii Osadchuk, Bernhard Spinnler, Wolfgang Schairer, Antonio Napoli, Nelson Costa, Jaroslaw E. Prilepsky, and Sergei K. Turitsyn

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Abstract

We propose a convolutional-recurrent channel equalizer and experiment tally demonstrate 1dB Q-factor improvement both in single-channel and 96×WDM, DP- 16QAM transmission over 450km of TWC fiber. The new equalizer outperforms previous NN-based approaches and a 3-steps-per-span DBP.

© 2021 The Author(s)

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Experimental Evaluation of Computational Complexity for Different Neural Network Equalizers in Optical Communications

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