4 papers
Domain Adaptation: the Key Enabler of Neural Network Equalizers in Coherent Optical Systems
Pedro J. Freire, Bernhard Spinnler, Daniel Abode +7
We introduce the domain adaptation and randomization approach for calibrating neural network-based equalizers for real transmissions, using synthetic data. The approach renders up…
Experimental Evaluation of Computational Complexity for Different Neural Network Equalizers in Optical Communications
Pedro J. Freire, Yevhenii Osadchuk, Antonio Napoli +5
Addressing the neural network-based optical channel equalizers, we quantify the trade-off between their performance and complexity by carrying out the comparative analysis of sever…
Experimental Study of Deep Neural Network Equalizers Performance in Optical Links
Pedro J. Freire, Yevhenii Osadchuk, Bernhard Spinnler +5
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…
Performance versus Complexity Study of Neural Network Equalizers in Coherent Optical Systems
Pedro J. Freire, Yevhenii Osadchuk, Bernhard Spinnler +5
We present the results of the comparative analysis of the performance versus complexity for several types of artificial neural networks (NNs) used for nonlinear channel equalizatio…