3 papers
eess.SP2021
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…
eess.SP2021
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…
eess.SP2021
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…