Performance and Complexity Analysis of Bi-Directional Recurrent Neural Network Models Versus Volterra Nonlinear Equalizers in Digital Coherent Systems

We investigate the complexity and performance of recurrent neural network (RNN) models as post-processing units for the compensation of fibre nonlinearities in digital coherent systems carrying polarization multiplexed 16-QAM and 32-QAM signals. We evaluate three bi-directional RNN models, namely th...

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