Fully connected feed-forward neural network based nonlinearity compensation method for polarization multiplexed transmission systems

摘要

In this work we propose a receiver-side nonlinearity compensation method based on fully connected feed-forward neural networks applicable to polarization-division multiplexing transmission systems. We consider different neural network architectures and show that the use of information from both polarizations allows to effectively compensate the accumulated nonlinear distortion.