Power Profile Estimation of Optical Transmission Links Based on Machine Learning

We propose a method for estimation of power profile in optical transmissions by employing machine learning optimization to a digital back-propagation model. The method allows to estimate the absolute power values along the link and it requires solely the coherently acquired data at the receiver-side. The estimated values are validated using experimental results from an unrepeatered transmission, employing remote and Raman amplification.