Power Profile Estimation of Optical Transmission Links Based on Machine Learning

Abstract

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 receiverside. The estimated values are validated using experimental results from an unrepeatered transmission, employing remote and Raman amplification.