Applications of Machine Learning on Nonlinear Frequency Division Multiplexing Optic-Fiber Communication Systems

Abstract

Nonlinear frequency division multiplexing system becomes one of the promising candidates for overcoming the fiber’s nonlinearity limitations. To improve the system’s performance, machine learning was introduced to the NFDM systems in the past few years. In this paper, an overview on the applications of machine learning in the NFDM systems is presented.