IEICE Communications Express
Online ISSN : 2187-0136
ISSN-L : 2187-0136

This article has now been updated. Please use the final version.

Polarization demultiplexing and optical nonlinearity compensation based on artificial neural networks
Yuichiro KurokawaTakeru KyonoYuta FukumotoNoriki SumimotoMoriya Nakamura
Author information
JOURNAL FREE ACCESS Advance online publication

Article ID: 2019GCL0003

Details
Abstract

We proposed and investigated novel methods for polarization demultiplexing using artificial neural networks (ANNs). It was shown that a three-layer ANN includes butterfly operations and has a polarization-demultiplexing capability. Our proposed cascaded construction of a butterfly-structure of FIR filters and an ANN connecting x- and y-polarization components exhibited superior performance in terms of the polarization-demultiplexing speed. By using the proposed method, optical nonlinearity can also be compensated for at the same time. We examined and compared the performance of the proposed methods by numerical simulations using 10-Gsymbol/s polarization multiplexed 16QAM optical signals.

Content from these authors
© 2019 The Institute of Electronics, Information and Communication Engineers
feedback
Top