Artificial Neural Network Symbol Estimator With Enhanced Robustness to Nonlinear Phase Noise
- 14 October 2021
- journal article
- research article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Photonics Technology Letters
- Vol. 33 (23), 1341-1344
- https://doi.org/10.1109/lpt.2021.3120074
Abstract
This letter reports a novel approach for nonlinear phase noise mitigation, based on artificial neural networks (ANNs) tailored to classification applications and a pre-processing stage of feature engineering. Starting with a set of proof-of-concept simulations, we verify that the proposed system can achieve optimal performance for the additive white Gaussian noise (AWGN) channel. Then, considering a dispersion-less channel with strong nonlinear phase noise (NLPN) distortion, we demonstrate a Q-factor increase of 0.4dB, comparing with standard carrier-phase estimation (CPE) followed by minimum distance detection. Finally, simulating the propagation of 64Gbaud PM-16QAM over standard single mode fiber (SSMF), we verify that the ANN-based solution is effective on wavelength-division multiplexing (WDM) transmission conditions, enabling to increase the maximum signal reach by approximately 1 fiber span over the legacy CPE-enabled NLPN compensation.Keywords
Funding Information
- European Regional Development Fund (FEDER), through the Portugal 2020 Framework
- National Public Funds (Fundação para a Ciência e Tecnologia (FCT), OE) Projects Optical Radio Convergence Infrastructure for Communications and Power Delivering (CENTRO-01-0145-FEDER-022141)
- FreeComm-B5G (UIDB/50008/2020)
- Italian Ministry for University and Research
- “la Caixa” Foundation (ID 100010434, LCF/BQ/PR20/11770015)
This publication has 10 references indexed in Scilit:
- An Overview on Application of Machine Learning Techniques in Optical NetworksIEEE Communications Surveys & Tutorials, 2018
- Evolution from 8QAM live traffic to PS 64-QAM with Neural-Network Based Nonlinearity Compensation on 11000 km Open Subsea CablePublished by Optica Publishing Group ,2018
- Mitigation of Multi-user Access Impairments in 5G A-RoF-based Mobile Fronthaul utilizing Machine Learning for an Artificial Neural Network Nonlinear EqualizerPublished by Optica Publishing Group ,2018
- Applying Neural Networks in Optical Communication Systems: Possible PitfallsIEEE Photonics Technology Letters, 2017
- Nonlinear mitigation on subcarrier-multiplexed PM-16QAM optical systemsOptics Express, 2017
- Inter-Channel Nonlinear Interference Noise in WDM Systems: Modeling and MitigationJournal of Lightwave Technology, 2014
- EGN model of non-linear fiber propagationOptics Express, 2014
- Multiplier-Free Intrachannel Nonlinearity Compensating Algorithm Operating at Symbol RateJournal of Lightwave Technology, 2011
- Compensation of Dispersion and Nonlinear Impairments Using Digital BackpropagationJournal of Lightwave Technology, 2008
- A direct adaptive method for faster backpropagation learning: the RPROP algorithmPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002