Skip to main content
U.S. flag

An official website of the United States government

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.

Applications of artificial neural networks in optical performance monitoring

Published

Author(s)

Jeffrey A. Jargon, Xiaoxia Wu, Ronald Skoog, Loukas Paraschis, Alan Willner

Abstract

Applications using artificial neural networks (ANNs) for optical performance monitoring (OPM) are proposed and demonstrated. Simultaneous identification of optical signal-to-noise-ratio (OSNR), chromatic dispersion (CD), and polarization-mode-dispersion (PMD) from eye-diagram parameters is shown via simulation in both 40 Gb/s on-off keying (OOK) and differential phase-shift-keying (DPSK) systems. Experimental verification is performed to simultaneously identify OSNR and CD. We then extend this technique to simultaneously identify accumulated fiber nonlinearity, OSNR, CD, and PMD from eye-diagram and eye-histogram parameters in a 3-channel 40 Gb/s DPSK wavelength- division multiplexing (WDM) system. Furthermore, we propose using this ANN approach to monitor impairment causing changes from a baseline. Simultaneous identification of accumulated fiber nonlinearity, OSNR, CD, and PMD causing changes from a baseline by use of the eye-diagram and eye-histogram parameters is obtained and high correlation coefficients are achieved with various baselines. Finally, the ANNs are also shown for simultaneous identification of in-phase/quadrature (I/Q) data misalignment and data/carver misalignment in return-to-zero differential quadrature phase shift keying (RZ-DQPSK) transmitters.
Citation
Journal of Lightwave Technology
Volume
27
Issue
16

Keywords

neural networks, optical fiber communication, optical performance monitoring, phase modulation

Citation

Jargon, J. , Wu, X. , Skoog, R. , Paraschis, L. and Willner, A. (2009), Applications of artificial neural networks in optical performance monitoring, Journal of Lightwave Technology, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=901396 (Accessed March 28, 2024)
Created August 15, 2009, Updated February 19, 2017