Title :
OSNR Monitoring for PM-QPSK Systems With Large Inline Chromatic Dispersion Using Artificial Neural Network Technique
Author :
Shen, Thomas Shun Rong ; Sui, Qi ; Lau, Alan Pak Tao
Author_Institution :
Department of Electrical Engineering, Stanford University, Stanford, CA, USA
Abstract :
We propose an optical signal-to-noise ratio (OSNR) monitoring technique for polarization-multiplexed (PM) quadrature phase shift keying (QPSK) systems with large inline chromatic dispersion (CD) based on artificial neural network (ANN) techniques. The transmitted signal is directly detected, and part of the corresponding radio frequency spectrum is used as the input to ANN. Simulation results for 112-Gb/s PM return-to-zero QPSK systems demonstrate an OSNR monitoring range of 12–24 dB in presence of CD up to 27000 ps/nm with a maximum monitoring error of 0.84 dB. Tolerance of the proposed technique on polarization-mode dispersion effects is also investigated.
Keywords :
Adaptive optics; Artificial neural networks; Monitoring; Optical noise; Optical polarization; Radio frequency; Signal to noise ratio; Artificial neural network (ANN); optical fiber communication; optical performance monitoring (OPM); optical signal-to-noise ratio (OSNR);
Journal_Title :
Photonics Technology Letters, IEEE
DOI :
10.1109/LPT.2012.2209413
