Comparison of optical performance monitoring techniques using artificial neural networks
Ribeiro, V. M. C.
Lima, M. J. N.
Neural Computing and Applications Vol. NEW APPLICATIONS OF ARTIFICIAL NEURAL NETWORKS IN MODELING & CONTROL, Nº 1, pp. 1 - 7, April, 2013.
ISSN (print): 0941-0643
ISSN (online): 1433-3058
Journal Impact Factor: 0,812 (in 2009)
Digital Object Identifier: 10.1007/s00521-013-1405-z
In this paper, we make an overview of three techniques that have used artificial neural networks (ANNs) to model impairments in optical fiber. A compar-ison between a linear partial least squares regression algorithm and ANN is also shown. We demonstrate that nonlinear modeling is required for multi-impairment monitoring in optical fiber when using Parametric Asyn-chronous Eye Diagram (PAED). Results demonstrating the accuracy of PAED are also shown. A comparison between PAED and Synchronous Eye Diagrams is also demon-strated, for NRZ, RZ and QPSK modulated signals. We show that PAED can provide comprehensible diagrams for QPSK modulated signals, under a certain range of chro-matic dispersion.