Creating and sharing knowledge for telecommunications

Comparison of optical performance monitoring techniques using artificial neural networks

Ribeiro, V. M. C. ; Lima, M. J. N. ; Teixeira, A.

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

Abstract
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.