Comparison of optical performance monitoring techniques using artificial neural networks

Vítor Ribeiro, Mário Lima, António Teixeira

Research output: Contribution to journalArticlepeer-review


In this paper, we make an overview of three techniques that have used artificial neural networks (ANNs) to model impairments in optical fiber. A comparison 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 Asynchronous Eye Diagram (PAED). Results demonstrating the accuracy of PAED are also shown. A comparison between PAED and Synchronous Eye Diagrams is also demonstrated, for NRZ, RZ and QPSK modulated signals. We show that PAED can provide comprehensible diagrams for QPSK modulated signals, under a certain range of chromatic dispersion.
Original languageEnglish
Pages (from-to)583–589
JournalNeural Computing and Applications
Issue number3-4
Publication statusPublished - 14 Apr 2013


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