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Monitoring I/Q data and pulse carving misalignments in RZ-DQPSK transmitters using a neural network approach

Published

Author(s)

Jeffrey A. Jargon, Xiaoxia Wu, Louis Christen, Alan Willner, Loukas Paraschis

Abstract

We propose a technique using artificial neural networks (ANNs) to simultaneously identify I/Q data misalignment and data/carver misalignment in both parallel-type and serial-type RZ-DQPSK transmitters. A correlation coefficient of 0.99 is obtained by using a 3-input ANN for the parallel case and a 2-input ANN for the serial case.
Proceedings Title
The 21st Annual Meeting of The IEEE Lasers & Electro-Optics Society
Conference Dates
November 9-13, 2008
Conference Location
Newport Beach, CA

Keywords

Artificial neural network, fiber optics communications, return-to-zero differential quadrature phase-shift-keying (RZ-DQPSK), synchronization monitoring.

Citation

Jargon, J. , Wu, X. , Christen, L. , Willner, A. and Paraschis, L. (2008), Monitoring I/Q data and pulse carving misalignments in RZ-DQPSK transmitters using a neural network approach, The 21st Annual Meeting of The IEEE Lasers & Electro-Optics Society, Newport Beach, CA, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=33152 (Accessed June 20, 2024)

Issues

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Created November 1, 2008, Updated February 19, 2017