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Publication Citation: Optical performance monitoring of (Q)PSK data channels using artificial neural networks trained with parameters derived from delay-tap asynchronous diagrams

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Author(s): Jeffrey A. Jargon; Xiaoxia Wu; Alan Willner; Loukas Paraschis;
Title: Optical performance monitoring of (Q)PSK data channels using artificial neural networks trained with parameters derived from delay-tap asynchronous diagrams
Published: February 15, 2011
Abstract: We demonstrate a technique of using artificial neural networks trained with parameters derived from delay-tap asynchronous diagrams for optical performance monitoring of phase shift keying (PSK) data signals. We show that asynchronous diagrams from balanced detection give superior results compared to direct detection in a 40 Gb/s binary PSK system. Experimental demonstration in a 100 Gb/s quadrature PSK system verifies the effectiveness of the proposed technique.
Citation: IEEE Photonics Technology Letters
Keywords: neural networks; optical fiber communication; optical performance monitoring; phase modulation
Research Areas: Electronics & Telecommunications, Measurement Solutions, Optoelectronics