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Proceedings Article

Optical performance monitoring in 40-Gbps optical duobinary system using artificial neural networks trained with reconstructed eye diagram parameters

[+] Author Affiliations
Jun-sen Lai, Ai-ying Yang, Lin Zuo, Yu-nan Sun

Beijing Institute of Technology (China)

Proc. SPIE 8310, Network Architectures, Management, and Applications IX, 83100M (December 15, 2011); doi:10.1117/12.903195
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From Conference Volume 8310

  • Network Architectures, Management, and Applications IX
  • Lena Wosinska; Ken-ichi Sato; Jing Wu; Jie Zhang
  • Shanghai, China | November 13, 2011

abstract

A technique using artificial neural networks trained with parameters derived from reconstructed eye diagrams for optical performance monitoring in 40-Gbps optical duobinary (ODB) system is demonstrated. Firstly, the optical signal is asynchronously sampled by short pulse in the nonlinear medium such as semiconductor optical amplifier and highly nonlinear fiber, the sampled and collected data is then processed by improved software synchronization algorithm to obtain reconstructed eye diagrams without data clock recovery. Secondly, the features of the reconstructed eye diagrams are extracted to train the three-layer preceptor artificial neural network. Finally, the outputs of trained neural network are used to monitor multiple optical signal impairments. Simulation experiments of optical signal noise ratio (OSNR), chromatic dispersion (CD) and polarization mode dispersion (PMD) monitoring in 40-Gbps ODB system is presented. The proposed monitoring scheme can accurately identify simultaneous impairment with the root-mean-square (RMS) monitoring error less than 3%.

© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Citation

Jun-sen Lai ; Ai-ying Yang ; Lin Zuo and Yu-nan Sun
"Optical performance monitoring in 40-Gbps optical duobinary system using artificial neural networks trained with reconstructed eye diagram parameters", Proc. SPIE 8310, Network Architectures, Management, and Applications IX, 83100M (December 15, 2011); doi:10.1117/12.903195; http://dx.doi.org/10.1117/12.903195


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