Abstract

In this paper we present a novel technique, based in what we have called Parametric Asynchronous Eye Diagram (PAED). We have used a simulation scheme, which includes a differentiator and an Artificial Neural Network to monitor simultaneously several impairments such as Chromatic Dispersion, Polarization Mode Dispersion and Optical Signal to Noise Ratio. A number of modulation formats, including NRZ, RZ and QPSK is used in the computation of results. This paper also demonstrates the effectiveness of this technique in monitoring with one single device, mixed traffic, with different bit rates and On-Off Keying (OOK) modulation formats traveling through the network.

© 2012 OSA

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  1. V. Ribeiro, L. Costa, A. Teixeira, R. Nogueira, and M. Lima, “Chromatic-dispersion-monitoring scheme using a mach-zehnder interferometer and q-factor calculation,” J. Opt. Commun. Netw. 2, 10–19 (2010).
    [CrossRef]
  2. A. Campillo, “Chromatic dispersion-monitoring technique based on phase-sensitive detection,” IEEE Photon. Technol. Lett. 17, 1241–1243 (2005).
    [CrossRef]
  3. P. Westbrook, B. Eggleton, G. Raybon, S. Hunsche, and T. H. Her, “Measurement of residual chromatic dispersion of a 40-gb/s rz signal via spectral broadening,” IEEE Photon. Technol. Lett. 14, 346–348 (2002).
    [CrossRef]
  4. S. M. R. M. Nezam, Y.-W. Song, C. Yu, J. E. McGeehan, A. B. Sahin, and A. E. Willner, “First-order pmd monitoring for nrz data using rf clock regeneration techniques,” J. Lightwave Technol. 22, 1086 (2004).
    [CrossRef]
  5. F. Khan, A. Lau, Z. Li, C. Lu, and P. Wai, “Osnr monitoring for rz-dqpsk systems using half-symbol delay-tap sampling technique,” IEEE Photon. Technol. Lett. 22, 823–825 (2010).
    [CrossRef]
  6. R. S. Luís, A. Teixeira, and P. Monteiro, “Optical signal-to-noise ratio estimation using reference asynchronous histograms,” J. Lightwave Technol. 27, 731–743 (2009).
    [CrossRef]
  7. T. Anderson, A. Kowalczyk, K. Clarke, S. Dods, D. Hewitt, and J. Li, “Multi impairment monitoring for optical networks,” J. Lightwave Technol. 27, 3729–3736 (2009).
    [CrossRef]
  8. J. A. Jargon, X. Wu, and A. E. Willner, “Optical performance monitoring by use of artificial neural networks trained with parameters derived from delay-tap asynchronous sampling,” in “Optical Fiber Communication Conference,” (Optical Society of America, 2009), paper OThH1.
  9. T. Anderson, S. Dods, A. Kowalczyk, J. Bedo, and K. P. Clarke, “Method and apparatus for sampled optical signal monitoring,” United States Patent and Trademark Office, (2009). Patent Application.
  10. J. Jargon, X. Wu, and A. Willner, “Optical performance monitoring using artificial neural networks trained with eye-diagram parameters,” IEEE Photon. Technol. Lett. 21, 54–56 (2009).
    [CrossRef]
  11. S. Wielandy, M. Fishteyn, and B. Zhu, “Optical performance monitoring using nonlinear detection,” J. Lightwave Technol. 22, 784–793 (2004).
    [CrossRef]
  12. J.-Y. Yang, L. Zhang, Y. Yue, J. Jackel, A. Agarwal, L. Paraschis, and A. E. Willner, “Cd-insensitive pmd monitoring of a high-speed polarization-multiplexed data channel,” Opt. Express 17, 18171–18177 (2009).
    [CrossRef] [PubMed]
  13. T. Shen, K. Meng, A. Lau, and Z. Y. Dong, “Optical performance monitoring using artificial neural network trained with asynchronous amplitude histograms,” IEEE Photon. Technol. Lett. 22, 1665–1667 (2010).
  14. X. Wu, J. Jargon, L. Paraschis, and A. Willner, “Ann-based optical performance monitoring of qpsk signals using parameters derived from balanced-detected asynchronous diagrams,” IEEE Photon. Technol. Lett. 23, 248–250 (2011).
    [CrossRef]
  15. X. Wu, J. Jargon, R. Skoog, L. Paraschis, and A. Willner, “Applications of artificial neural networks in optical performance monitoring,” J. Lightwave Technol. 27, 3580–3589 (2009).
    [CrossRef]
  16. V. M. Ribeiro, M. Lima, and A. Teixeira, “Parametric asynchronous eye diagram for optical performance monitoring,” in “Optical Fiber Communication Conference,” (Optical Society of America, 2012), paper JW2A.33.
  17. H. Wang, K.-Y. Lin, Z.-M. Tsai, L.-H. Lu, H.-C. Lu, C.-H. Wang, J.-H. Tsai, T.-W. Huang, and Y.-C. Lin, “Mmics in the millimeter-wave regime,” IEEE Microw. Mag. 10, 99–117 (2009).
    [CrossRef]
  18. P. Velanas, A. Bogris, A. Argyris, and D. Syvridis, “High-speed all-optical first- and second-order differentiators based on cross-phase modulation in fibers,” J. Lightwave Technol. 26, 3269–3276 (2008).
    [CrossRef]
  19. M. Kulishov and J. A. na, “Long-period fiber gratings as ultrafast optical differentiators,” Opt. Lett. 30, 2700–2702 (2005).
    [CrossRef] [PubMed]
  20. M. Li and J. Yao, “Multichannel photonic temporal differentiator for wavelength-division-multiplexed signal processing using a single fiber bragg grating,” in “Microwave Photonics (MWP), 2010 IEEE Topical Meeting on,” (2010), pp. 269–272.
  21. Y. Park, J. A. na, and R. Slavík, “Ultrafast all-optical first- and higher-order differentiators based on interferometers,” Opt. Lett. 32, 710–712 (2007).
    [CrossRef] [PubMed]
  22. Q.-J. Zhang, K. Gupta, and V. Devabhaktuni, “Artificial neural networks for rf and microwave design - from theory to practice,” IEEE Trans. Microw. Theory 51, 1339–1350 (2003).
    [CrossRef]
  23. J. Misra and I. Saha, “Artificial neural networks in hardware: A survey of two decades of progress,” Neurocomputing 74, 239–255 (2010).
    [CrossRef]

2011

X. Wu, J. Jargon, L. Paraschis, and A. Willner, “Ann-based optical performance monitoring of qpsk signals using parameters derived from balanced-detected asynchronous diagrams,” IEEE Photon. Technol. Lett. 23, 248–250 (2011).
[CrossRef]

2010

T. Shen, K. Meng, A. Lau, and Z. Y. Dong, “Optical performance monitoring using artificial neural network trained with asynchronous amplitude histograms,” IEEE Photon. Technol. Lett. 22, 1665–1667 (2010).

J. Misra and I. Saha, “Artificial neural networks in hardware: A survey of two decades of progress,” Neurocomputing 74, 239–255 (2010).
[CrossRef]

F. Khan, A. Lau, Z. Li, C. Lu, and P. Wai, “Osnr monitoring for rz-dqpsk systems using half-symbol delay-tap sampling technique,” IEEE Photon. Technol. Lett. 22, 823–825 (2010).
[CrossRef]

V. Ribeiro, L. Costa, A. Teixeira, R. Nogueira, and M. Lima, “Chromatic-dispersion-monitoring scheme using a mach-zehnder interferometer and q-factor calculation,” J. Opt. Commun. Netw. 2, 10–19 (2010).
[CrossRef]

2009

2008

2007

2005

M. Kulishov and J. A. na, “Long-period fiber gratings as ultrafast optical differentiators,” Opt. Lett. 30, 2700–2702 (2005).
[CrossRef] [PubMed]

A. Campillo, “Chromatic dispersion-monitoring technique based on phase-sensitive detection,” IEEE Photon. Technol. Lett. 17, 1241–1243 (2005).
[CrossRef]

2004

2003

Q.-J. Zhang, K. Gupta, and V. Devabhaktuni, “Artificial neural networks for rf and microwave design - from theory to practice,” IEEE Trans. Microw. Theory 51, 1339–1350 (2003).
[CrossRef]

2002

P. Westbrook, B. Eggleton, G. Raybon, S. Hunsche, and T. H. Her, “Measurement of residual chromatic dispersion of a 40-gb/s rz signal via spectral broadening,” IEEE Photon. Technol. Lett. 14, 346–348 (2002).
[CrossRef]

Agarwal, A.

Anderson, T.

T. Anderson, A. Kowalczyk, K. Clarke, S. Dods, D. Hewitt, and J. Li, “Multi impairment monitoring for optical networks,” J. Lightwave Technol. 27, 3729–3736 (2009).
[CrossRef]

T. Anderson, S. Dods, A. Kowalczyk, J. Bedo, and K. P. Clarke, “Method and apparatus for sampled optical signal monitoring,” United States Patent and Trademark Office, (2009). Patent Application.

Argyris, A.

Bedo, J.

T. Anderson, S. Dods, A. Kowalczyk, J. Bedo, and K. P. Clarke, “Method and apparatus for sampled optical signal monitoring,” United States Patent and Trademark Office, (2009). Patent Application.

Bogris, A.

Campillo, A.

A. Campillo, “Chromatic dispersion-monitoring technique based on phase-sensitive detection,” IEEE Photon. Technol. Lett. 17, 1241–1243 (2005).
[CrossRef]

Clarke, K.

Clarke, K. P.

T. Anderson, S. Dods, A. Kowalczyk, J. Bedo, and K. P. Clarke, “Method and apparatus for sampled optical signal monitoring,” United States Patent and Trademark Office, (2009). Patent Application.

Costa, L.

Devabhaktuni, V.

Q.-J. Zhang, K. Gupta, and V. Devabhaktuni, “Artificial neural networks for rf and microwave design - from theory to practice,” IEEE Trans. Microw. Theory 51, 1339–1350 (2003).
[CrossRef]

Dods, S.

T. Anderson, A. Kowalczyk, K. Clarke, S. Dods, D. Hewitt, and J. Li, “Multi impairment monitoring for optical networks,” J. Lightwave Technol. 27, 3729–3736 (2009).
[CrossRef]

T. Anderson, S. Dods, A. Kowalczyk, J. Bedo, and K. P. Clarke, “Method and apparatus for sampled optical signal monitoring,” United States Patent and Trademark Office, (2009). Patent Application.

Dong, Z. Y.

T. Shen, K. Meng, A. Lau, and Z. Y. Dong, “Optical performance monitoring using artificial neural network trained with asynchronous amplitude histograms,” IEEE Photon. Technol. Lett. 22, 1665–1667 (2010).

Eggleton, B.

P. Westbrook, B. Eggleton, G. Raybon, S. Hunsche, and T. H. Her, “Measurement of residual chromatic dispersion of a 40-gb/s rz signal via spectral broadening,” IEEE Photon. Technol. Lett. 14, 346–348 (2002).
[CrossRef]

Fishteyn, M.

Gupta, K.

Q.-J. Zhang, K. Gupta, and V. Devabhaktuni, “Artificial neural networks for rf and microwave design - from theory to practice,” IEEE Trans. Microw. Theory 51, 1339–1350 (2003).
[CrossRef]

Her, T. H.

P. Westbrook, B. Eggleton, G. Raybon, S. Hunsche, and T. H. Her, “Measurement of residual chromatic dispersion of a 40-gb/s rz signal via spectral broadening,” IEEE Photon. Technol. Lett. 14, 346–348 (2002).
[CrossRef]

Hewitt, D.

Huang, T.-W.

H. Wang, K.-Y. Lin, Z.-M. Tsai, L.-H. Lu, H.-C. Lu, C.-H. Wang, J.-H. Tsai, T.-W. Huang, and Y.-C. Lin, “Mmics in the millimeter-wave regime,” IEEE Microw. Mag. 10, 99–117 (2009).
[CrossRef]

Hunsche, S.

P. Westbrook, B. Eggleton, G. Raybon, S. Hunsche, and T. H. Her, “Measurement of residual chromatic dispersion of a 40-gb/s rz signal via spectral broadening,” IEEE Photon. Technol. Lett. 14, 346–348 (2002).
[CrossRef]

Jackel, J.

Jargon, J.

X. Wu, J. Jargon, L. Paraschis, and A. Willner, “Ann-based optical performance monitoring of qpsk signals using parameters derived from balanced-detected asynchronous diagrams,” IEEE Photon. Technol. Lett. 23, 248–250 (2011).
[CrossRef]

X. Wu, J. Jargon, R. Skoog, L. Paraschis, and A. Willner, “Applications of artificial neural networks in optical performance monitoring,” J. Lightwave Technol. 27, 3580–3589 (2009).
[CrossRef]

J. Jargon, X. Wu, and A. Willner, “Optical performance monitoring using artificial neural networks trained with eye-diagram parameters,” IEEE Photon. Technol. Lett. 21, 54–56 (2009).
[CrossRef]

Jargon, J. A.

J. A. Jargon, X. Wu, and A. E. Willner, “Optical performance monitoring by use of artificial neural networks trained with parameters derived from delay-tap asynchronous sampling,” in “Optical Fiber Communication Conference,” (Optical Society of America, 2009), paper OThH1.

Khan, F.

F. Khan, A. Lau, Z. Li, C. Lu, and P. Wai, “Osnr monitoring for rz-dqpsk systems using half-symbol delay-tap sampling technique,” IEEE Photon. Technol. Lett. 22, 823–825 (2010).
[CrossRef]

Kowalczyk, A.

T. Anderson, A. Kowalczyk, K. Clarke, S. Dods, D. Hewitt, and J. Li, “Multi impairment monitoring for optical networks,” J. Lightwave Technol. 27, 3729–3736 (2009).
[CrossRef]

T. Anderson, S. Dods, A. Kowalczyk, J. Bedo, and K. P. Clarke, “Method and apparatus for sampled optical signal monitoring,” United States Patent and Trademark Office, (2009). Patent Application.

Kulishov, M.

Lau, A.

T. Shen, K. Meng, A. Lau, and Z. Y. Dong, “Optical performance monitoring using artificial neural network trained with asynchronous amplitude histograms,” IEEE Photon. Technol. Lett. 22, 1665–1667 (2010).

F. Khan, A. Lau, Z. Li, C. Lu, and P. Wai, “Osnr monitoring for rz-dqpsk systems using half-symbol delay-tap sampling technique,” IEEE Photon. Technol. Lett. 22, 823–825 (2010).
[CrossRef]

Li, J.

Li, M.

M. Li and J. Yao, “Multichannel photonic temporal differentiator for wavelength-division-multiplexed signal processing using a single fiber bragg grating,” in “Microwave Photonics (MWP), 2010 IEEE Topical Meeting on,” (2010), pp. 269–272.

Li, Z.

F. Khan, A. Lau, Z. Li, C. Lu, and P. Wai, “Osnr monitoring for rz-dqpsk systems using half-symbol delay-tap sampling technique,” IEEE Photon. Technol. Lett. 22, 823–825 (2010).
[CrossRef]

Lima, M.

V. Ribeiro, L. Costa, A. Teixeira, R. Nogueira, and M. Lima, “Chromatic-dispersion-monitoring scheme using a mach-zehnder interferometer and q-factor calculation,” J. Opt. Commun. Netw. 2, 10–19 (2010).
[CrossRef]

V. M. Ribeiro, M. Lima, and A. Teixeira, “Parametric asynchronous eye diagram for optical performance monitoring,” in “Optical Fiber Communication Conference,” (Optical Society of America, 2012), paper JW2A.33.

Lin, K.-Y.

H. Wang, K.-Y. Lin, Z.-M. Tsai, L.-H. Lu, H.-C. Lu, C.-H. Wang, J.-H. Tsai, T.-W. Huang, and Y.-C. Lin, “Mmics in the millimeter-wave regime,” IEEE Microw. Mag. 10, 99–117 (2009).
[CrossRef]

Lin, Y.-C.

H. Wang, K.-Y. Lin, Z.-M. Tsai, L.-H. Lu, H.-C. Lu, C.-H. Wang, J.-H. Tsai, T.-W. Huang, and Y.-C. Lin, “Mmics in the millimeter-wave regime,” IEEE Microw. Mag. 10, 99–117 (2009).
[CrossRef]

Lu, C.

F. Khan, A. Lau, Z. Li, C. Lu, and P. Wai, “Osnr monitoring for rz-dqpsk systems using half-symbol delay-tap sampling technique,” IEEE Photon. Technol. Lett. 22, 823–825 (2010).
[CrossRef]

Lu, H.-C.

H. Wang, K.-Y. Lin, Z.-M. Tsai, L.-H. Lu, H.-C. Lu, C.-H. Wang, J.-H. Tsai, T.-W. Huang, and Y.-C. Lin, “Mmics in the millimeter-wave regime,” IEEE Microw. Mag. 10, 99–117 (2009).
[CrossRef]

Lu, L.-H.

H. Wang, K.-Y. Lin, Z.-M. Tsai, L.-H. Lu, H.-C. Lu, C.-H. Wang, J.-H. Tsai, T.-W. Huang, and Y.-C. Lin, “Mmics in the millimeter-wave regime,” IEEE Microw. Mag. 10, 99–117 (2009).
[CrossRef]

Luís, R. S.

McGeehan, J. E.

Meng, K.

T. Shen, K. Meng, A. Lau, and Z. Y. Dong, “Optical performance monitoring using artificial neural network trained with asynchronous amplitude histograms,” IEEE Photon. Technol. Lett. 22, 1665–1667 (2010).

Misra, J.

J. Misra and I. Saha, “Artificial neural networks in hardware: A survey of two decades of progress,” Neurocomputing 74, 239–255 (2010).
[CrossRef]

Monteiro, P.

na, J. A.

Nezam, S. M. R. M.

Nogueira, R.

Paraschis, L.

Park, Y.

Raybon, G.

P. Westbrook, B. Eggleton, G. Raybon, S. Hunsche, and T. H. Her, “Measurement of residual chromatic dispersion of a 40-gb/s rz signal via spectral broadening,” IEEE Photon. Technol. Lett. 14, 346–348 (2002).
[CrossRef]

Ribeiro, V.

Ribeiro, V. M.

V. M. Ribeiro, M. Lima, and A. Teixeira, “Parametric asynchronous eye diagram for optical performance monitoring,” in “Optical Fiber Communication Conference,” (Optical Society of America, 2012), paper JW2A.33.

Saha, I.

J. Misra and I. Saha, “Artificial neural networks in hardware: A survey of two decades of progress,” Neurocomputing 74, 239–255 (2010).
[CrossRef]

Sahin, A. B.

Shen, T.

T. Shen, K. Meng, A. Lau, and Z. Y. Dong, “Optical performance monitoring using artificial neural network trained with asynchronous amplitude histograms,” IEEE Photon. Technol. Lett. 22, 1665–1667 (2010).

Skoog, R.

Slavík, R.

Song, Y.-W.

Syvridis, D.

Teixeira, A.

Tsai, J.-H.

H. Wang, K.-Y. Lin, Z.-M. Tsai, L.-H. Lu, H.-C. Lu, C.-H. Wang, J.-H. Tsai, T.-W. Huang, and Y.-C. Lin, “Mmics in the millimeter-wave regime,” IEEE Microw. Mag. 10, 99–117 (2009).
[CrossRef]

Tsai, Z.-M.

H. Wang, K.-Y. Lin, Z.-M. Tsai, L.-H. Lu, H.-C. Lu, C.-H. Wang, J.-H. Tsai, T.-W. Huang, and Y.-C. Lin, “Mmics in the millimeter-wave regime,” IEEE Microw. Mag. 10, 99–117 (2009).
[CrossRef]

Velanas, P.

Wai, P.

F. Khan, A. Lau, Z. Li, C. Lu, and P. Wai, “Osnr monitoring for rz-dqpsk systems using half-symbol delay-tap sampling technique,” IEEE Photon. Technol. Lett. 22, 823–825 (2010).
[CrossRef]

Wang, C.-H.

H. Wang, K.-Y. Lin, Z.-M. Tsai, L.-H. Lu, H.-C. Lu, C.-H. Wang, J.-H. Tsai, T.-W. Huang, and Y.-C. Lin, “Mmics in the millimeter-wave regime,” IEEE Microw. Mag. 10, 99–117 (2009).
[CrossRef]

Wang, H.

H. Wang, K.-Y. Lin, Z.-M. Tsai, L.-H. Lu, H.-C. Lu, C.-H. Wang, J.-H. Tsai, T.-W. Huang, and Y.-C. Lin, “Mmics in the millimeter-wave regime,” IEEE Microw. Mag. 10, 99–117 (2009).
[CrossRef]

Westbrook, P.

P. Westbrook, B. Eggleton, G. Raybon, S. Hunsche, and T. H. Her, “Measurement of residual chromatic dispersion of a 40-gb/s rz signal via spectral broadening,” IEEE Photon. Technol. Lett. 14, 346–348 (2002).
[CrossRef]

Wielandy, S.

Willner, A.

X. Wu, J. Jargon, L. Paraschis, and A. Willner, “Ann-based optical performance monitoring of qpsk signals using parameters derived from balanced-detected asynchronous diagrams,” IEEE Photon. Technol. Lett. 23, 248–250 (2011).
[CrossRef]

X. Wu, J. Jargon, R. Skoog, L. Paraschis, and A. Willner, “Applications of artificial neural networks in optical performance monitoring,” J. Lightwave Technol. 27, 3580–3589 (2009).
[CrossRef]

J. Jargon, X. Wu, and A. Willner, “Optical performance monitoring using artificial neural networks trained with eye-diagram parameters,” IEEE Photon. Technol. Lett. 21, 54–56 (2009).
[CrossRef]

Willner, A. E.

Wu, X.

X. Wu, J. Jargon, L. Paraschis, and A. Willner, “Ann-based optical performance monitoring of qpsk signals using parameters derived from balanced-detected asynchronous diagrams,” IEEE Photon. Technol. Lett. 23, 248–250 (2011).
[CrossRef]

X. Wu, J. Jargon, R. Skoog, L. Paraschis, and A. Willner, “Applications of artificial neural networks in optical performance monitoring,” J. Lightwave Technol. 27, 3580–3589 (2009).
[CrossRef]

J. Jargon, X. Wu, and A. Willner, “Optical performance monitoring using artificial neural networks trained with eye-diagram parameters,” IEEE Photon. Technol. Lett. 21, 54–56 (2009).
[CrossRef]

J. A. Jargon, X. Wu, and A. E. Willner, “Optical performance monitoring by use of artificial neural networks trained with parameters derived from delay-tap asynchronous sampling,” in “Optical Fiber Communication Conference,” (Optical Society of America, 2009), paper OThH1.

Yang, J.-Y.

Yao, J.

M. Li and J. Yao, “Multichannel photonic temporal differentiator for wavelength-division-multiplexed signal processing using a single fiber bragg grating,” in “Microwave Photonics (MWP), 2010 IEEE Topical Meeting on,” (2010), pp. 269–272.

Yu, C.

Yue, Y.

Zhang, L.

Zhang, Q.-J.

Q.-J. Zhang, K. Gupta, and V. Devabhaktuni, “Artificial neural networks for rf and microwave design - from theory to practice,” IEEE Trans. Microw. Theory 51, 1339–1350 (2003).
[CrossRef]

Zhu, B.

IEEE Microw. Mag.

H. Wang, K.-Y. Lin, Z.-M. Tsai, L.-H. Lu, H.-C. Lu, C.-H. Wang, J.-H. Tsai, T.-W. Huang, and Y.-C. Lin, “Mmics in the millimeter-wave regime,” IEEE Microw. Mag. 10, 99–117 (2009).
[CrossRef]

IEEE Photon. Technol. Lett.

T. Shen, K. Meng, A. Lau, and Z. Y. Dong, “Optical performance monitoring using artificial neural network trained with asynchronous amplitude histograms,” IEEE Photon. Technol. Lett. 22, 1665–1667 (2010).

X. Wu, J. Jargon, L. Paraschis, and A. Willner, “Ann-based optical performance monitoring of qpsk signals using parameters derived from balanced-detected asynchronous diagrams,” IEEE Photon. Technol. Lett. 23, 248–250 (2011).
[CrossRef]

F. Khan, A. Lau, Z. Li, C. Lu, and P. Wai, “Osnr monitoring for rz-dqpsk systems using half-symbol delay-tap sampling technique,” IEEE Photon. Technol. Lett. 22, 823–825 (2010).
[CrossRef]

A. Campillo, “Chromatic dispersion-monitoring technique based on phase-sensitive detection,” IEEE Photon. Technol. Lett. 17, 1241–1243 (2005).
[CrossRef]

P. Westbrook, B. Eggleton, G. Raybon, S. Hunsche, and T. H. Her, “Measurement of residual chromatic dispersion of a 40-gb/s rz signal via spectral broadening,” IEEE Photon. Technol. Lett. 14, 346–348 (2002).
[CrossRef]

J. Jargon, X. Wu, and A. Willner, “Optical performance monitoring using artificial neural networks trained with eye-diagram parameters,” IEEE Photon. Technol. Lett. 21, 54–56 (2009).
[CrossRef]

IEEE Trans. Microw. Theory

Q.-J. Zhang, K. Gupta, and V. Devabhaktuni, “Artificial neural networks for rf and microwave design - from theory to practice,” IEEE Trans. Microw. Theory 51, 1339–1350 (2003).
[CrossRef]

J. Lightwave Technol.

J. Opt. Commun. Netw.

Neurocomputing

J. Misra and I. Saha, “Artificial neural networks in hardware: A survey of two decades of progress,” Neurocomputing 74, 239–255 (2010).
[CrossRef]

Opt. Express

Opt. Lett.

Other

M. Li and J. Yao, “Multichannel photonic temporal differentiator for wavelength-division-multiplexed signal processing using a single fiber bragg grating,” in “Microwave Photonics (MWP), 2010 IEEE Topical Meeting on,” (2010), pp. 269–272.

V. M. Ribeiro, M. Lima, and A. Teixeira, “Parametric asynchronous eye diagram for optical performance monitoring,” in “Optical Fiber Communication Conference,” (Optical Society of America, 2012), paper JW2A.33.

J. A. Jargon, X. Wu, and A. E. Willner, “Optical performance monitoring by use of artificial neural networks trained with parameters derived from delay-tap asynchronous sampling,” in “Optical Fiber Communication Conference,” (Optical Society of America, 2009), paper OThH1.

T. Anderson, S. Dods, A. Kowalczyk, J. Bedo, and K. P. Clarke, “Method and apparatus for sampled optical signal monitoring,” United States Patent and Trademark Office, (2009). Patent Application.

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Figures (8)

Fig. 1
Fig. 1

Artificial Neural Network. Qn represents the nth subset of the diagram of PAED (see 5), σ the standard deviation, Q n ¯ and d Q n ¯ d t, represents the mean of the amplitude and derivative of the subset of the diagram, respectively.

Fig. 2
Fig. 2

Setup of the novel technique using an electrical differentiator. SMF-Single Mode Fiber, DCF-Dispersion Compensating Fiber.

Fig. 3
Fig. 3

(a) Amplitude and (b) phase transfer function of the electrical differentiator, represented in the simulation setup of Fig. 2.

Fig. 4
Fig. 4

Diagrams generated by the novel technique, using different modulation formats and bit rates. (a)-10 Gbit/s RZ signal, (b)-10 Gbit/s NRZ signal, (d)-20 Gbit/s NRZ signal and (e)-20 Gbit/s RZ signal with CD=0 ps/nm, PMD=0 ps, OSNR=30 dB. (c)-10 Gbit/s NRZ signal and (f)-10 Gbit/s RZ signal with CD=500 ps/nm, PMD=7 ps, OSNR=20 dB.

Fig. 5
Fig. 5

Parametric Asynchronous Eye Diagram splitted in 6 subsets of the diagram for training procedure.

Fig. 6
Fig. 6

10 Gbit/s NRZ. Error bars of CD PMD and OSNR test data. (a)-CD, (b)-PMD and (c)-OSNR.

Fig. 7
Fig. 7

40 Gbit/s NRZ-QPSK. RMSE as a function of CD, PMD and OSNR test data. (a)-CD, (b)-PMD and (c)-OSNR.

Fig. 8
Fig. 8

Predictions of CD, bit rate, PMD, modulation format and PMD as a function of number of the test data examples, when mixed traffic is in the network. (a)-CD and bit rate,(b)-PMD, modulation format and (c)-OSNR.

Tables (1)

Tables Icon

Table 1 Monitoring Windows for each Impairment - RMSE-Root Mean Square Error

Metrics