Abstract

Optical spectrum (OS) is a vital characteristic of optical signals. Ultra-high resolution (UHR) OS can provide more detailed and accurate information for optical performance monitoring and optical link quality diagnosis. By comparing actual signal UHR-OS observed at in-line monitoring points with the theoretical ideal ones, various signal distortions can be readily identified and more accurately estimated. But in the future flexible heterogeneous optical networks optical signals with different symbol rates, modulation formats and pulse shaping schemes may coexist in the same system. Hence the ideal reference OS of the channel to be monitored can’t be assumed to be fixed or known in advance. It may also be impossible to undertake a reference OS measurement at or near the transmitter as the route path may be dynamically generated. To solve this problem we proposed an automatic ideal reference optical spectrum retrieval (OSR) method according to the actually observed ones. The OSR method can tolerate large OS distortions due to non-ideal optical links or transmitters by the integration of two machine learning techniques, namely unsupervised principle component analysis (PCA) and supervised multiclass support vector machines (SVMs) for feature extraction and UHR-OS classification, respectively. Extensive simulations conducted for nine types of optical signals commonly used show that this method performs very well in the presence of various significant distortions caused by non-ideal optical links or transmitters.

© 2017 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

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References

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2017 (4)

2016 (2)

2015 (3)

2014 (3)

2013 (1)

R. Borkowski, D. Zibar, A. Caballero, V. Arlunno, and I. T. Monroy, “Stokes Space-Based Optical Modulation Format Recognition for Digital Coherent Receivers,” IEEE Photonics Technol. Lett. 25(21), 2129–2132 (2013).
[Crossref]

2012 (1)

2011 (2)

G. Gariépy, G. He, and G. W. Schinn, “Non-intrusive measurement of In-Band OSNR of high bitrate polarization-multiplexed signals,” Opt. Fiber Technol. 17(5), 518–522 (2011).
[Crossref]

C. C. Chang and C. J. Lin, “LIBSVM: a library for support vector machines,” ACM Trans. Intell. Syst. Technol. 2(3), 27 (2011).
[Crossref]

2009 (1)

Y. Bengio, “Learning deep architectures for AI,” Found. Trends Mach. Learn. 2(1), 1–127 (2009).
[Crossref]

2006 (1)

2005 (1)

J. M. S. Domingo, J. Pelayo, F. Villuendas, C. D. Heras, and E. Pellejer, “Very high resolution optical spectrometry by stimulated Brillouin scattering,” IEEE Photonics Technol. Lett. 17(4), 855–857 (2005).
[Crossref]

2002 (1)

D. M. Baney, B. Szafraniec, and A. Motamedi, “Coherent optical spectrum analyzer,” IEEE Photonics Technol. Lett. 14(3), 355–357 (2002).
[Crossref]

2000 (1)

T. Saito, T. Ota, T. Toratani, and Y. Ono, “16-ch arrayed waveguide grating module with 100-GHz spacing,” Furukawa Review 19, 47–52 (2000).

Al-Arashi, W. H.

Arlunno, V.

R. Borkowski, D. Zibar, A. Caballero, V. Arlunno, and I. T. Monroy, “Stokes Space-Based Optical Modulation Format Recognition for Digital Coherent Receivers,” IEEE Photonics Technol. Lett. 25(21), 2129–2132 (2013).
[Crossref]

Baney, D. M.

D. M. Baney, B. Szafraniec, and A. Motamedi, “Coherent optical spectrum analyzer,” IEEE Photonics Technol. Lett. 14(3), 355–357 (2002).
[Crossref]

Bengio, Y.

Y. Bengio, “Learning deep architectures for AI,” Found. Trends Mach. Learn. 2(1), 1–127 (2009).
[Crossref]

Bilal, S. M.

Bohn, M.

T. Rahman, A. Napoli, D. Rafique, B. Spinnler, M. Kuschnerov, I. Lobato, B. Clouet, M. Bohn, C. Okonkwo, and H. de Waardt, “On the mitigation of optical filtering penalties originating from ROADM cascade,” IEEE Photonics Technol. Lett. 26(2), 154–157 (2014).
[Crossref]

Borkowski, R.

R. Borkowski, D. Zibar, A. Caballero, V. Arlunno, and I. T. Monroy, “Stokes Space-Based Optical Modulation Format Recognition for Digital Coherent Receivers,” IEEE Photonics Technol. Lett. 25(21), 2129–2132 (2013).
[Crossref]

Bosco, G.

Caballero, A.

R. Borkowski, D. Zibar, A. Caballero, V. Arlunno, and I. T. Monroy, “Stokes Space-Based Optical Modulation Format Recognition for Digital Coherent Receivers,” IEEE Photonics Technol. Lett. 25(21), 2129–2132 (2013).
[Crossref]

Chang, C. C.

C. C. Chang and C. J. Lin, “LIBSVM: a library for support vector machines,” ACM Trans. Intell. Syst. Technol. 2(3), 27 (2011).
[Crossref]

Chen, Z.

Chiadò Piat, A.

Clouet, B.

T. Rahman, A. Napoli, D. Rafique, B. Spinnler, M. Kuschnerov, I. Lobato, B. Clouet, M. Bohn, C. Okonkwo, and H. de Waardt, “On the mitigation of optical filtering penalties originating from ROADM cascade,” IEEE Photonics Technol. Lett. 26(2), 154–157 (2014).
[Crossref]

Cugini, F.

de Waardt, H.

J. M. Fabrega, M. Svaluto Moreolo, L. Martín, A. Chiadò Piat, E. Riccardi, D. Roccato, N. Sambo, F. Cugini, L. Potì, S. Yan, E. Hugues-Salas, D. Simeonidou, M. Gunkel, R. Palmer, S. Fedderwitz, D. Rafique, T. Rahman, H. de Waardt, and A. Napoli, “On the Filter Narrowing Issues in Elastic Optical Networks,” J. Opt. Commun. Netw. 8(7), A23–A33 (2016).
[Crossref]

T. Rahman, A. Napoli, D. Rafique, B. Spinnler, M. Kuschnerov, I. Lobato, B. Clouet, M. Bohn, C. Okonkwo, and H. de Waardt, “On the mitigation of optical filtering penalties originating from ROADM cascade,” IEEE Photonics Technol. Lett. 26(2), 154–157 (2014).
[Crossref]

Desalvo, R.

Diniz, J.

Diniz, J. C. M.

Domingo, J. M. S.

J. M. S. Domingo, J. Pelayo, F. Villuendas, C. D. Heras, and E. Pellejer, “Very high resolution optical spectrometry by stimulated Brillouin scattering,” IEEE Photonics Technol. Lett. 17(4), 855–857 (2005).
[Crossref]

Dong, Z.

Fabrega, J. M.

Fedderwitz, S.

Gariépy, D.

Gariépy, G.

G. Gariépy, G. He, and G. W. Schinn, “Non-intrusive measurement of In-Band OSNR of high bitrate polarization-multiplexed signals,” Opt. Fiber Technol. 17(5), 518–522 (2011).
[Crossref]

Gunkel, M.

Guo, Z.

He, G.

Heras, C. D.

J. M. S. Domingo, J. Pelayo, F. Villuendas, C. D. Heras, and E. Pellejer, “Very high resolution optical spectrometry by stimulated Brillouin scattering,” IEEE Photonics Technol. Lett. 17(4), 855–857 (2005).
[Crossref]

Hugues-Salas, E.

Ip, E.

Isautier, P.

Jones, R.

Kahn, J. M.

Ke, C.

Khan, F. N.

Kuschnerov, M.

T. Rahman, A. Napoli, D. Rafique, B. Spinnler, M. Kuschnerov, I. Lobato, B. Clouet, M. Bohn, C. Okonkwo, and H. de Waardt, “On the mitigation of optical filtering penalties originating from ROADM cascade,” IEEE Photonics Technol. Lett. 26(2), 154–157 (2014).
[Crossref]

Lau, A. P. T.

Li, L.

Lin, C. J.

C. C. Chang and C. J. Lin, “LIBSVM: a library for support vector machines,” ACM Trans. Intell. Syst. Technol. 2(3), 27 (2011).
[Crossref]

Liu, D.

Lobato, I.

T. Rahman, A. Napoli, D. Rafique, B. Spinnler, M. Kuschnerov, I. Lobato, B. Clouet, M. Bohn, C. Okonkwo, and H. de Waardt, “On the mitigation of optical filtering penalties originating from ROADM cascade,” IEEE Photonics Technol. Lett. 26(2), 154–157 (2014).
[Crossref]

Lu, C.

Lu, Y.

Martín, L.

Monroy, I. T.

R. Borkowski, D. Zibar, A. Caballero, V. Arlunno, and I. T. Monroy, “Stokes Space-Based Optical Modulation Format Recognition for Digital Coherent Receivers,” IEEE Photonics Technol. Lett. 25(21), 2129–2132 (2013).
[Crossref]

Motamedi, A.

D. M. Baney, B. Szafraniec, and A. Motamedi, “Coherent optical spectrum analyzer,” IEEE Photonics Technol. Lett. 14(3), 355–357 (2002).
[Crossref]

Napoli, A.

J. M. Fabrega, M. Svaluto Moreolo, L. Martín, A. Chiadò Piat, E. Riccardi, D. Roccato, N. Sambo, F. Cugini, L. Potì, S. Yan, E. Hugues-Salas, D. Simeonidou, M. Gunkel, R. Palmer, S. Fedderwitz, D. Rafique, T. Rahman, H. de Waardt, and A. Napoli, “On the Filter Narrowing Issues in Elastic Optical Networks,” J. Opt. Commun. Netw. 8(7), A23–A33 (2016).
[Crossref]

T. Rahman, A. Napoli, D. Rafique, B. Spinnler, M. Kuschnerov, I. Lobato, B. Clouet, M. Bohn, C. Okonkwo, and H. de Waardt, “On the mitigation of optical filtering penalties originating from ROADM cascade,” IEEE Photonics Technol. Lett. 26(2), 154–157 (2014).
[Crossref]

Okonkwo, C.

T. Rahman, A. Napoli, D. Rafique, B. Spinnler, M. Kuschnerov, I. Lobato, B. Clouet, M. Bohn, C. Okonkwo, and H. de Waardt, “On the mitigation of optical filtering penalties originating from ROADM cascade,” IEEE Photonics Technol. Lett. 26(2), 154–157 (2014).
[Crossref]

Ono, Y.

T. Saito, T. Ota, T. Toratani, and Y. Ono, “16-ch arrayed waveguide grating module with 100-GHz spacing,” Furukawa Review 19, 47–52 (2000).

Ota, T.

T. Saito, T. Ota, T. Toratani, and Y. Ono, “16-ch arrayed waveguide grating module with 100-GHz spacing,” Furukawa Review 19, 47–52 (2000).

Palmer, R.

Pan, J.

Pelayo, J.

J. M. S. Domingo, J. Pelayo, F. Villuendas, C. D. Heras, and E. Pellejer, “Very high resolution optical spectrometry by stimulated Brillouin scattering,” IEEE Photonics Technol. Lett. 17(4), 855–857 (2005).
[Crossref]

Pellejer, E.

J. M. S. Domingo, J. Pelayo, F. Villuendas, C. D. Heras, and E. Pellejer, “Very high resolution optical spectrometry by stimulated Brillouin scattering,” IEEE Photonics Technol. Lett. 17(4), 855–857 (2005).
[Crossref]

Piels, M.

Potì, L.

Rafique, D.

J. M. Fabrega, M. Svaluto Moreolo, L. Martín, A. Chiadò Piat, E. Riccardi, D. Roccato, N. Sambo, F. Cugini, L. Potì, S. Yan, E. Hugues-Salas, D. Simeonidou, M. Gunkel, R. Palmer, S. Fedderwitz, D. Rafique, T. Rahman, H. de Waardt, and A. Napoli, “On the Filter Narrowing Issues in Elastic Optical Networks,” J. Opt. Commun. Netw. 8(7), A23–A33 (2016).
[Crossref]

T. Rahman, A. Napoli, D. Rafique, B. Spinnler, M. Kuschnerov, I. Lobato, B. Clouet, M. Bohn, C. Okonkwo, and H. de Waardt, “On the mitigation of optical filtering penalties originating from ROADM cascade,” IEEE Photonics Technol. Lett. 26(2), 154–157 (2014).
[Crossref]

Rahman, T.

J. M. Fabrega, M. Svaluto Moreolo, L. Martín, A. Chiadò Piat, E. Riccardi, D. Roccato, N. Sambo, F. Cugini, L. Potì, S. Yan, E. Hugues-Salas, D. Simeonidou, M. Gunkel, R. Palmer, S. Fedderwitz, D. Rafique, T. Rahman, H. de Waardt, and A. Napoli, “On the Filter Narrowing Issues in Elastic Optical Networks,” J. Opt. Commun. Netw. 8(7), A23–A33 (2016).
[Crossref]

T. Rahman, A. Napoli, D. Rafique, B. Spinnler, M. Kuschnerov, I. Lobato, B. Clouet, M. Bohn, C. Okonkwo, and H. de Waardt, “On the mitigation of optical filtering penalties originating from ROADM cascade,” IEEE Photonics Technol. Lett. 26(2), 154–157 (2014).
[Crossref]

Ralph, S. E.

Riccardi, E.

Roccato, D.

Saito, T.

T. Saito, T. Ota, T. Toratani, and Y. Ono, “16-ch arrayed waveguide grating module with 100-GHz spacing,” Furukawa Review 19, 47–52 (2000).

Sambo, N.

Schinn, G. W.

G. Gariépy, G. He, and G. W. Schinn, “Non-intrusive measurement of In-Band OSNR of high bitrate polarization-multiplexed signals,” Opt. Fiber Technol. 17(5), 518–522 (2011).
[Crossref]

Searcy, S.

Simeonidou, D.

Spinnler, B.

T. Rahman, A. Napoli, D. Rafique, B. Spinnler, M. Kuschnerov, I. Lobato, B. Clouet, M. Bohn, C. Okonkwo, and H. de Waardt, “On the mitigation of optical filtering penalties originating from ROADM cascade,” IEEE Photonics Technol. Lett. 26(2), 154–157 (2014).
[Crossref]

Svaluto Moreolo, M.

Szafraniec, B.

D. M. Baney, B. Szafraniec, and A. Motamedi, “Coherent optical spectrum analyzer,” IEEE Photonics Technol. Lett. 14(3), 355–357 (2002).
[Crossref]

Tan, M. C.

Tao, Z.

Tao Lau, A. P.

Thrane, J.

Tibuleac, S.

Toratani, T.

T. Saito, T. Ota, T. Toratani, and Y. Ono, “16-ch arrayed waveguide grating module with 100-GHz spacing,” Furukawa Review 19, 47–52 (2000).

Villuendas, F.

J. M. S. Domingo, J. Pelayo, F. Villuendas, C. D. Heras, and E. Pellejer, “Very high resolution optical spectrometry by stimulated Brillouin scattering,” IEEE Photonics Technol. Lett. 17(4), 855–857 (2005).
[Crossref]

Wass, J.

Xing, C.

Yan, S.

Yu, C.

Zhang, C.

Zhang, K.

Zheng, Z.

Zhong, K.

Zhong, Y.

Zhou, X.

Zhou, Y.

Zhu, L.

Zhu, X.

Zibar, D.

J. Thrane, J. Wass, J. Diniz, M. Piels, J. C. M. Diniz, R. Jones, and D. Zibar, “Machine Learning Techniques for Optical Performance Monitoring from Directly Detected PDM-QAM Signals,” J. Lightwave Technol. 35(4), 868–875 (2017).
[Crossref]

R. Borkowski, D. Zibar, A. Caballero, V. Arlunno, and I. T. Monroy, “Stokes Space-Based Optical Modulation Format Recognition for Digital Coherent Receivers,” IEEE Photonics Technol. Lett. 25(21), 2129–2132 (2013).
[Crossref]

ACM Trans. Intell. Syst. Technol. (1)

C. C. Chang and C. J. Lin, “LIBSVM: a library for support vector machines,” ACM Trans. Intell. Syst. Technol. 2(3), 27 (2011).
[Crossref]

Found. Trends Mach. Learn. (1)

Y. Bengio, “Learning deep architectures for AI,” Found. Trends Mach. Learn. 2(1), 1–127 (2009).
[Crossref]

Furukawa Review (1)

T. Saito, T. Ota, T. Toratani, and Y. Ono, “16-ch arrayed waveguide grating module with 100-GHz spacing,” Furukawa Review 19, 47–52 (2000).

IEEE Photonics Technol. Lett. (4)

R. Borkowski, D. Zibar, A. Caballero, V. Arlunno, and I. T. Monroy, “Stokes Space-Based Optical Modulation Format Recognition for Digital Coherent Receivers,” IEEE Photonics Technol. Lett. 25(21), 2129–2132 (2013).
[Crossref]

J. M. S. Domingo, J. Pelayo, F. Villuendas, C. D. Heras, and E. Pellejer, “Very high resolution optical spectrometry by stimulated Brillouin scattering,” IEEE Photonics Technol. Lett. 17(4), 855–857 (2005).
[Crossref]

D. M. Baney, B. Szafraniec, and A. Motamedi, “Coherent optical spectrum analyzer,” IEEE Photonics Technol. Lett. 14(3), 355–357 (2002).
[Crossref]

T. Rahman, A. Napoli, D. Rafique, B. Spinnler, M. Kuschnerov, I. Lobato, B. Clouet, M. Bohn, C. Okonkwo, and H. de Waardt, “On the mitigation of optical filtering penalties originating from ROADM cascade,” IEEE Photonics Technol. Lett. 26(2), 154–157 (2014).
[Crossref]

J. Lightwave Technol. (4)

J. Opt. Commun. Netw. (2)

Opt. Express (6)

Opt. Fiber Technol. (1)

G. Gariépy, G. He, and G. W. Schinn, “Non-intrusive measurement of In-Band OSNR of high bitrate polarization-multiplexed signals,” Opt. Fiber Technol. 17(5), 518–522 (2011).
[Crossref]

Opt. Lett. (1)

Other (11)

Aragon Photonics, “Aragon Photonics BOSA 100 & 400 series,” http://aragonphotonics.com/bosa-100-400-series-optical-spectrum-analyzer .

D. Gariépy, S. Searcy, G. He, and S. Tibuleac, “Demonstration of non-intrusive in-band OSNR measurement technique for PM-16QAM signals with spectral shaping and subject to fiber nonlinearity,” in Proc. Optical Fiber Comm. Conf. (OFC, 2016), paper Tu3G.5.
[Crossref]

Yokogawa, “OSA AQ6370D” https://www.yokogawa.com/pdf/provide/E/GW/Bulletin/0000028273/0/BUAQ6370SR-20EN.pdf

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Figures (11)

Fig. 1
Fig. 1 OS distortions induced by non-ideal optical link or transmitters. (solid line: the ideal OS, dashed line: the distorted OS).
Fig. 2
Fig. 2 UHR-OS of nine commonly used optical signals without distortions.
Fig. 3
Fig. 3 The Schematic diagram of the OSR process.
Fig. 4
Fig. 4 The Schematic diagram of the setup of the simulation system. SSMF: standard single mode fiber, EDFA: erbium doped fiber amplifier, OBPF: multichannel optical band pass filter, UHR-OSM: UHR-OS measurement.
Fig. 5
Fig. 5 (a) Eigenvalues for a few PCs in descending order, (b) Parameter r as a function of the number of PCs selected.
Fig. 6
Fig. 6 The variations of the classification accuracy of all training samples versus γ and c in the SVMs training process.
Fig. 7
Fig. 7 (a) The RAs for each of the nine types of optical signals (solid line: OSNR varied in the range of 6-30dB, dashed line: OSNR varied in the range of 10-30dB). (b) The contribution of each type of optical signals to the total retrieval errors.
Fig. 8
Fig. 8 UHR-OS of No.5 (a) and No.6 (b) signals with non-ideal modulation. (a) BVD = −0.16 V π , DVSV = 16%, ER = 18dB. (b) BVD = −0.16 V π , DVSV = −16%, ER = 24dB.
Fig. 9
Fig. 9 The UHR-OS of No.6 (blue) and No.7 (red) UHR-OS filtered by 1 (a) and 30 OBPFs (b), respectively, OSNR is set at 24dB.
Fig. 10
Fig. 10 (a) The variations of the overall average RA against the number of OBPFs crossed. (b) The RA against the different drift ranges of the OBPFs when the number of OBPFs is 17 and 30, respectively. For the 8 types of signals case No.7 signal is not included.
Fig. 11
Fig. 11 The influence of laser linewidth (a) and wavelength drift (b) on the RA when the number of OBPFs is 17 and 30, respectively. For the 8 types of signals case No.7 signal is not included.

Tables (3)

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Table 1 Nine of the commonly used optical signals and their SVM classification labels

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Table 2 The variation ranges of distortions

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Table 3 The OSR results using PCA and SVM. The average OSR accuracy is 96.97%.

Equations (2)

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Y n,k = X n,p × W p,k ,
r= i=1 k λ i / i=1 p λ i >thr,

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