Abstract

We propose and experimentally demonstrate a multiple input multiple output - artificial neural network (MIMO-ANN) nonlinear equalizer (NLE) to process the complex quadrature amplitude modulation (QAM) signal in a single-sideband (SSB) self-coherent detection (SCD) system. In the proposed scheme, a 2-by-2 MIMO structure with two ANNs is employed to effectively mitigate the signal distortions induced by in-phase and quadrature (IQ) imbalance and fiber nonlinear effects. By using the proposed MIMO-ANN NLE, we successfully transmit a 112-Gb/s SSB 16-QAM signal over a single-span 120-km single mode fiber (SMF) in a direct detection (DD) system with a bit error rate (BER) lower than 3.8 × 10−3. We also conduct a comparative study between the proposed MIMO-ANN NLE, a feedforward equalizer (FFE), a NLE consisting of two independent real-valued Volterra filters, and a MIMO-Volterra filter. The proposed MIMO-ANN NLE outperforms other equalizers with the longer fiber length and thus stronger nonlinearities, since it can easily approximate a complicated nonlinear function. To the best of our knowledge, this is the first experimental demonstration of an ANN-based equalizer in an SSB SCD system.

© 2019 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

Full Article  |  PDF Article
OSA Recommended Articles
Nonlinear equalization based on pruned artificial neural networks for 112-Gb/s SSB-PAM4 transmission over 80-km SSMF

Zhiquan Wan, Jianqiang Li, Liang Shu, Ming Luo, Xiang Li, Songnian Fu, and Kun Xu
Opt. Express 26(8) 10631-10642 (2018)

Single-photodiode 112-Gbit/s 16-QAM transmission over 960-km SSMF enabled by Kramers-Kronig detection and sparse I/Q Volterra filter

Liang Shu, Jianqiang Li, Zhiquan Wan, Zhenming Yu, Xiang Li, Ming Luo, Songnian Fu, and Kun Xu
Opt. Express 26(19) 24564-24576 (2018)

C-band 56-Gb/s PAM4 transmission over 80-km SSMF with electrical equalization at receiver

Xizi Tang, Shuangyue Liu, Zhongliang Sun, Han Cui, Xuekai Xu, Jia Qi, Mengqi Guo, Yueming Lu, and Yaojun Qiao
Opt. Express 27(18) 25708-25717 (2019)

References

  • View by:
  • |
  • |
  • |

  1. Cisco, “Cisco Global Cloud Index: Forecast and Methodology, 2016–2021 White Paper”, 2018, https://www.cisco.com/c/en/us/solutions/collateral/service-provider/global-cloud-index-gci/white-paper-c11-738085.pdf
  2. E. Giacoumidis, A. Choudhary, E. Magi, D. Marpaung, K. Vu, P. Ma, D.-Y. Choi, S. Madden, B. Corcoran, M. Pelusi, and B. J. Eggleton, “Chip-based Brillouin processing for carrier recovery in self-coherent optical communications,” Optica 5(10), 1191–1199 (2018).
    [Crossref]
  3. D. Che and W. Shieh, “Polarization demultiplexing for Stokes vector direct detection,” J. Lightwave Technol. 34(2), 754–760 (2016).
    [Crossref]
  4. X. Chen, C. Antonelli, S. Chandrasekhar, G. Raybon, A. Mecozzi, M. Shtaif, and P. Winzer, “Kramers–Kronig Receivers for 100-km Datacenter Interconnects,” J. Lightwave Technol. 36(1), 79–89 (2018).
    [Crossref]
  5. G. N. Liu, L. Zhang, T. Zuo, and Q. Zhang, “IM/DD transmission techniques for emerging 5G Fronthaul, DCI, and metro applications,” J. Lightwave Technol. 36(2), 560–567 (2018).
    [Crossref]
  6. X. Chen, S. Chandrasekhar, and P. Winzer, “Self-Coherent Systems for Short Reach Transmission,” in European Conference on Optical Communication, (IEEE, 2018), 1–3.
  7. A. Mecozzi, C. Antonelli, and M. Shtaif, “Kramers–Kronig coherent receiver,” Optica 3(11), 1220–1227 (2016).
    [Crossref]
  8. Z. Li, M. S. Erkılınç, K. Shi, E. Sillekens, L. Galdino, B. C. Thomsen, P. Bayvel, and R. I. Killey, “SSBI mitigation and the Kramers–Kronig scheme in single-sideband direct-detection transmission with receiver-based electronic dispersion compensation,” J. Lightwave Technol. 35(10), 1887–1893 (2017).
    [Crossref]
  9. Y. Su, G. Raybon, L. K. Wickham, R.-J. Essiambre, S. Chandrasekhar, S. Radic, L. E. Nelson, L. Gruner-Nielsen, and B. J. Eggleton, “40-Gb/s transmission over 2000 km of nonzero-dispersion fiber using 100-km amplifier spacing,” in Optical Fiber Communications Conference, (Optical Society of America, 2002), ThFF3.
    [Crossref]
  10. L. Shu, J. Li, Z. Wan, Z. Yu, X. Li, M. Luo, S. Fu, and K. Xu, “Single-photodiode 112-Gbit/s 16-QAM transmission over 960-km SSMF enabled by Kramers-Kronig detection and sparse I/Q Volterra filter,” Opt. Express 26(19), 24564–24576 (2018).
    [Crossref] [PubMed]
  11. L. Yi, T. Liao, L. Huang, L. Xue, P. Li, and W. Hu, “Machine learning for 100Gb/s/λ passive optical network,” J. Lightwave Technol. 1, 1 (2018).
    [Crossref]
  12. F. N. Khan, C. Lu, and A. P. T. Lau, “Machine Learning Methods for Optical Communication Systems,” in Advanced Photonics (IPR, NOMA, Sensors, Networks, SPPCom, PS), (Optical Society of America, 2017), SpW2F.3.
  13. O. Sidelnikov, A. Redyuk, and S. Sygletos, “Equalization performance and complexity analysis of dynamic deep neural networks in long haul transmission systems,” Opt. Express 26(25), 32765–32776 (2018).
    [Crossref] [PubMed]
  14. M. A. Jarajreh, E. Giacoumidis, I. Aldaya, S. T. Le, A. Tsokanos, Z. Ghassemlooy, N. J. Doran, S. T. and, and Lee, “Artificial neural network nonlinear equalizer for coherent optical OFDM,” IEEE Photonics Technol. Lett. 27(4), 387–390 (2015).
    [Crossref]
  15. Z. Wan, J. Li, L. Shu, M. Luo, X. Li, S. Fu, and K. Xu, “Nonlinear equalization based on pruned artificial neural networks for 112-Gb/s SSB-PAM4 transmission over 80-km SSMF,” Opt. Express 26(8), 10631–10642 (2018).
    [Crossref] [PubMed]
  16. T. A. Eriksson, H. Bülow, and A. Leven, “Applying neural networks in optical communication systems: possible pitfalls,” IEEE Photonics Technol. Lett. 29(23), 2091–2094 (2017).
    [Crossref]
  17. F. Zhang, D. Wang, R. Ding, and Z. Chen, “Terabit Nyquist PDM-32QAM signal transmission with training sequence based time domain channel estimation,” Opt. Express 22(19), 23415–23426 (2014).
    [Crossref] [PubMed]
  18. J. Shi, J. Zhang, X. Li, N. Chi, G.-K. Chang, and J. Yu, “112 Gb/s/λ CAP Signals Transmission over 480 km in IM-DD System,” in Optical Fiber Communication Conference, (Optical Society of America, 2018), W1J.5.
    [Crossref]
  19. Y. LeCun, Y. Bengio, and G. Hinton, “Deep learning,” Nature 521(7553), 436–444 (2015).
    [Crossref] [PubMed]
  20. A. Krizhevsky, I. Sutskever, and G. E. Hinton, “Imagenet classification with deep convolutional neural networks,” in Advances in neural information processing systems, (NIPS, 2012), 1097–1105.
  21. D. E. Rumelhart, G. E. Hinton, and R. J. Williams, “Learning representations by back-propagating errors,” Nature 323(6088), 533–536 (1986).
    [Crossref]
  22. Z. Yang, F. Gao, S. Fu, X. Li, L. Deng, Z. He, M. Tang, and D. Liu, “Radial basis function neural network enabled C-band 4 × 50 Gb/s PAM-4 transmission over 80 km SSMF,” Opt. Lett. 43(15), 3542–3545 (2018).
    [Crossref] [PubMed]
  23. S. T. Le, K. Schuh, M. Chagnon, F. Buchali, R. Dischler, V. Aref, H. Buelow, and K. M. Engenhardt, “1.72-Tb/s virtual-carrier-assisted direct-detection transmission over 200 km,” J. Lightwave Technol. 36(6), 1347–1353 (2018).
    [Crossref]
  24. X. Tang, Y. Qiao, J. Zhou, M. Guo, J. Qi, S. Liu, X. Xu, and Y. Lu, “Equalization scheme of C-band PAM4 signal for optical amplified 50-Gb/s PON,” Opt. Express 26(25), 33418–33427 (2018).
    [Crossref] [PubMed]
  25. X. Zhou, “an improved feed-forward carrier recovery algorithm for coherent receivers with M-QAM modulation format,” IEEE Photonics Technol. Lett. 22(14), 1051–1053 (2010).
    [Crossref]
  26. Y. Zhu, K. Zou, Z. Chen, and F. Zhang, “224 Gb/s optical carrier-assisted Nyquist 16-QAM half-cycle single-sideband direct detection transmission over 160 km SSMF,” J. Lightwave Technol. 35(9), 1557–1565 (2017).
    [Crossref]

2018 (10)

E. Giacoumidis, A. Choudhary, E. Magi, D. Marpaung, K. Vu, P. Ma, D.-Y. Choi, S. Madden, B. Corcoran, M. Pelusi, and B. J. Eggleton, “Chip-based Brillouin processing for carrier recovery in self-coherent optical communications,” Optica 5(10), 1191–1199 (2018).
[Crossref]

X. Chen, C. Antonelli, S. Chandrasekhar, G. Raybon, A. Mecozzi, M. Shtaif, and P. Winzer, “Kramers–Kronig Receivers for 100-km Datacenter Interconnects,” J. Lightwave Technol. 36(1), 79–89 (2018).
[Crossref]

G. N. Liu, L. Zhang, T. Zuo, and Q. Zhang, “IM/DD transmission techniques for emerging 5G Fronthaul, DCI, and metro applications,” J. Lightwave Technol. 36(2), 560–567 (2018).
[Crossref]

L. Shu, J. Li, Z. Wan, Z. Yu, X. Li, M. Luo, S. Fu, and K. Xu, “Single-photodiode 112-Gbit/s 16-QAM transmission over 960-km SSMF enabled by Kramers-Kronig detection and sparse I/Q Volterra filter,” Opt. Express 26(19), 24564–24576 (2018).
[Crossref] [PubMed]

L. Yi, T. Liao, L. Huang, L. Xue, P. Li, and W. Hu, “Machine learning for 100Gb/s/λ passive optical network,” J. Lightwave Technol. 1, 1 (2018).
[Crossref]

O. Sidelnikov, A. Redyuk, and S. Sygletos, “Equalization performance and complexity analysis of dynamic deep neural networks in long haul transmission systems,” Opt. Express 26(25), 32765–32776 (2018).
[Crossref] [PubMed]

Z. Wan, J. Li, L. Shu, M. Luo, X. Li, S. Fu, and K. Xu, “Nonlinear equalization based on pruned artificial neural networks for 112-Gb/s SSB-PAM4 transmission over 80-km SSMF,” Opt. Express 26(8), 10631–10642 (2018).
[Crossref] [PubMed]

Z. Yang, F. Gao, S. Fu, X. Li, L. Deng, Z. He, M. Tang, and D. Liu, “Radial basis function neural network enabled C-band 4 × 50 Gb/s PAM-4 transmission over 80 km SSMF,” Opt. Lett. 43(15), 3542–3545 (2018).
[Crossref] [PubMed]

S. T. Le, K. Schuh, M. Chagnon, F. Buchali, R. Dischler, V. Aref, H. Buelow, and K. M. Engenhardt, “1.72-Tb/s virtual-carrier-assisted direct-detection transmission over 200 km,” J. Lightwave Technol. 36(6), 1347–1353 (2018).
[Crossref]

X. Tang, Y. Qiao, J. Zhou, M. Guo, J. Qi, S. Liu, X. Xu, and Y. Lu, “Equalization scheme of C-band PAM4 signal for optical amplified 50-Gb/s PON,” Opt. Express 26(25), 33418–33427 (2018).
[Crossref] [PubMed]

2017 (3)

2016 (2)

2015 (2)

M. A. Jarajreh, E. Giacoumidis, I. Aldaya, S. T. Le, A. Tsokanos, Z. Ghassemlooy, N. J. Doran, S. T. and, and Lee, “Artificial neural network nonlinear equalizer for coherent optical OFDM,” IEEE Photonics Technol. Lett. 27(4), 387–390 (2015).
[Crossref]

Y. LeCun, Y. Bengio, and G. Hinton, “Deep learning,” Nature 521(7553), 436–444 (2015).
[Crossref] [PubMed]

2014 (1)

2010 (1)

X. Zhou, “an improved feed-forward carrier recovery algorithm for coherent receivers with M-QAM modulation format,” IEEE Photonics Technol. Lett. 22(14), 1051–1053 (2010).
[Crossref]

1986 (1)

D. E. Rumelhart, G. E. Hinton, and R. J. Williams, “Learning representations by back-propagating errors,” Nature 323(6088), 533–536 (1986).
[Crossref]

Aldaya, I.

M. A. Jarajreh, E. Giacoumidis, I. Aldaya, S. T. Le, A. Tsokanos, Z. Ghassemlooy, N. J. Doran, S. T. and, and Lee, “Artificial neural network nonlinear equalizer for coherent optical OFDM,” IEEE Photonics Technol. Lett. 27(4), 387–390 (2015).
[Crossref]

and, S. T.

M. A. Jarajreh, E. Giacoumidis, I. Aldaya, S. T. Le, A. Tsokanos, Z. Ghassemlooy, N. J. Doran, S. T. and, and Lee, “Artificial neural network nonlinear equalizer for coherent optical OFDM,” IEEE Photonics Technol. Lett. 27(4), 387–390 (2015).
[Crossref]

Antonelli, C.

Aref, V.

Bayvel, P.

Bengio, Y.

Y. LeCun, Y. Bengio, and G. Hinton, “Deep learning,” Nature 521(7553), 436–444 (2015).
[Crossref] [PubMed]

Buchali, F.

Buelow, H.

Bülow, H.

T. A. Eriksson, H. Bülow, and A. Leven, “Applying neural networks in optical communication systems: possible pitfalls,” IEEE Photonics Technol. Lett. 29(23), 2091–2094 (2017).
[Crossref]

Chagnon, M.

Chandrasekhar, S.

X. Chen, C. Antonelli, S. Chandrasekhar, G. Raybon, A. Mecozzi, M. Shtaif, and P. Winzer, “Kramers–Kronig Receivers for 100-km Datacenter Interconnects,” J. Lightwave Technol. 36(1), 79–89 (2018).
[Crossref]

Y. Su, G. Raybon, L. K. Wickham, R.-J. Essiambre, S. Chandrasekhar, S. Radic, L. E. Nelson, L. Gruner-Nielsen, and B. J. Eggleton, “40-Gb/s transmission over 2000 km of nonzero-dispersion fiber using 100-km amplifier spacing,” in Optical Fiber Communications Conference, (Optical Society of America, 2002), ThFF3.
[Crossref]

X. Chen, S. Chandrasekhar, and P. Winzer, “Self-Coherent Systems for Short Reach Transmission,” in European Conference on Optical Communication, (IEEE, 2018), 1–3.

Chang, G.-K.

J. Shi, J. Zhang, X. Li, N. Chi, G.-K. Chang, and J. Yu, “112 Gb/s/λ CAP Signals Transmission over 480 km in IM-DD System,” in Optical Fiber Communication Conference, (Optical Society of America, 2018), W1J.5.
[Crossref]

Che, D.

Chen, X.

X. Chen, C. Antonelli, S. Chandrasekhar, G. Raybon, A. Mecozzi, M. Shtaif, and P. Winzer, “Kramers–Kronig Receivers for 100-km Datacenter Interconnects,” J. Lightwave Technol. 36(1), 79–89 (2018).
[Crossref]

X. Chen, S. Chandrasekhar, and P. Winzer, “Self-Coherent Systems for Short Reach Transmission,” in European Conference on Optical Communication, (IEEE, 2018), 1–3.

Chen, Z.

Chi, N.

J. Shi, J. Zhang, X. Li, N. Chi, G.-K. Chang, and J. Yu, “112 Gb/s/λ CAP Signals Transmission over 480 km in IM-DD System,” in Optical Fiber Communication Conference, (Optical Society of America, 2018), W1J.5.
[Crossref]

Choi, D.-Y.

Choudhary, A.

Corcoran, B.

Deng, L.

Ding, R.

Dischler, R.

Doran, N. J.

M. A. Jarajreh, E. Giacoumidis, I. Aldaya, S. T. Le, A. Tsokanos, Z. Ghassemlooy, N. J. Doran, S. T. and, and Lee, “Artificial neural network nonlinear equalizer for coherent optical OFDM,” IEEE Photonics Technol. Lett. 27(4), 387–390 (2015).
[Crossref]

Eggleton, B. J.

E. Giacoumidis, A. Choudhary, E. Magi, D. Marpaung, K. Vu, P. Ma, D.-Y. Choi, S. Madden, B. Corcoran, M. Pelusi, and B. J. Eggleton, “Chip-based Brillouin processing for carrier recovery in self-coherent optical communications,” Optica 5(10), 1191–1199 (2018).
[Crossref]

Y. Su, G. Raybon, L. K. Wickham, R.-J. Essiambre, S. Chandrasekhar, S. Radic, L. E. Nelson, L. Gruner-Nielsen, and B. J. Eggleton, “40-Gb/s transmission over 2000 km of nonzero-dispersion fiber using 100-km amplifier spacing,” in Optical Fiber Communications Conference, (Optical Society of America, 2002), ThFF3.
[Crossref]

Engenhardt, K. M.

Eriksson, T. A.

T. A. Eriksson, H. Bülow, and A. Leven, “Applying neural networks in optical communication systems: possible pitfalls,” IEEE Photonics Technol. Lett. 29(23), 2091–2094 (2017).
[Crossref]

Erkilinç, M. S.

Essiambre, R.-J.

Y. Su, G. Raybon, L. K. Wickham, R.-J. Essiambre, S. Chandrasekhar, S. Radic, L. E. Nelson, L. Gruner-Nielsen, and B. J. Eggleton, “40-Gb/s transmission over 2000 km of nonzero-dispersion fiber using 100-km amplifier spacing,” in Optical Fiber Communications Conference, (Optical Society of America, 2002), ThFF3.
[Crossref]

Fu, S.

Galdino, L.

Gao, F.

Ghassemlooy, Z.

M. A. Jarajreh, E. Giacoumidis, I. Aldaya, S. T. Le, A. Tsokanos, Z. Ghassemlooy, N. J. Doran, S. T. and, and Lee, “Artificial neural network nonlinear equalizer for coherent optical OFDM,” IEEE Photonics Technol. Lett. 27(4), 387–390 (2015).
[Crossref]

Giacoumidis, E.

E. Giacoumidis, A. Choudhary, E. Magi, D. Marpaung, K. Vu, P. Ma, D.-Y. Choi, S. Madden, B. Corcoran, M. Pelusi, and B. J. Eggleton, “Chip-based Brillouin processing for carrier recovery in self-coherent optical communications,” Optica 5(10), 1191–1199 (2018).
[Crossref]

M. A. Jarajreh, E. Giacoumidis, I. Aldaya, S. T. Le, A. Tsokanos, Z. Ghassemlooy, N. J. Doran, S. T. and, and Lee, “Artificial neural network nonlinear equalizer for coherent optical OFDM,” IEEE Photonics Technol. Lett. 27(4), 387–390 (2015).
[Crossref]

Gruner-Nielsen, L.

Y. Su, G. Raybon, L. K. Wickham, R.-J. Essiambre, S. Chandrasekhar, S. Radic, L. E. Nelson, L. Gruner-Nielsen, and B. J. Eggleton, “40-Gb/s transmission over 2000 km of nonzero-dispersion fiber using 100-km amplifier spacing,” in Optical Fiber Communications Conference, (Optical Society of America, 2002), ThFF3.
[Crossref]

Guo, M.

He, Z.

Hinton, G.

Y. LeCun, Y. Bengio, and G. Hinton, “Deep learning,” Nature 521(7553), 436–444 (2015).
[Crossref] [PubMed]

Hinton, G. E.

D. E. Rumelhart, G. E. Hinton, and R. J. Williams, “Learning representations by back-propagating errors,” Nature 323(6088), 533–536 (1986).
[Crossref]

Hu, W.

L. Yi, T. Liao, L. Huang, L. Xue, P. Li, and W. Hu, “Machine learning for 100Gb/s/λ passive optical network,” J. Lightwave Technol. 1, 1 (2018).
[Crossref]

Huang, L.

L. Yi, T. Liao, L. Huang, L. Xue, P. Li, and W. Hu, “Machine learning for 100Gb/s/λ passive optical network,” J. Lightwave Technol. 1, 1 (2018).
[Crossref]

Jarajreh, M. A.

M. A. Jarajreh, E. Giacoumidis, I. Aldaya, S. T. Le, A. Tsokanos, Z. Ghassemlooy, N. J. Doran, S. T. and, and Lee, “Artificial neural network nonlinear equalizer for coherent optical OFDM,” IEEE Photonics Technol. Lett. 27(4), 387–390 (2015).
[Crossref]

Killey, R. I.

Le, S. T.

S. T. Le, K. Schuh, M. Chagnon, F. Buchali, R. Dischler, V. Aref, H. Buelow, and K. M. Engenhardt, “1.72-Tb/s virtual-carrier-assisted direct-detection transmission over 200 km,” J. Lightwave Technol. 36(6), 1347–1353 (2018).
[Crossref]

M. A. Jarajreh, E. Giacoumidis, I. Aldaya, S. T. Le, A. Tsokanos, Z. Ghassemlooy, N. J. Doran, S. T. and, and Lee, “Artificial neural network nonlinear equalizer for coherent optical OFDM,” IEEE Photonics Technol. Lett. 27(4), 387–390 (2015).
[Crossref]

LeCun, Y.

Y. LeCun, Y. Bengio, and G. Hinton, “Deep learning,” Nature 521(7553), 436–444 (2015).
[Crossref] [PubMed]

Lee,

M. A. Jarajreh, E. Giacoumidis, I. Aldaya, S. T. Le, A. Tsokanos, Z. Ghassemlooy, N. J. Doran, S. T. and, and Lee, “Artificial neural network nonlinear equalizer for coherent optical OFDM,” IEEE Photonics Technol. Lett. 27(4), 387–390 (2015).
[Crossref]

Leven, A.

T. A. Eriksson, H. Bülow, and A. Leven, “Applying neural networks in optical communication systems: possible pitfalls,” IEEE Photonics Technol. Lett. 29(23), 2091–2094 (2017).
[Crossref]

Li, J.

Li, P.

L. Yi, T. Liao, L. Huang, L. Xue, P. Li, and W. Hu, “Machine learning for 100Gb/s/λ passive optical network,” J. Lightwave Technol. 1, 1 (2018).
[Crossref]

Li, X.

Li, Z.

Liao, T.

L. Yi, T. Liao, L. Huang, L. Xue, P. Li, and W. Hu, “Machine learning for 100Gb/s/λ passive optical network,” J. Lightwave Technol. 1, 1 (2018).
[Crossref]

Liu, D.

Liu, G. N.

Liu, S.

Lu, Y.

Luo, M.

Ma, P.

Madden, S.

Magi, E.

Marpaung, D.

Mecozzi, A.

Nelson, L. E.

Y. Su, G. Raybon, L. K. Wickham, R.-J. Essiambre, S. Chandrasekhar, S. Radic, L. E. Nelson, L. Gruner-Nielsen, and B. J. Eggleton, “40-Gb/s transmission over 2000 km of nonzero-dispersion fiber using 100-km amplifier spacing,” in Optical Fiber Communications Conference, (Optical Society of America, 2002), ThFF3.
[Crossref]

Pelusi, M.

Qi, J.

Qiao, Y.

Radic, S.

Y. Su, G. Raybon, L. K. Wickham, R.-J. Essiambre, S. Chandrasekhar, S. Radic, L. E. Nelson, L. Gruner-Nielsen, and B. J. Eggleton, “40-Gb/s transmission over 2000 km of nonzero-dispersion fiber using 100-km amplifier spacing,” in Optical Fiber Communications Conference, (Optical Society of America, 2002), ThFF3.
[Crossref]

Raybon, G.

X. Chen, C. Antonelli, S. Chandrasekhar, G. Raybon, A. Mecozzi, M. Shtaif, and P. Winzer, “Kramers–Kronig Receivers for 100-km Datacenter Interconnects,” J. Lightwave Technol. 36(1), 79–89 (2018).
[Crossref]

Y. Su, G. Raybon, L. K. Wickham, R.-J. Essiambre, S. Chandrasekhar, S. Radic, L. E. Nelson, L. Gruner-Nielsen, and B. J. Eggleton, “40-Gb/s transmission over 2000 km of nonzero-dispersion fiber using 100-km amplifier spacing,” in Optical Fiber Communications Conference, (Optical Society of America, 2002), ThFF3.
[Crossref]

Redyuk, A.

Rumelhart, D. E.

D. E. Rumelhart, G. E. Hinton, and R. J. Williams, “Learning representations by back-propagating errors,” Nature 323(6088), 533–536 (1986).
[Crossref]

Schuh, K.

Shi, J.

J. Shi, J. Zhang, X. Li, N. Chi, G.-K. Chang, and J. Yu, “112 Gb/s/λ CAP Signals Transmission over 480 km in IM-DD System,” in Optical Fiber Communication Conference, (Optical Society of America, 2018), W1J.5.
[Crossref]

Shi, K.

Shieh, W.

Shtaif, M.

Shu, L.

Sidelnikov, O.

Sillekens, E.

Su, Y.

Y. Su, G. Raybon, L. K. Wickham, R.-J. Essiambre, S. Chandrasekhar, S. Radic, L. E. Nelson, L. Gruner-Nielsen, and B. J. Eggleton, “40-Gb/s transmission over 2000 km of nonzero-dispersion fiber using 100-km amplifier spacing,” in Optical Fiber Communications Conference, (Optical Society of America, 2002), ThFF3.
[Crossref]

Sygletos, S.

Tang, M.

Tang, X.

Thomsen, B. C.

Tsokanos, A.

M. A. Jarajreh, E. Giacoumidis, I. Aldaya, S. T. Le, A. Tsokanos, Z. Ghassemlooy, N. J. Doran, S. T. and, and Lee, “Artificial neural network nonlinear equalizer for coherent optical OFDM,” IEEE Photonics Technol. Lett. 27(4), 387–390 (2015).
[Crossref]

Vu, K.

Wan, Z.

Wang, D.

Wickham, L. K.

Y. Su, G. Raybon, L. K. Wickham, R.-J. Essiambre, S. Chandrasekhar, S. Radic, L. E. Nelson, L. Gruner-Nielsen, and B. J. Eggleton, “40-Gb/s transmission over 2000 km of nonzero-dispersion fiber using 100-km amplifier spacing,” in Optical Fiber Communications Conference, (Optical Society of America, 2002), ThFF3.
[Crossref]

Williams, R. J.

D. E. Rumelhart, G. E. Hinton, and R. J. Williams, “Learning representations by back-propagating errors,” Nature 323(6088), 533–536 (1986).
[Crossref]

Winzer, P.

X. Chen, C. Antonelli, S. Chandrasekhar, G. Raybon, A. Mecozzi, M. Shtaif, and P. Winzer, “Kramers–Kronig Receivers for 100-km Datacenter Interconnects,” J. Lightwave Technol. 36(1), 79–89 (2018).
[Crossref]

X. Chen, S. Chandrasekhar, and P. Winzer, “Self-Coherent Systems for Short Reach Transmission,” in European Conference on Optical Communication, (IEEE, 2018), 1–3.

Xu, K.

Xu, X.

Xue, L.

L. Yi, T. Liao, L. Huang, L. Xue, P. Li, and W. Hu, “Machine learning for 100Gb/s/λ passive optical network,” J. Lightwave Technol. 1, 1 (2018).
[Crossref]

Yang, Z.

Yi, L.

L. Yi, T. Liao, L. Huang, L. Xue, P. Li, and W. Hu, “Machine learning for 100Gb/s/λ passive optical network,” J. Lightwave Technol. 1, 1 (2018).
[Crossref]

Yu, J.

J. Shi, J. Zhang, X. Li, N. Chi, G.-K. Chang, and J. Yu, “112 Gb/s/λ CAP Signals Transmission over 480 km in IM-DD System,” in Optical Fiber Communication Conference, (Optical Society of America, 2018), W1J.5.
[Crossref]

Yu, Z.

Zhang, F.

Zhang, J.

J. Shi, J. Zhang, X. Li, N. Chi, G.-K. Chang, and J. Yu, “112 Gb/s/λ CAP Signals Transmission over 480 km in IM-DD System,” in Optical Fiber Communication Conference, (Optical Society of America, 2018), W1J.5.
[Crossref]

Zhang, L.

Zhang, Q.

Zhou, J.

Zhou, X.

X. Zhou, “an improved feed-forward carrier recovery algorithm for coherent receivers with M-QAM modulation format,” IEEE Photonics Technol. Lett. 22(14), 1051–1053 (2010).
[Crossref]

Zhu, Y.

Zou, K.

Zuo, T.

IEEE Photonics Technol. Lett. (3)

M. A. Jarajreh, E. Giacoumidis, I. Aldaya, S. T. Le, A. Tsokanos, Z. Ghassemlooy, N. J. Doran, S. T. and, and Lee, “Artificial neural network nonlinear equalizer for coherent optical OFDM,” IEEE Photonics Technol. Lett. 27(4), 387–390 (2015).
[Crossref]

T. A. Eriksson, H. Bülow, and A. Leven, “Applying neural networks in optical communication systems: possible pitfalls,” IEEE Photonics Technol. Lett. 29(23), 2091–2094 (2017).
[Crossref]

X. Zhou, “an improved feed-forward carrier recovery algorithm for coherent receivers with M-QAM modulation format,” IEEE Photonics Technol. Lett. 22(14), 1051–1053 (2010).
[Crossref]

J. Lightwave Technol. (7)

Y. Zhu, K. Zou, Z. Chen, and F. Zhang, “224 Gb/s optical carrier-assisted Nyquist 16-QAM half-cycle single-sideband direct detection transmission over 160 km SSMF,” J. Lightwave Technol. 35(9), 1557–1565 (2017).
[Crossref]

S. T. Le, K. Schuh, M. Chagnon, F. Buchali, R. Dischler, V. Aref, H. Buelow, and K. M. Engenhardt, “1.72-Tb/s virtual-carrier-assisted direct-detection transmission over 200 km,” J. Lightwave Technol. 36(6), 1347–1353 (2018).
[Crossref]

L. Yi, T. Liao, L. Huang, L. Xue, P. Li, and W. Hu, “Machine learning for 100Gb/s/λ passive optical network,” J. Lightwave Technol. 1, 1 (2018).
[Crossref]

D. Che and W. Shieh, “Polarization demultiplexing for Stokes vector direct detection,” J. Lightwave Technol. 34(2), 754–760 (2016).
[Crossref]

X. Chen, C. Antonelli, S. Chandrasekhar, G. Raybon, A. Mecozzi, M. Shtaif, and P. Winzer, “Kramers–Kronig Receivers for 100-km Datacenter Interconnects,” J. Lightwave Technol. 36(1), 79–89 (2018).
[Crossref]

G. N. Liu, L. Zhang, T. Zuo, and Q. Zhang, “IM/DD transmission techniques for emerging 5G Fronthaul, DCI, and metro applications,” J. Lightwave Technol. 36(2), 560–567 (2018).
[Crossref]

Z. Li, M. S. Erkılınç, K. Shi, E. Sillekens, L. Galdino, B. C. Thomsen, P. Bayvel, and R. I. Killey, “SSBI mitigation and the Kramers–Kronig scheme in single-sideband direct-detection transmission with receiver-based electronic dispersion compensation,” J. Lightwave Technol. 35(10), 1887–1893 (2017).
[Crossref]

Nature (2)

Y. LeCun, Y. Bengio, and G. Hinton, “Deep learning,” Nature 521(7553), 436–444 (2015).
[Crossref] [PubMed]

D. E. Rumelhart, G. E. Hinton, and R. J. Williams, “Learning representations by back-propagating errors,” Nature 323(6088), 533–536 (1986).
[Crossref]

Opt. Express (5)

Opt. Lett. (1)

Optica (2)

Other (6)

Cisco, “Cisco Global Cloud Index: Forecast and Methodology, 2016–2021 White Paper”, 2018, https://www.cisco.com/c/en/us/solutions/collateral/service-provider/global-cloud-index-gci/white-paper-c11-738085.pdf

Y. Su, G. Raybon, L. K. Wickham, R.-J. Essiambre, S. Chandrasekhar, S. Radic, L. E. Nelson, L. Gruner-Nielsen, and B. J. Eggleton, “40-Gb/s transmission over 2000 km of nonzero-dispersion fiber using 100-km amplifier spacing,” in Optical Fiber Communications Conference, (Optical Society of America, 2002), ThFF3.
[Crossref]

X. Chen, S. Chandrasekhar, and P. Winzer, “Self-Coherent Systems for Short Reach Transmission,” in European Conference on Optical Communication, (IEEE, 2018), 1–3.

F. N. Khan, C. Lu, and A. P. T. Lau, “Machine Learning Methods for Optical Communication Systems,” in Advanced Photonics (IPR, NOMA, Sensors, Networks, SPPCom, PS), (Optical Society of America, 2017), SpW2F.3.

J. Shi, J. Zhang, X. Li, N. Chi, G.-K. Chang, and J. Yu, “112 Gb/s/λ CAP Signals Transmission over 480 km in IM-DD System,” in Optical Fiber Communication Conference, (Optical Society of America, 2018), W1J.5.
[Crossref]

A. Krizhevsky, I. Sutskever, and G. E. Hinton, “Imagenet classification with deep convolutional neural networks,” in Advances in neural information processing systems, (NIPS, 2012), 1097–1105.

Cited By

OSA participates in Crossref's Cited-By Linking service. Citing articles from OSA journals and other participating publishers are listed here.

Alert me when this article is cited.


Figures (9)

Fig. 1
Fig. 1 (a) Block diagram of the proposed MIMO-ANN NLE. (b) Block diagram of each ANN in the proposed MIMO-ANN NLE.
Fig. 2
Fig. 2 Experimental setup.
Fig. 3
Fig. 3 (a) DSP flow charts. (b) Block diagram of the NLE with 2 real VFs. (c) Block diagram of the MIMO-VF. NE: construction of nonlinear items.
Fig. 4
Fig. 4 Optical spectra measured after different transmission distances.
Fig. 5
Fig. 5 (a) BER versus delay length in the input layer. (b) BER versus neuron number in the hidden layer.
Fig. 6
Fig. 6 BER versus bias voltage of the phase shifter in the IQM. Insets (i-ii): constellations at the 6.9-V bias of the phase shifter in the IQM for the NLE with 2 real VFs, and the proposed MIMO-ANN NLE, respectively.
Fig. 7
Fig. 7 BERs versus launch powers at different CSPRs after the single-span 120-km (a), and 145-km (b) transmissions, respectively.
Fig. 8
Fig. 8 BERs versus launch powers with different equalizers after the single-span 120-km (a), and 145-km (b) transmissions, respectively.
Fig. 9
Fig. 9 BER versus frame length.

Tables (1)

Tables Icon

Table 1 Computational complexity comparisons

Equations (7)

Equations on this page are rendered with MathJax. Learn more.

y m =f( k w mk x k ),
ReLU(x)=max(0,x).
J(w)= | d(n)y(n) | 2 ,
Δ w 2 (n)=μ J( w 2 ) w 2 (n) =2μ( d(n)y(n) ) y 1 T (n),
w 2 (n+1)= w 2 (n)+Δ w 2 (n),
Δ w 1 (n)=[ ( v 1 (n)>0) w 2 T (n)( d(n)y(n) ) ] x T (n),
w 1 (n+1)= w 1 (n)+Δ w 1 (n),

Metrics