On the Impact of the Optical Phase Conjugation on the Computational Complexity of Neural Network-Based Equalisers

D. Arguello Ron; K. Nurlybayeva; M. Kamalian-Kopae; A. A. Ali; E. Turitsyna; S. Turitsyn

On the Impact of the Optical Phase Conjugation on the Computational Complexity of Neural Network-Based Equalisers

D. Arguello Ron^*
, K. Nurlybayeva
, M. Kamalian-Kopae
, A. A. Ali
, E. Turitsyna
, S. Turitsyn

^*Corresponding author for this work

Research output: Chapter in Book/Published conference output › Conference publication

1 Citation (Scopus)

Abstract

We develop a low complexity complex-valued neural network to compensate the nonlinearity from the transmission of PDM 28 Gbaud 64QAM over 400km of SSMF, by combining midlink optical phase conjugation and pruning.

Original language	English
Title of host publication	2022 European Conference on Optical Communication, ECOC 2022
Publisher	IEEE
Number of pages	4
ISBN (Electronic)	9781957171159
Publication status	Published - 18 Sept 2022
Event	2022 European Conference on Optical Communication, ECOC 2022 - Basel, Switzerland Duration: 18 Sept 2022 → 22 Sept 2022

Publication series

Name	2022 European Conference on Optical Communication, ECOC 2022

Conference

Conference	2022 European Conference on Optical Communication, ECOC 2022
Country/Territory	Switzerland
City	Basel
Period	18/09/22 → 22/09/22

Bibliographical note

Funding Information:
This work has received funding from: EU H2020 MSCA project No. 860360 and EPSRC project TRANSNET.

Funding

This work has received funding from: EU H2020 MSCA project No. 860360 and EPSRC project TRANSNET.

Access to Document

https://opg.optica.org/viewmedia.cfm?uri=ECEOC-2022-We5.29&seq=0

Cite this

Ron, D. A., Nurlybayeva, K., Kamalian-Kopae, M., Ali, A. A., Turitsyna, E., & Turitsyn, S. (2022). On the Impact of the Optical Phase Conjugation on the Computational Complexity of Neural Network-Based Equalisers. In 2022 European Conference on Optical Communication, ECOC 2022 Article We5.29 (2022 European Conference on Optical Communication, ECOC 2022). IEEE. https://opg.optica.org/viewmedia.cfm?uri=ECEOC-2022-We5.29&seq=0

@inproceedings{19402f0299a1424bb253fefc819c9b62,

title = "On the Impact of the Optical Phase Conjugation on the Computational Complexity of Neural Network-Based Equalisers",

abstract = "We develop a low complexity complex-valued neural network to compensate the nonlinearity from the transmission of PDM 28 Gbaud 64QAM over 400km of SSMF, by combining midlink optical phase conjugation and pruning.",

author = "Ron, \{D. Arguello\} and K. Nurlybayeva and M. Kamalian-Kopae and Ali, \{A. A.\} and E. Turitsyna and S. Turitsyn",

note = "Funding Information: This work has received funding from: EU H2020 MSCA project No. 860360 and EPSRC project TRANSNET. ; 2022 European Conference on Optical Communication, ECOC 2022 ; Conference date: 18-09-2022 Through 22-09-2022",

year = "2022",

month = sep,

day = "18",

language = "English",

series = "2022 European Conference on Optical Communication, ECOC 2022",

publisher = "IEEE",

booktitle = "2022 European Conference on Optical Communication, ECOC 2022",

address = "United States",

}

Ron, DA, Nurlybayeva, K, Kamalian-Kopae, M, Ali, AA, Turitsyna, E & Turitsyn, S 2022, On the Impact of the Optical Phase Conjugation on the Computational Complexity of Neural Network-Based Equalisers. in 2022 European Conference on Optical Communication, ECOC 2022., We5.29, 2022 European Conference on Optical Communication, ECOC 2022, IEEE, 2022 European Conference on Optical Communication, ECOC 2022, Basel, Switzerland, 18/09/22. <https://opg.optica.org/viewmedia.cfm?uri=ECEOC-2022-We5.29&seq=0>

On the Impact of the Optical Phase Conjugation on the Computational Complexity of Neural Network-Based Equalisers. / Ron, D. Arguello; Nurlybayeva, K.; Kamalian-Kopae, M. et al.
2022 European Conference on Optical Communication, ECOC 2022. IEEE, 2022. We5.29 (2022 European Conference on Optical Communication, ECOC 2022).

Research output: Chapter in Book/Published conference output › Conference publication

TY - GEN

T1 - On the Impact of the Optical Phase Conjugation on the Computational Complexity of Neural Network-Based Equalisers

AU - Ron, D. Arguello

AU - Nurlybayeva, K.

AU - Kamalian-Kopae, M.

AU - Ali, A. A.

AU - Turitsyna, E.

AU - Turitsyn, S.

N1 - Funding Information: This work has received funding from: EU H2020 MSCA project No. 860360 and EPSRC project TRANSNET.

PY - 2022/9/18

Y1 - 2022/9/18

N2 - We develop a low complexity complex-valued neural network to compensate the nonlinearity from the transmission of PDM 28 Gbaud 64QAM over 400km of SSMF, by combining midlink optical phase conjugation and pruning.

AB - We develop a low complexity complex-valued neural network to compensate the nonlinearity from the transmission of PDM 28 Gbaud 64QAM over 400km of SSMF, by combining midlink optical phase conjugation and pruning.

UR - https://www.scopus.com/pages/publications/85146400506

M3 - Conference publication

AN - SCOPUS:85146400506

T3 - 2022 European Conference on Optical Communication, ECOC 2022

BT - 2022 European Conference on Optical Communication, ECOC 2022

PB - IEEE

T2 - 2022 European Conference on Optical Communication, ECOC 2022

Y2 - 18 September 2022 through 22 September 2022

ER -

On the Impact of the Optical Phase Conjugation on the Computational Complexity of Neural Network-Based Equalisers

Abstract

Publication series

Conference

Bibliographical note

Funding

Access to Document

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