Artificial neural network equalizers for PAM-4 using DML-on-silicon

Nikolaos Panteleimon Diamantopoulos; Takuro Fujii; Hidetaka Nishi; Koji Takeda; Takaaki Kakitsuka; Shinji Matsuo

doi:10.1109/CLEOE-EQEC.2019.8873002

Artificial neural network equalizers for PAM-4 using DML-on-silicon

Nikolaos Panteleimon Diamantopoulos, Takuro Fujii, Hidetaka Nishi, Koji Takeda, Takaaki Kakitsuka, Shinji Matsuo

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Nonlinear equalizers (NLEs) based on artificial neural networks (ANNs) are studied for short-reach 4-level pulse amplitude modulation (PAM-4) transmissions [1,2] utilizing directly-modulated membrane lasers fabricated on silicon substrates (DMLs-on-Si) [3,4]. Using 28-GBaud signals over 2-km of single-mode fiber (SMF), we compare two ANN-NLEs with a previously developed reduced-complexity Volterra-NLE (VNLE) [5].

Original language	English
Title of host publication	2019 Conference on Lasers and Electro-Optics Europe and European Quantum Electronics Conference, CLEO/Europe-EQEC 2019
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781728104690
DOIs	https://doi.org/10.1109/CLEOE-EQEC.2019.8873002
Publication status	Published - 2019 Jun
Externally published	Yes
Event	2019 Conference on Lasers and Electro-Optics Europe and European Quantum Electronics Conference, CLEO/Europe-EQEC 2019 - Munich, Germany Duration: 2019 Jun 23 → 2019 Jun 27

Publication series

Name	2019 Conference on Lasers and Electro-Optics Europe and European Quantum Electronics Conference, CLEO/Europe-EQEC 2019

Conference

Conference	2019 Conference on Lasers and Electro-Optics Europe and European Quantum Electronics Conference, CLEO/Europe-EQEC 2019
Country/Territory	Germany
City	Munich
Period	19/6/23 → 19/6/27

ASJC Scopus subject areas

Spectroscopy
Electronic, Optical and Magnetic Materials
Instrumentation
Atomic and Molecular Physics, and Optics
Computer Networks and Communications

Access to Document

10.1109/CLEOE-EQEC.2019.8873002

Cite this

Diamantopoulos, N. P., Fujii, T., Nishi, H., Takeda, K., Kakitsuka, T., & Matsuo, S. (2019). Artificial neural network equalizers for PAM-4 using DML-on-silicon. In 2019 Conference on Lasers and Electro-Optics Europe and European Quantum Electronics Conference, CLEO/Europe-EQEC 2019 [8873002] (2019 Conference on Lasers and Electro-Optics Europe and European Quantum Electronics Conference, CLEO/Europe-EQEC 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CLEOE-EQEC.2019.8873002

Artificial neural network equalizers for PAM-4 using DML-on-silicon. / Diamantopoulos, Nikolaos Panteleimon; Fujii, Takuro; Nishi, Hidetaka et al.

2019 Conference on Lasers and Electro-Optics Europe and European Quantum Electronics Conference, CLEO/Europe-EQEC 2019. Institute of Electrical and Electronics Engineers Inc., 2019. 8873002 (2019 Conference on Lasers and Electro-Optics Europe and European Quantum Electronics Conference, CLEO/Europe-EQEC 2019).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Diamantopoulos, NP, Fujii, T, Nishi, H, Takeda, K, Kakitsuka, T & Matsuo, S 2019, Artificial neural network equalizers for PAM-4 using DML-on-silicon. in 2019 Conference on Lasers and Electro-Optics Europe and European Quantum Electronics Conference, CLEO/Europe-EQEC 2019., 8873002, 2019 Conference on Lasers and Electro-Optics Europe and European Quantum Electronics Conference, CLEO/Europe-EQEC 2019, Institute of Electrical and Electronics Engineers Inc., 2019 Conference on Lasers and Electro-Optics Europe and European Quantum Electronics Conference, CLEO/Europe-EQEC 2019, Munich, Germany, 19/6/23. https://doi.org/10.1109/CLEOE-EQEC.2019.8873002

Diamantopoulos NP, Fujii T, Nishi H, Takeda K, Kakitsuka T, Matsuo S. Artificial neural network equalizers for PAM-4 using DML-on-silicon. In 2019 Conference on Lasers and Electro-Optics Europe and European Quantum Electronics Conference, CLEO/Europe-EQEC 2019. Institute of Electrical and Electronics Engineers Inc. 2019. 8873002. (2019 Conference on Lasers and Electro-Optics Europe and European Quantum Electronics Conference, CLEO/Europe-EQEC 2019). doi: 10.1109/CLEOE-EQEC.2019.8873002

Diamantopoulos, Nikolaos Panteleimon ; Fujii, Takuro ; Nishi, Hidetaka et al. / Artificial neural network equalizers for PAM-4 using DML-on-silicon. 2019 Conference on Lasers and Electro-Optics Europe and European Quantum Electronics Conference, CLEO/Europe-EQEC 2019. Institute of Electrical and Electronics Engineers Inc., 2019. (2019 Conference on Lasers and Electro-Optics Europe and European Quantum Electronics Conference, CLEO/Europe-EQEC 2019).

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abstract = "Nonlinear equalizers (NLEs) based on artificial neural networks (ANNs) are studied for short-reach 4-level pulse amplitude modulation (PAM-4) transmissions [1,2] utilizing directly-modulated membrane lasers fabricated on silicon substrates (DMLs-on-Si) [3,4]. Using 28-GBaud signals over 2-km of single-mode fiber (SMF), we compare two ANN-NLEs with a previously developed reduced-complexity Volterra-NLE (VNLE) [5].",

author = "Diamantopoulos, {Nikolaos Panteleimon} and Takuro Fujii and Hidetaka Nishi and Koji Takeda and Takaaki Kakitsuka and Shinji Matsuo",

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AU - Diamantopoulos, Nikolaos Panteleimon

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AU - Takeda, Koji

AU - Kakitsuka, Takaaki

AU - Matsuo, Shinji

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N2 - Nonlinear equalizers (NLEs) based on artificial neural networks (ANNs) are studied for short-reach 4-level pulse amplitude modulation (PAM-4) transmissions [1,2] utilizing directly-modulated membrane lasers fabricated on silicon substrates (DMLs-on-Si) [3,4]. Using 28-GBaud signals over 2-km of single-mode fiber (SMF), we compare two ANN-NLEs with a previously developed reduced-complexity Volterra-NLE (VNLE) [5].

AB - Nonlinear equalizers (NLEs) based on artificial neural networks (ANNs) are studied for short-reach 4-level pulse amplitude modulation (PAM-4) transmissions [1,2] utilizing directly-modulated membrane lasers fabricated on silicon substrates (DMLs-on-Si) [3,4]. Using 28-GBaud signals over 2-km of single-mode fiber (SMF), we compare two ANN-NLEs with a previously developed reduced-complexity Volterra-NLE (VNLE) [5].

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BT - 2019 Conference on Lasers and Electro-Optics Europe and European Quantum Electronics Conference, CLEO/Europe-EQEC 2019

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Artificial neural network equalizers for PAM-4 using DML-on-silicon

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