Artificial Neural Network Equalizers for PAM-4 Using DML-on-Silicon

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

2019 Conference on Lasers and Electro-Optics Europe and European Quantum Electronics Conference
OSA Technical Digest (Optica Publishing Group, 2019),
paper ci_3_2

Artificial Neural Network Equalizers for PAM-4 Using DML-on-Silicon

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

The European Conference on Lasers and Electro-Optics 2019

Munich Germany
23–27 June 2019
ISBN: 978-1-7281-0469-0

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Components and systems for metro and short range networks (ci_3)

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N. Diamantopoulos, T. Fujii, H. Nishi, K. Takeda, T. Kakitsuka, and S. Matsuo, "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, OSA Technical Digest (Optica Publishing Group, 2019), paper ci_3_2.

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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].

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