Learning Optimal PAM Levels for VCSEL-based Optical Interconnects

Muralikrishnan Srinivasan; Jinxiang Song; Christian Häger; Krzysztof Szczerba; Henk Wymeersch; Jochen Schröder

European Conference on Optical Communication (ECOC) 2022
Technical Digest Series (Optica Publishing Group, 2022),
paper We2C.3

Learning Optimal PAM Levels for VCSEL-based Optical Interconnects

Muralikrishnan Srinivasan, Jinxiang Song, Christian Häger, Krzysztof Szczerba, Henk Wymeersch, and Jochen Schröder

European Conference and Exhibition on Optical Communication 2022

Basel Switzerland
18–22 September 2022
ISBN: 978-1-957171-15-9

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Deep Learning for Optical Fiber Communications (We2C)

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M. Srinivasan, J. Song, C. Häger, K. Szczerba, H. Wymeersch, and J. Schröder, "Learning Optimal PAM Levels for VCSEL-based Optical Interconnects," in European Conference on Optical Communication (ECOC) 2022, J. Leuthold, C. Harder, B. Offrein, and H. Limberger, eds., Technical Digest Series (Optica Publishing Group, 2022), paper We2C.3.

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Abstract

An auto-encoder that optimizes a VCSEL-based fiber-optic system end-to-end and provides a 1.5dB sensitivity gain at higher temperatures is trained, utilizing a neural network that models the response of a VCSEL for a range of operating temperatures.

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