Learning Optimal PAM Levels for VCSEL-based Optical Interconnects

被引：0

作者：

Srinivasan, Muralikrishnan ^{[1
]}

Song, Jinxiang ^{[1
]}

Hager, Christian ^{[1
]}

Szczerba, Krzysztof ^{[2
]}

Wymeersch, Henk ^{[1
]}

Schroder, Jochen ^{[3
]}

机构：

[1] Chalmers Univ Technol, Dept Elect Engn, Gothenburg, Sweden

[2] Juniper Networks, Sunnyvale, CA USA

[3] Chalmers Univ Technol, Dept Microtechnol & Nanosci, Gothenburg, Sweden

来源：

2022 EUROPEAN CONFERENCE ON OPTICAL COMMUNICATION (ECOC) | 2022年

基金：

瑞典研究理事会;

关键词：

NEURAL-NETWORK;

D O I：

暂无

中图分类号：

O43 [光学];

学科分类号：

070207 ; 0803 ;

摘要：

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. (C) 2022 The Author(s)

引用

页数：4

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