Dynamic Neural Network Enabled 50 Gb/s PAM-4 IM/DD Transmissions Based on 10G-Class Optical Devices

被引：0

作者：

Zhang, Qianwu ^{[1
]}

Zhou, Hai ^{[1
]}

Liu, Min ^{[1
]}

Xu, Tingting ^{[1
]}

Jiang, Yuntong ^{[1
]}

Jian, Aoqun ^{[2
,3
]}

Song, Yingxiong ^{[1
]}

Li, Yingchun ^{[1
]}

Zhang, Junjie ^{[1
]}

Chen, Jian ^{[1
]}

Cao, Bingyao ^{[1
]}

机构：

[1] Shanghai Univ, Shanghai Inst Adv Commun & Data Sci, Key Lab Specialty Fiber Opt & Opt Access Networks, Shanghai 200072, Peoples R China

[2] Taiyuan Univ Technol, MicroNano Syst Res Ctr, Taiyuan 03002, Peoples R China

[3] Shanxi Prov & Minist Educ, Key Lab Adv Transducers & Intelligent Control Sys, Taiyuan 030024, Peoples R China

来源：

2019 18TH INTERNATIONAL CONFERENCE ON OPTICAL COMMUNICATIONS AND NETWORKS (ICOCN) | 2019年

基金：

上海市科技启明星计划;

关键词：

Dynamic neural network; 50 Gb/s PAM-4; 10G-class optical devices;

D O I：

10.1109/icocn.2019.8934670

中图分类号：

TN [电子技术、通信技术];

学科分类号：

0809 ;

摘要：

A dynamic neural network based equalization scheme is experimentally demonstrated for 50 Gb/s PAM-4 signal transmissions based on 10G-class optical devices. More than 2.5 dB power penalty improvement is achieved compare to the MLSE.

引用

页数：3

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