用于200+ Gbps IM/DD系统的多符号输出长短期记忆神经网络均衡器

Bohan Sang, Jiao Zhang, Chen Wang, Miao Kong, Yuxuan Tan, Li Zhao, Wen Zhou, Dongdong Shang, Yamin Zhu, Hong Yi, Jianjun Yu
{"title":"用于200+ Gbps IM/DD系统的多符号输出长短期记忆神经网络均衡器","authors":"Bohan Sang, Jiao Zhang, Chen Wang, Miao Kong, Yuxuan Tan, Li Zhao, Wen Zhou, Dongdong Shang, Yamin Zhu, Hong Yi, Jianjun Yu","doi":"10.1109/ecoc52684.2021.9606010","DOIUrl":null,"url":null,"abstract":"We propose a single-lane 212Gbps IM/DD PAM-4 system with a novel Multi-Symbol Output LSTM equalizer that performs much better than FFE&VNE and single-symbol output LSTM, and reduces complexity by 49.85% at the same time, and achieves similar performance with Bi-directional LSTM with around 1/4 complexity.","PeriodicalId":117375,"journal":{"name":"2021 European Conference on Optical Communication (ECOC)","volume":"129 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Multi-Symbol Output Long Short-Term Memory Neural Network Equalizer For 200+ Gbps IM/DD System\",\"authors\":\"Bohan Sang, Jiao Zhang, Chen Wang, Miao Kong, Yuxuan Tan, Li Zhao, Wen Zhou, Dongdong Shang, Yamin Zhu, Hong Yi, Jianjun Yu\",\"doi\":\"10.1109/ecoc52684.2021.9606010\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We propose a single-lane 212Gbps IM/DD PAM-4 system with a novel Multi-Symbol Output LSTM equalizer that performs much better than FFE&VNE and single-symbol output LSTM, and reduces complexity by 49.85% at the same time, and achieves similar performance with Bi-directional LSTM with around 1/4 complexity.\",\"PeriodicalId\":117375,\"journal\":{\"name\":\"2021 European Conference on Optical Communication (ECOC)\",\"volume\":\"129 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-09-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 European Conference on Optical Communication (ECOC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ecoc52684.2021.9606010\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 European Conference on Optical Communication (ECOC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ecoc52684.2021.9606010","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9

摘要

我们提出了一种单通道212Gbps的IM/DD pam4系统,该系统具有新颖的多符号输出LSTM均衡器,其性能远远优于FFE&VNE和单符号输出LSTM,同时将复杂度降低49.85%,并且与双向LSTM性能相似,复杂度约为1/4。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multi-Symbol Output Long Short-Term Memory Neural Network Equalizer For 200+ Gbps IM/DD System
We propose a single-lane 212Gbps IM/DD PAM-4 system with a novel Multi-Symbol Output LSTM equalizer that performs much better than FFE&VNE and single-symbol output LSTM, and reduces complexity by 49.85% at the same time, and achieves similar performance with Bi-directional LSTM with around 1/4 complexity.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信