CNN Nonlinear Equalizer with Reducing the Dimensionality of Feature Maps

Shuo Liu; Yongjun Wang; Lu Han; Chao Li; Xingyuan Huang; Qi Zhang; Xiangjun Xin

doi:10.1109/ICOCN59242.2023.10236423

CNN Nonlinear Equalizer with Reducing the Dimensionality of Feature Maps

Shuo Liu^*
, Yongjun Wang^*
, Lu Han
, Chao Li
, Xingyuan Huang
, Qi Zhang
, Xiangjun Xin

^*此作品的通讯作者

Beijing University of Posts and Telecommunications
State Key Laboratory of Information Photonics and Optical Communications
Beijing Key Laboratory of Space-ground Interconnection and Convergence

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

摘要

In this paper, we propose a method of feature map dimensionality reduction as the input of CNN. We validate the complexity advantages of this scheme in a 120Gb/s PDM 64QAM coherent optical communication system.

源语言	英语
主期刊名	2023 21st International Conference on Optical Communications and Networks, ICOCN 2023
出版商	Institute of Electrical and Electronics Engineers Inc.
ISBN（电子版）	9798350343502
DOI	https://doi.org/10.1109/ICOCN59242.2023.10236423
出版状态	已出版 - 2023
已对外发布	是
活动	21st International Conference on Optical Communications and Networks, ICOCN 2023 - Qufu, 中国期限: 31 7月 2023 → 3 8月 2023

丛书

姓名	2023 21st International Conference on Optical Communications and Networks, ICOCN 2023

会议

会议	21st International Conference on Optical Communications and Networks, ICOCN 2023
国家/地区	中国
市	Qufu
时期	31/07/23 → 3/08/23

访问文件

10.1109/ICOCN59242.2023.10236423

其它文件与链接

链接到 Scopus 的出版物

引用此

Liu, S., Wang, Y., Han, L., Li, C., Huang, X., Zhang, Q., & Xin, X. (2023). CNN Nonlinear Equalizer with Reducing the Dimensionality of Feature Maps. 在 2023 21st International Conference on Optical Communications and Networks, ICOCN 2023 (2023 21st International Conference on Optical Communications and Networks, ICOCN 2023). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICOCN59242.2023.10236423

@inproceedings{545fd8fe075b40308d5559fa60a6e91e,

title = "CNN Nonlinear Equalizer with Reducing the Dimensionality of Feature Maps",

abstract = "In this paper, we propose a method of feature map dimensionality reduction as the input of CNN. We validate the complexity advantages of this scheme in a 120Gb/s PDM 64QAM coherent optical communication system.",

keywords = "Non-linear compensation, dimensionality reduction, perturbation theory",

author = "Shuo Liu and Yongjun Wang and Lu Han and Chao Li and Xingyuan Huang and Qi Zhang and Xiangjun Xin",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 21st International Conference on Optical Communications and Networks, ICOCN 2023 ; Conference date: 31-07-2023 Through 03-08-2023",

year = "2023",

doi = "10.1109/ICOCN59242.2023.10236423",

language = "English",

series = "2023 21st International Conference on Optical Communications and Networks, ICOCN 2023",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "2023 21st International Conference on Optical Communications and Networks, ICOCN 2023",

address = "United States",

}

Liu, S, Wang, Y, Han, L, Li, C, Huang, X, Zhang, Q & Xin, X 2023, CNN Nonlinear Equalizer with Reducing the Dimensionality of Feature Maps. 在 2023 21st International Conference on Optical Communications and Networks, ICOCN 2023. 2023 21st International Conference on Optical Communications and Networks, ICOCN 2023, Institute of Electrical and Electronics Engineers Inc., 21st International Conference on Optical Communications and Networks, ICOCN 2023, Qufu, 中国, 31/07/23. https://doi.org/10.1109/ICOCN59242.2023.10236423

CNN Nonlinear Equalizer with Reducing the Dimensionality of Feature Maps. / Liu, Shuo; Wang, Yongjun; Han, Lu 等.
2023 21st International Conference on Optical Communications and Networks, ICOCN 2023. Institute of Electrical and Electronics Engineers Inc., 2023. (2023 21st International Conference on Optical Communications and Networks, ICOCN 2023).

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

TY - GEN

T1 - CNN Nonlinear Equalizer with Reducing the Dimensionality of Feature Maps

AU - Liu, Shuo

AU - Wang, Yongjun

AU - Han, Lu

AU - Li, Chao

AU - Huang, Xingyuan

AU - Zhang, Qi

AU - Xin, Xiangjun

PY - 2023

Y1 - 2023

N2 - In this paper, we propose a method of feature map dimensionality reduction as the input of CNN. We validate the complexity advantages of this scheme in a 120Gb/s PDM 64QAM coherent optical communication system.

AB - In this paper, we propose a method of feature map dimensionality reduction as the input of CNN. We validate the complexity advantages of this scheme in a 120Gb/s PDM 64QAM coherent optical communication system.

KW - Non-linear compensation

KW - dimensionality reduction

KW - perturbation theory

UR - https://www.scopus.com/pages/publications/85173124606

U2 - 10.1109/ICOCN59242.2023.10236423

DO - 10.1109/ICOCN59242.2023.10236423

M3 - Conference contribution

AN - SCOPUS:85173124606

T3 - 2023 21st International Conference on Optical Communications and Networks, ICOCN 2023

BT - 2023 21st International Conference on Optical Communications and Networks, ICOCN 2023

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 21st International Conference on Optical Communications and Networks, ICOCN 2023

Y2 - 31 July 2023 through 3 August 2023

ER -

Liu S, Wang Y, Han L, Li C, Huang X, Zhang Q 等. CNN Nonlinear Equalizer with Reducing the Dimensionality of Feature Maps. 在 2023 21st International Conference on Optical Communications and Networks, ICOCN 2023. Institute of Electrical and Electronics Engineers Inc. 2023. (2023 21st International Conference on Optical Communications and Networks, ICOCN 2023). doi: 10.1109/ICOCN59242.2023.10236423

CNN Nonlinear Equalizer with Reducing the Dimensionality of Feature Maps

摘要

丛书

会议

访问文件

其它文件与链接

学术指纹

引用此