QoT Estimation for Large-scale Mixed-rate Disaggregated Metro DCI Networks by Artificial Neural Networks

被引：0
|
作者：
He, Yan [1 ]
Chandramouli, Kausthubh [1 ]
Zhai, Zhiqun [2 ]
Chen, Sai [2 ]
Dou, Liang [3 ]
Xie, Chongjin [4 ]
Lu, Chao [1 ]
Lau, Alan Pak Tao [1 ]
机构：
[1] Hong Kong Polytech Univ, Photon Res Inst, Dept Elect & Elect Engn, Hong Kong, Peoples R China
[2] Alibaba Cloud, Alibaba Grp, Hangzhou, Peoples R China
[3] Alibaba Cloud, Alibaba Grp, Beijing, Peoples R China
[4] Alibaba Cloud, Alibaba Grp, New York, NY 10014 USA
来源：
2024 OPTICAL FIBER COMMUNICATIONS CONFERENCE AND EXHIBITION, OFC | 2024年
关键词：
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
We proposed an artificial neural network (ANN)-based QoT estimator for large-scale mixed-rate disaggregated metro DCI networks with an estimation error standard deviation of 0.3 dB, outperforming analytical-based methods with vendor-specific transponder SNR characterization. (c) 2024 The Author(s)
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页数：3
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