Estimation of Spectral Spacing in Gridless NyquistWDM systems using Fuzzy Clustering and Deep Learning

被引：0

作者：

Montoya Ocampo, C. A. ^{[1
]}

Granada Torres, J. J. ^{[1
]}

机构：

[1] Univ Antioquia, Fac Ingn, GITA Lab, Calle 67 53-108, Medellin, Colombia

来源：

2023 IEEE PHOTONICS CONFERENCE, IPC | 2023年

关键词：

Deep Learning; Interchannel Interference; Nyquist-WDM;

D O I：

10.1109/IPC57732.2023.10360663

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 model a deep neural network to estimate the level of spectral spacing in optical gridless networks. This method is experimentally validated in a 3x32-Gbaud 16-QAM Nyquist-WDM system in transmission up to 270km. Errors lower than 1GHz and accuracies up to 92% were obtained.

引用

页数：2

共 6 条

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