KNN, k-Means and Fuzzy c-Means for 16-QAM Demodulation in Coherent Optical Systems

被引：0
|
作者：
Escobar Perez, Alejandro [1 ]
Granada Torres, Jhon J. [1 ]
机构：
[1] Univ Antioquia, GITA Res Grp, Fac Ingn, Cl 67 53 108, Medellin, Colombia
来源：
2019 IEEE COLOMBIAN CONFERENCE ON COMMUNICATIONS AND COMPUTING (COLCOM 2019) | 2019年
关键词：
Machine Learning; 16-QAM; Coherent Optical Systems;
D O I：
10.1109/colcomcon.2019.8809116
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：
In this paper, Machine Learning (ML) techniques such as k-Nearest Neighbors (KNN), k-Means and Fuzzy c-Means (FCM) are implemented in coherent optical system with DSP-based receiver. Nyquist single carrier optical transmission at 32 Gbaud is simulated in VPIDesignSuite Software in co-simulation with Matlab. Simulations results shows gains up to 1 dB and 2 dB using ML techniques at 50 km of optical link with 100 kHz and 25 kHz of laser linewidth, respectively. Besides, it is demonstrated that ML techniques can be effectively used as a nonsymmetrical demodulation (NSD) method.
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页数：4
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