RBF Neural Network Nonlinear Equalizer for 100G 16-QAM Coherent Optical System

被引：0
|
作者：
Ahmad, Syed Tajammul [1 ]
Kumar, Pradeep K. [1 ]
机构：
[1] Indian Inst Technol, Dept Elect Engn, Kanpur, Uttar Pradesh, India
来源：
2018 3RD INTERNATIONAL CONFERENCE ON MICROWAVE AND PHOTONICS (ICMAP) | 2018年
关键词：
Kerr Nonlinearity; 16-QAM; Radial basis function; Neural networks; K-means algorithm;
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 evaluate the performance of radial basis function neural network (RBFNN) based nonlinear equalizer (NLE) for single carrier (SC) 16-QAM system. We provide the comparison of nonlinearity compensation results of RBFNN-NLE and K-means clustering algorithm in SC 16-QAM system over dispersion managed (DML) and unmanaged links (DUL). The simulation results show that nonlinear penalty reduces by nearly 2 dB and 1 dB for DUL and DML cases respectively.
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页数：2
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