Full-Text Search:
Home|Journal Papers|About CNKI|User Service|FAQ|Contact Us|中文
《Optical Technique》 2018-05
Add to Favorite Get Latest Update

Estimation and management of fiber dispersion in the data center based on the deep learning

QU Guoqing;YU Shuke;Internet of Things Technology Research Institute,Jiangsu Vocational College of Business;Nantong Greatwisdom Information Technology Co.,Ltd.;  
Fiber dispersion can be estimated by maximum likelihood sequence estimation accurately,but it suffers from the high computational complexity in the condition of high-speed transmission symbol rate,the optical networks of data centers of cloud computing usually work with high-speed transmission symbol rate,in order to reduce the computational cost of estimation of fiber dispersion in data center,an efficient equalizer of the optical communication of data center based on deep learning is designed.The equalizer based on artificial neural network(ANN)consists of two phases,in the first phase,the impulse response datasets of the optical channel are adopted to train ANN and optimize the parameters of ANN model,and the non-linear response model of ANN is constructed;in the second phase,the trained ANN equalizer is used to process the transmitted data of optical channels,and the fiber dispersion is estimated and compensated.Simulation experimental results according to the optical network scenario of data center show that,the equalizer based on the ANN model improves the optical signal to noise ratio,and extend the transmission distance of optical communication.
【Fund】: 江苏省第十四批“六大人才高峰”高层次人才培养资助项目(XYDXX-121);; 南通市崇川区科技创新计划项目(CCY201607)
【CateGory Index】: TN929.1;TP18
Download(CAJ format) Download(PDF format)
CAJViewer7.0 supports all the CNKI file formats; AdobeReader only supports the PDF format.
©2006 Tsinghua Tongfang Knowledge Network Technology Co., Ltd.(Beijing)(TTKN) All rights reserved