典型文献
Deep learning-based symbol detection algorithm in IMDD-OOFDM system
文献摘要：
In the current research on intensity-modulation and direct-detection optical orthogonal frequency division multiplexing(IMDD-OOFDM)system,effective channel compensation is a key factor to improve system performance.In order to improve the efficiency of channel compensation,a deep learning-based symbol detection algorithm is proposed in this paper for IMDD-OOFDM system.Firstly,a high-speed data streams symbol synchronization algorithm based on a training sequence is used to ensure accurate symbol synchronization.Then the traditional channel estimation and channel compensation are replaced by an echo state network(ESN)to restore the transmitted signal.Finally,we collect the data from the system experiment and calculate the signal-to-noise ratio(SNR).The analysis of the SNR optimized by the ESN proves that the ESN-based symbol detection algorithm is effective in compensating nonlinear distortion.
文献关键词：
中图分类号：
作者姓名：
Zhang Huibin;Li Tianzhu;Liu Haojiang;Li Zhuotong
作者机构：
Key Laboratory of Information Photonics and Optical Communications,Beijing University of Posts and Telecommunications,Beijing 100876,China
文献出处：
引用格式：
[1]Zhang Huibin;Li Tianzhu;Liu Haojiang;Li Zhuotong-.Deep learning-based symbol detection algorithm in IMDD-OOFDM system)[J].中国邮电高校学报（英文版）,2022(06):36-45
A类：
IMDD,OOFDM
B类：
Deep,learning,symbol,detection,algorithm,system,In,current,research,intensity,modulation,direct,optical,orthogonal,frequency,division,multiplexing,effective,channel,compensation,key,improve,performance,order,efficiency,deep,proposed,this,paper,Firstly,high,speed,data,streams,synchronization,training,sequence,used,ensure,accurate,Then,traditional,estimation,are,replaced,by,echo,state,network,ESN,restore,transmitted,signal,Finally,we,collect,from,experiment,calculate,noise,ratio,SNR,analysis,optimized,proves,that,compensating,nonlinear,distortion
AB值：
0.515092
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