首页 | 本学科首页   官方微博 | 高级检索  
     

基于机器学习方法的高速信道建模研究
引用本文:何静,李晋文,杨安毅. 基于机器学习方法的高速信道建模研究[J]. 计算机工程与科学, 2021, 43(6): 984-988. DOI: 10.3969/j.issn.1007-130X.2021.06.005
作者姓名:何静  李晋文  杨安毅
作者单位:(国防科技大学计算机学院,湖南 长沙 410073)
摘    要:随着高速信道的传输速率变快,传输长度变长,结构复杂度变高,对信道进行建模也变得复杂与艰难.将目前比较火热的机器学习方法与高速信道结合起来,提出了一个新颖的方法.利用采集的大量模拟数据,采用深度神经网络DN N与循环神经网络RN N对信道建模,模型一旦训练成功,就可以通过该仿真模型预测输出信号的眼图,快速精准地对信号完整...

关 键 词:高速信道  DNN  RNN  眼图  机器学习  均衡  LMS
收稿时间:2020-11-08
修稿时间:2021-01-13

High speed channel modeling based on machine learning
HE Jing,LI Jin-wen,YANG An-yi. High speed channel modeling based on machine learning[J]. Computer Engineering & Science, 2021, 43(6): 984-988. DOI: 10.3969/j.issn.1007-130X.2021.06.005
Authors:HE Jing  LI Jin-wen  YANG An-yi
Affiliation:(College of Computer Science and Technology,National  University of Defense Technology,Changsha 410073,China)
Abstract:With the increase of transmission rate, transmission length and structure complexity of high-speed channel, channel modeling technology becomes more complex and difficult. This paper proposes a novel method by combining the popular machine learning method with high-speed channel. A large number of analog data are collected, and deep neural network (DNN) and recurrent neural network (RNN) methods are used to model the channel. Once the model is trained successfully, the eye diagram of the output signal can be predicted by the simulation model, and the signal integrity can be evaluated and analyzed quickly and accurately. In addition, in the high-speed channel, the serious interference and attenuation of the signal limits the transmission distance and transmission rate, which brings difficulties to the test and information collection. In order to recover the ideal signal, the high-speed serial link usually contains complex equalization blocks.The least mean square (LMS) algorithm is adopted to effectively eliminate the interference, reduce the bit error rate and improve the transmission rate.
Keywords:high speed channel  deep neural network(DNN)  recurrent neural network(RNN)  eye diagram  machine learning   equalization  least mean square(LMS)  
本文献已被 万方数据 等数据库收录!
点击此处可从《计算机工程与科学》浏览原始摘要信息
点击此处可从《计算机工程与科学》下载全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号