解辉1,,,
韩壮志1,
史林1,
尹园威1
1.陆军工程大学石家庄校区电子与光学工程系 ??石家庄 ??050003
2.北京科技大学自动化学院 ??北京 ??100083
基金项目:国家自然科学基金(61473033)，中国博士后科学基金(2015M580988)
详细信息
作者简介:姚智刚：男，1980年生，讲师，研究方向为控制系统故障诊断与容错控制技术
解辉：男，1983年生，讲师，研究方向为雷达、通信信号侦察处理及信道编码识别分析技术
韩壮志：男，1972年生，副教授，硕士生导师，研究方向为电子对抗技术
史林：男，1985年生，讲师，研究方向为信号处理与雷达成像技术
尹园威：男，1984年生，讲师，研究方向为数字信号与信息处理技术
通讯作者:解辉 xiehui_oec@163.com
中图分类号:TN911计量
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被引次数:0
出版历程
收稿日期:2018-12-10
修回日期:2019-05-17
网络出版日期:2019-05-28
刊出日期:2019-09-10
Blind Reconstruction of Convolutional Code Based on Partitioned Walsh-Hadamard Transform
Zhigang YAO1, 2,Hui XIE1,,,
Zhuangzhi HAN1,
Lin SHI1,
Yuanwei YIN1
1. Department of Electronic and Optics Engineering, Army Engineering University Shijiazhuang Campus, Shijiazhuang 050003, China
2. School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, China
Funds:The National Natural Science Foundation of China (61473033), China Postdoctoral Science Foundation (2015M580988)
摘要
摘要:利用Walsh-Hadamard变换可实现2元域含错方程组的求解，该方法可用于卷积码的盲识别，但当方程组未知数较多时，其对计算机内存的要求使得该方法在实际中难以应用，为此该文提出一种基于分段Walsh-Hadamard变换的卷积码识别方法。该方法通过对方程组高维系数向量进行分段，使其转化为两个低维的系数向量，将Walsh-Hadamard变换求解高维方程组的问题分解为求解两个较低维数方程组的问题，同时证明了两个低维方程组解向量的组合就是高维方程组的解。算法有效减少了对计算机内存的需求，仿真结果验证了该算法的有效性，且算法具有良好的误码适应能力。
关键词:卷积码/
盲识别/
Walsh-Hadamard变换/
含错方程/
重构
Abstract:The Walsh-Hadamard transform can be used to solve binary domain error-containing equations, and the method can be used for blind identification of convolutional codes. However, when the number of system unknowns is large, the requirement of computer memory makes it difficult to apply this method to practice. Therefore, a convolutional code recognition method based on partitioned Walsh-Hadamard transform is proposed. By segmenting the high-dimensional coefficient vectors of the equations into two low-dimensional coefficient vectors, the problem of solving the high-dimensional equations by Walsh-Hadamard transformation is decomposed into the problem of solving the two low-dimensional equations, and it is proved that the combination of the solution vectors of the two low-dimensional equations is the solution of the high-dimensional equations. The algorithm reduces effectively the need for computer memory, and the simulation results verify the effectiveness of the proposed algorithm, and the algorithm has good error code adaptability.
Key words:Convolutional code/
Blind identification/
Walsh-Hadamard transformation/
Error- containing equation/
Reconstruction
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