基于编码矩阵估计的极化码参数盲识别算法  

Blind identification algorithm for polarization code parameters based on encoding matrix estimation

作　　者：张天骐[1] 杨宗方 邹涵 马焜然 ZHANG Tianqi;YANG Zongfang;ZOU Han;MA Kunran(School of Communication and Information Engineering,Chongqing University of Posts and Telecommunications,Chongqing 400065,China)

机构地区：[1]重庆邮电大学通信与信息工程学院,重庆400065

出　　处：《系统工程与电子技术》2024年第9期3221-3230,共10页Systems Engineering and Electronics

基　　金：国家自然科学基金(61671095,61702065,61701067,61771085);信号与信息处理重庆市市级重点实验室建设项目(CSTC2009CA2003);重庆市自然基金(cstc2021jcyj-msxmX0836);重庆市教育委员会科研项目(KJ1600427,KJ1600429)资助课题。

摘　　要：针对当前极化码参数识别算法缺少对码字起点的识别以及识别信息位算法计算复杂的问题,提出一种基于编码矩阵估计的极化码参数盲识别算法。所提算法首先将截获的码字矩阵、相应码长下的克罗内克矩阵以及逆向重排矩阵相乘得到编码矩阵估计,然后通过编码矩阵的分布特征识别出码长和码字起点,最后使用训练好的卷积神经网络对极化码信息位以及冻结位进行识别。实验结果表明,所提方法不仅完成了码字起点的识别,而且在未知码字起点的情况下完成了对码长的识别,且码长的识别准确率优于现有算法,误比特率在0.19时,参数为(32,12)的极化码码长识别率仍然可以达到90%以上。In order to solve the problem that the current polarization code parameter recognition algorithm lacks the recognition for the starting point of code word and the information bit recognition algorithm is complicated,a polarization code parameter blind recognition algorithm based on the code matrix estimation is proposed.The proposed algorithm firstly multiplies the intercepted codeword matrix with the Kronecker matrix under the corresponding code length and the reverse rearrangement matrix to obtain the code matrix estimation,then identifies the code length and the code word starting point by the distribution characteristics of the code matrix,and finally uses the trained convolutional neural network to identify the information bits and freezing bits of the polarization code.The experimental results show that the proposed method not only realizes the recognition for the starting point of code word,but also realizes the code length recognition when the code word’s starting point is unknown,and the code length recognition accuracy is better than the existing algorithm.When the bit error rate is 0.19,the polarization code length recognition rate of parameter(32,12)can still reach more than 90%.

关 键 词：极化码 参数盲识别 编码估计矩阵 神经网络 

分 类 号：TN911.7[电子电信—通信与信息系统]