系统工程与电子技术 ›› 2022, Vol. 44 ›› Issue (2): 668-676.doi: 10.12305/j.issn.1001-506X.2022.02.38

• 通信与网络 • 上一篇    下一篇

基于信息矩阵估计的极化码参数盲识别算法

刘鉴兴1,2,*, 张天骐1,2, 柏浩钧1,2, 叶绍鹏1,2   

  1. 1. 重庆邮电大学通信与信息工程学院, 重庆 400065
    2. 重庆邮电大学信号与信息处理重庆市重点实验室, 重庆 400065
  • 收稿日期:2021-01-15 出版日期:2022-02-18 发布日期:2022-02-24
  • 通讯作者: 刘鉴兴
  • 作者简介:刘鉴兴(1997—), 男, 硕士研究生, 主要研究方向为信道编码参数盲识别技术研究|张天骐(1971—), 男, 教授, 博士, 主要研究方向为通信信号的调制解调, 盲处理, 图像、语音信号处理, 神经网络实现以及FPGA、VLSL实现|柏浩钧(1997—), 男, 硕士研究生, 主要研究方向为语音信号处理、语音增强|叶绍鹏(1996—), 男, 硕士研究生, 主要研究方向为图像处理、数字水印、信息隐藏
  • 基金资助:
    国家自然科学基金(61671095);国家自然科学基金(61702065);国家自然科学基金(61701067);国家自然科学基金(61771085);信号与信息处理重庆市市级重点实验室建设项目(CSTC2009CA2003);重庆市研究生科研创新项目(CYS19248);重庆市教育委员会科研项目(KJ1600427);重庆市教育委员会科研项目(KJ1600429)

Blind recognition algorithm of polar code based on information matrix estimation

Jianxing LIU1,2,*, Tianqi ZHANG1,2, Haojun BAI1,2, Shaopeng YE1,2   

  1. 1. School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
    2. Chongqing Key Laboratory of Signal and Information Processing, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
  • Received:2021-01-15 Online:2022-02-18 Published:2022-02-24
  • Contact: Jianxing LIU

摘要:

针对目前极化码码长识别存在抗噪声性能差的问题, 提出了基于信息矩阵估计的极化码参数盲识别算法。本文算法利用极化码生成矩阵的逆矩阵, 与码字比特流构造的码字矩阵相乘得到估计的信息矩阵, 在无误码情况下根据分析矩阵所含的信息得到码率, 并利用其分布情况来识别码长、信息比特位数和位置分布。在有误码的情况下, 引入了零均值比计量, 根据峰值识别出码长。最后, 利用分析矩阵和设定判决门限, 识别出信息比特位数和位置分布。仿真结果表明, 本文算法对码长的识别性能有所提高, 对于参数为(64, 30)的极化码, 在误码率高达1.06×10-1时, 码长的识别率依然能达到80%。

关键词: 非合作信号处理, 零均值比, 极化码, 盲识别

Abstract:

In order to solve the problem of poor anti-noise performance in the current polar code length recognition, a blind recognition algorithm of polar code parameters based on information matrix estimation is proposed. In this algorithm, the inverse matrix of the polar code generation matrix is used to multiply with the code word matrix constructed by the code word bit stream to obtain the estimated information matrix. In the case of no error code, the bit rate is obtained according to the information contained in the analysis matrix, and its distribution is used to identify the code length, bit number and position distribution. In the case of bit error, zero mean ratio measurement is introduced to identify the code length according to the peak value. Finally, by using the analysis matrix and setting the decision threshold, the information bit number and position distribution are identified. The simulation results show that the recognition performance of the proposed algorithm for code length is improved. For the polar code with parameters of (64, 30), the recognition rate of code length can still reach 80% when the bit error rate is as high as 1.06×10-1.

Key words: non-cooperative signal processing, zero mean ratio, polar code, blind recognition

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