一种软判决下的本原BCH码盲识别方法

刘杰; 张立民; 钟兆根; 马超

doi:10.7652/xjtuxb201706010

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一种软判决下的本原BCH码盲识别方法

更新时间：2025-07-09

- 一种软判决下的本原BCH码盲识别方法
- A Blind Recognition Method for Primitive BCH Codes in Soft Decision Situations
- 西安交通大学学报 2017年51卷第6期页码：59-65
- 作者机构：
  
  海军航空工程学院信息融合研究所,山东,烟台,264001
- 作者简介：
- 基金信息：
  
  : 2016-12-02。作者简介: 刘杰(1990—),男,博士生;张立民(通信作者),男,教授,博士生导师。基金项目: 国家自然科学基金重大研究计划资助项目(91538201);泰山学者工程专项经费资助项目(st201511020)
- DOI：10.7652/xjtuxb201706010
  中图分类号： TN911.22
- 网络首发：2017-06-10，
  
  纸质出版：2017
- 稿件说明：
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刘杰, 张立民, 钟兆根, 等. 一种软判决下的本原BCH码盲识别方法[J]. 西安交通大学学报, 2017,51(6):59-65.

A Blind Recognition Method for Primitive BCH Codes in Soft Decision Situations[J]. 2017, 51(6): 59-65.
刘杰, 张立民, 钟兆根, 等. 一种软判决下的本原BCH码盲识别方法[J]. 西安交通大学学报, 2017,51(6):59-65. DOI： 10.7652/xjtuxb201706010.

A Blind Recognition Method for Primitive BCH Codes in Soft Decision Situations[J]. 2017, 51(6): 59-65. DOI： 10.7652/xjtuxb201706010.

摘要

为解决现有BCH码识别方法容错性较差的问题

提出了一种软判决下的本原BCH码盲识别(SDBR)方法。首先

将截获数据进行解调软判决得到比特序列和对应可靠性信息

然后对比特序列进行码字划分

再由软判决可靠性信息建立码根可靠性系数

以此计算不同码根出现的概率

并引入Kullback-Leibler散度来确定码长; 其次

定义公共码根可靠性统计量并建立二元假设检验

在不同本原多项式下对公共码根进行判定; 最后

利用公共码根连续分布特点识别本原多项式

进而由所有公共码根计算生成多项式。仿真结果表明:SDBR方法在信噪比大于7 dB时能有效对常用本原BCH码进行识别; 与基于码根信息差熵的方法相比

容错性提升了1.8 dB。

Abstract

A soft decision based blind recognition(SDBR)method for primitive BCH codes is proposed to solve the problem that existing recognition methods have low error-resilient capabilities. Firstly

bit sequences as well as the corresponding reliability information are obtained by soft demodulation of the intercepted data

then code words are divided and a reliability coefficient of code roots is established with the reliability information to calculate the occurrence probability of code roots

and code length is estimated by using Kullback-Leibler divergence. Secondly

reliability statistics of common code roots are defined and a binary hypothesis test is built

then common code roots are verified under different primitive polynomials. Finally

the right primitive polynomial is recognized by using the continuous distribution characteristics of common code roots

and a generator polynomial is calculated from all these code roots. Simulation results show that the SDBR method effectively recognizes the commonly used primitive BCH codes when the signal-to-noise ratio is above 7 dB. A comparison with the roots information dispersion entropy based method shows that the SDBR method improves the error-resilient performance by 1.8 dB.

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Keywords

references

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