基于概率逼近的本原BCH码编码参数的盲识别方法

阔永红 曾伟涛 陈 健



基于概率逼近的本原BCH码编码参数的盲识别方法

阔永红*曾伟涛 陈 健

(西安电子科技大学通信工程学院 西安 710071)

针对本原BCH码编码参数的盲识别问题，该文提出了一种基于概率逼近的盲识别方法。首先，利用Gauss分布和Poisson分布逼近随机码字的根概率特性，确定了搜索BCH码长的门限；然后，通过分析本原域元素的检错能力及同构对域的影响，应用临近域对的方法确定编码域，提高了其识别能力；最后，给出识别生成多项式时的共轭根系表，从而减少了计算量。仿真结果表明，在较高的误码率下，该方法能快速地识别出BCH码编码所采用的编码参数。

信道编码；BCH码；共轭根系；盲识别

1 引言

2 BCH码定义及分析

2.1 BCH码定义及分析

2.2 概率分布特性的逼近

3 BCH编码盲识别的实现

3.1 用于域间搜索的门限定义

3.2 算法描述

图1 误码率与误码码字比例的关系

表1部分临近域对

(203,253)(607,895)(701,647)(827,607) (425,333)(761,539)(859,761)(911,787)

4 仿真分析

4.1 仿真实验与复杂度分析

4.2 仿真性能

表2算法的复杂度分析

文献[10]文献[11]本文所提算法 m=h m=9 m=3

图3 不同码长在各种误码率下的识别率

5 结束语

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阔永红： 女，1967年生，博士，教授，研究方向为智能信号处理.

曾伟涛： 男，1988年生，硕士生，研究方向为通信编码识别技术.

陈 健： 男，1968年生，教授，博士生导师，研究方向为通信对抗、认知网络.

Blind Identification of Primitive BCH Codes Parameters Based on Probability Approximation

Kuo Yong-hong Zeng Wei-tao Chen Jian

(,,,710071,)

To solve the issues of blind identification of primitive BCH codes encoding parameters, a novel identification algorithm with probability approximation is presented. Frist, by taking advantage of the approximation of random code words’ root probability character which uses Gaussian distribution and Poisson distribution, the thresholds for searching code length are structured. Second, though analyzing the checking ability of the primitive element and the impact of isomorphism on searching, the coding filed is determined by using the method of nearby fields pair which improves the performace of identification. Finally, the calculation is reduced by creating and using the conjugate roots table in the recognition of generator polynomial. Simulation results show that, the proposed algorithm achieves a significant improvement in identification probability even if in high BER situation.

Channel coding; BCH codes; Conjugate roots; Blind identification

TP391;TN911.22

A

1009-5896(2014)02-0332-08

10.3724/SP.J.1146.2013.00584

阔永红 yhkuo@mail.xidian.edu.cn

2013-04-27收到，2013-07-27改回

国家自然科学基金(60972072)和高等学校学科创新引智计划(B08038)资助课题