一种循环码参数的全盲识别方法  

Blind Recognition Method of Cyclic Codes Parameters

作　　者：王兰勋[1] 贾层娟 熊政达 WANG Lan-xun JIA Ceng-juan XIONG Zheng-da(College of Electronic and Informational Engineering, Hebei University, Baoding 071000, China)

机构地区：[1]河北大学电子信息工程学院,保定071000

出　　处：《计算机科学》2017年第3期283-287,共5页Computer Science

基　　金：河北省自然科技基金项目(F2014201168)资助

摘　　要：针对循环码参数的全盲识别问题,利用实际序列与随机序列码重分布差异最大的特性,提出了基于数据挖掘中的相似性度量函数与统计学中的斯皮尔曼等级相关系数进行融合来识别码长和起始点的方法,在此基础上,利用有限域同构的原理,选取码重概率最大的码字进行伽罗华域的傅里叶变换来识别生成多项式,实现了对循环码的全盲识别。理论分析及仿真实验表明,该算法简单易行,容错性较强,在误码率为0.01的条件下对中短码的识别效果较好。In view of the problem of the blind recognition of cyclic code parameters, the code length and starting point are identified by the recognition method based on the fusion of a similarity measuring function in data mining and Spearman Rank correlation coefficient in statistics. The method was proposed by the maximum difference between the code weight distribution of the actual sequence and random sequence. Then, on the basis of the isomorphic principle of finite fields, the generator matrix is solved by selecting code words of code weight with the highest probability for Galois field Fourier transform. The blind recognition of cyclic code is finally realized. Theoretical analysis and simulation experi- ments show that the method is simple and has stronger error-tolerance, and it can identify medium short code better un- der the condition of BER of 0. 01.

关 键 词：循环码 全盲识别 码重分布 生成多项式 

分 类 号：TN911.22[电子电信—通信与信息系统]