基于改进Walsh-Hadamard变换的(n,1,m)卷积码盲识别

针对高误码率情况下(n,1,m)卷积码的盲识别问题，该文提出一种新的基于改进Walsh-Hadamard变换(Walsh-Hadamard Transform, WHT)的方法。首先将原问题等效为多路1/2码率卷积码的盲识别问题，并建立关于其生成多项式系数的线性方程组。然后分析了现有基于WHT的方法直接求解该方程组所存在的不足，重新建立更稳健的判决门限，同时通过缩小解的取值范围降低计算量，进而在求得正确解向量的同时完成对码长的识别。最后，将多路等效1/2码率卷积码的生成多项式按一定条件组合，得到(n,1,m)卷积码的生成多项式矩阵。仿真结果验证了所提方法的有效性，且性能优于传统方法。

Blind Recognition of (n,1,m) Convolutional Codes Based on Modified Walsh-Hadamard Transform

Considering the blind recognition of (n,1,m) convolutional codes at high bit error rate, a novel method based on modified Walsh-Hadamard Transform (WHT) is presented. First, the original issue is equivalent to the blind recognition of several 1/2 rate convolutional codes, and a system of linear equations for generating polynomial coefficients is established. Disadvantages of the existing methods based on WHT are analyzed, after which a more robust decision threshold is deduced, with a reduction in computational complexity by limiting the range of roots, and then the code length is recognized while the correct solution vector is found. Finally, the generator polynomial matrix of (n,1,m) convolutional codes is obtained by combining the generator polynomial of the equivalent 1/2 rate convolutional codes. The simulation results verify the effectiveness of the proposed method, which has a better performance when comparing to the traditional method.