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(n,1,m)递归系统卷积码(RSC)是Turbo码分量编码采用最多的一种编码方式。针对RSC提出了基于改进欧几里德算法的识别方法,为Turbo码的识别奠定了基础。该方法首先将(2,1,m)卷积码的识别模型应用推广至(n,1,m)卷积码,即求解n个多项式的最高公因式,进而利用改进的欧几里德算法识别生成多项式。最后,实例仿真验证了该方法的有效性。
(n, 1, m) Recursive System Convolutional Codes (RSCs) are the most commonly used coding schemes for Turbo code component coding. Aiming at RSC, an identification method based on improved Euclidean algorithm is proposed, which lays the foundation for the identification of Turbo codes. Firstly, the identification model of (2, 1, m) convolutional codes is extended to (n, 1, m) convolutional codes to solve the highest common divisor of n polynomials, and then the improved Euclidean The algorithm identifies the generator polynomial. Finally, the simulation results show the effectiveness of the method.