高误码率下归零Turbo码帧结构识别

现有的高斯消元法在Turbo码帧结构识别中，存在着容错性差且计算量大的缺点，直接导致后续分量编码器以及交织器识别算法无法应用.为此，提出了一种基于矩阵模型列相关性的识别方法.首先在待定帧长下构建分析矩阵，并对其前后相邻两列进行差分处理，然后建立关于差分后矩阵列重的统计量，根据码长及其整数倍处必有统计值能通过判决这一特点确定帧长.最后，通过分析正确码长下通过判决的统计值对应的相对位置关系，归纳帧起点的同步方法.仿真结果表明，本文算法在误码率高达0.1条件下，Turbo帧结构参数识别能够达到100%的识别率，与现有方法相比，本文算法计算复杂度更低且识别性能更好，可应用于认知无线电等非协作通信领域.

Blind Identification of Frame Structure of Turbo Codes on Trellis Termination at High Bit Error

The Gauss elimination method to recognize Turbo code frame structure has the shortcomings of poor fault tolerance and high complex computation,which directly leads to the inapplicability of subsequent algorithms to recognize the component coder and interleaver.For this reason,a novel method based on correlation between columns of the matrix is proposed.Firstly,analysis matrix is constructed under the undetermined frame length,with the neighboring columns being differentiated.Then statistics about column weight is established,and frame length is confirmed by the statistical values,which can pass the decision threshold when the column is frame length and its multiple.Finally,frame staring point is synchronized according to the relative position of statistical values which pass the threshold.The simulation results show that the correct recognition rate of parameters of Turbo frame structure can reach 100%,when the bit error rate is as high as 0.1.Compared with the existing methods,the proposed algorithm has lower computational complexity and better recognition performance,and is very suitable for non-cooperative communication fields such as cognitive radio.