基于酉矩阵训练序列的CFO估计算法

A CFO Estimation Algorithm Based on Unitary Matrix Training Sequence

分析数据辅助类算法传输效率较低、盲估计算法精度较差的特性,通过公开已知的训练序列,借助酉矩阵的逆矩阵为其转置矩阵的性质,将训练符号与其接收信号作相关运算,提出一种新的CFO估计算法。该算法能够消除信道噪声的影响,且其计算复杂度能够根据酉矩阵训练长度进行灵活调整。通过Matlab仿真发现,该算法性能存在最优值,在最优值以外,一味增加训练序列长度并不能有效提升算法性能,且增加了复杂度。

Analyzing the characteristics of low data transportation efficiency of data-aided algorithm, and relatively worse performance of blind estimation, it proposed a new CFO estimation algorithm named UMTS based on unitary matrix training sequence. Apply-ing correlative computation into training sequence and its received signal, with the help that unitary matrix’s inverse matrix is its transpose one, this algorithm can eliminate the effect of channel noise, its computation complexity can be easily adjusted according to the dimension of training sequence. After simulation by matlab, we found that there exists an optimum dimension for the training sequence. We cannot significantly improve the performance by increasing the size of unitary matrix, which wil increase the complexity of UMTS.