摘要
针对二阶统计量信道盲辨识算法中有效阶数估计问题,该文提出了一种基于子空间信道矩阵迭代的阶数估计(SS-CMR)算法。基于过估计条件下的Q矩阵特殊结构和其解空间向量可等价为真实信道冲激响应与公共零点信道的卷积,该算法首先利用子空间算法获得估计的信道矩阵,然后构建迭代形式的代价函数进行阶数估计。仿真表明,SS-CMR算法较CMR算法性能提升,且明显优于现有其他阶数估计算法;解析分析表明算法复杂度较CMR算法明显降低,对首尾系数很小的信道的阶数估计尤为有效。
Effective channel order estimation is a critical step of blind channel identification. A blind channel effective order estimation algorithm based on SubSpace Channel Matrix Recursion （SS-CMR） is proposed. On the basis of the special structure of Q matrix and the its null space vector equivalently viewed as the convolution of true channel impulse response and the common zero channel, the channel matrix is obtained by SS method and then the estimated channel order is got by the constructed recursion cost function. The simulation proves that the performance of SS-CRM is improved compared with CMR and obviously better than the other existing algorithm, especially when the channel impulse response has small head and tail taps; analytical analysis shows that the algorithm complexity of SS-CMR is obviously reduced compared with CMR.
出处
《电子与信息学报》
EI
CSCD
北大核心
2013年第2期432-437,共6页
Journal of Electronics & Information Technology
基金
国家863计划项目(2009AA011205)资助课题
