摘要
针对二阶统计量信道盲辨识算法在小样本观测数据条件下性能恶化且对信道阶数误差敏感的问题,本文首先提出一种改进的基于FFT变换的信道盲辨识算法(FFT-MCR),该算法充分利用MCR算法只需最小冗余度信息求解信道向量的特性,有效地降低了原算法(BI-FFT)的计算复杂度且性能相当。研究表明FFT-MCR算法在信道阶数过估计情况下额外引入的公零点具有单位圆聚集性,同时提出一种具有较强阶数鲁棒性的盲辨识算法(R-FFT-MCR),算法通过聚类的思想搜索单位圆周围的公零点并将其移除,实现准确的信道估计。理论分析与仿真实验验证了所提算法的有效性。
According to performance of the blind channel identification algorithms based on second-order statistics deteri- orates under the small received data and is sensitive to the error of channel order. This paper proposes an improved blind channel identificattion algorithm based on FFT, This algorithm is expoliting the property of the MCR algorithm requiring minimum redundancy information to obtain the channel vector, then effectively reduces the computational complexity of the original algorithm（BI-FFT） but the performance is quite. It has been found that the extra estimated channel common zeros introduced by overestimating the channel order based on FFT-MCR algorithm are gathered around the unit circle, at the same time puts forward R-FFT-MCR algorithm that is robustness to channel order overestimation, We can search the com- mon zeros around the unit circle through the idea of clustering, remove them and realize the correct channel estimation. Theoretical analysis and simulation results verify the effectiveness of the proposed algorithm.
出处
《信号处理》
CSCD
北大核心
2014年第1期65-71,共7页
Journal of Signal Processing
基金
超宽带无线通信系统研发与应用示范(2009AA011205)
关键词
信道盲辨识
单输入多输出
二阶统计量
小样本数据
blind channel identification
single-input multiple-output（SIMO）
second order statistics
small sample data
