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对于单输入一多输出(SIMO)FIR信道,文中提出一种基于二阶统计的自适应盲识别和均衡算法.首先,基于输入数据矩阵的QR分解把盲信道识别问题转换为低秩矩阵近似解.然后,应用双递推最小二乘(Bi-LS)子空间跟踪方法来推导快速递归盲信道识别算法.新算法仅需要O(md~2)计算复杂度或者O(md)如果仅是均衡,其中m为接收数据矢量的维数(或信道矩阵的行秩),而d是信号子空间维数(或信道矩阵的列秩).为了克服后向迭代的缺陷,也提出一种逆QR子空间跟踪和信道均衡递推算法.逆QR递推算法十分适合于脉动阵并行实现.模拟结果证明了所提出的算法对于信道识别和均衡的有效性.
For single-input-multiple-output (SIMO) FIR channel, an adaptive blind identification and equalization algorithm based on second-order statistics is proposed.Firstly, QR decomposition based on input data matrix converts blind channel identification problem into low-rank matrix approximate solution Then, a fast recursive blind channel identification algorithm is derived by using Bi-LS subspace tracking method.The new algorithm only needs O (md ~ 2) computational complexity or O (md) if only balanced , Where m is the dimension of the received data vector (or the rank of the channel matrix) and d is the signal subspace dimension (or the column rank of the channel matrix). To overcome the drawbacks of the backward iteration, an inverse QR Subspace tracking and channel equalization recursion algorithm.The inverse QR recursive algorithm is very suitable for the parallel implementation of the pulsation matrix.The simulation results show the effectiveness of the proposed algorithm for channel identification and equalization.