该文提出一种基于矩阵开方(computing Roots of Matrices,RM)的盲信道估计算法和一种自适应矩阵开方(Adaptive computing Roots of Matrices,ARM)盲信道估计算法。RM算法利用信息符号的有限字符集特性,在时域上通过对一个Toeplitz下三角矩阵开方进行信道解卷积,得到信道估计的闭合解。该运算复杂度远低于现有的盲信道估计搜索算法,并且适用于信道阶数较大、搜索算法不能处理的情况。仿真结果表明RM信道估计性能接近于搜索算法的最佳性能,而ARM通过最陡下降迭代将代价函数最小化,可以进一步提高信道估计的准确性。
A novel blind channel estimator based on computing Roots of Matrices (RM) is proposed for OFDM systems. This algorithm exploits the finite alphabet property of information symbols and implements channel deconvolution by computing the J^th principle root of a low-triangular Toeplitz matrix. Therefore, RM algorithm has much lower computation complexity than searching algorithms in previous works and is able to function in the case of large channel order that is intractable by searching algorithms. Moreover, an Adaptive RM (ARM) algorithm is proposed to adjust RM estimator by steepest descent method. Simulation results indicate that RM algorithm has great accuracy comparable to the optimal exhaustive search and ARM improves the estimation performance of RM considerably.