针对采用循环前缀的多输入多输出(MIMO-CP)系统,提出了一种基于子空间的盲信道估计方法。MIMO-CP系统中其信道矩阵具有块循环特性,对于连续的两个接收数据块以及对应的循环前缀部分组成的向量,可以重新构造一组新的向量而不改变系统的信道矩阵,因此通过较少的接收块就能够得到准确的自相关矩阵的估计值,该方法十分适用于对快变信道的盲估计。文章通过仿真分析了在不同的重复系数以及不同的接收块下该算法的性能并且比较了该算法与现有盲信道估计算法的性能。仿真结果表明,该算法利用较少的数据块个数就得到了一个可靠的信道估计值和较好的误码率性能。
This paper proposes a subspace based blind channel estimation algorithm for Multi-Input Multi-Output with cyclic prefix (MIMO-CP) systems,which utilizes the redundancy introduced by the cyclic prefix.The channel matrix of MIMO-CP system is a block circulant matrix,exploiting the circulant property of channel matrix,for the vector composed of the two consecutive received data blocks and the corresponding cyclic prefix part,we can obtain a group of new vectors without changing the channel matrix.By utilizing these extended vectors,we can get an accurate estimation of auto-correlation matrix with fewer received blocks.The proposed method is very suitable for blind estimation of the fast varying channels.This paper analyzes the system performance in different repetition factors and the number of received blocks by numerical simulation.Furthermore,compared with some existing methods,the proposed algorithm archived a more reliable estimation and better bit error rate performance with fewer received blocks.