本文提出一种基于相关矩阵列矢量平均的信道估计算法，该算法不需要特征分解或跟踪。
A new method based on column vector average of the autocorrelation matrix without eigendecomposition is presented to estimate the channel vector.
在不求出DOA的情况下，采用离散傅里叶变换来估计该路径下行信道协方差矩阵。
DFT is used to estimate the covariance matrix of downlink channel of the path, not calculating DOA.
与传统解码的算法不同，该算法无需在发送端进行信道相关矩阵的估计和预编码，降低了发送端的编码复杂度。
Compared to the traditional decoding algorithms, the proposed scheme is no need to estimate the correlation matrix of the channel and pre-code at the transmitter, and its coding complexity is reduced.
与已有线性最小均方差(LMMSE)信道估计方法相比，该算法简单并且不需要预先知道信道相关矩阵以及信噪比等信道信息。
Comparing with the Linear Minimum Mean Square Error (LMMSE) channel estimation method, the method is simple and need not know the channel correlation and signal-to-noise (SNR).
该方法采用固定点ica算法来估计多径信道的混合矩阵，从而提取信道的延迟信息。
The mixture matrix of multi-path channel can be estimated using a fast fixed-point algorithm, and then the delay information of channel can be obtained.
该方法采用固定点ica算法来估计多径信道的混合矩阵，从而提取信道的延迟信息。
The mixture matrix of multi-path channel can be estimated using a fast fixed-point algorithm, and then the delay information of channel can be obtained.
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