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Channel estimation is critical to receiver performance in the long term evolution (LTE) system. Reference signals are interspersed with data signals among the subcarriers to aid channel estimation. Linear minimum mean square error (LMMSE) channel estimation is an efficient approach to estimate the knowledge of channel with high complexity. LMMSE based on singular value decomposition and partitioning the channel autocorrelation matrix have been investigated respectively. In this paper, we propose a new complexity reduction channel estimation approach combining the advantages of the above two optimal LMMSE algorithms. Since the proposed approach substitutes the whole channel autocorrelation matrix by small submatrices, the complexity is significantly reduced with negligible performance degradation.