Abstract: In view of the pilot contamination problems in Massive MIMO systems, together with the present study of ?SVD-based channel estimation algorithm, because the covariance matrix is made of the finite sample data rather than real data, it is a deviation here. Thus, joint SVD-based method and Iterative Least Square with Projection（ILSP） algorithm is introduced. Simulation results indicate that the proposed method can effectively reduce the deviation?and improve the channel estimation accuracy, and it can effectively mitigate the effect of pilot contamination, so as to realize the purpose of Massive MIMO system performance improvement.

Key words: massive Multiple-Input Multiple-Output（MIMO） systems, pilot contamination, Singular?Value?Decomposition（SVD） algorithm, Iterative Least Square with Projection（ILSP） algorithm

摘要： 针对大规模MIMO系统中存在的导频污染问题，结合目前研究的基于奇异值（SVD）分解的信道估计算法，在考虑到该算法中的协方差矩阵是用有限的样本数据代替真实数据必然存在偏差的问题，给出了一种联合ILSP（Iterative Least Square with Projection）的基于SVD的半盲信道估计算法。仿真结果表明改进后的信道估计算法能够有效减小已有算法中存在的偏差问题，提高信道估计精确度，有效减轻导频污染给大规模MIMO系统带来的影响，从而实现大规模MIMO系统性能的提升。

关键词: 大规模多输入多输出（MIMO）系统, 导频污染, 奇异值分解（SVD）算法, 迭代最小二乘投影（ILSP）算法