联合波束域分解和SVD的多用户大规模MIMO系统信道估计

针对TDD(Time Division Duplex)模式下的多用户大规模MIMO(Multiple-Input Multiple-Output)系统，本文研究了将波束域分解和SVD(Singular Value Decomposition)同时用于该系统的信道估计。当基站天线数目较多时，信道估计误差、导频开销、信道估计算法的复杂度等问题将成为影响大规模MIMO系统性能的关键因素。运用波束域分解理论，将多用户的大规模MIMO系统分解成多个单用户的大规模MIMO系统，同时从波束域对信道建模，该方法降低导频开销的同时也减小了信道估计误差。另外运用SVD对信道自相关矩阵优化，可以进一步降低信道估计算法的复杂度。基于以上两点，本文提出了一种联合波束域分解和SVD的大规模MIMO信道估计方案，并推导出了估计误差协方差矩阵的闭式表达式。仿真结果表明，与同类方案相比，本文提出的方案具有更好的信道估计性能。 

Joint Beam Domain Decomposition and SVD for Channel Estimation in Multi-user Massive MIMO System

Aiming at the multi-user massive multiple-input multiple-output(MIMO) system under TDD mode, beam domain decomposition and SVD are used in the channel estimation of the system at the same time in this paper. When the base station equipped with a large number of antennas, the problems such as channel estimation accuracy, pilot overhead and complexity of channel estimation algorithm will be the key factors that affect the performance of massive MIMO system. By using the beam domain decomposition theory, multi-user massive MIMO system can be decomposed into multiple single-user massive MIMO system, and modeling the channel from the beam domain, which reduces the pilot overhead while also reducing the channel estimation error. In addition, the use of SVD to optimize the channel autocorrelation matrix can further reduce the complexity of the channel estimation algorithm. Based on the above two points, this paper proposes a massive MIMO channel estimation scheme based on beam domain decomposition and SVD, and deduces the closed expression of the estimated error covariance matrix. The simulation results show that compared with the similar scheme, the proposed scheme has better channel estimation performance.