信道估计是大规模多输入多输出(MIMO)系统的关键技术之一。本文针对频分双工(FDD)大规模MIMO正交频分复用(OFDM)系统, 研究了下行信道估计问题。通过利用大规模MIMO-OFDM信道在角度-频域中的块稀疏特性, 提出了基于块匹配追踪的低复杂度估计算法。另外, 针对采用时域正交导频存在估计周期过长, 有可能超过系统相干时间的问题, 提出了天线分组发送方案, 通过牺牲观测数据长度来换取信道估计周期的减少。仿真结果表明, 所提算法具有良好的抗噪性能, 可以准确找出稀疏向量的非零值位置, 并可自适应确定稀疏度。

One of the key technologies of massive Multiple Input Multiple Output(MIMO) systems is channel estimation. The problem of downlink channel estimation in the Frequency Division Duplexing (FDD) Massive MIMO system is studied. By using the block sparsity of the Massive MIMO-OFDM channel in the angular-frequency domain, a low complexity estimation algorithm based on block matching pursuit is proposed. In addition, the system coherence time may be exceeded due to too much time cost when adopting orthogonal pilot symbol in the time domain. To solve this problem, an antenna grouping transmission scheme is proposed to reduce the total channel estimation time by sacrificing the observed data length. The simulation results show that the proposed algorithm has good anti-noise performance, and it can accurately determine the non-zero position of the sparse vector and can adaptively determine the sparsity.