基于空频相关性的大规模MIMO-OFDM信道压缩反馈算法

大规模MIMO-OFDM系统中，信道常常存在较强的空间和频域相关性。针对多数信道压缩反馈算法仅考虑空间或频域相关性的问题，该文提出一种空频联合压缩反馈算法。首先，根据压缩感知理论进行了信道空频2维稀疏度分析；然后，推导了信道矩阵在空间和频域2维相关性下的联合稀疏基；最后，利用该联合稀疏基给出了空频联合压缩算法。仿真结果与分析表明，该算法在保证信道反馈精度的同时，可显著降低反馈量。

Compressed Channel Feedback Based on Spatial-frequency Correlation for Massive MIMO-OFDM Systems

In Massive MIMO-OFDM systems, the channel shows strong correlations in both spatial and frequency domain. Aiming at the problem that only spatial or frequency domain correlation is considered in most of the existing compressed feedback algorithms, a joint spatial-frequency compression algorithm is proposed. First, a two dimensional sparsity of channel in spatial-frequency domain is analyzed according to the compressed sensing theory. Then, a joint sparse matrix of channel is derived. Based on the joint sparse matrix, the joint spatial-frequency compression algorithm is presented. Simulation results and analysis show that, the proposed algorithm can significantly reduce the feedback load with acceptable accuracy.