毫米波MIMO系统中稀疏度自适应的压缩感知信道估计

利用毫米波MIMO系统的稀疏特性,信道估计可以转化为稀疏信号重构的问题。解决毫米波MIMO稀疏信道估计问题时,传统的OMP方法需要信号的稀疏度作为先验信息,实际系统难以满足此需要。文中引入StOMP算法,根据信号已知的稀疏先验信息确定阈值,并结合动态的阈值调整,提出一种新的StOMP-D算法,实现了稀疏度自适应的毫米波MIMO信道估计。仿真结果表明,所提的方法与传统的LS方法比较,信道估计性能显著提高,并且与稀疏度已知的OMP方法性能十分接近,在稀疏度未知时有明显的优势。

Sparse Adaptive Compressed Sensing Channel Estimation in Millimeter Wave MIMO Systems

With the sparse characteristics of millimeter-wave MIMO systems, channel estimation can be transformed to the problem of sparse signal reconstruction. When solving the problem of millimeter-wave MIMO sparse channel estimation, the traditional OMP method requires the signal sparsity as a priori information, which is difficult to meet in practical systems. The StOMP algorithm was introduced in this paper. The threshold was determined according to the sparse prior information known by the signal. Combined with the dynamic threshold adjustment, a new StOMP-D algorithm was proposed to realize the sparse adaptive millimeter-wave MIMO channel estimation. The simulation results showed that compared with the traditional LS method, the performance of the proposed algorithm was significantly improved, and the performance of the OMP method with known sparsity was very close. It had obvious advantages when the sparsity was unknown.