基于压缩感知的MIMO双选择性衰落信道的估计

为了减少MIMO （multiple-input multiple-output）时频双选择性衰落信道估计过程中需要的导频符号数,文中对多径信道的时延和多普勒频移构成的时频二维有界区域进行量化,将该信道估计问题建模为压缩感知理论中的稀疏信号重构问题,提出了一种采用正交匹配追踪估计MIMO双选择性衰落信道的方法.仿真结果表明获得相同的估计性能,所提出的压缩信道感知方法比传统的最小二乘法能节省近50％的导频符号,且该方法在低信噪比的场景里也能获得较高的估计性能.

Doubly-Selective Fading Channel Estimation in MIMO Systems Based on Compressed Sensing

In order to reduce the numbers of pilots needed for estimating the doubly-selective channel in multiple-input multiple-output （MIMO） systems,the time-frequency two dimensional bounded region,which is composed of time delay of multi-path channel and Doppler frequency shift,is quantized.The channel estimation is modeled as the problem of sparse signal reconstruction in the theory of compressed sensing.A method is proposed for tracing and estimating doubly-selective channel using the orthogonal matching pursuit （OMP） algorithm.Simulation results show that the proposed compressed channel sensing method can save nearly 50％ pilot numbers than the conventional least square （LS） method to obtain the same performance.Moreover,the proposed method can achieve high performance of channel estimation in the case of low SNR.