MIMO-OFDM快衰落信道的压缩感知估计方法

Compressed sensing estimation methods for fast fading channel of MIMO-OFDM systems

在快衰落多输入多输出(MIMO)-正交频分复用(OFDM)系统中,为了避免传统的信道估计方法中存在大量系数需要估计的问题,利用快衰落信道在角时延多普勒域可稀疏的特性,提出了基于压缩感知的MIMO-OFDM系统快衰落信道估计方法。根据压缩感知的受限等距特性(RIP),推导了一种少量导频随机结构测量矩阵,用于测量快衰落信道在角时延多普勒域稀疏系数。接收端可从这些少量的测量数据中以高概率重构出快衰落信道。理论分析与仿真结果都表明:该方法与传统的信道估计方法相比,所得到的系统数据传输效率及估计性能都有了明显提高。

To avoid estimating a large number of coefficients of the traditional channel estimation methods,a compressed sensing（CS）based channel estimation algorithm is proposed in fast fading environment.An angle-delay Doppler spread sparse channel model in space,time and frequency domain is presented.A structurally random pilot matrix is given to measure the angle-delay Doppler sparse multiple-input multiple-output（MIMO）Orthogonal frequency division multiplexing（OFDM）channels.The relatively nonzero channel coefficients are tracked and estimated from a very limited number of channel measurements at a sampling rate significantly below the Nyquist rate.The simulation results show that the new channel estimator can provide a considerable performance improvement in estimating fast fading channels when the significant reduction is achieved in the required number of pilots and computational complexity.