基于压缩感知的多中继协作通信系统稀疏信道估计算法研究

提出了一种基于压缩感知理论的多中继协作通信系统稀疏信道估计方法.采用正交匹配追踪（Orthogonal Matching Pursuit,OMP）压缩感知算法,对时域信道脉冲响应进行估计.对多中继协作通信系统进行稀疏建模;结合压缩感知理论构建观测矩阵,并给出卷积信道的稀疏表示;利用压缩信道感知算法重建了系统的卷积复合信道.仿真结果表明,与传统的最小二乘法（Least Square,LS）相比,采用压缩感知理论的信道估计算法,能利用较少的导频信号获得很好的信道估计性能,提高了频谱利用率.

Sparse Channel Estimation Method Based on Compressed Sensing Multiple Relay Cooperation System

A compressed channel sensing method is proposed for multiple relay cooperative communication network. The Orthogonal Matching Pursuit （Orthogonal Matching Pursuit, OMP） compression algorithm has been used for time domain channel estimation. From the perspective of compressive sensing, and considering the channel characteristics in cooperative relay system with multiple relay and single antenna, a sparse channel model, employing the amplify-and-forward （AF） transmission scheme, is proposed. Moreover, the optimal measurement matrix is designed, and then the sparse representation of convolution channel is given. Finally, convolution channel impulse response was reconstructed with compressed sensing algorithm. According to the figures example, the cooperative channel exhibits an inherent sparse or sparse clustering structure. Hence, the proposed method can fully exploit the inherent sparse structure in cooperative channel. Simulation results confirm that the proposed method provide significant improvement in mean square error （MSE） performance or spectral efficiency comparing with the traditional linear channel estimation methods.