文中针对无线通信系统中稀疏信道估计算法进行研究,通过对比传统的基于训练序列的信道估计算法LS,对基于压缩感知的稀疏信道估计算法OMP进行分析。讨论了训练信号长度、信道稀疏度及噪声强度对整个估计性能的影响。在相同的实验条件下生成二维稀疏信号,从精确重构概率和信噪比方面对比了两种算法的性能。证明压缩感知方法可以有效的利用稀疏特性,在较短的训练序列情况下实现信道脉冲响应的精确估计。 In this paper, the sparse channel estimation algorithm in wireless communication system is studied. By comparing the traditional channel estimation algorithm LS based on training sequence, the sparse channel estimation algorithm OMP based on compressed sensing is analyzed. The effects of training signal length, channel sparsity and noise intensity on the whole estimation performance are discussed. Two-dimensional sparse signals are generated under the same experimental conditions, and the performances of the two algorithms are compared with the exact reconstruction probability and signal-to-noise ratio. It is proved that the compressive sensing method can effectively use the sparse features and realize the accurate estimation of channel impulse response with a short training sequence.