一种改进的基于压缩感知的稀疏信道估计算法

分析了突发信号的结构特征，提出了一种改进的基于压缩感知的稀疏信道估计方法。在信道初始估计中，利用前导伪随机序列的自相关特性，估计信道的路径时延，以此初始化稀疏重构算法，增加了信道估计的先验信息。在后续处理中，利用前一时刻已估计出的信道信息，跟踪估计当前时刻的信道信息。仿真证明，与最小二乘估计算法、正交匹配追踪算法和分离近似稀疏重构算法相比，本文提出的算法提高了信道估计的精度，降低了接收系统的误码率。

Improved Sparse Channel Estimation Algorithm Based on Compressive Sensing

After investigating the structural features of burst signal, an improved sparse channel estimation algorithm is proposed based on compressive sensing. In the initial estimation, the autocorrelation property of preamble pseudo-random sequence is utilized to estimate the path delay of channel. Then the sparse recovery with the delay is initialized, which takes advantage of the prior information of channel estimation. In the follow-up channel estimation, the algorithm tracks the current channel information through the channel information estimated in the previous moment. Simulations indicate that the proposed algorithm improves channel estimation precision, and decreases the bit error rate of receiver system, when compared with the lease square estimation algorithm, orthogonal matching pursuit algorithm and sparse reconstruction by separable approximation algorithm.