一种基于RAMP算法的OFDM稀疏信道估计方法

针对OFDM稀疏信道估计需要信道稀疏度作先验条件的不足，将正则化自适应匹配追踪（RAMP）用于信道重建，可在信道稀疏度未知的情况下，自适应地调整候选集原子的个数，并利用正则化过程实现支撑集的二次筛选，逐步扩大支撑集，准确地估计出信道的冲激响应。仿真结果表明，该方法收敛速度快，估计效果好，有较好的应用价值。

An OFDM sparse channel estimation method based on regularized adaptive matching pursuit algorithm

To solve the problem that many existing sparse channel estimation methods require the sparsity of the channel impulse response as prior information,the regularized adaptive matching pursuit(RAMP) algorithm is used for channel reconstruction. Even if the sparsity of the channel is unknown, it can also recover the channel impulse response accurately by both the adaptive process which chooses the candidate set automatically and the regularized process which expands the final support. Simulation results show that the proposed algorithm has a good estimation performance and a high convergence speed and it is suitable for real application.