基于压缩感知的OFDM稀疏信道估计算法

The Estimation Algorithm of OFDM Sparse Channel Based on Compressed Sensing

针对OFDM通信系统信道具有稀疏性且稀疏度未知的特点,提出了一种稀疏度自适应压缩感知信道估计算法,即变步长自适应压缩采样匹配追踪算法。该算法首先采用变步长匹配测试的估计方法对信道稀疏度进行预估,然后通过压缩采样匹配追踪改善估计结果,若压缩采样匹配追踪不能成功重构,则通过弱选择选取新的原子,渐进增加信号稀疏度。仿真结果表明:相较于传统自适应压缩感知重构算法,提出的VSACSMP算法具有更好的信道估计性能。

The channels of orthogonal frequency division multiplexing(OFDM)communication systems are sparse but the sparsity is unknown.Aiming at this characteristic,a sparsity adaptive channel estimation algorithm for compressive sensing,i.e.a variable step adaptive compressive sampling matching pursuit(VSACSMP)algorithm was proposed.In this algorithm,the estimation method of variable step size matching test was firstly adopted to estimate the channel sparsity.Then,the compressive sampling matching pursuit was used to improve the estimation result.If recovery was unsuccessful with the compressive sampling matching pursuit,weak selection would be utilized to choose new atoms and increase the signal sparsity gradually.The simulation results demonstrated that compared to traditional adaptive recovery algorithms for compressive sensing,the proposed VSACSMP algorithm could deliver better channel estimation performance.