基于AOMP 重建的宽带频谱感知算法

为解决OMP(Orthogonal Matching Pursuit)算法在盲稀疏度情况下迭代终止条件带来的过匹配问题, 提出了一种AOMP(Adptive Orthogonal Matching Pursuit)算法。该算法在迭代过程中通过额外增加观测样本估算原始信号的重构误差, 通过寻找最小误差点自适应地确定最佳频谱重构对应的迭代次数。仿真结果表明, 该算法在
低信噪比下, 能有效地重构原始信号, 与已知信号稀疏度的重构效果相当。

Adaptive OMP Algorithm for Wideband Spectrum Sensing

In the case of blind signal sparsity, in order to solve the problem of over-fitting which is caused by the termination conditions of OMP(Orthogonal Matching Pursuit) algorithm, an AOMP(Adptive Orthogonal Matching Pursuit) algorithm is proposed. It estimates reconstruction error of the original signal through additional observations in the iteration process. It adaptively determines the iteration corresponding to the best spectrum reconstruction by finding the minimum error point. Simulation results show that the proposed adaptive OMP algorithm can effectively improve signal reconstruction performance under low SNR and the reconstruction effect is as good as the case of known signal sparsity.