子空间投影的频谱感知算法研究

为了发现空间中的“频谱空洞”而加以利用以使频谱利用率最大化，频谱感知技术得到了广泛关注。已有基于特征矢量的频谱感知算法因涉及大量特征值分解运算导致算法运算量大，不适应实时检测。本文提出的频谱感知算法利用信号子空间和噪声子空间之间的正交性，将次用户接收信号分别投影到上述子空间，根据投影值的差异实现快速频谱感知。理论分析和仿真结果表明本文提出的算法与已有算法相比有效降低了运算量，检测性能不受噪声不确定度影响、不需要预知主用户先验知识和噪声方差，且低信噪比、小采样情况下有更优越的检测性能。 

The Research of Spectrum Sensing Method Based on Subspace Projection

Spectrum sensing technology had been widely concerned in order to find the available spectrum holes to improve the spectrum utilization. Because of the existing algorithms that based on the eigenvector involved a large number of eigenvalue decomposition, so they didn't fit for the real-time detection. Utilized the orthogonality between the signal subspace and the noise subspace, the proposed spectrum sensing algorithm projected the received signal of the secondary users(SU) on the two subspace and achieved fast spectrum perception based on the differences of the projection values. The theoretical analysis and the simulation results show that the proposed algorithm reduces the computational complexity effectively and it is robust to the noise uncertainty and need neither the prior knowledge of the primary user(PU) nor the noise variance. Furthermore, it can achieve a better detection performance with low SNR and small sampling.