基于压缩感知的通信信号频谱检测方法

Spectrum detection method for communication signal based on compressed sensing

频谱感知是无线通信网络中提高频谱利用率的关键。针对现有通信信号频谱检测方法抗噪性低的问题,文中提出一种基于压缩感知的频谱检测方法。该方法首先利用压缩感知理论对通信信号的宽频带进行稀疏采样,其次采用改进的平滑范数重构算法对信号循环谱进行重构,提高了信号循环谱的重构性能,最后在循环谱域实现频谱检测。仿真实验结果表明,改进的平滑范数重构算法对信号的重构精度优于正交匹配追踪算法,压缩感知信号频谱检测算法的抗噪性优于传统能量检测算法。

Spectrum sensing is the key to improve spectrum utilization in wireless communication networks.To solve the problem of low noise resistance of existing spectrum detection methods for communication signals,a spectrum detection method based on compressed sensing is proposed in this paper.Firstly,compressed sensing theory is used to take sparsely samples form the broadband of communication signals.Then,the improved smoothing norm reconstruction algorithm is used to reconstruct the signal cyclic spectrum,what improves the performance of signal cyclic spectrum reconstruction.Finally,spectrum detection is implemented in the cyclic spectrum domain.The simulation results show that the improved smoothing norm reconstruction algorithm is better than the orthogonal matching pursuit algorithm for signal reconstruction,and the noise immunity of the compressed sensing signal spectrum detection algorithm is better than that of the traditional energy detection algorithm.