基于分数阶小波的频谱感知算法

针对非平稳信号在低信噪比下使用能量感知算法感知效果差的问题,提出了一种基于分数阶小波的频谱感知算法。首先对接收信号进行分数阶小波变换达到能量聚集与去噪处理的目的,之后对重构信号进行能量感知。仿真结果表明,该算法相比于传统的能量感知算法以及基于小波变换的能量感知算法,可以提高在低信噪比下对非平稳信号的感知效果。在感知概率为0.3时,基于分数阶小波的能量感知算法比传统的能量感知算法和基于小波变换的能量感知算法分别提高了6 d B和2 d B的信噪比增益;在虚警概率恒为0.1时,基于分数阶小波变换的频谱感知算法的感知概率为0.867,明显高于传统能量感知算法0.287的感知概率和基于小波变换的频谱感知算法0.628的感知概率。

Spectrum Sensing Algorithm Based on Fractional Wavelet Transform

Spectrum sensing algorithm based on fractional wavelet transform was proposed to solve the problem that the performance of non-stationary signal energy detection was not satisfactory in low SNR scenarios .Firstly, the fractional wavelet transform is made for the received signal to gather the energy and undermine the noise,then the energy detection is done to the reconstructed signal. Both the theory analysis and the simulation results show that this algorithm could improve the performance of non-stationary signal energy detection in low SNR scenarios.When the sensing rate is 0.3, spectrum sensing algorithm based on fractional wavelet transform gets 6dB and 2dB SNR gain compared with the traditional algorithm and algorithm based on wavelet transform; In the condition that the constant false alarm rate is 0.1,the sensing rate of spectrum sensing algorithm based on fractional wavelet transform is 0.867,which is obviously higher than the 0.287 of traditional algorithm and the 0.628 of algorithm based on wavelet transform.