基于循环平稳特征的频谱检测

频谱检测是实现认知无线电的前提。从认知无线电的核心功能出发,分析了循环平稳特征检测抗噪方面的性能以及影响其检测性能的主要因素,通过理论推导和仿真验证了噪声对检测性能的影响,提出了一种基于小波变换的频谱检测方案。该方案通过小波变换将接收到的信号进行主信号与噪声分离,并对信号进行重构,提高了频谱检测的性能。仿真结果表明,在低信噪比情况下,采用基于小波变换的频谱检测方法,无论是系统的频谱检测虚警率还是频谱检测漏检率都有了显著的降低。

Spectrum Sensing Based on Cyclostationary Characteristics

Spectrum sensing is the prerequisite to cognitive radio （CR）.From the core function of CR,this paper analyzes the anti-AWGN （additive white Gaussian noise） robustness of cyclostationary characteristic detection,and the main factors which affect the performance of spectrum sensing.Theoretical deduction and simulation indicate the AWGN effect on the sensing performance.An improved spectrum sensing scheme based on wavelet transform is proposed.The prime signal is separated from the received signal and reconstructed by the wavelet transform,thus improving the performance of spectrum sensing.The simulation shows that,in the case of low signal to noise ratio,both the probability of false alarm and the probability of missing are reduced obviously.