摘要
根据信号循环平稳谱的特征,研究在低信噪比环境下的频谱检测问题,提出一种基于循环谱能量的自适应判决门限频谱检测算法。该算法融合能量检测与循环平稳特征检测的机理,以信号的循环谱能量为检测统计量,加权合并虚警率与检测率,准确估计循环谱特征值,构建了具有噪声自适应能力的频谱检测判决门限。仿真结果表明,该算法可以在低信噪比环境下有效地完成频谱检测,克服了噪声波动对频谱检测性能的影响,对不同调制主信号的感知具有稳健性。与最大—最小特征值算法和盲检测算法相比,该算法分别改善了信噪比4dB和8dB。
Focused on the characteristic of cyclostationary spectrum of signal and the spectrum sensing in low sig-nal-to-noise ratio,an adaptive decision threshold spectrum sensing algorithm was proposed,which combines cyclosta-tionary spectrum sensing with energy detection.By weighting the sum of probabilities of detection and false alarm,esti-mating the eigenvalues of the cyclostationary spectrum,the algorithm provides an adaptive decision threshold which could differentiate the primary signal from the background noise.The simulation results show that the algorithm could perform well in low signal-to-noise ratio and remove the effect of noise uncertainty on the spectrum sensing.It outper-forms maximum-minimum eigenvalue and blind detection with 4dB and 8dB respectively in signal-to-noise ratio,and has robustness to different modulated primary signal.
出处
《通信学报》
EI
CSCD
北大核心
2011年第11期95-103,共9页
Journal on Communications
基金
国家自然科学基金资助项目(60872002
61071086)~~
关键词
认知网络
频谱检测
循环平稳
加权
自适应门限
cognitive network
spectrum sensing
cyclostationary
weighting
adaptive threshold
