Adaptive spectrum sensing algorithm based on cyclostationary spectrum energy

Abstract

Focused on the characteristic of cyclostationary spectrum of signal and the spectrum sensing in low signal-to-noise ratio,an adaptive decision threshold spectrum sensing algorithm was proposed,which combines cyclostationary spectrum sensing with energy detection.By weighting the sum of probabilities of detection and false alarm,estimating 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 outperforms maximum-minimum eigenvalue and blind detection with 4dB and 8dB respectively in signal-to-noise ratio,and has robustness to different modulated primary signal.

Keywords

• cognitive network;spectrum sensing;cyclostationary;weighting;adaptive threshold