A frequency domain two-stage spectrum sensing method based on SVM
frequency domain detection, noise estimation, spectrum sensing, support vector machine, two-stage sensing
IEEE International Conference on Electro Information Technology
Spectrum sensing is one of the key technologies of cognitive radio. Based on noise characteristics estimation and support vector machine (SVM) technology, this paper proposed a frequency domain two-stage spectrum sensing method to improve sensing accuracy under low signal-to-noise ratio scenarios with low system complexity and high generalization ability. In the slow sensing stage, the frequency-domain data is used as the feature data of the SVM and the noise parameters (the variance and the mean) are estimated. In the fast sensing stage, only the variance and the mean of the input signals are used as the feature data of the SVM. The simulation results show that the average detection error probability of the proposed method could be as low as 5% when the signal-to-noise ratio is -15dB.
Original Publication Date
DOI of published version
UNI ScholarWorks, Rod Library, University of Northern Iowa
Zhai, Xuping; Nie, Yong; Ye, Xiang; Wang, Tao; and Nie, Hong, "A frequency domain two-stage spectrum sensing method based on SVM" (2017). Faculty Publications. 837.