Cognitive Radio Spectrum Sensing Based on Wavelet Denoising
Spectrum sensing which detects the presence of primary user in a licensed spectrum is a fundamental problem in cognitive radio. Sensing accuracy is the most important factor to determine the performance of cognitive radio. Due to the existence of noise, many algorithms are subject to some limitations for application. In this paper, a novel spectrum sensing method is proposed based on the wavelet denoising. An important scenario for the different characterization of signal and noise in the wavelet multi-scale analysis is the case where the receiver is able to distinguish the signal and noise. This method does not require any prior information about the primary signal, and also has a good spectrum sensing performance at a low SNR.
KeywordsCognitive Radio Primary User Cognitive Radio User Wavelet Shrinkage Wavelet Denoising
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