A Wideband Spectrum Sensing Based on ESPRIT Algorithm

Abstract

Spectrum sensing is a prerequisite for cognitive dio. This paper proposes a wideband spectrum sensing method based on ESPRIT algorithm for detecting active channels. In this method, it detects the occupied channels directly according to the relationship between the Fourier transform (FT) of the multicoset sampler's output sequences and the active channels, which can save a lot of sampling rate and reduce the computational complexity. And the performance of this method is evaluated by calculating the detection probabilities for different numbers of samples and different signals to noise ratios (SNRs). The simulation results show that the proposed method performs well in low SNR and less data samples.