Multiscale Discrete Wavelet Transform based Efficient Energy Detection for Wideband Spectrum Sensing

Abstract

In a wireless radio environment of cognitive radio, spotting of vacant spectrum of Primary user demands more efficient technique. The edge detection of sub-bands of the received signal spectrum is one such efficient technique of spectrum sensing achieved by Discrete Wavelet Transform (DWT). In low noise variance, the DWT based technique has a better detection performance, but as noise variance increases, the performance degrades. In this paper, blind energy detection spectrum-sensing approach is proposed with Multiscale DWT. Here depending on the noise variance two modified forms of DWT are proposed. When noise variance is less DWT Modulus Maxima (DWTMM) and for high noise variance DWT Moving window ESPIT Method (DWTMEM). The simulation of the proposed algorithm, shows efficient performance of the algorithm in terms of Probability of Detection PD, Probability of missed detection PM and the Probability of Error Pe in low and high noise variance environment.