Signal denoising using hybrid slantlet transform based energy detector in cognitive radios

In this paper, signal denoising approach has been employed to enhance the detection performance of the energy detection (ED) technique via reducing the noise effects on the PU signal that is received by the secondary user (SU). Hybrid slantlet transform (HST) has been used to implement the proposed technique. HST is a mixed transform between discrete wavelet transform (DWT) and slantlet transform (ST). Simulation results compare the proposed technique for detection performance with a wavelet signal denoising technique, which was used for spectrum sensing, under AWGN and Rayleigh fading channels. Furthermore, the results show the obvious enhancement in the probability of detection (P_d) versus the signal to noise ratio (SNR) for our proposed technique in comparison with wavelet denoising technique. Moreover, HST has complexity less than that in DWT.