A novel approach to Wavelet Transform-based Edge Detection in wideband spectrum sensing

Cognitive Radio network has been suggested to alleviate the problem of spectrum scarcity. For the operation of Cognitive Radio devices, detection of possible spectrum opportunities (also known as spectrum holes) reliably and efficiently is an important step. One way to do this is to use Wavelet Transform based Edge Detection methods. There has been much advancement in this direction, leading to development of Wavelet Transform Modulus Maxima (WTMM), Wavelet Transform Multiscale Sum (WTMS) and Wavelet Transform Multiscale Product (WTMP) algorithms. Each of these techniques has its merits and demerits. In this paper, we have proposed a novel method which has simplicity and computation efficiency of WTMM along with the error performance comparable to that of WTMS and WTMP. Error performances for the proposed method using Gaus1 and db1 wavelets, for different Signal-to-Noise ratios, have been studied and db1 is shown to be the better choice.