This bands with minimum power are again scanned

This transform decomposes the signal into mutually orthogonal set of wavelets 40. This is different from the Continuous Wavelet Transform (CWT). Wavelets provide a better way for spectrum sensing. This method is easier and  reliable than that of conventional energy detector 41,42. Discrete Wavelet Transform (DWT) is a transform technique to analyze the signals. Here the signal are represented in terms of coef?cients of scaling and wavelet functions ?(t) and ?(t) respectively. Decomposing a signal by means of wavelet transform is same as passing the signal through a high pass ?lter and low pass ?lter 43. The algorithm can be summarized as: • Perform DWT and  the  power in each band is calculated. • Calculate Power to bandwidth ratio. • In case the estimated R is relatively high, bands with minimum power are  directly categorized as unoccupied where R is  the ratio of minimum of normalized power in occupied bands to the maximum of normalized power in unoccupied bands. • In case the estimated R is relatively low, arrange the bands in ascending order and the bands with minimum power are again scanned using some other better spectrum sensing techniques. Another method includes WATRAB,  a novel based wavelet transform spectrum sensing algorithm 44. The very basic idea used here is that the signals of PU  carry a very limited amount of information, where as the noise forms the major part. Carefully select a wavelet transform method, to exploit such a difference so that a very different transform result is obtained. Wavelet transformation algorithm is to be applied in determining whether the original received wave from antenna holds signals or not ie H1 or H0 (refer eqn(1) and (2)), as shown in ?g 11.Fig. 11. General architecture of WATRABHere, we use a mixer  and a combination of low pass ?lters and daubechies db4 wavelet transform is then applied. The signals remains  nearly unaffected after the transform, whereas noises are  intensely affected. Wavelet transform is suf?cient for identi?cation of information for low frequency but not for high frequency band. The Wavelet Packet Transform (WPT), another version of DWT identifies information in high frequency band also in comparison to Wavelet Transform (WT). WPT is an ideal tool for handling non stationary time variable signal. Energy detection algorithm based on WT for spectrum sensing is shown in ?g 12 45.