C9. A New Wideband Spectrum Sensing Technique based on Compressive Sensing, Wavelet Edge Detection and Parallel Processing

In this paper parallel processing is employed to improve the performance of compressive sensing techniques for wideband spectrum edge detection. By taking different sets of random sub-Nyquist samples of the spectrum and processing them in parallel then combining the edges detected by using each set we can get a better estimate of the location of the occupied bands. The compressive sensing technique applied uses the wavelet transfrom to detect the spectrum edges. An implementation of multiscale wavelet sum in the form of matrix multiplication is presented in order to enable its application in a compressive sensing framework.