Using Convex Optimization For Detecting Spectrum Hole in Cognitive Radio Network

Convex Optimization for Spectrum Hole Detection in Cognitive Radio Network Using Tensor Analysis is aimed at developing an enhanced technique for detecting spectrum hole location, Fast Fourier Series Transform was used to split the Spectrum into sub-band channels. The paper adopted the use of Convex optimization in determining the actual range for the bounds, this was done by first formulation the problem where the range of the sub-band was established. Fast Fourier Transform was used to decompose the wideband spectrum to 64 Sub-band channels. the result of this shows that there exists a relationship between the covariance matrix and the sub-band energy. Two important properties of any square matrix are its trace, and its determinant. Analysis of Results obtained from Simulations shows that at signal-to-noise ratio (SNR) value of −10dB, spectrum holes were identified in 2 sub-band channels 13 and 53.