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AUTHOR(S): Emeshili O. Joseph, Emmanuel Eronu, Evans Ashigwuike
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ABSTRACT This paper worked on Using Covariance Matrix and Fast Fourier Transform for Estimating Spectrum Hole Location in Cognitive Radio Network, Fast Fourier Transform (FFT) was used to split the Spectrum into sub-band channels. The paper adopted the use of Covariance Matrix in determining the actual range for the bounds. From the result it can be deduce that the areas where there are no signals at all are point where noise is prevalent, while thee point between 0 and 20 on the principal component axis are the point where you have high possibility of spectrum hole availability, the point between 20 and 30 on the principal axis is the point with high possibility of error false alarm.. 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. |
KEYWORDS Fast Fourier Transform, Covariance Matrix, Cognitive Radio, Spectrum, Ultra-Wide Band |
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Cite this paper Emeshili O. Joseph, Emmanuel Eronu, Evans Ashigwuike. (2020) Using Covariance Matrix and Fast Fourier Transform for Estimating Spectrum Hole Location in Cognitive Radio Network. International Journal of Communications, 5, 1-11 |
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