Wavelet Transform Analysis of Dual-Stage Spectrum Sensing on Fractal Dimension Topology

In cognitive radio (CR) networks, spectrum sensing is crucial. Wideband spectrum sensing (WSS) techniques are used in CR to locate the temporarily vacant frequency bands, enabling dynamic spectrum access (DSA). In this paper, wavelet transform as well as collaborative spectrum detection approaches are utilized for wideband dynamic spectrum accessing CR. The Discrete Wavelet Transform (DWT) method, along with Sevcik’s Fractal Dimension (SFD) are combined to create a selection method that enables the centralized collaborative spectrum detector to sense the spectrum bands and send the sensed data to the fusion center, where the received, data is analyzed to determine whether the spectrum is vacant or occupied. The proposed methodology is effective when applied to simulated signals with signal-to-noise ratios (SNR) greater than 0dB, as well less than 0dB.