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The advancement in the digital world has led to the increase in the demand for the radio spectrum, which eventually has led to the spectrum scarcity and underutilization of it. The under-utilization of allocated spectrum is due to the fixed spectrum allocation to the primary user. This problem can be overcome by an intelligent radio network called Cognitive Radio (CR). The CR helps in detecting the idle spectrum in the radio environment and thus allocating it to the Secondary Users (SU). Cognitive Radio provides reliable service to the secondary user by preventing interference between secondary and primary user. Spectrum Sensing plays the vital role in the Cognitive Radio to sense the idle spectrum and allocate the vacant spectrum for SU. The major and prominent spectrum sensing methods include Energy Based Detection (EBD), Matched Filter Detection (MFD), Cyclostationary Feature Detection (CFD), Covariance Based Detection (CBD) and Wavelet Based Detection (WBD). This paper discusses Cyclostationary based detection method exploit the periodic statistics and spectral correlation of the received signal to detect the presence of the primary signal in the channel. In wavelet based spectrum sensing wavelet transform technique is applied on the received signal to determine the edges in the spectrum of the signal.

Enhanced spectrum sensing based on Cyclo-stationary Feature Detection (CFD) in cognitive radio network using Fixed &amp; Dynamic Thresholds Levels

Enhanced spectrum sensing based on Cyclo-stationary Feature Detection (CFD) in cognitive radio network using Fixed & Dynamic Thresholds Levels