Comparison between Adaptive Double-Threshold Based Energy Detection and Cyclostationary Detection Technique for Cognitive Radio Networks

Cognitive radio is the key technology for future wireless communication. Spectrum sensing is one of the most important functions in cognitive radio (CR) applications. It involves the detection of primary user (PU) transmissions on a preassigned frequency band. PU licensed band can be sensed via appropriate spectrum sensing techniques. In this paper, we propose an energy detector utilizing adaptive double-threshold (ED_ADT) for spectrum sensing. Using simulations, a comparative analysis of the Adaptive Double-Threshold Based Energy Detection and Cyclostationary feature detection technique has been carried out in terms of probability of detection alarm (Pd), and total error probability (Pe). Numerical results show that proposed ED_ADT scheme outperforms cyclostationary feature detection by 44.1 % at - 8 dB signal to noise ratio (SNR) in terms of probability of detection alarm (Pd).