The simulation study of entropy-based signal detector over fading channel

Entropy-based signal detector has been proposed recently to counteract noise uncertainty in cognitive radio networks. The time-domain and frequency-domain entropy-based detector are introduced, and detailed simulations are produced to study the detection and classification performance of the two detectors over Rayleigh and Rice fading channel. The results of computer simulation show that the frequency-domain entropy-based detector is robust in fading channel, but it can not be used to classify different modulation signals. In contrast, the time-domain entropy-based detector deteriorates rapidly at low signal-to-noise ratios (SNR), but it can classify different modulation signals in medium SNR domain.