Real time blind spectrum sensing based in statistical processing of instantaneous magnitudes

Abstract

A novel method for real time blind spectrum sensing (RTBSS) based on statistical processing of instantaneous magnitude (SPIM) is presented. The proposal covers need to detect unknown signals in real time, with low implementation complexity and hardware resources, to minimize energy consumption in cognitive radio systems for wireless networks. The SPIM method uses the fundamentals of instantaneous magnitude signal processing (IMSP). By statistical processing the instantaneous values of the amplitude and phase magnitudes, the signal envelope is determined and automati threshold is set for the decision. The solution detects presence of unknown signals with only two samples and low signal to noise ratio (SNR). Have superior accuracy and performance compared to the energy detector (ED). In addition to detection this approach allows to characterize the temporal behavior, amplitude and frequency of the signal. The numerical results of its application in the detection of frequency hopping spread spectrum (FHSS) is presented.