Relative Study of Bayesian Approach for Spectrum Sensing in C.R.

Abstract: The spectrum sensing problem is one of the most challenging problem in cognitive radio systems. Cognitive radio automatically detects available channels in wireless spectrum, then consequently changes, its transmission or reception parameters to allow additional concurrent wireless communications in a given spectrum band. Many detection methods are used for spectrum sensing. In this paper, we discussed Bayesian approach for maximum spectrum utilization. We described optimal detector structure for MPSK modulated primary signal. We also described its suboptimal detector in both low and high SNR regime. Through approximations, it is found that, in low SNR regime, for MPSK signals, the suboptimal detector is that the energy detector as well as for BPSK signals, the suboptimal detector is that the energy detector on the real part. A relative study between Bayesian detector and other spectrum sensing algorithm for cognitive radio is presented. The performance analysis of Bayesian detector is shown in terms of probabilities of detection, false alarm, selection of detection threshold.

Keywords: Cognitive radio (CR), spectrum sensing, energy detector, Bayesian detector, matched filter detection, wavelet based detector.