A statistical approach to spectrum sensing using bayes factor and p-Values

Abstract

The sensing methods with multiple receive antennas  in the Cognitive Radio (CR) device, provide a promising solution for reducing the error rates in the detection of the Primary User (PU) signal. The received Signal to Noise Ratio at the CR receiver is enhanced using the diversity combiners. This paper proposes a statistical approach based on minimum Bayes factors and p-Values as diversity combiners in the spectrum sensing scenario. The effect of these statistical measures in sensing the spectrum in a CR environment is investigated. Through extensive Monte Carlo simulations it is shown that this novel statistical approach based on Bayes factors provides a promising solution to combine the test statistics from multiple receiver antennas and can be used as an alternative to the conventional hypothesis testing methods for spectrum sensing. The Bayesian results provide more accurate results when measuring the strength of the evidence against the hypothesis.