Bayesian Approach to Spectrum Sensing for Cognitive Radio Applications
In this paper, the authors address the spectrum sensing task of cognitive radio from Bayesian Detection (BD) perspective. They first show that BD essentially simplifies to classical Energy Detection (ED) under Gaussian signal assumption but the threshold setting has more degrees of freedom to optimize the sensing performance, e.g., against given spectrum utilization. Then they propose a novel BD based algorithm where the sample energy is calculated iteratively, and the odds ratio is used to quantify the measurement reliability. Depending on the reliability, either a hard decision is forced or the algorithm progresses to accumulate more sample energy.