Alternative Detectors for Spectrum Sensing by Exploiting Excess Bandwidth

The problems regarding spectrum sensing are studied by exploiting a priori and a posteriori in information of the received noise variance. First, the traditional Average Likelihood Ratio (ALR) detector is investigated under a Gamma distributed function as a channel noise, for the first time, under the availability of a priori statistical distribution about the noise variance. Then, two robust detectors are proposed using the exiting excess bandwidth to deliver a posteriori probability on the received noise variance uncertainty. The first proposed detector that is based on traditional ALR employs marginal distribution of the observation under available a priori and a posteriori of the received signal, while the second proposed detector employs the Maximum a posteriori (MAP) estimation of the inverse of the noise power. In addition, analytical expressions for the performance of the proposed detectors are obtained in terms of the false-alarm and detection probabilities. The simulation results exhibit the superiority of the proposed detectors over the traditional counterparts.