Cooperative Quickest Spectrum Sensing in Cognitive Radios with Unknown Parameters

In this paper, cooperative quickest spectrum sensing for cognitive radios is studied. Various cooperative schemes are considered based on the cumulative sum (CUSUM) algorithm, for different memory and communication constraint scenarios. The optimal CUSUM statistics are derived for each of these cooperative sensing schemes in the noisy channel scenario. In practice, due to unknown parameters in the distribution of the observations, the CUSUM-based approaches are not directly applicable to cognitive radios. Therefore, we propose to apply a linear test, which does not require any prior knowledge or estimates of the unknown parameters, for quickest spectrum sensing of cognitive radios. We derive linear-based CUSUM statistics for different cooperative sensing scenarios. The proposed approach results in fast and simple algorithms for cooperative quickest detection with unknown parameters, while maintaining a performance close to that of the perfectly known parameter schemes.