Blind cooperative parametric spectrum sensing with distributed sensors using local average power passing

This work deals with the issue of blind cooperative

spectrum sensing using distributed sensors with large-scale fading.

We first investigate the Friedman-test-based nonparametric

detector and analyze its performance. Due to the operations of

instantaneous power passing and ranking, the nonparametric

detector has relatively high-sensing overhead and computational

complexity. To overcome these drawbacks, we then propose a

blind cooperative parametric detector for which only local average

power passing is needed and instantaneous power ranking is

avoided. Compared with the nonparametric detector, the parametricdetectordeliversbetterperformancewithmuch

lower overhead

and complexity. The detection probability and false alarm probability

of the parametric detector are analyzed, and its decision

threshold is derived. Simulation results demonstrate the superior

performance of the parametric detector, compared with the energy

detector and the eigenvalue-based detectors in the literature.