Performance improvements of cooperative spectrum sensing in cognitive radio networks with correlated cognitive users

In cognitive radio networks, secondary (unlicensed) users opportunistically access vacant frequency bands licensed to primary users. Spectrum sensing is the technique exploited to discover these unused bands. Cooperative spectrum sensing is the solution to problems that arise in the presence of fading and shadowing effects. Observations from the cooperative sensors are usually assumed independent, in order to simplify the analysis. Conversely, we consider the case of correlated observations and propose an innovative test for cooperative sensing, in order to improve the detection performance. Our test combines two different fusion rules at once (i.e. the OR and the Majority voting rules), recovering all those unlucky detection cases that are not sensed due to strong fading and shadowing. Our simulation results show the efficacy and effectiveness of our method for application to cooperative sensing in the presence of correlated cognitive users.