Aggregate Interference and Capacity-Outage Analysis in a Cognitive Radio Network using Cooperative Sensing

This paper presents a study on interference caused by Secondary Users (SUs) due to miss-detection in a cognitive network over Nakagami fading channels. Interference analysis shows that aggregate interference power from SUs can be closely approximated as a Gamma random variable. The probabilistic properties of aggregate interference power are investigated for non-cooperative, OR1 and Maximum Likelihood (ML) cooperative sensing techniques. Then, closed-form expressions for capacity-outage probability of the Primary User (PU) are derived to study the benefits of cooperative sensing in mitigating interference. Simulation results are also provided to verify the developed analytical models. It is shown that ML sensing offers lower interference and hence better PU capacity-outage probability than OR sensing.