Accumulative Interference Modeling for Distributed Cognitive Radio Networks

Abstract

A Cognitive Radio (CR) network should be able to sense its environment to adapt its communication so that it can utilize unused licensed spectrum without interfering with incumbent users. Properly modeling the expected interference from the entire CR network is therefore very important to effectively protect these incumbent users. We model the accumulative interference generated from a large-scale CR network and investigate how the CR network density affects the sensing requirements of the CRs to meet an interference constraint. More specifically, our model considers the impact of discrete network topology, the impact of imperfect sensing and the impact of collisions when the CR uses a distributed channel access scheme. We then apply our model to a CR network based on the IEEE 802.11 standard. We show that the collisions occurring frequently in these networks only have a small on the sensing requirements to protect the incumbent network.