Cross-layer performance analysis for cognitive radio network with a random transmission protocol in presence of sensing errors

In this paper, we develop a queueing analytic model that incorporates imperfect sensing in order to measure different performance parameters e.g., collision probability, packet loss probability and queueing delay. This analytic model is useful for call admission control (CAC) decision in cognitive radio network (CRN) when there is a certain sensing error as well as certain quality of service (QoS) requirements for both primary and cognitive radio (CR) users. Using our developed model, we compare the performance of a random transmission protocol with that of the traditional deterministic transmission protocol. Selected numerical results show that for given QoS requirements, the random transmission protocol can support higher number of CR users than the traditional deterministic transmission protocol when there is a certain probability of sensing error.