Delay performance modeling and analysis in clustered cognitive radio networks

Cognitive radio networks (CRNs) emerge as a promising solution for overcoming the shortage and inefficient use of bandwidth resources by allowing secondary users (SUs) to access the primary users' (PUs) channels so long as they do not interfere with them. The random availability of the PU channels makes the delay analysis of the SU, which accesses the channels opportunistically, plays a crucial role as a quality of service measure. In this paper, we model and characterize the total average delay the SUs experience in a CRN. The cognitive radio system is modeled as a discrete-time queueing system. The availability of the N independent and identical PU channels is modeled as a two states Markov chain. Our contributions in this paper is that we provide a solid performance evaluation that gives a closed-formula for the two delay components experienced by the SUs, namely the waiting delay and the service delay. We derive the waiting delay using the residual time concept. We characterize the service time distribution by considering the buffered-slotted-ALOHA systems. We also provide numerical results to show the effects of the analysis on the CRN design.