Stochastic geometric analysis of the uplink throughput in cognitive radio cellular networks

This paper investigates the uplink throughput of Cognitive Radio Cellular Networks (CRCNs). As oppose to traditional performance evaluation schemes which mainly adopt complex system level simulations, we use the theoretical framework of stochastic geometry to provide a tractable and accurate analysis of the uplink throughput in the CRCN. By modelling the positions of User Equipments (UEs) and Base Stations (BSs) as Poisson Point Processes (PPPs), we analyse and derive expressions for the link rate and the cell throughput in the Primary (PR) and Secondary (SR) networks. The expressions show that the throughput of the CRCN is mainly affected by the density ratios between the UEs and the BSs in both the PR and SR networks. Besides, a comparative analysis of the link rate between random and regular BS deployments is concluded, and the results confirm the accuracy of our analysis. Furthermore, we define the cognitive throughput gain and derive an expression which is dominated by the traffic load in the PR network.