Opportunistic call admission control for wireless broadband cognitive networks

Wireless Broadband Cognitive Networks (WBCN) are new trend to better utilization of spectrum and resources. However, in multiservice WBCN networks, call admission control (CAC) is a challenging point to effectively control different traffic loads and prevent the network from being overloaded and thus provide promised quality of service. In this paper, we propose a CAC framework and formulate it as an optimization problem, where the demands of both WBCN service providers and cognitive subscribers are taken into account. To solve the optimization problem, we developed an opportunistic multivariate CAC algorithm based on a joint optimization of utility, weighted fairness, and greedy revenue algorithms. Extensive simulation results show that, the proposed call admission control framework can meet the expectations of both service providers and subscribers in wireless broadband cognitive networks.