Maximizing Throughput for Overlaid Cognitive Radio Networks

We consider a cognitive radio network in which a set of base stations make opportunistic spectrum access to support wireless subscribers within their covering cells. The spectrum of interest is divided into independent channels licensed to the primary users. Channel assignment and power control must be carried out in the cognitive network so that no excessive interference is caused to the primary users in the overlaid network. We are interested in the downlink channel assignment and power control problem for a cognitive radio network, with the objective of maximizing the total throughput of all secondary users. We first develop a mathematical model and present a Mixed Integer Linear Programming formulation, which is generally NP-hard. Subsequently, to obtain a suboptimal control scheme with lower complexity, we develop a distributed optimization algorithm that iteratively increases the overall cognitive radio network throughput. Through simulation results, we compare the performance of the distributed optimization algorithm with the optimal and validate its efficacy.