Guaranteed opportunistic scheduling in multi-hop cognitive radio networks

Abstract

Cognitive radio networks enable opportunistic sharing of bandwidth/spectrum. In this paper, we introduce optimal control and scheduling algorithms for multi-hop cognitive radio networks to maximize the throughput of secondary users while stabilizing the cognitive radio network subject to collision rate constraints required by primary users. We show that by employing our proposed optimal algorithm, the achievable network throughput can be arbitrarily close to the optimal value. To reduce complexity, we propose a class of feasible suboptimal algorithms that can achieve at least a fraction of the optimal throughput. In addition, we also analyze the optimal algorithm in the fixed-routing scenario and deduce the corresponding lower-bound of average end-to-end delay across a link set.