Energy-efficient contention-aware channel selection in Cognitive Radio Ad-Hoc Networks

In this paper, we propose a novel contention-aware channel selection algorithm that focuses on throughput and energy efficiency improvement in Cognitive Radio Ad-Hoc Networks (CRAHNs). Specifically, we study the operation and performance of a Secondary Network (SN) in a scenario where other non-cooperating CRAHNs are also using the primary resources. We prove that a channel categorization of the idle channels based on their contention level and the selection of the less contented ones can result in up to 70% improvement in throughput and up to 68% improvement in energy efficiency. Simulation results are presented for the performance evaluation of our proposed algorithm.