Energy-Efficient Contention-Aware Channel Selection in Cognitive Radio Ad-Hoc Networks
In this paper, the authors propose a novel contention-aware channel selection algorithm that focuses on throughput and energy efficiency improvement in Cognitive Radio Ad-Hoc Networks (CRAHNs). Specifically, they study the operation and performance of a Secondary Network (SN) in a scenario where other non-cooperating CRAHNs are also using the primary resources. They 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 their proposed algorithm.