Increase the End-to-end Throughput of a Cognitive Radio Chain by Considering the Primary Usage Pattern and Transmission Scheduling

In this paper, we investigated the end-to-end throughput of a chain in Cognitive Radio Networks (CRNs). We found that, the end-to-end throughput is dependant on both the primary usage patterns and the transmission scheduling scheme being used. In addition, to increase the end-to-end throughput of a Cognitive Radio (CR) chain, the scheduling scheme should be adjusted according to the primary usage patterns of the CR links in the chain. In the paper, firstly, we proposed an algorithm to approximate the achievable end-to-end throughput considering the primary usage patterns by abstraction and iteration. Then, a novel layered packets transmission scheduling scheme was proposed in attempt to realize the approximated end-to-end throughput. Finally, extensive simulations were conducted and results showed that, using proposed transmission scheduling scheme, the achievable end-to-end throughput of a CR chain is increased by considering the primary usage patterns and the final end-to-end throughput is close to the approximation.