On-Demand Multicast Routing in Cognitive Radio Mesh Networks

Cognitive radio networks (CRN) have emerged as a promising, yet challenging, solution to enhance spectrum utilization, thanks to the technology of cognitive radios. In this work, we consider the multicast routing and channel allocation problem in cognitive radio mesh networks. Due to the potential heterogeneity in channel availability among mesh routers (MRs) and the frequency switching latency, end-to-end delay and throughput degradation could be subject to a significant increase. We propose an on-demand multicast routing and channel allocation algorithm that takes channel heterogeneity and switching latency into consideration. The algorithm aims at reducing the end-to-end delay, and at the same time reducing the degradation of throughput using a dynamic programming approach.