Computing Capacity and Connectivity in Cognitive Radio Ad-Hoc Networks
The authors present some unique challenges in Cognitive Radio Ad-Hoc Networks (CRAHNs) that are not present in conventional single-channel or multi-channel wireless ad-hoc networks. They first briefly survey these challenges and their potential impact on the design of efficient algorithms for several fundamental problems in CRAHNs. Then, they describe their recent contributions to the capacity maximization problem and the connectivity problem. The capacity maximization problem is to maximize the overall throughput utility among multiple unicast sessions; the connectivity problem is to find a connected sub-graph from the given cognitive radio network where each secondary node is equipped with multiple radios.