Joint rate adaptation, channel assignment and routing to maximize social welfare in multi-hop cognitive radio networks

It is a fundamental goal but a tough task to fully utilize various resources in wireless networks. In multi-hop cognitive radio ad hoc networks (CRAHNs), it becomes more challenging due to primary users' uncertain activities, varying available channels, arbitrary traffic arrivals and rate requirements, and channel interference among multiple links. In this paper, we propose a Joint Rate adaptation, Channel assignment and Routing (J-RCR) approach to maximize social welfare by optimizing the resource utility in multi-channel multi-hop CRAHNs. Our J-RCR, jointly and dynamically adjusts the data transmission rate based on network states and rate requirements, assigns interference-free channels, and selects a route when a new data flow arrives or any primary node activates. The routing mechanism in our J-RCR considers the relay workload, the distance between the relay and the destination node, and co-channel interference to primary and secondary nodes. To show the efficiency of our J-RCR, we conduct both rigorous theoretical analysis and comprehensive performance evaluations. We derive the performance bound of our J-RCR on social welfare and compare it with the ideal approach that can precisely predict future network states. Numerical results further demonstrate that our J-RCR outperforms the related solutions (e.g., Robust Route, BPR and GPSR) in terms of social welfare, average throughput, network stability, and end-to-end delay.