A Hierarchical Routing Protocol based on Energy Consumption Weight Clustering Scheme for Cognitive Radio Networks

: In order to reduce the network congestion and data forwarding times, a hierarchical routing protocol based on energy consumption weight clustering scheme is proposed. Firstly, the concept of Energy Consumption Weight (ECW) is introduced. Then the clustering problem is modelled as a complete bipartite graph decomposition problem with maximum weights and a greedy clustering scheme based on ECW is presented to minimize the energy consumption of intra-cluster transmission. Subsequently, the Equal Reward Timeslots based Conjectural Multi-Agent Q-Learning (ERT-CMAQL) is applied to optimize routing and resource allocation in inter-cluster communication. Simulation results show that the proposed hierarchical routing scheme outperforms the flat routing protocol in terms of system energy consumption and packet transmission latency, and it effectively reduces the number of nodes involved in operation and decision-making in the multi-agent learning scheme when the size of network is large.