As the traditional clustering algorithm cannot be applied to the cognitive ad hoc network for dynamic channels

a distributed clustering algorithm based on the similarity of channels has been proposed.Firstly the channel similarity between nodes will be calculated and the probability of a node within the cluster will be estimated using an adapted EM algorithm.Then by using minimum cut algorithm in graph theory

the optimal clustering results will be obtained with maximum similarity within a cluster and minimum similarity between clusters.Finally

a coordination mechanism to synchronize the global clustering information has been proposed.Throughout

these processes are evenly distributed

without relying on a common control channel.The simulation results show that the proposed algorithm can change the cluster structure according to the dynamic nature of channels

increase the intra-cluster common channels

and effectively reduce inter-cluster common channels to lower the interference.