  Cluster structure in cognitive radio networks facilitates cooperative
spectrum sensing, routing and other functionalities. The unlicensed channels,
which are available for every member of a group of cognitive radio users,
consolidate the group into a cluster, and the availability of unlicensed
channels decides the robustness of that cluster against the licensed users'
influence. This paper analyses the problem that how to form robust clusters in
cognitive radio network, so that more cognitive radio users can get benefits
from cluster structure even when the primary users' operation are intense. We
provide a formal description of robust clustering problem, prove it to be
NP-hard and propose a centralized solution, besides, a distributed solution is
proposed to suit the dynamics in the ad hoc cognitive radio network. Congestion
game model is adopted to analyze the process of cluster formation, which not
only contributes designing the distributed clustering scheme directly, but also
provides the guarantee of convergence into Nash Equilibrium and convergence
speed. Our proposed clustering solution is versatile to fulfill some other
requirements such as faster convergence and cluster size control. The proposed
distributed clustering scheme outperforms the related work in terms of cluster
robustness, convergence speed and overhead. The extensive simulation supports
our claims.
