Topology Reconfiguration in Cognitive Radio Networks Using Ant Colony Optimization

Considering the inevitable trends for heterogeneous network convergence and self-adaptation ability, Cognitive Radio Network (CRN) concept has been proposed with some essential characteristics to achieve global end-to-end goals. CRNs are composed of cognitive devices which have the capable of changing network configurations based on the dynamic environment. This capability opens up the possibility of designing flexible and dynamic topology control strategies with the purpose of opportunistically reusing idle licensed spectrum and effectively achieving data transmission. This work focuses on the problem of designing effective topology reconfiguration algorithm to offer optimal routing solutions. We analyze the topology control for CRNs finding the topology problem can be formularized as a multi-objective optimization problem. In this context, as an intelligent technology for complex multi-objective optimization, the ant colony optimization (ACO) techniques are applied in topology reconfiguration for optimal decision making in this paper. Finally, the reconfiguration algorithm is simulated, and the simulation results with detailed are analyzed.