Spectrum allocation optimization for Cognitive Radio networks using Binary Firefly Algorithm

Abstract

Cognitive Radio is a promising technology to improve the spectrum utilization and ease the shortage of spectrum resources, and the quality of spectrum allocation directly determines the spectrum utilization. In order to explore a better solution for spectrum allocation in cognitive radio networks, a spectrum allocation model based on graph theory is established to describe the problem in this paper, and the novel Binary Firefly Algorithm is used to facilitate the spectrum allocation optimization, so as to maximize the cognitive network spectrum utilization and secondary user fair within the interference constraint. Finally, the simulation results demonstrate that the proposed spectrum allocation algorithm can perform better than a set of existing algorithms in network reward, secondary user's fairness and convergence.