Spectrum allocation of cognitive radio network based on artificial physics optimization

Abstract

To study the spectrum allocation problem based on graph coloring model in cognitive radio network, an algorithm to maximize total network revenue is proposed, which is based on artificial physics optimization because of its NP-based features. In artificial physics optimization algorithm, the solution of spectrum allocation problem is mapped into a particle with mass. It establishes the relation between particle mass and its fitness value, and defines the virtual force between the particles by the law of gravity so that the entire group can move to the better direction and achieve population optimization. The detailed spectrum allocation process is given and the particle position updating equation is improved because of its binary coding features. Simulation results show that the proposed algorithm can better maximize network revenue.