Abstract: In order to solve the spectrum allocation problem in cognitive wireless network,a spectrum allocation algorithm based on multigroup evolution and particle swarm optimization hybrid was proposed in this paper.It uses graph coloring model,and makes multiple populations evolve independently by genetic algorithm in order to improve global search capability of populations first.Then it selects the optimal particle of each individual population as a particle particle swarm optimization,and controls the direction of the initial velocity of each particle to speed up the convergence rate.Finally,the maximum benefit and the fairness among users were taken as the optimization goal to compare with genetic algorithm and particle swarm optimization by simulation experiment.The experimental results show that the algorithm is better than genetic algorithm and particle swarm optimization in convergence speed,cognitive user access fairness and total system efficiency.

Key words: Cognitive radio network,Spectrum allocation,Particle swarm optimization algorithm,Genetic algorithm,System benefit