Cognitive radio power allocation algorithm based on improved particle swarm optimization

Considering the interference power threshold of the primary users (PUs) in the cognitive radio network, the transmission rate limitation of the secondary users (SUs) and the signal to interference and noise ratio (SINR) requirement, an adaptive simulated annealing particle swarm optimization algorithm (ASAPSO) is proposed in this paper. According to the change of the fitness value, the adaptive control is used to adjust the particle swarm parameters dynamically, and improve the rules of the Metropoils criterion to generate new solutions. The optimal fitness value is selected by the simulated annealing idea. The simulation results show that the ASAPSO algorithm has achieved good optimization results in all aspects.