Abstract
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.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.