An adaptive Particle Swarm Optimization algorithm for multi-user cognitive radio system

In Cognitive Radio (CR) context, the second user (SU) can achieve an optimization with multiple objectives in the decision-making process by making the radio parameters adaptive to the complex wireless environment, and share the spectrum resources with other CR users under the radio regulatory policy. It is well recommended that each SU should consume the radio resources appropriately to meet its Quality of Service (QoS) and unnecessary excessive consumption demands. Compared with the Genetic Algorithm (GA), the Particle Swarm Optimization (PSO) algorithm is applied to the decision-making process of adjusting radio parameters in the sequential and simultaneous modes for the multi-user CR system in this paper. And the simulation results show that the PSO-based algorithm outperforms than the GA in convergence rate for the system.