Power Control Algorithm for Cognitive Radio Based on Chaos Particle Swarm Optimization

Power control is one of key technologies for Cognitive Radio Networks (CRNs) since it can protect Primary Users (PUs) in the networks and guarantee Quality of Service (QoS) requirements for Second Users (SUs). In this paper, for an underlay CRNs in the scenario of the presence of multiple SUs and PUs, a novel power control approach with the objective to minimize total power consumption of SUs is proposed based on Chaos Particle Swarm Optimization (CPSO). The approach takes three constraints (minimum accepted SINR, maximum transmit power of SUs as well as maximum tolerated interference power for PUs) into account. The utility functions and constraints of original optimization problem are transformed into a related penalty function by CPSO approach. Simulation results indicate that the proposed CPSO algorithm can reduce total transmit power consumption, obtain faster convergence rate and improve searching quality compared with the standard Particle Swarm Optimization (PSO) and the Adaptation Particle Swarm Optimization (APSO) algorithms respectively.