基于协进化粒子群优化的认知决策引擎  

Cognitive Decision Engine Based on Co-evolutionary Particle Swarm Optimization

作　　者：赵知劲[1] 张伟卫[1] 彭振[1] 徐春云[1] 

机构地区：[1]杭州电子科技大学通信工程学院,杭州310018

出　　处：《计算机工程》2011年第3期163-165,共3页Computer Engineering

基　　金：电科院预研基金资助项目(41101040102);浙江省大学生创新创业孵化基金资助项目(ZX100701060)

摘　　要：提出基于协进化理论的认知无线电参数跨层优化体系结构和基于协进化粒子群优化算法的认知决策引擎。通过协进化技术将高维粒子降低为低维粒子,提高算法收敛速度和收敛效率。对多载波系统进行仿真分析,结果表明,基于协进化粒子群优化算法的认知决策引擎在收敛速度和运行效率上优于基于二进制粒子群优化和量子遗传的认知决策引擎。A Cognitive Radio（CR） cross-layer optimization architecture based on co-evolutionary theory and cognitive decision engine based on co-evolutionary Particle Swarm Optimization（PSO） algorithm are proposed in this paper. For improving the convergence rate and efficiency, the proposed algorithm reduces the high dimensional particle to low dimensional particle by co-evolutionary theory. Simulation results for multi-carrier system show that the proposed cognitive decision engine in convergence rate and operational efficiency are better than the cognitive decision engine based on basic particle swarm optimization and based on quantum genetic.

关 键 词：认知无线电 决策引擎 粒子群优化 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]