摘要
针对认知系统的工作参数调整问题,提出基于差分进化算法的认知无线电决策引擎算法.利用差分算法设置参数少、寻优能力强、不易于陷入局部最优等特点,实现认知系统根据工作环境变化和用户需求自适应调整工作参数.仿真结果表明,在多载波通信系统中,与协进化粒子群算法相比,提出的算法能增强系统的整体性能,提高系统的工作效率.
According to the problem of working parameter′s adjustment in cognitive radio system,this paper puts forward a cognitive radio decision engine based on the differential evolution algorithm.Using less parameters,good ability of finding the best,avoiding getting into local optimality,we can make the cognitive radio system adjust working parameters according to the change in working environment and the user requirement.The simulation results show that the algorithm in this paper performs better in the whole function and work efficiency of the system than coevolutionary particle swarm optimization algorithm.
出处
《智能系统学报》
北大核心
2012年第6期542-546,共5页
CAAI Transactions on Intelligent Systems
基金
国家自然科学基金资助项目(61175126)
中央高校基本科研业务费专项资金资助项目(HEUCFZ1209)
教育部博士点基金资助项目(20112304110009)
关键词
认知无线电
决策引擎
差分进化算法
多载波通信
协进化粒子群算法
cognitive radio
decision engine
differential evolution algorithm
multi-carrier communication
coevolutionary particle swarm
