其于差分进化算法的认知无线电决策引擎

摘要

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 eoevolutionary particle swarm optimization algorithm.%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.