摘要
认知无线电(Cognitive Radio,CR)技术通过智能的频谱管理来解决频谱资源"短缺"问题,它能够感知到授权用户的空闲频谱,并有效地加以利用,从而减少与授权用户的冲突。现有无线电参数调整策略无法根据环境变化和用户需求进行智能调整,认知引擎中的决策方法能够解决该问题。遗传算法(Genetic Algorithm,GA)和二进制粒子群算法是实现认知引擎决策的典型算法,在对2种算法进行了介绍之后,仿真比较了2种算法在性能方面的差异。
Cognitive radio technology can make the best use of radio spectrum through intelligent spectrum management. With the ability of sensing the idle spectrum resources, it can effectively preclude the possibility of conflict. The existing radio parameters adjus- ting strategy can not adjust the radio parameters intelligently either according to the change of the environment or the user demand. The decision-making method for the cognitive engine provides a new approach. The genetic algorithm and the particle swarm optimization are the typical methods to realize the decision-making for the cognitive engine. The simulation presents the differences between these two methods in the performance.
出处
《无线电工程》
2013年第2期58-60,64,共4页
Radio Engineering
关键词
认知无线电
认知引擎
遗传算法
二进制粒子群算法
cognitive radio
cognitive engine
genetic algorithm
binary particle swarm optimization
