摘要
针对传统蚁群算法在认知无线电频谱分配中搜索时间长、信息素更新效率低等问题,提出了一种新的多态蚁群算法的认知无线电频谱分配方案。改变了传统蚁群算法单一信息素的调控机制,引入侦察蚁并给效益值较高的路径标记信息;以效益值为标准设置多态蚁群的各项指标;利用多态规则进行路径选点并更新信息素;最后与传统蚁群算法就最大平均网络效益和最大比例公平网络效益进行仿真对比。实验结果表明了多态蚁群算法的高效性和优越性。
Aimed at the problems that spectrum allocation based on traditional ant colony algorithm in cognitive radio is long in search time and is low in efficiency on pheromone update,a new cognitive radio allocation scheme based on polymorphic ant colony algorithm is proposed in this paper. The scheme changes the regulation mechanism of the single pheromone in the traditional ant colony algorithm, introduces scouts to the algorithm, and marks information in higher benefit value path. And the scheme takes benefit value as a standard to set the index of polymorphic ant colony algorithm. In addition, the polymorphism rule is applied in path selecting and pheromone updating. Finally, Polymorphic Ant Colony Algorithm （PACA） is compared with traditional Ant Colony Algorithm （ACA） on Max-Sum-Reward and Max-Pro- portional-Fair. The experiment results show that the proposed spectrum allocation algorithm has a high ef- ficiency and superiority.
出处
《空军工程大学学报（自然科学版）》
CSCD
北大核心
2016年第2期58-63,共6页
Journal of Air Force Engineering University(Natural Science Edition)
基金
陕西省自然科学基金(2014JM2-6106)
关键词
认知无线电
频谱分配
多态蚁群算法
信息素更新
cognitive radio
spectrum allocation
polymorphic ant colony algorithm
pheromone update
作者简介
张婧怡（1991-），女，山西运城人，硕士，主要从事认知无线电研究．E-mail：zhangjy_1991@163．com.
