Intelligent access selection in cognitive networks: a fuzzy neural network approach

被引：0

作者：

Wang, Huiqiang ^{[1
,2
]}

Wang, Zhendong ^{[1
,2
]}

Feng, Guangsheng ^{[1
,2
]}

Lv, Hongwu ^{[1
,2
]}

Chen, Xiaoming ^{[1
,2
]}

Zhu, Qiang ^{[1
,2
]}

机构：

[1] College of Computer Science and Technology, Harbin Engineering University, Harbin 150001, China

[2] New Generation Networks and Information Assurance Engineering Laboratory, Harbin 150001, China

来源：

Journal of Computational Information Systems | 2012年 / 8卷 / 21期

关键词：

Particle swarm optimization (PSO);

D O I：

暂无

中图分类号：

学科分类号：

摘要：

Traditional single attribute access selection scheme can't meet the requirements of new service and user experience in cognitive networks. In this paper, we present a novel multi-attributes intelligent access selection scheme based on fuzzy neural network. By means of considering network side, terminal side and user preference as access elements, we get the optimal access network by using fuzzy neural network. Parameter learning makes the scheme adapt network environment variation dynamically. Simulation results show the advantages comparing to the existing schemes. © 2012 Binary Information Press.

引用

页码：8877 / 8884