当前位置: X-MOL 学术Comput. Intell. Neurosci. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
A User-Oriented Intelligent Access Selection Algorithm in Heterogeneous Wireless Networks
Computational Intelligence and Neuroscience Pub Date : 2020-11-24 , DOI: 10.1155/2020/8828355
Gen Liang 1 , Xiaoxue Guo 1 , Guoxi Sun 1 , Jingcheng Fang 1
Affiliation  

A heterogeneous wireless network (HWN) contains many kinds of wireless networks with overlapping areas of signal coverage. One of the research topics on HWNs is how to make users choose the most suitable network. This paper designs a user-oriented intelligent access selection algorithm in HWNs with five modules (input, user preference calculation, candidate network score calculation, output, and learning). Essentially, the input module uses a utility function to calculate the utility value of the judgment parameter; the user preference calculation module calculates the weight of the judgment parameter using the fuzzy analysis hierarchy process (FAHP) approach; the candidate network score calculation module calculates the network score through a fuzzy neural network; the output module calculates the error between the actual output value and the expected output value; and the learning module corrects the parameter of the membership function in the fuzzy neural network structure according to the error. Simulation results show that the algorithm proposed in this paper can enable users to select the most suitable network according to service characteristics and can enable users to obtain higher gains.

中文翻译:

异构无线网络中面向用户的智能访问选择算法

异构无线网络(HWN)包含信号覆盖范围重叠的多种无线网络。HWN的研究主题之一是如何使用户选择最合适的网络。本文设计了具有五个模块(输入,用户偏好计算,候选网络分数计算,输出和学习)的HWN中面向用户的智能访问选择算法。本质上,输入模块使用效用函数来计算判断参数的效用值。用户偏好计算模块采用模糊层次分析法(FAHP)计算判断参数的权重。候选网络得分计算模块通过模糊神经网络计算网络得分;输出模块计算实际输出值与预期输出值之间的误差;学习模块根据误差校正模糊神经网络结构中隶属函数的参数。仿真结果表明,本文提出的算法可以使用户根据业务特点选择最合适的网络,并可以使用户获得更高的收益。
更新日期:2020-11-25
down
wechat
bug