基于DA优化模糊神经网络的异构无线网络接入选择算法

钱志鸿; 冯一诺; 孙佳妮; 王雪

doi:10.11959/j.issn.1000-436X.2020230

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基于DA优化模糊神经网络的异构无线网络接入选择算法

学术论文 | 更新时间：2024-06-05

- 基于DA优化模糊神经网络的异构无线网络接入选择算法
- Access selection algorithm for heterogeneous wireless network based on DA optimized fuzzy neural network
- 通信学报 2020年41卷第12期页码：118-127
- 作者机构：
  
  吉林大学通信工程学院，吉林长春 130012
- 作者简介：
  
  [ "钱志鸿（1957- ），男，吉林长春人，博士，吉林大学教授、博士生导师，主要研究方向为物联网、D2D、Wi-Fi、RFID等无线网络与通信技术。" ]
  [ "冯一诺（1995- ），女，吉林四平人，吉林大学硕士生，主要研究方向为异构无线网络。" ]
  [ "孙佳妮（1996- ），女，吉林长春人，吉林大学硕士生，主要研究方向为异构无线网络。" ]
  [ "王雪（1984- ），女，吉林白山人，博士，吉林大学副教授，主要研究方向为物联网与 D2D 通信技术。" ]
- 基金信息：
  
  国家自然科学基金资助项目(61771219);吉林大学基础科研基金资助项目(SXGJQY2017-9);吉林大学基础科研基金资助项目(2017TD-19)
- DOI：10.11959/j.issn.1000-436X.2020230
  中图分类号： TN92
- 网络出版日期：2020-12，
  
  纸质出版日期：2020-12-25
- 稿件说明：
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钱志鸿, 冯一诺, 孙佳妮, 等. 基于DA优化模糊神经网络的异构无线网络接入选择算法[J]. 通信学报, 2020,41(12):118-127.

Zhihong QIAN, Yinuo FENG, Jiani SUN, et al. Access selection algorithm for heterogeneous wireless network based on DA optimized fuzzy neural network[J]. Journal on communications, 2020, 41(12): 118-127.
钱志鸿, 冯一诺, 孙佳妮, 等. 基于DA优化模糊神经网络的异构无线网络接入选择算法[J]. 通信学报, 2020,41(12):118-127. DOI： 10.11959/j.issn.1000-436X.2020230.

Zhihong QIAN, Yinuo FENG, Jiani SUN, et al. Access selection algorithm for heterogeneous wireless network based on DA optimized fuzzy neural network[J]. Journal on communications, 2020, 41(12): 118-127. DOI： 10.11959/j.issn.1000-436X.2020230.

摘要

针对异构无线网络的接入选择问题，在考虑用户业务类型和网络状态的前提下，提出了一种基于蜻蜓算法优化模糊神经网络的异构无线网络接入选择算法。针对模糊神经网络收敛速度低的问题，利用蜻蜓算法对模糊神经网络第二层和第五层的隶属度函数参数进行寻优，以得到模糊神经网络隶属度函数参数的初始值。系统根据不同业务类型下用户对网络的偏好程度和网络的输出评分为用户选择最适合的网络。实验结果表明，利用蜻蜓算法优化模糊神经网络能够提高模糊神经网络的收敛速度，提高系统吞吐量，降低接入阻塞率，并在一定程度上减少切换次数。

Abstract

To solve the access selection problem of heterogeneous wireless network

an access selection algorithm based on dragonfly algorithm (DA) optimized fuzzy neural network (FNN) was proposed

considering the user’s business type and network state.In view of the low convergence speed of the fuzzy neural network

the dragonfly algorithm was used to optimize the membership function parameters of the second and fifth layers of the fuzzy neural network

so as to obtain the initial value of membership function parameters of the fuzzy neural network.The most suitable network was selected for the users according to their preference to the network and the output score of the network under different business types.The experimental results show that dragonfly algorithm optimization can improve the convergence speed of fuzzy neural network

improve system throughput

reduce blocking rate

and reduce switching times to some extent.

关键词

Keywords

references

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