基于区间二型模糊神经网络的垂直切换算法

doi:10.12263/DZXB.20200850

电子学报 ›› 2021, Vol. 49 ›› Issue (5): 928-935.DOI: 10.12263/DZXB.20200850

基于区间二型模糊神经网络的垂直切换算法

马彬^1,2, 王双双^1,2, 陈海波^1,2

1. 重庆邮电大学计算机科学与技术学院, 重庆 400065;
2. 重庆邮电大学计算机网络与通信技术重点实验室, 重庆 400065

收稿日期:2020-08-06 修回日期:2020-12-04 出版日期:2021-05-25
- 通讯作者:
- 王双双
- 作者简介:
- 马彬男,1978年出生,四川人,博士,重庆邮电大学教授,主要研究方向为认知无线电网络、异构无线网络、不确定智能算法等. E-mail:mab_cqupt@sina.com
- 基金资助:
- 重庆市自然科学基金 (No.CSTC2018jcyjAX0432）; 重庆市教委科学技术研究计划重大项目 (No.KJZD-M201900602）; 重庆市教委科学技术研究重点项目 (No.KJZD-K201800603）

Vertical Handover Algorithm Based on Interval Type-2 Fuzzy Neural Network

MA Bin^1,2, WANG Shuang-shuang^1,2, CHEN Hai-bo^1,2

1. Institute of Computer Science and Technology, Chongqing University of Post and Telecommunication, Chongqing 400065, China;
2. Chongqing Key Laboratory of Computer Network and Communication Technology, Chongqing 400065, China

Received:2020-08-06 Revised:2020-12-04 Online:2021-05-25 Published:2021-05-25
- Corresponding author:
- WANG Shuang-shuang
- Supported by:
- Natural Science Foundation of Chongqing Municipality, China (No.CSTC2018jcyjAX0432); Science and Technology Research Major Program of Chongqing Municipal Education Commission (No.KJZD-M201900602); Science and Technology Research Key Program of Chongqing Municipal Education Commission (No.KJZD-K201800603)

摘要/Abstract

摘要： 在超密集异构无线网络中,针对传统垂直切换算法无法同时描述网络状态的模糊性和随机性,导致网络性能得不到有效提升的问题,提出一种基于区间二型模糊神经网络的垂直切换算法.重构了两阶段判决算法:在网络预筛选阶段,定义了历史接入率,结合当前候选网络集的数目设置阈值.根据接收信号强度和剩余可用带宽,对用户接收范围内的所有网络进行初步筛选; 再在垂直切换判决阶段,将剩余候选网络的时延,丢包率以及误码率作为区间二型模糊神经网络的输入,利用前馈神经网络的结构完成模糊逻辑推理,经训练之后计算得到输出判决值,从而选择最佳接入网络.实验结果表明,该算法能在保证时间开销较低的同时,有效降低切换决策的错误概率,减少切换失败和切换次数,提升网络总吞吐量.

关键词: 区间二型模糊神经网络, 超密集, 垂直切换, 模糊性, 随机性

Abstract: In the ultra-dense heterogeneous wireless network, the traditional vertical handoff algorithm can not describe the fuzziness and randomness of the network state at the same time, so the network performance can not be effectively improved. A vertical handoff algorithm based on the interval type II fuzzy neural network is proposed to solve above problem. A two-stage decision system is reconstructed: in the network’s prescreening stage, the historical access rate is defined to set the threshold combine with the number of current candidate network sets. According to the received signal strength and the remaining available bandwidth, all the networks within the user’s receiving range are preliminarily screened; The delay, packet loss rate and bit error rate of the remaining candidate networks are taken as the inputs of the it2fnn in the vertical handoff decision stage. The fuzzy logic reasoning is completed by using the structure of the feedforward neural network, and the output decision value is calculated after the training, and the optimal network is selected. The simulation results show that the algorithm can ensure low time consumption, and effectively reduce the error probability of handoff decision and the number of handoff failures and handoff times. Meanwhile, it can improve the total throughput of networks.

Key words: interval type II fuzzy neural network, ultra-dense, vertical handoff, fuzziness, randomness

中图分类号:

TN915

马彬, 王双双, 陈海波. 基于区间二型模糊神经网络的垂直切换算法[J]. 电子学报, 2021, 49(5): 928-935.

MA Bin, WANG Shuang-shuang, CHEN Hai-bo . Vertical Handover Algorithm Based on Interval Type-2 Fuzzy Neural Network[J]. Acta Electronica Sinica, 2021, 49(5): 928-935.

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基于区间二型模糊神经网络的垂直切换算法

Vertical Handover Algorithm Based on Interval Type-2 Fuzzy Neural Network

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