An Adaptive Vertical Handover Algorithm Based on Artificial Neural Network in Heterogeneous Wireless Networks

Bin MA; Shangru LI; Xianzhong XIE

doi:10.11999/JEIT180534

Volume 41 Issue 5

Apr. 2019

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Bin MA, Shangru LI, Xianzhong XIE. An Adaptive Vertical Handover Algorithm Based on Artificial Neural Network in Heterogeneous Wireless Networks[J]. Journal of Electronics & Information Technology, 2019, 41(5): 1210-1216. doi: 10.11999/JEIT180534

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Bin MA, Shangru LI, Xianzhong XIE. An Adaptive Vertical Handover Algorithm Based on Artificial Neural Network in Heterogeneous Wireless Networks[J]. Journal of Electronics & Information Technology, 2019, 41(5): 1210-1216. doi: 10.11999/JEIT180534

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An Adaptive Vertical Handover Algorithm Based on Artificial Neural Network in Heterogeneous Wireless Networks

doi: 10.11999/JEIT180534

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

Funds: The National Natural Science Foundation of China (61471076, 61601070), The Foundation and Advanced Research Program of Chongqing (cstc2016jcyjA0455), The Foundation Research and Advanced Exploration Project of Chongqing (cstc2018jcyjAX0432), The Doctoral Start-up Fund of Chongqing University of Posts and Telecommunications (A2015-16)

Received Date: 2018-05-30
Rev Recd Date: 2019-01-30

Available Online: 2019-02-25

Publish Date: 2019-05-01

Abstract

Abstract

Current research on Vertical HandOver algorithm based on Artificial Neural Network (ANN-VHO) has a poor service adaptability and high computational complexity. Considering this problem, an adaptive vertical handover algorithm based on artificial neural network is proposed. Firstly, according to the Received Signal Strength (RSS) obtained by the terminal, a method of thresholding is used to select a candidate network set. Secondly, in terms of the different types of services classified in this paper, the parameters are normalized and adaptively selected; Thirdly, the selected parameters are input into the artificial neural network to choose the best access network from the candidate network. Finally, the experimental results show that the algorithm can reasonably select the handover network according to the user's service type, reduce the handover blocking rate and lower the time complexity of the algorithm.
- Heterogeneous wireless networks,
- Type of service,
- Adaptive selection,
- Neural network

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References(16)

References

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