Vertical handover algorithm based on multi-attribute and neural network in heterogeneous integrated network
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RESEARCH
Open Access
Vertical handover algorithm based on multi-attribute and neural network in heterogeneous integrated network Xiaonan Tan1, Geng Chen1* * Correspondence: gengchen@ sdust.edu.cn 1 College of Electronic and Information Engineering, Shandong University of Science and Technology, Qingdao 266590, China Full list of author information is available at the end of the article
and Hongyu Sun1,2
Abstract A novel vertical handover algorithm based on multi-attribute and neural network for heterogeneous integrated network is proposed in this paper. The whole frame of the algorithm is constructed by setting the network environment in which we use the network resources by switching between UMTS, GPRS, WLAN, 4G, and 5G. Each network build their own three-layer BP (Back Propagation, BP) neural network model and then the maximum transmission rate, minimum delay, SINR (signal to interference and noise ratio, SINR), bit error rate, user moving speed, and packet loss rate which can affect the overall performance of the wireless network are employed as reference objects to participate in the setting of BP neural network input layer neurons and the training and learning process of subsequent neural network data. Finally, the network download rate is adopted as prediction target to evaluate performance on the five wireless networks and then the vertical handover algorithm will select the right wireless network to perform vertical handover decision. The simulation results on MATLAB platform show that the vertical handover algorithm designed in this paper has a handover success rate up to 90% and realizes efficient handover and seamless connectivity between multi-heterogeneous networks. Keywords: Neural network, Multi-attribute, Vertical handover, Network selection
1 Methods/experimental In this paper, in order to solve the problem of users switching networks under the condition of heterogeneous integrated network, we propose a vertical handover algorithm of heterogeneous integrated network based on neural network framework. We introduce the BP neural network to participate in the construction and execution of this algorithm, and introduce the 5G network in the environment where UMTS, GPRS, WLAN, and 4G networks coexist to improve the scope of this algorithm. The type of three-layer BP neural network uses user moving speed, maximum transmission rate, minimum transmission delay, signal-to-interference plus noise ratio, bit error rate, and packet loss rate as inputs of the neural network in a heterogeneous network environment. The six network input factors are set the middle layer of the neural network according to the relevant empirical formula, we use the network download rate as the © The Author(s). 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons li
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