Vertical Handover Decision based on RBF Approach for Ubiquitous Wireless Networks

被引:0
作者
Kunarak, Sunisa [1 ]
机构
[1] Srinakharinwirot Univ, Dept Elect Engn, Nakhonnayok 26120, Thailand
来源
2016 INTERNATIONAL CONFERENCE ON PLATFORM TECHNOLOGY AND SERVICE (PLATCON) | 2016年
关键词
heterogeneous; neural network; next generation wireless networks; radial basis function; vertical handover decision;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Next generation wireless networks are integrated the multiple wireless access technologies in order to provide the users with the best connection. The vertical handover decision algorithm is an important role to guarantee the seamless mobility in single mobile terminal. In this paper, we apply the radial basis function neural network (RBFNN) for the decision making process in vertical handover based on received signal strength, mobile speed and monetary cost metrics. The simulation results indicate that the proposed approach outperforms in reducing the unnecessary handover and connection dropping but increasing the grade of service with comparing the other two methods as threshold and back propagation neural network
引用
收藏
页数:4
相关论文
共 50 条
  • [41] A sequential learning algorithm based on adaptive particle filtering for RBF networks
    Xi, Yanhui
    Peng, Hui
    Chen, Xiaohong
    NEURAL COMPUTING & APPLICATIONS, 2014, 25 (3-4) : 807 - 814
  • [42] Nonlinear modeling of MCFC stack based on RBF neural networks identification
    Shen, C
    Cao, GY
    Zhu, XJ
    SIMULATION MODELLING PRACTICE AND THEORY, 2002, 10 (1-2) : 109 - 119
  • [43] A PAES based optimization of RBF networks to predict overhead feeder failures
    Cochenour, G
    Simon, J
    Nag, S
    Odeh, O
    Poupe, J
    Pahwa, A
    PROCEEDINGS OF THE 8TH JOINT CONFERENCE ON INFORMATION SCIENCES, VOLS 1-3, 2005, : 1726 - 1729
  • [44] A Mesh-Based Approach for RBF-Based Planar Shape Deformation
    Hu X.
    Cai T.
    Zhang H.
    Wang L.
    Zhou Y.
    Jin Y.
    Jisuanji Fuzhu Sheji Yu Tuxingxue Xuebao/Journal of Computer-Aided Design and Computer Graphics, 2020, 32 (11): : 1742 - 1752
  • [45] Vertical handover algorithm based on multi-attribute and neural network in heterogeneous integrated network
    Xiaonan Tan
    Geng Chen
    Hongyu Sun
    EURASIP Journal on Wireless Communications and Networking, 2020
  • [46] Vertical handover algorithm based on multi-attribute and neural network in heterogeneous integrated network
    Tan, Xiaonan
    Chen, Geng
    Sun, Hongyu
    EURASIP JOURNAL ON WIRELESS COMMUNICATIONS AND NETWORKING, 2020, 2020 (01)
  • [47] Wireless based object tracking based on neural networks
    Derr, Kurt
    Manic, Milos
    ICIEA 2008: 3RD IEEE CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS, PROCEEDINGS, VOLS 1-3, 2008, : 308 - +
  • [48] LinUCB-Based Handover Algorithm for Throughput Maximization in Heterogeneous Cellular Networks
    Chen, Yu-Shu
    Huang, Zhi-Hong
    Tsai, Ming-Jer
    2023 IEEE 20TH CONSUMER COMMUNICATIONS & NETWORKING CONFERENCE, CCNC, 2023,
  • [49] Representing 3D shapes based on implicit surface functions learned from RBF neural networks
    Lu, Guoyu
    Ren, Li
    Kolagunda, Abhishek
    Wang, Xiaolong
    Turkbey, Ismail B.
    Choyke, Peter L.
    Kambhamettu, Chandra
    JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION, 2016, 40 : 852 - 860
  • [50] A Novel Reliability Analysis Approach With Collaborative Active Learning Strategy-Based Augmented RBF Metamodel
    Wei, Yanxu
    Bai, Guangchen
    Song, Lu-Kai
    IEEE ACCESS, 2020, 8 : 199603 - 199617