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Volume 42 Issue 3
Mar.  2020
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Bin MA, Shangru LI, Xianzhong XIE. A Hierarchical Vertical Handover Algorithm Based on Fuzzy Logic in Heterogeneous Wireless Networks[J]. Journal of Electronics & Information Technology, 2020, 42(3): 629-636. doi: 10.11999/JEIT190190
Citation: Bin MA, Shangru LI, Xianzhong XIE. A Hierarchical Vertical Handover Algorithm Based on Fuzzy Logic in Heterogeneous Wireless Networks[J]. Journal of Electronics & Information Technology, 2020, 42(3): 629-636. doi: 10.11999/JEIT190190

A Hierarchical Vertical Handover Algorithm Based on Fuzzy Logic in Heterogeneous Wireless Networks

doi: 10.11999/JEIT190190
Funds:  The Major Project of Science and Technology Research of Chongqing Education Commission (KJZD-M201900602), The Key Project of Science and Technology Research of Chongqing Education Commission (KJZD-K201800603), The Foundation Research and Advanced Exploration Project of Chongqing (cstc2018jcyjAX0432), The Doctoral Startup Fund of Chongqing University of Posts and Telecommunications (A2015-16), The Key Project of Chongqing Graduate Education&Teaching Reform (yjg182024), The Project of Chongqing Graduate Higher Education&Teaching Reform (193095)
  • Received Date: 2019-03-27
  • Rev Recd Date: 2019-06-13
  • Available Online: 2019-07-03
  • Publish Date: 2020-03-19
  • In the heterogeneous wireless networks, the parameter weight is difficult to determine for the vertical handover algorithm considering the parameters of the network and the user, at the same time, the vertical handover algorithm based on fuzzy logic has high complexity. Considering this problem, a hierarchical vertical handover algorithm based on fuzzy logic is proposed. Firstly, the Received Signal Strength (RSS), bandwidth and delay are input into the first-level fuzzy logic system. Combining with the rule adaptive matching, the QoS fuzzy value is inferred, and the network is initially filtered by the QoS fuzzy value to obtain the candidate network set; Then, the second-level fuzzy logic system is triggered by the trigger mechanism, and the QoS fuzzy value, network load rate and user access cost of the candidate network are input into the second-level fuzzy logic system. At the same time, the output decision value is obtained by combining the adaptive rule matching, so as to select the best access network. Finally, the experimental results show that the algorithm can guarantee the network performance while reducing the time cost of the system.

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