Multi-Attribute Vertical Handover Decision-Making Algorithm in a Hybrid VLC-Femto System

2017 ◽  
Vol 21 (7) ◽  
pp. 1521-1524 ◽  
Author(s):  
Shufei Liang ◽  
Yuexia Zhang ◽  
Bo Fan ◽  
Hui Tian
Author(s):  
Saida DRIOUACHE ◽  
Najib Naja ◽  
Abdellah Jamali

In emerging heterogeneous networks, seamless vertical handover is a critical issue. There must be a trade-off between the handover decision delay and accuracy. This paper’s concern is to contribute to reliable vertical handover decision making that makes a trade-off between complexity and effectiveness. So, the paper proposes a neuro-fuzzy architecture that joints the capacity of learning of the artificial neural networks with the power of linguistic interpretation of the fuzzy logic. The architecture can learn from experience how executing a handover to a particular access network affects the quality of service. Simulation results reveal that this architecture is fast, enhances the overall performance and reliability better than the fuzzy logic-based approach.


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