ECTI TRANSACTIONS ON COMPUTER INFORMATION TECHNOLOGYVolume 15, No. 03, Month DECEMBER, Year 2021, Pages 303 - 312
Neuro-fuzzy architecture for handover decision making in emerging heterogeneous networks
Saida Driouache, Najib Naja, Abdellah Jamali
Abstract Download PDFIn 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.
Heterogeneous Network, Seamless Vertical Handover, Articial Neural Network, Fuzzy Logic, Reinforcement Learning, Quality of Service