An Intelligent Fuzzy Neural Call Admission Control Mechanism for Guaranteed QoS in Heterogeneous Wireless Networks

The Call admission control (CAC) is a Radio Resource Management (RRM) technique that plays instrumental role in ensuring the desired Quality of Service (QoS) to the users working on different applications with diversified QoS requirements in next generation wireless networks (NGWN). This paper proposes an Analytical system model and the stochastic activity network (SAN) based performance model and an intelligent fuzzy neural model for call admission control for a multi class traffic based Next Generation Wireless Networks. The performance study is made between the analytical model and SAN model .The paper proposes an intelligent Fuzzy Neural call admission control (FNCAC) scheme - an integrated CAC module that combines the linguistic control capabilities of the fuzzy logic controller and the learning capabilities of the neural networks to make the CAC decision. The simulation results are optimistic and indicate that the proposed FNCAC algorithm achieves minimal call blocking probability and performs better when compared to Fuzzy logic based CAC and Conventional CAC methods.

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