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Call admission control (CAC), a resource management function, is required to regulate network access to provide the required levels of QoS to emerging services in Fourth Generation (4G) mobile networks. However, CAC is one of the challenging issues for quality of service (QoS) due to imprecise, uncertain and inaccurate measurements of network data. Although a type-1 fuzzy system (T1FLS) can handle the uncertainties related to imprecise data, it cannot adequately handle new problems posed by the complex nature of data traffic and diversity of the QoS requirements of data users. This is because T1FLS is characterized by precise membership functions. This study presents an intelligent CAC controller for a 4G network using interval type-2 fuzzy logic (IT2FL) for providing guaranteed QoS requirements. The IT2FLS with fuzzy membership functions can fully cope with uncertainties associated with such dynamic network environments by raising its accuracy for better performance. The Karnik–Mendel (KM) iterative algorithm and Wu-Mendel (WM) approach are explored for computing the centroid and to derive inner and outer-bound sets for the type-reduced set of IT2FS respectively. The study also implements a T1FLS – CAC for comparison with the KM and WM methods. The empirical comparison is made on the designed system with synthetic datasets. Simulation and analyses of results indicate that IT2FLS-CAC using the WU approach achieves minimal call blocking probability and provides high performance in CAC decision making with a more reduced root mean square error (RMSE) than IT2FLS-CAC using KM and IT1FLS approaches.
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