An Interval Type-2 Fuzzy Logic Based Framework for Call Admission Control in 4G Mobile Networks

Umoh, Uduak; Asuquo, Daniel E.; Eyoh, Imo

doi:10.5121/csit.2017.71003

Cited by 1 publication

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References 19 publications

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“…In [18][19], has been proposed a fuzzy-based CAC method to maintain the QoS level of ongoing calls and estimate the system performance using the shadow cluster concept (SCC). An integrated fuzzy logic based CAC for 4G networks in order to improve the QoS provision with the help of Karnik-Mendel (KM) and Wu-Mendel (WM) model and also compare type-1 fuzzy logic with type-2 fuzzy logic controller [20]. The fuzzy logic system has been a great deal of attention during last two decades and has achieved great success in many different real-world application like ATM networks, wireless mobile network, wireless sensor networks, and traffic congestion control.…”

Section: Previous Workmentioning

confidence: 99%

Neuro-Fuzzy based Call Admission Control for next Generation Mobile Multimedia Networks

2019

ijeat

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As the demand of the mobile users are increasing day by day, wireless/mobile multimedia networks still need advancement in terms of, reliable traffic performance, link availability, efficient bandwidth utilization, and user mobility, that can attain extremely consistent wireless communication and data transmission over the networks. Due to the emerging demand of multimedia services a high-speed network and call admission control (CAC) scheme is required, which not only guarantees the quality of services (QoS) for new and handoff calls but also results in optimum resource utilization in bursty traffic network environments. The main objective of this integrated neural fuzzy based CAC scheme is to improve QoS with decent resource allocation, such that it minimizes the probability of call dropping and call blocking in mobile multimedia networks. The proposed neural fuzzy CAC scheme is a hybrid approach that integrates the semantic rule ability of fuzzy logic (FL) controller and self-training capability of a neural network (NN) which is further enhanced to construct an efficient computational model for traffic control and fair radio resources allocation for new calls and handoff calls. The simulation results conclude that a neural fuzzy based CAC can achieve minimal call dropping probabilities and maximum resource utilization in high-speed networks as compared to fuzzy logic based CAC and conventional CAC or existing CAC schemes

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Section: Previous Workmentioning

confidence: 99%

Neuro-Fuzzy based Call Admission Control for next Generation Mobile Multimedia Networks

2019

ijeat

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An Interval Type-2 Fuzzy Logic Based Framework for Call Admission Control in 4G Mobile Networks

Abstract: This paper presents a technique to control based on interval type-2 fuzzy logic system (IT2FLS) of Mamdani fuzzy inference, employed to model connection admission control in Fourth Generation (4G) Networks in order to improve quality of service (QoS

Cited by 1 publication

References 19 publications

Neuro-Fuzzy based Call Admission Control for next Generation Mobile Multimedia Networks

Neuro-Fuzzy based Call Admission Control for next Generation Mobile Multimedia Networks

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