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Fuzzy-Logic Based Call Admission Control in 5G Cloud Radio Access Networks with Pre-emption
Sigwele, Tshiamo ; Pillai, Prashant ; Alam, Atm S. ; Hu, Yim Fun
Sigwele, Tshiamo
Pillai, Prashant
Alam, Atm S.
Hu, Yim Fun
Publication Date
2017-09-21
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© 2017 The Authors. This is an Open Access article distributed under the
Creative Commons CC-BY license (https://creativecommons.org/licenses/by/4.0/legalcode)
Peer-Reviewed
Yes
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openAccess
Accepted for publication
2017-08-31
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Abstract
Fifth generation (5G) cellular networks will be comprised of millions of connected devices like wearable devices, Androids, iPhones, tablets and the Internet of Things (IoT) with a plethora of
applications generating requests to the network. The 5G cellular networks need to cope with such
sky-rocketing tra c requests from these devices to avoid network congestion. As such, cloud radio
access networks (C-RAN) has been considered as a paradigm shift for 5G in which requests from
mobile devices are processed in the cloud with shared baseband processing. Despite call admission
control (CAC) being one of radio resource management techniques to avoid the network
congestion, it has recently been overlooked by the community. The CAC technique in 5G C-RAN has
a direct impact on the quality of service (QoS) for individual connections and overall system
e ciency. In this paper, a novel Fuzzy-Logic based CAC scheme with pre-emption in C-RAN is proposed. In this scheme, cloud bursting technique is proposed to be used during congestion, where
some delay tolerant low-priority connections are pre-empted and outsourced to a public cloud with
a penalty charge. Simulation results show that the proposed scheme has low blocking probability
below 5%, high throughput, low energy consumption and up to 95% of return on revenue.
Version
Published version
Citation
Sigwele T, Pillai P, Alam AS et al (2017) Fuzzy-Logic Based Call Admission Control in 5G
Cloud Radio Access Networks with Pre-emption. EURASIP Journal on Wireless Communications and Networking. 2017: 157.
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Article