NDLI: Traffic Offloading in 5G Heterogeneous Networks using Rank based Network Selection

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Traffic Offloading in 5G Heterogeneous Networks using Rank based Network Selection

Content Provider	Semantic Scholar
Author	Gachhadar, Anand Qamar, Faizan Dong, Dhawa Sang Majed, Mohammed B. Hanafi, Effariza Amiri, Iraj Sadegh
Copyright Year	2019
Abstract	The exponential growth of mobile data traffic and a limited number of spectrum resources has been a big challenge for cellular network providers, henceforth traffic offloading has become one of the most critical issues especially in 5G Heterogeneous Networks (HetNets). Further, network selection plays a vital role for traffic offloading in a cellular network to maintain Quality of Service (QoS), increasing offloading efficiency and throughput. In order to efficiently utilize spectral resources, a Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) algorithm is proposed to be used for ranking a candidate network. The proposed algorithm helps in alleviating the spectrum shortage by offloading the data traffic over Wi-Fi network using unlicensed spectrum. In this work, analysis of the performance of the proposed system model through simulation of an analytical framework has been made. The results have been accumulated in terms of cumulative handover, throughput, the extent of equilibrium & offloading efficiency with respect to residence time and the number of Wi-Fi Access Points (AP’s). Analysis proves that the proposed algorithm improves the equilibrium extent and throughput as compared to traditional Load balancing (LB) and SDN based LB mechanisms. It also shows that offloading efficiency is highly improved over Wi-Fi density and residence time.
Starting Page	9
Ending Page	16
Page Count	8
File Format	PDF HTM / HTML
DOI	10.25103/jestr.122.02
Volume Number	12
Alternate Webpage(s)	http://www.jestr.org/downloads/Volume12Issue2/fulltext21222019.pdf
Alternate Webpage(s)	https://doi.org/10.25103/jestr.122.02
Language	English
Access Restriction	Open
Content Type	Text
Resource Type	Article

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