DocumentCode :
3613096
Title :
Intelligent network selection for data offloading in 5G multi-radio heterogeneous networks
Author :
Jin Wu ; Jing Liu ; Zhangpeng Huang ; Chen Du ; Hui Zhao ; Yu Bai
Author_Institution :
Shanghai Jiao Tong Univ., Shanghai, China
Volume :
12
fYear :
2015
fDate :
12/1/2015 12:00:00 AM
Firstpage :
132
Lastpage :
139
Abstract :
In next generation networks, multi-radio networks are emerging in order to deal with exponential data traffic increasing. Integrated Femto-WiFi (IFW) small cells have been introduced by 3GPP to offload data from cellular networks recently. These IFW cells are multi-mode capable (i.e., both licensed bands via cellular interface and unlicensed bands via WiFi interface). Therefore how to offload data effectively has become one of the most significant discussions in 5G Multi-Radio Heterogeneous Network. So far, most researches mainly focus on the generality of UEs, few attention has been paid to UEs´ individual requirements. Considering UE´s preference vary from individual to individual, in this paper, we present an UE preference-aware network selection scheme for mobile data offloading. It intelligently supports the distribution of heterogeneous classes of services, considers different types of UEs and delay-tolerant flows, and handles the mobility of UEs. The simulation results show the superiority of the proposed algorithm in user fairness, enhanced capacity and energy saving maximization.
Keywords :
5G mobile communication; energy conservation; femtocellular radio; next generation networks; radio networks; wireless LAN; 3GPP; 5G multiradio heterogeneous networks; cellular networks; energy saving; femto-WiFi small cells; intelligent network selection; mobile data offloading; multiradio networks; next generation networks; Batteries; Delays; Heterogeneous networks; IEEE 802.11 Standard; Interference; Mobile communication; Signal to noise ratio; LTE; WiFi; data offloading; multi-radio heterogeneous network;
fLanguage :
English
Journal_Title :
Communications, China
Publisher :
ieee
ISSN :
1673-5447
Type :
jour
DOI :
10.1109/CC.2015.7386161
Filename :
7386161
Link To Document :
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