DocumentCode
3604722
Title
On Big Data Analytics for Greener and Softer RAN
Author
Chih-Lin I ; Yunlu Liu ; Shuangfeng Han ; Sihai Wang ; Guangyi Liu
Author_Institution
China Mobile Res. Inst., Beijing, China
Volume
3
fYear
2015
fDate
7/7/1905 12:00:00 AM
Firstpage
3068
Lastpage
3075
Abstract
Big data analytics applied to signaling, traffic, and wireless environment data in mobile communication networks can help realize autonomous network optimization and build big data-based network operation. In this paper, a signaling-based intelligent network optimization scheme is introduced and applied to the current mobile communication networks, such as 4G Long Term Evolution. In 5G era, big data analytics can help mine user and service requirements from the radio access network level, thus allowing a more efficient 5G design and operation. This paper illustrates how it would significantly facilitate local content provision, dynamical network and functionality deployment, user behavior awareness, fine-tuned network operation, and globally optimized energy saving solutions. It is anticipated that the big data-based 5G network design, and the operation will be greener and softer, and better meet the ever increasing user-centric requirements of mobile communication.
Keywords
4G mobile communication; 5G mobile communication; Big Data; Long Term Evolution; data analysis; environmental factors; telecommunication computing; 4G long term evolution; 5G era; autonomous network optimization; big data analytics; big data-based 5G network design; big data-based network operation; dynamical network; fine-tuned network operation; functionality deployment; globally optimized energy saving solutions; greener RAN; local content provision; mobile communication; mobile communication networks; radio access network level; signaling-based intelligent network optimization scheme; softer RAN; user behavior awareness; user-centric requirements; wireless environment data; 5G mobile communication; Behavioral science; Big data; Data analysis; Green design; Mobile communication; Wireless communication; 5G; Big data; big data; network operation; user behavior sensing; user-centric;
fLanguage
English
Journal_Title
Access, IEEE
Publisher
ieee
ISSN
2169-3536
Type
jour
DOI
10.1109/ACCESS.2015.2469737
Filename
7210136
Link To Document