Efficient Multi-Radio Selections for Device-to-Device in Wireless Cellular Networks

Recently, Cisco has predicted that there will be an explosive growth of the mobile data traffic such that video streaming will account for nearly 70% total demand. To foresee such heavy burden in each eNB, Device-to-Device (D2D) technology is a promising solution to do data offloading while maintain...

Full description

Saved in:
Bibliographic Details
Published in2016 International Computer Symposium (ICS) pp. 142 - 147
Main Authors Te-Chuan Chiu, Ya-Ju Yu, Shih-Fan Chou, Yu-Ting Tsai, Ai-Chun Pang
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.12.2016
Subjects
Online AccessGet full text

Cover

Loading…
More Information
Summary:Recently, Cisco has predicted that there will be an explosive growth of the mobile data traffic such that video streaming will account for nearly 70% total demand. To foresee such heavy burden in each eNB, Device-to-Device (D2D) technology is a promising solution to do data offloading while maintain acceptable service quality. In this paper, we first target on two different D2D interfaces, Wi-Fi and LTE direct, and propose an efficient multi-radio selection scheme by dynamic programming design approach for video streaming in wireless cellular networks. To minimize total LTE radio resource usage, we leverage D2D technology and adaptively select the different transmission links to meet QoS requirement of each user. Since the data rate of Wi-Fi transmission link is hard to correctly evaluate, we conduct a series of experiments under realistic interference environment to measure the actual capacity of Wi-Fi transmission links. Besides, we also study related works about general capacity predict model to take both measurement and mathematical model into consideration for designing our solution. The simulation results show that the proposed scheme can significantly reduce the LTE radio resource usage and successfully do data offloading for each eNB in wireless cellular networks.
DOI:10.1109/ICS.2016.0037