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

Te Chuan Chiu, Ya Ju Yu, Shih Fan Chou, Yu Ting Tsai, Ai Chun Pang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)


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.

Original languageEnglish
Title of host publicationProceedings - 2016 International Computer Symposium, ICS 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages6
ISBN (Electronic)9781509034383
Publication statusPublished - 2017 Feb 16
Event2016 International Computer Symposium, ICS 2016 - Chiayi, Taiwan
Duration: 2016 Dec 152016 Dec 17

Publication series

NameProceedings - 2016 International Computer Symposium, ICS 2016


Other2016 International Computer Symposium, ICS 2016

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition
  • Hardware and Architecture
  • Computer Networks and Communications
  • Computer Science Applications

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