When Machine Learning Meets Big Data: A Wireless Communication Perspective

The authors have witnessed an exponential growth in commercial data services, which has led to the so-called big data era. Machine learning, one of the most promising artificial intelligence (AI) tools for analyzing this deluge of data, has been called upon in many industry and academic research areas. In this article, the authors briefly review big data analysis and machine learning, along with their potential applications in next-generation (NG) wireless networks. Next, the authors invoke big data analysis to predict the requirements of mobile users and exploit such analysis to improve the performance of "social network-aware wireless." In particular, a unified, big data-aided machine learning framework is proposed that consists of feature extraction, data modeling, and prediction/online refinement. The main benefits of this proposed framework are that, by relying on big data that reflects both the spectral and other challenging requirements of users, the authors can refine the motivation, problem formulations, and methodology of powerful machine-learning algorithms in the context of wireless networks.

• Record URL:
  https://doi.org/10.1109/MVT.2019.2953857
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/15566072
• Supplemental Notes:
  • Copyright © 2020, IEEE.
• Authors:
  • Liu, Yuanwei
  • Bi, Suzhi
  • Shi, Zhiyuan
  • Hanzo, Lajos
• Publication Date: 2020-3

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: pp 63-72
• Serial:
  • IEEE Vehicular Technology Magazine
  • Volume: 15
  • Issue Number: 1
  • Publisher: Institute of Electrical and Electronics Engineers (IEEE)
  • ISSN: 1556-6072
  • Serial URL: http://ieeexplore.ieee.org/xpl/tocresult.jsp?isnumber=34840

Subject/Index Terms

• TRT Terms: Computer security; Data files; Machine learning; Mobile computing; Wireless communication systems
• Subject Areas: Data and Information Technology; Highways; Vehicles and Equipment;

Filing Info

• Accession Number: 01736294
• Record Type: Publication
• Files: TRIS
• Created Date: Apr 17 2020 9:37AM