Machine Learning for Intelligent-Reflecting-Surface-Based Wireless Communication towards 6G: A Review.

Journal: Sensors (Basel, Switzerland)
PMID:

Abstract

An intelligent reflecting surface (IRS) is a programmable device that can be used to control electromagnetic waves propagation by changing the electric and magnetic properties of its surface. Therefore, IRS is considered a smart technology for the sixth generation (6G) of communication networks. In addition, machine learning (ML) techniques are now widely adopted in wireless communication as the computation power of devices has increased. As it is an emerging topic, we provide a comprehensive overview of the state-of-the-art on ML, especially on deep learning (DL)-based IRS-enhanced communication. We focus on their operating principles, channel estimation (CE), and the applications of machine learning to IRS-enhanced wireless networks. In addition, we systematically survey existing designs for IRS-enhanced wireless networks. Furthermore, we identify major issues and research opportunities associated with the integration of IRS and other emerging technologies for applications to next-generation wireless communication.

Authors

  • Mohammad Abrar Shakil Sejan
    Department of Information and Communication Engineering, Sejong University, Seoul 05006, Korea.
  • Md Habibur Rahman
    1Department of Biomedical Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong SAR, China.
  • Beom-Sik Shin
    Department of Information and Communication Engineering, Sejong University, Seoul 05006, Korea.
  • Ji-Hye Oh
    Department of Medical Science, Asan Medical Institute of Convergence Science and Technology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea.
  • Young-Hwan You
    Department of Convergence Engineering for Intelligent Drone, Sejong University, Seoul 05006, Korea.
  • Hyoung-Kyu Song
    Korea Advanced Institute of Science and Technology, Daejeon, South Korea.