Demod-CNN: A Robust Deep Learning Approach for Intelligent Reflecting Surface-Assisted Multiuser MIMO Communication.

Journal: Sensors (Basel, Switzerland)
Published Date:

Abstract

The intelligent reflecting surface (IRS) is a novel and innovative communication technology that aims at the control of the wireless environment. The IRS is considered as a promising technology for sixth-generation wireless communication. In the last few years, machine learning has emerged as a powerful tool for solving complex problems in diverse application areas. In this paper, we propose a convolutional neural network (CNN)-based demodulation technique called Demod-CNN in IRS-based wireless communication for multiple users. A multiple-input multiple-output based orthogonal multiple frequency division multiplexing system is considered for channel modeling. The received signal data are used for training and testing the model. The simulation results show that the proposed model performs better than the conventional demodulation technique.

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.
  • Hyoung-Kyu Song
    Korea Advanced Institute of Science and Technology, Daejeon, South Korea.