Neural Network MIMO Detection for Coded Wireless Communication with Impairments

Omer Sholev; H. Permuter; Eilam Ben-Dror; Wenliang Liang

DOI:10.1109/WCNC45663.2020.9120517

Corpus ID: 219978098

Neural Network MIMO Detection for Coded Wireless Communication with Impairments

@article{Sholev2020NeuralNM,
  title={Neural Network MIMO Detection for Coded Wireless Communication with Impairments},
  author={Omer Sholev and H. Permuter and Eilam Ben-Dror and Wenliang Liang},
  journal={2020 IEEE Wireless Communications and Networking Conference (WCNC)},
  year={2020},
  pages={1-8}
}

Omer Sholev, H. Permuter, +1 author Wenliang Liang

Published 2020

Computer Science

2020 IEEE Wireless Communications and Networking Conference (WCNC)

In this paper, a neural network based Multiple-Input-Multiple-Output (MIMO) algorithm is presented. The algorithm is specifically designed to be integrated in a coded MIMO-OFDM system, and is based upon projected gradient descent iterations. We combine our model as a part of a modern coded MIMO-OFDM system, and we compare its performance with common MIMO detectors on simulated data, as well as on field data. We also investigated our model’s performance in the presence of several common… CONTINUE READING

View on IEEE

Share This Paper

3 Citations

Figures and Topics from this paper

Figures

A Study on MIMO Channel Estimation by 2D and 3D Convolutional Neural Networks

Ben Marinberg, A. Cohen, Eilam Ben-Dror, H. Permuter
Computer Science, Engineering
2020 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS)
2020

Low PAPR Waveform Design for OFDM Systems Based on Convolutional Autoencoder

Yara Huleihel, Eilam Ben-Dror, H. Permuter
Computer Science, Engineering
2020 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS)
2020