Graph Neural Network Assisted Efficient Signal Detection for OTFS Systems-Reference-Cited by-同舟云学术

Graph Neural Network Assisted Efficient Signal Detection for OTFS Systems

Published:2023-08 Issue:8 Volume:27 Page:2058-2062
ISSN:1089-7798
Container-title:IEEE Communications Letters
language:
Short-container-title:IEEE Commun. Lett.

Author:

Zhang Xufan¹^ORCID,Zhang Shengyu²^ORCID,Xiao Lixia¹^ORCID,Li Shuo³,Jiang Tao¹^ORCID

Affiliation:

1. Research Center of 6G Mobile Communication, School of Cyber Science and Engineering, Huazhong University of Science and Technology, Wuhan, China

2. Research Center of 6G Mobile Communication, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China

3. Research Center of 6G Mobile Communication, School of Electronic Information and Communications, Huazhong University of Science and Technology, Wuhan, China

Funder

National Key Research and Development Program of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Modeling and Simulation

Link

http://xplorestaging.ieee.org/ielx7/4234/10214690/10154051.pdf?arnumber=10154051

Reference19 articles.

1. Trainable ISTA for Sparse Signal Recovery

2. Gaussian AMP Aided Model-Driven Learning for OTFS System

3. Graph neural networks for massive MIMO detection;scotti;arXiv 2007 05703,2020

4. Model-Driven Deep Learning for MIMO Detection

5. Power of Deep Learning for Channel Estimation and Signal Detection in OFDM Systems

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1. Approximate Message Passing-Enhanced Graph Neural Network for OTFS Data Detection;IEEE Wireless Communications Letters;2024-07

2. A Survey on Orthogonal Time Frequency Space Modulation;IEEE Open Journal of the Communications Society;2024

3. Profuse Channel Estimation and Signal Detection Techniques for Orthogonal Time Frequency Space in 6G Epoch: A Survey;IEEE Access;2023