Gaussian AMP Aided Model-Driven Learning for OTFS System-Reference-Cited by-同舟云学术

Gaussian AMP Aided Model-Driven Learning for OTFS System

Published:2022-12 Issue:12 Volume:26 Page:2949-2953
ISSN:1089-7798
Container-title:IEEE Communications Letters
language:
Short-container-title:IEEE Commun. Lett.

Author:

Zhang Xufan¹,Xiao Lixia²^ORCID,Li Shuo¹,Yuan Qijiang²^ORCID,Xiang Luping³^ORCID,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, School of Cyber Science and Engineering, and the Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China

3. School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China

Funder

National Key Research and Development Program of China

National Science Foundation of China

Fundamental Research Funds for the Central Universities

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

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

Link

http://xplorestaging.ieee.org/ielx7/4234/9979638/09893070.pdf?arnumber=9893070

Reference16 articles.

1. Model-Driven Deep Learning for Physical Layer Communications

2. Learning to Detect

3. Trainable ISTA for Sparse Signal Recovery

4. Model-Driven Deep Learning for MIMO Detection

5. Improving Massive MIMO Message Passing Detectors With Deep Neural Network

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1. Neural Network-Based Two-Dimensional Filtering for OTFS Symbol Detection;ICC 2024 - IEEE International Conference on Communications;2024-06-09

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

3. Graph Neural Network Assisted Efficient Signal Detection for OTFS Systems;IEEE Communications Letters;2023-08