Deep Learning for Channel Estimation in Physical Layer Wireless Communications: Fundamental, Methods, and Challenges

Chaoluo Lv; Zhongqiang Luo

doi:10.3390/electronics12244965

journal article Open Access Dec 11, 2023

Deep Learning for Channel Estimation in Physical Layer Wireless Communications: Fundamental, Methods, and Challenges

Chaoluo Lv Zhongqiang Luo

Electronics Vol. 12 No. 24 pp. 4965 · MDPI AG

View at Publisher Save 10.3390/electronics12244965

Abstract

With the rapid development of wireless communication technology, intelligent communication has become one of the mainstream research directions after the fifth generation (5G). In particular, deep learning has emerged as a significant artificial intelligence technology widely applied in the physical layer of wireless communication for achieving intelligent receiving processing. Channel estimation, a crucial component of physical layer communication, is essential for further information recovery. As a motivation, this paper aims to review the relevant research on applying deep learning methods in channel estimation. Firstly, this paper briefly introduces the conventional channel estimation methods and then analyzes their respective merits and drawbacks. Subsequently, this paper introduces several common types of neural networks and describes the application of deep learning in channel estimation according to data-driven and model-driven approaches, respectively. Then, this paper extends to emerging communication scenarios and discusses the existing research on channel estimation based on deep learning for reconfigurable intelligent surface (RIS)-aided communication systems. Finally, to meet the demands of next-generation wireless communication, challenges and future research trends in deep-learning-based channel estimation are discussed.

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Details

Published: Dec 11, 2023
Vol/Issue: 12(24)
Pages: 4965
License: View

Authors

C

Chaoluo Lv

School of Automation and Information Engineering, Sichuan University of Science and Engineering, Yibin 644000, China

Z

Zhongqiang Luo

School of Automation and Information Engineering, Sichuan University of Science and Engineering, Yibin 644000, China; Artificial Intelligence Key Laboratory of Sichuan Province, Sichuan University of Science and Engineering, Yibin 644000, China

Funding

National Natural Science Foundation of China Award: 61801319

Sichuan Science and Technology Program Award: 61801319

Innovation Fund of Chinese Universities Award: 61801319

Sichuan University of Science and Engineering Talent Introduction Project Award: 61801319

Postgraduate Innovation Fund Project of Sichuan University of Science and Engineering Award: 61801319

Cite This Article

Chaoluo Lv, Zhongqiang Luo (2023). Deep Learning for Channel Estimation in Physical Layer Wireless Communications: Fundamental, Methods, and Challenges. Electronics, 12(24), 4965. https://doi.org/10.3390/electronics12244965

Deep Learning for Channel Estimation in Physical Layer Wireless Communications: Fundamental, Methods, and Challenges

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