Applications of Deep Learning and Deep Reinforcement Learning in 6G Networks

Tri Hai Nguyen; Heejae Park; Kihyun Seol; Seonghyeon So; Laihyuk Park

doi:10.1109/ICUFN57995.2023.10200390

Applications of Deep Learning and Deep Reinforcement Learning in 6G Networks

Tri Hai Nguyen, Heejae Park, Kihyun Seol, Seonghyeon So, Laihyuk Park

Dept. of Computer Science and Engineering

Seoul National University of Science and Technology (SNUST)

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

14 Scopus citations

Abstract

As the demand for data-driven applications and emerging technologies such as extended reality, autonomous vehicles, and the Internet of Things (IoT) continues to grow, the development of a next-generation wireless communication system, 6G, becomes necessary. To fulfill the stringent requirements of 6G networks, new enabling technologies are necessary. Deep learning (DL) and deep reinforcement learning (DRL) are two promising technologies that have gained significant attention in recent years. In this paper, we provide an overview of the applications and advancements of DL and DRL in 6G networks. We discuss the latest research and identify areas for further exploration in this field.

Original language	English
Title of host publication	ICUFN 2023 - 14th International Conference on Ubiquitous and Future Networks
Publisher	IEEE Computer Society
Pages	427-432
Number of pages	6
ISBN (Electronic)	9798350335385
DOIs	https://doi.org/10.1109/ICUFN57995.2023.10200390
State	Published - 2023
Event	14th International Conference on Ubiquitous and Future Networks, ICUFN 2023 - Paris, France Duration: 4 Jul 2023 → 7 Jul 2023

Publication series

Name	International Conference on Ubiquitous and Future Networks, ICUFN
Volume	2023-July
ISSN (Print)	2165-8528
ISSN (Electronic)	2165-8536

Conference

Conference	14th International Conference on Ubiquitous and Future Networks, ICUFN 2023
Country/Territory	France
City	Paris
Period	4/07/23 → 7/07/23

Keywords

6G
deep learning
deep reinforcement learning
wireless communications

Access to Document

10.1109/ICUFN57995.2023.10200390

Cite this

Nguyen, T. H., Park, H., Seol, K., So, S., & Park, L. (2023). Applications of Deep Learning and Deep Reinforcement Learning in 6G Networks. In ICUFN 2023 - 14th International Conference on Ubiquitous and Future Networks (pp. 427-432). (International Conference on Ubiquitous and Future Networks, ICUFN; Vol. 2023-July). IEEE Computer Society. https://doi.org/10.1109/ICUFN57995.2023.10200390

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title = "Applications of Deep Learning and Deep Reinforcement Learning in 6G Networks",

abstract = "As the demand for data-driven applications and emerging technologies such as extended reality, autonomous vehicles, and the Internet of Things (IoT) continues to grow, the development of a next-generation wireless communication system, 6G, becomes necessary. To fulfill the stringent requirements of 6G networks, new enabling technologies are necessary. Deep learning (DL) and deep reinforcement learning (DRL) are two promising technologies that have gained significant attention in recent years. In this paper, we provide an overview of the applications and advancements of DL and DRL in 6G networks. We discuss the latest research and identify areas for further exploration in this field.",

keywords = "6G, deep learning, deep reinforcement learning, wireless communications",

author = "Nguyen, \{Tri Hai\} and Heejae Park and Kihyun Seol and Seonghyeon So and Laihyuk Park",

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year = "2023",

doi = "10.1109/ICUFN57995.2023.10200390",

language = "English",

series = "International Conference on Ubiquitous and Future Networks, ICUFN",

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Nguyen, TH, Park, H, Seol, K, So, S & Park, L 2023, Applications of Deep Learning and Deep Reinforcement Learning in 6G Networks. in ICUFN 2023 - 14th International Conference on Ubiquitous and Future Networks. International Conference on Ubiquitous and Future Networks, ICUFN, vol. 2023-July, IEEE Computer Society, pp. 427-432, 14th International Conference on Ubiquitous and Future Networks, ICUFN 2023, Paris, France, 4/07/23. https://doi.org/10.1109/ICUFN57995.2023.10200390

Applications of Deep Learning and Deep Reinforcement Learning in 6G Networks. / Nguyen, Tri Hai; Park, Heejae; Seol, Kihyun et al.
ICUFN 2023 - 14th International Conference on Ubiquitous and Future Networks. IEEE Computer Society, 2023. p. 427-432 (International Conference on Ubiquitous and Future Networks, ICUFN; Vol. 2023-July).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - As the demand for data-driven applications and emerging technologies such as extended reality, autonomous vehicles, and the Internet of Things (IoT) continues to grow, the development of a next-generation wireless communication system, 6G, becomes necessary. To fulfill the stringent requirements of 6G networks, new enabling technologies are necessary. Deep learning (DL) and deep reinforcement learning (DRL) are two promising technologies that have gained significant attention in recent years. In this paper, we provide an overview of the applications and advancements of DL and DRL in 6G networks. We discuss the latest research and identify areas for further exploration in this field.

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KW - deep reinforcement learning

KW - wireless communications

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DO - 10.1109/ICUFN57995.2023.10200390

M3 - Conference contribution

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BT - ICUFN 2023 - 14th International Conference on Ubiquitous and Future Networks

PB - IEEE Computer Society

T2 - 14th International Conference on Ubiquitous and Future Networks, ICUFN 2023

Y2 - 4 July 2023 through 7 July 2023

ER -

Applications of Deep Learning and Deep Reinforcement Learning in 6G Networks

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