Evolution toward intelligent communications: Impact of deep learning applications on the future of 6G technology,WIREs Data Mining and Knowledge Discovery

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Evolution toward intelligent communications: Impact of deep learning applications on the future of 6G technology
WIREs Data Mining and Knowledge Discovery ( IF 6.4 ) Pub Date : 2023-11-07 , DOI: 10.1002/widm.1521
Mohamed Abd Elaziz _{1,

2,

3,

4} , Mohammed A. A. Al‐qaness ₅ , Abdelghani Dahou _{6,

7} , Saeed Hamood Alsamhi _{8,

9} , Laith Abualigah _{4,

10,

11,

12} , Rehab Ali Ibrahim ₁ , Ahmed A. Ewees ₁₃

Affiliation

Department of Mathematics, Faculty of Science Zagazig University Zagazig Egypt
Faculty of Computer Science and Engineering Galala University Suze Egypt
Artificial Intelligence Research Center (AIRC) Ajman University Ajman United Arab Emirates
Department of Electrical and Computer Engineering Lebanese American University Byblos Lebanon
College of Physics and Electronic Information Engineering Zhejiang Normal University Jinhua China
School of Computer Science and Technology Zhejiang Normal University Jinhua China
LDDI Laboratory, Faculty of Science and Technology University of Ahmed DRAIA Adrar Algeria
Insight Centre for Data Analytics University of Galway Galway Ireland
Faculty of Engineering IBB University IBB Yemen
Hourani Center for Applied Scientific Research Al‐Ahliyya Amman University Amman Jordan
MEU Research Unit Middle East University Amman Jordan
Applied Science Research Center Applied Science Private University Amman Jordan
Department of Computer Damietta University Damietta Egypt

The sixth generation (6G) represents the next evolution in wireless communication technology and is currently under research and development. It is expected to deliver faster speeds, reduced latency, and greater capacity compared to the current 5G wireless technology. 6G is envisioned as a technology capable of establishing a fully data-driven network, proficient in analyzing and optimizing end-to-end behavior and handling massive volumes of real-time data at rates of up to terabits per second (Tb/s). Moreover, 6G is designed to accommodate an average of 1000+ substantial connections per person over the course of a decade. The concept of a data-driven network introduces a new service paradigm, which offers fresh opportunities for applications within 6G wireless communication and network design in the future. This paper aims to provide a survey of existing applications of 6G that are based on deep learning techniques. It also explores the potential, essential technologies, scenarios, challenges, and related topics associated with 6G. These aspects are crucial for meeting the requirements for the development of future intelligent networks. Furthermore, this work delves into various research gaps between deep learning and 6G that remain unexplored. Different potential deep learning applications for 6G networks, including privacy, security, environmentally friendly communication, sustainability, and various wireless applications, are discussed. Additionally, we shed light on the challenges and future trends in this field.

中文翻译：

向智能通信演进：深度学习应用对 6G 技术未来的影响

第六代（6G）代表无线通信技术的下一代演进，目前正在研究和开发中。与当前的 5G 无线技术相比，它预计将提供更快的速度、更低的延迟和更大的容量。6G 被设想为一种能够建立完全数据驱动的网络的技术，能够熟练分析和优化端到端行为，并以高达每秒太比特 (Tb/s) 的速率处理大量实时数据。此外，6G 的设计目标是在十年内平均容纳每人 1000 多个实质性连接。数据驱动网络的概念引入了一种新的服务范式，为未来6G无线通信和网络设计中的应用提供了新的机会。本文旨在对基于深度学习技术的 6G 现有应用进行调查。它还探讨了与 6G 相关的潜力、基本技术、场景、挑战和相关主题。这些方面对于满足未来智能网络发展的要求至关重要。此外，这项工作还深入探讨了深度学习和 6G 之间尚未探索的各种研究差距。讨论了 6G 网络的不同潜在深度学习应用，包括隐私、安全、环保通信、可持续性和各种无线应用。此外，我们还阐明了该领域的挑战和未来趋势。

更新日期：2023-11-07

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