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Evolution toward intelligent communications: Impact of deep learning applications on the future of <scp>6G</scp> technology

Mohamed Abd ElazizArtificial Intelligence Research Center (AIRC) Ajman University Ajman United Arab EmiratesMohammed A. A. Al‐qanessCollege of Physics and Electronic Information Engineering Zhejiang Normal University Jinhua ChinaAbdelghani DahouLDDI Laboratory, Faculty of Science and Technology University of Ahmed DRAIA Adrar AlgeriaSaeed Hamood AlsamhiFaculty of Engineering IBB University IBB YemenLaith AbualigahApplied Science Research Center Applied Science Private University Amman JordanRehab Ali IbrahimDepartment of Mathematics, Faculty of Science Zagazig University Zagazig EgyptAhmed A. EweesDepartment of Computer Damietta University Damietta Egypt
2023en
ABI

Аннотация

Abstract 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. This article is categorized under: Technologies &gt; Computational Intelligence Fundamental Concepts of Data and Knowledge &gt; Explainable AI Technologies &gt; Machine Learning

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