A tutorial on ultrareliable and low-latency communications in 6G: Integrating domain knowledge into deep learning

C She, C Sun, Z Gu, Y Li, C Yang… - Proceedings of the …, 2021 - ieeexplore.ieee.org
As one of the key communication scenarios in the fifth-generation and also the sixth-
generation (6G) mobile communication networks, ultrareliable and low-latency …

A survey of machine and deep learning methods for internet of things (IoT) security

MA Al-Garadi, A Mohamed, AK Al-Ali… - … surveys & tutorials, 2020 - ieeexplore.ieee.org
The Internet of Things (IoT) integrates billions of smart devices that can communicate with
one another with minimal human intervention. IoT is one of the fastest develo** fields in …

Deep learning for B5G open radio access network: Evolution, survey, case studies, and challenges

B Brik, K Boutiba, A Ksentini - IEEE Open Journal of the …, 2022 - ieeexplore.ieee.org
Open Radio Access Network (O-RAN) alliance was recently launched to devise a new RAN
architecture featuring open, software-driven, virtual, and intelligent radio access architecture …

Deep reinforcement learning for resource management on network slicing: A survey

JA Hurtado Sánchez, K Casilimas… - Sensors, 2022 - mdpi.com
Network Slicing and Deep Reinforcement Learning (DRL) are vital enablers for achieving
5G and 6G networks. A 5G/6G network can comprise various network slices from unique or …

A survey on 5G coverage improvement techniques: Issues and future challenges

C Sudhamani, M Roslee, JJ Tiang, AU Rehman - Sensors, 2023 - mdpi.com
Fifth generation (5G) is a recent wireless communication technology in mobile networks. The
key parameters of 5G are enhanced coverage, ultra reliable low latency, high data rates …

A survey of 5G network systems: challenges and machine learning approaches

H Fourati, R Maaloul, L Chaari - International Journal of Machine Learning …, 2021 - Springer
Abstract 5G cellular networks are expected to be the key infrastructure to deliver the
emerging services. These services bring new requirements and challenges that obstruct the …

Machine and deep learning for iot security and privacy: applications, challenges, and future directions

S Bharati, P Podder - Security and communication networks, 2022 - Wiley Online Library
The integration of the Internet of Things (IoT) connects a number of intelligent devices with
minimum human interference that can interact with one another. IoT is rapidly emerging in …

Privacy-preserved task offloading in mobile blockchain with deep reinforcement learning

DC Nguyen, PN Pathirana, M Ding… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Blockchain technology with its secure, transparent and decentralized nature has been
recently employed in many mobile applications. However, the process of executing …

Scheduling algorithms for 5G networks and beyond: Classification and survey

A Mamane, M Fattah, M El Ghazi, M El Bekkali… - IEEe …, 2022 - ieeexplore.ieee.org
Over the years, several research groups have been develo** effective and efficient
scheduling algorithms to enhance the quality of service of mobile communication networks …

AI-enabled future wireless networks: Challenges, opportunities, and open issues

M Elsayed, M Erol-Kantarci - IEEE Vehicular Technology …, 2019 - ieeexplore.ieee.org
An expected plethora of demanding services and use cases mandates a revolutionary shift
in the way future wireless network resources are managed. Indeed, when application …