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A tutorial on ultrareliable and low-latency communications in 6G: Integrating domain knowledge into deep learning
As one of the key communication scenarios in the fifth-generation and also the sixth-
generation (6G) mobile communication networks, ultrareliable and low-latency …
generation (6G) mobile communication networks, ultrareliable and low-latency …
A survey of machine and deep learning methods for internet of things (IoT) security
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 …
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
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 …
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 …
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
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 …
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
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 …
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
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 …
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
Blockchain technology with its secure, transparent and decentralized nature has been
recently employed in many mobile applications. However, the process of executing …
recently employed in many mobile applications. However, the process of executing …
Scheduling algorithms for 5G networks and beyond: Classification and survey
Over the years, several research groups have been develo** effective and efficient
scheduling algorithms to enhance the quality of service of mobile communication networks …
scheduling algorithms to enhance the quality of service of mobile communication networks …
AI-enabled future wireless networks: Challenges, opportunities, and open issues
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 …
in the way future wireless network resources are managed. Indeed, when application …