Deep reinforcement learning for mobile 5G and beyond: Fundamentals, applications, and challenges
Future-generation wireless networks (5G and beyond) must accommodate surging growth in
mobile data traffic and support an increasingly high density of mobile users involving a …
mobile data traffic and support an increasingly high density of mobile users involving a …
[HTML][HTML] A survey of deep reinforcement learning application in 5G and beyond network slicing and virtualization
Abstract The 5th Generation (5G) and beyond networks are expected to offer huge
throughputs, connect large number of devices, support low latency and large numbers of …
throughputs, connect large number of devices, support low latency and large numbers of …
Applications of deep reinforcement learning in communications and networking: A survey
This paper presents a comprehensive literature review on applications of deep
reinforcement learning (DRL) in communications and networking. Modern networks, eg …
reinforcement learning (DRL) in communications and networking. Modern networks, eg …
Deep reinforcement learning-based network slicing for beyond 5G
With the advent of 5G era, network slicing has received a great deal of attention as a means
to support a variety of wireless services in a flexible manner. Network slicing is a technique …
to support a variety of wireless services in a flexible manner. Network slicing is a technique …
The frontiers of deep reinforcement learning for resource management in future wireless HetNets: Techniques, challenges, and research directions
Next generation wireless networks are expected to be extremely complex due to their
massive heterogeneity in terms of the types of network architectures they incorporate, the …
massive heterogeneity in terms of the types of network architectures they incorporate, the …
Survey on reinforcement learning applications in communication networks
Y Qian, J Wu, R Wang, F Zhu… - … of Communications and …, 2019 - ieeexplore.ieee.org
In recent years, intelligent communication has drawn huge research efforts in both academia
and industry. With the advent of 5G technology, intelligent wireless terminals and intelligent …
and industry. With the advent of 5G technology, intelligent wireless terminals and intelligent …
Single and multi-agent deep reinforcement learning for AI-enabled wireless networks: A tutorial
Deep Reinforcement Learning (DRL) has recently witnessed significant advances that have
led to multiple successes in solving sequential decision-making problems in various …
led to multiple successes in solving sequential decision-making problems in various …
A federated reinforcement learning framework for incumbent technologies in beyond 5G networks
Incumbent wireless technologies for futuristic fifth generation (5G) and beyond 5G (B5G)
networks, such as IEEE 802.11 ax (WiFi), are vital to provide ubiquitous ultra-reliable and …
networks, such as IEEE 802.11 ax (WiFi), are vital to provide ubiquitous ultra-reliable and …
Deep reinforcement learning techniques for vehicular networks: Recent advances and future trends towards 6G
Employing machine learning into 6G vehicular networks to support vehicular application
services is being widely studied and a hot topic for the latest research works in the literature …
services is being widely studied and a hot topic for the latest research works in the literature …
Machine learning for 5G/B5G mobile and wireless communications: Potential, limitations, and future directions
Driven by the demand to accommodate today's growing mobile traffic, 5G is designed to be
a key enabler and a leading infrastructure provider in the information and communication …
a key enabler and a leading infrastructure provider in the information and communication …