[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 …
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 …
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 …
Deep reinforcement learning approaches to network slice scaling and placement: A survey
N Saha, M Zangooei, M Golkarifard… - IEEE Communications …, 2023 - ieeexplore.ieee.org
Network slicing in 5G and beyond networks allows the network to be customized for each
application or service by chaining together different virtualized network functions (VNFs) …
application or service by chaining together different virtualized network functions (VNFs) …
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 …
Data-driven dynamic resource scheduling for network slicing: A deep reinforcement learning approach
Network slicing is designed to support a variety of emerging applications with diverse
performance and flexibility requirements, by dividing the physical network into multiple …
performance and flexibility requirements, by dividing the physical network into multiple …
DeepSlice: A deep learning approach towards an efficient and reliable network slicing in 5G networks
Existing cellular communications and the upcoming 5G mobile network requires meeting
high-reliability standards, very low latency, higher capacity, more security, and high-speed …
high-reliability standards, very low latency, higher capacity, more security, and high-speed …
Admission control for 5G core network slicing based on deep reinforcement learning
WF Villota-Jacome, OMC Rendon… - IEEE Systems …, 2022 - ieeexplore.ieee.org
Network slicing is a promising technology for providing customized logical and virtualized
networks for the fifth-generation (5G) use-cases (enhanced mobile broadband, ultrareliable …
networks for the fifth-generation (5G) use-cases (enhanced mobile broadband, ultrareliable …
Deep reinforcement learning for adaptive network slicing in 5G for intelligent vehicular systems and smart cities
A Nassar, Y Yilmaz - IEEE Internet of Things Journal, 2021 - ieeexplore.ieee.org
Intelligent vehicular systems and smart city applications are the fastest growing Internet-of-
Things (IoT) implementations at a compound annual growth rate of 30%. In view of the …
Things (IoT) implementations at a compound annual growth rate of 30%. In view of the …
Learn to improve: A novel deep reinforcement learning approach for beyond 5G network slicing
A Rkhami, Y Hadjadj-Aoul… - 2021 IEEE 18th Annual …, 2021 - ieeexplore.ieee.org
Network slicing remains one of the key technologies in 5G and beyond 5G networks (B5G).
By leveraging SDN and NVF techniques, it enables the coexistence of several …
By leveraging SDN and NVF techniques, it enables the coexistence of several …