RAN resource slicing in 5G using multi-agent correlated Q-learning
5G is regarded as a revolutionary mobile network, which is expected to satisfy a vast number
of novel services, ranging from remote health care to smart cities. However, heterogeneous …
of novel services, ranging from remote health care to smart cities. However, heterogeneous …
Reinforcement learning based resource allocation for network slicing in 5G C-RAN
X Wang, T Zhang - 2019 Computing, Communications and IoT …, 2019 - ieeexplore.ieee.org
In network slicing enabled 5G cloud radio access networks (C-RAN), we study the network
slice resource allocation to ensure the differentiated performance requirements of diversified …
slice resource allocation to ensure the differentiated performance requirements of diversified …
Energy-efficient deep reinforcement learning assisted resource allocation for 5G-RAN slicing
One of the pillars of the 5G architecture is network slicing, in which hardware, radio, and
power resources are virtualized as a logical network taking into account the requirements of …
power resources are virtualized as a logical network taking into account the requirements of …
Transfer learning-based accelerated deep reinforcement learning for 5G RAN slicing
AM Nagib, H Abou-Zeid… - 2021 IEEE 46th …, 2021 - ieeexplore.ieee.org
Deep Reinforcement Learning (DRL) algorithms have been recently proposed to solve
dynamic Radio Resource Management (RRM) problems in 5G networks. However, the slow …
dynamic Radio Resource Management (RRM) problems in 5G networks. However, the slow …
Learning from peers: Deep transfer reinforcement learning for joint radio and cache resource allocation in 5G RAN slicing
Network slicing is a critical technique for 5G communications that covers radio access
network (RAN), edge, transport and core slicing. The evolving network architecture requires …
network (RAN), edge, transport and core slicing. The evolving network architecture requires …
Slice management in radio access network via deep reinforcement learning
In future 5G systems, it is envisioned that the physical resources of a single network will be
dynamically shared between the virtual end-to-end networks called “slices” and the network …
dynamically shared between the virtual end-to-end networks called “slices” and the network …
Reinforcement learning for dynamic resource optimization in 5G radio access network slicing
The paper presents a reinforcement learning solution to dynamic resource allocation for 5G
radio access network slicing. Available communication resources (frequency-time blocks …
radio access network slicing. Available communication resources (frequency-time blocks …
GAN-powered deep distributional reinforcement learning for resource management in network slicing
Network slicing is a key technology in 5G communications system. Its purpose is to
dynamically and efficiently allocate resources for diversified services with distinct …
dynamically and efficiently allocate resources for diversified services with distinct …
A reinforcement learning agent for mixed-numerology interference-aware slice spectrum allocation with non-deterministic and deterministic traffic
M Zambianco, G Verticale - Computer Communications, 2022 - Elsevier
Abstract 5G RAN slicing is an essential tool to support the simultaneous coexistence of
enhanced mobile broadband (eMBB) and ultra-reliable low-latency communications …
enhanced mobile broadband (eMBB) and ultra-reliable low-latency communications …
Online convex optimization for efficient and robust inter-slice radio resource management
T Wang, S Wang - IEEE Transactions on Communications, 2021 - ieeexplore.ieee.org
Radio access network (RAN) slicing is one of the key technologies in 5G and beyond mobile
networks, where multiple logical subnets, ie, RAN slices, are allowed to run on top of the …
networks, where multiple logical subnets, ie, RAN slices, are allowed to run on top of the …