DeepRMSA: A deep reinforcement learning framework for routing, modulation and spectrum assignment in elastic optical networks
This paper proposes DeepRMSA, a deep reinforcement learning framework for routing,
modulation and spectrum assignment (RMSA) in elastic optical networks (EONs) …
modulation and spectrum assignment (RMSA) in elastic optical networks (EONs) …
Optical X-haul options for 5G fixed wireless access: Which one to choose?
5G is anticipated to be a significant leap in the evolution of mobile communication. Being
designed to facilitate 10 to 100 times more capacity than 4G, 5G is considered to be the most …
designed to facilitate 10 to 100 times more capacity than 4G, 5G is considered to be the most …
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 …
Connection management xAPP for O-RAN RIC: A graph neural network and reinforcement learning approach
Connection management is an important problem for any wireless network to ensure smooth
and well-balanced operation throughout. Traditional methods for connection management …
and well-balanced operation throughout. Traditional methods for connection management …
Radio resource management for C-V2X: From a hybrid centralized-distributed scheme to a distributed scheme
C Guo, C Wang, L Cui, Q Zhou… - IEEE Journal on Selected …, 2023 - ieeexplore.ieee.org
Spectrum sharing in cellular vehicle-to-everything (C-V2X) has been conceived as a
promising solution to improve spectrum efficiency. However, the co-channel interference …
promising solution to improve spectrum efficiency. However, the co-channel interference …
Empowering Non-Terrestrial Networks with Artificial Intelligence: A Survey
6G networks can support global, ubiquitous and seamless connectivity through the
convergence of terrestrial and non-terrestrial networks (NTNs). Unlike terrestrial scenarios …
convergence of terrestrial and non-terrestrial networks (NTNs). Unlike terrestrial scenarios …
Federated deep reinforcement learning for user access control in open radio access networks
The Open Radio Access Network (O-RAN) introducing a particular unit known as RAN
Intelligent Controllers (RICs) has been regarded as revolutionary paradigms to support …
Intelligent Controllers (RICs) has been regarded as revolutionary paradigms to support …
Location-recommendation-aware virtual network embedding in energy-efficient optical-wireless hybrid networks supporting 5G models
Given the possibility of ubiquitous 5G wireless access, location data bridge the gap between
the physical world and digital online social networking services and also reflect user …
the physical world and digital online social networking services and also reflect user …
Network Selection over 5G-Advanced Heterogeneous Networks Based on Federated Learning and Cooperative Game Theory
5G-Advanced and Beyond claims a 3D ecosystem with cooperation between terrestrial and
non-terrestrial networks to achieve seamless coverage, improve capacity, and enable …
non-terrestrial networks to achieve seamless coverage, improve capacity, and enable …
Resource slicing and customization in RAN with dueling deep Q-network
The emerging future generation 5G technology is expected to support service-oriented
virtualized networks where different network applications provide unique services. 5G …
virtualized networks where different network applications provide unique services. 5G …