An in-depth survey on virtualization technologies in 6g integrated terrestrial and non-terrestrial networks
6G networks are envisioned to deliver a large diversity of applications and meet stringent
Quality of Service (QoS) requirements. Hence, integrated Terrestrial and Non-Terrestrial …
Quality of Service (QoS) requirements. Hence, integrated Terrestrial and Non-Terrestrial …
Novel Adaptive Multi-User Multi-Services Scheduling to Enhance Throughput in 5G-Advanced and Beyond
S Ravindran, S Chaudhuri, J Bapat… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Optimum network slice resource allocation for multiple User Equipment (UE) requesting
several services concurrently in a scalable manner is a complex open research problem …
several services concurrently in a scalable manner is a complex open research problem …
Federated deep reinforcement learning for task offloading and resource allocation in mobile edge computing-assisted vehicular networks
X Zhao, Y Wu, T Zhao, F Wang, M Li - Journal of Network and Computer …, 2024 - Elsevier
Mobile edge computing (MEC) enables computation intensive applications in the Internet of
Vehicles (IoV) to no longer be limited by device resources. However, the lack of an effective …
Vehicles (IoV) to no longer be limited by device resources. However, the lack of an effective …
Slicing for Dense Smart Factory Network: Current State, Scenarios, Challenges and Expectations
In the era of Industry 4.0, smart factories have emerged as a paradigm shift, redefining
manufacturing with the integration of advanced digital technologies. Central to this …
manufacturing with the integration of advanced digital technologies. Central to this …
Mobility aware and energy-efficient federated deep reinforcement learning assisted resource allocation for 5G-RAN slicing
Network slicing is one of the foundations for the realization of 5G and beyond. However, due
to the mobility of the users and the network dynamics, flexible and efficient radio access …
to the mobility of the users and the network dynamics, flexible and efficient radio access …
5G and edge: A reinforcement learning approach for Virtual Network Embedding with cost optimization and improved acceptance rate
CL Moreira, CA Kamienski, RAC Bianchi - Computer Networks, 2024 - Elsevier
Abstract 5G technologies are fueling a revolution across numerous industries, including
manufacturing, healthcare, and entertainment, by enabling the development and …
manufacturing, healthcare, and entertainment, by enabling the development and …
Semi-Supervised Learning Approach for Efficient Resource Allocation with Network Slicing in O-RAN
S Nouri, MK Motalleb, V Shah-Mansouri… - arXiv preprint arXiv …, 2024 - arxiv.org
The Open Radio Access Network (O-RAN) technology has emerged as a promising solution
for network operators, providing them with an open and favorable environment. Ensuring …
for network operators, providing them with an open and favorable environment. Ensuring …
Edge Intelligence: Deep learning-enabled edge computing
S Benedict - 2024 - iopscience.iop.org
Edge Intelligence: deep learning-enabled edge computing is a book that targets researchers
and practitioners who are interested in applying intelligence without compromising data …
and practitioners who are interested in applying intelligence without compromising data …
[PDF][PDF] PandORA: Automated Design and Comprehensive Evaluation of Deep Reinforcement Learning Agents for Open RAN
The highly heterogeneous ecosystem of Next Generation (NextG) wireless communication
systems calls for novel networking paradigms where functionalities and operations can be …
systems calls for novel networking paradigms where functionalities and operations can be …