[HTML][HTML] Augmented Lagrangian-Based Reinforcement Learning for Network Slicing in IIoT
Q Qi, W Lin, B Guo, J Chen, C Deng, G Lin, X Sun… - Electronics, 2022 - mdpi.com
Network slicing enables the multiplexing of independent logical networks on the same
physical network infrastructure to provide different network services for different applications …
physical network infrastructure to provide different network services for different applications …
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 …
Action Elimination-assisted Deep Reinforcement Learning for B5G Cell Selection and Network Slicing
With the emergence of 5G era, network slicing has received much attention due to its ability
to support various services. Network slicing is an approach to partition a single physical …
to support various services. Network slicing is an approach to partition a single physical …
Adaptive Resource Management for Edge Network Slicing using Incremental Multi-Agent Deep Reinforcement Learning
Multi-access edge computing provides local resources in mobile networks as the essential
means for meeting the demands of emerging ultra-reliable low-latency communications. At …
means for meeting the demands of emerging ultra-reliable low-latency communications. At …
Random Access based on LSTM for Mixed Traffic IoT Networks
HL dos Santos, JC Marinello… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
A critical issue on the telecommunication systems relies on serving different demands of
service specification in an on-demand fashion. This approach has gained more and more …
service specification in an on-demand fashion. This approach has gained more and more …
Admission Control with Resource Efficiency Using Reinforcement Learning in Beyond-5G Networks
LA Garrido, K Ramantas, A Dalgkitsis… - 2023 IEEE 34th …, 2023 - ieeexplore.ieee.org
Managing network slices in 5G networks and in communication technologies Beyond-5G
(B5G) requires intelligent mechanisms to ensure users' service access and to maximize the …
(B5G) requires intelligent mechanisms to ensure users' service access and to maximize the …
Intelligence-learning driven resource allocation for B5G Ultra-Dense Networks: A structured literature review
Network densification is a suitable solution to improve the capacity of future mobile
networks. However, deploying massive low-power base stations sharing the radio spectrum …
networks. However, deploying massive low-power base stations sharing the radio spectrum …
Machine Learning and 5G Charging Function with Network Analytics Function for Network Slice as a Service
M Bhavsar, P Deshmukh… - 2022 4th International …, 2022 - ieeexplore.ieee.org
5g system is more customer centric which give very high throughput, low latency, highly
scalable, customer industry driven technology. 5G system has charging function which …
scalable, customer industry driven technology. 5G system has charging function which …
Slice Admission and Deployment Strategies in Resource-Constrained 5G Network Slices using an Actor-Critic Approach
RVJ Dayot, IH Ra - 2022 Joint 12th International Conference on …, 2022 - ieeexplore.ieee.org
The advent of 5G mobile communications networks has enabled the emergence of various
services and applications. However, the diverse and complex requirements of these new …
services and applications. However, the diverse and complex requirements of these new …
Edge Intelligence: Deep learning-enabled edge computing
S Benedict - 2024 - beta.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 …