Graph-based deep learning for communication networks: A survey
W Jiang - Computer Communications, 2022 - Elsevier
Communication networks are important infrastructures in contemporary society. There are
still many challenges that are not fully solved and new solutions are proposed continuously …
still many challenges that are not fully solved and new solutions are proposed continuously …
Wi-Fi meets ML: A survey on improving IEEE 802.11 performance with machine learning
Wireless local area networks (WLANs) empowered by IEEE 802.11 (Wi-Fi) hold a dominant
position in providing Internet access thanks to their freedom of deployment and configuration …
position in providing Internet access thanks to their freedom of deployment and configuration …
An overview on the application of graph neural networks in wireless networks
In recent years, with the rapid enhancement of computing power, deep learning methods
have been widely applied in wireless networks and achieved impressive performance. To …
have been widely applied in wireless networks and achieved impressive performance. To …
Requirements and Specifications for the Orchestration of Network Intelligence in 6G
Next-generation mobile networks are expected to flaunt highly (if not fully) automated
management. To achieve such a vision, Artificial Intelligence (AI) and Machine Learning …
management. To achieve such a vision, Artificial Intelligence (AI) and Machine Learning …
Federated spatial reuse optimization in next-generation decentralized ieee 802.11 wlans
As wireless standards evolve, more complex functionalities are introduced to address the
increasing requirements in terms of throughput, latency, security, and efficiency. To unleash …
increasing requirements in terms of throughput, latency, security, and efficiency. To unleash …
HTNet: Dynamic WLAN Performance Prediction using Heterogenous Temporal GNN
Predicting the throughput of WLAN deployments is a classic problem that occurs in the
design of robust and high performance WLAN systems. However, due to the increasingly …
design of robust and high performance WLAN systems. However, due to the increasingly …
[HTML][HTML] Value is king: the mecforge deep reinforcement learning solution for resource management in 5g and beyond
F Poltronieri, C Stefanelli, N Suri… - Journal of Network and …, 2022 - Springer
Multi-access edge computing (MEC) is a key enabler to fulfill the promises of a new
generation of immersive and low-latency services in 5G and Beyond networks. MEC …
generation of immersive and low-latency services in 5G and Beyond networks. MEC …
Survey of Graph Neural Network for Internet of Things and NextG Networks
SK Moorthy, J Jagannath - arXiv preprint arXiv:2405.17309, 2024 - arxiv.org
The exponential increase in Internet of Things (IoT) devices coupled with 6G pushing
towards higher data rates and connected devices has sparked a surge in data …
towards higher data rates and connected devices has sparked a surge in data …
Radio Resource Management of WLAN Hotspot Access Points in Next Generation Wireless Networks
MA Adelabu, AL Imoize, MB Ugwu - SN Computer Science, 2023 - Springer
The proliferation of the IEEE wireless local area network (WLAN), due to its flexibility,
mobility, and support for billions of smart mobile devices, has gained widespread popularity …
mobility, and support for billions of smart mobile devices, has gained widespread popularity …
Predicting network performance using GNNs: generalization to larger unseen networks
Autonomous Fifth Generation (5G) and Beyond 5G (B5G) networks require modelling tools
to predict the impact on the performance when new configurations and features are applied …
to predict the impact on the performance when new configurations and features are applied …