[HTML][HTML] Federated learning enables 6 G communication technology: Requirements, applications, and integrated with intelligence framework
The 5 G networks are effectively deployed worldwide, and academia and industries have
begun looking at 6 G network communication technology for consumer electronics …
begun looking at 6 G network communication technology for consumer electronics …
Federated learning for 5G and beyond, a blessing and a curse-an experimental study on intrusion detection systems
Abstract 5G's service providers now leverage Deep Learning (DL) to automate their network
slice management, provisioning, and security. To this end, each slice owner contributes data …
slice management, provisioning, and security. To this end, each slice owner contributes data …
Multi-frame scheduling for federated learning over energy-efficient 6g wireless networks
M Beitollahi, N Lu - IEEE INFOCOM 2022-IEEE Conference on …, 2022 - ieeexplore.ieee.org
It is envisioned that data-driven distributed learning approaches such as federated learning
(FL) will be a key enabler for 6G wireless networks. However, the deployment of FL over …
(FL) will be a key enabler for 6G wireless networks. However, the deployment of FL over …
Worker-centric model allocation for federated learning in mobile edge computing
Federated Learning (FL) is believed as a promising manner of distributed machine learning
for 5G and future 6G networks in the context of mobile edge computing (MEC). From the …
for 5G and future 6G networks in the context of mobile edge computing (MEC). From the …
Efficiency-Boosting Federated Learning in Wireless Networks: A Long-Term Perspective
Federated learning (FL) can train a global model from clients' local dataset, which can make
full use of the computing resources of clients and performs more extensive and efficient …
full use of the computing resources of clients and performs more extensive and efficient …
Intelligence slicing: A unified framework to integrate artificial intelligence into 5G networks
The fifth-generation and beyond mobile networks should support extremely high and
diversified requirements from a wide variety of emerging applications. It is envisioned that …
diversified requirements from a wide variety of emerging applications. It is envisioned that …
Fedrelay: Federated relay learning for 6g mobile edge intelligence
Federated learning (FL) is a promising training paradigm to achieve ubiquitous intelligence
for future 6G communication systems. However, it is challenging to apply FL in 6G-enabled …
for future 6G communication systems. However, it is challenging to apply FL in 6G-enabled …
Empowering edge intelligence by air-ground integrated federated learning
Ubiquitous intelligence has been widely recognized as a critical vision of the future sixth
generation (6G) networks, which implies intelligence over the whole network from the core to …
generation (6G) networks, which implies intelligence over the whole network from the core to …
Centralized and federated learning for predictive VNF autoscaling in multi-domain 5G networks and beyond
T Subramanya, R Riggio - IEEE Transactions on Network and …, 2021 - ieeexplore.ieee.org
Network Function Virtualization (NFV) and Multi-access Edge Computing (MEC) are two
technologies expected to play a vital role in 5G and beyond networks. However, adequate …
technologies expected to play a vital role in 5G and beyond networks. However, adequate …
Wireless Federated Learning (WFL) for 6G Networks⁴Part I: Research Challenges and Future Trends
PS Bouzinis, PD Diamantoulakis… - IEEE …, 2021 - ieeexplore.ieee.org
Conventional machine learning techniques are conducted in a centralized manner.
Recently, the massive volume of generated wireless data, the privacy concerns and the …
Recently, the massive volume of generated wireless data, the privacy concerns and the …