Pushing AI to wireless network edge: An overview on integrated sensing, communication, and computation towards 6G
Pushing artificial intelligence (AI) from central cloud to network edge has reached board
consensus in both industry and academia for materializing the vision of artificial intelligence …
consensus in both industry and academia for materializing the vision of artificial intelligence …
A survey on over-the-air computation
Communication and computation are often viewed as separate tasks. This approach is very
effective from the perspective of engineering as isolated optimizations can be performed …
effective from the perspective of engineering as isolated optimizations can be performed …
Edge learning for B5G networks with distributed signal processing: Semantic communication, edge computing, and wireless sensing
To process and transfer large amounts of data in emerging wireless services, it has become
increasingly appealing to exploit distributed data communication and learning. Specifically …
increasingly appealing to exploit distributed data communication and learning. Specifically …
Edge artificial intelligence for 6G: Vision, enabling technologies, and applications
The thriving of artificial intelligence (AI) applications is driving the further evolution of
wireless networks. It has been envisioned that 6G will be transformative and will …
wireless networks. It has been envisioned that 6G will be transformative and will …
Machine learning for large-scale optimization in 6g wireless networks
The sixth generation (6G) wireless systems are envisioned to enable the paradigm shift from
“connected things” to “connected intelligence”, featured by ultra high density, large-scale …
“connected things” to “connected intelligence”, featured by ultra high density, large-scale …
Interference management for over-the-air federated learning in multi-cell wireless networks
Federated learning (FL) over resource-constrained wireless networks has recently attracted
much attention. However, most existing studies consider one FL task in single-cell wireless …
much attention. However, most existing studies consider one FL task in single-cell wireless …
Federated learning for connected and automated vehicles: A survey of existing approaches and challenges
Machine learning (ML) is widely used for key tasks in Connected and Automated Vehicles
(CAV), including perception, planning, and control. However, its reliance on vehicular data …
(CAV), including perception, planning, and control. However, its reliance on vehicular data …
Decentralized federated learning: A survey and perspective
Federated learning (FL) has been gaining attention for its ability to share knowledge while
maintaining user data, protecting privacy, increasing learning efficiency, and reducing …
maintaining user data, protecting privacy, increasing learning efficiency, and reducing …
Over-the-Air Computation for 6G: Foundations, Technologies, and Applications
The rapid advancement of artificial intelligence technologies has given rise to diversified
intelligent services, which place unprecedented demands on massive connectivity and …
intelligent services, which place unprecedented demands on massive connectivity and …
[HTML][HTML] Over-the-air federated learning: Status quo, open challenges, and future directions
The development of applications based on artificial intelligence and implemented over
wireless networks is increasingly rapidly and is expected to grow dramatically in the future …
wireless networks is increasingly rapidly and is expected to grow dramatically in the future …