The next-generation of wireless networks will enable many machine learning (ML) tools and applications to efficiently analyze various types of data collected by edge devices for …
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 …
KB Letaief, Y Shi, J Lu, J Lu - IEEE Journal on Selected Areas …, 2021 - ieeexplore.ieee.org
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 …
Full leverage of the huge volume of data generated on a large number of user devices for providing intelligent services in the 6G network calls for Ubiquitous Intelligence (UI). A key to …
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 …
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 …
L Chen, L Fan, X Lei, TQ Duong… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
In this paper, we study a relay-assisted federated edge learning (FEEL) network under latency and bandwidth constraints. In this network, users collaboratively train a global model …
Distributed learning is envisioned as the bedrock of next-generation intelligent networks, where intelligent agents, such as mobile devices, robots, and sensors, exchange information …
Z Wang, Y Zhou, Y Shi… - IEEE Journal on Selected …, 2022 - ieeexplore.ieee.org
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 …