We study federated learning (FL) at the wireless edge, where power-limited devices with local datasets collaboratively train a joint model with the help of a remote parameter server …
The aim of this paper is to propose a novel dynamic resource allocation strategy for energy- efficient federated learning at the wireless network edge, with latency and learning …
We study federated learning (FL) at the wireless edge, where power-limited devices with local datasets train a joint model with the help of a remote parameter server (PS). We …
There is an increasing interest in a new machine learning technique called Federated Learning, in which the model training is distributed over mobile user equipments (UEs), and …
J Yun, Y Oh, YS Jeon, HV Poor - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
In this paper, we propose a communication-efficient federated learning (FL) framework to enhance the convergence rate of FL under limited uplink capacity. The core idea of our …
JP Hong, S Park, W Choi - IEEE Transactions on Wireless …, 2023 - ieeexplore.ieee.org
This paper proposes an over-the-air aggregation framework for federated learning (FL) in broadband wireless networks where not only edge devices but also a base station (BS) has …
N Zhang, M Tao - 2020 IEEE International Conference on …, 2020 - ieeexplore.ieee.org
To enable communication-efficient federated learning, fast model aggregation can be designed using over-the-air computation (AirComp). In order to implement a reliable and …
J Wang, M Dong, B Liang, G Boudreau… - … -IEEE Conference on …, 2022 - ieeexplore.ieee.org
We consider federated learning in a wireless edge network, where multiple power-limited mobile devices collaboratively train a global model, using their local data with the assistance …
J Zheng, W Ni, H Tian, D Gündüz… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Under the organization of the base station (BS), wireless federated learning (FL) enables collaborative model training among multiple devices. However, the BS is merely responsible …