Y Wan, Y Qu, W Ni, Y Xiang, L Gao… - … Surveys & Tutorials, 2024 - ieeexplore.ieee.org
Due to the greatly improved capabilities of devices, massive data, and increasing concern about data privacy, Federated Learning (FL) has been increasingly considered for …
S Hu, X Yuan, W Ni, X Wang… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Federated learning (FL) can suffer from communication bottlenecks when deployed in mobile networks, limiting participating clients and deterring FL convergence. In this context …
To enable wireless federated learning (FL) in communication resource-constrained networks, two communication schemes, ie, digital and analog ones, are effective solutions …
Wireless federated learning (WFL) suffers from heterogeneity prevailing in the data distributions, computing powers, and channel conditions of participating devices. This paper …
H Kim, H Nam, DJ Love - 2024 58th Annual Conference on …, 2024 - ieeexplore.ieee.org
Interest continues to grow in using federated learning (FL) for a variety of signal processing and communications applications. This paper focuses on a robust design for FL to mitigate …