Analysis and optimization of wireless federated learning with data heterogeneity

X Han, J Li, W Chen, Z Mei, K Wei… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
With the rapid proliferation of smart mobile devices, federated learning (FL) has been widely
considered for application in wireless networks for distributed model training. However, data …

Energy-efficient clustering to address data heterogeneity in federated learning

Y Luo, X Liu, J Xiu - ICC 2021-IEEE International Conference …, 2021 - ieeexplore.ieee.org
Federated Learning (FL) is a promising distributed learning paradigm and has gained recent
attention from both academia and industry. One challenge in FL is that when local data …

Scalable hierarchical over-the-air federated learning

SM Azimi-Abarghouyi, V Fodor - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
When implementing hierarchical federated learning over wireless networks, scalability
assurance and the ability to handle both interference and device data heterogeneity are …

Over-the-air aggregation for federated learning: Waveform superposition and prototype validation

H Guo, Y Zhu, H Ma, VKN Lau, K Huang… - Journal of …, 2021 - ieeexplore.ieee.org
In this paper, we develop an orthogonal frequency-division multiplexing (OFDM)-based over-
the-air (OTA) aggregation solution for wireless federated learning (FL). In particular, the local …

Federated learning over noisy channels

X Wei, C Shen - ICC 2021-IEEE International Conference on …, 2021 - ieeexplore.ieee.org
Does Federated Learning (FL) work when both uplink and downlink communications have
errors? How much communication noise can FL handle and what is its impact to the learning …

Over-the-air decentralized federated learning

Y Shi, Y Zhou, Y Shi - 2021 IEEE International Symposium on …, 2021 - ieeexplore.ieee.org
In this paper, we consider decentralized federated learning (FL) over wireless networks,
where over-the-air computation (AirComp) is adopted to facilitate the local model consensus …

Performance optimization of federated learning over wireless networks

M Chen, Z Yang, W Saad, C Yin… - 2019 IEEE global …, 2019 - ieeexplore.ieee.org
In this paper, the problem of training federated learning (FL) algorithms over a realistic
wireless network is studied. In particular, in the considered model, wireless users perform an …

Federated learning with additional mechanisms on clients to reduce communication costs

X Yao, T Huang, C Wu, RX Zhang, L Sun - arXiv preprint arXiv:1908.05891, 2019 - arxiv.org
Federated learning (FL) enables on-device training over distributed networks consisting of a
massive amount of modern smart devices, such as smartphones and IoT (Internet of Things) …

Federated learning via unmanned aerial vehicle

M Fu, Y Shi, Y Zhou - IEEE Transactions on Wireless …, 2023 - ieeexplore.ieee.org
Federated learning (FL) has emerged as a promising alternative to centralized machine
learning for exploiting large amounts of data generated by networks while ensuring data …

Hierarchical Over-the-Air Federated Learning with Awareness of Interference and Data Heterogeneity

SM Azimi-Abarghouyi, V Fodor - arXiv preprint arXiv:2401.01442, 2024 - arxiv.org
When implementing hierarchical federated learning over wireless networks, scalability
assurance and the ability to handle both interference and device data heterogeneity are …