Modeling and Analysis of Intermittent Federated Learning Over Cellular-Connected UAV Networks

Chun Hung Liu, Di Chun Liang, Rung Hung Gau, Lu Wei

研究成果: Conference contribution同行評審

摘要

Federated learning (FL) is a promising distributed learning technique particularly suitable for wireless learning scenarios since it can accomplish a learning task without raw data transportation so as to preserve data privacy and lower network resource consumption. However, current works on FL over wireless networks do not profoundly study the fundamental performance of FL over wireless networks that suffers from communication outage due to channel impairment and network interference. To accurately exploit the performance of FL over wireless networks, this paper proposes a novel intermittent FL model over a cellular-connected Unmanned Aerial Vehicle (UAV) network, which characterizes communication outage from UAV (clients) to their server and data heterogeneity among the datasets at UAVs. We propose an analytically tractable framework to derive the uplink outage probability and use it to devise a simulation-based approach so as to evaluate the performance of the proposed intermittent FL model. Our findings reveal how the intermittent FL model is impacted by uplink communication outage and UAV deployment. Extensive numerical simulations are provided to show the consistency between the simulated and analytical performances of the proposed intermittent FL model.

原文English
主出版物標題2022 IEEE 95th Vehicular Technology Conference - Spring, VTC 2022-Spring - Proceedings
發行者Institute of Electrical and Electronics Engineers Inc.
ISBN(電子)9781665482431
DOIs
出版狀態Published - 2022
事件95th IEEE Vehicular Technology Conference - Spring, VTC 2022-Spring - Helsinki, Finland
持續時間: 19 6月 202222 6月 2022

出版系列

名字IEEE Vehicular Technology Conference
2022-June
ISSN(列印)1550-2252

Conference

Conference95th IEEE Vehicular Technology Conference - Spring, VTC 2022-Spring
國家/地區Finland
城市Helsinki
期間19/06/2222/06/22

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