Federated Learning in 6G Non-Terrestrial Network for IoT services: From the Perspective of Perceptive Mobile Network

IEEE Network(2024)

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摘要
Recently, federated learning (FL) has been a hotspot for its capacity of data privacy protection and excellent performance under few-shot conditions for Internet of Things (IoT) services. Meanwhile, 6G non-terrestrial network (NTN) brings an effective and affordable option for enhancing IoT device connectivity. When FL meets NTN, various challenges and opportunities will emerge to promote technological evolution in the field of IoT services. Motivated by this, this paper investigates the present situations of FL in NTN from the perspective of perceptive mobile network (PMN), and discusses the open challenges for FL assisted PMN. Additionally, current opportunities are concluded from three aspects, including sensing and communication (S&C) aided learning, S&C as a task, and edge intelligence. Finally, the future directions are exploited and analyzed. This paper overviews NTN from the perspective of PMN and proposes the framework of sensing assisted FL in NTN. We hope that this article will provide some inspirations for FL and wireless communication researchers.
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关键词
Federated Learning,Non-Terrestrial Network,Perceptive Mobile Network,IoT services
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