Federated Learning with Privacy-Preserving Incentives for Aerial Computing Networks
Peng Wang,
Yi Yang,
Wen Sun
et al.
Abstract:With the help of artificial intelligence (AI) model, aerial computing can help analyze and predict the network dynamics and support intelligent decision-making to improve the performance of 6G space-air-ground integrated networks. Federated learning has been proposed to tackle the challenges of limited energy and data shortage for the application of AI models in aerial computing networks. A critical problem of FL for aerial computing is the lack of incentives due to privacy concerns. On the one hand, the infor… Show more
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