June 5, 2024, 4:42 a.m. | Sravan Reddy Chintareddy, Keenan Roach, Kenny Cheung, Morteza Hashemi

cs.LG updates on arXiv.org arxiv.org

arXiv:2406.01727v1 Announce Type: new
Abstract: In this paper, we propose a data-driven framework for collaborative wideband spectrum sensing and scheduling for networked unmanned aerial vehicles (UAVs), which act as the secondary users (SUs) to opportunistically utilize detected "spectrum holes". Our overall framework consists of three main stages. Firstly, in the model training stage, we explore dataset generation in a multi-cell environment and training a machine learning (ML) model using the federated learning (FL) architecture. Unlike the existing studies on FL …

abstract act aerial arxiv collaborative cs.lg cs.ma data data-driven eess.sp federated learning framework paper scheduling sensing spectrum stages systems type unmanned aerial vehicles vehicles

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