The FedJam dataset is a multimodal dataset for jamming detection and classification in wireless networks, combining time–frequency spectrogram images with
cross-layer network KPI time series. Each sample includes aligned vision and time-series modalities, allowing joint analysis of physical-layer signal behavior
and network-layer performance. The data are collected from a real over-the-air experimental testbed, under a variety of operating conditions, including… See the full description on the dataset page:
https://huggingface.co/datasets/panitsasi/FedJam.
