Problem
Research questions and friction points this paper is trying to address.
Wi-Fi spectral scan
RF jamming dataset
commodity Wi-Fi hardware
spectrum monitoring
WiFiSpectralJam: A Large-Scale Open Wi-Fi Spectral Scan Dataset with Controlled RF Jamming
🤖 AI Summary
This study addresses the critical scarcity of large-scale Wi-Fi spectrum and controlled interference datasets by developing an open scanning platform based on Raspberry Pi CM4 and QCA9880 commercial network interface cards. The research collected 520 million observations encompassing background noise and controlled interference scenarios across 2.4 GHz and 5 GHz bands, resulting in the release of a 14.52 GB dataset accompanied by comprehensive metadata and reproducible protocols. This work establishes a vital benchmark for spectrum sensing using commercial off-the-shelf hardware, filling a significant gap in existing resources. Consequently, the released dataset effectively facilitates key tasks including radio frequency interference detection, distribution shift evaluation, and machine learning model validation, thereby advancing empirical research in wireless spectrum analysis.
📝 Abstract
WiFiSpectralJam is a Wi-Fi spectral-scan dataset comprising 14.52 GB, 96,090 CSV files, and 522,771,130 ordered spectral observations using commodity Wi-Fi sensing hardware. Measurements were acquired with a Raspberry Pi Compute Module 4 equipped with a Qualcomm Atheros QCA9880 802.11ac network interface and the Linux ath10k spectral-scan interface. The dataset spans active and passive scan modalities across the 2.4 and 5 GHz bands and includes real-world benign background captures, benign RF-chamber floor captures, and controlled RF-jamming captures generated with a HackRF One. Jamming conditions vary by transmit power, target channel, and, in the active subset, waveform type. The release provides the raw spectral-scan records together with a file-level metadata manifest, derived spectral-summary features, validation outputs, and reproducible benchmark protocols. These resources support reuse in RF interference characterisation, jamming detection, spectrum monitoring, distribution-shift evaluation, and machine-learning studies using commodity-NIC spectral measurements. The dataset is publicly available at: https://www.kaggle.com/datasets/daniaherzalla/radio-frequency-jamming/data.
Innovation
Methods, ideas, or system contributions that make the work stand out.
Wi-Fi Spectral Scan
Controlled RF Jamming
Commodity Hardware
Open Dataset
Reproducible Benchmark
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