RFSSC: Radio-Frequency Spectrum-Sharing Challenge Data for ML

The First RF Spectrum-Sharing Challenge was held in 2024-2025, culminating in announcing the winner AiRANACULUS on January 30, 2025. These data were used in the contest, which was co-sponsored by the United States Air Force Research Laboratory (AFRL) and the National Security Innovation Network (NSIN). The challenge was a data-centric contest open to US academic and industrial organizations intended to spur innovation in machine learning and signal processing for automatic radio-frequency scene analysis (RFSA).

Use Cases

• Developing machine learning models for automatic radio-frequency scene analysis (RFSA) based on the challenge's focus.
• Benchmarking signal processing algorithms for spectrum-sharing scenarios using the contest data.
• Training models to identify and classify RF signals in a shared spectrum environment as implied by the challenge goal.

Strengths

• Data originates from a challenge co-sponsored by authoritative organizations: the United States Air Force Research Laboratory (AFRL) and the National Security Innovation Network (NSIN).
• The dataset is associated with a named, time-bound event: the First RF Spectrum-Sharing Challenge held in 2024-2025, with a winner announced on January 30, 2025.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment for large-scale model training.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

Texas Data Repository Harvested Dataverse, author Chad Spooner.

Collection Method

Likely collected or generated for the First RF Spectrum-Sharing Challenge.

Time Range

Associated with the 2024-2025 challenge period.

Freshness

Last updated 2025-10 06:53:29; freshness should be verified.

Geography

Challenge was open to US organizations; specific data geography is unknown.