Nomad: Providing Insights into the Spectrum Environment
The proliferation of transmissions in the RF spectrum demands robust and responsive signal analysis techniques to detect and label malicious activity. Traditional methods struggle to balance sensitivity and accuracy in real-time. This paper introduces Nomad, a modular system that combines global spectral pattern recognition with localized energy detection and classic signal processing methods for efficient and accurate RF analysis. Nomad's innovative architecture facilitates rapid development and deployment, while its intuitive visualizations provide actionable insights into even weak signals within complex RF environments.
Authors
- Raini Wu (ORCID: https://orcid.org/0009-0009-1550-028X)
- Richard Bell
- Srivatsan Rajagopal
- Wei Sun (ORCID: https://orcid.org/0009-0006-3333-7672)
- Dinesh Bharadia (ORCID: https://orcid.org/0000-0002-3518-4722)
- Isamu Poy (ORCID: https://orcid.org/0000-0002-4625-1310)
- Raghav Subbaraman (ORCID: https://orcid.org/0000-0001-5352-093X)
- Kewei Chen (ORCID: https://orcid.org/0000-0003-4168-0463)
- Hadi Givehchian
- Fredric Harris (ORCID: https://orcid.org/0000-0002-6984-4629)
- Gavin Roberts
- Sreevatsank Kadaveru (ORCID: https://orcid.org/0009-0008-4670-7737)
Institutions
- University of California San Diego (US)
Publication Details
- Published
- 2024-12-04
- DOI
- https://doi.org/10.1145/3636534.3698867
- Primary Topic
- Cognitive Radio Networks and Spectrum Sensing
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Intelligence Advanced Research Projects Activity