Radio Frequency AI/ML (RF AI/ML) for Wireless Spectrum Sensing and Awareness
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Intelligent Sensors".
Deadline for manuscript submissions: 1 September 2025
Special Issue Editors
Interests: digital signal processing; wireless spectrum sensing; radio frequency machine learning; adversarial machine learning
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
In recent years, the rapid growth in AI/ML technologies in other modalities (images, text, audio, video, etc.) has led to an increased interest in these technologies for use in the radio frequency domain. While this field of research is becoming ever more popular, primarily due to its promise in solving commercial spectrum scarcity issues and its inherent importance in military communications, a vast majority of the research to date has been focused on the transfer of these technologies/solutions directly to RF applications.
In this Special Issue, we will collate original research on recent advances, technologies, solutions, applications, and challenges in the field of radio frequency spectrum sensing and awareness that go beyond transfer learning and investigate novel research from an RF-domain-centric perspective.
Potential topics include, but are not limited to, the following:
- RF AI/ML Applications
- Spectrum Scanning and Prioritization;
- Signal Detection;
- Signal Classification/Identification;
- Specific Emitter Identification;
- Co-Channel Signal Separation;
- Multi-Antenna Sensing;
- Collaborative Sensing.
- RF AI/ML Datasets
- Modality Investigations (Image-based, IQ-based, feature-based, etc.);
- “Cyborg” Dataset Generation (intelligent use of synthetic and real data);
- Datasets/Tools (contribution is the dataset/tool with numerical experiments as baselines).
- RF AI/ML Security
- Adversarial Attacks;
- Adversarial Hardening.
- RF AI/ML Trust
- Uncertainty Quantification;
- Explainability.
Dr. William Headley
Dr. Stephen Adams
Guest Editors
Manuscript Submission Information
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Keywords
- radio frequency
- spectrum sensing
- RF AI/ML
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