A Benchmark Study of RF Anomaly Detection Models on NVIDIA Jetson Orin Nano
Abstract
Radio frequency (RF) communication has become essential for critical infrastructure including healthcare, transportation, and government services. While numerous ML models have been developed for RF security, many require cloud computing due to computational demands, introducing latency and privacy concerns. With advances in AI edge computing, there is growing opportunity to deploy models directly on edge devices. This work presents the first benchmark study evaluating ML models for RF anomaly detection on the NVIDIA Jetson Orin Nano platform.
Fields of Study & Subjects
Wireless Signal Modulation Classification
Molecular Communication and Nanonetworks
Network Security and Intrusion Detection
Publication details
- Journal / source
- 2026 IEEE 23rd Consumer Communications & Networking Conference (CCNC)
- Publisher
- IEEE
- Pages
- 1–2
- Publication date
- 9 January 2026