AMTIDIN applies adversarial training and adaptive task coefficients in a multi-task setup to jointly solve interference detection, modulation identification, and interference identification, outperforming baselines especially at low SNR and with limited data.
Deep learning models for wireless signal classification with distributed low-cost spectrum sensors
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Joint Interference Detection and Identification via Adversarial Multi-task Learning
AMTIDIN applies adversarial training and adaptive task coefficients in a multi-task setup to jointly solve interference detection, modulation identification, and interference identification, outperforming baselines especially at low SNR and with limited data.