A Confidence-Aware Semi-Supervised Learning Framework for Automatic Modulation Recognition
Automatic modulation recognition (AMR) is a cornerstone of dynamic spectrum allocation and cognitive radio. Despite the promise of deep learning-based methods, their reliance on large labeled datasets limits their practicality in scenarios with scarce labeled samples. To address this, we propose a confidence-aware semi...