Automatic Modulation Classification

Automatic Modulation Classification (AMC) aims to identify the modulation scheme used in a received signal without prior knowledge, a crucial task in various communication systems. Current research focuses on improving the robustness and efficiency of AMC, particularly using deep learning models like convolutional neural networks (CNNs) and exploring techniques such as adversarial training, knowledge distillation, and model optimization (pruning, quantization). These advancements are significant for enhancing the security and performance of wireless networks, particularly in resource-constrained edge environments and for applications like cognitive radio and spectrum management.