Automatic Channel Coding Recognition Based on DeepVGG

This paper proposes a deep learning-based automatic channel coding recognition method. Channel coding is a crucial technology in wireless communication systems that enhances communication quality through error correction, ensuring reliable data transmission. To overcome the limitations of traditional one-dimensional data processing methods, this study utilizes a DeepVGG model to convert one-dimensional channel coding data into a two-dimensional format, thereby improving recognition performance. The proposed method maintains high recognition accuracy even in low SNR environments and shows an average performance improvement of over 10% compared to TextCNN and BiLSTM-CNN models. Notably, it demonstrates superior classification performance for seven types of channel coding and has the potential to contribute to real-time channel coding recognition in communication systems.