Modulation Scheme

Modulation schemes, methods for encoding information onto signals, are a crucial aspect of communication systems, with research focused on improving efficiency, robustness, and security. Current efforts involve developing novel architectures, such as efficient modulation blocks for vision networks and two-dimensional neural networks for OTFS symbol detection, as well as leveraging deep learning techniques like incremental learning for dynamic modulation recognition and split learning for privacy-preserving automatic modulation classification. These advancements aim to enhance data transmission in various applications, from mobile robotics and wireless communication to power converter optimization and spectral filling in congested RF environments, ultimately improving the reliability and capacity of communication systems.