Channel Knowledge

Channel knowledge, encompassing the characterization and prediction of communication channel properties, aims to improve the efficiency and reliability of wireless systems. Current research focuses on learning-based approaches, employing neural networks (including implicit neural representations and autoencoders) and reinforcement learning algorithms to map locations to channel responses, construct channel knowledge maps, and optimize resource allocation (e.g., dynamic channel allocation). These advancements are crucial for enabling environment-aware communication, improving signal processing techniques, and ultimately enhancing the performance and robustness of wireless networks in diverse and challenging environments.