Channel Estimation

Channel estimation aims to accurately determine the characteristics of a communication channel, enabling reliable data transmission. Current research heavily focuses on improving estimation accuracy and efficiency using deep learning models, such as convolutional and recurrent neural networks, often combined with traditional algorithms like expectation-maximization and belief propagation, or leveraging generative models like diffusion models and Gaussian mixture models. These advancements are crucial for enhancing the performance of various wireless communication systems, including massive MIMO, integrated sensing and communication, and the Internet of Things, by reducing pilot overhead and improving robustness in challenging environments.