Channel Simulator

Channel simulators are computational models that recreate wireless communication channels, aiming to accurately predict signal propagation for various applications like indoor positioning and vehicular communication. Current research focuses on improving simulator efficiency and accuracy, particularly through integrating machine learning techniques like semi-supervised learning and leveraging data from diverse sources such as cameras and 3D models to create more realistic digital twins of environments. These advancements are crucial for optimizing the design and performance of wireless systems, especially in complex scenarios like dense urban areas and indoor spaces, by reducing the need for extensive and costly real-world measurements.