Channel Measurement

Channel measurement focuses on characterizing the propagation of radio waves between transmitter and receiver, aiming to accurately model signal strength and delay for improved wireless system design and performance. Current research emphasizes developing efficient and accurate channel prediction methods, leveraging machine learning techniques like neural networks and gradient-based optimization alongside traditional ray tracing, to overcome computational limitations and handle increasingly complex scenarios. These advancements are crucial for optimizing resource allocation in 5G and beyond, enabling applications such as precise localization, activity recognition through micro-Doppler analysis, and real-time traffic classification even with encrypted data.