Near Field

Near-field research focuses on phenomena occurring at distances where the wavefront is significantly curved, unlike the simplified far-field approximation. Current research emphasizes developing efficient algorithms, often employing deep learning models like convolutional neural networks and LISTA, to address challenges in near-field beamforming, imaging, and channel estimation across diverse applications such as wireless communication, radar, and audio rendering. These advancements improve accuracy and reduce computational overhead in various fields, leading to more robust and efficient systems. The impact spans improved wireless communication technologies, enhanced medical imaging capabilities, and more realistic virtual and augmented reality experiences.