A Gram-Attention Learning Framework for Spatially Non-Stationary Channel Estimation
A signal processing and deep learning co-design framework, where data-driven JAS parallel support detection is followed by least-squares (LS)-based channel reconstruction and a Gram-attention module that incorporates the Gram matrix as a physical prior to guide feature purification, enabling the network to suppress lea...