Data-Aided Channel Estimation and Sensing With Sparse Bayesian Learning for AFDM-ISAC System
This work develops an efficient data-aided iterative receiver, in which reliably decoded data symbols are fed back as additional pseudo-pilot information to assist channel estimation and sensing, and develops a grid evolution procedure that iteratively adjusts the virtual grids in the discrete affine Fourier domain acc...