arXiv:2610.36609v1 Announce Type: new Abstract: Near-field line-of-sight (LoS) channels in extremely large-scale multiple-input multiple-output (XL-MIMO) systems exhibit distinctive structural properties in the wavenumber domain. In this paper, we develop a structured wavenumber-domain channel estimation framework that first obtains an initial channel estimate using classical estimators and then refines it through a windowing-based refinement step that suppresses out-of-band noise by exploiting the localized spatial-frequency power distribution. The resulting estimate is subsequently enhanced through a convex constrained formulation that exploits the sparsity and low-rank structure of the wavenumber-domain channel. The corresponding sparsity and rank constraint bounds are selected using a conservative worst-case characterization over the relative position of the transmitter and receiver. Numerical results show that the proposed framework improves estimation accuracy, particularly at low signal-to-noise ratio, by effectively leveraging the structural properties of the wavenumber-domain channel.