[2602.04083] Structure-Informed Estimation for Pilot-Limited MIMO Channels via Tensor Decomposition

Electrical Engineering and Systems Science > Signal Processing arXiv:2602.04083 (eess) [Submitted on 3 Feb 2026 (v1), last revised 2 Mar 2026 (this version, v2)] Title:Structure-Informed Estimation for Pilot-Limited MIMO Channels via Tensor Decomposition Authors:Alexandre Barbosa de Lima View a PDF of the paper titled Structure-Informed Estimation for Pilot-Limited MIMO Channels via Tensor Decomposition, by Alexandre Barbosa de Lima View PDF HTML (experimental) Abstract:Accurate channel state information in wideband multiple-input multiple-output (MIMO) systems is fundamentally constrained by pilot overhead, a challenge that intensifies as antenna counts and bandwidths scale toward 6G. This paper proposes a structure-informed hybrid estimator that formulates pilot-limited MIMO channel estimation as low-rank tensor completion from sparse pilot observations -- a severely underdetermined inverse problem that prior tensor approaches avoid by assuming fully observed received signal tensors. Canonical polyadic~(CP) and Tucker decompositions are comparatively analyzed: CP excels for specular channels whose rank-one multipath structure matches the CP parameterization exactly, while Tucker provides greater numerical stability at extreme pilot scarcity where CP exhibits heavy-tail divergence. A lightweight 3D U-Net learns residual components beyond the dominant low-rank structure, compensating for diffuse scattering and hardware non-idealities that algebraic priors alone cannot capt...