Author

Wolfgang Utschick

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Preprint Sep 2026

OTFS Channel Estimation Utilizing Sparse Bayesian Generative Modelling

This work establishes the OTFS-CSGMM framework as a promising solution for high mobility wireless channel estimation by employing a compressive sensing (CS)-based sparse Bayesian generative model (SBGM), namely the recently introduced compressive sensing Gaussian mixture model (CSGMM).

Louis Anseaume, Benedikt Böck, Franz Weisser et al. · 0 citations

Preprint Jul 2026

Efficient Channel Prediction based on Gram-Square-Root Factorization using GMMs

This work proposes a Gaussian mixture model (GMM)-based prediction framework for MIMO-orthogonal frequency-division multiplexing channels under partial feedback using Gram-square-root factorization, and introduces an efficient parameter reduction technique that exploits structured covariance matrices, significantly low...

Kathrin Klein, Amar Kasibovic, M. Joham et al. · 0 citations