works on

From the 1 of 11 linked papers with an AI index.

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20242026
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11 papers

eess.SP2026

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

Kathrin Klein, Amar Kasibovic, Michael Joham +2

The paper proposes a Gaussian mixture model framework that uses Gram‑square‑root factorization to efficiently predict MIMO‑OFDM channel state information from partial feedback, red…

cs.IT2026

Is Lattice Reduction Necessary for Vector Perturbation Precoding?

Dominik Semmler, Wolfgang Utschick, Michael Joham

Vector perturbation (VP) precoding is an effective nonlinear precoding technique in the downlink (DL) with modulo channels, providing an approximation of dirty paper coding (DPC) w…

eess.SP2026

On the Optimality of Rate Balancing for Max-Min Fair Multicasting

Sadaf Syed, Wolfgang Utschick, Michael Joham

The max-min fair (MMF) multicasting problem is known to be NP-hard. In this work, we analytically derive the optimal solution to this NP-hard problem and establish the equivalence…

cs.IT2025

Precoder Design in Multi-User FDD Systems with VQ-VAE and GNN

Srikar Allaparapu, Michael Baur, Benedikt Böck +2

Robust precoding is efficiently feasible in frequency division duplex (FDD) systems by incorporating the learnt statistics of the propagation environment through a generative model…

eess.SP2025

Sum-Rate Optimisation of a Multi-User STAR-RIS-Aided System with Low Complexity

Sadaf Syed, Wolfgang Utschick, Michael Joham

Reconfigurable intelligent surface (RIS) is a promising technology for future wireless communication systems. However, the conventional RIS can only reflect the incident signal. He…

cs.LG2025

On the Asymptotic Mean Square Error Optimality of Diffusion Models

Benedikt Fesl, Benedikt Böck, Florian Strasser +3

Diffusion models (DMs) as generative priors have recently shown great potential for denoising tasks but lack theoretical understanding with respect to their mean square error (MSE)…