4 citations · 6 across the 32 of their papers we have counts for
15 papers · 1 filter
Statistical Precoder Design in Multi-User Systems via Graph Neural Networks and Generative Modeling
Nurettin Turan, Srikar Allaparapu, Donia Ben Amor +3
This letter proposes a graph neural network (GNN)-based framework for statistical precoder design that leverages model-based insights to compactly represent statistical knowledge,…
Decoupling Networks and Super-Quadratic Gains for RIS Systems with Mutual Coupling
Dominik Semmler, Josef A. Nossek, Michael Joham +2
We propose decoupling networks for the reconfigurable intelligent surface (RIS) array as a solution to benefit from the mutual coupling between the reflecting elements. In particul…
Sparse Bayesian Generative Modeling for Compressive Sensing
Benedikt Böck, Sadaf Syed, Wolfgang Utschick
This work addresses the fundamental linear inverse problem in compressive sensing (CS) by introducing a new type of regularizing generative prior. Our proposed method utilizes idea…
Robust Precoding for FDD MISO Systems via Minorization Maximization
Donia Ben Amor, Michael Joham, Wolfgang Utschick
In this work, we propose an approach to robust precoder design based on a minorization maximization technique that optimizes a surrogate function of the achievable spectral efficie…
Bilinear Precoder Based Efficient Rate Splitting Method in FDD Systems
Sadaf Syed, Donia Ben Amor, Michael Joham +1
In this work, we propose a low-cost rate splitting (RS) technique for a multi-user multiple-input single-output (MISO) system operating in frequency division duplex (FDD) mode. The…
Low Complexity Rate Splitting Approach in RIS-Aided Systems Based on Channel Statistics
Sadaf Syed, Michael Joham, Wolfgang Utschick
Rate splitting multiple access (RSMA) and reconfigurable intelligent surface (RIS) are two prospective technologies for improving the spectral and energy efficiency in future wirel…
Addressing Pilot Contamination in Channel Estimation with Variational Autoencoders
Amar Kasibovic, Benedikt Fesl, Michael Baur +1
Pilot contamination (PC) is a well-known problem that affects massive multiple-input multiple-output (MIMO) systems. When frequency and pilots are reused between different cells, P…
Nonlinear Precoding in the RIS-Aided MIMO Broadcast Channel
Dominik Semmler, Michael Joham, Wolfgang Utschick
We propose to use Tomlinson-Harashima Precoding (THP) for the reconfigurable intelligent surface (RIS)-aided multiple-input multiple-output (MIMO) broadcast channel where we assume…
Feedback Design with VQ-VAE for Robust Precoding in Multi-User FDD Systems
Nurettin Turan, Michael Baur, Jianqing Li +1
In this letter, we propose a vector quantized-variational autoencoder (VQ-VAE)-based feedback scheme for robust precoder design in multi-user frequency division duplex (FDD) system…
A Versatile Pilot Design Scheme for FDD Systems Utilizing Gaussian Mixture Models
Nurettin Turan, Benedikt Böck, Benedikt Fesl +3
In this work, we propose a Gaussian mixture model (GMM)-based pilot design scheme for downlink (DL) channel estimation in single- and multi-user multiple-input multiple-output (MIM…
Evaluation Metrics and Methods for Generative Models in the Wireless PHY Layer
Michael Baur, Nurettin Turan, Simon Wallner +1
Generative models are typically evaluated by direct inspection of their generated samples, e.g., by visual inspection in the case of images. Further evaluation metrics like the Fré…
Linear and Nonlinear MMSE Estimation in One-Bit Quantized Systems under a Gaussian Mixture Prior
Benedikt Fesl, Wolfgang Utschick
We present new fundamental results for the mean square error (MSE)-optimal conditional mean estimator (CME) in one-bit quantized systems for a Gaussian mixture model (GMM) distribu…
A Statistical Characterization of Wireless Channels Conditioned on Side Information
Benedikt Böck, Michael Baur, Nurettin Turan +2
Statistical prior channel knowledge, such as the wide-sense-stationary-uncorrelated-scattering (WSSUS) property, and additional side information both can be used to enhance physica…
Reliable Trajectory Prediction and Uncertainty Quantification with Conditioned Diffusion Models
Marion Neumeier, Sebastian Dorn, Michael Botsch +1
This work introduces the conditioned Vehicle Motion Diffusion (cVMD) model, a novel network architecture for highway trajectory prediction using diffusion models. The proposed mode…
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)…