11 citations · 22 across the 17 of their papers we have counts for
8 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…
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…
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…
Channel-Adaptive Pilot Design for FDD-MIMO Systems Utilizing Gaussian Mixture Models
Nurettin Turan, Benedikt Fesl, Benedikt Böck +2
In this work, we propose to utilize Gaussian mixture models (GMMs) to design pilots for downlink (DL) channel estimation in frequency division duplex (FDD) systems. The GMM capture…
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)…
Wireless Channel Prediction via Gaussian Mixture Models
Nurettin Turan, Benedikt Böck, Kai Jie Chan +5
In this work, we utilize a Gaussian mixture model (GMM) to capture the underlying probability density function (PDF) of the channel trajectories of moving mobile terminals (MTs) wi…