46 citations · 112 across the 29 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,…
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…
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…
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…
Limited Feedback on Measurements: Sharing a Codebook or a Generative Model?
Nurettin Turan, Benedikt Fesl, Michael Joham +5
Discrete Fourier transform (DFT) codebook-based solutions are well-established for limited feedback schemes in frequency division duplex (FDD) systems. In recent years, data-aided…