318 citations · 1k across the 84 of their papers we have counts for
13 papers · 1 filter
An Asymptotically MSE-Optimal Estimator based on Gaussian Mixture Models
Michael Koller, Benedikt Fesl, Nurettin Turan +1
This paper investigates a channel estimator based on Gaussian mixture models (GMMs) in the context of linear inverse problems with additive Gaussian noise. We fit a GMM to given ch…
An Asymptotically Optimal Approximation of the Conditional Mean Channel Estimator based on Gaussian Mixture Models
Michael Koller, Benedikt Fesl, Nurettin Turan +1
This paper investigates a channel estimator based on Gaussian mixture models (GMMs). We fit a GMM to given channel samples to obtain an analytic probability density function (PDF)…
CSI Clustering with Variational Autoencoding
Michael Baur, Michael Würth, Michael Koller +2
The model order of a wireless channel plays an important role for a variety of applications in communications engineering, e.g., it represents the number of resolvable incident wav…
Distributed Joint Multi-cell Optimization of IRS Parameters with Linear Precoders
Reinhard Wiesmayr, Michael Honig, Michael Joham +1
We present distributed methods for jointly optimizing Intelligent Reflecting Surface (IRS) phase-shifts and beamformers in a cellular network. The proposed schemes require knowledg…
Learning a Compressive Sensing Matrix with Structural Constraints via Maximum Mean Discrepancy Optimization
Michael Koller, Wolfgang Utschick
We introduce a learning-based algorithm to obtain a measurement matrix for compressive sensing related recovery problems. The focus lies on matrices with a constant modulus constra…
Centralized Learning of the Distributed Downlink Channel Estimators in FDD Systems using Uplink Data
B. Fesl, N. Turan, M. Koller +2
In this work, we propose a convolutional neural network (CNN) based low-complexity approach for downlink (DL) channel estimation (CE) in frequency division duplex (FDD) systems. In…
Unsupervised Learning of Adaptive Codebooks for Deep Feedback Encoding in FDD Systems
Nurettin Turan, Michael Koller, Samer Bazzi +2
In this work, we propose a joint adaptive codebook construction and feedback generation scheme in frequency division duplex (FDD) systems. Both unsupervised and supervised deep lea…
Classification and Uncertainty Quantification of Corrupted Data using Semi-Supervised Autoencoders
Philipp Joppich, Sebastian Dorn, Oliver De Candido +2
Parametric and non-parametric classifiers often have to deal with real-world data, where corruptions like noise, occlusions, and blur are unavoidable - posing significant challenge…
ChainNet: Neural Network-Based Successive Spectral Analysis
Andreas Barthelme, Wolfgang Utschick
We discuss a new neural network-based direction of arrival estimation scheme that tackles the estimation task as a multidimensional classification problem. The proposed estimator u…
Novelty Detection and Analysis of Traffic Scenario Infrastructures in the Latent Space of a Vision Transformer-Based Triplet Autoencoder
Jonas Wurst, Lakshman Balasubramanian, Michael Botsch +1
Detecting unknown and untested scenarios is crucial for scenario-based testing. Scenario-based testing is considered to be a possible approach to validate autonomous vehicles. A tr…
A Low-Complexity MIMO Channel Estimator with Implicit Structure of a Convolutional Neural Network
B. Fesl, N. Turan, M. Koller +1
A low-complexity convolutional neural network estimator which learns the minimum mean squared error channel estimator for single-antenna users was recently proposed. We generalize…
Learning the CSI Denoising and Feedback Without Supervision
Valentina Rizzello, Wolfgang Utschick
In this work, we develop a joint denoising and feedback strategy for channel state information in frequency division duplex systems. In such systems, the biggest challenge is the o…
Learning the CSI Recovery in FDD Systems
Wolfgang Utschick, Valentina Rizzello, Michael Joham +2
We propose an innovative machine learning-based technique to address the problem of channel acquisition at the base station in frequency division duplex systems. In this context, t…