46 citations · 151 across the 13 of their papers we have counts for
7 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…
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…
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…