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20152023
most citedChannel Estimation in Massive MIMO Systems

33 citations · 41 across the 13 of their papers we have counts for

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eess.SP20231 cited

Gohberg-Semencul Estimation of Toeplitz Structured Covariance Matrices and Their Inverses

Benedikt Böck, Dominik Semmler, Benedikt Fesl +2

When only few data samples are accessible, utilizing structural prior knowledge is essential for estimating covariance matrices and their inverses. One prominent example is knowing…

eess.SP2022

Variational Inference Aided Estimation of Time Varying Channels

Benedikt Böck, Michael Baur, Valentina Rizzello +1

One way to improve the estimation of time varying channels is to incorporate knowledge of previous observations. In this context, Dynamical VAEs (DVAEs) build a promising deep lear…

eess.SP2021

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…

eess.SP2019

Model Order Selection in DoA Scenarios via Cross-Entropy based Machine Learning Techniques

Andreas Barthelme, Reinhard Wiesmayr, Wolfgang Utschick

In this paper, we present a machine learning approach for estimating the number of incident wavefronts in a direction of arrival scenario. In contrast to previous works, a multilay…

eess.SP2018

User Demand Based Precoding for G.fast DSL Systems

Andreas Barthelme, Michael Joham, Rainer Strobel +1

It can be observed that the achievable rate region of a G.fast DSL system is no longer rectangular, as it is the case for vectored VDSL systems, due to stronger crosstalk couplings…