69 citations · 377 across the 27 of their papers we have counts for
28 papers
SICNN: Soft Interference Cancellation Inspired Neural Network Equalizers
Stefan Baumgartner, Oliver Lang, Mario Huemer
In recent years data-driven machine learning approaches have been extensively studied to replace or enhance traditionally model-based processing in digital communication systems. I…
Analysis and Compensation of Carrier Frequency Offset Impairments in Unique Word OFDM
Christian Hofbauer, Werner Haselmayr, Hans-Peter Bernhard +1
Unique Word-orthogonal frequency division multiplexing (UW-OFDM) is known to provide various performance benefits over conventional cyclic prefix (CP) based OFDM. Most important, U…
Complex-valued Adaptive System Identification via Low-Rank Tensor Decomposition
Oliver Ploder, Christina Auer, Oliver Lang +2
Machine learning (ML) and tensor-based methods have been of significant interest for the scientific community for the last few decades. In a previous work we presented a novel tens…
Doppler-Division Multiplexing for MIMO OFDM Joint Sensing and Communications
Oliver Lang, Christian Hofbauer, Reinhard Feger +1
A promising waveform candidate for future joint sensing and communication systems is orthogonal frequencydivision multiplexing (OFDM). For such systems, supporting multiple transmi…
Enhanced Nonlinear System Identification by Interpolating Low-Rank Tensors
Christina Auer, Thomas Paireder, Oliver Ploder +2
Function approximation from input and output data is one of the most investigated problems in signal processing. This problem has been tackled with various signal processing and ma…
Neural Network Approaches for Data Estimation in Unique Word OFDM Systems
Stefan Baumgartner, Gergő Bognár, Oliver Lang +1
Data estimation is conducted with model-based estimation methods since the beginning of digital communications. However, motivated by the growing success of machine learning, curre…
Diagnostic Quality Assessment for Low-Dimensional ECG Representations
Péter Kovács, Carl Böck, Thomas Tschoellitsch +2
There have been several attempts to quantify the diagnostic distortion caused by algorithms that perform low-dimensional electrocardiogram (ECG) representation. However, there is n…
Homogeneity Enforced Calibration of Stage Nonidealities for Pipelined ADCs
Matthias Wagner, Oliver Lang, Thomas Bauernfeind +1
Pipelined analog-to-digital converters (ADCs) are fundamental components of various signal processing systems requiring high sampling rates and a high linearity. Over the past year…
ECG Beat Representation and Delineation by means of Variable Projection
Carl Böck, Péter Kovács, Pablo Laguna +2
The electrocardiogram (ECG) follows a characteristic shape, which has led to the development of several mathematical models for extracting clinically important information. Our mai…
Efficient Majority Voting in Digital Hardware
Stefan Baumgartner, Mario Huemer, Michael Lunglmayr
In recent years, machine learning methods became increasingly important for a manifold number of applications. However, they often suffer from high computational requirements impai…
Spline-Based Adaptive Cancellation of Even-Order Intermodulation Distortions in LTE-A/5G RF Transceivers
Thomas Paireder, Christian Motz, Mario Huemer
Radio frequency transceivers operating in in-band full-duplex or frequency-division duplex mode experience strong transmitter leakage. Combined with receiver nonlinearities, this c…
VPNet: Variable Projection Networks
Péter Kovács, Gergő Bognár, Christian Huber +1
We introduce VPNet, a novel model-driven neural network architecture based on variable projection (VP). Applying VP operators to neural networks results in learnable features, inte…
On the Inclusion and Utilization of Pilot Tones in Unique Word OFDM
Christian Hofbauer, Werner Haselmayr, Hans-Peter Bernhard +1
Unique word-orthogonal frequency division multiplexing (UW-OFDM) is known to provide various performance benefits over conventional OFDM using cyclic prefixes (CP). Most important,…
A Linear State Space Model for Photoacoustic Imaging in an Acoustic Attenuating Media
Oliver Lang, Peter Kovacs, Christian Motz +3
In photoacoustic imaging, ultrasound waves generated by a temperature rise after illumination of light absorbing structures are measured on the sample surface. These measurements a…
A Robust Nonlinear RLS Type Adaptive Filter for Second-Order-Intermodulation Distortion Cancellation in FDD LTE and 5G Direct Conversion Transceivers
Andreas Gebhard, Oliver Lang, Michael Lunglmayr +7
Transceivers operating in frequency division duplex experience a transmitter leakage (TxL) signal into the receiver due to the limited duplexer stop-band isolation. This TxL signal…
Knowledge-Aided Kaczmarz and LMS Algorithms
Michael Lunglmayr, Oliver Lang, Mario Huemer
The least mean squares (LMS) filter is often derived via the Wiener filter solution. For a system identification scenario, such a derivation makes it hard to incorporate prior info…
Constrained Best Linear Unbiased Estimation
Oliver Lang, Mario Huemer, Markus Steindl
The least squares (LS) estimator and the best linear unbiased estimator (BLUE) are two well-studied approaches for the estimation of a deterministic but unknown parameter vector. I…
Study of Buffer-aided physical-layer network coding with ML and MMSE linear code designs for cooperative DS-CDMA systems
Jiaqi Gu, Rodrigo C. de Lamare, Mario Huemer
In this work, we propose buffer-aided physical-layer network coding (PLNC) techniques for cooperative direct-sequence code-division multiple access systems. In the proposed buffer-…
Classical Widely Linear Estimation of Real Valued Parameter Vectors in Complex Valued Environments
Oliver Lang, Mario Huemer
This work investigates the task of estimating a real valued parameter vector based on complex valued measurements in a classical set-up. The application of standard estimators in g…
Best Widely Linear Unbiased Estimator for Real Valued Parameter Vectors
Oliver Lang, Mario Huemer
For classical estimation with an underlying linear model the best linear unbiased estimator (BLUE) is usually utilized for estimating the deterministic but unknown parameter vector…
Parameter Estimation Under Model Uncertainties by Iterative Covariance Approximation
Oliver Lang, Michael Lunglmayr, Mario Huemer
We propose a novel iterative algorithm for estimating a deterministic but unknown parameter vector in the presence of model uncertainties. This iterative algorithm is based on a sy…
On the Log-Likelihood Ratio Evaluation of CWCU Linear and Widely Linear MMSE Data Estimators
Oliver Lang, Mario Huemer, Christian Hofbauer
In soft decoding of data bits, the log-likelihood ratios are evaluated from the estimated data symbols. For proper constellation diagrams such as QPSK or 16-QAM, these data symbols…
CWCU LMMSE Estimation: Prerequisites and Properties
Mario Huemer, Oliver Lang
The classical unbiasedness condition utilized e.g. by the best linear unbiased estimator (BLUE) is very stringent. By softening the "global" unbiasedness condition and introducing…
Approximate Least Squares
Michael Lunglmayr, Christoph Unterrieder, Mario Huemer
We present a novel iterative algorithm for approximating the linear least squares solution with low complexity. After a motivation of the algorithm we discuss the algorithm's prope…