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eess.SP2023

OFDM-based Waveforms for Joint Sensing and Communications Robust to Frequency Selective IQ Imbalance

Oliver Lang, Christian Hofbauer, Moritz Tockner +3

Orthogonal frequency-division multiplexing (OFDM) is a promising waveform candidate for future joint sensing and communication systems. It is well known that the OFDM waveform is v…

eess.SP2023

Bi-Linear Homogeneity Enforced Calibration for Pipelined ADCs

Matthias Wagner, Oliver Lang, Esmaeil Kavousi Ghafi +3

Pipelined analog-to-digital converters (ADCs) are key enablers in many state-of-the-art signal processing systems with high sampling rates. In addition to high sampling rates, such…

eess.SP2023

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…

cs.LG2023

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…

cs.IT2023

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…