Recent publications

October 2024

Time Adaptive Probabilistic Shaping for Combined Optical/THz Links

In-Ho Baek, Colja Schubert, Ronald Freund, Robert Elschner, Frederik Bart, Fred Meier, David Hellmann, Andreas Maaßen

We investigate the applicability of PAS for outdoor THz wireless links in simulations with weather-dependent loss models. Link performances are evaluated and optimal shaping entropies are determined to adjust error rates to a given FEC threshold....


October 2024

Experimental Dataset for Developing and Testing ML Models in Optical Communication Systems

Caio Marciano Santos, Colja Schubert, Johannes Fischer, Robert Emmerich, Mohammad Behnam Shariati, Pooyan Safari, Abdelrahmane Moawad

We present here a public dataset for developing and testing ML models. The dataset is developed in a laboratory setting and includes 12672 samples including data points with different modulation formats, symbol rates, distances, WDM channel...


October 2024

Causes of Outcome Learning: A causal inference-inspired machine learning approach to disentangling common combinations of potential causes of a health outcome

Andreas Rieckmann, Wojciech Samek, Sebastian Lapuschkin, Leila Arras, Piotr Dworzynski, Onyebuchi A. Arah, Naja H. Rod, Claus T. Ekstrom

Nearly all diseases are caused by different combinations of exposures. We present the Causes of Outcome Learning approach (CoOL), which seeks to discover combinations of exposures that lead to an increased risk of a specific outcome in parts of...


October 2024

SPVLoc: Semantic Panoramic Viewport Matching for 6D Camera Localization in Unseen Environments

Niklas Gard, Peter Eisert, Anna Hilsmann

We present SPVLoc, a global indoor localization method that accurately determines the six-dimensional (6D) camera pose of a query image and requires minimal scene-specific prior knowledge and no scene-specific training. Our approach employs a...


October 2024

Compact 3D Scene Representation via Self-Organizing Gaussian Grids

Wieland Morgenstern, Peter Eisert, Anna Hilsmann, Florian Tim Barthel

We introduce a compact scene representation organizing the parameters of 3D Gaussian Splatting (3DGS) into a 2D grid with local homogeneity, ensuring a drastic reduction in storage requirements without compromising visual quality during...


October 2024

Evolution of the 5G New Radio Two-Step Random Access towards 6G Unsourced MAC

Patrick Agostini, Slawomir Stanczak, Johannes Dommel, Zoran Utkovski, Andrea Munari, Federico Clazzer, Jean-Francois Chamberland, Gianluigi Liva, Krishna Narayanan, Yury Polyanskiy

This report explores the future of grant-free random access in next-generation 3GPP wireless standards, focusing on how it aligns with the unsourced multiple access channel (UMAC) model.


October 2024

Impact of Multi-Band Transmission on Optical Signal-to-Noise Ratio Measurements

Robert Emmerich

Fraunhofer HHI researchers investigate the influence error of a fixed noise bandwidth assumption (i.e., 12.5 GHz) on optical signal-to-noise ratio (OSNR) measurements in the context of multi-band transmission and propose a correction method that...


September 2024

Demonstration of a Real-Time Testbed for D-Band Integrated Sensing and Communication

Sven Wittig, Slawomir Stanczak, Michael Peter, Ramez Askar, Rodrigo Hernangómez, Amr Haj-Omar, Karen Vardanyan

The D-band, spanning 110 GHz to 170 GHz, has emerged as a relevant frequency range for future mobile communications and radar sensing applications, particularly in the context of 6G technologies. This demonstration presents a high-bandwidth,...


September 2024

BTSeg: Barlow Twins Regularization for Domain Adaptation in Semantic Segmentation

Johannes Wolf Künzel, Peter Eisert, Anna Hilsmann

We introduce BTSeg, an innovative, semi-supervised training approach enhancing semantic segmentation models in order to effectively handle a range of adverse conditions without requiring the creation of extensive new datasets. BTSeg employs a...


August 2024

Dual-Polarized Sub-THz Channel Measurements in D-Band in an Industrial Environment

Alper Schultze, Wilhelm Keusgen, Michael Peter, Ramez Askar, Taro Eichler, Mathis Schmieder

In this paper, we introduce a novel time domain (TD) correlation based channel sounder that operates in the D-band (110 GHz to 170 GHz) with which we performed dual-polarized sub-THz channel measurements in an industrial environment.


August 2024

Localization in Dynamic Indoor MIMO-OFDM Wireless Systems using Domain Adaptation

Rafail Ismayilov, Slawomir Stanczak, Renato L. G. Cavalcante

Predicting user locations in dynamic indoor wireless environments is improved by using domain adaptation techniques. This approach effectively addresses challenges such as the birth, death, and drift of scattering clusters caused by environmental...


August 2024

W-Band Beamforming Front-End Implementation and Outdoor Trials for Mobile Backhaul and Access

Mathis Schmieder, Wilhelm Keusgen, Michael Peter, Mehrnoosh Mazhar Sarmadi, Alper Schultze, Dirk Schwantuschke

This paper presents the design and implementation of a novel analog beam former for the frequency range around 85 GHz. The capabilites are demonstrated through an outdoor trial in an urban environment, showcasing the potential of high frequency...


August 2024

When Only Time Will Tell: Interpreting How Transformers Process Local Ambiguities Through the Lens of Restart-Incrementality

Brielen Madureira, Patrick Kahardipraja, David Schlangen

A method to interpret how restart-incremental bidirectional models process local ambiguities, with an analysis on meaning representation and dependency parsing.


August 2024

32 GBd, 109 Gbit/s probabilistically shaped THz wireless transmission using PIN-PD based photonic upconversion

In-Ho Baek, Martin Schell, Colja Schubert, Ronald Freund, Robert Elschner, Simon Nellen, Robert Kohlhaas, Oliver Stiewe, Garrit William Johannes Schwanke

We characterize the performance of high symbol rate probabilistic constellation shaping (PCS) in a THz wireless link utilizing a PIN photodiode-assisted transmitter. Using a 64-QAM base constellation we demonstrate high data rate adaptivity,...


August 2024

Gradual Change Detection in Covariance Matrix: A Lazy Approach

Sida Dai, Lars Thiele, Slawomir Stanczak, Setareh Maghsudi, Ehsan Tohidi

The covariance matrix offers a balance between frequent channel estimations and maintaining acceptable system performance. In this work, we propose an intelligent autonomous mechanism that monitors changes in the covariance matrix, minimizing...


August 2024

Sub-THz D-Band Integrated Analog Beamforming Front-End Prototyping and 6G Outdoor Trials

Ramez Askar, Thomas Haustein, Slawomir Stanczak, Wilhelm Keusgen, Michael Peter, Mathis Schmieder, Thomas Merkle, Jaehoon Chung, Sven Wittig, Laurenz John, Yonghak Suh, Jongpil Lee

This paper reports the development outcomes of the world’s first integrated analog beamforming – transmit and receive – wireless front-ends operating in the D-band (a sub- THz band), particularly designed to operate within 150 GHz to 170 GHz...


August 2024

Two-timescale weighted sum-rate maximization for large cellular and cell-free massive MIMO

Lorenzo Miretti, Slawomir Stanczak, Emil Björnson

Discover a groundbreaking two-timescale method for optimizing the weighted sum-rate in future multi-antenna wireless systems. Our innovative approach overcomes the severe scalability issues of traditional methods, namely the extreme computational...


August 2024

User-Centric Monostatic Sensing Aided by Reconfigurable Intelligent Surfaces

Abdolvakil Fazli, Slawomir Stanczak, Zoran Utkovski, Ehsan Tohidi

We propose that deploying Reflecting Intelligent Surfaces (RIS) as auxiliary sensors can either enable (in cases of blockage) or assist UEs in improving sensing performance. This can be achieved by deploying larger surfaces, offering superior...


August 2024

Load Balancing in O-RAN

Hammad Zafar, Slawomir Stanczak, Martin Kasparick, Ehsan Tohidi

Efficiently managing network load has long been a challenge in wireless networks, and open radio access networks (O-RAN) can offer a potential solution through open interfaces and optimization capabilities. This paper focuses on addressing the...


July 2024

First Polymer-based Passive Optical Waveguide for the Visible Range from 633 nm down to 488 nm

Tianwen Qian, Martin Schell, Moritz Kleinert, Crispin Zawadzki, David de Felipe Mesquida, Norbert Keil, Madeleine Weigel, Jakob Reck, Klara Mihov, Martin Kresse, Philipp Winklhofer, Csongor Keuer, Robin Kraft, Thomas Wiglanda, Arne Schleunitz

We investigated the transmission properties of optical waveguide based on fluorinated acrylate polymer and Ormocer® based polymer in the visible range (VIS). Laser transmission-induced transparency (LTIT) and fluorescence were observed in the...


July 2024

Neuromorphic Wireless Device-Edge Co-Inference via the Directed Information Bottleneck

Yuzhen Ke, Slawomir Stanczak, Johannes Dommel, Zoran Utkovski, Osvaldo Simeone, Mehdi Heshmati

We consider neuromorphic wireless device-edge co-inference for edge intelligence applications. The directed information bottleneck principle is applied to extract the most relevant information for the task. The model demonstrates superior...


July 2024

Understanding the (Extra-)Ordinary: Validating Deep Model Decisions with Prototypical Concept-based Explanations

Maximilian Dreyer, Wojciech Samek, Sebastian Lapuschkin, Reduan Achtibat

With PCX, we introduce a method that summarizes similar single explanations via prototypical ones. As such, we can understand the whole model behavior quickly and in detail. PCX further allows to validate individual predictions by communicating...


July 2024

AttnLRP: Attention-Aware Layer-wise Relevance Propagation for Transformers

Reduan Achtibat, Thomas Wiegand, Wojciech Samek, Sebastian Lapuschkin, Maximilian Dreyer, Sayed M. V. Hatefi, Aakriti Jain

Our new method, AttnLRP, is the first to faithfully and holistically attribute not only input but also latent representations of transformer models with the computational efficiency similar to a single backward pass. We demonstrate that our...


July 2024

Reactive Model Correction: Mitigating Harm to Task-Relevant Features via Conditional Bias Suppression

Dilyara Bareeva, Wojciech Samek, Sebastian Lapuschkin, Maximilian Dreyer, Frederik Pahde

DNNs are prone to relying on spurious correlations in data, posing risks in critical applications. Post-hoc methods exist to mitigate this without retraining but can globally shift latent features distributions, harming model performance. We...


July 2024

Explainable Concept Mappings of MRI: Revealing the Mechanisms Underlying Deep Learning-Based Brain Disease Classification

Christian Tinauer, Wojciech Samek, Sebastian Lapuschkin, Maximilian Dreyer, Reduan Achtibat, Frederik Pahde, Anna Damulina, Maximilian Sackl, Martin Soellradl, Reinhold Schmidt, Stefan Ropele, Christian Langkammer

While recent studies show high accuracy in the classification of Alzheimer's disease using deep neural networks, the underlying learned concepts have not been investigated. We separated Alzheimer's patients (n=117) from normal controls (n=219) by...


July 2024

PURE: Turning Polysemantic Neurons Into Pure Features by Identifying Relevant Circuits

Maximilian Dreyer, Wojciech Samek, Sebastian Lapuschkin, Johanna Vielhaben, Erblina Purelku

Neurons in deep neural networks can act polysemantically, meaning that they encode for multiple (unrelated) features. As such, understanding the inner workings of machine learning models becomes more difficult. We present PURE to turn...


July 2024

Model guidance via explanations turns image classifiers into segmentation models

Xiaoyan Yu, Wojciech Samek, Marina M.-C. Höhne, Dagmar Kainmüller, Jannik Franzen

Heatmaps generated on inputs of image classification networks via explainable AI methods have been observed to resemble segmentations of input images in many cases. We apply the "Right for the Right Reason" paradigm of imposing additional losses...


July 2024

Distributed Convex Optimization “Over-the-Air” in Dynamic Environments

Navneet Agrawal, Slawomir Stanczak, Renato L. G. Cavalcante, Masahiro Yukawa

The paper proposes a class of distributed algorithms where the consensus step is implemented in a scalable and truly decentralized fashion using a novel communication protocol based on the “over-the-air” function computation (OTA-C)...


June 2024

Unlocking the Potential of Local CSI in Cell-Free Networks with Channel Aging and Fronthaul Delays

Lorenzo Miretti, Slawomir Stanczak

Centralized or distributed precoding? This is perhaps the most heated debate in the Cell-free Massive MIMO literature. However, in this work we argue that the best option may actually be a mix of the two. The reason is that centralized precoding,...


June 2024

Towards Bridging the Gap between Near and Far-Field Characterizations of the Wireless Channel

Navneet Agrawal, Slawomir Stanczak, Renato L. G. Cavalcante, Ehsan Tohidi

Exploring near-field propagation is vital for 6G technologies like intelligent reflecting surfaces (IRS). Unlike far-field models, near-field models offer accuracy critical for applications such as beamforming and multiple-access, enhancing...


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