Time Adaptive Probabilistic Shaping for Combined Optical/THz Links
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....
Experimental Dataset for Developing and Testing ML Models in Optical Communication Systems
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...
Causes of Outcome Learning: A causal inference-inspired machine learning approach to disentangling common combinations of potential causes of a health outcome
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...
SPVLoc: Semantic Panoramic Viewport Matching for 6D Camera Localization in Unseen Environments
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...
Compact 3D Scene Representation via Self-Organizing Gaussian Grids
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...
Evolution of the 5G New Radio Two-Step Random Access towards 6G Unsourced MAC
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.
Impact of Multi-Band Transmission on Optical Signal-to-Noise Ratio Measurements
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...
Demonstration of a Real-Time Testbed for D-Band Integrated Sensing and Communication
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,...
BTSeg: Barlow Twins Regularization for Domain Adaptation in Semantic Segmentation
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...
Dual-Polarized Sub-THz Channel Measurements in D-Band in an Industrial Environment
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.
Localization in Dynamic Indoor MIMO-OFDM Wireless Systems using Domain Adaptation
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...
W-Band Beamforming Front-End Implementation and Outdoor Trials for Mobile Backhaul and Access
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...
When Only Time Will Tell: Interpreting How Transformers Process Local Ambiguities Through the Lens of Restart-Incrementality
A method to interpret how restart-incremental bidirectional models process local ambiguities, with an analysis on meaning representation and dependency parsing.
32 GBd, 109 Gbit/s probabilistically shaped THz wireless transmission using PIN-PD based photonic upconversion
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,...
Gradual Change Detection in Covariance Matrix: A Lazy Approach
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...
Sub-THz D-Band Integrated Analog Beamforming Front-End Prototyping and 6G Outdoor Trials
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...
Two-timescale weighted sum-rate maximization for large cellular and cell-free massive MIMO
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...
User-Centric Monostatic Sensing Aided by Reconfigurable Intelligent Surfaces
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...
Load Balancing in O-RAN
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...
First Polymer-based Passive Optical Waveguide for the Visible Range from 633 nm down to 488 nm
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...
Neuromorphic Wireless Device-Edge Co-Inference via the Directed Information Bottleneck
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...
Understanding the (Extra-)Ordinary: Validating Deep Model Decisions with Prototypical Concept-based Explanations
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...
AttnLRP: Attention-Aware Layer-wise Relevance Propagation for Transformers
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...
Reactive Model Correction: Mitigating Harm to Task-Relevant Features via Conditional Bias Suppression
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...
Explainable Concept Mappings of MRI: Revealing the Mechanisms Underlying Deep Learning-Based Brain Disease Classification
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...
PURE: Turning Polysemantic Neurons Into Pure Features by Identifying Relevant Circuits
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...
Model guidance via explanations turns image classifiers into segmentation models
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...
Distributed Convex Optimization “Over-the-Air” in Dynamic Environments
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)...
Unlocking the Potential of Local CSI in Cell-Free Networks with Channel Aging and Fronthaul Delays
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,...
Towards Bridging the Gap between Near and Far-Field Characterizations of the Wireless Channel
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...