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Aktuelle Publikationen
Gaussian Splatting Decoder for 3D-aware Generative Adversarial Networks
We present a novel approach that combines the high rendering quality of NeRF-based 3D-aware GANs with the flexibility and computational advantages of 3DGS. By training a decoder that maps implicit NeRF representations to explicit 3D Gaussian...
Experimental Characterization of a WR3-Coupled Photodiode Transmitter for High-Speed Terahertz Wireless Communication
We analyze the system performance of a large bandwidth photonic THz transmitter based on a WR3 coupled photodiode. Employing probabilistic constellation shaping (PCS) alongside a 64-QAM base constellation, we achieve net data rates of up to 76.8...
Multi-Resolution Generative Modeling of Human Motion from Limited Data
We present a generative model that learns to synthesize human motion from limited training sequences. Our framework provides conditional generation and blending across multiple temporal resolutions. moOurdel adeptly captures human motion patterns...
Robust mmWave/sub-THz multi-connectivity using minimal coordination and coarse synchronization
How to provide robust connectivity against signal blockage in 6G mmWave/sub-THz networks? This study demonstrates that carefully designed multi-connectivity schemes can realize full macrodiversity gains and significant SNR gains through canonical...
Real-time Experiments towards an Automotive OFDMA Communication Bus
We present a new automotive bus system which allows enhanced channel adaptation and fine-granular multi-user access based on OFDMA. We highlight advantages of OFDMA in automotive applications, sketch the concept and present an FPGA prototype.
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 o...
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...
Innovationen für die digitale Gesellschaft
Innovationen für die digitale Gesellschaft von morgen stehen im Mittelpunkt der Forschungs- und Entwicklungsarbeit des Fraunhofer-Instituts für Nachrichtentechnik, Heinrich-Hertz-Institut, HHI. Dabei ist das Fraunhofer HHI weltweit führend in der Erforschung von mobilen und optischen Kommunikationsnetzen und -systemen, faseroptischen Sensorsystemen sowie der Kodierung von Videosignalen und der Bilddatenverarbeitung.
Gemeinsam mit internationalen Partnern aus Forschung und Industrie arbeitet das Fraunhofer HHI im gesamten Spektrum der digitalen Infrastruktur – von der grundlegenden Forschung bis hin zur Entwicklung von Prototypen und Lösungen. Das Institut trägt signifikant zu den Standards für Informations- und Kommunikationstechnologien bei und schafft neue Anwendungen als Partner der Industrie.
Innovationen für die digitale Gesellschaft von morgen stehen im Mittelpunkt der Forschungs- und Entwicklungsarbeit des Fraunhofer Heinrich-Hertz-Instituts HHI. Dabei ist das Institut weltweit führend in der Erforschung von mobilen und optischen Kommunikationsnetzen und -systemen, faseroptischen Sensorsystemen sowie der Kodierung von Videosignalen und der Bilddatenverarbeitung.