Recent publications

October 2025

Agile Sub-Terahertz to Terahertz Broadband Time-Domain Photonic Channel Sounder

Ramez Askar, Mario Goldenbaum, Wilhelm Keusgen, Michael Peter, Colja Schubert, Ronald Freund, Robert Elschner, Taro Eichler, Shahram Keyvaninia, Robert Kohlhaas, Oliver Stiewe, Milan Deumer, Alper Schultze, Garrit William Johannes Schwanke, Nico Vieweg, Thomas Puppe, Sebastian Müller, Albrecht Neudecker

This paper presents the design and implementation of an agile sub-terahertz (sub-THz) broadband time-domain photonic channel sounder, capable of characterizing wireless propagation channels within the 100 GHz to 500 GHz frequency range.


October 2025

RIPE: Reinforcement Learning on Unlabeled Image Pairs for Robust Keypoint Extraction

Johannes Wolf Künzel, Peter Eisert, Anna Hilsmann

We introduce RIPE, an innovative reinforcement learning-based framework for weakly-supervised training of a keypoint extractor that excels in both detection and description tasks. In contrast to conventional training regimes that depend heavily...


October 2025

Waveform Design for Simultaneous MIMO Radar Sensing and Multi-User Communication

Berkan Kilic, Slawomir Stanczak, Kenan Turbic

This work introduces a two-stage waveform design framework for multi-antenna integrated sensing and communication systems. By optimizing radar beampatterns and communication signals under practical constraints, the proposed method achieves...


October 2025

Digital Post-Distortion Architectures for Nonlinear Power Amplifiers: Volterra and Kernel Methods

Daniel Schäufele, Slawomir Stanczak, Renato L. G. Cavalcante, Jochen Fink

In modern 5G UEs, the PA consumes large amounts of power. However, there is a trade-off between power efficiency and nonlinear distortion. This study explores digital post-distortion to address PA nonlinearities at the base station. We take a...


September 2025

Batch-Aware Active Learning for Object Detection

Mykyta Kovalenko, Peter Eisert, Anna Hilsmann, Sebastian Bosse

Active Learning is a powerful way to cut down the time and effort needed to annotate data, but its use in object detection remains underexplored. We introduce a Batch-Aware Active Learning (BAAL) framework that combines uncertainty with diversity...


September 2025

D-Band Adaptive Beamforming for 6G Sub-THz Communications: Feasibility and Experimental Results

Sven Wittig, Thomas Haustein, Matthias Mehlhose, Slawomir Stanczak, Michael Peter, Ramez Askar, Mathis Schmieder, Thomas Merkle, Jaehoon Chung, Utku Uçak, Laurenz John, Yonghak Suh, Jongpil Lee, Bersant Gashi, Arnulf Leuther

Making sub-Terahertz frequencies usable in future mobile radio networks such as 6G requires adaptive beamforming techniques. Using newly developed D-band front ends, we present first experimental evidence for the feasibility of this approach.


September 2025

Beampattern Synthesis with a Computationally Efficient Matrix Nearness Approach

Berkan Kilic, Slawomir Stanczak, Martin Kasparick, Kenan Turbic

This work introduces a computationally efficient method for MIMO radar beampattern synthesis through optimized waveform covariance matrix design. The approach directs transmitted power toward target regions, minimizes cross-correlations, and...


September 2025

Linear Phase Beampattern Design with Set-theoretic Methods

Jochen Fink, Slawomir Stanczak, Renato L. G. Cavalcante

This paper investigates the potential to approximate a nonconvex beampattern design problem with constraints in the angular domain via a restriction to a convex subset of the feasible region. Simulations show that that imposing this convex...


September 2025

NOBS: A Data-Sovereign Telemetry and Monitoring Framework for 6G Networks

Aydin Jafari, Mohammad Behnam Shariati, Pooyan Safari, Angela Mitrovska, Mihail Balanici, Johannes Karl Fischer Fischer

In this paper, we present the Network Observability Platform (NOBS), a data-sovereign telemetry and monitoring framework designed to meet the primary needs of multi-vendor packet-optical networks in the Sixth Generation (6G) era. NOBS supports...


September 2025

Resilience Enhancement of Optical Network-Cloud Ecosystems with Dataspace Framework and Multi-entity Cooperation (Invited)

Sugang Xu, Ronald Freund, Johannes Fischer, Mohammad Behnam Shariati, Pooyan Safari, Angela Mitrovska, Hideaki Furukawa, Subhadeep Sahoo, Yusuke Hirota, Yuki Yoshida, Kouichi Akahane, Sifat Ferdousi, Massimo Tornatore, Yoshinari Awaji , Biswanath Mukherjee

To enhance the resilience of network-cloud ecosystems, we establish a data governance framework for sharing optical testbed data across organizations and fostering machine learning research of optical networks. We further introduce multientity...


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