Tensor Completion for Radio Map Reconstruction using Low Rank and Smoothness. - Daniel Schäufele; Renato L. G. Cavalcante; Slawomir Stanczak (SPAWC, 2019)

Cooperative Localization by Set-theoretic Estimation. - Jochen Fink; Daniel Schäufele; Martin Kasparick 001; Renato L. G. Cavalcante; Slawomir Stanczak (WSA, 2019)

Quality-of-Service Prediction for Physical-layer Security via Secrecy Maps. - Miguel Angel Gutierrez-Estevez; Zoran Utkovski; Patrick Agostini; Daniel Schäufele; Matthias Frey; Igor Bjelakovic; Slawomir Stanczak (ICASSP, 2020)

Network under Control: Multi-Vehicle E2E Measurements for AI-based QoS Prediction. - Alexandros Palaios; Philipp Geuer; Jochen Fink; Daniel Fabian Külzer; Fabian Göttsch; Martin Kasparick 001; Daniel Schäufele; Rodrigo Hernangómez; Sanket Partani; Raja Sattiraju; Atul Kumar 005; Friedrich Burmeister; et al. (PIMRC, 2021)

Terminal-Side Data Rate Prediction For High-Mobility Users. - Daniel Schäufele; Martin Kasparick 001; Jens Schwardmann; Johannes Morgenroth; Slawomir Stanczak (VTC Spring, 2021)

GPU-Accelerated Machine Learning in Non-Orthogonal Multiple Access. - Daniel Schäufele; Guillermo Marcus; Nikolaus Binder; Matthias Mehlhose; Alexander Keller 001; Slawomir Stanczak (EUSIPCO, 2022)

GPU-Accelerated Partially Linear Multiuser Detection for 5G and Beyond URLLC Systems. - Matthias Mehlhose; Guillermo Marcus; Daniel Schäufele; Daniyal Amir Awan; Nikolaus Binder; Martin Kasparick 001; Renato L. G. Cavalcante; Slawomir Stanczak; Alexander Keller 001 (IEEE Access, 2022)

Real-Time GPU-Accelerated Machine Learning Based Multiuser Detection for 5G and Beyond. - Matthias Mehlhose; Guillermo Marcus; Daniel Schäufele; Daniyal Amir Awan; Nikolaus Binder; Martin Kasparick 001; Renato L. G. Cavalcante; Slawomir Stanczak; Alexander Keller 001 (CoRR, 2022)

Berlin V2X: A Machine Learning Dataset from Multiple Vehicles and Radio Access Technologies. - Rodrigo Hernangómez; Philipp Geuer; Alexandros Palaios; Daniel Schäufele; Cara Watermann; Khawla Taleb-Bouhemadi; Mohammad Parvini; Anton Krause; Sanket Partani; Christian Vielhaus; Martin Kasparick 001; Daniel Fabian Külzer; et al. (VTC2023-Spring, 2023)

From Empirical Measurements to Augmented Data Rates: A Machine Learning Approach for MCS Adaptation in Sidelink Communication. - Asif Abdullah Rokoni; Daniel Schäufele; Martin Kasparick 001; Slawomir Stanczak (VTC Fall, 2023)

Towards an AI-enabled Connected Industry: AGV Communication and Sensor Measurement Datasets. - Rodrigo Hernangómez; Alexandros Palaios; Cara Watermann; Daniel Schäufele; Philipp Geuer; Rafail Ismayilov; Mohammad Parvini; Anton Krause; Martin Kasparick 001; Thomas Neugebauer; Oscar Dario Ramos-Cantor; Hugues Tchouankem; et al. (CoRR, 2023)

Berlin V2X. - Rodrigo Hernangómez; Philipp Geuer; Alexandros Palaios; Daniel Schäufele; Cara Watermann; Khawla Taleb-Bouhemadi; Mohammad Parvini; Anton Krause; Sanket Partani; Christian Vielhaus; Martin Kasparick 001; Daniel Fabian Külzer; et al. (IEEE DataPort, 2023)

AI4Mobile Industrial Wireless Datasets: iV2V and iV2I+. - Rodrigo Hernangómez; Alexandros Palaios; Cara Watermann; Daniel Schäufele; Philipp Geuer; Rafail Ismayilov; Mohammad Parvini; Anton Krause; Martin Kasparick 001; Thomas Neugebauer; Oscar Dario Ramos-Cantor; Hugues Tchouankem; et al. (IEEE DataPort, 2023)

Toward an AI-Enabled Connected Industry: AGV Communication and Sensor Measurement Datasets. - Rodrigo Hernangómez; Alexandros Palaios; Cara Watermann; Daniel Schäufele; Philipp Geuer; Rafail Ismayilov; Mohammad Parvini; Anton Krause; Martin Kasparick 001; Thomas Neugebauer; Oscar Dario Ramos-Cantor; Hugues Tchouankem; et al. (IEEE Commun. Mag., 2024)