412 citations
- Technical University of MunichDE5 papers
- University of KaiserslauternDE5 papers
- Karlsruhe Institute of TechnologyDE4 papers
- Nokia (Finland)FI4 papers
- Nokia (United States)US4 papers
- University of StuttgartDE4 papers
- Technische Universität BraunschweigDE3 papers
- Aalborg UniversityDK2 papers
- Aalto UniversityFI2 papers
- Fraunhofer Institute for Telecommunications, Heinrich Hertz InstituteDE2 papers
- Friedrich-Alexander-Universität Erlangen-NürnbergDE2 papers
- German Research Centre for Artificial IntelligenceDE2 papers
50 papers
The QTF-Backbone: Proposal for a Nationwide Optical Fibre Backbone in Germany for Quantum Technology and Time and Frequency Metrology
Tara Cubel Liebisch, Peter Kaufmann, Harald Schnatz +166
The recent breakthroughs in the distribution of quantum information and high-precision time and frequency (T&F) signals over long-haul optical fibre networks have transformative po…
Inter-Cell Network Slicing With Transfer Learning Empowered Multi-Agent Deep Reinforcement Learning
Tianlun Hu, Qi Liao, Qiang Liu +1
Network slicing enables operators to efficiently support diverse applications on a common physical infrastructure. The ever-increasing densification of network deployment leads to…
Network Slicing via Transfer Learning aided Distributed Deep Reinforcement Learning
Tianlun Hu, Qi Liao, Qiang Liu +1
Deep reinforcement learning (DRL) has been increasingly employed to handle the dynamic and complex resource management in network slicing. The deployment of DRL policies in real ne…
Energy Efficient Extreme MIMO: Design Goals and Directions
Stefan Wesemann, Jinfeng Du, Harish Viswanathan
Ever since the invention of Bell Laboratories Layer Space-Time (BLAST) in mid 1990s, the focus of MIMO research and development has been largely on pushing the limit of spectral ef…
Delay Analysis of IEEE 802.11be Multi-link Operation under Finite Load
Boris Bellalta, Marc Carrascosa, Lorenzo Galati-Giordano +1
Multi-link Operation (MLO), arguably the most disruptive feature introduced in IEEE 802.11be, will cater for delay-sensitive applications by using multiple radio interfaces concurr…
Deep Learning for Multi-User Proactive Beam Handoff: A 6G Application
Faris B. Mismar, Alperen Gundogan, Aliye Ozge Kaya +1
This paper demonstrates the use of deep learning and time series data generated from user equipment (UE) beam measurements and positions collected by the base station (BS) to enabl…