An Offline Multi-Agent Reinforcement Learning Framework for Radio Resource Management
Offline multi-agent reinforcement learning (MARL) addresses key limitations of online MARL, such as safety concerns, expensive data collection, extended training intervals, and […]
Efficient Recursive Convolutional Target Detector for FMCW Radar with Implementation on a Programmable Deep Learning Processor Unit
The advanced driver assistance systems (ADASs) and autonomous driving (AD) systems are becoming increasingly vital in modern vehicles. These systems rely on […]
IEEE Pervasive Computing 2025: 1 (SI)
Non-Orthogonal Multiple-Access Strategies for Direct-to-Satellite IoT Networks
Direct-to-Satellite IoT (DtS-IoT) has the potential to support multiple verticals, including agriculture, industry, smart cities, and environmental disaster prevention. However, device transmissions […]
Offline and Distributional Reinforcement Learning for Wireless Communications
The rapid growth of heterogeneous and massive wireless connectivity in 6G networks demands intelligent solutions to ensure scalability, reliability, privacy, ultra-low latency, […]
6G AI-Driven Air Interface – Hexa-X-II View
This article presents the European 6G Flagship project Hexa-X-II’s view on 6G AI-driven air interface. It outlines motivations for AI in the […]
A Simplified Algorithm for Joint Real-Time Synchronization, NLoS Identification, and Multi-Agent Localization
Real-time, high-precision localization in large-scale wireless networks faces two primary challenges: clock offsets caused by network asynchrony and non-line-of-sight (NLoS) conditions. To […]
Understanding Subterahertz Radio Channels: The Impact of Beamforming on Wireless System Design
Wireless connectivity in the subterahertz (sub-THz) band, spanning from 100 GHz to 300 GHz, is envisioned as an enhanced feature of 6G […]
Stacked Intelligent Metasurfaces for Wireless Communications: Applications and Challenges
The rapid growth of wireless communications has created a significant demand for high through-put, seamless connectivity, and extremely low latency. To meet […]
Screening of Material Defects using Universal Machine-Learning Interatomic Potentials
Finding new materials with previously unknown atomic structure or materials with optimal set of properties for a specific application greatly benefits from […]