2 papers
eess.SY2026
Mission-critical spectrum sharing with decentralized Multi-Agent Reinforcement Learning
Dimitrios Pylorof, Imtiaz Nasim, Humberto E. Garcia +3
Motivated by emerging mission-critical applications and an increasingly congested spectrum, we develop a decentralized multi-agent reinforcement learning (MARL) model for dynamic s…
eess.SP2026
Calibrating the Digital Twin Channel: Statistics-Consistent Sim-to-Lab Adaptation for W-Band Industrial OFDM Links
Pulok Tarafder, Abigail O. Oyekola, Jasni Areepatta Mannil +4
Digital twins (DTs) can reduce over-the-air validation cost in industrial wireless networks, but their utility depends on the fidelity of the underlying channel twin (CT). At W-ban…