2 papers
cs.IT2026
Enhancing User Throughput in Multi-panel mmWave Radio Access Networks for Beam-based MU-MIMO Using a DRL Method
Ramin Hashemi, Vismika Ranasinghe, Teemu Veijalainen +2
Millimeter-wave (mmWave) communication systems, particularly those leveraging multi-user multiple-input and multiple-output (MU-MIMO) with hybrid beamforming, face challenges in op…
eess.SP2025
From Simulation to Practice: Generalizable Deep Reinforcement Learning for Cellular Schedulers
Petteri Kela, Bryan Liu, Alvaro Valcarce
Efficient radio packet scheduling remains one of the most challenging tasks in cellular networks, and while heuristic methods exist, practical deep learning-based schedulers that a…