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cs.NI2026
Improving 5G AI-RAN MCS Selection by Predicting Retransmissions
Tamerlan Aghayev, Maxime Elkael, Michele Polese +5
Link Adaptation (LA) in 5G NR is inherently reactive, relying on channel measurements and HARQ feedback that may become quickly obsolete when the channel changes quickly. This data…
cs.NI2026
AUGUSTE: Online-Learning dApp for Predictive URLLC Scheduling
Maxime Elkael, Michele Polese, Yunseong Lee +2
Ultra Reliable and Low Latency Communications (URLLC) was one of the main motivations behind 5G, with 3GPP advertising 1-10 ms latency targets for applications such as industrial a…
cs.NI2026
ARCHES: Adaptive Real-Time Switching of AI Models for the RAN
Neagin Neasamoni Santhi, Davide Villa, Michele Polese +4
Artificial Intelligence (AI) has become a powerful tool for model-free Radio Access Network (RAN) signal processing and optimization. However, designing a single model that general…