activity
20232026
most citedEnergy-Efficient On-Board Radio Resource Management for Satellite Communications via Neuromorphic Computing

1 citations · 1 across the 3 of their papers we have counts for

collaborators

7 papers

cs.LG2026

Online Learning via Learned Latent Bayesian Tracking

Guy Gerson, Tomer Raviv, Nir Shlezinger +2

Online learning in non-stationary environments requires models to adapt rapidly from streaming data under strict computational constraints. A principled approach casts online learn…

eess.SP2026

Post-Hoc Conformal Prediction for Reliable Wireless Communications

Xin Su, Meiyi Zhu, Osvaldo Simeone +1

Deploying artificial intelligence (AI) in high-stakes wireless applications such as autonomous transportation requires guarantees of reliable operation. Such guarantees can often b…

eess.SP2026

Reliable Narrowband Interference Detection via Backward Conformal Prediction

Xin Su, Meiyi Zhu, Osvaldo Simeone +2

Narrowband interference can severely degrade the performance of wireless links by concentrating significant power on a small portion of the channel. Machine learning detectors trai…

eess.SP2026

From High-Level Requirements to KPIs: Conformal Signal Temporal Logic Learning for Wireless Communications

Jiechen Chen, Michele Polese, Osvaldo Simeone

Softwarized radio access networks (RANs), such as those based on the Open RAN (O-RAN) architecture, generate rich streams of key performance indicators (KPIs) that can be leveraged…

eess.SP2025

Online Learning of Modular Bayesian Deep Receivers: Single-Step Adaptation with Streaming Data

Yakov Gusakov, Osvaldo Simeone, Tirza Routtenberg +1

Deep neural network (DNN)-based receivers offer a powerful alternative to classical model-based designs for wireless communication, especially in complex and nonlinear propagation…

cs.IT2025

In-Context Learning for Gradient-Free Receiver Adaptation: Principles, Applications, and Theory

Matteo Zecchin, Tomer Raviv, Dileep Kalathil +3

In recent years, deep learning has facilitated the creation of wireless receivers capable of functioning effectively in conditions that challenge traditional model-based designs. L…

eess.SY2023★ 1 cited

Energy-Efficient On-Board Radio Resource Management for Satellite Communications via Neuromorphic Computing

Flor Ortiz, Nicolas Skatchkovsky, Eva Lagunas +6

The latest satellite communication (SatCom) missions are characterized by a fully reconfigurable on-board software-defined payload, capable of adapting radio resources to the tempo…