13 papers · 1 filter
Wireless Foundation Models: State-of-the-Art and Open Challenges
Alonso M. Pacheco Huachaca, Juan J. Rodriguez Rodriguez, Ahmed Aboulfotouh +3
Wireless foundation models (WFMs) have emerged as a promising approach for learning reusable representations from large-scale wireless data and adapting them to downstream tasks. H…
Fast Wireless Foundation Models with Early-Exits
Omar Mashaal, Hatem Abou-Zeid
While wireless foundation models (FMs) are demonstrating strong potential to enable AI-Native 6G networks, their high computational cost remains a critical barrier to deployment. T…
LatentWave: JEPA Pretraining for Wireless Foundation Models
Ahmed Mohamed, Ahmed Aboulfotouh, Hatem Abou-Zeid
Wireless foundation models have emerged as a promising alternative to building separate models for each wireless task. However, existing approaches rely on masked input reconstruct…
ProtoAoA: Few-Shot Angle-of-Arrival Estimation using Prototypical Networks
Elsayed Mohammed, Omar Mashaal, Alec Digby +4
Angle-of-arrival (AoA) estimation is a crucial function in wireless communications used for localization, beam-forming, interference management, and other applications. Deep learni…
BEACON: Benefit-Aware Early-Exit for Automatic Modulation Classification via Recoverability Prediction
Zheng Liu, Hatem Abou-Zeid, Huaqing Wu
Convolutional neural networks (CNNs) have emerged as a powerful tool for automatic modulation classification (AMC) by directly extracting discriminative features from raw in-phase…
WirelessJEPA: A Multi-Antenna Foundation Model using Spatio-temporal Wireless Latent Predictions
Viet Chu, Omar Mashaal, Hatem Abou-Zeid
We propose WirelessJEPA, a novel wireless foundation model (WFM) that uses the Joint Embedding Predictive Architecture (JEPA). WirelessJEPA learns general-purpose representations d…