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10 papers · 1 filter

eess.SP2026

AngularWM: Wireless World Modeling for AoA Prediction from Multi-Antenna I/Q

Omar Mashaal, Hatem Abou-Zeid

Tracking angle-of-arrival (AoA) under mobility enables proactive beam alignment in multi-antenna wireless systems. However, learning this evolution directly from raw I/Q data is ch…

eess.SP2026

RRM-GPT: A Framework and Vision for Radio Resource Management Foundation Models

Ahmed Aboulfotouh, Akram Bin Sediq, Koosha Pourtahmasi Roshandeh +4

Learning-based models for radio resource management (RRM) are typically built for a single function and deployment, so each new setting repeats the development pipeline. RRM decisi…

eess.SP2026

Scaling of Wireless Foundation Models via Representation Diversity and Multi-Branch Architectures

Ahmed Mohamed, Ahmed Aboulfotouh, Hatem Abou-Zeid

Wireless foundation models learn representations from unlabeled radio signals for reuse across downstream tasks. Scaling model capacity is a common strategy for learning richer rep…

eess.SP2026

VitalFR3: Wireless Vital Sign Sensing in the Upper Mid-Band (FR3)

Gholamreza Bakhshi, Hatem Abou-Zeid

Frequency range 3 (FR3) is being explored for sixth-generation (6G) integrated sensing and communication (ISAC).However, experimental evidence on the feasibility of physiological s…

eess.SP2026

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…

eess.SP2026

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…

eess.SP2026

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…

eess.SP2026

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…

eess.SP2026

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…

eess.SP2026

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…