37 citations · 37 across the 7 of their papers we have counts for
9 papers
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…
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…
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…
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…
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…
IQFM A Wireless Foundational Model for I/Q Streams in AI-Native 6G
Omar Mashaal, Hatem Abou-Zeid
Foundational models have shown remarkable potential in natural language processing and computer vision, yet remain in their infancy in wireless communications. While a few efforts…
ProtoBeam: Generalizing Deep Beam Prediction to Unseen Antennas using Prototypical Networks
Omar Mashaal, Elsayed Mohammed, Alec Digby +3
Deep learning techniques have recently emerged to efficiently manage mmWave beam transmissions without requiring time consuming beam sweeping strategies. A fundamental challenge in…
Using Early Exits for Fast Inference in Automatic Modulation Classification
Elsayed Mohammed, Omar Mashaal, Hatem Abou-Zeid
Automatic modulation classification (AMC) plays a critical role in wireless communications by autonomously classifying signals transmitted over the radio spectrum. Deep learning (D…
Feature selection for intrusion detection systems
Firuz Kamalov, Sherif Moussa, Rita Zgheib +1
In this paper, we analyze existing feature selection methods to identify the key elements of network traffic data that allow intrusion detection. In addition, we propose a new feat…