5 papers · 1 filter
Multimodal Wireless Foundation Models
Ahmed Aboulfotouh, Hatem Abou-Zeid
Wireless foundation models (WFMs) have recently demonstrated promising capabilities, jointly performing multiple wireless functions and adapting effectively to new environments. Ho…
Self-supervised Radio Representation Learning: Can we Learn Multiple Tasks?
Ogechukwu Kanu, Ashkan Eshaghbeigi, Hatem Abou-Zeid
Artificial intelligence (AI) is anticipated to play a pivotal role in 6G. However, a key challenge in developing AI-powered solutions is the extensive data collection and labeling…
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…
6G WavesFM: A Foundation Model for Sensing, Communication, and Localization
Ahmed Aboulfotouh, Elsayed Mohammed, Hatem Abou-Zeid
This paper introduces WavesFM, a novel Wireless Foundation Model (WFM) framework, capable of supporting a wide array of communication, sensing, and localization tasks. Our proposed…
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…