23 citations · 36 across the 8 of their papers we have counts for
8 papers
Contrastive Predictive Coding with Compression for Enhanced Channel State Feedback in Wireless Networks
Ahmed Y. Radwan, Fahad Syed Muhammad, Matthew Baker +1
Accurate and timely channel state information (CSI) is essential for next-generation wireless systems, yet existing works treat CSI compression and CSI prediction as separate probl…
SONIC-O1: A Real-World Benchmark for Evaluating Multimodal Large Language Models on Audio-Video Understanding
Ahmed Y. Radwan, Christos Emmanouilidis, Hina Tabassum +2
Multimodal Large Language Models (MLLMs) are a major focus of recent AI research. However, most prior work focuses on static image understanding, while their ability to process seq…
A Tutorial-cum-Survey on Self-Supervised Learning for Wi-Fi Sensing: Trends, Challenges, and Outlook
Ahmed Y. Radwan, Mustafa Yildirim, Navid Hasanzadeh +2
Wi-Fi technology has evolved from simple communication routers to sensing devices. Wi-Fi sensing leverages conventional Wi-Fi transmissions to extract and analyze channel state inf…
CVaR-Based Variational Quantum Optimization for User Association in Handoff-Aware Vehicular Networks
Zijiang Yan, Hao Zhou, Jianhua Pei +3
Efficient resource allocation is essential for optimizing various tasks in wireless networks, which are usually formulated as generalized assignment problems (GAP). GAP, as a gener…
Semantic-Aware Adaptive Video Streaming Using Latent Diffusion Models for Wireless Networks
Zijiang Yan, Jianhua Pei, Hongda Wu +2
This paper proposes a novel Semantic Communication (SemCom) framework for real-time adaptive-bitrate video streaming by integrating Latent Diffusion Models (LDMs) within the FFmpeg…
Over-the-Air FEEL with Integrated Sensing: Joint Scheduling and Beamforming Design
Saba Asaad, Ping Wang, Hina Tabassum
Employing wireless systems with dual sensing and communications functionalities is becoming critical in next generation of wireless networks. In this paper, we propose a robust des…
Latent Diffusion Model-Enabled Low-Latency Semantic Communication in the Presence of Semantic Ambiguities and Wireless Channel Noises
Jianhua Pei, Cheng Feng, Ping Wang +2
Deep learning (DL)-based Semantic Communications (SemCom) is becoming critical to maximize overall efficiency of communication networks. Nevertheless, SemCom is sensitive to wirele…
Joint Spectrum Partitioning and Power Allocation for Energy Efficient Semi-Integrated Sensing and Communications
Ammar Mohamed Abouelmaati, Sylvester Aboagye, Hina Tabassum
With spectrum resources becoming congested and the emergence of sensing-enabled wireless applications, conventional resource allocation methods need a revamp to support communicati…