7 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…
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…
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…
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…
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…