5 papers
Enwar 3.0: An Agentic Multi-Modal LLM Orchestrator for Situation-Aware Beamforming, Blockage Prediction, and Handover Management
Ahmad M. Nazar, Abdulkadir Celik, Asmaa Abdallah +3
Maintaining robust millimeter-wave (mmWave) connectivity in vehicular networks requires real-time adaptation to environmental dynamics, sensor degradation, and link variability. Th…
Multi-Modal Sensor Fusion for Proactive Blockage Prediction in mmWave Vehicular Networks
Ahmad M. Nazar, Abdulkadir Celik, Mohamed Y. Selim +3
Vehicular communication systems operating in the millimeter wave (mmWave) band are highly susceptible to signal blockage from dynamic obstacles such as vehicles, pedestrians, and i…
NextG-GPT: Leveraging GenAI for Advancing Wireless Networks and Communication Research
Ahmad M. Nazar, Mohamed Y. Selim, Daji Qiao +1
Artificial intelligence (AI) and wireless networking advancements have created new opportunities to enhance network efficiency and performance. In this paper, we introduce Next-Gen…
Revolutionizing Undergraduate Learning: CourseGPT and Its Generative AI Advancements
Ahmad M. Nazar, Mohamed Y. Selim, Ashraf Gaffar +1
Integrating Generative AI (GenAI) into educational contexts presents a transformative potential for enhancing learning experiences. This paper introduces CourseGPT, a generative AI…
ENWAR: A RAG-empowered Multi-Modal LLM Framework for Wireless Environment Perception
Ahmad M. Nazar, Abdulkadir Celik, Mohamed Y. Selim +3
Large language models (LLMs) hold significant promise in advancing network management and orchestration in 6G and beyond networks. However, existing LLMs are limited in domain-spec…