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AI for Wireless Communication

AI for Wireless Communication AI for Radio Access Networks (AI-RAN) and Open RAN (O-RAN) represent key enablers for next-generation wireless systems, introducing intelligence, adaptability, and openness into network design and operation. AI-RAN, with its machine learning capability, and O-RAN, with its open and interoperable architecture, foster flexibility, vendor diversity, and innovation in RAN deployment. We’re currently updating this section. More content and visuals will be added soon.
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Digital Twin For Wireless Communication

Digital Twin For Wireless Communication Digital Twin (DT) in wireless communication refers to a high-fidelity virtual replica of a physical communication environment that enables real-time monitoring, analysis, and optimization of wireless systems. By bridging the physical and digital domains, DTs provide significant advantages such as predictive system behavior, performance enhancement, rapid prototyping, and reduced testing costs. At CCSL, we are developing DT frameworks across various scenarios, including both indoor and outdoor wireless environments, with a particular focus on real-time DT

Research

‌The Communication and Computing Systems Lab (CCSL) at KAUST is led by Professor Ahmed Eltawil. The research focus of the group lies in the area of efficient architectures for mobile computing and communications systems. Our philosophy is to employ a multidisciplinary approach to the design and development of mobile systems spanning algorithm, architecture and implementation. The goal is to simultaneously address two seemingly diverging trends. The first trend is concerned with efficient, high data rate broadband wireless systems driven by continuously expanding networking applications. The

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Publications

Publications

2025 Journals Abdallah, A., Celik, A., Mansour, M. M., & Eltawil, A. M. (2025). Multi-agent deep reinforcement learning for beam training in cell-free RIS-aided systems. IEEE Transactions on Wireless Communications. Nazar, A. M., Celik, A., Selim, M. Y., Abdallah, A., Qiao, D., & Eltawil, A. M. (2025). ENWAR 2.0: An agentic multimodal wireless LLM framework with reasoning, situation-aware explainability and beam tracking. IEEE Transactions on Mobile Computing. (Submitted) Awad, Y., Celik, A., & Eltawil, A. (2025). SSB-based multi-target detection and joint velocity, angle, and range estimation

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Communication and Computing Systems Lab Research Group

Communication and Computing Systems Lab Professor Ahmed Eltawil leads the CCSL research group, which stands for Communication and Computing Systems Lab The Communication and Computing Systems Lab (CCSL) at KAUST is led by Professor Ahmed Eltawil. The research focus of the group lies in the area of efficient architectures for mobile computing and communications systems. Our philosophy is to employ a multidisciplinary approach to the design and development of mobile systems spanning algorithm, architecture and implementation. The goal is to simultaneously address two seemingly diverging trends

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Body Area Network

Body Area Network Our work explores new frontiers where the human body and nature itself become powerful channels for communication. We are driven by the vision that signals can be harnessed and transformed into reliable pathways for exchanging information. By combining innovative circuit design, ultra-low-power integrated systems, and bio-inspired networking, we seek to enable technologies that go far beyond traditional wireless communication. Our research spans from the Internet of Body, where multiple biosensors can communicate seamlessly through the human body, to the Internet of Plants

Wireless Communication

Wireless Communication The CCSL advances next-generation wireless communication through a synergistic combination of theory, system design, and artificial intelligence. Our research explores digital twin frameworks for both indoor and outdoor wireless scenarios, enabling real-time system monitoring, optimization, and predictive analysis. We leverage multimodal sensing to enhance situational awareness and resilience, while reconfigurable intelligent surface (RIS)-aided localization pushes the boundaries of positioning accuracy. In integrated sensing and communication (ISAC), the lab