12 papers
Reimagining RAN Automation in 6G: An Agentic AI Framework with Hierarchical Online Decision Transformer
Md Arafat Habib, Medhat Elsayed, Majid Bavand +3
In this paper, we propose an Agentic Artificial Intelligence (AI) framework for wireless networks. The framework coordinates a pool of AI agents guided by Natural Language (NL) inp…
Hierarchical Decision Mamba Meets Agentic AI: A Novel Approach for RAN Slicing in 6G
Md Arafat Habib, Medhat Elsayed, Majid Bavand +3
Radio Access Network (RAN) slicing enables multiple logical networks to exist on top of the same physical infrastructure by allocating resources to distinct service groups, where r…
Generative AI for Intent-Driven Network Management in 6G RAN: A Case Study on the Mamba Model
Md Arafat Habib, Medhat Elsayed, Yigit Ozcan +3
With the emergence of 6G, mobile networks are becoming increasingly heterogeneous and dynamic, necessitating advanced automation for efficient management. Intent-Driven Networks (I…
GenAI-enabled Residual Motion Estimation for Energy-Efficient Semantic Video Communication
Shavbo Salehi, Pedro Enrique Iturria-Rivera, Medhat Elsayed +3
Semantic communication addresses the limitations of the Shannon paradigm by focusing on transmitting meaning rather than exact representations, thereby reducing unnecessary resourc…
Harnessing the Power of LLMs, Informers and Decision Transformers for Intent-driven RAN Management in 6G
Md Arafat Habib, Pedro Enrique Iturria Rivera, Yigit Ozcan +4
Intent-driven network management is critical for managing the complexity of 5G and 6G networks. It enables adaptive, on-demand management of the network based on the objectives of…
Intelligent Attacks and Defense Methods in Federated Learning-enabled Energy-Efficient Wireless Networks
Han Zhang, Hao Zhou, Medhat Elsayed +4
Federated learning (FL) is a promising technique for learning-based functions in wireless networks, thanks to its distributed implementation capability. On the other hand, distribu…