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LocAttMamba: A Low-Complexity Mamba Framework with Attention-Based Multi-AP Fusion for Indoor Localization
MohammadMahdi Ghadaksaz, Mohammad Farzanullah, Melike Erol-Kantarci
Accurate and low-complexity indoor localization is important for location-based services in fifth generation (5G) and sixth generation (6G) networks, where positioning devices oper…
Out-of-Distribution Detection in Wireless Multimodal Foundation Models for 6G ISAC
Mohammad Farzanullah, Akram Bin Sediq, Ali Afana +1
The integration of Foundation Models (FMs), such as the Wireless Multimodal Foundation Model (WMFM), into 6G networks provides a unified framework for Integrated Sensing and Commun…
PERA: A Perceive-Reason-Act Interface Bridging Sensing, Cognitive Reasoning, and Trustworthy Agentic Response for 6G
Mohammad Farzanullah, Melike Erol-Kantarci, Lajos Hanzo
The realization of next-generation (NG) networks hinges on a fundamental departure from preprogrammed protocol engineering towards a paradigm of self-consciously evolving, autonomo…
Chain-of-Thought Reasoning Enhances In-Context Learning for LLM-Based Mobile Traffic Prediction
MohammadMahdi Ghadaksaz, Mohammad Farzanullah, Akram Bin Sediq +2
Accurate short-term mobile traffic prediction is important for proactive resource allocation and low-latency network management in fifth generation (5G) and sixth generation (6G).…
Multi-Modal Data-Enhanced Foundation Models for Prediction and Control in Wireless Networks: A Survey
Han Zhang, Mohammad Farzanullah, Mohammad Ghassemi +3
Foundation models (FMs) are recognized as a transformative breakthrough that has started to reshape the future of artificial intelligence (AI) across both academia and industry. Th…