4 citations · 6 across the 24 of their papers we have counts for
25 papers
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…
Toward Proactive RF Charging Scheduling: Generative AI for Decision Support
Amirhossein Azarbahram, Osmel M. Rosabal, David Ernesto Ruiz-Guirola +3
Radio frequency wireless power transfer (RF-WPT) is an enabling technology for supporting uninterrupted communications in future Internet of Things systems by reducing the need for…
Generalizable Multi-Task Learning for Wireless Networks Using Prompt Decision Transformers
Fatih Temiz, Shavbo Salehi, Melike Erol-Kantarci
Future wireless networks demand rapid adaptation to highly heterogeneous environments and dynamic task configurations, necessitating a shift from conventional rule-based and optimi…
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).…
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…
Foundation Model-Aided Hierarchical Deep Reinforcement Learning for Blockage-Aware Link in RIS-Assisted Networks
Mohammad Ghassemi, Han Zhang, Ali Afana +2
Reconfigurable intelligent surface (RIS) technology has the potential to significantly enhance the spectral efficiency (SE) of 6G wireless networks. However, practical deployment r…
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…
Dual-Transformer Aided Hierarchical Deep Reinforcement Learning for Robust RIS-Assisted Near-Field Communications
Mohammad Ghassemi, Han Zhang, Ali Afana +2
The deployment of extremely large aperture arrays (ELAAs) in sixth-generation (6G) networks is expected to shift communications into the near-field regime, where spherical-wave pro…
Wireless Multimodal Foundation Model (WMFM): Integrating Vision and Communication Modalities for 6G ISAC Systems
Mohammad Farzanullah, Han Zhang, Akram Bin Sediq +2
The emergence of multimodal foundation models has revolutionized learning paradigms by enabling joint understanding across diverse data types. In the context of next-generation wir…
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…
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…
Foundation Model-Aided Deep Reinforcement Learning for RIS-Assisted Wireless Communication
Mohammad Ghassemi, Sara Farrag Mobarak, Han Zhang +3
Reconfigurable intelligent surfaces (RIS) have emerged as a promising technology for enhancing wireless communication by dynamically controlling signal propagation in the environme…
Conditional Denoising Diffusion for ISAC Enhanced Channel Estimation in Cell-Free 6G
Mohammad Farzanullah, Han Zhang, Akram Bin Sediq +2
Cell-free Integrated Sensing and Communication (ISAC) aims to revolutionize 6th Generation (6G) networks. By combining distributed access points with ISAC capabilities, it boosts s…
Mobile Traffic Prediction using LLMs with Efficient In-context Demonstration Selection
Han Zhang, Akram Bin Sediq, Ali Afana +1
Mobile traffic prediction is an important enabler for optimizing resource allocation and improving energy efficiency in mobile wireless networks. Building on the advanced contextua…
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…
Beam Selection in ISAC using Contextual Bandit with Multi-modal Transformer and Transfer Learning
Mohammad Farzanullah, Han Zhang, Akram Bin Sediq +2
Sixth generation (6G) wireless technology is anticipated to introduce Integrated Sensing and Communication (ISAC) as a transformative paradigm. ISAC unifies wireless communication…
Generative AI-enabled Blockage Prediction for Robust Dual-Band mmWave Communication
Mohammad Ghassemi, Han Zhang, Ali Afana +2
In mmWave wireless networks, signal blockages present a significant challenge due to the susceptibility to environmental moving obstructions. Recently, the availability of visual d…
Cooperation and Personalization on a Seesaw: Choice-based FL for Safe Cooperation in Wireless Networks
Han Zhang, Medhat Elsayed, Majid Bavand +3
Federated learning (FL) is an innovative distributed artificial intelligence (AI) technique. It has been used for interdisciplinary studies in different fields such as healthcare,…
Multi-Modal Transformer and Reinforcement Learning-based Beam Management
Mohammad Ghassemi, Han Zhang, Ali Afana +2
Beam management is an important technique to improve signal strength and reduce interference in wireless communication systems. Recently, there has been increasing interest in usin…
Generative AI-in-the-loop: Integrating LLMs and GPTs into the Next Generation Networks
Han Zhang, Akram Bin Sediq, Ali Afana +1
In recent years, machine learning (ML) techniques have created numerous opportunities for intelligent mobile networks and have accelerated the automation of network operations. How…
Generative AI Empowered LiDAR Point Cloud Generation with Multimodal Transformer
Mohammad Farzanullah, Han Zhang, Akram Bin Sediq +2
Integrated sensing and communications is a key enabler for the 6G wireless communication systems. The multiple sensing modalities will allow the base station to have a more accurat…