9 papers · 1 filter
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…
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…
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…
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…