4 papers
GCNO: Gramian Chebyshev Neural Operator for Physics-Based Compression of Wireless Channels
Rafid Umayer Murshed, Shahab Hamidi-Rad, Elahe Soltanaghai +1
Large antenna arrays allow wireless systems to serve more users and achieve higher data rates, but they also make channel feedback expensive: the receiving device must repeatedly r…
Physics-Unrolled Neural Operator for Wireless Field Modeling
Rafid Umayer Murshed, Saif Ur Rahman, Mingyue Tang +1
Radio maps are essential for wireless decision-making tasks such as access-point placement, coverage planning, and localization, but their fine spatial details are governed by comp…
MetaFAP: Meta-Learning for Frequency Agnostic Prediction of Metasurface Properties
Rafid Umayer Murshed, Md Shoaib Akhter Rafi, Sakib Reza +2
Metasurfaces, and in particular reconfigurable intelligent surfaces (RIS), are revolutionizing wireless communications by dynamically controlling electromagnetic waves. Recent wire…
Self-supervised Contrastive Learning for 6G UM-MIMO THz Communications: Improving Robustness Under Imperfect CSI
Rafid Umayer Murshed, Md Saheed Ullah, Mohammad Saquib +1
This paper investigates the potential of contrastive learning in 6G ultra-massive multiple-input multiple-output (UM-MIMO) communication systems, specifically focusing on hybrid be…