3 papers
cs.IT2026
Type-Based Unsourced Federated Learning With Client Self-Selection
Kaan Okumus, Khac-Hoang Ngo, Unnikrishnan Kunnath Ganesan +3
We address the client-selection problem in federated learning over wireless networks under data heterogeneity. Existing client-selection methods often rely on server-side knowledge…
cs.IT2025
Type-Based Unsourced Multiple Access over Fading Channels with Cell-Free Massive MIMO
Kaan Okumus, Khac-Hoang Ngo, Giuseppe Durisi +1
Type-based unsourced multiple access (TUMA) is a recently proposed framework for type-based estimation in massive uncoordinated access networks. We extend the existing design of TU…
cs.IT2025
An Achievability Bound for Type-Based Unsourced Multiple Access
Deekshith Pathayappilly Krishnan, Kaan Okumus, Khac-Hoang Ngo +1
We derive an achievability bound to quantify the performance of a type-based unsourced multiple access system -- an information-theoretic model for grant-free multiple access with…