7 papers
AoI-Oriented Globally Optimal Joint Source and Update Scheduling in Fluid Antenna Systems
Xiaopeng Yuan, Paul Zheng, Anke Schmeink
As a promising technique, fluid antennas enable adaptive radio environment management and interference mitigation through reconfigurable fluid port selections. In this work, to exp…
Benchmarking Wireless Representations: High-Dimensional vs. Compressed Embeddings for Efficiency and Robustness
Murilo Batista, Shirin Salehi, Saeed Mashdour +3
Building on recent advances in representation learning for wireless channels, this work investigates the cost-benefit trade-offs of high-dimensional channel embeddings in practical…
Analytically Characterized Optimal Power Control for Signal-Level-Integrated Sensing, Computing and Communication in Federated Learning
Paul Zheng, Yao Zhu, Xiaopeng Yuan +2
In the Internet-of-Things (IoT) era, efficient functionality integration is essential to address the growing demands of communication, computation, and sensing. Signal-level integr…
On Signal Peak Power Constraint of Over-the-Air Federated Learning
Lorenz Bielefeld, Paul Zheng, Oner Hanay +3
Federated learning (FL) has been considered a promising privacy preserving distributed edge learning framework. Over-the-air computation (AirComp) leveraging analog transmission en…
Joint Communication Scheduling and Resource Allocation for Distributed Edge Learning: Seamless Integration in Next-Generation Wireless Networks
Paul Zheng, Navid Keshtiarast, Pradyumna Kumar Bishoyi +4
Distributed edge learning (DL) is considered a cornerstone of intelligence enablers, since it allows for collaborative training without the necessity for local clients to share raw…
Joint Link Adaptation and Device Scheduling Approach for URLLC Industrial IoT Network: A DRL-based Method with Bayesian Optimization
Wei Gao, Paul Zheng, Peng Wu +2
In this article, we consider an industrial internet of things (IIoT) network supporting multi-device dynamic ultra-reliable low-latency communication (URLLC) while the channel stat…