activity
20242026
most citedJoint Communication Scheduling and Resource Allocation for Distributed Edge Learning: Seamless Integration in Next-Generation Wireless Networks

1 citations · 1 across the 12 of their papers we have counts for

collaborators

13 papers

eess.SP2026

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…

cs.IT2026

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…

cs.IT2026

Deep Reinforcement Learning for Cognitive Time-Division Joint SAR and Secure Communications

Mohamed-Amine Lahmeri, Ata Khalili, Yujiao Liu +2

Synthetic aperture radar (SAR) imaging can be exploited to enhance wireless communication performance through high-precision environmental awareness. However, integrating sensing a…

eess.SY2026

Efficient Trajectory Design and Communication Scheduling for Dual-UAV Jamming-Aided Secure Communication Networks

Xinran Wang, Peng Wu, Xiaopeng Yuan +2

We study dual-unmanned aerial vehicle (UAV) jamming-aided secure communication networks, in which one UAV delivers confidential data to multiple ground users (GUs), while a coopera…

cs.IT2026

Confusions and Erasures of Error-Bounded Block Decoders with Finite Blocklength

Bin Han, Yao Zhu, Rafael F. Schaefer +4

This paper investigates two distinct types of block errors - undetected errors (confusions) and erasures - in additive white Gaussian noise (AWGN) channels with error-bounded block…

cs.LG2025

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…

eess.SP2025

Efficient Joint Resource Allocation for Wireless Powered ISAC with Target Localization

Boyao Li, Qinwei He, Boao Zhang +2

Wireless powered integrated sensing and communication (ISAC) faces a fundamental tradeoff between energy supply, communication throughput, and sensing accuracy. This paper investig…

eess.SP2025

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…

cs.CR2025

Physical Layer Deception as a Stackelberg Game: Strategy Regimes, Equilibrium, and Robust Design

Wenwen Chen, Bin Han, Yao Zhu +3

Physical layer deception (PLD) combines physical layer security (PLS) with deception: the transmitter actively misleads the eavesdropper with falsified information. We model the tr…

eess.SY2025★ 1 cited

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…

eess.SY2025

Efficient Integration of Distributed Learning Services in Next-Generation Wireless Networks

Paul Zheng, Navid Keshtiarast, Pradyumna Kumar Bishoyi +4

Distributed learning (DL) is considered a cornerstone of intelligence enabler, since it allows for collaborative training without the necessity for local clients to share raw data…

cs.IT2024

Physical Layer Deception in OFDM Systems

Wenwen Chen, Bin Han, Yao Zhu +2

As a promising technology, physical layer security (PLS) enhances security by leveraging the physical characteristics of communication channels. However, it commonly takes the legi…

cs.IT2024

A Semantic Model for Physical Layer Deception

Bin Han, Yao Zhu, Anke Schmeink +2

Physical layer deception (PLD) is a novel security mechanism that combines physical layer security (PLS) with deception technologies to actively defend against eavesdroppers. In th…