activity
20112026
most citedStatistical Age-of-Information Optimization for Status Update over Multi-State Fading Channels

15 citations · 34 across the 12 of their papers we have counts for

collaborators

13 papers

cs.CR2026

Diff-DDoS: Realistic Cyber-Physical Attack Synthesis and Robust Detection for 5G-Enabled CPS Using Tabular Diffusion Models

Bilal Hussain, Xiao Tang, Qinghe Du +3

Deep learning-based DDoS detectors for 5G-enabled cyber-physical systems face scarce labeled attack data and unrealistic synthetic substitutes, which limit robustness against adapt…

eess.SP2023

A Two-Dimensional Deep Network for RF-based Drone Detection and Identification Towards Secure Coverage Extension

Zixiao Zhao, Qinghe Du, Xiang Yao +2

As drones become increasingly prevalent in human life, they also raises security concerns such as unauthorized access and control, as well as collisions and interference with manne…

cs.IT2023★ 15 cited

Statistical Age-of-Information Optimization for Status Update over Multi-State Fading Channels

Yuquan Xiao, Qinghe Du

Age of information (AoI) is a powerful metric to evaluate the freshness of information, where minimization of average statistics, such as the average AoI and average peak AoI, curr…

eess.SP2023

Robust Secrecy via Aerial Reflection and Jamming: Joint Optimization of Deployment and Transmission

Xiao Tang, Hongliang He, Limeng Dong +3

Reconfigurable intelligent surfaces (RISs) are recognized with great potential to strengthen wireless security, yet the performance gain largely depends on the deployment location…

cs.IT2022★ 1 cited

Improved Grant-Free Access for URLLC via Multi-Tier-Driven Computing: Network-Load Learning, Prediction, and Resource Allocation

Zixiao Zhao, Qinghe Du, George K. Karagiannidis

Grant-Free (GF) access has been recognized as a promising candidate for Ultra-Reliable and Low-Latency Communications (URLLC). However, even with GF access, URLLC still may not eff…

eess.SP2022

Online Learning of Trellis Diagram Using Neural Network for Robust Detection and Decoding

Jie Yang, Qinghe Du, Yi Jiang

This paper studies machine learning-assisted maximum likelihood (ML) and maximum a posteriori (MAP) receivers for a communication system with memory, which can be modelled by a tre…