1 citations · 1 across the 6 of their papers we have counts for
6 papers
RIS-based Communication Enhancement and Location Privacy Protection in UAV Networks
Ziqi Chen, Jun Du, Chunxiao Jiang +2
With the explosive advancement of unmanned aerial vehicles (UAVs), the security of efficient UAV networks has become increasingly critical. Owing to the open nature of its communic…
Sovereign AI for 6G: Towards the Future of AI-Native Networks
Swarna Bindu Chetty, David Grace, Simon Saunders +4
The advent of Generative Artificial Intelligence (GenAI), Large Language Models (LLMs), and Large Telecom Models (LTM) significantly reshapes mobile networks, especially as the tel…
Pigeon-SL: Robust Split Learning Framework for Edge Intelligence under Malicious Clients
Sangjun Park, Tony Q. S. Quek, Hyowoon Seo
Recent advances in split learning (SL) have established it as a promising framework for privacy-preserving, communication-efficient distributed learning at the network edge. Howeve…
Capacity Analysis on OAM-Based Wireless Communications: An Electromagnetic Information Theory Perspective
Runyu Lyu, Wenchi Cheng, Qinghe Du +1
Orbital angular momentum (OAM) technology enhances the spectrum and energy efficiency of wireless communications by enabling multiplexing over different OAM modes. However, classic…
A New Channel Model for OAM Wireless Communication at 5.8 and 28 GHz
Runyu Lyu, Wenchi Cheng, Muyao Wang +2
Orbital angular momentum (OAM) in electromagnetic (EM) waves can significantly enhance spectrum efficiency in wireless communications without requiring additional power, time, or f…
Training Classifiers that are Universally Robust to All Label Noise Levels
Jingyi Xu, Tony Q. S. Quek, Kai Fong Ernest Chong
For classification tasks, deep neural networks are prone to overfitting in the presence of label noise. Although existing methods are able to alleviate this problem at low noise le…