7 citations · 14 across the 17 of their papers we have counts for
17 papers
FedVSSAM: Mitigating Flatness Incompatibility in Sharpness-Aware Federated Learning
Bingnan Xiao, Yuan Gao, Bingcong Li +3
Sharpness-aware minimization (SAM) is an effective method for improving the generalization of federated learning (FL) by steering local training toward flat minima. Under data hete…
Event-Triggered Gossip for Distributed Learning
Zhiyuan Zhai, Xiaojun Yuan, Wei Ni +3
While distributed learning offers a new learning paradigm for distributed network with no central coordination, it is constrained by communication bottleneck between nodes. We deve…
Divergence-Based Adaptive Aggregation for Byzantine Robust Federated Learning
Bingnan Xiao, Feng Zhu, Jingjing Zhang +2
Inherent client drifts caused by data heterogeneity, as well as vulnerability to Byzantine attacks within the system, hinder effective model training and convergence in federated l…
Synchronization, Identification, and Signal Detection for Underwater Photon-Counting Communications With Input-Dependent Shot Noise
Fanghua Li, Xiaolin Zhou, Yongkang Chen +4
Photon counting (PhC) is an effective detection technology for underwater optical wireless communication (OWC) systems. The presence of signal-dependent Poisson shot noise and asyn…
Non-Orthogonal Multiple Access-Based Continuous-Variable Quantum Key Distribution: Secret Key Rate Analysis and Power Allocation
Zhichao Dong, Xiaolin Zhou, Huang Peng +3
We address the multi-user quantum key distribution (QKD) problem under malicious quantum attacks, which is critical for realizing a large-scale quantum Internet. This paper maximiz…
Non-Orthogonal Multiple-Access for Coherent-State Optical Quantum Communications Under Lossy Photon Channels
Zhichao Dong, Xiaolin Zhou, Yongkang Chen +3
Coherent states have been increasingly considered in optical quantum communications (OQCs). With the inherent non-orthogonality of coherent states, non-orthogonal multiple-access (…
Learning Performance Optimization for Edge AI System with Time and Energy Constraints
Zhiyuan Zhai, Wei Ni, Xin Wang
Edge AI, which brings artificial intelligence to the edge of the network for real-time processing and decision-making, has emerged as a transformative technology across various app…
Spectral-Convergent Decentralized Machine Learning: Theory and Application in Space Networks
Zhiyuan Zhai, Shuyan Hu, Wei Ni +2
Decentralized machine learning (DML) supports collaborative training in large-scale networks with no central server. It is sensitive to the quality and reliability of inter-device…
Integrated Sensing and Communication with UAV Swarms via Decentralized Consensus ADMM
Zhiyuan Zhai, Wei Ni, Xin Wang +2
UAV swarms can form virtual antenna arrays to exploit additional spatial degrees of freedom and enhance integrated sensing and communication (ISAC). The optimization of UAV positio…
Edge Intelligence in Satellite-Terrestrial Networks with Hybrid Quantum Computing
Siyue Huang, Lifeng Wang, Xin Wang +3
This paper exploits the potential of edge intelligence empowered satellite-terrestrial networks, where users' computation tasks are offloaded to the satellites or terrestrial base…
Towards Dynamic Resource Allocation and Client Scheduling in Hierarchical Federated Learning: A Two-Phase Deep Reinforcement Learning Approach
Xiaojing Chen, Zhenyuan Li, Wei Ni +5
Federated learning (FL) is a viable technique to train a shared machine learning model without sharing data. Hierarchical FL (HFL) system has yet to be studied regrading its multip…
FLARE: A New Federated Learning Framework with Adjustable Learning Rates over Resource-Constrained Wireless Networks
Bingnan Xiao, Jingjing Zhang, Wei Ni +1
Wireless federated learning (WFL) suffers from heterogeneity prevailing in the data distributions, computing powers, and channel conditions of participating devices. This paper pre…
Failure Analysis in Next-Generation Critical Cellular Communication Infrastructures
Siguo Bi, Xin Yuan, Shuyan Hu +4
The advent of communication technologies marks a transformative phase in critical infrastructure construction, where the meticulous analysis of failures becomes paramount in achiev…
Data and Model Poisoning Backdoor Attacks on Wireless Federated Learning, and the Defense Mechanisms: A Comprehensive Survey
Yichen Wan, Youyang Qu, Wei Ni +3
Due to the greatly improved capabilities of devices, massive data, and increasing concern about data privacy, Federated Learning (FL) has been increasingly considered for applicati…
Detection and Mitigation of Position Spoofing Attacks on Cooperative UAV Swarm Formations
Siguo Bi, Kai Li, Shuyan Hu +3
Detecting spoofing attacks on the positions of unmanned aerial vehicles (UAVs) within a swarm is challenging. Traditional methods relying solely on individually reported positions…
Towards Quantum-Native Communication Systems: State-of-the-Art, Trends, and Challenges
Xiaolin Zhou, Anqi Shen, Shuyan Hu +3
The potential synergy between quantum communications and future wireless communication systems is explored. By proposing a quantum-native or quantum-by-design philosophy, the surve…
Over-The-Air Federated Learning: Status Quo, Open Challenges, and Future Directions
Bingnan Xiao, Xichen Yu, Wei Ni +2
The development of applications based on artificial intelligence and implemented over wireless networks is increasingly rapidly and is expected to grow dramatically in the future.…