7 papers
A Modular and Scalable Simulator for Connected-UAVs Communication in 5G Networks
Yong Su, Yiyi Chen, Shenghong Yi +4
Cellular-connected UAV systems have enabled a wide range of low-altitude aerial services. However, these systems still face many challenges, such as frequent handovers and the inef…
On Sampling of Multiple Correlated Stochastic Signals
Lin Jin, Hang Sheng, Hui Feng +1
Multiple stochastic signals possess inherent statistical correlations, yet conventional sampling methods that process each channel independently result in data redundancy. To lever…
Subset Random Sampling and Reconstruction of Finite Time-Vertex Graph Signals
Hang Sheng, Qinji Shu, Hui Feng +1
Finite time-vertex graph signals (FTVGS) provide an efficient representation for capturing spatio-temporal correlations across multiple data sources on irregular structures. Althou…
Sampling Theory of Jointly Bandlimited Time-vertex Graph Signals
Hang Sheng, Hui Feng, Junhao Yu +2
Time-vertex graph signal (TVGS) models describe time-varying data with irregular structures. The bandlimitedness in the joint time-vertex Fourier spectral domain reflects smoothnes…
Invariant Federated Learning for Edge Intelligence: Mitigating Heterogeneity and Asynchrony via Exit Strategy and Invariant Penalty
Ziruo Hao, Zhenhua Cui, Tao Yang +3
This paper provides an invariant federated learning system for resource-constrained edge intelligence. This framework can mitigate the impact of heterogeneity and asynchrony via ex…
The Impact Analysis of Delays in Asynchronous Federated Learning with Data Heterogeneity for Edge Intelligence
Ziruo Hao, Zhenhua Cui, Tao Yang +3
Federated learning (FL) has provided a new methodology for coordinating a group of clients to train a machine learning model collaboratively, bringing an efficient paradigm in edge…