9 citations · 13 across the 10 of their papers we have counts for
11 papers
Conditional Diffusion Model-Driven Generative Channels for Double RIS-Aided Wireless Systems
Yiyang Ni, Qi Zhang, Guangji Chen +3
With the development of the upcoming sixth-generation networks (6G), reconfigurable intelligent surfaces (RISs) have gained significant attention due to its ability of reconfigurin…
Attention-Enhanced Prompt Decision Transformers for UAV-Assisted Communications with AoI
Chi Lu, Yiyang Ni, Zhe Wang +3
Decision Transformer (DT) has recently demonstrated strong generalizability in dynamic resource allocation within unmanned aerial vehicle (UAV) networks, compared to conventional d…
Decision Transformers for RIS-Assisted Systems with Diffusion Model-Based Channel Acquisition
Jie Zhang, Yiyang Ni, Jun Li +6
Reconfigurable intelligent surfaces (RISs) have been recognized as a revolutionary technology for future wireless networks. However, RIS-assisted communications have to continuousl…
Adversarial Federated Consensus Learning for Surface Defect Classification Under Data Heterogeneity in IIoT
Jixuan Cui, Jun Li, Zhen Mei +3
The challenge of data scarcity hinders the application of deep learning in industrial surface defect classification (SDC), as it's difficult to collect and centralize sufficient tr…
Resource Efficient Asynchronous Federated Learning for Digital Twin Empowered IoT Network
Shunfeng Chu, Jun Li, Jianxin Wang +4
As an emerging technology, digital twin (DT) can provide real-time status and dynamic topology mapping for Internet of Things (IoT) devices. However, DT and its implementation with…
Blockchain-aided wireless federated learning: Resource allocation and client scheduling
Jun Li, Weiwei Zhang, Kang Wei +4
Federated learning (FL) based on the centralized design faces both challenges regarding the trust issue and a single point of failure. To alleviate these issues, blockchain-aided d…
Trustworthy DNN Partition for Blockchain-enabled Digital Twin in Wireless IIoT Networks
Xiumei Deng, Jun Li, Long Shi +5
Digital twin (DT) has emerged as a promising solution to enhance manufacturing efficiency in industrial Internet of Things (IIoT) networks. To promote the efficiency and trustworth…
Robust Model Aggregation for Heterogeneous Federated Learning: Analysis and Optimizations
Yumeng Shao, Jun Li, Long Shi +6
Conventional synchronous federated learning (SFL) frameworks suffer from performance degradation in heterogeneous systems due to imbalanced local data size and diverse computing po…
Deploying Graph Neural Networks in Wireless Networks: A Link Stability Viewpoint
Jun Li, Weiwei Zhang, Kang Wei +3
As an emerging artificial intelligence technology, graph neural networks (GNNs) have exhibited promising performance across a wide range of graph-related applications. However, inf…
Towards Communication-efficient Federated Learning via Sparse and Aligned Adaptive Optimization
Xiumei Deng, Jun Li, Kang Wei +6
Adaptive moment estimation (Adam), as a Stochastic Gradient Descent (SGD) variant, has gained widespread popularity in federated learning (FL) due to its fast convergence. However,…
Decision Transformers for Wireless Communications: A New Paradigm of Resource Management
Jie Zhang, Jun Li, Long Shi +4
As the next generation of mobile systems evolves, artificial intelligence (AI) is expected to deeply integrate with wireless communications for resource management in variable envi…