6 papers
Semantic-Aware Command and Control Transmission for Multi-UAVs
Boya Li, Xiaonan Liu, Dongzhu Liu +2
Uncrewed aerial vehicles (UAVs) have played an important role in the low-altitude economy and have been used in various applications. However, with the increasing number of UAVs an…
Null-Space Flow Matching for MIMO Channel Estimation in Latency-Constrained Systems
Junjie Zhao, Guangming Liang, Dongzhu Liu +1
Accurate yet low-latency channel state information (CSI) acquisition is essential for multiple-input multiple-output (MIMO) communication systems. While advanced deep generative mo…
Joint User Association and Resource Allocation for Adaptive Semantic Communication in 5G and Beyond Networks
Xingqiu He, Chaoqun You, Zihan Chen +4
Semantic communication (SemCom) has emerged as a promising paradigm that leverages Deep Neural Networks (DNNs) to extract task-relevant information, thereby substantially reducing…
Environment-Aware Channel Inference via Cross-Modal Flow: From Multimodal Sensing to Wireless Channels
Guangming Liang, Mingjie Yang, Dongzhu Liu +2
Accurate channel state information (CSI) underpins reliable and efficient wireless communication. However, acquiring CSI via pilot estimation incurs substantial overhead, especiall…
Efficient Wireless Federated Learning via Low-Rank Gradient Factorization
Mingzhao Guo, Dongzhu Liu, Osvaldo Simeone +1
This paper presents a novel gradient compression method for federated learning (FL) in wireless systems. The proposed method centers on a low-rank matrix factorization strategy for…
Personalizing Low-Rank Bayesian Neural Networks Via Federated Learning
Boning Zhang, Dongzhu Liu, Osvaldo Simeone +3
To support real-world decision-making, it is crucial for models to be well-calibrated, i.e., to assign reliable confidence estimates to their predictions. Uncertainty quantificatio…