16 citations · 52 across the 13 of their papers we have counts for
14 papers
Decentralized Federated Learning for Heterogeneous Multi-Task Semantic Communication
Lin Yin, Tiejun Lv, Weicai Li +2
Collaborative training in distributed semantic communication (DSC) networks typically relies on decentralized federated learning (DFL). However, pushing topology-agnostic aggregati…
Adaptive Dual-Path Framework for Covert Semantic Communication
Xi Yu, Weicai Li, Lin Yin +1
This paper proposes a novel adaptive dual-path framework for covert semantic communication (SemCom), which integrates covert information transmission with task-oriented semantic co…
Joint Routing and Model Pruning for Decentralized Federated Learning in Bandwidth-Constrained Multi-Hop Wireless Networks
Xiaoyu He, Weicai Li, Tiejun Lv +1
Decentralized federated learning (D-FL) enables privacy-preserving training without a central server, but multi-hop model exchanges and aggregation are often bottlenecked by commun…
Navigating the Dual-Use Nature and Security Implications of Reconfigurable Intelligent Surfaces in Next-Generation Wireless Systems
Hetong Wang, Tiejun Lv, Yashuai Cao +4
Reconfigurable intelligent surface (RIS) technology offers significant promise in enhancing wireless communication systems, but its dual-use potential also introduces substantial s…
Free Privacy Protection for Wireless Federated Learning: Enjoy It or Suffer from It?
Weicai Li, Tiejun Lv, Xiyu Zhao +2
Inherent communication noises have the potential to preserve privacy for wireless federated learning (WFL) but have been overlooked in digital communication systems predominantly u…
Convergence-Privacy-Fairness Trade-Off in Personalized Federated Learning
Xiyu Zhao, Qimei Cui, Weicai Li +5
Personalized federated learning (PFL), e.g., the renowned Ditto, strikes a balance between personalization and generalization by conducting federated learning (FL) to guide persona…
Enhancing Convergence, Privacy and Fairness for Wireless Personalized Federated Learning: Quantization-Assisted Min-Max Fair Scheduling
Xiyu Zhao, Qimei Cui, Ziqiang Du +6
Personalized federated learning (PFL) offers a solution to balancing personalization and generalization by conducting federated learning (FL) to guide personalized learning (PL). L…
Subspace-Based Super-Resolution Sensing for Bi-Static ISAC with Clock Asynchronism
Jingbo Zhao, Zhaoming Lu, J. Andrew Zhang +3
Bi-static sensing is an attractive configuration for integrated sensing and communications (ISAC) systems; however, clock asynchronism between widely separated transmitters and rec…
Route-and-Aggregate Decentralized Federated Learning Under Communication Errors
Weicai Li, Tiejun Lv, Wei Ni +3
Decentralized federated learning (D-FL) allows clients to aggregate learning models locally, offering flexibility and scalability. Existing D-FL methods use gossip protocols, which…
Multi-Task Semantic Communication With Graph Attention-Based Feature Correlation Extraction
Xi Yu, Tiejun Lv, Weicai Li +3
Multi-task semantic communication can serve multiple learning tasks using a shared encoder model. Existing models have overlooked the intricate relationships between features extra…
Decentralized Federated Learning Over Imperfect Communication Channels
Weicai Li, Tiejun Lv, Wei Ni +3
This paper analyzes the impact of imperfect communication channels on decentralized federated learning (D-FL) and subsequently determines the optimal number of local aggregations p…
Performance Bounds for Passive Sensing in Asynchronous ISAC Systems -- Appendices
Jingbo Zhao, Zhaoming Lu, J. Andrew Zhang +5
This document contains the appendices for our paper titled ``Performance Bounds for Passive Sensing in Asynchronous ISAC Systems." The appendices include rigorous derivations of ke…
Multi-Carrier NOMA-Empowered Wireless Federated Learning with Optimal Power and Bandwidth Allocation
Weicai Li, Tiejun Lv, Yashuai Cao +2
Wireless federated learning (WFL) undergoes a communication bottleneck in uplink, limiting the number of users that can upload their local models in each global aggregation round.…
When Internet of Things meets Metaverse: Convergence of Physical and Cyber Worlds
Kai Li, Yingping Cui, Weicai Li +6
In recent years, the Internet of Things (IoT) is studied in the context of the Metaverse to provide users immersive cyber-virtual experiences in mixed reality environments. This su…