1 citations · 1 across the 33 of their papers we have counts for
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Convergence-Latency-Aware Adaptive Modulation and Resource Allocation in RIS-Assisted Wireless Federated Learning
Liwei Wang, Wen Chen, Jun Li +4
Federated learning (FL) over wireless networks suffers from significant training latency and degraded convergence due to unreliable wireless transmission, especially under blocked…
U-Parking: Distributed UWB-Assisted Autonomous Parking System with Robust Localization and Intelligent Planning
Yiang Wu, Qiong Wu, Pingyi Fan +4
This demonstration presents U-Parking, a distributed Ultra-Wideband (UWB)-assisted autonomous parking system. By integrating Large Language Models (LLMs)-assisted planning with rob…
Semantic-Aware Cooperative Communication and Computation Framework in Vehicular Networks
Jingbo Zhang, Maoxin Ji, Qiong Wu +3
Semantic Communication (SC) combined with Vehicular edge computing (VEC) provides an efficient edge task processing paradigm for Internet of Vehicles (IoV). Focusing on highway sce…
Personalized Federated Distillation Assisted Vehicle Edge Caching Strategy
Xun Li, Qiong Wu, Pingyi Fan +3
Vehicle edge caching is a promising technology that can significantly reduce the latency for vehicle users (VUs) to access content by pre-caching user-interested content at edge no…
Velocity and Density-Aware RRI Analysis and Optimization for AoI Minimization in IoV SPS
Maoxin Ji, Tong Wang, Qiong Wu +3
Addressing the problem of Age of Information (AoI) deterioration caused by packet collisions and vehicle speed-related channel uncertainties in Semi-Persistent Scheduling (SPS) for…
DRL-Based Optimization for AoI and Energy Consumption in C-V2X Enabled IoV
Zheng Zhang, Qiong Wu, Pingyi Fan +3
To address communication latency issues, the Third Generation Partnership Project (3GPP) has defined Cellular-Vehicle to Everything (C-V2X) technology, which includes Vehicle-to-Ve…
Semantic-Aware Resource Management for C-V2X Platooning via Multi-Agent Reinforcement Learning
Wenjun Zhang, Qiong Wu, Pingyi Fan +4
Semantic communication transmits the extracted features of information rather than raw data, significantly reducing redundancy, which is crucial for addressing spectrum and energy…
DRL-Based Federated Self-Supervised Learning for Task Offloading and Resource Allocation in ISAC-Enabled Vehicle Edge Computing
Xueying Gu, Qiong Wu, Pingyi Fan +3
Intelligent Transportation Systems (ITS) leverage Integrated Sensing and Communications (ISAC) to enhance data exchange between vehicles and infrastructure in the Internet of Vehic…
Reconfigurable Intelligent Surface Aided Vehicular Edge Computing: Joint Phase-shift Optimization and Multi-User Power Allocation
Kangwei Qi, Qiong Wu, Pingyi Fan +3
Vehicular edge computing (VEC) is an emerging technology with significant potential in the field of internet of vehicles (IoV), enabling vehicles to perform intensive computational…
Graph Neural Networks and Deep Reinforcement Learning Based Resource Allocation for V2X Communications
Maoxin Ji, Qiong Wu, Pingyi Fan +4
In the rapidly evolving landscape of Internet of Vehicles (IoV) technology, Cellular Vehicle-to-Everything (C-V2X) communication has attracted much attention due to its superior pe…