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20242026
most citedGraph Neural Networks and Deep Reinforcement Learning Based Resource Allocation for V2X Communications

1 citations · 3 across the 28 of their papers we have counts for

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13 papers · 1 filter

cs.LG2026

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…

cs.LG2025

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…

cs.LG2025

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…

cs.LG2025

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…

cs.LG2024

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…

cs.LG2024

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…