13 citations · 15 across the 22 of their papers we have counts for
23 papers
Joint Optimization of Trajectory Control, Resource Allocation, and Task Offloading for Multi-UAV-Assisted IoV
Maoxin Ji, Qiong Wu, Pingyi Fan +4
This paper investigates a multi-Unmanned Aerial Vehicle (UAV) joint base station-assisted Internet of Vehicles (IoV) task offloading system in dense urban environments. To minimize…
LLM-Empowered Cooperative Content Caching in Vehicular Fog Caching-Assisted Platoon Networks
Bowen Tan, Qiong Wu, Pingyi Fan +3
This letter proposes a novel three-tier content caching architecture for Vehicular Fog Caching (VFC)-assisted platoon, where the VFC is formed by the vehicles driving near the plat…
Accurate Network Traffic Matrix Prediction via LEAD: a Large Language Model-Enhanced Adapter-Based Conditional Diffusion Model
Yu Sun, Yaqiong Liu, Nan Cheng +4
Driven by the evolution toward 6G and AI-native edge intelligence, network operations increasingly require predictive and risk-aware adaptation under stringent computation and late…
Velocity-Adaptive Access Scheme for Semantic-Aware Vehicular Networks: Joint Fairness and AoI Optimization
Xiao Xu, Qiong Wu, Pingyi Fan +4
In this paper, we address the problem of fair access and Age of Information (AoI) optimization in 5G New Radio (NR) Vehicle to Everything (V2X) Mode 2. Specifically, vehicles need…
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…
Large Language Model-Based Task Offloading and Resource Allocation for Digital Twin Edge Computing Networks
Qiong Wu, Yu Xie, Pingyi Fan +4
In this paper, we propose a general digital twin edge computing network comprising multiple vehicles and a server. Each vehicle generates multiple computing tasks within a time slo…
Enhanced Velocity-Adaptive Scheme: Joint Fair Access and Age of Information Optimization in Vehicular Networks
Xiao Xu, Qiong Wu, Pingyi Fan +4
In this paper, we consider the fair access problem and the Age of Information (AoI) under 5G New Radio (NR) Vehicle-to-Infrastructure (V2I) Mode 2 in vehicular networks. Specifical…
Federated Learning Assisted Edge Caching Scheme Based on Lightweight Architecture DDPM
Xun Li, Qiong Wu, Pingyi Fan +3
Edge caching is an emerging technology that empowers caching units at edge nodes, allowing users to fetch contents of interest that have been pre-cached at the edge nodes. The key…
PPO-Based Vehicle Control for Ramp Merging Scheme Assisted by Enhanced C-V2X
Qiong Wu, Maoxin Ji, Pingyi Fan +4
On-ramp merging presents a critical challenge in autonomous driving, as vehicles from merging lanes need to dynamically adjust their positions and speeds while monitoring traffic o…
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…
V2X-Assisted Distributed Computing and Control Framework for Connected and Automated Vehicles under Ramp Merging Scenario
Qiong Wu, Jiahou Chu, Pingyi Fan +4
This paper investigates distributed computing and cooperative control of connected and automated vehicles (CAVs) in ramp merging scenario under transportation cyber-physical system…
Blockchain-Enabled Variational Information Bottleneck for Data Extraction Based on Mutual Information in Internet of Vehicles
Cui Zhang, Wenjun Zhang, Qiong Wu +4
The Internet of Vehicles (IoV) network can address the issue of limited computing resources and data processing capabilities of individual vehicles, but it also brings the risk of…
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…
DRL-Based Resource Allocation for Motion Blur Resistant Federated Self-Supervised Learning in IoV
Xueying Gu, Qiong Wu, Pingyi Fan +4
In the Internet of Vehicles (IoV), Federated Learning (FL) provides a privacy-preserving solution by aggregating local models without sharing data. Traditional supervised learning…
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…
Resource Allocation for Twin Maintenance and Computing Task Processing in Digital Twin Vehicular Edge Computing Network
Yu Xie, Qiong Wu, Pingyi Fan +4
As a promising technology, vehicular edge computing (VEC) can provide computing and caching services by deploying VEC servers near vehicles. However, VEC networks still face challe…
Enhancing Robustness and Security in ISAC Network Design: Leveraging Transmissive Reconfigurable Intelligent Surface with RSMA
Ziwei Liu, Wen Chen, Qingqing Wu +4
In this paper, we propose a novel transmissive reconfigurable intelligent surface transceiver-enhanced robust and secure integrated sensing and communication network. A time-divisi…
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…
Optimizing Age of Information in Vehicular Edge Computing with Federated Graph Neural Network Multi-Agent Reinforcement Learning
Wenhua Wang, Qiong Wu, Pingyi Fan +4
With the rapid development of intelligent vehicles and Intelligent Transport Systems (ITS), the sensors such as cameras and LiDAR installed on intelligent vehicles provides higher…
Reconfigurable Intelligent Surface Assisted VEC Based on Multi-Agent Reinforcement Learning
Kangwei Qi, Qiong Wu, Pingyi Fan +3
Vehicular edge computing (VEC) is an emerging technology that enables vehicles to perform high-intensity tasks by executing tasks locally or offloading them to nearby edge devices.…
Deep-Reinforcement-Learning-Based AoI-Aware Resource Allocation for RIS-Aided IoV Networks
Kangwei Qi, Qiong Wu, Pingyi Fan +4
Reconfigurable Intelligent Surface (RIS) is a pivotal technology in communication, offering an alternative path that significantly enhances the link quality in wireless communicati…
Semantic-Aware Resource Allocation Based on Deep Reinforcement Learning for 5G-V2X HetNets
Zhiyu Shao, Qiong Wu, Pingyi Fan +3
This letter proposes a semantic-aware resource allocation (SARA) framework with flexible duty cycle (DC) coexistence mechanism (SARADC) for 5G-V2X Heterogeneous Network (HetNets) b…
Vehicular Communication Networks in Automated Driving Era
Shan Zhang, Jiayin Chen, Feng Lyu +4
Embedded with advanced sensors, cameras and processors, the emerging automated driving vehicles are capable of sensing the environment and conducting automobile operation, paving t…