1 citations · 3 across the 28 of their papers we have counts for
16 papers · 1 filter
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…
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…
Channel Characterization of IRS-assisted Resonant Beam Communication Systems
Wen Fang, Wen Chen, Qingqing Wu +3
To meet the growing demand for data traffic, spectrum-rich optical wireless communication (OWC) has emerged as a key technological driver for the development of 6G. The resonant be…
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…
Cramer-Rao Bound Minimization for Movable Antenna-Assisted Multiuser Integrated Sensing and Communications
Haoran Qin, Wen Chen, Qingqing Wu +3
This paper investigates a movable antenna (MA)-assisted multiuser integrated sensing and communication (ISAC) system, where the base station (BS) and communication users are all eq…
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…
Movable Antenna Enhanced NOMA Short-Packet Transmission
Xinyuan He, Wen Chen, Qingqing Wu +2
This letter investigates a short-packet downlink transmission system using non-orthogonal multiple access (NOMA) enhanced via movable antenna (MA). We focuses on maximizing the eff…
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 Spectrum Sharing in Internet of Vehicles Based on Deep Reinforcement Learning
Zhiyu Shao, Qiong Wu, Pingyi Fan +4
This work aims to investigate semantic communication in high-speed mobile Internet of vehicles (IoV) environments, with a focus on the spectrum sharing between vehicle-to-vehicle (…