9 citations · 9 across the 10 of their papers we have counts for
10 papers
Edge-Assisted Accelerated Cooperative Sensing for CAVs: Task Placement and Resource Allocation
Yuxuan Wang, Kaige Qu, Wen Wu +2
In this paper, we propose a novel road side unit (RSU)-assisted cooperative sensing scheme for connected autonomous vehicles (CAVs), with the objective to reduce completion time of…
Meta Learning Based Adaptive Cooperative Perception in Nonstationary Vehicular Networks
Kaige Qu, Zixiong Qin, Weihua Zhuang
To accommodate high network dynamics in real-time cooperative perception (CP), reinforcement learning (RL) based adaptive CP schemes have been proposed, to allow adaptive switching…
Accuracy-Aware Cooperative Sensing and Computing for Connected Autonomous Vehicles
Xuehan Ye, Kaige Qu, Weihua Zhuang +1
To maintain high perception performance among connected and autonomous vehicles (CAVs), in this paper, we propose an accuracy-aware and resource-efficient raw-level cooperative sen…
Digital Twin Assisted Intelligent Network Management for Vehicular Applications
Kaige Qu, Weihua Zhuang
The emerging data-driven methods based on artificial intelligence (AI) have paved the way for intelligent, flexible, and adaptive network management in vehicular applications. To e…
Model-Assisted Learning for Adaptive Cooperative Perception of Connected Autonomous Vehicles
Kaige Qu, Weihua Zhuang, Qiang Ye +2
Cooperative perception (CP) is a key technology to facilitate consistent and accurate situational awareness for connected and autonomous vehicles (CAVs). To tackle the network reso…
Digital Twin-Based User-Centric Edge Continual Learning in Integrated Sensing and Communication
Shisheng Hu, Jie Gao, Xinyu Huang +5
In this paper, we propose a digital twin (DT)-based user-centric approach for processing sensing data in an integrated sensing and communication (ISAC) system with high accuracy an…
Millimeter Wave Full-Duplex Networks: MAC Design and Throughput Optimization
Shengbo Liu, Wen Wu, Liqun Fu +4
Full-duplex (FD) technique can remarkably boost the network capacity in the millimeter wave (mmWave) bands by enabling simultaneous transmission and reception. However, due to dire…
Cost-Effective Two-Stage Network Slicing for Edge-Cloud Orchestrated Vehicular Networks
Wen Wu, Kaige Qu, Peng Yang +4
In this paper, we study a network slicing problem for edge-cloud orchestrated vehicular networks, in which the edge and cloud servers are orchestrated to process computation tasks…
Split Learning over Wireless Networks: Parallel Design and Resource Management
Wen Wu, Mushu Li, Kaige Qu +6
Split learning (SL) is a collaborative learning framework, which can train an artificial intelligence (AI) model between a device and an edge server by splitting the AI model into…
Delay-Aware Flow Migration for Embedded Services in 5G Core Networks
Kaige Qu, Weihua Zhuang, Qiang Ye +4
Service-oriented virtual network deployment is based on statistical resource demands of different services, while data traffic from each service fluctuates over time. In this paper…