activity
20162025
most citedCross-layer Design for Mission-Critical IoT in Mobile Edge Computing Systems

58 citations · 201 across the 41 of their papers we have counts for

collaborators

44 papers

cs.LG2025

Graph Neural Networks for Resource Allocation in Interference-limited Multi-Channel Wireless Networks with QoS Constraints

Lili Chen, Changyang She, Jingge Zhu +1

Meeting minimum data rate constraints is a significant challenge in wireless communication systems, particularly as network complexity grows. Traditional deep learning approaches o…

cs.LG2025★ 1 cited

Graph Neural Networks for Resource Allocation in Multi-Channel Wireless Networks

Lili Chen, Changyang She, Jingge Zhu +1

As the number of mobile devices continues to grow, interference has become a major bottleneck in improving data rates in wireless networks. Efficient joint channel and power alloca…

cs.IT2025

Radio Map-Enabled 3D Trajectory and Communication Optimization for Low-Altitude Air-Ground Cooperation

Menghao Hu, Tong Zhang, Shuai Wang +4

Low-altitude economy includes the application of unmanned aerial vehicles (UAVs) serving ground robots. This paper investigates the 3-dimensional (3D) trajectory and communication…

cs.IT2025

Aligning Task- and Reconstruction-Oriented Communications for Edge Intelligence

Yufeng Diao, Yichi Zhang, Changyang She +2

Existing communication systems aim to reconstruct the information at the receiver side, and are known as reconstruction-oriented communications. This approach often falls short in…

cs.LG2024★ 1 cited

GNN-based Auto-Encoder for Short Linear Block Codes: A DRL Approach

Kou Tian, Chentao Yue, Changyang She +2

This paper presents a novel auto-encoder based end-to-end channel encoding and decoding. It integrates deep reinforcement learning (DRL) and graph neural networks (GNN) in code des…

eess.SY2024

Augmented Intelligence in Smart Intersections: Local Digital Twins-Assisted Hybrid Autonomous Driving

Kui Wang, Kazuma Nonomura, Zongdian Li +6

Vehicle-road collaboration is a promising approach for enhancing the safety and efficiency of autonomous driving by extending the intelligence of onboard systems to smart roadside…