5 citations · 8 across the 5 of their papers we have counts for
5 papers
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…
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…
GNN-Based Joint Channel and Power Allocation in Heterogeneous Wireless Networks
Lili Chen, Jingge Zhu, Jamie Evans
The optimal allocation of channels and power resources plays a crucial role in ensuring minimal interference, maximal data rates, and efficient energy utilisation. As a successful…
Accelerating Graph Neural Networks via Edge Pruning for Power Allocation in Wireless Networks
Lili Chen, Jingge Zhu, Jamie Evans
Graph Neural Networks (GNNs) have recently emerged as a promising approach to tackling power allocation problems in wireless networks. Since unpaired transmitters and receivers are…
Graph Neural Networks for Power Allocation in Wireless Networks with Full Duplex Nodes
Lili Chen, Jingge Zhu, Jamie Evans
Due to mutual interference between users, power allocation problems in wireless networks are often non-convex and computationally challenging. Graph neural networks (GNNs) have rec…