4 papers
NOMANet: A Graph Neural Network Enabled Power Allocation Scheme for NOMA
Yipu Hou, Yang Lu, Wei Chen +3
This paper proposes a graph neural network (GNN) enabled power allocation scheme for non-orthogonal multiple access (NOMA) networks. In particular, a downlink scenario with one bas…
Graph Neural Network Enabled Pinching Antennas
Xinke Xie, Yang Lu, Zhiguo Ding
The pinching-antenna system is a novel flexible-antenna technology, which has the capabilities not only to combat large-scale path loss, but also to reconfigure the antenna array i…
ICGNN: Graph Neural Network Enabled Scalable Beamforming for MISO Interference Channels
Changpeng He, Yang Lu, Bo Ai +3
This paper investigates the graph neural network (GNN)-enabled beamforming design for interference channels. We propose a model termed interference channel GNN (ICGNN) to solve a q…
Model-Based GNN Enabled Energy-Efficient Beamforming for Ultra-Dense Wireless Networks
Rongsheng Zhang, Yang Lu, Wei Chen +2
This paper investigates deep learning enabled beamforming design for ultra-dense wireless networks by integrating prior knowledge and graph neural network (GNN), named model-based…