6 papers
BERT4beam: Large AI Model Enabled Generalized Beamforming Optimization
Yuhang Li, Yang Lu, Wei Chen +2
Artificial intelligence (AI) is anticipated to emerge as a pivotal enabler for the forthcoming sixth-generation (6G) wireless communication systems. However, current research effor…
GNN-Enabled Robust Hybrid Beamforming with Score-Based CSI Generation and Denoising
Yuhang Li, Yang Lu, Bo Ai +2
Accurate Channel State Information (CSI) is critical for Hybrid Beamforming (HBF) tasks. However, obtaining high-resolution CSI remains challenging in practical wireless communicat…
Spectral- and Energy-efficient Multi-BS Multi-RIS Pinching-antenna Systems: A GNN-based Approach
Changpeng He, Yang Lu, Wei Chen +3
This paper investigates coordinated downlink transmission in a multi-base station (multi-BS) multi-reconfigurable intelligent surface (multi-RIS)-assisted pinching-antenna (PA) sys…
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…