12 papers
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…
Two-Stage Heterogeneous Graph Neural Network for RIS-Aided Physical-Layer Security
Zihan Song, Yang Lu, Wei Chen +3
This paper investigates physical-layer security (PLS) enabled by graph neural networks (GNNs). We propose a two-stage heterogeneous GNN (HGNN) to maximize the secrecy energy effici…
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…
Mamba for Wireless Communications and Networking: Principles and Opportunities
Rongsheng Zhang, Ruichen Zhang, Yang Lu +3
Mamba has emerged as a powerful model for efficiently addressing tasks involving temporal and spatial data. Regarding the escalating heterogeneity and dynamics in wireless networks…
6G-Enabled Smart Railways
Bo Ai, Yunlong Lu, Yuguang Fang +7
Smart railways integrate advanced information technologies into railway operating systems to improve efficiency and reliability. Although the development of 5G has enhanced railway…
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…
SWIPTNet: A Unified Deep Learning Framework for SWIPT based on GNN and Transfer Learning
Hong Han, Yang Lu, Zihan Song +5
This paper investigates the deep learning based approaches for simultaneous wireless information and power transfer (SWIPT). The quality-of-service (QoS) constrained sum-rate maxim…
Graph Neural Network Enabled Fluid Antenna Systems: A Two-Stage Approach
Changpeng He, Yang Lu, Wei Chen +3
An emerging fluid antenna system (FAS) brings a new dimension, i.e., the antenna positions, to deal with the deep fading, but simultaneously introduces challenges related to the tr…
KANsformer for Scalable Beamforming
Xinke Xie, Yang Lu, Chong-Yung Chi +3
This paper proposes an unsupervised deep-learning (DL) approach by integrating transformer and Kolmogorov-Arnold networks (KAN) termed KANsformer to realize scalable beamforming fo…
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…
GNN-Enabled Optimization of Placement and Transmission Design for UAV Communications
Qinyu Wang, Yang Lu, Wei Chen +3
This paper applies graph neural networks (GNN) in UAV communications to optimize the placement and transmission design. We consider a multiple-user multiple-input-single-output UAV…
Graph Neural Networks for Wireless Networks: Graph Representation, Architecture and Evaluation
Yang Lu, Yuhang Li, Ruichen Zhang +3
Graph neural networks (GNNs) have been regarded as the basic model to facilitate deep learning (DL) to revolutionize resource allocation in wireless networks. GNN-based models are…