15 papers · 1 filter
Outage-Constrained Environment Division Multiple Access (EDMA) for Pinching-Antenna Systems
Weihao Mao, Yang Lu, Yanqing Xu +1
Environment division multiple access (EDMA) has emerged as a promising multiple access paradigm, which mitigates inter-user interference by dynamically adjusting pinching antenna (…
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…
Dual-Waveguide Pinching Antennas for PLS: Parallel Placement or Orthogonal Placement?
Yang Lu, Xinke Xie, Yanqing Xu +3
Pinching antennas (PAs) represent an emerging flexible-antenna paradigm, where movable PAs arranged along dielectric waveguides enable on-demand customization of wireless channel c…
Agentic Graph Neural Networks for Wireless Communications and Networking Towards Edge General Intelligence: A Survey
Yang Lu, Shengli Zhang, Chang Liu +6
The rapid advancement of communication technologies has driven the evolution of communication networks towards both high-dimensional resource utilization and multifunctional integr…
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…
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…
AI-Empowered RIS-Assisted Networks: CV-Enabled RIS Selection and DNN-Enabled Transmission
Conggang Hu, Yang Lu, Hongyang Du +3
This paper investigates artificial intelligence (AI) empowered schemes for reconfigurable intelligent surface (RIS) assisted networks from the perspective of fast implementation. W…
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…