10 papers · 1 filter
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), as an emerging flexible-antenna technology, enables movable PAs deployed along waveguides to customize channel conditions over a large scale. This paper in…
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…
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…