6 papers · 1 filter
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…