7 papers
Deep Learning-based Position-domain Channel Extrapolation for Cell-Free Massive MIMO
Jiajia Guo, Chao-Kai Wen, Xiao Li +1
To reduce channel acquisition overhead, spatial, time, and frequency-domain channel extrapolation techniques have been widely studied. In this paper, we propose a novel deep learni…
Semantic-aware Digital Twin for AI-based CSI Acquisition
Jiajia Guo, Yiming Cui, Shi Jin
Artificial intelligence (AI) substantially enhances channel state information (CSI) acquisition performance but is limited by its reliance on single-modality information and deploy…
AI for CSI Prediction in 5G-Advanced and Beyond
Chengyong Jiang, Jiajia Guo, Xiangyi Li +2
Artificial intelligence (AI) is pivotal in advancing fifth-generation (5G)-Advanced and sixth-generation systems, capturing substantial research interest. Both the 3rd Generation P…
AdapCsiNet: Environment-Adaptive CSI Feedback via Scene Graph-Aided Deep Learning
Jiayi Liu, Jiajia Guo, Yiming Cui +2
Accurate channel state information (CSI) is critical for realizing the full potential of multiple-antenna wireless communication systems. While deep learning (DL)-based CSI feedbac…
Efficient Deployment of Deep MIMO Detection Using Learngene
Jinya Zhang, Jiajia Guo, Xiangyi Li +3
Deep learning (DL) has introduced a new paradigm in multiple-input multiple-output (MIMO) detection, balancing performance and complexity. However, the practical deployment of DL-b…
Deep Learning-based CSI Feedback in Wi-Fi Systems
Fan Qi, Jiajia Guo, Yiming Cui +3
In Wi-Fi systems, channel state information (CSI) plays a crucial role in enabling access points to execute beamforming operations. However, the feedback overhead associated with C…