261 citations · 577 across the 53 of their papers we have counts for
35 papers · 1 filter
Learnware for CSI Feedback: Scene-specific Small Models Can Do Big
Xiangyi Li, Jiajia Guo, Chao-Kai Wen +3
Intelligent channel state information (CSI) feedback is essential for realizing the high capacity and spectral efficiency goals of future 6G systems, yet existing deep learning sol…
GeoGS-CE: Learning Delay--Beam Channel Priors with 3D Gaussians for High-Mobility Scenarios
Yumeng Zhang, Jiajia Guo, Chaozheng Wen +2
Wideband channel estimation (CE) in high-mobility scenarios remains challenging because channel responses vary rapidly, while practical systems can allocate only sparse pilots to a…
FPNet: Joint Wi-Fi Beamforming Matrix Feedback and Anomaly-Aware Indoor Positioning
Ran Tao, Jiajia Guo, Yiming Cui +3
Channel State Information (CSI) provides a detailed description of the wireless channel and has been widely adopted for Wi-Fi sensing, particularly for high-precision indoor positi…
Large and Small Model Collaboration for Air Interface
Yiming Cui, Jiajia Guo, Xiao Li +2
Large artificial intelligence models (LAMs) have shown strong capability in wireless communications, yet existing works mainly rely on their generalized knowledge across environmen…
Joint Active and Passive Beamforming with Sensing-Assisted Discrete Phase Shifts for Dual-RIS ISAC Systems
Qing Xue, Yun Lan, Jiajia Guo +2
Targeting the requirements of 6G, this paper investigates a semi-passive dual-reconfigurable intelligent surface (RIS)-assisted integrated sensing and communication (ISAC) system,…
MUSE-FM: Multi-task Environment-aware Foundation Model for Wireless Communications
Tianyue Zheng, Jiajia Guo, Linglong Dai +2
Recent advancements in foundation models (FMs) have attracted increasing attention in the wireless communication domain. Leveraging the powerful multi-task learning capability, FMs…
Large AI Models for Wireless Physical Layer
Jiajia Guo, Yiming Cui, Shi Jin +1
Large artificial intelligence models (LAMs) are transforming wireless physical layer technologies through their robust generalization, multitask processing, and multimodal capabili…
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…
LVM4CSI: Enabling Direct Application of Pre-Trained Large Vision Models for Wireless Channel Tasks
Jiajia Guo, Peiwen Jiang, Chao-Kai Wen +2
Accurate channel state information (CSI) is critical to the performance of wireless communication systems, especially with the increasing scale and complexity introduced by 5G and…
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…
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…
Exploring the Potential of Large Language Models for Massive MIMO CSI Feedback
Yiming Cui, Jiajia Guo, Chao-Kai Wen +2
Large language models (LLMs) have achieved remarkable success across a wide range of tasks, particularly in natural language processing and computer vision. This success naturally…
Prompt-Enabled Large AI Models for CSI Feedback
Jiajia Guo, Yiming Cui, Chao-Kai Wen +1
Artificial intelligence (AI) has emerged as a promising tool for channel state information (CSI) feedback. While recent research primarily focuses on improving feedback accuracy on…
Fluid Antenna-enabled Integrated Sensing, Communication, and Computing Systems
Yiping Zuo, Jiajia Guo, Weicong Chen +4
The current integrated sensing, communication, and computing (ISCC) systems face significant challenges in both efficiency and resource utilization. To tackle these issues, we prop…
Fluid Antenna for Mobile Edge Computing
Yiping Zuo, Jiajia Guo, Biyun Sheng +3
In the evolving environment of mobile edge computing (MEC), optimizing system performance to meet the growing demand for low-latency computing services is a top priority. Integrati…
Achievable Rate Analysis and Optimization of Double-RIS Assisted Spatially Correlated MIMO with Statistical CSI
Kaizhe Xu, Jiajia Guo, Jun Zhang +2
Reconfigurable intelligent surface (RIS) is a novel meta-material which can form a smart radio environment by dynamically altering reflection directions of the impinging electromag…
Auto-CsiNet: Scenario-customized Automatic Neural Network Architecture Generation for Massive MIMO CSI Feedback
Xiangyi Li, Jiajia Guo, Chao-Kai Wen +1
Deep learning has revolutionized the design of the channel state information (CSI) feedback module in wireless communications. However, designing the optimal neural network (NN) ar…
AI/ML for Beam Management in 5G-Advanced: A Standardization Perspective
Qing Xue, Jiajia Guo, Binggui Zhou +3
In beamformed wireless cellular systems such as 5G New Radio (NR) networks, beam management (BM) is a crucial operation. In the second phase of 5G NR standardization, known as 5G-A…
A Survey of Beam Management for mmWave and THz Communications Towards 6G
Qing Xue, Chengwang Ji, Shaodan Ma +4
Communication in millimeter wave (mmWave) and even terahertz (THz) frequency bands is ushering in a new era of wireless communications. Beam management, namely initial access and b…
A Survey of Blockchain and Artificial Intelligence for 6G Wireless Communications
Yiping Zuo, Jiajia Guo, Ning Gao +3
The research on the sixth-generation (6G) wireless communications for the development of future mobile communication networks has been officially launched around the world. 6G netw…
AI for CSI Feedback Enhancement in 5G-Advanced
Jiajia Guo, Chao-Kai Wen, Shi Jin +1
The 3rd Generation Partnership Project started the study of Release 18 in 2021. Artificial intelligence (AI)-native air interface is one of the key features of Release 18, where AI…
Model-based Learning Network for 3-D Localization in mmWave Communications
Jie Yang, Shi Jin, Chao-Kai Wen +3
This study considers the joint location and velocity estimation of UE and scatterers in a three-dimensional mmWave CRAN architecture. Several existing works have achieved satisfact…
CAnet: Uplink-aided Downlink Channel Acquisition in FDD Massive MIMO using Deep Learning
Jiajia Guo, Chao-Kai Wen, Shi Jin
In frequency-division duplexing systems, the downlink channel state information (CSI) acquisition scheme leads to high training and feedback overheads. In this paper, we propose an…
Deep Learning-Based CSI Feedback for Beamforming in Single- and Multi-cell Massive MIMO Systems
Jiajia Guo, Chao-Kai Wen, Shi Jin
The potentials of massive multiple-input multiple-output (MIMO) are all based on the available instantaneous channel state information (CSI) at the base station (BS). Therefore, th…