261 citations · 577 across the 53 of their papers we have counts for
22 papers · 1 filter
Foundation Models for Wireless Localization: Pretraining, Adaptation, and Utilization
Guangjin Pan, Jiajia Guo, Zheng Xing +4
Accurate wireless localization is a key enabler for 6G networks, yet remains challenging under diverse and rapidly changing propagation conditions. Model-based methods degrade when…
CORF-GS: Real-Time Wireless Radiance Field Reconstruction via Coupled Optical-RF Gaussian Splatting
Jinya Zhang, Jiajia Guo, Chao-Kai Wen +1
Recent advances in 3D Gaussian Splatting (3DGS)-based wireless radiance field (WRF) reconstruction provide an efficient solution for wireless channel modeling. However, existing WR…
Physics-Informed Path-Parametric Learning for Efficient and Lightweight CSI Feedback
Chunyu Ling, Jiajia Guo, Yiming Cui +4
Channel State Information (CSI) feedback is vital for high spectral efficiency in wireless systems, yet high-dimensional CSI introduce significant feedback overhead. Recent deep le…
Foundation Models for Wireless Communications: From PHY Intelligence to Network Autonomy
Le Liang, Jiajia Guo, Jun Zhang +6
6G networks will introduce unprecedented complexity, which calls for a paradigm shift in network optimization and management. Artificial intelligence (AI)-based solutions, especial…
AI-Empowered Low-Altitude Economy: Cooperative Sensing With Fixed Wireless Access
Jinya Zhang, Jiajia Guo, Xiangyi Li +2
The rapid growth of the low-altitude economy has intensified safety concerns arising from unauthorized unmanned aerial vehicles (UAVs), positioning UAV supervision as a key use cas…
Intention-Aware Semantic Agent Communications for AI Glasses
Peiwen Jiang, Fangyu Liu, Jiajia Guo +3
Smart glasses are emerging as a promising interface between humans and artificial intelligence (AI) agents, enabling first-person perception, contextual awareness, and real-time as…
AgentComm: Semantic Communication for Embodied Agents
Peiwen Jiang, Yushuo Feng, Jiajia Guo +2
The increasing deployment of agentic artificial intelligence (AI) systems has intensified the demand for efficient agent to agent communication, particularly over bandwidth limited…
AI-Driven Subcarrier-Level CQI Feedback
Chengyong Jiang, Jiajia Guo, Yuqing Hua +2
The Channel Quality Indicator (CQI) is a fundamental component of channel state information (CSI) that enables adaptive modulation and coding by selecting the optimal modulation an…
Limited Feedback in RIS-Assisted Wireless Communications: Use Cases, Challenges, and Future Directions
Weicong Chen, Jiajia Guo, Yiming Cui +2
Channel state information (CSI) is essential to unlock the potential of reconfigurable intelligent surfaces (RISs) in wireless communication systems. Since massive RIS elements are…
Out-of-Band Modality Synergy Based Multi-User Beam Prediction and Proactive BS Selection with Zero Pilot Overhead
Kehui Li, Binggui Zhou, Jiajia Guo +3
Multi-user millimeter-wave communication relies on narrow beams and dense cell deployments to ensure reliable connectivity. However, tracking optimal beams for multiple mobile user…
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…
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…
Efficient Deep Learning-based Cascaded Channel Feedback in RIS-Assisted Communications
Yiming Cui, Jiajia Guo, Chao-Kai Wen +1
In the realm of reconfigurable intelligent surface (RIS)-assisted communication systems, the connection between a base station (BS) and user equipment (UE) is formed by a cascaded…
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…
Knowledge-driven Meta-learning for CSI Feedback
Han Xiao, Wenqiang Tian, Wendong Liu +6
Accurate and effective channel state information (CSI) feedback is a key technology for massive multiple-input and multiple-output systems. Recently, deep learning (DL) has been in…
Demo: Reconfigurable Distributed Antennas and Reflecting Surface (RDARS)-aided Integrated Sensing and Communication System
Jintao Wang, Chengwang Ji, Jiajia Guo +1
Integrated sensing and communication (ISAC) system has been envisioned as a promising technology to be applied in future applications requiring both communication and high-accuracy…
Communication-efficient Personalized Federated Edge Learning for Massive MIMO CSI Feedback
Yiming Cui, Jiajia Guo, Chao-Kai Wen +1
Deep learning (DL)-based channel state information (CSI) feedback has received significant research attention in recent years. However, previous research has overlooked the potenti…
Lightweight Neural Network with Knowledge Distillation for CSI Feedback
Yiming Cui, Jiajia Guo, Zheng Cao +5
Deep learning has shown promise in enhancing channel state information (CSI) feedback. However, many studies indicate that better feedback performance often accompanies higher comp…
Overview of Deep Learning-based CSI Feedback in Massive MIMO Systems
Jiajia Guo, Chao-Kai Wen, Shi Jin +1
Many performance gains achieved by massive multiple-input and multiple-output depend on the accuracy of the downlink channel state information (CSI) at the transmitter (base statio…
Multi-task Learning-based CSI Feedback Design in Multiple Scenarios
Xiangyi Li, Jiajia Guo, Chao-Kai Wen +3
For frequency division duplex systems, the essential downlink channel state information (CSI) feedback includes the links of compression, feedback, decompression and reconstruction…
Deep Learning-based Implicit CSI Feedback in Massive MIMO
Muhan Chen, Jiajia Guo, Chao-Kai Wen +3
Massive multiple-input multiple-output can obtain more performance gain by exploiting the downlink channel state information (CSI) at the base station (BS). Therefore, studying CSI…
Convolutional Neural Network based Multiple-Rate Compressive Sensing for Massive MIMO CSI Feedback: Design, Simulation, and Analysis
Jiajia Guo, Chao-Kai Wen, Shi Jin +1
Massive multiple-input multiple-output (MIMO) is a promising technology to increase link capacity and energy efficiency. However, these benefits are based on available channel stat…