19 citations · 36 across the 32 of their papers we have counts for
14 papers · 1 filter
Model-Driven Deep Learning for Distributed Detection with Low-Bit Quantization
Wei Guo, Meng He, Chuan Huang +4
Distributed detection plays a fundamental role in communication-efficient collaborative inference over large-scale networks, where spatially distributed nodes must cooperate using…
Task-Oriented Precoding for Edge Inference over Large-Scale MIMO Systems
Hongru Li, Zeyan Zhuang, Zixin Wang +4
Future wireless networks are expected to support networked artificial intelligence (AI) services, where multiple devices transmit learned features to an edge server for distributed…
A Unified Two-Stage Generative Diffusion Framework for Channel Estimation and Port Selection in Multiuser MIMO-FAS
Erqiang Tang, Wei Guo, Hengtao He +3
Fluid antenna systems (FAS) have emerged as a promising technology for next-generation wireless systems. However, practical multiuser multiple-input multiple-output FAS (MIMO-FAS)…
Rethinking Mutual Coupling in Movable Antenna MIMO Systems: Modeling and Optimization
Tianyi Liao, Wei Guo, Jun Qian +4
Movable antennas (MAs) have attracted growing interest for their ability to improve channel conditions via adaptive antenna movement. Nevertheless, such movement inevitably introdu…
Rotatable Antenna Assisted Mobile Edge Computing
Ji Wang, Hao Chen, Yixuan Li +4
This paper investigates a rotatable antenna (RA) assisted mobile edge computing (MEC) network, where multiple users offload their computation tasks to an edge server equipped with…
Rethinking Mutual Coupling in Movable Antenna MIMO Systems
Tianyi Liao, Wei Guo, Jun Qian +3
Movable antenna (MA) systems have emerged as a promising technology for future wireless communication systems. The movement of antennas gives rise to mutual coupling (MC) effects,…
Multi-modal Data Driven Virtual Base Station Construction for Massive MIMO Beam Alignment
Yijie Bian, Wei Guo, Jie Yang +4
Massive multiple-input multiple-output (MIMO) is a key enabler for the high data rates required by the sixth-generation networks, yet its performance hinges on effective beam manag…
Fluid Antenna-Assisted MU-MIMO Systems with Decentralized Baseband Processing
Tianyi Liao, Wei Guo, Hengtao He +3
The fluid antenna system (FAS) has emerged as a disruptive technology, offering unprecedented degrees of freedom (DoF) for wireless communication systems. However, optimizing fluid…
Accurate and Fast Channel Estimation for Fluid Antenna Systems with Diffusion Models
Erqiang Tang, Wei Guo, Hengtao He +3
Fluid antenna systems (FAS) offer enhanced spatial diversity for next-generation wireless systems. However, acquiring accurate channel state information (CSI) remains challenging d…
Mutual Information-Empowered Task-Oriented Communication: Principles, Applications and Challenges
Hongru Li, Songjie Xie, Jiawei Shao +5
Mutual information (MI)-based guidelines have recently proven to be effective for designing task-oriented communication systems, where the ultimate goal is to extract and transmit…
Joint Beamforming and Antenna Position Optimization for Fluid Antenna-Assisted MU-MIMO Networks
Tianyi Liao, Wei Guo, Hengtao He +3
The fluid antenna system (FAS) is a disruptive tech-nology for future wireless communication networks. This paper considers the joint optimization of beamforming matrices and anten…
Remote Training in Task-Oriented Communication: Supervised or Self-Supervised with Fine-Tuning?
Hongru Li, Hang Zhao, Hengtao He +3
Task-oriented communication focuses on extracting and transmitting only the information relevant to specific tasks, effectively minimizing communication overhead. Most existing met…
Model-Driven Deep Learning for Distributed Detection with Binary Quantization
Wei Guo, Meng He, Chuan Huang +4
Within the realm of rapidly advancing wireless sensor networks (WSNs), distributed detection assumes a significant role in various practical applications. However, critical challen…
Deep Learning-Based Adaptive Joint Source-Channel Coding using Hypernetworks
Songjie Xie, Hengtao He, Hongru Li +4
Deep learning-based joint source-channel coding (DJSCC) is expected to be a key technique for {the} next-generation wireless networks. However, the existing DJSCC schemes still fac…