2 citations · 3 across the 32 of their papers we have counts for
34 papers
Multi-Modal Environment-Aware Beam Management for Massive MIMO: A Geometry-Driven Virtual Base Station Framework
Yijie Bian, Wei Guo, Jie Yang +4
High-frequency massive multiple-input multiple-output (MIMO) systems promise ultra-high data rates. However, efficient beam management remains challenging due to the prohibitive be…
Sensing-Assisted Channel Estimation for Flexible-Antenna Systems: A Unified Framework
Ruoxiao Cao, Wentao Yu, Zixin Wang +4
Flexible-antenna systems, which use a small number of radio frequency (RF) chains to dynamically access a large set of candidate antenna locations, have emerged as a hardware-effic…
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…
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,…
Unseen Cost of Space Computing: Quantifying LEO Battery Aging via Physics-Driven Modeling
Li Zeng, Jingyang Zhu, Zixin Wang +2
Low Earth Orbit (LEO) satellite constellations in the 6G era are evolving into intelligent in-orbit computational platforms, forming Space Computing Power Networks (SCPNs) to deliv…
Service Function Chain Routing in LEO Networks Using Shortest-Path Delay Statistical Stability
Li Zeng, Zixin Wang, Yuanming Shi +1
Low Earth orbit (LEO) satellite constellations have become a critical enabler for global coverage, utilizing numerous satellites orbiting Earth at high speeds. By decomposing compl…
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…
Decentralized Federated Learning With Energy Harvesting Devices
Kai Zhang, Xuanyu Cao, Khaled B. Letaief
Decentralized federated learning (DFL) enables edge devices to collaboratively train models through local training and fully decentralized device-to-device (D2D) model exchanges. H…
Modular Foundation Model Inference at the Edge: Network-Aware Microservice Optimization
Juan Zhu, Zixin Wang, Shenghui Song +2
Foundation models (FMs) unlock unprecedented multimodal and multitask intelligence, yet their cloud-centric deployment precludes real-time responsiveness and compromises user priva…
Communication-Efficient Multi-Modal Edge Inference via Uncertainty-Aware Distributed Learning
Hang Zhao, Hongru Li, Dongfang Xu +2
Semantic communication is emerging as a key enabler for distributed edge intelligence due to its capability to convey task-relevant meaning. However, achieving communication-effici…
Near-Field Communication with Massive Movable Antennas: An Electrostatic Equilibrium Perspective
Shicong Liu, Xianghao Yu, Shenghui Song +1
Recent advancements in large-scale position-reconfigurable antennas have opened up new dimensions to effectively utilize the spatial degrees of freedom (DoFs) of wireless channels.…
Multimodal Mixture-of-Experts for ISAC in Low-Altitude Wireless Networks
Kai Zhang, Wentao Yu, Hengtao He +3
Integrated sensing and communication (ISAC) is a key enabler for low-altitude wireless networks (LAWNs), providing simultaneous environmental perception and data transmission in co…
On the performance of Active STAR-RIS-Assisted Cell-Free Massive MIMO Systems with Phase Errors and Channel Aging
Jun Qian, Ross Murch, Khaled B. Letaief
Active reconfigurable intelligent surfaces (RISs) employ amplification to overcome attenuation caused by the RIS cascaded link. In this paper, we analyze the effects of phase error…
Optimal Transceiver Design in Over-the-Air Federated Distillation
Zihao Hu, Jia Yan, Ying-Jun Angela Zhang +2
The rapid proliferation and growth of artificial intelligence (AI) has led to the development of federated learning (FL). FL allows wireless devices (WDs) to cooperatively learn by…
A Tractable Approach to Massive Communication and Ubiquitous Connectivity in 6G Standardization
Junyi Jiang, Wei Chen, Xin Guo +6
The full-scale 6G standardization has attracted considerable recent attention, especially since the first 3GPP-wide 6G workshop held in March 2025. To understand the practical and…
Sensing for Free: Learn to Localize More Sources than Antennas without Pilots
Wentao Yu, Khaled B. Letaief, Lizhong Zheng
Integrated sensing and communication (ISAC) represents a key paradigm for future wireless networks. However, existing approaches require waveform modifications, dedicated pilots, o…
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…
Edge Large AI Models: Collaborative Deployment and IoT Applications
Zixin Wang, Yuanming Shi, Khaled. B. Letaief
Large artificial intelligence models (LAMs) emulate human-like problem-solving capabilities across diverse domains, modalities, and tasks. By leveraging the communication and compu…
Multimodal Deep Learning-Empowered Beam Prediction in Future THz ISAC Systems
Kai Zhang, Wentao Yu, Hengtao He +3
Integrated sensing and communication (ISAC) systems operating at terahertz (THz) bands are envisioned to enable both ultra-high data-rate communication and precise environmental aw…
Edge Large AI Models: Revolutionizing 6G Networks
Zixin Wang, Yuanming Shi, Yong Zhou +2
Large artificial intelligence models (LAMs) possess human-like abilities to solve a wide range of real-world problems, exemplifying the potential of experts in various domains and…
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…
Communication-Efficient Distributed On-Device LLM Inference Over Wireless Networks
Kai Zhang, Hengtao He, Shenghui Song +2
Large language models (LLMs) have demonstrated remarkable success across various application domains, but their enormous sizes and computational demands pose significant challenges…
Multi-Modal Self-Supervised Semantic Communication
Hang Zhao, Hongru Li, Dongfang Xu +2
Semantic communication is emerging as a promising paradigm that focuses on the extraction and transmission of semantic meanings using deep learning techniques. While current resear…