collaborators

6 papers

eess.SP2026

Sense Smarter, Think Better: A Survey on Edge Perception for Next-Generation Networks

Zhonghao Lyu, Xiaowen Cao, Xianxin Song +11

Edge perception has emerged as a foundational capability for future wireless networks, enabling the network edge to proactively sense, interpret, and interact with the physical env…

cs.LG2025

Closing the Generalization Gap in Parameter-efficient Federated Edge Learning

Xinnong Du, Zhonghao Lyu, Xiaowen Cao +3

Federated edge learning (FEEL) provides a promising foundation for edge artificial intelligence (AI) by enabling collaborative model training while preserving data privacy. However…

eess.SP2025

Integrated Sensing and Communication: Towards Multifunctional Perceptive Network

Yuanhao Cui, Jiali Nie, Fan Liu +7

The capacity-maximization design philosophy has driven the growth of wireless networks for decades. However, with the slowdown in recent data traffic demand, the mobile industry ca…

cs.IT2025

Integrated Sensing, Communication, and Computation for Over-the-Air Federated Edge Learning

Dingzhu Wen, Sijing Xie, Xiaowen Cao +4

This paper studies an over-the-air federated edge learning (Air-FEEL) system with integrated sensing, communication, and computation (ISCC), in which one edge server coordinates mu…

cs.IT2025

Sensing-Enhanced Channel Estimation for Near-Field XL-MIMO Systems

Shicong Liu, Xianghao Yu, Zhen Gao +3

Future sixth-generation (6G) systems are expected to leverage extremely large-scale multiple-input multiple-output (XL-MIMO) technology, which significantly expands the range of th…

cs.IT2025

Wireless Control over Edge Networks: Joint User Association and Communication-Computation Co-Design

Zhilin Liu, Yiyang Li, Huijun Xing +3

This paper studies a wireless networked control system with multiple base stations (BSs) cooperatively coordinating the wireless control of a number of subsystems each consisting o…