9 citations · 11 across the 7 of their papers we have counts for
5 papers · 1 filter
Learning to Beamform for Cooperative Localization and Communication: A Link Heterogeneous GNN-Based Approach
Lixiang Lian, Chuanqi Bai, Yihan Xu +3
Integrated sensing and communication (ISAC) has emerged as a key enabler for next-generation wireless networks, supporting advanced applications such as high-precision localization…
Localization and Tracking for Cooperative Users in Multi-RIS-assisted Systems: Theoretical Analysis and Principles of Interpretations
Peng Gao, Lixiang Lian, Yuan Shen
Localization and tracking (LocTrack) are fundamental enablers for a wide range of emerging applications. Reconfigurable intelligent surfaces (RISs) have emerged as key components f…
Adaptive Multi-User Channel Estimation Based on Contrastive Feature Learning
Yihan Xu, Lixiang Lian
Correlation exploitation is essential for efficient multi-user channel estimation (MUCE) in massive MIMO systems. However, the existing works either rely on presumed strong correla…
Machine Learning for Large-Scale Optimization in 6G Wireless Networks
Yandong Shi, Lixiang Lian, Yuanming Shi +6
The sixth generation (6G) wireless systems are envisioned to enable the paradigm shift from "connected things" to "connected intelligence", featured by ultra high density, large-sc…
Wireless Federated Learning over MIMO Networks: Joint Device Scheduling and Beamforming Design
Shaoming Huang, Pengfei Zhang, Yijie Mao +2
Federated learning (FL) is recognized as a key enabling technology to support distributed artificial intelligence (AI) services in future 6G. By supporting decentralized data train…