5 citations · 14 across the 7 of their papers we have counts for
9 papers
Collaborative Sensing in Perceptive Mobile Networks: Opportunities and Challenges
Lei Xie, S. H. Song, Yonina C. Eldar +1
With the development of innovative applications that demand accurate environment information, e.g., autonomous driving, sensing becomes an important requirement for future wireless…
Communication-Efficient Federated Distillation with Active Data Sampling
Lumin Liu, Jun Zhang, S. H. Song +1
Federated learning (FL) is a promising paradigm to enable privacy-preserving deep learning from distributed data. Most previous works are based on federated average (FedAvg), which…
Learn to Communicate with Neural Calibration: Scalability and Generalization
Yifan Ma, Yifei Shen, Xianghao Yu +3
The conventional design of wireless communication systems typically relies on established mathematical models that capture the characteristics of different communication modules. U…
Distributed Expectation Propagation Detection for Cell-Free Massive MIMO
Hengtao He, Hanqing Wang, Xianghao Yu +3
In cell-free massive MIMO networks, an efficient distributed detection algorithm is of significant importance. In this paper, we propose a distributed expectation propagation (EP)…
Neural Calibration for Scalable Beamforming in FDD Massive MIMO with Implicit Channel Estimation
Yifan Ma, Yifei Shen, Xianghao Yu +3
Channel estimation and beamforming play critical roles in frequency-division duplexing (FDD) massive multiple-input multiple-output (MIMO) systems. However, these two modules have…
AI Empowered Resource Management for Future Wireless Networks
Yifei Shen, Jun Zhang, S. H. Song +1
Resource management plays a pivotal role in wireless networks, which, unfortunately, leads to challenging NP-hard problems. Artificial Intelligence (AI), especially deep learning t…