116 citations · 515 across the 26 of their papers we have counts for
4 papers · 1 filter
Random Aggregate Beamforming for Over-the-Air Federated Learning in Large-Scale Networks
Chunmei Xu, Shengheng Liu, Yongming Huang +2
At present, there is a trend to deploy ubiquitous artificial intelligence (AI) applications at the edge of the network. As a promising framework that enables secure edge intelligen…
Learning-Aided Beam Prediction in mmWave MU-MIMO Systems for High-Speed Railway
Fan Meng, Shengheng Liu, Yongming Huang +1
The problem of beam alignment and tracking in high mobility scenarios such as high-speed railway (HSR) becomes extremely challenging, since large overhead cost and significant time…
Learnable Model-Driven Performance Prediction and Optimization for Imperfect MIMO System: Framework and Application
Fan Meng, Shengheng Liu, Yongming Huang +1
State-of-the-art schemes for performance analysis and optimization of multiple-input multiple-output systems generally experience degradation or even become invalid in dynamic comp…
Learning Rate Optimization for Federated Learning Exploiting Over-the-air Computation
Chunmei Xu, Shengheng Liu, Zhaohui Yang +2
Federated learning (FL) as a promising edge-learning framework can effectively address the latency and privacy issues by featuring distributed learning at the devices and model agg…