activity
20222024
most citedUnsupervised Recurrent Federated Learning for Edge Popularity Prediction in Privacy-Preserving Mobile Edge Computing Networks

36 citations · 89 across the 7 of their papers we have counts for

collaborators

6 papers

eess.SP20231 cited

In-Situ Calibration of Antenna Arrays for Positioning With 5G Networks

Mengguan Pan, Shengheng Liu, Peng Liu +5

Owing to the ubiquity of cellular communication signals, positioning with the fifth generation (5G) signal has emerged as a promising solution in global navigation satellite system…

eess.SP202319 cited

Fast Direct Localization for Millimeter Wave MIMO Systems via Deep ADMM Unfolding

Wenzhe Fan, Shengheng Liu, Chunguo Li +1

Massive arrays deployed in millimeter-wave systems enable high angular resolution performance, which in turn facilitates sub-meter localization services. Albeit suboptimal, up to n…

cs.NI20223 cited

Toward 6G TK Extreme Connectivity: Architecture, Key Technologies and Experiments

Xiaohu You, Yongming Huang, Shengheng Liu +20

Sixth-generation (6G) networks are evolving towards new features and order-of-magnitude enhancement of systematic performance metrics compared to the current 5G. In particular, the…

cs.MM202236 cited

Unsupervised Recurrent Federated Learning for Edge Popularity Prediction in Privacy-Preserving Mobile Edge Computing Networks

Chong Zheng, Shengheng Liu, Yongming Huang +2

Nowadays wireless communication is rapidly reshaping entire industry sectors. In particular, mobile edge computing (MEC) as an enabling technology for industrial Internet of things…

cs.IT202230 cited

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…

cs.IT2022

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…