313 citations · 425 across the 11 of their papers we have counts for
10 papers · 1 filter
Reconfigurable Intelligent Surface Empowered Over-the-Air Federated Edge Learning
Hang Liu, Zehong Lin, Xiaojun Yuan +1
Federated edge learning (FEEL) has emerged as a revolutionary paradigm to develop AI services at the edge of 6G wireless networks as it supports collaborative model training at a m…
Relay-Assisted Cooperative Federated Learning
Zehong Lin, Hang Liu, Ying-Jun Angela Zhang
Federated learning (FL) has recently emerged as a promising technology to enable artificial intelligence (AI) at the network edge, where distributed mobile devices collaboratively…
Semi-Blind Cascaded Channel Estimation for Reconfigurable Intelligent Surface Aided Massive MIMO
Zhen-Qing He, Hang Liu, Xiaojun Yuan +2
Reconfigurable intelligent surface (RIS) is envisioned to be a promising green technology to reduce the energy consumption and improve the coverage and spectral efficiency of massi…
CSIT-Free Model Aggregation for Federated Edge Learning via Reconfigurable Intelligent Surface
Hang Liu, Xiaojun Yuan, Ying-Jun Angela Zhang
We study over-the-air model aggregation in federated edge learning (FEEL) systems, where channel state information at the transmitters (CSIT) is assumed to be unavailable. We lever…
Reconfigurable Intelligent Surface Enabled Federated Learning: A Unified Communication-Learning Design Approach
Hang Liu, Xiaojun Yuan, Ying-Jun Angela Zhang
To exploit massive amounts of data generated at mobile edge networks, federated learning (FL) has been proposed as an attractive substitute for centralized machine learning (ML). B…
Statistical Beamforming for FDD Downlink Massive MIMO via Spatial Information Extraction and Beam Selection
Hang Liu, Xiaojun Yuan, Ying Jun +1
In this paper, we study the beamforming design problem in frequency-division duplexing (FDD) downlink massive MIMO systems, where instantaneous channel state information (CSI) is a…
Reconfigurable-Intelligent-Surface Empowered Wireless Communications: Challenges and Opportunities
Xiaojun Yuan, Ying-Jun Angela Zhang, Yuanming Shi +2
Reconfigurable intelligent surfaces (RISs) are regarded as a promising emerging hardware technology to improve the spectrum and energy efficiency of wireless networks by artificial…
Matrix-Calibration-Based Cascaded Channel Estimation for Reconfigurable Intelligent Surface Assisted Multiuser MIMO
Hang Liu, Xiaojun Yuan, Ying-Jun Angela Zhang
Reconfigurable intelligent surface (RIS) is envisioned to be an essential component of the paradigm for beyond 5G networks as it can potentially provide similar or higher array gai…
Double-Sparsity Learning Based Channel-and-Signal Estimation in Massive MIMO with Generalized Spatial Modulation
Xiaoyan Kuai, Xiaojun Yuan, Wenjing Yan +3
In this paper, we study joint antenna activity detection, channel estimation, and multiuser detection for massive multiple-input multiple-output (MIMO) systems with general spatial…
Super-Resolution Blind Channel-and-Signal Estimation for Massive MIMO with One-Dimensional Antenna Array
Hang Liu, Xiaojun Yuan, Ying-Jun Angela Zhang
In this paper, we study blind channel-and-signal estimation by exploiting the burst-sparse structure of angular-domain propagation channels in massive MIMO systems. The state-of-th…