13 citations · 23 across the 12 of their papers we have counts for
12 papers
Joint Channel Estimation and Data Recovery for Millimeter Massive MIMO: Using Pilot to Capture Principal Components
Shusen Cai, Li Chen, Yunfei Chen +2
Channel state information (CSI) is important to reap the full benefits of millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) systems. The traditional channel es…
Communication-Efficient Design for Quantized Decentralized Federated Learning
Li Chen, Wei Liu, Yunfei Chen +1
Decentralized federated learning (DFL) is a variant of federated learning, where edge nodes only communicate with their one-hop neighbors to learn the optimal model. However, as in…
Hierarchical-Absolute Reciprocity Calibration for Millimeter-wave Hybrid Beamforming Systems
Li Chen, Rongjiang Nie, Yunfei Chen +1
In time-division duplexing (TDD) millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) systems, the reciprocity mismatch severely degrades the performance of the h…
Blind Diagnosis for Millimeter-wave Large-scale Antenna Systems
Rui Sun, Weidong Wang, Li Chen +2
Millimeter-wave (mmWave) communication systems rely on large-scale antenna arrays to combat large path-loss at mmWave band. Due to hardware characteristics and deployment environme…
Diagnosis of Intelligent Reflecting Surface in Millimeter-wave Communication Systems
Rui Sun, Weidong Wang, Li Chen +2
Intelligent reflecting surface (IRS) is a promising technology for enhancing wireless communication systems. It adaptively configures massive passive reflecting elements to control…
Impact and Calibration of Nonlinear Reciprocity Mismatch in Massive MIMO
Rongjiang Nie, Li Chen, Nan Zhao +3
Time-division-duplexing massive multiple-input multiple-output (MIMO) systems estimate the channel state information (CSI) by leveraging the uplink-downlink channel reciprocity, wh…
Robust Federated Learning with Noisy Communication
Fan Ang, Li Chen, Nan Zhao +3
Federated learning is a communication-efficient training process that alternates between local training at the edge devices and averaging the updated local model at the central ser…
An End-to-End Block Autoencoder For Physical Layer Based On Neural Networks
Tianjie Mu, Xiaohui Chen, Li Chen +2
Deep Learning has been widely applied in the area of image processing and natural language processing. In this paper, we propose an end-to-end communication structure based on auto…
TCP Decoupling for Next Generation Communication System
Xiaohui Chen, Xiaowei Qin, Li Chen +7
In traditional networks, interfaces of network nodes are duplex. But, emerging communication technologies such as visible light communication, millimeter-wave communications, can o…
Hybrid Beamforming Design and Performance with Imperfect Phase Shifters in Multiuser Millimeter Wave Systems
Wendi Wang, Huarui Yin, Xiaohui Chen +1
Hybrid beamforming (HBF) includes analog beamforming with phase shifted array in RF domain and digital beamforming in baseband domain. Phase shifted array is usually made up with a…
Stopping Condition for Greedy Block Sparse Signal Recovery
Yu Luo, Ronggui Xie, Huarui Yin +1
For greedy block sparse recovery where the sparsity level is unknown, we derive a stopping condition to stop the iteration process. Focused on the block orthogonal matching pursuit…
Low complexity resource allocation for load minimization in OFDMA wireless networks
Ying Yang, Marco Moretti, Wenxiang Dong +1
To cope with the ever increasing demand for bandwidth, future wireless networks will be designed with reuse distance equal to one. This scenario requires the implementation of tech…