activity
20182021
most citedAn End-to-End Block Autoencoder For Physical Layer Based On Neural Networks

13 citations · 14 across the 4 of their papers we have counts for

collaborators

7 papers

eess.SY2021

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…

eess.SY2021

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…

cs.IT2020

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…

cs.LG20191 cited

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…

cs.IT201913 cited

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…

cs.NI2018

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…