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20172023
most citedScalable massively parallel computing using continuous-time data representation in nanoscale crossbar array

101 citations · 127 across the 11 of their papers we have counts for

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Showing 2018 · eess.SPShow all

9 papers · 2 filters

eess.SP2018

Polar Decoding on Sparse Graphs with Deep Learning

Weihong Xu, Xiaohu You, Chuan Zhang +1

In this paper, we present a sparse neural network decoder (SNND) of polar codes based on belief propagation (BP) and deep learning. At first, the conventional factor graph of polar…

eess.SP2018

AI for 5G: Research Directions and Paradigms

Xiaohu You, Chuan Zhang, Xiaosi Tan +2

The 5th wireless communication (5G) techniques not only fulfil the requirement of times increase of internet traffic in the next decade, but also offer the underlying techn…

eess.SP2018

Joint Neural Network Equalizer and Decoder

Weihong Xu, Zhiwei Zhong, Yair Be'ery +2

Recently, deep learning methods have shown significant improvements in communication systems. In this paper, we study the equalization problem over the nonlinear channel using neur…

eess.SP2018

Efficient Channel Estimator with Angle-Division Multiple Access

Xiaozhen Liu, Jin Sha, Hongxiang Xie +5

Massive multiple-input multiple-output (M-MIMO) is an enabling technology of 5G wireless communication. The performance of an M-MIMO system is highly dependent on the speed and acc…

eess.SP2018

Efficient Soft-Output Gauss-Seidel Data Detector for Massive MIMO Systems

Chuan Zhang, Zhizhen Wu, Christoph Studer +2

For massive multiple-input multiple-output (MIMO) systems, linear minimum mean-square error (MMSE) detection has been shown to achieve near-optimal performance but suffers from exc…

eess.SP2018

Improving Massive MIMO Belief Propagation Detector with Deep Neural Network

Xiaosi Tan, Weihong Xu, Yair Be'ery +3

In this paper, deep neural network (DNN) is utilized to improve the belief propagation (BP) detection for massive multiple-input multiple-output (MIMO) systems. A neural network ar…