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20122022
most citedDeep-Learning-based Millimeter-Wave Massive MIMO for Hybrid Precoding

449 citations · 487 across the 18 of their papers we have counts for

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Showing cs.ITShow all

13 papers · 1 filter

cs.IT2022

Analysis of the Power Imbalance in Power-Domain NOMA on Correlated Rayleigh Fading Channels

Shaokai Hu, Hao Huang, Guan Gui +1

This paper analyzes the power imbalance issue in power-domain NOMA (PD-NOMA) in the presence of channel correlations, typically encountered on the downlink of cellular systems when…

cs.IT2019

Principal Component Analysis Based Broadband Hybrid Precoding for Millimeter-Wave Massive MIMO Systems

Yiwei Sun, Zhen Gao, Hua Wang +4

Hybrid analog-digital precoding is challenging for broadband millimeter-wave (mmWave) massive MIMO systems, since the analog precoder is frequency-flat but the mmWave channels are…

cs.IT20171 cited

On the Foundation of NOMA and its Application to 5G Cellular Networks

Hikmet Sari, Ali Maatouk, Ersoy Caliskan +3

Non-Orthogonal Multiple Access (NOMA) is recognized today as a most promising technology for future 5G cellular networks and a large number of papers have been published on the sub…

cs.IT20151 cited

Regularization Parameter Selection Method for Sign LMS with Reweighted L1-Norm Constriant Algorithm

Guan Gui, Li Xu

Broadband frequency-selective fading channels usually have the inherent sparse nature. By exploiting the sparsity, adaptive sparse channel estimation (ASCE) algorithms, e.g., least…

cs.IT2015

Maximum correntropy criterion based sparse adaptive filtering algorithms for robust channel estimation under non-Gaussian environments

Wentao Ma, Hua Qua, Guan Gui +3

Sparse adaptive channel estimation problem is one of the most important topics in broadband wireless communications systems due to its simplicity and robustness. So far many sparsi…

cs.IT2015

ROSA: Robust sparse adaptive channel estimation in the presence of impulsive noises

Guan Gui, Li Xu, Nobuhiro Shimoi

Based on the assumption of Gaussian noise model, conventional adaptive filtering algorithms for reconstruction sparse channels were proposed to take advantage of channel sparsity d…