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Predicting the Path Loss of Wireless Channel Models Using Machine
  Learning Techniques in MmWave Urban Communications

Predicting the Path Loss of Wireless Channel Models Using Machine Learning Techniques in MmWave Urban Communications

2 May 2020
S. Aldossari
Kwang-Cheng Chen
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Papers citing "Predicting the Path Loss of Wireless Channel Models Using Machine Learning Techniques in MmWave Urban Communications"

3 / 3 papers shown
Title
Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless
  Networks
Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks
Jingjing Wang
Chunxiao Jiang
Haijun Zhang
Yong Ren
Kwang-Cheng Chen
L. Hanzo
36
38
0
24 Jan 2019
Inferring Remote Channel State Information: Cramér-Rao Lower Bound and
  Deep Learning Implementation
Inferring Remote Channel State Information: Cramér-Rao Lower Bound and Deep Learning Implementation
Zhiyuan Jiang
Ziyan He
Sheng Chen
A. Molisch
Sheng Zhou
Z. Niu
36
15
0
04 Dec 2018
Learning Approximate Neural Estimators for Wireless Channel State
  Information
Learning Approximate Neural Estimators for Wireless Channel State Information
Tim O'Shea
Kiran Karra
T. Clancy
48
47
0
19 Jul 2017
1