Papers
Communities
Events
Blog
Pricing
Search
Open menu
Home
Papers
2012.08177
Cited By
Machine Learning for MU-MIMO Receive Processing in OFDM Systems
15 December 2020
Mathieu Goutay
Fayçal Ait Aoudia
J. Hoydis
J. Gorce
Re-assign community
ArXiv
PDF
HTML
Papers citing
"Machine Learning for MU-MIMO Receive Processing in OFDM Systems"
18 / 18 papers shown
Title
DeepRx MIMO: Convolutional MIMO Detection with Learned Multiplicative Transformations
D. Korpi
Mikko Honkala
Janne M. J. Huttunen
Vesa Starck
17
31
0
30 Oct 2020
DeepWiPHY: Deep Learning-based Receiver Design and Dataset for IEEE 802.11ax Systems
Yize Zhang
Akash S. Doshi
Rob Liston
Wai-tian Tan
Xiaoqing Zhu
J. Andrews
R. Heath
29
31
0
19 Oct 2020
End-to-end Learning for OFDM: From Neural Receivers to Pilotless Communication
Fayçal Ait Aoudia
J. Hoydis
74
90
0
11 Sep 2020
RE-MIMO: Recurrent and Permutation Equivariant Neural MIMO Detection
Kumar Pratik
Bhaskar D. Rao
Max Welling
45
54
0
30 Jun 2020
Pruning the Pilots: Deep Learning-Based Pilot Design and Channel Estimation for MIMO-OFDM Systems
Mahdi Boloursaz Mashhadi
Deniz Gunduz
48
124
0
21 Jun 2020
DeepRx: Fully Convolutional Deep Learning Receiver
Mikko Honkala
D. Korpi
Janne M. J. Huttunen
73
134
0
04 May 2020
Deep HyperNetwork-Based MIMO Detection
Mathieu Goutay
Fayçal Ait Aoudia
J. Hoydis
53
54
0
07 Feb 2020
"Machine LLRning": Learning to Softly Demodulate
O. Shental
J. Hoydis
23
52
0
02 Jul 2019
Learning for Detection: MIMO-OFDM Symbol Detection through Downlink Pilots
Zhou Zhou
Lingjia Liu
Hao-Hsuan Chang
29
4
0
25 Jun 2019
Adaptive Neural Signal Detection for Massive MIMO
Mehrdad Khani
Mohammad Alizadeh
J. Hoydis
Phil Fleming
29
212
0
11 Jun 2019
Machine Learning in the Air
Deniz Gunduz
Paul de Kerret
N. Sidiropoulos
David Gesbert
C. Murthy
M. Schaar
AI4CE
30
195
0
28 Apr 2019
Learning to Detect
N. Samuel
Tzvi Diskin
A. Wiesel
48
434
0
19 May 2018
Deep Learning-Based Communication Over the Air
Sebastian Dörner
Sebastian Cammerer
J. Hoydis
S. Brink
45
707
0
11 Jul 2017
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
Andrew G. Howard
Menglong Zhu
Bo Chen
Dmitry Kalenichenko
Weijun Wang
Tobias Weyand
M. Andreetto
Hartwig Adam
3DH
1.0K
20,692
0
17 Apr 2017
An Introduction to Deep Learning for the Physical Layer
Tim O'Shea
J. Hoydis
AI4CE
125
2,184
0
02 Feb 2017
Learning to Decode Linear Codes Using Deep Learning
Eliya Nachmani
Yair Be’ery
D. Burshtein
106
459
0
16 Jul 2016
Identity Mappings in Deep Residual Networks
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
264
10,149
0
16 Mar 2016
Adam: A Method for Stochastic Optimization
Diederik P. Kingma
Jimmy Ba
ODL
624
149,474
0
22 Dec 2014
1