https://github.com/lasseufpa/5gm-data

Datasets and code for machine learning in 5G mmWave MIMO systems involving mobility (5GMdata)
https://github.com/lasseufpa/5gm-data

Last synced: 25 days ago
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Datasets and code for machine learning in 5G mmWave MIMO systems involving mobility (5GMdata)

• Host: GitHub
• URL: https://github.com/lasseufpa/5gm-data
• Owner: lasseufpa
• License: gpl-3.0
• Created: 2018-04-06T00:43:37.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2022-05-09T20:25:38.000Z (over 2 years ago)
• Last Synced: 2024-08-04T00:04:55.543Z (4 months ago)
• Language: Python
• Homepage:
• Size: 349 KB
• Stars: 81
• Watchers: 13
• Forks: 35
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

• awesome-5g - 5GMdata - Datasets and code for machine learning in 5G mmWave MIMO systems involving mobility (5GMdata). (Research / Diameter)

README

        
# 5GMdata

Datasets and code for machine learning in 5G mmWave MIMO systems involving mobility (5GMdata)

See the Wiki page at https://github.com/lasseufpa/5gm-data/wiki

# Reference

If you use any data or code, please cite: "5G MIMO Data for Machine Learning: Application to Beam-Selection using Deep Learning", Aldebaro Klautau, Pedro Batista, Nuria Gonzalez-Prelcic, Yuyang Wang and Robert W. Heath Jr., ITA'2018 (available at http://ita.ucsd.edu/workshop/18/files/paper/paper_3313.pdf).

```

Bibtex entry:

@inproceedings{Klautau18,

  author    = {Aldebaro Klautau and Pedro Batista and Nuria Gonzalez-Prelcic and Yuyang Wang and Robert W. {Heath Jr.}},

  title     = {{5G} {MIMO} Data for Machine Learning: Application to Beam-Selection using Deep Learning},

  booktitle = {2018 Information Theory and Applications Workshop, San Diego},

  pages     = {1--1},

  year      = {2018},

  url       = {http://ita.ucsd.edu/workshop/18/files/paper/paper_3313.pdf}

}

```