Journal article Open Access
vrAIn: Deep Learning based Orchestration for Computing and Radio Resources in vRANs
Jose A. Ayala-Romero;
Andres Garcia-Saavedra;
Marco Gramaglia;
Xavier Costa-Perez;
Albert Banchs;
Juan J. Alcaraz
BibTeX Export
@article{jose_a_ayala_romero_2021_5746896,
author = {Jose A. Ayala-Romero and
Andres Garcia-Saavedra and
Marco Gramaglia and
Xavier Costa-Perez and
Albert Banchs and
Juan J. Alcaraz},
title = {{vrAIn: Deep Learning based Orchestration for
Computing and Radio Resources in vRANs}},
journal = {IEEE Transactions on Mobile Computing},
year = 2021,
month = jan,
doi = {10.5281/zenodo.5746896},
url = {https://doi.org/10.5281/zenodo.5746896}
}
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| All versions | This version | |
|---|---|---|
| Views | 111 | 67 |
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| Data volume | 748.8 MB | 444.0 MB |
| Unique views | 94 | 61 |
| Unique downloads | 93 | 56 |
Indexed in
- Publication date:
- January 15, 2021
- DOI:
-
- Keyword(s):
- RAN virtualization resource management machine learning
- Published in:
- IEEE Transactions on Mobile Computing:.
- Grants:
-
European Commission:
-
DAEMON - Network intelligence for aDAptive and sElf-Learning MObile Networks (101017109)
-
5G-TOURS - SmarT mObility, media and e-health for toURists and citizenS (856950)
- 5GROWTH - 5G-enabled Growth in Vertical Industries (856709)
-
DAEMON - Network intelligence for aDAptive and sElf-Learning MObile Networks (101017109)
- Related identifiers:
- New versions
- 10.1109/TMC.2020.3043100 (Journal article)
- Communities:
- License (for files):
- Creative Commons Attribution 4.0 International