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%0 Journal Article
%1 journals/tvt/NetoAMMA21
%A Neto, Francisco Hugo Costa
%A Araújo, Daniel Costa
%A Mota, Mateus P.
%A Maciel, Tarcisio F.
%A de Almeida, André L. F.
%D 2021
%J IEEE Trans. Veh. Technol.
%K dblp
%N 6
%P 5734-5748
%T Uplink Power Control Framework Based on Reinforcement Learning for 5G Networks.
%U http://dblp.uni-trier.de/db/journals/tvt/tvt70.html#NetoAMMA21
%V 70
@article{journals/tvt/NetoAMMA21,
added-at = {2022-11-24T00:00:00.000+0100},
author = {Neto, Francisco Hugo Costa and Araújo, Daniel Costa and Mota, Mateus P. and Maciel, Tarcisio F. and de Almeida, André L. F.},
biburl = {https://www.bibsonomy.org/bibtex/2db079abceac6d661dd6513aebb67682c/dblp},
ee = {https://doi.org/10.1109/TVT.2021.3074892},
interhash = {58da20f0793f65dcf969445c459b1d28},
intrahash = {db079abceac6d661dd6513aebb67682c},
journal = {IEEE Trans. Veh. Technol.},
keywords = {dblp},
number = 6,
pages = {5734-5748},
timestamp = {2024-04-08T09:51:44.000+0200},
title = {Uplink Power Control Framework Based on Reinforcement Learning for 5G Networks.},
url = {http://dblp.uni-trier.de/db/journals/tvt/tvt70.html#NetoAMMA21},
volume = 70,
year = 2021
}