%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 }