FORLORN: A Framework for Comparing Offline Methods and Reinforcement Learning for Optimization of RAN Parameters

8 September 2022

Papers citing "FORLORN: A Framework for Comparing Offline Methods and Reinforcement Learning for Optimization of RAN Parameters"

8 / 8 papers shown

Title
A Comparative study of Hyper-Parameter Optimization Tools Shashank Shekhar Adesh Bansode Asif Salim 31 48 0 17 Jan 2022
ColO-RAN: Developing Machine Learning-based xApps for Open RAN Closed-loop Control on Programmable Experimental Platforms Michele Polese Leonardo Bonati Salvatore D’oro S. Basagni Tommaso Melodia 66 151 0 17 Dec 2021
RLOps: Development Life-cycle of Reinforcement Learning Aided Open RAN Peizheng Li Jonathan D. Thomas Xiaoyang Wang Ahmed Khalil A. Ahmad ... S. Kapoor Arjun Parekh A. Doufexi Arman Shojaeifard Robert Piechocki AI4TS 49 37 0 12 Nov 2021
Intelligence and Learning in O-RAN for Data-driven NextG Cellular Networks Leonardo Bonati Salvatore D’oro Michele Polese S. Basagni Tommaso Melodia 54 252 0 02 Dec 2020
Intelligent O-RAN for Beyond 5G and 6G Wireless Networks Solmaz Niknam A. Roy Harpreet S. Dhillon Sukhdeep Singh Rahul Banerji Jeffrey H. Reed N. Saxena Seungil Yoon 34 139 0 17 May 2020
Optuna: A Next-generation Hyperparameter Optimization Framework Takuya Akiba Shotaro Sano Toshihiko Yanase Takeru Ohta Masanori Koyama 663 5,808 0 25 Jul 2019
An Introduction to Deep Learning for the Physical Layer Tim O'Shea J. Hoydis AI4CE 132 2,198 0 02 Feb 2017
Asynchronous Methods for Deep Reinforcement Learning Volodymyr Mnih Adria Puigdomenech Badia M. Berk Mirza Alex Graves Timothy Lillicrap Tim Harley David Silver Koray Kavukcuoglu 197 8,859 0 04 Feb 2016