Learning-Based Adaptive Sliding-Window RLNC for High Bandwidth-Delay Product Networks
Author:
Affiliation:
1. Department of Intelligent Mechatronics Engineering, Sejong University, Seoul, South Korea
2. Department of Information and Communication Technologies (DTIC), Universitat Pompeu Fabra (UPF), Barcelona, Spain
Funder
Institute of Information and Communications Technology Planning and Evaluation
Korean Government through the Ministry of Science and Information Communication Technology
National Research Foundation of Korea
Korean Government through MSIT
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/6287639/10005208/10190623.pdf?arnumber=10190623
Reference26 articles.
1. Reinforcement-Learning-Based Overhead Reduction for Online Fountain Codes With Limited Feedback
2. A Federated Reinforcement Learning Framework for Incumbent Technologies in Beyond 5G Networks
3. Reinforcement Learning-Aided Edge Intelligence Framework for Delay-Sensitive Industrial Applications
4. Caching Placement Optimization in UAV-Assisted Cellular Networks: A Deep Reinforcement Learning-Based Framework
5. Learning Based FEC for Non-Terrestrial Networks with Delayed Feedback
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