Multi-Agent Deep Reinforcement Learning for Interference-Aware Channel Allocation in Non-Terrestrial Networks
Author:
Affiliation:
1. Department of Electronic Engineering, Hanbat National University, Daejeon, South Korea
2. Radio and Satellite Research Division, Electronics and Telecommunications Research Institute, Daejeon, South Korea
Funder
Institute of Information & Communications Technology Planning & Evaluation
Korea Government
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Computer Science Applications,Modeling and Simulation
Link
http://xplorestaging.ieee.org/ielx7/4234/10064471/10018208.pdf?arnumber=10018208
Reference14 articles.
1. Playing atari with deep reinforcement learning;mnih;arXiv 1312 5602,2013
2. Modeling and Analysis on Radio Interference of OFDM Waveforms for Coexistence Study
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