TY - GEN
T1 - Optimization for LEO Satellite-Ground Integrated Networks via Deep Reinforcement Learning
AU - Lee, Ju Hyung
AU - Ko, Young Chai
N1 - Funding Information:
ACKNOWLEDGEMENT This work was supported by the ICT R&D program of MSIT/IITP. [2021-0-01810, Development of elemental technologies for Ultra-secure Quantum Internet]
Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - Witnessing an emerging communication platform of low-altitude earth orbit (LEO) satellites (SATs), integrating LEO SAT networks and existing terrestrial networks is getting attention. In this paper, we study the optimization of space-ground-integrated networks. Towards maximizing the communication efficiency, using a ground terminal as a relay terminal for the orbiting LEO SAT networks should be considered and optimized; however, that is tricky due to the time-varying network topology and a huge number of possible control actions. To tackle the challenge, a deep reinforcement learning method is used. Simulation results validate that SAT-ground relay (GR)-integrated scheme achieves 2.9x higher end-to-end sum throughput compared to a benchmark scheme with only-SAT scheme.
AB - Witnessing an emerging communication platform of low-altitude earth orbit (LEO) satellites (SATs), integrating LEO SAT networks and existing terrestrial networks is getting attention. In this paper, we study the optimization of space-ground-integrated networks. Towards maximizing the communication efficiency, using a ground terminal as a relay terminal for the orbiting LEO SAT networks should be considered and optimized; however, that is tricky due to the time-varying network topology and a huge number of possible control actions. To tackle the challenge, a deep reinforcement learning method is used. Simulation results validate that SAT-ground relay (GR)-integrated scheme achieves 2.9x higher end-to-end sum throughput compared to a benchmark scheme with only-SAT scheme.
UR - http://www.scopus.com/inward/record.url?scp=85122962471&partnerID=8YFLogxK
U2 - 10.1109/ICTC52510.2021.9621058
DO - 10.1109/ICTC52510.2021.9621058
M3 - Conference contribution
AN - SCOPUS:85122962471
T3 - International Conference on ICT Convergence
SP - 1758
EP - 1762
BT - ICTC 2021 - 12th International Conference on ICT Convergence
PB - IEEE Computer Society
T2 - 12th International Conference on Information and Communication Technology Convergence, ICTC 2021
Y2 - 20 October 2021 through 22 October 2021
ER -