Deep Reinforcement Learning Based Dynamic Channel Allocation Algorithm in Multibeam Satellite Systems

Deep Reinforcement Learning Based Dynamic Channel Allocation Algorithm in Multibeam Satellite Systems

Dynamic channel allocation (DCA) is the key technology to efficiently utilize the spectrum resources and decrease the co-channel interference for multibeam satellite systems. Most works allocate the channel on the basis of the beam traffic load or the user terminal distribution of the current moment...

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Bibliographic Details
Main Authors: Shuaijun Liu, Xin Hu, Weidong Wang
Format: Article
Language:English
Published: IEEE 2018-01-01
Series:IEEE Access
Subjects:
Dynamic channel allocation (DCA)
multibeam satellite systems
Markov decision process (MDP)
deep reinforcement learning (DRL)
blocking probability
Online Access:https://ieeexplore.ieee.org/document/8302493/

Internet

https://ieeexplore.ieee.org/document/8302493/

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