Abstract
An intelligent wireless channel allocation algorithm for HAPS 5G systems based on reinforcement learning was proposed. Q-learning reinforcement learning algorithm and the back-propagation neural network were combined, which made HAPS 5G systems autonomous learn according to the environment and allocate channel resources of the system efficiently.
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Acknowledgement
This paper is supported by the national natural science foundation of China (61401288), the Guangdong Province higher vocational colleges & schools Pearl River scholar funded scheme (2016), the project of Shenzhen science and technology innovation committee (JCYJ20170817114522834,JCYJ20160608151239996), the science and technology development center of Ministry of Education of China (2017A15009) and Engineering Applications of Artificial intelligence Technology Laboratory (PT201701). The author would like to thank the editor and the anonymous reviewers for their contributions that enriched the final paper.
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© 2019 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Wu, Z. et al. (2019). Research on Intelligent Wireless Channel Allocation in HAPS 5G System Based on Reinforcement Learning. In: Jia, M., Guo, Q., Meng, W. (eds) Wireless and Satellite Systems. WiSATS 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 281. Springer, Cham. https://doi.org/10.1007/978-3-030-19156-6_61
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DOI: https://doi.org/10.1007/978-3-030-19156-6_61
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