A Reinforcement Learning Handover Parameter Adaptation Method Based on LSTM-Aided Digital Twin for UDN

Adaptation of handover parameters in ultra-dense networks has always been one of the key issues in optimizing network performance. Aiming at the optimization goal of effective handover ratio, this paper proposes a deep Q-learning (DQN) method that dynamically selects handover parameters according to...

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Detalles Bibliográficos
Autores principales: He, Jiao, Xiang, Tianqi, Wang, Yixin, Ruan, Huiyuan, Zhang, Xin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9960529/
https://www.ncbi.nlm.nih.gov/pubmed/36850792
http://dx.doi.org/10.3390/s23042191

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9960529/
https://www.ncbi.nlm.nih.gov/pubmed/36850792
http://dx.doi.org/10.3390/s23042191

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