Cargando…
Reinforcement-Learning-Based Robust Resource Management for Multi-Radio Systems
The advent of the Internet of Things (IoT) has triggered an increased demand for sensing devices with multiple integrated wireless transceivers. These platforms often support the advantageous use of multiple radio technologies to exploit their differing characteristics. Intelligent radio selection t...
Autores principales: | Delaney, James, Dowey, Steve, Cheng, Chi-Tsun |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10223095/ https://www.ncbi.nlm.nih.gov/pubmed/37430736 http://dx.doi.org/10.3390/s23104821 |
Ejemplares similares
-
Distributed Spectrum Management in Cognitive Radio Networks by Consensus-Based Reinforcement Learning†
por: Dašić, Dejan, et al.
Publicado: (2021) -
Radio resource management in multi-tier cellular wireless networks
por: Hossain, Ekram, et al.
Publicado: (2013) -
Spectrum-Efficient Resource Allocation in Multi-Radio Multi-Hop Cognitive Radio Networks
por: Han, Bin, et al.
Publicado: (2019) -
A Graph Convolutional Network-Based Deep Reinforcement Learning Approach for Resource Allocation in a Cognitive Radio Network
por: Zhao, Di, et al.
Publicado: (2020) -
Adversarial Robustness of Deep Reinforcement Learning Based Dynamic Recommender Systems
por: Wang, Siyu, et al.
Publicado: (2022)