Cargando…
Reinforcement Learning for Routing in Cognitive Radio Ad Hoc Networks
Cognitive radio (CR) enables unlicensed users (or secondary users, SUs) to sense for and exploit underutilized licensed spectrum owned by the licensed users (or primary users, PUs). Reinforcement learning (RL) is an artificial intelligence approach that enables a node to observe, learn, and make app...
Autores principales: | Al-Rawi, Hasan A. A., Yau, Kok-Lim Alvin, Mohamad, Hafizal, Ramli, Nordin, Hashim, Wahidah |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2014
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4128325/ https://www.ncbi.nlm.nih.gov/pubmed/25140350 http://dx.doi.org/10.1155/2014/960584 |
Ejemplares similares
-
Application of Reinforcement Learning in Cognitive Radio Networks: Models and Algorithms
por: Yau, Kok-Lim Alvin, et al.
Publicado: (2014) -
An Energy-Efficient and Robust Multipath Routing Protocol for Cognitive Radio Ad Hoc Networks
por: Singh, Kishor, et al.
Publicado: (2017) -
An Energy-Efficient Spectrum-Aware Reinforcement Learning-Based Clustering Algorithm for Cognitive Radio Sensor Networks
por: Mustapha, Ibrahim, et al.
Publicado: (2015) -
Receiver-Based Ad Hoc On Demand Multipath Routing Protocol for Mobile Ad Hoc Networks
por: Al-Nahari, Abdulaziz, et al.
Publicado: (2016) -
In-Network Data Aggregation for Ad Hoc Clustered Cognitive Radio Wireless Sensor Network
por: Mortada, Mohamad Rida, et al.
Publicado: (2021)