Reinforcement Learning Based 5G Enabled Cognitive Radio Networks
| Autor: | Ratih Hikmah Puspita, Byeong-hee Roh, Jimyeong Oh, Sungjin Kang, Syed Danial Ali Shah, Gyu-min Lee |
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| Rok vydání: | 2019 |
| Předmět: |
Cognitive radio
Multimedia Computer science 0202 electrical engineering electronic engineering information engineering Reinforcement learning 020206 networking & telecommunications 020201 artificial intelligence & image processing 02 engineering and technology computer.software_genre Spectrum sharing computer Spectrum management 5G |
| Zdroj: | ICTC |
| Popis: | Cognitive radio (CR) is a spectrum sharing technology that facilitates a hierarchal coexistence between licensed and license-exempt users over licensed bands. One of the biggest challenges in cognitive radio network (CRN) is efficient spectrum management. Recently, a trend has shifted towards the use of machine learning techniques such as reinforcement learning for learning problem in CRN. This paper provides an insight into the working principles of reinforcement learning based CRN and summarizes the recent survey papers done on the topic of learning based CRN. This paper also presents a 5G technology i.e. network slicing, based intelligent CRN architecture for efficient spectrum management. Some challenges in the existing solutions and future research directions are also introduced. |
| Databáze: | OpenAIRE |
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