Intelligent Channel Assignment for WI-FI System Based on Reinforcement Learning
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F14%3APU110397" target="_blank" >RIV/00216305:26220/14:PU110397 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Intelligent Channel Assignment for WI-FI System Based on Reinforcement Learning
Original language description
This paper focuses on enhanced channel planning for WI-FI systems. Based on a real measurement of the frequency spectrum background, the quality of each channel has been classified. Machine learning algorithms are used to process these data and control the system. Reinforcement learning (a special example of machine learning) is used due to its complexity as a test-trial agents system. In the proposed system punishment and reward schema are utilized making it possible to change channels during the transmission and use the one with minimal interference. The promising increase of SINR up to 5% for outdoor scenarios and up to 30% for indoor scenarios should be applied to improve modulation schemas and increase data throughput.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
20201 - Electrical and electronic engineering
Result continuities
Project
<a href="/en/project/ED2.1.00%2F03.0072" target="_blank" >ED2.1.00/03.0072: Centre of sensor, information and communication systems</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2014
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of PIERS 2014 in Guangzhou
ISBN
978-1-934142-28-8
ISSN
1559-9450
e-ISSN
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Number of pages
4
Pages from-to
2322-2325
Publisher name
Neuveden
Place of publication
Neuveden
Event location
Guangzhou
Event date
Aug 25, 2014
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000393225900515