Publication detail

Intelligent Channel Assignment for WI-FI System Based on Reinforcement Learning

URBAN, R. DREXLER, P.

Original Title

Intelligent Channel Assignment for WI-FI System Based on Reinforcement Learning

Type

conference paper

Language

English

Original Abstract

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.

Keywords

machine learning, channel assignment, WI-FI

Authors

URBAN, R.; DREXLER, P.

RIV year

2014

Released

21. 3. 2014

ISBN

978-1-934142-28-8

Book

Proceedings of PIERS 2014 in Guangzhou

ISBN

1559-9450

Periodical

Progress In Electromagnetics

State

United States of America

Pages from

2322

Pages to

2325

Pages count

4

BibTex

@inproceedings{BUT109330,
  author="Robert {Urban} and Petr {Drexler}",
  title="Intelligent Channel Assignment for WI-FI System Based on Reinforcement Learning",
  booktitle="Proceedings of PIERS 2014 in Guangzhou",
  year="2014",
  journal="Progress In Electromagnetics",
  pages="2322--2325",
  isbn="978-1-934142-28-8",
  issn="1559-9450"
}