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Title: Evaluation of Radio Channel Utility using Epsilon-Greedy Action Selection, Journal of Telecommunications and Information Technology, 2021, nr 3

Creator:

Malon, Krzysztof

Date:

2021, nr 3

Resource Type:

artykuł

Description:

This paper presents an algorithm that supports the dynamic spectrum access process in cognitive radio networks by generating a sorted list of best radio channels or by identifying those frequency ranges that are not in use temporarily. The concept is based on the reinforcement learning technique named Q-learning. To evaluate the utility of individual radio channels, spectrum monitoring is performed. In the presented solution, the epsilon-greedy action selection method is used to indicate which channel should be monitored next. The article includes a description of the proposed algorithm, scenarios, metrics, and simulation results showing the correct operation of the approach relied upon to evaluate the utility of radio channels and the epsilon-greedy action selection method. Based on the performed tests, it is possible to determine algorithm parameters that should be used in this proposed deployment. The paper also presents a comparison of the results with two other action selection methods

Publisher:

Instytut Łączności - Państwowy Instytut Badawczy

Format:

application/pdf

Resource Identifier:

ISSN 1509-4553, on-line: ISSN 1899-8852 ; oai:bc.itl.waw.pl:2191

Source:

Journal of Telecommunications and Information Technology

Language:

ang

Rights Management:

Biblioteka Naukowa Instytutu Łączności

Subject and keywords:

cognitive radio machine learning dynamic spectrum access spectrum monitoring Q-learning

Object collections:

Last modified:

Oct 11, 2021

In our library since:

Oct 11, 2021

Number of object content hits:

40

All available object's versions:

https://ribes-54.man.poznan.pl/publication/2493

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Edition name Date
Malon, Krzysztof, 2021, nr 3, Evaluation of Radio Channel Utility using Epsilon-Greedy Action Selection, Journal of Telecommunications and Information Technology, 2021, nr 3 Oct 11, 2021

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