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Channel access framework for cognitive radio-based wireless sensor networks using reinforcement learning

Cognitive radio-based wireless sensor network is a new paradigm in sensor networks research. It is considered to revolutionize next generation sensor networks. Therefore, it is of paramount importance to develop an efficient channel access technique suitable for cognitive radio-based wireless sensor...

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Main Authors: Abolarinwa, J. A., Latiff, N. M. A., Yusof, S. K. S.
Format: Conference or Workshop Item
Published: 2015
Subjects:
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://eprints.utm.my/id/eprint/59180/
http://dx.doi.org/10.1109/SCOReD.2013.7002615
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spelling my.utm.591802021-08-19T00:35:24Z http://eprints.utm.my/id/eprint/59180/ Channel access framework for cognitive radio-based wireless sensor networks using reinforcement learning Abolarinwa, J. A. Latiff, N. M. A. Yusof, S. K. S. TK Electrical engineering. Electronics Nuclear engineering Cognitive radio-based wireless sensor network is a new paradigm in sensor networks research. It is considered to revolutionize next generation sensor networks. Therefore, it is of paramount importance to develop an efficient channel access technique suitable for cognitive radio-based wireless sensor network. In this paper we have proposed a channel access framework for cognitive radio-based wireless sensor networks which is based on reinforcement learning technique. We have used Q-learning approach to develop a simple access algorithm. We have analyzed the effect of sensing time on the probability of detection, probability of misdetection and probability of false alarm. These parameters were compared using different detection threshold values and significant simulation results were discussed. 2015 Conference or Workshop Item PeerReviewed Abolarinwa, J. A. and Latiff, N. M. A. and Yusof, S. K. S. (2015) Channel access framework for cognitive radio-based wireless sensor networks using reinforcement learning. In: 2013 11th IEEE Student Conference on Research and Development, SCOReD 2013, 16 - 17 December 2013, Putrajaya, Malaysia. http://dx.doi.org/10.1109/SCOReD.2013.7002615
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Abolarinwa, J. A.
Latiff, N. M. A.
Yusof, S. K. S.
Channel access framework for cognitive radio-based wireless sensor networks using reinforcement learning
description Cognitive radio-based wireless sensor network is a new paradigm in sensor networks research. It is considered to revolutionize next generation sensor networks. Therefore, it is of paramount importance to develop an efficient channel access technique suitable for cognitive radio-based wireless sensor network. In this paper we have proposed a channel access framework for cognitive radio-based wireless sensor networks which is based on reinforcement learning technique. We have used Q-learning approach to develop a simple access algorithm. We have analyzed the effect of sensing time on the probability of detection, probability of misdetection and probability of false alarm. These parameters were compared using different detection threshold values and significant simulation results were discussed.
format Conference or Workshop Item
author Abolarinwa, J. A.
Latiff, N. M. A.
Yusof, S. K. S.
author_facet Abolarinwa, J. A.
Latiff, N. M. A.
Yusof, S. K. S.
author_sort Abolarinwa, J. A.
title Channel access framework for cognitive radio-based wireless sensor networks using reinforcement learning
title_short Channel access framework for cognitive radio-based wireless sensor networks using reinforcement learning
title_full Channel access framework for cognitive radio-based wireless sensor networks using reinforcement learning
title_fullStr Channel access framework for cognitive radio-based wireless sensor networks using reinforcement learning
title_full_unstemmed Channel access framework for cognitive radio-based wireless sensor networks using reinforcement learning
title_sort channel access framework for cognitive radio-based wireless sensor networks using reinforcement learning
publishDate 2015
url http://eprints.utm.my/id/eprint/59180/
http://dx.doi.org/10.1109/SCOReD.2013.7002615
_version_ 1709667350365601792
score 13.211869

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