A novel scheme for spectrum prediction in cognitive radio networks / Mehdi Askari and Rezvan Dastanian
An efficient spectrum prediction model is presented to improve the spectrum utilization in cognitive radio network. In this model, a novel improved version of Teaching-Learning-Based-Optimization algorithm, also referred to iTLBO algorithm, is proposed to train a feed forward artificial neural netwo...
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Universiti Teknologi MARA
2021
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my.uitm.ir.520562021-10-07T08:23:33Z https://ir.uitm.edu.my/id/eprint/52056/ A novel scheme for spectrum prediction in cognitive radio networks / Mehdi Askari and Rezvan Dastanian Askari, Mehdi Dastanian, Rezvan Radio Radio frequency identification systems Probes (Electronic instruments) An efficient spectrum prediction model is presented to improve the spectrum utilization in cognitive radio network. In this model, a novel improved version of Teaching-Learning-Based-Optimization algorithm, also referred to iTLBO algorithm, is proposed to train a feed forward artificial neural network (ANN). The performance of the proposed iTLBO-ANN model is compared with some hybrid prediction models, including the genetic algorithm with ANN (GA-ANN), the firefly algorithm with ANN (FF-ANN), and the conventional TLBO algorithm with ANN (TLBO- ANN). Performance evaluation via a real-word spectrum data set (GSM-900) confirms that iTLBO-ANN outperforms other spectrum prediction schemes in terms of prediction error and prediction efficiency. Universiti Teknologi MARA 2021-10 Article PeerReviewed text en https://ir.uitm.edu.my/id/eprint/52056/1/52056.pdf ID52056 Askari, Mehdi and Dastanian, Rezvan (2021) A novel scheme for spectrum prediction in cognitive radio networks / Mehdi Askari and Rezvan Dastanian. Journal of Electrical and Electronic Systems Research (JEESR), 19: 8. pp. 17-24. ISSN 1985-5389 https://jeesr.uitm.edu.my/ |
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Tun Abdul Razak Library |
| collection |
Institutional Repository |
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Malaysia |
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Universiti Teknologi Mara |
| content_source |
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| language |
English |
| topic |
Radio Radio frequency identification systems Probes (Electronic instruments) |
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Radio Radio frequency identification systems Probes (Electronic instruments) Askari, Mehdi Dastanian, Rezvan A novel scheme for spectrum prediction in cognitive radio networks / Mehdi Askari and Rezvan Dastanian |
| description |
An efficient spectrum prediction model is presented to improve the spectrum utilization in cognitive radio network. In this model, a novel improved version of Teaching-Learning-Based-Optimization algorithm, also referred to iTLBO algorithm, is proposed to train a feed forward artificial neural network (ANN). The performance of the proposed iTLBO-ANN model is compared with some hybrid prediction models, including the genetic algorithm with ANN (GA-ANN), the firefly algorithm with ANN (FF-ANN), and the conventional TLBO algorithm with ANN (TLBO- ANN). Performance evaluation via a real-word spectrum data set (GSM-900) confirms that iTLBO-ANN outperforms other spectrum prediction schemes in terms of prediction error and prediction efficiency. |
| format |
Article |
| author |
Askari, Mehdi Dastanian, Rezvan |
| author_facet |
Askari, Mehdi Dastanian, Rezvan |
| author_sort |
Askari, Mehdi |
| title |
A novel scheme for spectrum prediction in cognitive radio networks / Mehdi Askari and Rezvan Dastanian |
| title_short |
A novel scheme for spectrum prediction in cognitive radio networks / Mehdi Askari and Rezvan Dastanian |
| title_full |
A novel scheme for spectrum prediction in cognitive radio networks / Mehdi Askari and Rezvan Dastanian |
| title_fullStr |
A novel scheme for spectrum prediction in cognitive radio networks / Mehdi Askari and Rezvan Dastanian |
| title_full_unstemmed |
A novel scheme for spectrum prediction in cognitive radio networks / Mehdi Askari and Rezvan Dastanian |
| title_sort |
novel scheme for spectrum prediction in cognitive radio networks / mehdi askari and rezvan dastanian |
| publisher |
Universiti Teknologi MARA |
| publishDate |
2021 |
| url |
https://ir.uitm.edu.my/id/eprint/52056/1/52056.pdf https://ir.uitm.edu.my/id/eprint/52056/ https://jeesr.uitm.edu.my/ |
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1713202959128461312 |
| score |
13.251813 |