Effect of spectrum occupancy on the performance of a real valued neural network based energy detector
In this paper, a newly proposed Real Valued Neural Network (RVNN) based Energy Detector (ED) is presented for Cognitive Radio (CR) application. With little available on the performance of EDs in varying spectrum occupancy conditions, we provide a study to understand how occupancy variation affec...
| Main Authors: | , , , , |
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| Format: | Proceeding Paper |
| Language: | English |
| Published: |
IEEE
2014
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/38900/ http://irep.iium.edu.my/38900/1/momoh2.pdf |
| _version_ | 1848781690173915136 |
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| author | Onumanyi, Adeirza J. Onwuka, Elizabeth Nonyelu Aibinu, Abiodun Musa Ugweje, Okechukwu Salami, Momoh Jimoh Eyiomika |
| author_facet | Onumanyi, Adeirza J. Onwuka, Elizabeth Nonyelu Aibinu, Abiodun Musa Ugweje, Okechukwu Salami, Momoh Jimoh Eyiomika |
| author_sort | Onumanyi, Adeirza J. |
| building | IIUM Repository |
| collection | Online Access |
| description | In this paper, a newly proposed Real Valued Neural
Network (RVNN) based Energy Detector (ED) is presented for
Cognitive Radio (CR) application. With little available on the performance of EDs in varying spectrum occupancy conditions, we provide a study to understand how occupancy variation affects the performance of a newly proposed RVNN based ED and other ED schemes. Other factors such as varying Signal to Noise Ratio (SNR) and model order values were also examined in this study and result analysis conducted using the Precision-detection statistics. Implication of results obtained indicate that
the RVNN based ED would perform optimum in high
occupancy and SNR conditions for a model order choice of
P = 20 . We also observed that the RVNN based ED would
provide better precision performance characteristics over the Periodogram, Welch and Multitaper based ED schemes
compared herein. Hence, the RVNN based ED suffices as a
favourable choice for CR application even under varying
occupancy conditions. |
| first_indexed | 2025-11-14T15:53:34Z |
| format | Proceeding Paper |
| id | iium-38900 |
| institution | International Islamic University Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T15:53:34Z |
| publishDate | 2014 |
| publisher | IEEE |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | iium-389002018-06-19T06:27:05Z http://irep.iium.edu.my/38900/ Effect of spectrum occupancy on the performance of a real valued neural network based energy detector Onumanyi, Adeirza J. Onwuka, Elizabeth Nonyelu Aibinu, Abiodun Musa Ugweje, Okechukwu Salami, Momoh Jimoh Eyiomika Q Science (General) In this paper, a newly proposed Real Valued Neural Network (RVNN) based Energy Detector (ED) is presented for Cognitive Radio (CR) application. With little available on the performance of EDs in varying spectrum occupancy conditions, we provide a study to understand how occupancy variation affects the performance of a newly proposed RVNN based ED and other ED schemes. Other factors such as varying Signal to Noise Ratio (SNR) and model order values were also examined in this study and result analysis conducted using the Precision-detection statistics. Implication of results obtained indicate that the RVNN based ED would perform optimum in high occupancy and SNR conditions for a model order choice of P = 20 . We also observed that the RVNN based ED would provide better precision performance characteristics over the Periodogram, Welch and Multitaper based ED schemes compared herein. Hence, the RVNN based ED suffices as a favourable choice for CR application even under varying occupancy conditions. IEEE 2014-07-06 Proceeding Paper PeerReviewed application/pdf en http://irep.iium.edu.my/38900/1/momoh2.pdf Onumanyi, Adeirza J. and Onwuka, Elizabeth Nonyelu and Aibinu, Abiodun Musa and Ugweje, Okechukwu and Salami, Momoh Jimoh Eyiomika (2014) Effect of spectrum occupancy on the performance of a real valued neural network based energy detector. In: 2014 International Joint Conference on Neural Networks (IJCNN), 06 Jul - 11 Jul 2014, Beijing International Convention Center. http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6889586 978-1-4799-1484-5/14/$31.00 ©2014 IEEE |
| spellingShingle | Q Science (General) Onumanyi, Adeirza J. Onwuka, Elizabeth Nonyelu Aibinu, Abiodun Musa Ugweje, Okechukwu Salami, Momoh Jimoh Eyiomika Effect of spectrum occupancy on the performance of a real valued neural network based energy detector |
| title | Effect of spectrum occupancy on the performance of a real valued neural network based energy detector |
| title_full | Effect of spectrum occupancy on the performance of a real valued neural network based energy detector |
| title_fullStr | Effect of spectrum occupancy on the performance of a real valued neural network based energy detector |
| title_full_unstemmed | Effect of spectrum occupancy on the performance of a real valued neural network based energy detector |
| title_short | Effect of spectrum occupancy on the performance of a real valued neural network based energy detector |
| title_sort | effect of spectrum occupancy on the performance of a real valued neural network based energy detector |
| topic | Q Science (General) |
| url | http://irep.iium.edu.my/38900/ http://irep.iium.edu.my/38900/ http://irep.iium.edu.my/38900/ http://irep.iium.edu.my/38900/1/momoh2.pdf |