Enhanced distributed cooperative spectrum sensing for cognitive radio networks

Cognitive radio will gain acceptance only when the primary detection model is accurate to insure no interference to primary system. Cooperative sensing for primary detection is degraded by the reliability of local node sensing in high fading environments. Further, managing the control channel and fu...

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Main Author:	Abdelhameed Mokhtar, Rania
Format:	Thesis
Language:	English
Published:	2011
Subjects:	Software radio Wireless communication systems Artificial intelligence
Online Access:	http://psasir.upm.edu.my/id/eprint/42291/1/FK%202011%2089.pdf
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id	my-upm-ir.42291
record_format	uketd_dc
spelling	my-upm-ir.422912024-09-18T07:07:12Z Enhanced distributed cooperative spectrum sensing for cognitive radio networks 2011-07 Abdelhameed Mokhtar, Rania Cognitive radio will gain acceptance only when the primary detection model is accurate to insure no interference to primary system. Cooperative sensing for primary detection is degraded by the reliability of local node sensing in high fading environments. Further, managing the control channel and fusion node is problematic aspect. For instance, to ensure the local sensing is reported correctly to fusion centre requires very low bit error rate (BER) channel. Another issue, that reporting channel needs large bandwidth to carry the reporting traffics. In order to improve the sensing performance and reduce the reporting error, a distributed architecture for processing and fusion of sensing information is considered. This thesis proposes an adaptive and distributed detection threshold based on maintained probability of false alarm to increase reliability of sensing under Rayleigh fading channel. The link quality status of the sensing channel of the candidate nodes is used to determine the detection threshold dynamically and the reporting link status is used for dynamic selection of fusion node for the distributed cooperative sensing. Furthermore a dynamic TDMA MAC is proposed for media access and information exchange where the noise estimation is also used for the nodes reporting scheduling; this method increases the sensing time for the later scheduled cognitive radios. The proposed distributed scheme shows a significant improvement in the overall detection readability. The probability of detection, and bit error rate (BER) were used as performance metrics in the analytical and simulation results to validate the proposed method over the direct cooperation and non-cooperative sensing. Also analytical formulation with possible candidate selection criteria is used to investigate and optimize the distributed cooperation gain. The results show that by employing such distribution and selection technique, the reporting error due to the fading channel is reduced up to 42% based on number of candidate nodes. Results also shown that the method significantly improved the sensing performance by increase the probability of detection up to 0.9 at <0.1 probability of false alarm. Sensitivity requirement is reduced dramatically by more than 95% with varying number of nodes and probability of detection. Receiver operation characteristic (ROC) curve with the parameters and performance achieved verified that the probability of detection Pd can be improved significantly while maintaining probability of false alarm <0.1. Software radio Wireless communication systems Artificial intelligence 2011-07 Thesis http://psasir.upm.edu.my/id/eprint/42291/ http://psasir.upm.edu.my/id/eprint/42291/1/FK%202011%2089.pdf text en public doctoral Universiti Putra Malaysia Software radio Wireless communication systems Artificial intelligence Mohd Ali, Borhanuddin
institution	Universiti Putra Malaysia
collection	PSAS Institutional Repository
language	English
advisor	Mohd Ali, Borhanuddin
topic	Software radio Wireless communication systems Artificial intelligence
spellingShingle	Software radio Wireless communication systems Artificial intelligence Abdelhameed Mokhtar, Rania Enhanced distributed cooperative spectrum sensing for cognitive radio networks
description	Cognitive radio will gain acceptance only when the primary detection model is accurate to insure no interference to primary system. Cooperative sensing for primary detection is degraded by the reliability of local node sensing in high fading environments. Further, managing the control channel and fusion node is problematic aspect. For instance, to ensure the local sensing is reported correctly to fusion centre requires very low bit error rate (BER) channel. Another issue, that reporting channel needs large bandwidth to carry the reporting traffics. In order to improve the sensing performance and reduce the reporting error, a distributed architecture for processing and fusion of sensing information is considered. This thesis proposes an adaptive and distributed detection threshold based on maintained probability of false alarm to increase reliability of sensing under Rayleigh fading channel. The link quality status of the sensing channel of the candidate nodes is used to determine the detection threshold dynamically and the reporting link status is used for dynamic selection of fusion node for the distributed cooperative sensing. Furthermore a dynamic TDMA MAC is proposed for media access and information exchange where the noise estimation is also used for the nodes reporting scheduling; this method increases the sensing time for the later scheduled cognitive radios. The proposed distributed scheme shows a significant improvement in the overall detection readability. The probability of detection, and bit error rate (BER) were used as performance metrics in the analytical and simulation results to validate the proposed method over the direct cooperation and non-cooperative sensing. Also analytical formulation with possible candidate selection criteria is used to investigate and optimize the distributed cooperation gain. The results show that by employing such distribution and selection technique, the reporting error due to the fading channel is reduced up to 42% based on number of candidate nodes. Results also shown that the method significantly improved the sensing performance by increase the probability of detection up to 0.9 at <0.1 probability of false alarm. Sensitivity requirement is reduced dramatically by more than 95% with varying number of nodes and probability of detection. Receiver operation characteristic (ROC) curve with the parameters and performance achieved verified that the probability of detection Pd can be improved significantly while maintaining probability of false alarm <0.1.
format	Thesis
qualification_level	Doctorate
author	Abdelhameed Mokhtar, Rania
author_facet	Abdelhameed Mokhtar, Rania
author_sort	Abdelhameed Mokhtar, Rania
title	Enhanced distributed cooperative spectrum sensing for cognitive radio networks
title_short	Enhanced distributed cooperative spectrum sensing for cognitive radio networks
title_full	Enhanced distributed cooperative spectrum sensing for cognitive radio networks
title_fullStr	Enhanced distributed cooperative spectrum sensing for cognitive radio networks
title_full_unstemmed	Enhanced distributed cooperative spectrum sensing for cognitive radio networks
title_sort	enhanced distributed cooperative spectrum sensing for cognitive radio networks
granting_institution	Universiti Putra Malaysia
publishDate	2011
url	http://psasir.upm.edu.my/id/eprint/42291/1/FK%202011%2089.pdf
_version_	1811767741892263936

Enhanced distributed cooperative spectrum sensing for cognitive radio networks

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