Hard decision Cooperative Spectrum Sensing based on estimating the noise uncertainty factor

Hossam M. Farag; Ehab Mahmoud Mohamed

doi:10.1109/ICCES.2015.7393049

Hard decision Cooperative Spectrum Sensing based on estimating the noise uncertainty factor

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

8 Citations (Scopus)

Abstract

Spectrum Sensing (SS) comprises the most important component in Cognitive Radio (CR) systems. Cooperative Spectrum Sensing (CSS) is proposed as an effective approach to improve detection performance in fading environments. This paper introduces an efficient energy detection based hard decision CSS algorithm to alleviate the noise uncertainty effect. In the proposed algorithm, the decision threshold is dynamically switched between two levels based on a prior prediction of the Primary User (PU) activity. The two threshold levels are evaluated using an estimated value of the noise uncertainty factor to maximize the probability of detection and minimize the probability of false alarm. The proposed algorithm is studied theoretically to deduce the enhanced detection and false alarm probabilities. Moreover, simulation analysis is used to confirm the theoretical claims and prove the high potency of the proposed scheme compared to the conventional CSS using different fusion rules.

Original language	English
Title of host publication	Proceedings - 2015 10th International Conference on Computer Engineering and Systems, ICCES 2015
Editors	Ayman M. Bahaa El-Din, M. Watheq El-Kharashi, Ahmed M. Zaki, Wahied Gharieb Ali Abdelaal, Mohamad Taher
Number of pages	6
Publisher	IEEE
Publication date	25 Jan 2016
Pages	217-222
Article number	7393049
ISBN (Electronic)	9781467399715
DOIs	https://doi.org/10.1109/ICCES.2015.7393049
Publication status	Published - 25 Jan 2016
Event	10th International Conference on Computer Engineering and Systems, ICCES 2015 - Cairo, Egypt Duration: 23 Dec 2015 → 24 Dec 2015

Conference

Conference	10th International Conference on Computer Engineering and Systems, ICCES 2015
Country/Territory	Egypt
City	Cairo
Period	23/12/2015 → 24/12/2015
Sponsor	Ain Shams University, IEEE Egypt Section

Series	Proceedings - 2015 10th International Conference on Computer Engineering and Systems, ICCES 2015

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© 2015 IEEE.

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Farag, H. M., & Mohamed, E. M. (2016). Hard decision Cooperative Spectrum Sensing based on estimating the noise uncertainty factor. In A. M. B. El-Din, M. W. El-Kharashi, A. M. Zaki, W. G. A. Abdelaal, & M. Taher (Eds.), Proceedings - 2015 10th International Conference on Computer Engineering and Systems, ICCES 2015 (pp. 217-222). Article 7393049 IEEE. https://doi.org/10.1109/ICCES.2015.7393049

Farag, Hossam M. ; Mohamed, Ehab Mahmoud. / Hard decision Cooperative Spectrum Sensing based on estimating the noise uncertainty factor. Proceedings - 2015 10th International Conference on Computer Engineering and Systems, ICCES 2015. editor / Ayman M. Bahaa El-Din ; M. Watheq El-Kharashi ; Ahmed M. Zaki ; Wahied Gharieb Ali Abdelaal ; Mohamad Taher. IEEE, 2016. pp. 217-222 (Proceedings - 2015 10th International Conference on Computer Engineering and Systems, ICCES 2015).

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abstract = "Spectrum Sensing (SS) comprises the most important component in Cognitive Radio (CR) systems. Cooperative Spectrum Sensing (CSS) is proposed as an effective approach to improve detection performance in fading environments. This paper introduces an efficient energy detection based hard decision CSS algorithm to alleviate the noise uncertainty effect. In the proposed algorithm, the decision threshold is dynamically switched between two levels based on a prior prediction of the Primary User (PU) activity. The two threshold levels are evaluated using an estimated value of the noise uncertainty factor to maximize the probability of detection and minimize the probability of false alarm. The proposed algorithm is studied theoretically to deduce the enhanced detection and false alarm probabilities. Moreover, simulation analysis is used to confirm the theoretical claims and prove the high potency of the proposed scheme compared to the conventional CSS using different fusion rules.",

author = "Farag, {Hossam M.} and Mohamed, {Ehab Mahmoud}",

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doi = "10.1109/ICCES.2015.7393049",

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Farag, HM & Mohamed, EM 2016, Hard decision Cooperative Spectrum Sensing based on estimating the noise uncertainty factor. in AMB El-Din, MW El-Kharashi, AM Zaki, WGA Abdelaal & M Taher (eds), Proceedings - 2015 10th International Conference on Computer Engineering and Systems, ICCES 2015., 7393049, IEEE, Proceedings - 2015 10th International Conference on Computer Engineering and Systems, ICCES 2015, pp. 217-222, 10th International Conference on Computer Engineering and Systems, ICCES 2015, Cairo, Egypt, 23/12/2015. https://doi.org/10.1109/ICCES.2015.7393049

Hard decision Cooperative Spectrum Sensing based on estimating the noise uncertainty factor. / Farag, Hossam M.; Mohamed, Ehab Mahmoud.
Proceedings - 2015 10th International Conference on Computer Engineering and Systems, ICCES 2015. ed. / Ayman M. Bahaa El-Din; M. Watheq El-Kharashi; Ahmed M. Zaki; Wahied Gharieb Ali Abdelaal; Mohamad Taher. IEEE, 2016. p. 217-222 7393049 (Proceedings - 2015 10th International Conference on Computer Engineering and Systems, ICCES 2015).

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

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AU - Farag, Hossam M.

AU - Mohamed, Ehab Mahmoud

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N2 - Spectrum Sensing (SS) comprises the most important component in Cognitive Radio (CR) systems. Cooperative Spectrum Sensing (CSS) is proposed as an effective approach to improve detection performance in fading environments. This paper introduces an efficient energy detection based hard decision CSS algorithm to alleviate the noise uncertainty effect. In the proposed algorithm, the decision threshold is dynamically switched between two levels based on a prior prediction of the Primary User (PU) activity. The two threshold levels are evaluated using an estimated value of the noise uncertainty factor to maximize the probability of detection and minimize the probability of false alarm. The proposed algorithm is studied theoretically to deduce the enhanced detection and false alarm probabilities. Moreover, simulation analysis is used to confirm the theoretical claims and prove the high potency of the proposed scheme compared to the conventional CSS using different fusion rules.

AB - Spectrum Sensing (SS) comprises the most important component in Cognitive Radio (CR) systems. Cooperative Spectrum Sensing (CSS) is proposed as an effective approach to improve detection performance in fading environments. This paper introduces an efficient energy detection based hard decision CSS algorithm to alleviate the noise uncertainty effect. In the proposed algorithm, the decision threshold is dynamically switched between two levels based on a prior prediction of the Primary User (PU) activity. The two threshold levels are evaluated using an estimated value of the noise uncertainty factor to maximize the probability of detection and minimize the probability of false alarm. The proposed algorithm is studied theoretically to deduce the enhanced detection and false alarm probabilities. Moreover, simulation analysis is used to confirm the theoretical claims and prove the high potency of the proposed scheme compared to the conventional CSS using different fusion rules.

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Farag HM, Mohamed EM. Hard decision Cooperative Spectrum Sensing based on estimating the noise uncertainty factor. In El-Din AMB, El-Kharashi MW, Zaki AM, Abdelaal WGA, Taher M, editors, Proceedings - 2015 10th International Conference on Computer Engineering and Systems, ICCES 2015. IEEE. 2016. p. 217-222. 7393049. (Proceedings - 2015 10th International Conference on Computer Engineering and Systems, ICCES 2015). doi: 10.1109/ICCES.2015.7393049

Hard decision Cooperative Spectrum Sensing based on estimating the noise uncertainty factor

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