Co-operative Spectrum sensing using CR node binary decision regression on estimated wireless path-loss curves

N. Nagaraja; G. Kadambi; Yuri Vershinin

doi:10.1109/ECS.2014.6892567

Co-operative Spectrum sensing using CR node binary decision regression on estimated wireless path-loss curves

N. Nagaraja, G. Kadambi, Yuri Vershinin

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

1 Citation (Scopus)

Abstract

This research is about improving detection probabilities using regression of binary decisions obtained from individual Cognitive radio nodes on possible radio path-loss curve between primary user and fusion center of co-operative spectrum sensing setup. This is a breakthrough technique in aiding the system probabilities improvements using deterministic nature of long distance radio propagation loss in a distributed detection setup. This paper considers the simple Log-distance path loss model and assumes effect of Log-normal shadowing. The frame work established in this paper can be extended to other variations and combination of path loss models and can deploy advanced pattern matching techniques.

Original language	English
Title of host publication	International Conference on Electronics and Communication Systems, ICECS 2014
Publisher	IEEE
Pages	Article number 6892567
Volume	2014
ISBN (Print)	978-147992320-5
DOIs	https://doi.org/10.1109/ECS.2014.6892567
Publication status	Published - Feb 2014

Bibliographical note

This conference paper is not yet available on the repository. The paper was given at the International Conference on Electronics and Communication Systems, ICECS 2014; Coimbatore; India; 13 February 2014 through 14 February 2014

Keywords

Co-operative spectrum sensing
Cognitive radio
Log-normal shadowing

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10.1109/ECS.2014.6892567

Cite this

Co-operative Spectrum sensing using CR node binary decision regression on estimated wireless path-loss curves. / Nagaraja, N.; Kadambi, G.; Vershinin, Yuri.
International Conference on Electronics and Communication Systems, ICECS 2014. Vol. 2014 IEEE, 2014. p. Article number 6892567.

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

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abstract = "This research is about improving detection probabilities using regression of binary decisions obtained from individual Cognitive radio nodes on possible radio path-loss curve between primary user and fusion center of co-operative spectrum sensing setup. This is a breakthrough technique in aiding the system probabilities improvements using deterministic nature of long distance radio propagation loss in a distributed detection setup. This paper considers the simple Log-distance path loss model and assumes effect of Log-normal shadowing. The frame work established in this paper can be extended to other variations and combination of path loss models and can deploy advanced pattern matching techniques.",

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N2 - This research is about improving detection probabilities using regression of binary decisions obtained from individual Cognitive radio nodes on possible radio path-loss curve between primary user and fusion center of co-operative spectrum sensing setup. This is a breakthrough technique in aiding the system probabilities improvements using deterministic nature of long distance radio propagation loss in a distributed detection setup. This paper considers the simple Log-distance path loss model and assumes effect of Log-normal shadowing. The frame work established in this paper can be extended to other variations and combination of path loss models and can deploy advanced pattern matching techniques.

AB - This research is about improving detection probabilities using regression of binary decisions obtained from individual Cognitive radio nodes on possible radio path-loss curve between primary user and fusion center of co-operative spectrum sensing setup. This is a breakthrough technique in aiding the system probabilities improvements using deterministic nature of long distance radio propagation loss in a distributed detection setup. This paper considers the simple Log-distance path loss model and assumes effect of Log-normal shadowing. The frame work established in this paper can be extended to other variations and combination of path loss models and can deploy advanced pattern matching techniques.

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KW - Log-normal shadowing

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BT - International Conference on Electronics and Communication Systems, ICECS 2014

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ER -

Co-operative Spectrum sensing using CR node binary decision regression on estimated wireless path-loss curves

Abstract

Bibliographical note

Keywords

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