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A Novel Approach for Spectrum Sensing in Cognitive Radio

Published on September 2016 by Avonpreet Kaur, Shweta Rani, Sushil Kakkar
International Conference on Advances in Emerging Technology
Foundation of Computer Science USA
ICAET2016 - Number 4
September 2016
Authors: Avonpreet Kaur, Shweta Rani, Sushil Kakkar
849f3842-d868-42fd-aac4-65eea97abc65

Avonpreet Kaur, Shweta Rani, Sushil Kakkar . A Novel Approach for Spectrum Sensing in Cognitive Radio. International Conference on Advances in Emerging Technology. ICAET2016, 4 (September 2016), 12-15.

@article{
author = { Avonpreet Kaur, Shweta Rani, Sushil Kakkar },
title = { A Novel Approach for Spectrum Sensing in Cognitive Radio },
journal = { International Conference on Advances in Emerging Technology },
issue_date = { September 2016 },
volume = { ICAET2016 },
number = { 4 },
month = { September },
year = { 2016 },
issn = 0975-8887,
pages = { 12-15 },
numpages = 4,
url = { /proceedings/icaet2016/number4/25898-t054/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference on Advances in Emerging Technology
%A Avonpreet Kaur
%A Shweta Rani
%A Sushil Kakkar
%T A Novel Approach for Spectrum Sensing in Cognitive Radio
%J International Conference on Advances in Emerging Technology
%@ 0975-8887
%V ICAET2016
%N 4
%P 12-15
%D 2016
%I International Journal of Computer Applications
Abstract

Cognitive radio has become an adequate approach to solve the inefficiency of the spectrum utilization by accessing the radio spectrum strategically. In this paper, adaptive multistage wiener filter is used for the detection purpose. With the designing of such filter, detection performance is boosted because of picking up of the signal report and abolishing the additive noise. Meanwhile, in this scheme estimation of the complex matrices as well as the eigenvalue from covariance matrices is not required. Thus this system achieves a low computational complexity. Unlike conventional algorithms, neither noise power estimation nor prior knowledge of primary user signal is needed. All these qualities make the proposed algorithm robust to noise uncertainty and suitable for unseeing detections. Simulation results illustrates how reliably the unused spectrum can be detected with an acceptable trade-off. In other words, the fundamental aim is to increase detection probability and minimizing the complexity

References
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Index Terms

Computer Science
Information Sciences

Keywords

Cognitive Spectrum Frequency Bands