Measurement Based Study of Improved Spectrum Sensing Algorithm Using Sample Covariance Matrices

Ming Jin; Jiongtao Wang; Youming Li; Gang Wang; Yang Gao

7th International Conference on Communications and Networking in China

Research Article

Measurement Based Study of Improved Spectrum Sensing Algorithm Using Sample Covariance Matrices

Cite: BibTeX Plain Text

@INPROCEEDINGS{10.1109/ChinaCom.2012.6417502,
    author={Ming Jin and Jiongtao Wang and Youming Li and Gang Wang and Yang Gao},
    title={Measurement Based Study of Improved Spectrum Sensing Algorithm Using Sample Covariance Matrices},
    proceedings={7th International Conference on Communications and Networking in China},
    publisher={IEEE},
    proceedings_a={CHINACOM},
    year={2012},
    month={10},
    keywords={cognitive radio spectrum sensing measured data correlation},
    doi={10.1109/ChinaCom.2012.6417502}
}

Ming Jin
Jiongtao Wang
Youming Li
Gang Wang
Yang Gao
Year: 2012
Measurement Based Study of Improved Spectrum Sensing Algorithm Using Sample Covariance Matrices
CHINACOM
IEEE
DOI: 10.1109/ChinaCom.2012.6417502

Ming Jin¹^,*, Jiongtao Wang², Youming Li², Gang Wang², Yang Gao³

1: Ningbo University
2: Nibgbo University
3: Xidian University

*Contact email: jinming@nbu.edu.cn

Abstract

In this paper, an improved blind spectrum sensing algorithm which exploits primary signal correlation is investigated based on actual Digital Video Broadcasting (DTV) signal measurements. There is trade-off between the effectiveness and the complexity of spectrum sensing algorithms. Compared with the covariance absolute value (CAV) detection, the proposed one has better performance and almost the same computational complexity.

Keywords: cognitive radio spectrum sensing measured data correlation

Published: 2012-10-06
Publisher: IEEE

: http://dx.doi.org/10.1109/ChinaCom.2012.6417502

Measurement Based Study of Improved Spectrum Sensing Algorithm Using Sample Covariance Matrices

Abstract

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