Optimal wideband spectrum sensing based on MTM with adaptive number of sensors

Lihui Huang; Li Li; Jing Zhang; Jing Liu

doi:10.1109/PIMRC.2011.6139972

Optimal wideband spectrum sensing based on MTM with adaptive number of sensors

Lihui Huang, Li Li, Jing Zhang, Jing Liu

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

1 Citation (Scopus)

Abstract

An optimal spectrum sensing algorithm is proposed based on the Neyman-Pearson theorem in this paper. The probability of detection is mathematically formulated through analytical discussions. The computational complexity of proposed algorithm is lower than that of the conventional algorithm based on multitaper method with singular value decomposition (MTM-SVD) because SVD is omitted in the proposed algorithm. Secondly, we obtain the optimal number of required sensors which is adaptive to the signal to noise ratio (SNR) in every frequency bin. Thirdly, we find the proposed algorithm outperforms the conventional MTM-SVD algorithm in the detection rate, especially when the number of samples is small. The analytical assertions to performance of detection are verified by simulations. Results show that the proposed algorithm has an increase of approximately 8% and 10% in the detection rate when the number of tapers K=4 and K=6 under the constraints of SNR=0dB and the number of samples N=8, compared with the conventional MTM-SVD algorithm.

Original language	English
Title of host publication	2011 IEEE 22nd International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC'11
Publisher	IEEE, Institute of Electrical and Electronics Engineers
Pages	310-314
Number of pages	5
ISBN (Print)	9781457713484
DOIs	https://doi.org/10.1109/PIMRC.2011.6139972
Publication status	Published - 2011
Externally published	Yes
Event	IEEE International Symposium on Personal and Indoor Mobile Radio Conference 2011 - Toronto, Canada Duration: 11 Sep 2011 → 14 Sep 2011 Conference number: 22nd http://pimrc2011.ieee-pimrc.org/ https://ieeexplore.ieee.org/xpl/conhome/6126164/proceeding (Proceedings)

Conference

Conference	IEEE International Symposium on Personal and Indoor Mobile Radio Conference 2011
Abbreviated title	PIMRC 2011
Country/Territory	Canada
City	Toronto
Period	11/09/11 → 14/09/11
Internet address	http://pimrc2011.ieee-pimrc.org/ https://ieeexplore.ieee.org/xpl/conhome/6126164/proceeding (Proceedings)

Keywords

Cognitive radio
MTM-SVD
Multitaper
Sensor
Spectrum sensing

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10.1109/PIMRC.2011.6139972

Cite this

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title = "Optimal wideband spectrum sensing based on MTM with adaptive number of sensors",

abstract = "An optimal spectrum sensing algorithm is proposed based on the Neyman-Pearson theorem in this paper. The probability of detection is mathematically formulated through analytical discussions. The computational complexity of proposed algorithm is lower than that of the conventional algorithm based on multitaper method with singular value decomposition (MTM-SVD) because SVD is omitted in the proposed algorithm. Secondly, we obtain the optimal number of required sensors which is adaptive to the signal to noise ratio (SNR) in every frequency bin. Thirdly, we find the proposed algorithm outperforms the conventional MTM-SVD algorithm in the detection rate, especially when the number of samples is small. The analytical assertions to performance of detection are verified by simulations. Results show that the proposed algorithm has an increase of approximately 8% and 10% in the detection rate when the number of tapers K=4 and K=6 under the constraints of SNR=0dB and the number of samples N=8, compared with the conventional MTM-SVD algorithm.",

keywords = "Cognitive radio, MTM-SVD, Multitaper, Sensor, Spectrum sensing",

author = "Lihui Huang and Li Li and Jing Zhang and Jing Liu",

year = "2011",

doi = "10.1109/PIMRC.2011.6139972",

language = "English",

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booktitle = "2011 IEEE 22nd International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC'11",

publisher = "IEEE, Institute of Electrical and Electronics Engineers",

address = "United States of America",

note = "IEEE International Symposium on Personal and Indoor Mobile Radio Conference 2011, PIMRC 2011 ; Conference date: 11-09-2011 Through 14-09-2011",

url = "http://pimrc2011.ieee-pimrc.org/, https://ieeexplore.ieee.org/xpl/conhome/6126164/proceeding",

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Huang, L, Li, L, Zhang, J & Liu, J 2011, Optimal wideband spectrum sensing based on MTM with adaptive number of sensors. in 2011 IEEE 22nd International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC'11., 6139972, IEEE, Institute of Electrical and Electronics Engineers, pp. 310-314, IEEE International Symposium on Personal and Indoor Mobile Radio Conference 2011, Toronto, Ontario, Canada, 11/09/11. https://doi.org/10.1109/PIMRC.2011.6139972

Optimal wideband spectrum sensing based on MTM with adaptive number of sensors. / Huang, Lihui; Li, Li; Zhang, Jing; Liu, Jing.

2011 IEEE 22nd International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC'11. IEEE, Institute of Electrical and Electronics Engineers, 2011. p. 310-314 6139972.

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

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T1 - Optimal wideband spectrum sensing based on MTM with adaptive number of sensors

AU - Huang, Lihui

AU - Li, Li

AU - Zhang, Jing

AU - Liu, Jing

N1 - Conference code: 22nd

PY - 2011

Y1 - 2011

N2 - An optimal spectrum sensing algorithm is proposed based on the Neyman-Pearson theorem in this paper. The probability of detection is mathematically formulated through analytical discussions. The computational complexity of proposed algorithm is lower than that of the conventional algorithm based on multitaper method with singular value decomposition (MTM-SVD) because SVD is omitted in the proposed algorithm. Secondly, we obtain the optimal number of required sensors which is adaptive to the signal to noise ratio (SNR) in every frequency bin. Thirdly, we find the proposed algorithm outperforms the conventional MTM-SVD algorithm in the detection rate, especially when the number of samples is small. The analytical assertions to performance of detection are verified by simulations. Results show that the proposed algorithm has an increase of approximately 8% and 10% in the detection rate when the number of tapers K=4 and K=6 under the constraints of SNR=0dB and the number of samples N=8, compared with the conventional MTM-SVD algorithm.

AB - An optimal spectrum sensing algorithm is proposed based on the Neyman-Pearson theorem in this paper. The probability of detection is mathematically formulated through analytical discussions. The computational complexity of proposed algorithm is lower than that of the conventional algorithm based on multitaper method with singular value decomposition (MTM-SVD) because SVD is omitted in the proposed algorithm. Secondly, we obtain the optimal number of required sensors which is adaptive to the signal to noise ratio (SNR) in every frequency bin. Thirdly, we find the proposed algorithm outperforms the conventional MTM-SVD algorithm in the detection rate, especially when the number of samples is small. The analytical assertions to performance of detection are verified by simulations. Results show that the proposed algorithm has an increase of approximately 8% and 10% in the detection rate when the number of tapers K=4 and K=6 under the constraints of SNR=0dB and the number of samples N=8, compared with the conventional MTM-SVD algorithm.

KW - Cognitive radio

KW - MTM-SVD

KW - Multitaper

KW - Sensor

KW - Spectrum sensing

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BT - 2011 IEEE 22nd International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC'11

PB - IEEE, Institute of Electrical and Electronics Engineers

T2 - IEEE International Symposium on Personal and Indoor Mobile Radio Conference 2011

Y2 - 11 September 2011 through 14 September 2011

ER -

Optimal wideband spectrum sensing based on MTM with adaptive number of sensors

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Keywords

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