Optimal decision threshold for eigenvalue-based spectrum sensing techniques

Yibo He; Tharmalingam Ratnarajah; Jiang Xue; Ebtihal H G Yousif; Mathini Sellathurai

doi:10.1109/ICASSP.2014.6855105

Optimal decision threshold for eigenvalue-based spectrum sensing techniques

Yibo He, Tharmalingam Ratnarajah, Jiang Xue, Ebtihal H G Yousif, Mathini Sellathurai

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

2 Citations (Scopus)

Abstract

This paper investigates optimization of the sensing threshold that minimizes the total error rate (i.e., the sum of the probabilities of false alarm and missed detection) of eigenvalue-based spectrum sensing techniques for multiple-antenna cognitive radio networks. Four techniques are investigated, which are maximum eigenvalue detection (MED), maximum minimum eigenvalue (MME) detection, energy with minimum eigenvalue (EME) detection, and the generalized likelihood ratio test (GLRT) detection. The contribution of this paper is of four parts. Firstly, we present the derivative of the matrix-variate confluent hypergeometric function, which is required for the MED case. Secondly, we derive the probabilities of false alarm for both cases MME and EME detection. Thirdly, we derive the probability of missed detection for the GLRT detector. Finally, we provide the exact expressions required to obtain the optimal sensing thresholds for all cases. The simulation results reveal that for all the investigated cases the chosen optimal sensing thresholds achieve the minimum total error rate.

Original language	English
Title of host publication	2014 IEEE International Conference on Acoustic, Speech and Signal Processing (ICASSP)
Publisher	IEEE
Pages	7734-7738
Number of pages	5
ISBN (Print)	9781479928927
DOIs	https://doi.org/10.1109/ICASSP.2014.6855105
Publication status	Published - 2014
Event	39th IEEE International Conference on Acoustics, Speech and Signal Processing 2014 - Florence, Italy, Florence, Italy Duration: 4 May 2014 → 9 May 2014 http://www.icassp2014.org/home.html

Publication series

Name	Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing
Publisher	IEEE
ISSN (Print)	1520-6149

Conference

Conference	39th IEEE International Conference on Acoustics, Speech and Signal Processing 2014
Abbreviated title	ICASSP 2014
Country/Territory	Italy
City	Florence
Period	4/05/14 → 9/05/14
Other	ICASSP is the world's largest and most comprehensive technical conference focused on signal processing and its applications. The series is sponsored by the IEEE Signal Processing Society and has been held annually since 1976. The conference features world-class speakers, tutorials, exhibits, a Show and Tell event, and over 120 lecture and poster sessions. ICASSP is a cooperative effort of the IEEE Signal Processing Society Technical Committees: Audio and Acoustic Signal Processing Bio Imaging and Signal Processing Design and Implementation of Signal Processing Systems Image, Video, and Multidimenional Signal Processing Information Forensics and Security Industry DSP Technology Standing Committee Machine Learning for Signal Processing Multimedia Signal Processing Sensor Array and Multichannel Signal Processing for Communications and Networking Signal Processing Education Standing Committee Signal Processing Theory and Methods Speech and Langauge Processing
Internet address	http://www.icassp2014.org/home.html

Keywords

Cognitive radio
eigenvalue-based spectrum sensing
matrix-variate confluent hyper-geometric function
optimal decision threshold

ASJC Scopus subject areas

Signal Processing
Software
Electrical and Electronic Engineering

Access to Document

10.1109/ICASSP.2014.6855105

Cite this

He, Y., Ratnarajah, T., Xue, J., Yousif, E. H. G., & Sellathurai, M. (2014). Optimal decision threshold for eigenvalue-based spectrum sensing techniques. In 2014 IEEE International Conference on Acoustic, Speech and Signal Processing (ICASSP) (pp. 7734-7738). Article 6855105 (Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing). IEEE. https://doi.org/10.1109/ICASSP.2014.6855105

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title = "Optimal decision threshold for eigenvalue-based spectrum sensing techniques",

abstract = "This paper investigates optimization of the sensing threshold that minimizes the total error rate (i.e., the sum of the probabilities of false alarm and missed detection) of eigenvalue-based spectrum sensing techniques for multiple-antenna cognitive radio networks. Four techniques are investigated, which are maximum eigenvalue detection (MED), maximum minimum eigenvalue (MME) detection, energy with minimum eigenvalue (EME) detection, and the generalized likelihood ratio test (GLRT) detection. The contribution of this paper is of four parts. Firstly, we present the derivative of the matrix-variate confluent hypergeometric function, which is required for the MED case. Secondly, we derive the probabilities of false alarm for both cases MME and EME detection. Thirdly, we derive the probability of missed detection for the GLRT detector. Finally, we provide the exact expressions required to obtain the optimal sensing thresholds for all cases. The simulation results reveal that for all the investigated cases the chosen optimal sensing thresholds achieve the minimum total error rate.",

keywords = "Cognitive radio, eigenvalue-based spectrum sensing, matrix-variate confluent hyper-geometric function, optimal decision threshold",

author = "Yibo He and Tharmalingam Ratnarajah and Jiang Xue and Yousif, {Ebtihal H G} and Mathini Sellathurai",

year = "2014",

doi = "10.1109/ICASSP.2014.6855105",

language = "English",

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He, Y, Ratnarajah, T, Xue, J, Yousif, EHG & Sellathurai, M 2014, Optimal decision threshold for eigenvalue-based spectrum sensing techniques. in 2014 IEEE International Conference on Acoustic, Speech and Signal Processing (ICASSP)., 6855105, Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, IEEE, pp. 7734-7738, 39th IEEE International Conference on Acoustics, Speech and Signal Processing 2014 , Florence, Italy, 4/05/14. https://doi.org/10.1109/ICASSP.2014.6855105

Optimal decision threshold for eigenvalue-based spectrum sensing techniques. / He, Yibo; Ratnarajah, Tharmalingam; Xue, Jiang et al.
2014 IEEE International Conference on Acoustic, Speech and Signal Processing (ICASSP). IEEE, 2014. p. 7734-7738 6855105 (Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Optimal decision threshold for eigenvalue-based spectrum sensing techniques

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AU - Ratnarajah, Tharmalingam

AU - Xue, Jiang

AU - Yousif, Ebtihal H G

AU - Sellathurai, Mathini

PY - 2014

Y1 - 2014

N2 - This paper investigates optimization of the sensing threshold that minimizes the total error rate (i.e., the sum of the probabilities of false alarm and missed detection) of eigenvalue-based spectrum sensing techniques for multiple-antenna cognitive radio networks. Four techniques are investigated, which are maximum eigenvalue detection (MED), maximum minimum eigenvalue (MME) detection, energy with minimum eigenvalue (EME) detection, and the generalized likelihood ratio test (GLRT) detection. The contribution of this paper is of four parts. Firstly, we present the derivative of the matrix-variate confluent hypergeometric function, which is required for the MED case. Secondly, we derive the probabilities of false alarm for both cases MME and EME detection. Thirdly, we derive the probability of missed detection for the GLRT detector. Finally, we provide the exact expressions required to obtain the optimal sensing thresholds for all cases. The simulation results reveal that for all the investigated cases the chosen optimal sensing thresholds achieve the minimum total error rate.

AB - This paper investigates optimization of the sensing threshold that minimizes the total error rate (i.e., the sum of the probabilities of false alarm and missed detection) of eigenvalue-based spectrum sensing techniques for multiple-antenna cognitive radio networks. Four techniques are investigated, which are maximum eigenvalue detection (MED), maximum minimum eigenvalue (MME) detection, energy with minimum eigenvalue (EME) detection, and the generalized likelihood ratio test (GLRT) detection. The contribution of this paper is of four parts. Firstly, we present the derivative of the matrix-variate confluent hypergeometric function, which is required for the MED case. Secondly, we derive the probabilities of false alarm for both cases MME and EME detection. Thirdly, we derive the probability of missed detection for the GLRT detector. Finally, we provide the exact expressions required to obtain the optimal sensing thresholds for all cases. The simulation results reveal that for all the investigated cases the chosen optimal sensing thresholds achieve the minimum total error rate.

KW - Cognitive radio

KW - eigenvalue-based spectrum sensing

KW - matrix-variate confluent hyper-geometric function

KW - optimal decision threshold

U2 - 10.1109/ICASSP.2014.6855105

DO - 10.1109/ICASSP.2014.6855105

M3 - Conference contribution

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SN - 9781479928927

T3 - Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing

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BT - 2014 IEEE International Conference on Acoustic, Speech and Signal Processing (ICASSP)

PB - IEEE

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Y2 - 4 May 2014 through 9 May 2014

ER -

He Y, Ratnarajah T, Xue J, Yousif EHG, Sellathurai M. Optimal decision threshold for eigenvalue-based spectrum sensing techniques. In 2014 IEEE International Conference on Acoustic, Speech and Signal Processing (ICASSP). IEEE. 2014. p. 7734-7738. 6855105. (Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing). doi: 10.1109/ICASSP.2014.6855105

Optimal decision threshold for eigenvalue-based spectrum sensing techniques

Abstract

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Conference

Keywords

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