Collaborative spectrum sensing based on upper bound on joint PDF of extreme eigenvalues

Muhammad Zeeshan Shakir, Wuchen Tang, Muhammad Ali Imran, Mohamed-Slim Alouini

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Detection based on eigenvalues of received signal covariance matrix is currently one of the most effective solution for spectrum sensing problem in cognitive radios. However, the results of these schemes often depend on asymptotic assumptions since the distribution of ratio of extreme eigenvalues is exceptionally mathematically complex to compute in practice. In this paper, a new approach to determine the distribution of ratio of the largest and the smallest eigenvalues is introduced to calculate the decision threshold and sense the spectrum. In this context, we derive a simple and analytically tractable expression for the distribution of the ratio of the largest and the smallest eigenvalues based on upper bound on the joint probability density function (PDF) of the largest and the smallest eigenvalues of the received covariance matrix. The performance analysis of proposed approach is compared with the empirical results. The decision threshold as a function of a given probability of false alarm is calculated to illustrate the effectiveness of the proposed approach.
Original languageEnglish
Title of host publication19th European Signal Processing Conference, 2011
Subtitle of host publicationEUSIPCO 2011
Place of PublicationBarcelona, Spain
PublisherIEEE
Pages1214-1218
Edition2011
Publication statusPublished - 2011
Externally publishedYes

Publication series

NameEuropean Signal Processing Conference
PublisherIEEE
ISSN (Print)2076-1465

Cite this

Shakir, M. Z., Tang, W., Imran, M. A., & Alouini, M-S. (2011). Collaborative spectrum sensing based on upper bound on joint PDF of extreme eigenvalues. In 19th European Signal Processing Conference, 2011: EUSIPCO 2011 (2011 ed., pp. 1214-1218). (European Signal Processing Conference ). Barcelona, Spain: IEEE.
Shakir, Muhammad Zeeshan ; Tang, Wuchen ; Imran, Muhammad Ali ; Alouini, Mohamed-Slim. / Collaborative spectrum sensing based on upper bound on joint PDF of extreme eigenvalues. 19th European Signal Processing Conference, 2011: EUSIPCO 2011. 2011. ed. Barcelona, Spain : IEEE, 2011. pp. 1214-1218 (European Signal Processing Conference ).
@inproceedings{9953091b9c8741bdb6c9de33e298b6e4,
title = "Collaborative spectrum sensing based on upper bound on joint PDF of extreme eigenvalues",
abstract = "Detection based on eigenvalues of received signal covariance matrix is currently one of the most effective solution for spectrum sensing problem in cognitive radios. However, the results of these schemes often depend on asymptotic assumptions since the distribution of ratio of extreme eigenvalues is exceptionally mathematically complex to compute in practice. In this paper, a new approach to determine the distribution of ratio of the largest and the smallest eigenvalues is introduced to calculate the decision threshold and sense the spectrum. In this context, we derive a simple and analytically tractable expression for the distribution of the ratio of the largest and the smallest eigenvalues based on upper bound on the joint probability density function (PDF) of the largest and the smallest eigenvalues of the received covariance matrix. The performance analysis of proposed approach is compared with the empirical results. The decision threshold as a function of a given probability of false alarm is calculated to illustrate the effectiveness of the proposed approach.",
author = "Shakir, {Muhammad Zeeshan} and Wuchen Tang and Imran, {Muhammad Ali} and Mohamed-Slim Alouini",
year = "2011",
language = "English",
series = "European Signal Processing Conference",
publisher = "IEEE",
pages = "1214--1218",
booktitle = "19th European Signal Processing Conference, 2011",
address = "United States",
edition = "2011",

}

Shakir, MZ, Tang, W, Imran, MA & Alouini, M-S 2011, Collaborative spectrum sensing based on upper bound on joint PDF of extreme eigenvalues. in 19th European Signal Processing Conference, 2011: EUSIPCO 2011. 2011 edn, European Signal Processing Conference , IEEE, Barcelona, Spain, pp. 1214-1218.

Collaborative spectrum sensing based on upper bound on joint PDF of extreme eigenvalues. / Shakir, Muhammad Zeeshan; Tang, Wuchen; Imran, Muhammad Ali; Alouini, Mohamed-Slim.

19th European Signal Processing Conference, 2011: EUSIPCO 2011. 2011. ed. Barcelona, Spain : IEEE, 2011. p. 1214-1218 (European Signal Processing Conference ).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

TY - GEN

T1 - Collaborative spectrum sensing based on upper bound on joint PDF of extreme eigenvalues

AU - Shakir, Muhammad Zeeshan

AU - Tang, Wuchen

AU - Imran, Muhammad Ali

AU - Alouini, Mohamed-Slim

PY - 2011

Y1 - 2011

N2 - Detection based on eigenvalues of received signal covariance matrix is currently one of the most effective solution for spectrum sensing problem in cognitive radios. However, the results of these schemes often depend on asymptotic assumptions since the distribution of ratio of extreme eigenvalues is exceptionally mathematically complex to compute in practice. In this paper, a new approach to determine the distribution of ratio of the largest and the smallest eigenvalues is introduced to calculate the decision threshold and sense the spectrum. In this context, we derive a simple and analytically tractable expression for the distribution of the ratio of the largest and the smallest eigenvalues based on upper bound on the joint probability density function (PDF) of the largest and the smallest eigenvalues of the received covariance matrix. The performance analysis of proposed approach is compared with the empirical results. The decision threshold as a function of a given probability of false alarm is calculated to illustrate the effectiveness of the proposed approach.

AB - Detection based on eigenvalues of received signal covariance matrix is currently one of the most effective solution for spectrum sensing problem in cognitive radios. However, the results of these schemes often depend on asymptotic assumptions since the distribution of ratio of extreme eigenvalues is exceptionally mathematically complex to compute in practice. In this paper, a new approach to determine the distribution of ratio of the largest and the smallest eigenvalues is introduced to calculate the decision threshold and sense the spectrum. In this context, we derive a simple and analytically tractable expression for the distribution of the ratio of the largest and the smallest eigenvalues based on upper bound on the joint probability density function (PDF) of the largest and the smallest eigenvalues of the received covariance matrix. The performance analysis of proposed approach is compared with the empirical results. The decision threshold as a function of a given probability of false alarm is calculated to illustrate the effectiveness of the proposed approach.

M3 - Conference contribution

T3 - European Signal Processing Conference

SP - 1214

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BT - 19th European Signal Processing Conference, 2011

PB - IEEE

CY - Barcelona, Spain

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Shakir MZ, Tang W, Imran MA, Alouini M-S. Collaborative spectrum sensing based on upper bound on joint PDF of extreme eigenvalues. In 19th European Signal Processing Conference, 2011: EUSIPCO 2011. 2011 ed. Barcelona, Spain: IEEE. 2011. p. 1214-1218. (European Signal Processing Conference ).