Distributed and collaborative primary signal feature estimation for cognitive radios under communication constraints

Zhenlei Shen; Yan Li; Shalinee Kishore; Aylin Yener

doi:10.1109/ACSSC.2007.4487601

Distributed and collaborative primary signal feature estimation for cognitive radios under communication constraints

Zhenlei Shen, Yan Li, Shalinee Kishore, Aylin Yener

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

Abstract

Collaborative algorithms are needed to improve the reliability of spectrum sensing in a network of cognitive radios (CRs). This work studies a consensus based approach to sharing spectral measurements between a multihop network of CRs. Specifically, the impact of link errors are incorporated in determining the convergence behavior of consensus based spectrum sensing. Results show that as the number of message exchanges increases, the convergence time and the deviation of the convergence value increase. Hierarchical consensus, a modification to the original consensus algorithm, is proposed to reduce the number of message exchanges while still obtaining the collaborative gains of shared spectrum sensing.

Original language	English (US)
Title of host publication	Conference Record of the 41st Asilomar Conference on Signals, Systems and Computers, ACSSC
Pages	2068-2072
Number of pages	5
DOIs	https://doi.org/10.1109/ACSSC.2007.4487601
State	Published - Dec 1 2007
Event	41st Asilomar Conference on Signals, Systems and Computers, ACSSC - Pacific Grove, CA, United States Duration: Nov 4 2007 → Nov 7 2007

Publication series

Name	Conference Record - Asilomar Conference on Signals, Systems and Computers
ISSN (Print)	1058-6393

Other

Other	41st Asilomar Conference on Signals, Systems and Computers, ACSSC
Country/Territory	United States
City	Pacific Grove, CA
Period	11/4/07 → 11/7/07

All Science Journal Classification (ASJC) codes

Signal Processing
Computer Networks and Communications

Access to Document

10.1109/ACSSC.2007.4487601

Cite this

Shen, Z., Li, Y., Kishore, S., & Yener, A. (2007). Distributed and collaborative primary signal feature estimation for cognitive radios under communication constraints. In Conference Record of the 41st Asilomar Conference on Signals, Systems and Computers, ACSSC (pp. 2068-2072). Article 4487601 (Conference Record - Asilomar Conference on Signals, Systems and Computers). https://doi.org/10.1109/ACSSC.2007.4487601

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title = "Distributed and collaborative primary signal feature estimation for cognitive radios under communication constraints",

abstract = "Collaborative algorithms are needed to improve the reliability of spectrum sensing in a network of cognitive radios (CRs). This work studies a consensus based approach to sharing spectral measurements between a multihop network of CRs. Specifically, the impact of link errors are incorporated in determining the convergence behavior of consensus based spectrum sensing. Results show that as the number of message exchanges increases, the convergence time and the deviation of the convergence value increase. Hierarchical consensus, a modification to the original consensus algorithm, is proposed to reduce the number of message exchanges while still obtaining the collaborative gains of shared spectrum sensing.",

author = "Zhenlei Shen and Yan Li and Shalinee Kishore and Aylin Yener",

year = "2007",

month = dec,

day = "1",

doi = "10.1109/ACSSC.2007.4487601",

language = "English (US)",

isbn = "9781424421107",

series = "Conference Record - Asilomar Conference on Signals, Systems and Computers",

pages = "2068--2072",

booktitle = "Conference Record of the 41st Asilomar Conference on Signals, Systems and Computers, ACSSC",

note = "41st Asilomar Conference on Signals, Systems and Computers, ACSSC ; Conference date: 04-11-2007 Through 07-11-2007",

}

Shen, Z, Li, Y, Kishore, S & Yener, A 2007, Distributed and collaborative primary signal feature estimation for cognitive radios under communication constraints. in Conference Record of the 41st Asilomar Conference on Signals, Systems and Computers, ACSSC., 4487601, Conference Record - Asilomar Conference on Signals, Systems and Computers, pp. 2068-2072, 41st Asilomar Conference on Signals, Systems and Computers, ACSSC, Pacific Grove, CA, United States, 11/4/07. https://doi.org/10.1109/ACSSC.2007.4487601

Distributed and collaborative primary signal feature estimation for cognitive radios under communication constraints. / Shen, Zhenlei; Li, Yan; Kishore, Shalinee et al.
Conference Record of the 41st Asilomar Conference on Signals, Systems and Computers, ACSSC. 2007. p. 2068-2072 4487601 (Conference Record - Asilomar Conference on Signals, Systems and Computers).

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

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AU - Shen, Zhenlei

AU - Li, Yan

AU - Kishore, Shalinee

AU - Yener, Aylin

PY - 2007/12/1

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N2 - Collaborative algorithms are needed to improve the reliability of spectrum sensing in a network of cognitive radios (CRs). This work studies a consensus based approach to sharing spectral measurements between a multihop network of CRs. Specifically, the impact of link errors are incorporated in determining the convergence behavior of consensus based spectrum sensing. Results show that as the number of message exchanges increases, the convergence time and the deviation of the convergence value increase. Hierarchical consensus, a modification to the original consensus algorithm, is proposed to reduce the number of message exchanges while still obtaining the collaborative gains of shared spectrum sensing.

AB - Collaborative algorithms are needed to improve the reliability of spectrum sensing in a network of cognitive radios (CRs). This work studies a consensus based approach to sharing spectral measurements between a multihop network of CRs. Specifically, the impact of link errors are incorporated in determining the convergence behavior of consensus based spectrum sensing. Results show that as the number of message exchanges increases, the convergence time and the deviation of the convergence value increase. Hierarchical consensus, a modification to the original consensus algorithm, is proposed to reduce the number of message exchanges while still obtaining the collaborative gains of shared spectrum sensing.

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Shen Z, Li Y, Kishore S, Yener A. Distributed and collaborative primary signal feature estimation for cognitive radios under communication constraints. In Conference Record of the 41st Asilomar Conference on Signals, Systems and Computers, ACSSC. 2007. p. 2068-2072. 4487601. (Conference Record - Asilomar Conference on Signals, Systems and Computers). doi: 10.1109/ACSSC.2007.4487601

Distributed and collaborative primary signal feature estimation for cognitive radios under communication constraints

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