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Performance Analysis of Spectrum Sensing Schemes Based on Fractional Lower Order Moments for Cognitive Radios in Alpha- Stable Noise Environments

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Date Issued:
2016
Summary:
Natural and manmade noise signals tend to exhibit impulsive behaviors. Therefore modeling those signals as α-stable processes is better suited towards the development of a practical spectrum sensing scheme. However, the performances of detectors operating in an α-stable noise environment are difficult to evaluate. This is because an α-stable random variable can usually only be modeled by the characteristic function since closed-form expressions are usually not available except for the special values of the characteristic exponent that correspond to the Cauchy and Gaussian noise distributions. In this thesis, we derive a general closed-form expression for the probability density function (PDF) of symmetric alpha stable processes having rational characteristic exponent (0<α≤2). Consequently, we obtain analytical expressions for the PDF and corresponding complementary cumulative distribution function (CCDF) of the proposed fractional lower order moment (FLOM) detector. Utilizing false alarm and detection probabilities, the performance analysis of the proposed spectrum sensing scheme is conducted with the assumption that the cognitive radio (CR) users are operating in non-fading channels. We validate the analytical results with Monte Carlo simulations. The effect of the distribution parameters on the receiver operating characteristic (ROC) curves is verified.
Title: Performance Analysis of Spectrum Sensing Schemes Based on Fractional Lower Order Moments for Cognitive Radios in Alpha- Stable Noise Environments.
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Name(s): Ackie, A-Bon Elfick, author
Aalo, Valentine A., Thesis advisor
Florida Atlantic University, Degree grantor
College of Engineering and Computer Science
Department of Computer and Electrical Engineering and Computer Science
Type of Resource: text
Genre: Electronic Thesis Or Dissertation
Date Created: 2016
Date Issued: 2016
Publisher: Florida Atlantic University
Place of Publication: Boca Raton, Fla.
Physical Form: application/pdf
Extent: 75 p.
Language(s): English
Summary: Natural and manmade noise signals tend to exhibit impulsive behaviors. Therefore modeling those signals as α-stable processes is better suited towards the development of a practical spectrum sensing scheme. However, the performances of detectors operating in an α-stable noise environment are difficult to evaluate. This is because an α-stable random variable can usually only be modeled by the characteristic function since closed-form expressions are usually not available except for the special values of the characteristic exponent that correspond to the Cauchy and Gaussian noise distributions. In this thesis, we derive a general closed-form expression for the probability density function (PDF) of symmetric alpha stable processes having rational characteristic exponent (0<α≤2). Consequently, we obtain analytical expressions for the PDF and corresponding complementary cumulative distribution function (CCDF) of the proposed fractional lower order moment (FLOM) detector. Utilizing false alarm and detection probabilities, the performance analysis of the proposed spectrum sensing scheme is conducted with the assumption that the cognitive radio (CR) users are operating in non-fading channels. We validate the analytical results with Monte Carlo simulations. The effect of the distribution parameters on the receiver operating characteristic (ROC) curves is verified.
Identifier: FA00004561 (IID)
Degree granted: Thesis (M.S.)--Florida Atlantic University, 2016.
Collection: FAU Electronic Theses and Dissertations Collection
Note(s): Includes bibliography.
Subject(s): Cognitive radio networks.
Radio frequency allocation.
Radio resource management (Wireless communications)
Wireless communication systems.
Held by: Florida Atlantic University Libraries
Sublocation: Digital Library
Links: http://purl.flvc.org/fau/fd/FA00004561
Persistent Link to This Record: http://purl.flvc.org/fau/fd/FA00004561
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Host Institution: FAU
Is Part of Series: Florida Atlantic University Digital Library Collections.