An analysis of energy detector based on improved approximations of the chi-square distributions

Abstract Closed-form expressions for the detection probability, the false alarm probability and the energy detector constant threshold are derived using approximations of the central chi-square and non-central chi-square distributions. The approximations used show closer proximity to the original fu...

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Main Authors: Felipe G. M. Elias, Evelio M. G. Fernández
Format: Article
Language:English
Published: SpringerOpen 2021-03-01
Series:EURASIP Journal on Wireless Communications and Networking
Subjects:
Online Access:https://doi.org/10.1186/s13638-021-01915-5
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author Felipe G. M. Elias
Evelio M. G. Fernández
author_facet Felipe G. M. Elias
Evelio M. G. Fernández
author_sort Felipe G. M. Elias
collection DOAJ
description Abstract Closed-form expressions for the detection probability, the false alarm probability and the energy detector constant threshold are derived using approximations of the central chi-square and non-central chi-square distributions. The approximations used show closer proximity to the original functions when compared to the expressions used in the literature. The novel expressions allow gains up to 6% and 16% in terms of measured false alarm and miss-detection probability, respectively, if compared to the Central Limit Theorem approach. The throughput of cognitive network is also enhanced when these novel expressions are implemented, providing gains up to 9%. New equations are also presented that minimize the total error rate to obtain the detection threshold and the optimal number of samples. The analytical results match the results of the simulation for a wide range of SNR values.
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spelling doaj.art-44a12e08f079471ca33c64154d3b97ef2022-12-21T22:00:20ZengSpringerOpenEURASIP Journal on Wireless Communications and Networking1687-14992021-03-012021111810.1186/s13638-021-01915-5An analysis of energy detector based on improved approximations of the chi-square distributionsFelipe G. M. Elias0Evelio M. G. Fernández1Department of Electrical Engineering, Federal University of ParanaDepartment of Electrical Engineering, Federal University of ParanaAbstract Closed-form expressions for the detection probability, the false alarm probability and the energy detector constant threshold are derived using approximations of the central chi-square and non-central chi-square distributions. The approximations used show closer proximity to the original functions when compared to the expressions used in the literature. The novel expressions allow gains up to 6% and 16% in terms of measured false alarm and miss-detection probability, respectively, if compared to the Central Limit Theorem approach. The throughput of cognitive network is also enhanced when these novel expressions are implemented, providing gains up to 9%. New equations are also presented that minimize the total error rate to obtain the detection threshold and the optimal number of samples. The analytical results match the results of the simulation for a wide range of SNR values.https://doi.org/10.1186/s13638-021-01915-5Cognitive radioSpectrum sensingEnergy detector
spellingShingle Felipe G. M. Elias
Evelio M. G. Fernández
An analysis of energy detector based on improved approximations of the chi-square distributions
EURASIP Journal on Wireless Communications and Networking
Cognitive radio
Spectrum sensing
Energy detector
title An analysis of energy detector based on improved approximations of the chi-square distributions
title_full An analysis of energy detector based on improved approximations of the chi-square distributions
title_fullStr An analysis of energy detector based on improved approximations of the chi-square distributions
title_full_unstemmed An analysis of energy detector based on improved approximations of the chi-square distributions
title_short An analysis of energy detector based on improved approximations of the chi-square distributions
title_sort analysis of energy detector based on improved approximations of the chi square distributions
topic Cognitive radio
Spectrum sensing
Energy detector
url https://doi.org/10.1186/s13638-021-01915-5
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