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A novel low complexity differential energy detection for sensing OFDM sources in low SNR environment

Cheraghi, P, Ma, Y, Lu, Z and Tafazolli, R (2012) A novel low complexity differential energy detection for sensing OFDM sources in low SNR environment In: 2011 IEEE GLOBECOM Workshops (GC Wkshps), 2011-12-05 - 2011-12-09, Houston TX.

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This paper presents a novel frequency-domain energy detection scheme based on extreme statistics for robust sensing of OFDM sources in the low SNR region. The basic idea is to exploit the frequency diversity gain inherited by frequency selective channels with the aid of extreme statistics of the differential energy spectral density (ESD). Thanks to the differential stage the proposed spectrum sensing is robust to noise uncertainty problem. The low computational complexity requirement of the proposed technique makes it suitable for even machine-to-machine sensing. Analytical performance analysis is performed in terms of two classical metrics, i.e. probability of detection and probability of false alarm. The computer simulations carried out further show that the proposed scheme outperforms energy detection and second order cyclostationarity based approach for up to 10 dB gain in the low SNR range. © 2011 IEEE.

Item Type: Conference or Workshop Item (Conference Paper)
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering > Centre for Communication Systems Research
Authors :
Cheraghi, P
Ma, Y
Lu, Z
Tafazolli, R
Date : 1 March 2012
DOI : 10.1109/GLOCOMW.2011.6162475
Contributors :
Additional Information : © 2011 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Depositing User : Symplectic Elements
Date Deposited : 19 Dec 2012 14:20
Last Modified : 31 Oct 2017 14:51

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