Computer vision aided OFDM-based standards detection and classification technique for cognitive radio systems

Author

Guibene, Wael ; Khirallah, Chadi ; Slock, D. ; Thompson, John

Author_Institution

Mobile Commun. Dept., EURECOM, Sophia Antipolis, France

fYear

2013

Firstpage

4479

Lastpage

4483

Abstract

This paper presents an innovative spectrum sensing scheme for Orthogonal Frequency Division Multiplexing (OFDM) signals based on enhancing the performance of the popular autocorrelation detectors (AD) using non-linear image processing methods. These methods improve the detection accuracy of the AD under particular false-alarm constraints. The proposed scheme is used in the detection of two OFDM systems, Long Term Evolution (LTE) and DVB terrestrial digital TV (DVB-T) under low signal to noise ratio (SNR) channel conditions. Results obtained show significant improvement in correct signals detection/classification up to 18% and 48% at a false-alarm of 5% and low SNR conditions equal to -18dB, using the combined AD and image processing scheme for the detection of LTE and DVB-T signals, respectively.

Keywords

Long Term Evolution; OFDM modulation; cognitive radio; computer vision; correlation methods; digital video broadcasting; image classification; radio spectrum management; signal detection; DVB terrestrial digital TV; DVB-T; LTE; Long Term Evolution; OFDM signal; OFDM-based standards classification technique; OFDM-based standards detection technique; autocorrelation detector; cognitive radio system; computer vision; false alarm constraints; innovative spectrum sensing scheme; low SNR channel condition; low signal to noise ratio channel condition; nonlinear image processing method; orthogonal frequency division multiplexing signal; signal classification; signal detection; Correlation; Detectors; Digital video broadcasting; OFDM; Signal to noise ratio; Standards; DVB-T; LTE; OFDM; Spectrum Sensing;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on

Conference_Location

Vancouver, BC

ISSN

1520-6149

Type

conf

DOI

10.1109/ICASSP.2013.6638507

Filename

6638507