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Blind Free Band Detector Based on the Sparsity of the Cyclic Autocorrelation Function

Abstract : In this paper, we will firstly show that the Cyclic Autocorrelation function (CAF) is a sparse function in the cyclic frequency domain . Then using this property we propose a new CAF estimator, using Compressed Sensing (CS) technique with OMP algorithm [1]. This estimator outperforms the classic estimator used in [2]. Furthermore, since our estimator does not need any information, we claim that it is a blind estimator whereas the estimator used in [2] is clearly not blind because it needs the knowledge of the cyclic frequency. Using this new CAF estimator we proposed in the second part of this paper a new blind free bands detector. It assumes that two estimated CAF of two successive packets of samples, should have close cyclic frequencies, if a telecommunication signal is present. This new detector is a soft version of the detector already presented in [3]. This methods outperforms the cyclostationnarity detector of Dantawate Giannakis of [2]
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Contributor : Myriam Andrieux Connect in order to contact the contributor
Submitted on : Tuesday, October 1, 2013 - 10:26:55 AM
Last modification on : Monday, January 24, 2022 - 2:07:58 PM


  • HAL Id : hal-00868154, version 1


Ziad Khalaf, Jacques Palicot, Amor Nafkha, Hongfei Zhang. Blind Free Band Detector Based on the Sparsity of the Cyclic Autocorrelation Function. EUSIPCO 2013, Sep 2013, Marrakech, Morocco. ⟨hal-00868154⟩



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