Application of a Channel Estimation Algorithm to Spectrum Sensing in a Cognitive Radio Context

Abstract : This article deals with spectrum sensing in an orthogonal frequency division multiplexing (OFDM) context, allowing an opportunistic user to detect a vacant spectrum resource in a licensed band. The proposed method is based on an iterative algorithm used for the joint estimation of noise variance and frequency selective channel. It can be seen as a second-order detector, since it is performed by means of the minimum mean square error criterion. The main advantage of the proposed algorithm is its capability to perform spectrum sensing, noise variance estimation and channel estimation in the presence of a signal. Furthermore, the sensing duration is limited to only one OFDM symbol. We theoretically show the convergence of the algorithm, and we derive its analytical detection and false alarm probabilities. Furthermore, we show that the detector is very efficient, even for low SNR values, and is robust against a channel uncertainty.
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International Journal of Antennas and Propagation, Hindawi Publishing Corporation, 2014, 2014, Article ID 506457, 13 p. 〈10.1155/2014/506457〉
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Soumis le : jeudi 22 mai 2014 - 14:30:11
Dernière modification le : mercredi 16 mai 2018 - 11:23:48

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Vincent Savaux, Moïse Djoko-Kouam, Yves Louët, Alexandre Skrzypczak. Application of a Channel Estimation Algorithm to Spectrum Sensing in a Cognitive Radio Context. International Journal of Antennas and Propagation, Hindawi Publishing Corporation, 2014, 2014, Article ID 506457, 13 p. 〈10.1155/2014/506457〉. 〈hal-00994981〉

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