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Communication Dans Un Congrès Année : 2016

Spectrum Sensing Enhancement Using Principal Component Analysis

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Résumé

In this paper, Principal Component Analysis (PCA) techniques are introduced in the context of Cognitive Radio to enhance the Spectrum Sensing performance. PCA step increases the SNR of the Primary User’s signal and, consequently, enhances the Spectrum Sensing performance. We applied PCA as a combination scheme of a multi-antenna Cognitive Radio system. Analytic results will be presented to show the effectiveness of this technique by deriving the new SNR obtained after applying PCA, which can be considered a pre-processing step for a classical Spectrum Sensing algorithm. The effect of PCA is examined with well known detectors in Spectrum Sensing, where the proposed technique shows its efficiency. The performance of the proposed technique is corroborated through many simulations.
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Dates et versions

hal-01466045 , version 1 (13-02-2017)

Identifiants

  • HAL Id : hal-01466045 , version 1

Citer

Abbass Nasser, Ali Mansour, Koffi Clément Yao, H. Abdallah, Mohamad Chaitou, et al.. Spectrum Sensing Enhancement Using Principal Component Analysis. ISSP 2016, Dec 2016, Limassol, Cyprus. ⟨hal-01466045⟩
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