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Communication Dans Un Congrès Année : 2022

Unsupervised and computationally lightweight spectrum sensing in IoT devices

Résumé

Principal component analysis (PCA) is a widespread technique in data analysis. Recently, the L1-norm has been proposed as an alternative criterion to classical L2-norm in PCA due to its greater robustness to outliers. The present work shows that, with a whitening step, L1-PCA can perform spectrum sensing and modulation recognition in IoT applications. Numerical experiments confirm this finding.
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Dates et versions

hal-04533656 , version 1 (05-04-2024)

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Rubén Martín-Clemente, Vicente Zarzoso. Unsupervised and computationally lightweight spectrum sensing in IoT devices. 9th International Electronic Conference on Sensors and Applications, Nov 2022, Online, Switzerland. ⟨10.3390/ecsa-9-13159⟩. ⟨hal-04533656⟩
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