JOURNAL ARTICLE

Spectrum sensing for cognitive radio architectures based on sub-Nyquist sampling schemes

Abstract

This paper investigates a signal processing architecture for cognitive radio based on a sub-Nyquist sampling of the wideband signal. Then spectrum scanning is performed by applying an adaptive digital filter to scan the bands which might be used for cognitive radio. In particular, the paper studies detectors which are tailored for the applied signal processing scheme and which takes into account the noise correlation, introduced by the digital scanning filter.

Keywords:
Cognitive radio Computer science Wideband Nyquist–Shannon sampling theorem Detector Sampling (signal processing) Electronic engineering SIGNAL (programming language) Nyquist frequency Anti-aliasing filter Nyquist rate Noise (video) Filter (signal processing) Digital filter Telecommunications Root-raised-cosine filter Computer vision Engineering Wireless

Metrics

4
Cited By
0.73
FWCI (Field Weighted Citation Impact)
19
Refs
0.72
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Cognitive Radio Networks and Spectrum Sensing
Physical Sciences →  Computer Science →  Computer Networks and Communications
Advanced Adaptive Filtering Techniques
Physical Sciences →  Engineering →  Computational Mechanics
Sparse and Compressive Sensing Techniques
Physical Sciences →  Engineering →  Computational Mechanics
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