Compressed Sensing for Wideband Cognitive Radios

By Zhi Tian, Georgios B. Giannakis. IEEE International Conference on Acoustics, Speech, and Signal Processing, 2007

780 citations recorded by the source corpus.

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A survey of spectrum sensing algorithms for cognitive radio applications (2009, methodology): “The method proposed in [96] is extended in [97] by using sub-Nyquist sampling.”
Collaborative Cyclostationary Spectrum Sensing for Cognitive Radio Systems (2009, neutral): “[2], [4]–[8].”
Compressed Sensing (2014, neutral): “Estas abarcan diversas áreas como: imagenoloǵıa medica [49, 45], conversión analógico/digital [68], detección mediante RADAR [4, 42], corrección de errores [18], cámaras digitales [34, 21, 51], Sismoloǵıa [41], Radioastronomı́a [71], comunicación inalámbrica [63, 3, 65] y redes de sensores inalámbri”
Advances on Spectrum Sensing for Cognitive Radio Networks: Theory and Applications (2017, methodology): “To implement compressive sensing in cognitive networks, [103] shows the detailed procedure which is shown in Fig.”
Cooperative spectrum sensing in cognitive radio networks: A survey (2011, methodology): “In the conventional compressed sensing scheme [40], the first step is to generate measurements xt of size K × 1 by sub-Nyquist-rate random sampling.”
Wireless interference identification with convolutional neural networks (2017, background): “In [6], [7] it is also applied for classification of frequency bands into white, gray and black sections.”