Scheduled Sequential Compressed Spectrum Sensing for Wideband Cognitive Radios

Compressed sensing based cyclic feature spectrum sensing for cognitive radios

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Machine Learning-aided, Robust Wideband Spectrum Sensing for Cognitive Radios

Compressed Spectrum Estimation for Cognitive Radios

Cognitive Radios observe the spectral environment through spectrum estimation. In particular, reconfigurable Software Defined Radio architectures generate large amounts of sample data, which can be computationally expensive to analyse. Compression by time-shifted random preintegration prior to spectrum estimation reduces the amount of data to be processed. It is simple to implement and scalable...

Spectrum Sensing in Cognitive Radios using Distributed Sequential Detection

Cognitive Radios are emerging communication systems which efficiently utilise the unused licensed radio spectrum called spectral holes. They run Spectrum sensing algorithms to identify these spectral holes. These holes need to be identified at very low SNR (≤ −20 dB) under multipath fading, unknown channel gains and noise power. Cooperative spectrum sensing which exploits spatial diversity has ...

Cognitive Radios – Spectrum Sensing Issues

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