A Wideband Spectrum Sensing Method For Cognitive Radio Using Sub-Nyquist Sampling
Paper i proceeding, 2011

Spectrum sensing is a fundamental component in cognitive radio. A major challenge in this area is the requirement of a high sampling rate in the sensing of a wideband signal. In this paper a wideband spectrum sensing model is presented that utilizes a sub-Nyquist sampling scheme to bring substantial savings in terms of the sampling rate. The correlation matrix of a finite number of noisy samples is computed and used by a subspace estimator to detect the occupied and vacant channels of the spectrum. In contrast with common methods, the proposed method does not need the knowledge of signal properties that mitigates the uncertainty problem. We evaluate the performance of this method by computing the probability of detecting signal occupancy in terms of the number of samples and the SNR of randomly generated signals. The results show a reliable detection even in low SNR and small number of samples.

Subspace methods

Cognitive radio

Correlation matrix

Wideband spectrum sensing

Sub-Nyquist sampling


Moslem Rashidi Avendi

Chalmers, Signaler och system, Signalbehandling och medicinsk teknik

Kasra Haghighi

Chalmers, Signaler och system, Kommunikation, Antenner och Optiska Nätverk

Arash Owrang

Chalmers, Signaler och system

Mats Viberg

Chalmers, Signaler och system, Signalbehandling och medicinsk teknik

2011 Digital Signal Processing and Signal Processing Education Meeting, DSP/SPE 2011 - Proceedings

30-35 5739182
978-161284227-1 (ISBN)


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