A Wideband Spectrum Sensing Method For Cognitive Radio Using Sub-Nyquist Sampling
Paper in proceedings, 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

Author

Moslem Rashidi Avendi

Chalmers, Signals and Systems, Signalbehandling och medicinsk teknik, Signal Processing

Kasra Haghighi

Chalmers, Signals and Systems, Communication and Antenna Systems, Communication Systems

Arash Owrang

Chalmers, Signals and Systems

Mats Viberg

Chalmers, Signals and Systems, Signalbehandling och medicinsk teknik, Signal Processing

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

30-35 5739182

Areas of Advance

Information and Communication Technology

Subject Categories

Telecommunications

Signal Processing

DOI

10.1109/DSP-SPE.2011.5739182

ISBN

978-161284227-1

More information

Created

10/7/2017