Research Article
A Modified Spectrum Sensing Method for Wideband Cognitive Radio Based on Compressive Sensing
@INPROCEEDINGS{10.1109/CHINACOM.2009.5339762, author={Xi Chen and Linjing Zhao and Jiandong Li}, title={A Modified Spectrum Sensing Method for Wideband Cognitive Radio Based on Compressive Sensing}, proceedings={3rd International ICST Workshop on Cognitive Radio Network}, publisher={IEEE}, proceedings_a={CRNET}, year={2009}, month={11}, keywords={Cognitive radio; spectrum sensing; compressive sensing; parallel; sub-Nyquist sampling}, doi={10.1109/CHINACOM.2009.5339762} }- Xi Chen
Linjing Zhao
Jiandong Li
Year: 2009
A Modified Spectrum Sensing Method for Wideband Cognitive Radio Based on Compressive Sensing
CRNET
IEEE
DOI: 10.1109/CHINACOM.2009.5339762
Abstract
In cognitive radio, secondary users require fast and accurate spectrum sensing, so that they can dynamically monitor the spectrum and rapidly tune their parameters to utilize the spectrum available, as well as avoid causing interference to primary users. The traditional spectrum sensing methods in a wideband cognitive radio are challenging to implement since they require very high sampling rates at or above the Nyquist rate. A new technique called compressive sensing (CS) can solve the problem, which exploits the sparsity of signal’s frequency response. In this paper, a parallel spectrum sensing structure in cognitive radio is proposed. In the structure, we use compressive sensing and wavelet to process the signal in each branch. Then we get the final renconstruction output from the results of all branches. The modified sensing method based on this special structure is more accurate since it can reduce the effect of noise. Simulation results show the proposed method has performance improvement over traditional methods.
