Journal
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
Volume 62, Issue 12, Pages 3351-3360Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIM.2013.2265607
Keywords
Cognitive radio; discriminant analysis; power spectrum; rice distribution; signal detection; spectral component; spectrum sensing; statistics
Funding
- Research Project of BelV Cognitive Radios for Nuclear Power Plants
- Research Foundation Flanders (FWO)
Ask authors/readers for more resources
Signal detection of primary users for cognitive radios enables spectrum use agility. In normal operation conditions, the sensed spectrum is nonflat, i.e. the power spectrum is not constant. A novel method proposes the segmentation of the measured spectra into regions where the flatness condition is approximately valid. As a result, an automatic detection of the significant spectral components together with an estimate of the magnitude of the spectral component and a measure of the quality of classification becomes available. In this paper, we optimize the methodology for signal detection in cognitive radios such that the probability that a spectral component was incorrectly classified is iteratively reduced. Simulation and measurement results show the advantages of the presented technique in different types of spectra.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available