Spectrum Sensing Error Performance in Cognitive Radio using PCA and Different Clustering Methods

In this article we examine various clustering methods suitable for signal processing from wide frequency range. Hierarchical and partitioning techniques are considered. The research is done on the basis of cluster size, signal to noise ratio and means square error. Preprocessing using principal component analysis and subsequent clustering can decrease mean square error and increase accuracy. The goal of this article is to improve quality parameters for cognitive radio systems by applying preprocessing and cluster analysis.