Computational Complexity Analysis of Cognitive Radio using PCA with Various Clustering Methods

Abstract

In this article we examine various clustering methods suitable for signal processing from wide frequency range. Partitioning and hierarchical clustering techniques are used. The research is done on the basis of cluster size, signal to noise ratio and relative computational time. Significant reduction in processing power is achieved by applying preprocessing using principal component analysis. The goal of this article is to improve quality parameters for cognitive radio systems by using preprocessing and cluster analysis.