Blind Spectrum Sensing for Cognitive Radios Using Discriminant Analysis: A Novel Approach

In this paper, we present a new spectrum sensing technique for cognitive radios based on discriminant analysis called spectrum discriminator. The presented technique uses the knowledge of the noise uncertainty and a probabilistic validation to overcome the limitations of the discriminant analysis. A comparative study between the proposed technique and the maximum-minimum eigenvalue detection has been performed based on two performance metrics: the probability of false alarm and the probability of detection. The spectrum discriminator has been further developed to a peel-off technique where all primary users can be detected. The performance of the spectrum discriminator and the peel-off technique has been tested on simulations and experimentally verified. The comparative study is based on simulations as well as measurements.