Multiple attribute dynamic spectrum decision making for cognitive radio networks

Spectrum Sensing and Spectrum Decision making are the main functions that cognitive radios have to perform in order to select the ‘best available band’ for the establishment of a wireless communication. We model the Spectrum Decision making functionality with multiple attributes and we propose a novel use of the Analytic Hierarchy Process to optimally select available bands from a finite set of options. The simulation results show that our approach classifies from the best to the worst bands based on the requirements from two different classes of service, Real Time and Best Effort. The selection of the best available bands is done with a low execution latency.