Evaluation of a belief-based decision making in a real-time platform for Cognitive Radio networks

This paper presents a real-time testbed based on reconfigurable devices able to transmit and receive data at different operating frequencies, which are dynamically configured. The main objective of this paper is to provide an advanced and realistic framework where the performance of algorithms and policies for spectrum selection in Cognitive Radio (CR) networks can be fully evaluated in a real-time environment. In particular, this paper focuses on a CR belief-based decision making framework particularized for different observation strategies that decide when measurements are carried out to predict the radio environment dynamism. Results show that an accurate selection of an observation strategy is a key element for the trade-off between achieved performance and measurement requirements.