Modeling and Characterization of Spectrum White Spaces for Underlay Cognitive Radio Networks

Abstract

Cognitive Radio (CR) networks are envisaged as the key technology to realize dynamic spectrum access and solving the scarcity of radio spectrum. Having a temporal characterization of the spectrum white spaces in the primary network is a key element for studying and designing radio resource management mechanisms in CR networks. In that sense, most of the studies in the literature rely on an ON-OFF model with exponentially distributed on and off times. The usage of that model, however, is principally based on its analytical tractability. In this paper we propose a versatile Markovian model for the duration of the spectrum white spaces. Our model builds on a simple model of the channel holding time (CHT) in the primary network and then matrix-analytic techniques are applied to derive and analyze the duration of the white spaces. Despite its simplicity, the proposed approach is proven to be able to model very accurately scenarios where the CHT distribution is of a more complex type not amenable to mathematical analysis. Our numerical results show that the duration of the white spaces exhibits a low sensitivity to the distribution of the channel holding time beyond the mean.