Statistical characterization of interference in cognitive radio networks

The increasing demand for radio spectrum along with inefficient usage of the licensed bands has led the regulatory bodies to consider opening up the under-utilized licensed frequency bands for dynamic access by unlicensed users. Such dynamic spectrum access is envisioned to resolve the spectrum scarcity by allowing unlicensed users to opportunistically utilize the white spaces across the licensed spectrum on a non-interfering basis. Cognitive radio networks offer a promising realization of this novel paradigm, thanks to their ability to autonomously identify the white spaces through spectrum sensing. Implementation of such networks, however, requires a model translating the regulatory constraint on the aggregate interference to the system- and device-level design parameters. In this paper a statistical model of interference aggregation in spectrum-sensing cognitive radio networks is developed. In particular, distribution of the aggregate interference is characterized in terms of parameters such as sensitivity, transmitted power, and density of the cognitive radios as well as the underlying propagation environment. The model is further extended to account for the effect of cooperative spectrum sensing on the distribution of the aggregate interference.