Interference Aggregation in Spectrum-Sensing Cognitive Wireless Networks

TLDR

Growing demand and inefficient use of licensed spectrum have prompted regulators to open under‑utilized bands for dynamic, non‑interfering access by unlicensed users, a goal that cognitive radio networks aim to achieve by autonomously sensing white spaces. The paper develops a statistical model of interference aggregation in spectrum‑sensing cognitive radio networks. The authors derive a statistical model that links regulatory interference limits to system parameters—sensitivity, transmit power, cognitive radio density, and propagation conditions—and extend it to include the impact of cooperative spectrum sensing on aggregate interference distribution.

Abstract

The increasing demand for the radio spectrum along with the 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.