Analysis of the Impact of Cognitive Vehicular Network Environment on Spectrum Sensing

The Cognitive Vehicular Network (CVN) has emerged as a promising solution providing additional resources and allowing spectrum efficiency. However, vehicular networks are highly challenging for spectrum sensing due to speed, mobility and dynamic topology. Furthermore, these parameters depend on the CVNs’ environment such as highway, urban or suburban. Therefore, solutions targeting CVNs should take into consideration these characteristics. As a first step towards an appropriate spectrum sensing solution for CVNs, we first, provide a comprehensive classification of existing spectrum sensing techniques for CVNs. Second, we discuss, for each class, the impact of the vehicular environment effects such as traffic density, speed and fading on the spectrum sensing and data fusion techniques. Finally we derive a set of requirements for CVN’s spectrum sensing that takes into consideration specific characteristics of CVN environments.