Analysis of Spectrum Sensing over Imperfect Channel conditions in Cognitive Vehicular Networks

An explosive growth in vehicular wireless services and applications gives rise to spectrum 1 resource starvation. Cognitive radio has been used to vehicular networks to mitigate the impending 2 spectrum starvation problem by allowing vehicles to fully exploit spectrum opportunities unoccupied 3 by licensed users. Efficient and effective detection of licensed user is a critical issue to realize cognitive 4 radio applications. However, spectrum sensing in vehicular environments is a very challenging 5 task due to vehicles mobility. For instance, vehicle mobility has a large effect on the wireless 6 channel, thereby impacting the detection performance of spectrum sensing. Thus, gargantuan efforts 7 have been made in order to analyze the fading properties of mobile radio channel in vehicular 8 environments. Indeed, numerous studies have demonstrated that the wireless channel in vehicular 9 environments can be characterized by a temporally correlated Rayleigh fading. In this paper, we 10 focus on energy detection for spectrum sensing and a counting rule for cooperative sensing based 11 on Neyman-Pearson criteria. Further, we go into the effect of the sensing and reporting channels 12 condition on spectrum sensing performance under temporally correlated Rayleigh sensing channel. 13 For local and cooperative sensing, we derive some alternative expressions for average probability of 14 miss detection. The pertinent numerical and simulating results are provided to further validate our 15 theoretical analyses under a variety of scenarios. 16