Performance analysis of spatial-temporal spectrum sensing for cognitive vehicular network
Xia Liu, Zhimin Zeng, Caili Guo, Siting Zhu · 2016
The mobility in cognitive vehicular network can deeply influence the percentage of discovered spectral opportunities while the existing spectrum sensing algorithms often assume secondary users stationary or with low mobility. In order to investigate the mobility impact on SU detection probability, the spatial-temporal spectrum sensing model is extended to account for the SU mobility effects and the mathematical analysis of detection capacity for highway and urban scenarios are carried out. The capacity achievable jointly in temporal and spatial domains is introduced to measure the expected transmission capacity achievable. In order to corroborate the analysis, numerical results obtained from simulations are presented. It is noted that the probability of detection mainly depends on the event for SU being within the protection range. The PU spatial distribution, the PU protection range, the SU mobility model, the network region size and the PU activity affect the detection capacity and the maximum achievable channel access probability. The theoretical analysis is further validated through simulations.