The research of spectrum sensing energy consumption in WCN based on Poisson model

In Wireless Cognitive Networks,a variety of spectrum sensing algorithms are proposed to improve the spectrum sensing performance and the detection probability,but few literature research the energy consumption in the process of spectrum sensing.In Wireless Cognitive Networks Poisson process can be used to count the energy consumption even under interference limited since its randomness.Therefore,we model and research spectrum sensing energy consumption in Wireless Cognitive Networks based on Poisson process,the energy of spectrum sensing is fitting as the function of spatial density,the number of secondary users and the number of hops in Wireless Cognitive Networks,we model spectrum sensing energy as a truncated gamma distribution.On the basis of this modeling,we analyze and compare the energy consumption of traditional time spectrum sensing to bandwidth spectrum sensing.Simulation and analysis results show that in terms of the number of user and time,the energy consumption of bandwidth spectrum sensing both less than time spectrum sensing,which proves the superiority of bandwidth spectrum sensing.