Research On Cognitive Radio Cooperative Spectrum Sensing Algorithms Based On Crowd Sensing

With the explosive growth of wireless communication systems applications,there is an increasing demand for spectrum resources,which leads to spectrum shortage and fierce competition.The emergence of cognitive radio has effectively relief the problem of spectrum resource shortage.Cognitive radio allows unlicensed users(secondary users)to use the same spectrum in a way of spectrum access when the licensed users(primary users)do not use spectrum resources.How to effectively detect whether primary users use spectrum resources and how to motivate secondary users to participate in spectrum sensing is the focus of this thesis.In this thesis,the incentive algorithm in crowd sensing is introduced,which is combined with spectrum sensing algorithm to motivate secondary users to participate in spectrum sensing and ultimately improve detection performance.The details are as follows:(1)Firstly,the Bayesian game model is introduced into spectrum sensing,and the incentive mechanism of Bayesian game is used to motivate secondary users to participate in spectrum sensing.In this model,the SNR of the secondary user is mapped to the type space of the Bayesian game,and the type space is set to be uniform and discrete;the perception time is mapped to the strategy space,from which the secondary user can choose the optimal strategy.The secondary users participating in the perception send the sensing information to the fusion center and get the final result after voting and fusion.The simulation results show that the proposed method effectively improves the spectrum sensing performance,detection probability and the perception enthusiasm of the secondary users.(2)Secondly,when the secondary user sends the data to the fusion center,factors such as shadow effect and large-scale fading will lead to poor transmission channel conditions.In order to reduce the influence of channel condition difference,this thesis introduces the relay method and proposes a relay cooperative spectrum sensing algorithm based on reverse auction.In this algorithm,secondary users are divided into ordinary secondary users and relay secondary users by setting a SNR threshold.Relay secondary users can not only send their own data to the fusion center,but also act as a relay to send the perception data of ordinary secondary users to the fusion center by way of compensation,and these two kinds of users carry on the interest exchange through the way of reverse auction.This algorithm can effectively solve the problem of the influence of the transmission channel conditions and improve the perception enthusiasm of the users.(3)Finally,this thesis proposes a cooperative spectrum sensing algorithm based on alliance game under the condition of multi-task.In the case of multi-task,there may be cases where the secondary user resource allocation is uneven.This algorithm treats each task as an alliance,and the user income in the alliance is only related to the alliance.When the number of participants participating in the alliance is too large,the average revenue of secondary users in the alliance will decrease,and those perceptive users with negative revenue will choose to join other alliances instead.In this algorithm,the perceptual secondary user resources are evenly allocated to each task to prevent the low perceptual performance caused by the uneven allocation of secondary user resources.The simulation results show that this algorithm effectively improves the performance of cooperative spectrum sensing.