Crowd Spectrum Sensing Based Cooperative Spectrum Sensing Algorithm

With the rapid development of mobile data services,the demand for wireless spectrum resources is also growing.So cognitive radio technology(CR)is proposed,and spectrum sensing technology is an important part of CR system.Cooperative spectrum sensing is a spectrum sensing method that several secondary users(SUs)work together,which can effectively improve the accuracy of sensing.Crowd-Sensing is a new data acquisition mode which combines crowdsourcing idea and terminal device sensing ability.It has gradually become a research hotspot.In this thesis,the crowd-sensing incentive mechanism is applied to cooperative spectrum sensing.Focus on how to design a reasonable mechanism to stimulate enough secondary users to participate in the sensing task and provide high quality and reliable sensing data.The sensing utility is optimized through game theory and convex optimization.Three cooperative spectrum sensing algorithms are proposed for multi-task,non-ideal channel and relay transmission scenarios respectively.The main contents and achievements of this paper are as follows:(1)For multitasking spectrum sensing,put forward a cooperative spectrum sensing algorithm based on multi-task incentive mechanism.The algorithm establishes utility functions of secondary users who take part in the sensing according to the relationship between detection probability and sensing time.SUs get the optimal utilities by optimizing the recognition time,and determine which channel to sense by comparing the utilities from different channel.Under the budget constraint,the base station chooses the SUs to take part in the sensing with greedy algorithm.SUs will get some rewards after they finish the sensing.The simulation results show that this algorithm can get an outstanding detection performance,which is superior to the algorithms compared.SUs can get large rewards.Hence,this algorithm can get multiple channels sensed,and promotes the cooperative detection probability effectively by stimulating the involvement of SUs.(2)For non-ideal channel,put forward a joint optimization algorithm for sensing time and transmitting power in crowd spectrum sensing under non-ideal channel.Define SUs' utility expectation functions related to rewards,sensing time and transmission power under non-ideal channel.Then,construct the optimization problem of maximizing the utilities of SUs by optimizing the sensing time and the transmission power,and prove that this problem is a convex optimization problem.The optimal sensing time and transmission power are obtained by using the Karush-Kuhn-Tucker(KKT)conditions.The numerical simulation results show that the spectrum detection performance of algorithm which we put forward is improved.(3)For the scenarios where sensing information can be forwarded through transactions,a bargaining-based cooperative spectrum sensing algorithm is proposed.When the secondary user is unable to send the sensing information directly to the base station,the sensing imformation can be forwarded through other secondary users by transaction.In this algorithm,the cooperative transmission of perceptual information between secondary users is modeled as Nash bargaining model.By Nash Bargaining Solution,the optimal transaction mode can be obtained,so as to encourage more secondary users who can not directly send data to the base station to participate in sensing and improve the accuracy of spectrum sensing.The simulation results show that the spectrum sensing performance of the algorithm is improved.