Cooperative Spectrum Sensing Incentive Mechanism Based On Game Theory

With the development of mobile intelligent terminals,higher quality of data transmission is required.However,the spectrum is a scarce natural resource.The traditional static spectrum access allocation scheme is obviously unable to adapt to the growing demand for high data rate,so cognitive radio(CR)technology is born.Spectrum sensing can sense spectrum holes and determine whether the primary user exists,which is an important part of cognitive radio.Cooperative spectrum sensing can improve the detection probability of primary user in spectrum sensing.In most research of cooperative spectrum sensing,it is assumed that the cooperative users are willing to participate,but in actual situations,users must pay a price to participate in spectrum sensing.Therefore,how to encourage more users to participate in spectrum sensing to improve the accuracy of sensing results is the main problem of this thesis.In this thesis,spectrum sensing is combined with incentive mechanism of crowdsensing.Considering different scenarios and optimization objectives,three cooperative spectrum sensing incentive mechanisms based on game theory are proposed.The main contents and innovations of this thesis are as follows:(1)A multi-task cooperative spectrum sensing algorithm based on Stackelberg game is proposed in this thesis,which applies crowd sensing and game theory to study spectrum sensing.In the Stackelberg game,the fusion center(platform)is modeled as the leader,while secondary users are modeled as the follower.In the leader game,the platform publishes the optimal reward value to the secondary users to get the optimal utility.In the follower game,we focus on the influence of residual energy on the secondary users.In this stage,the secondary users under the same task constantly adjust their participation time under the reward of the platform to achieve equilibrium.Eventually,the secondary users can obtain their own optimal utility.The simulation results show that the algorithm can improve the detection probability of the fusion center.(2)Considering the situation of incomplete information,a cooperative spectrum sensing algorithm based on incomplete information is proposed.The algorithm models the fusion center and the secondary user as the leader and the follower of Stackelberg game.In the leader game,the fusion center issues the optimal reward value to the secondary user to obtain the best utility.In the follower game,the secondary user predicts his own utility according to the strategy space and the signal-to-noise ratio space of other secondary users,and determines the sensing time to obtain the best expected utility.At the same time,considering the process of a multiple game period,a modification method of the utility function of the secondary user is proposed,which makes the expected utility and the actual utility basically consistent.The simulation results show that the algorithm can promote effectively cooperative spectrum sensing in the case of incomplete information,and the performance of spectrum sensing is also improved.(3)Considering that users can transmit and share data with each other,cooperative spectrum sensing based on cooperative game is proposed.High cost will affect the enthusiasm of secondary users to participate in spectrum sensing,so cooperative game model is adopted.Multiple secondary users cooperate with each other to form a coalition,which can reduce the cost of perception and improve the effectiveness.In the coalition,the secondary user sends the sensing information to the cluster head,and then the cluster head send it to the fusion center.Simulation results show that the algorithm can effectively reduce the cost of secondary users,encourage secondary users to participate in spectrum sensing,and improve the detection probability.