Research On Cooperative Spectrum Sensing Algorithm In Cognitive Radio Network

Compared with a single user spectrum sensing technology,collaborative spectrum sensing technology has much higher sensing performance.It integrates multiple users' sensing results in an appropriate way to achieve the final decision.Existing researches are performed under the ideal condition and do their best to find the optimal network detection probability to get peak throughput.However,those utilities are not discussed as a whole,such as sensing cost,resource waste and so on.Moreover,The general collaborative spectrum sensing strategy integrates all single users' spectrum sensing results indiscriminately to analyze and process,without taking interference and misleading from the malicious users into account.Based on the above-mentioned two questions,the main work of this paper can be demonstrated as follows:Under the distributed collaborative spectrum sensing network with the function of energy harvesting,two collaborative spectrum sensing strategies,which under different scenarios of selfish user and collaborate user respectively,have been proposed.Those strategies construct the relation between the sensing probability and gain function of the sensing users,and apply the Nash equilibrium of non-collaborate game strategy and Newton iteration theorem to achieve the corresponding optimal sensing probability,thus obtain the maximum earning values under different scenarios.The simulation results show the performance comparison of these two different sensing strategies,and draw the conclusion that the performance under the scenario of collaborative user is much higher.Furthermore,a fusion decision algorithm,which is based on the trust value of sensing user can be upgraded,has been proposed.The algorithm use the feedback of the transmitted result of the sensing user and the native sensing result of this sensing user to upgrade the current trust value of the sensing user with Bayes Criteria dynamically.The collaborative decision center can classify all sensing users in the network according to the current trust value of each sensing user,and select the reliable native sensing results to make the final decision.Hence prevent the final decision from being interfered by those malicious or unrelated users in the collaborative spectrum sensing network,and assure the accuracy of the final decision.When several malicious and unrelated users are existed in the network,the simulation results demonstrate that the proposed collaborative decision algorithm in this paper has much higher performance than the traditional decision scheme.