Optimal Design Of Network Selection In Cognitive Radio Network With Multiple Licensed Networks

Cognitive radio networks(CRNs)are envisioned to be an eff ective approach to increase the spectrum utilization,and thereby mitigate the problem of spectrum scarcity due to static spectrum allocation policy.However,because of the preemptive priority of Primary User(PU),as well as the network dynamics,the Qo S of Secondary User(SU)is significantly vulnerable,which seriously impedes the development and implementation of CRNs.Therefore,it is necessary to study an effective way to improve the stability of SUs' Qo S,so that CRNs can play a key role in future wireless network.With the development of increasing network convergence technology,it is envisaged that multi-PRNs will be incorporated into CRN,which offers CRN varied choices to access different spectrum resources,gets the gains of significant network diversity,and thereby provides more space to optimize the Qo S of SU.Network selection is a key point to maximize the potential gain,while it is nontrivial to study network selection strategies,due to imperfect spectrum sensing,high complicated system status,and unformed research frameworks.To address these issues,we investigate the problem of network selection of CRN on the basis of existing research achievements,aiming to improve the Qo S of SUs.The main contributions of this dissertations are as follows:With the joint considerations of imperfect spectrum sensing,complicated system status,and unformed research frameworks,we investigate the network selection problem in an offline situation where priori acknowledge ment of multi-PRNs are given.Specifically,we first obtain the variations of shared spectrum resources based on the statistical characteristics of PRNs,and then analyze the network selection strategy.In this dissertation,we use a continuous time Markov chain to model the interactions of PUs and SUs for spectrum sharing,then define network selection strategy as parameters of the model,so as to establish a unified research framework.On this basis,we discuss the realization of random network selection and greedy network selection wi th perfect/imperfect spectrum sensing,respectively,and calculate the performance metrics of studied system.In order to further improve the Qo S of SU,we propose a weighted offline network selection scheme.Simulation results are presented to validate the effectiveness of the proposed schemes in terms of throughput and load balancing.Furthermore,we investigate the network selection problem in an online situation where priori acknowledgement of multi-PRNs are absent.For this case,we dynamically perform network selection according to the observations of collisions between PUs and SUs,aiming to maximize SUs' throughput.Specifically,we first analyze existing schemes,and then propose new solutions by substituting greedy and weighted approach into the ex isting approaches.Simulation results are shown to verify that the proposed scheme outperforms existing ones in terms of blocking rate and throughput of SUs.