Performance Optimization Of MIMO Cognitive Network In Underlay Paradigm

With the advent of the fifth-generation mobile communications era,the increasing number of intelligent terminals and the emergence of high-speed services have led to increasingly prominent issues such as the scarcity and low utilization of spectrum resources.How to achieve high spectrum sharing and meet the access requirements of more types of high-speed services is an urgent task that needs to be solved in wireless communications.MIMO cognitive technology combines both cognitive intelligence flexibility and MIMO spatial transmission capabilities,which can significantly improve system performance.Along with research went thorough,in order to improve the system performance of the cognitive system further,new technologies may be introduced.Therefore,in underlay paradigm,this thesis focuses on the performance optimization of MIMO cognitive networks based on non-orthogonal multiple access technology.The main research work of this thesis is as follows.1.Aiming at the capacity requirements of downlink secondary users system of MIMO cognitive networks in underlay paradigm,a capacity optimization scheme for secondary users system based on non-orthogonal multiple access is proposed.Firstly,the system model is constructed,and the capacity expression of cognitive system is deduced according to the system model and the characteristics of the non-orthogonal multiple access receiver.Then,when constructing the system optimization equation,the power requirement of the decoding of non-orthogonal multiple access receiver is taken as one constraint,and the quality of service of secondary user is another constraint.Finally,using convex optimization theory combined with mathematical induction method to solve the optimal power allocation coefficient and verify the rationality of the solution.Simulation results show that the proposed scheme may improve the secondary users' system performance to some extent.2.Concerning the throughput requirements of cognitive base station and combining with energy harvesting in the uplink of MIMO cognitive networks,an optimization scheme for the throughput of secondary user base station in MIMO cognitive networks based on non-orthogonal multiple access is proposed.Firstly,equal symbols are used to represent different secondary users to construct the system model that on the basis of energy harvesting.Then,a novel optimal power allocation scheme is derived according to the system model,and meanwhile,the power characteristics of NOMA receiver decoding and the quality of service are taken as constraints.Finally,using convex optimization theory to solve the problem and verifying the feasibility of the algorithm.Simulation results show that the proposed scheme may improve cognitive base station performance to a certain extent.