Research Oil Jointing Precoding And Power Allocation For Distributed MIMO Cognitive Radio

With the update of wireless communication devices, and the development ofwireless communication technology, wireless communication has a great demand forspectrum resource. However, the traditional fixed spectrum allocation strategy resultsin low spectrum efficiency. In this case, cognitive radio technology which is a way toimprove spectrum efficiency has drawn wide attention of experts and scholars. Thespectrum sharing between primary and secondary users is implemented by cognitiveradio technology, whose premise is that cognitive users don’t have any effect oncommunication quality of primary users. Therefore, the power allocation algorithm ofcognitive users has important significance in the application of cognitive radiotechnology.Due to no central unit to coordinate cognitive users in distributed cognitive radiosystems, each cognitive user has to compete with other cognitive users for the samespectrum resource. As a result, the power allocation algorithm of cognitive users is amulti-objective optimization problem, which can be solved with the method based onnon-cooperative game. When each cognitive user chooses the best power allocationstrategy, the cognitive radio system will reach an equilibrium state, and eachcognitive user will gain a steady rate. However, it is not enough to only rely on thepower allocation algorithm of cognitive users, by which the user interference can beeffectively controlled in the cognitive radio system but not be eliminated. In order tosolve the above problem, this paper adopts an optimization algorithm by jointingprecoding and power allocation, which can further improve the performance ofcognitive radio systems.First, the non-cooperative game model of multi-user power allocation isconstructed, and precoding matrices are established by perfect channel stateinformation which is known by cognitive users. Therefore, the optimization algorithmby jointing precoding and power allocation can be realized. Simulation results showthat the optimization algorithm effectively improvers the performance of cognitiveradio systems. In fact, it’s hardly for cognitive users to obtain perfect channel state information. Then two kinds of imperfect channel state information on the influenceof cognitive users are studied. The first kind is between cognitive users, and it hasgreat effect on communication quality of cognitive users by multi-user interference.Simulation results show that with the increase of channel error, the multi-userinterference gradually increases, and all the rates of cognitive users decrease. Thesecond kind is between cognitive users and primary users, and it imposes restrictionson the transmitted power of cognitive users by the constraints of primary users. In thiscase, cognitive users have the low transmitted power, and they can’t have effectivecommunication. In order to minimize the effect of imperfect channel stateinformation, the overall channel state information is divided into multiple partialchannel state information, by which better precoding matrices can be found out.Simulation results show that cognitive users reduce the interference to primary usersby these precoding matrices, and have a significant improvement on data transferrates.