The Design And Research Of Beamforming Algorithm In The Cognitive Radio Network

With the development of wireless communication technologies and the increasing need of spectrum resources,the resources of spectrum become scarcer and scarcer.Cognitive radio is a typical implementation of the spectrum reuse technologies,which allows the secondary users to access to the spectrum that occupied by the primary users.It means that cognitive radio can solve the problem of unbalanced utilization of spectrum resource and improve the efficiency of spectrum.Multicast transmission is another technology that has been an integral part of mobile communication systems.Moreover,with the help of multi-antenna relay nodes,cooperative multicast is one of the most important technologies among that.For those schemes which are based on cooperative multicast mode,multi-antenna relay nodes may operate in either the distributed or the centralized scenario.When operating in the distributed scenario,each antenna forwards its own received signal with a respective amplification factor.Relatively speaking,when the relay node operates in the centralized scenario,each antenna forwards a combination of all received signals.In other words,joint signal processing across different antennas is executed in this manner.Although the implementation complexity increases,the supported throughout is much higher.In this paper,we focus on the design of the beamforming in cognitive network with the help of relays.Based on the following point,we completed the thesis writing.First of all,this paper proposes a model based on a cognitive network.In this cognitive network,two cognitive sub-networks share the same relay station,considering the cognitive network interference to the primary user.In this cognitive wireless network model,this paper studies the Weighted Rate Balance problem with the constraint of the transmit power of the cognitive network,and designs a joint beamforming scheme at the cognitive base station and the relay station which is used to maximize the Weighted Rate Balance of secondary users.For the sake of solving this kind of non-convex problem,this paper adopts the iterative optimization algorithm.Therefore,it shows that we only need to solve several semidefinite programming(SDP)sub-problems in each iterative step,which can be easily resolved.The results of simulation indicates that,compared with the widely studied diagonally structured beamforming design,the method proposed by this paper presents better performance.What's more,this paper studies the robustness beamforming problem in the cognitive relay network with the distributed relay nodes.In this typical cognitive relay network,several single-antenna cognitive relay nodes forward signals that are transmitted by a cognitive source to several cognitive destinations.It is assumed that there is no direct link from the source node to destinations and the communication can only be completed via the relay nodes.Meanwhile,some primary users are active and operating on the same authorized spectrum.In response to this distributed cognition network scenarios,the focus of this paper is the robustness of beamforming design in this network.It's assumed that the cognitive network only get part of channel state information.In our approach,the uncertainty on the channel covariance matrices is assumed to be confined in an ellipsoid of given size and shape,where prior knowledge about the statistical distribution of the CSI mismatch is taken into account.The design intent of this paper is to minimize the transmitted power under worst-case Quality-of-Service constraints.And we extend the developed robust problem in cognitive radio network where interference leaked to the primary users is required to be below a given interference threshold.This paper obtains exact reformulations for both worst-cast problems based on the method of Lagrange duality,and then,the resulting issues can be done by using semidefinite relaxation.