Research On Symbol Level Precoding In Cognitive Radio System Assisted By Intelligent Reflecting Surface

With the rapid development of wireless communication technology,a large number of mobile terminals,industrial facilities and transportation equipment need to access the communication network,resulting in an increasingly sharp contradiction between the huge demand for spectrum and the limited spectrum resources,so cognitive radio technology arises at the historic moment.It can ensure that the cognitive user and the primary user can share spectrum resources without interfering with the normal communication of the primary user,and effectively improve the spectrum utilization rate.In the working process of wireless communication system,all kinds of service quality indicators are easy to deteriorate due to the influence of communication environment.Intelligent reflecting surface can improve the energy efficiency and service quality of wireless communication system by dynamically configuring the communication environment.Based on the symbol level precoding scheme,this thesis studies the power optimization and signal-to-noise ratio optimization problems in cognitive radio communication systems assisted by intelligent reflecting surface.The specific research contents are as follows:1)The problem of transmitting power minimization in cognitive radio system assisted by intelligent reflecting surface is studied,which mainly considers to minimize the transmitting power of cognitive base station under the cognitive user side symbol error probability,the interference temperature imposed by the system and the constant modulus constraint of intelligent reflecting surface.Due to the existence of variable coupling in the constraint conditions,the optimization problem cannot be solved directly.In this thesis,block coordinate descent(BCD)and semi-definite relaxation(SDR)algorithms are used to deal with the optimization problem.Simulation experiments and comparative analysis show that the symbol level precoding scheme can save 1.2～2d BW of transmitting power compared with the zero forcing(ZF)linear precoding scheme at the same symbol error probability of the user side.2)The received signal-to-noise ratio maximization problem in cognitive radio system assisted by intelligent reflecting surface is studied,which mainly considers the maximization of the received signal-to-noise ratio of cognitive users under the constraints of symbol level precoding,interference temperature imposed by the system and the modulus of intelligent reflecting surface.Due to the variable coupling in the constraints,the optimization problem cannot be solved directly.In this thesis,the BCD algorithm is used to decompose the optimization problem into two sub-problems that can be iteratively updated respectively,and then the optimization problem is solved.Finally,through simulation experiments and comparative analysis,it is shown that the symbol level precoding scheme can obtain higher signal-to-noise ratio gain at the cognitive user side than the traditional linear precoding scheme.