Research And Design Of Cooperative Spectrum Sensing Scheme For IRS-Assisted Cognitive Radio System

With the rapid growth of communication equipment and the widespread application of wireless communication technology,the scarcity of spectrum resources and radio interference have become one of the bottlenecks restricting its development.Spectrum efficiency and energy efficiency are becoming the two basic standards for designing future wireless networks.In order to improve spectrum utilization,new frequency bands such as millimeter waves and terahertz frequency bands are continuously being developed and utilized,or more efficient spectrum management and sharing strategies are being researched to better meet the needs of wireless communication.In this context,Cognitive Radio(CR)technology has been proposed,whose core idea is to allow Secondary Users(SU)to share the unused spectrum resources of Primary Users(PU)through dynamic spectrum access mechanisms to improve spectrum efficiency and utilization efficiency.As a key technology of CR,the accuracy of spectrum sensing is one of the key factors that determine whether the CR system can successfully achieve spectrum sharing.In traditional single-user spectrum sensing methods,spectrum sensing results may be inaccurate due to the temporal and spatial variations of channel conditions and noise factors,which can lead to waste of spectrum resources or spectrum conflicts.However,Cooperative Spectrum Sensing(CSS)can improve the accuracy of spectrum sensing results by completing the sensing process through cooperation between multiple users,breaking through the limitations of single-user spectrum sensing.CSS can help CR systems better understand the current use of spectrum,thereby better utilizing available spectrum resources and improving network performance and reliability.This article aims to study the factors that affect system sensing performance,and to study how to improve the accuracy of CSS and further reduce system energy consumption,thereby improving the spectrum efficiency of CR systems.The main research contents and innovations are as follows:First,the emergence of Intelligent Reflecting Surface(IRS)has opened up tremendous possibilities for wireless communications.In order to mitigate the problems of shadow fading and multi-path effects present in the channel environment,and thus enhance the sensory performance of CR networks,we propose to introduce IRS in CR networks to aid multi-user CSS schemes.The primary objective is to maximize the SU sum rate by jointly optimizing the SU transmit power allocation and IRS phase under the SU power constraint as well as the interference constraint on the PU.We use an efficient alternating optimization algorithm based on block-coordinate descent to solve the proposed problem.The optimal power allocation is first obtained by solving the Lagrange multiplier and injection power allocation algorithms and the Karush-Kuhn-Tucker(KKT)algorithm;then,fixing the resulting power allocation solution,the non-convex problem is transformed into a semi-definite relaxation problem using a continuous convex approximation,semi-definite Then,fixing the obtained power allocation solution,the non-convex problem is transformed into a convex problem with semi-definite programming using the continuous convex approximation and semi-definite relaxation method,so as to solve the approximate optimal solution of the IRS phase shift matrix.The simulation results show that the proposed scheme can greatly improve the spectral sensing performance and spectral efficiency of the CR network.Second,in order to further reduce the energy consumption of the IRS-assisted CR system,this thesis conducts research on user selection in CSS.The study shows that the sensing performance of the system does not necessarily reach its optimum when all SU participate in sensing,as the performance of individual SUs involved in the CSS process may not be the best.However,this significantly increases the system’s energy consumption.To address this problem,this thesis proposes an energy-based SU selection algorithm in the IRS-assisted CR communication system.Firstly,based on the constraints of the system detection probability and false alarm probability,the minimum detection threshold that satisfies the system detection performance is found,and the sensing performance of a single SU is higher at this threshold.Then,with the detection threshold fixed,SUs are selected based on their sensing performance ranking,as the selected SUs can meet the system requirements for CSS under this threshold,thus reducing the system’s energy consumption.