Research On Beamforming Of IRS-Assisted Secure Communication System Based On PSO Algorithm

Physical layer security technology has become an effective solution to ensure the security of information transmission.The intelligent reflecting surface(IRS)can further improve the system performance at limited costly by cooperatively changing the wireless channel between the transmitter and receiver through software programming,and by reasonably optimizing and allocating network resources,namely,the transmit beamforming at the base station(BS)and the reflect beamforming at the IRS.It provides a new design idea for the development of secure communication at the physical layer.Therefore,this thesis focuses on beamforming design in IRS-assisted multiple input single output(MISO)secure communication system.For the single IRS-assisted scenario,under the constraint of the secrecy rate and IRS reflection coefficient,a nested optimization method based on particle swarm algorithm is proposed to jointly optimize the transmit and reflect beamforming to minimize the transmit power of the base station.Specifically,the particle swarm optimization(PSO)algorithm is used to optimize the reflect beamforming and the Lagrange function method derives a closed-form expression to solve for the transmit power,which is fed back to the particle swarm algorithm as the fitness value,enabling the nesting of the two algorithms.In this algorithm,the particle position is a feasible solution for the phase shift vector of the reflecting surface,and the limit of the phase shift of the reflecting unit is equivalent to the limit of the particle position,which cleverly satisfies the constraints on the reflection coefficients.Then,particles dynamically adjust based on their own and other particles’ movement experience to realize the update of reflect beamforming.Simulation results show that the IRS-assisted secure transmission strategy has great potential to reduce the required transmit power of the base station,and the proposed PSO-based nested optimization algorithm outperforms the traditional gaussian randomization-assisted semidefinite relaxation(SDR)algorithm.Furthermore,we find that increasing the number of IRS reflecting units is more cost-effective than enlarging the antenna array size of the transmitter in reducing base station transmit power.For the double IRS-assisted scenario,in order to fully exploit the potential of the two IRS-assisted wireless networks,the reflection link between the two IRSs is specifically considered to obtain cooperative beamforming gain.In the case of coexistence of single-and double-reflection links,an alternating optimization algorithm based on PSO is proposed to jointly optimize the transmit beamforming at the BS and the reflect beamforming at the two distributed IRSs(deployed near the BS and the user,respectively)to maximize the secrecy rate of the system.Specifically,fixing one of the reflect beamforming,the improved PSO algorithm is used to simultaneously optimize the transmit beamforming and the reflect beamforming of the other IRS.During the optimization process,the particle position is a feasible solution for the phase shift vector of the reflecting surface,and the transmit beamforming is dynamically adjusted with the update of the particle position,whose value can be obtained by solving the generalized Rayleigh entropy method.The method cleverly combines the update of the reflect beamforming with the adjustment of the transmit beamforming.Simulation results show that the proposed algorithm has good convergence for different numbers of reflection units and can effectively improve the secrecy rate of the system.