IRS辅助全双工NOMA-WPCN系统的高能效优化方法

he combination of intelligent reflective surface (IRS), non-orthogonal multiple access (NOMA), and wireless-powered communication network (WPCN) can significantly improve the spectral efficiency and energy efficiency of communication networks. In this paper, we study the energy efficiency maximization problem of the IRS-assisted full-duplex NOMA-WPCN system by jointly optimizing the user transmit power, energy beam matrix, and IRS phase shift to achieve the maximum total energy efficiency under the conditions of satisfying the minimum rate requirement, the energy station transmits power constraints, the IRS phase shift constraints, and the user transmit power limitations. The non-convex fractional structural properties of the problem and the high degree of coupling of the optimization variables make the problem difficult to solve. Therefore, in this paper, we first use Dinkelbach\'s algorithm to transform and reconstruct the objective function, and then propose an alternating iteration algorithm based on sub-problem decomposition, which decomposes the optimization problem into two sub-problems of power allocation and phase-shift optimization and solves them alternately. Simulation analysis shows that the scheme proposed in this paper can significantly improve the system\'s energy efficiency performance.