The research of improving the secrecy capacity (SC) of wireless communication system using artificial noise (AN) is one of the classic models in the field of physical layer security communication. In this paper, we consider the peak-to-average power ratio (PAPR) problem in this AN-aided model. A power allocation algorithm for AN subspaces is proposed to solve the nonconvex optimization problem of PAPR. This algorithm utilizes a series of convex optimization problems to relax the nonconvex optimization problem in a convex way based on fractional programming, difference of convex (DC) functions programming, and nonconvex quadratic equality constraint relaxation. Furthermore, we also derive the SC of the proposed signal under the condition of the AN-aided model with a finite alphabet and the nonlinear high-power amplifiers (HPAs). Simulation results show that the proposed algorithm reduces the PAPR value of transmit signal to improve the efficiency of HPA compared with benchmark AN-aided secure communication signals in the multiple-input single-output (MISO) model.

中文翻译：

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降低人工噪声辅助安全通信系统PAPR的功率分配

利用人工噪声（AN）提高无线通信系统的保密容量（SC）的研究是物理层安全通信领域的经典模型之一。在本文中，我们考虑了该AN辅助模型中的峰均功率比（PAPR）问题。为了解决PAPR的非凸优化问题，提出了一种AN子空间的功率分配算法。该算法基于分数规划，凸（DC）函数差分编程和非凸二次等式约束松弛，利用一系列凸优化问题以凸的方式松弛非凸优化问题。此外，在具有有限字母和非线性大功率放大器（HPA）的AN辅助模型的条件下，我们还推导了所提出信号的SC。