Power Allocation for Reducing PAPR of Artificial-Noise-Aided Secure Communication System

Power Allocation for Reducing PAPR of Artificial-Noise-Aided Secure Communication System
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降低人工噪声辅助安全通信系统PAPR的功率分配

DOI:
10.1155/2020/6203079
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发表时间:
2020-07
影响因子:
--
通讯作者:
Zhang Geng-xin
Zhang Geng-xin
中科院分区:
计算机科学4区
文献类型:
--
作者:
Hong Tao;Zhang Geng-xin

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利用人工噪声提高无线通信系统保密能力的研究是物理层安全通信领域的经典模型之一。在本文中,我们考虑的峰均功率比(PAPR)的问题,在这个AN辅助模型。针对峰均功率比的非凸优化问题,提出了一种基于AN子空间的功率分配算法。该算法利用一系列凸优化问题,基于分式规划、凸函数差分规划和非凸二次等式约束松弛,以凸的方式松弛非凸优化问题。此外,我们还在有限字母表的AN辅助模型和非线性高功率放大器(HPA)的条件下推导了该信号的SC。仿真结果表明,在多输入单输出(MISO)模型下,与标准的人工神经网络辅助保密通信信号相比,该算法降低了发射信号的峰均比,提高了HPA的效率。
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.
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