Abstract
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.
Highlights
With the rapid development of wireless communication technology, an ever-increasing amount of sensitive data is transmitted over wireless networks
For the practical multiantenna system, the power allocation (PA) is the same for each antenna. erefore, we focus on reducing the peak value of the transmit signal in artificial noise (AN)-aided secure communication system. e most aforementioned papers about the PA were mainly focused on the PA parameter α to optimize the secrecy capacity (SC) of this AN-aided method, such as [11] for Gaussian input and [47] for finitealphabet input
When transmit antenna number NA equals 64, the peak-to-average power ratio (PAPR) value is greater than 10.5 dB with the probability of 10− 4, which is similar to the performance of traditional OFDM signal with 64 subcarriers and BPSK modulation [57]
Summary
With the rapid development of wireless communication technology, an ever-increasing amount of sensitive data (e.g., private information and commercially confidential data) is transmitted over wireless networks. In [44], the researchers showed that the famous ANbased technique proposed by Nagi and Goel [10] creates high PAPR in the antenna domain for a multiple-input single-output (MISO) model due to the accidental in-phase addition (superposition) of AN subspaces and the signal subspace compared with traditional OFDM signal in the time domain. To solve this problem, an angle rotation based technique was proposed to reduce the PAPR, while maintaining the SC performance as that of the original AN-aided method. Given a matrix Z, ZT and Z† denote the transpose and conjugate transpose of Z. e L × L identity matrix is referred to as IL and Eh[·] denotes expectation of a random variable h
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