scholarly journals The Secrecy Capacity Optimization Artificial Noise: A New Type of Artificial Noise for Secure Communication in MIMO System

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 58353-58360 ◽  
Author(s):  
Yebo Gu ◽  
Zhilu Wu ◽  
Zhendong Yin ◽  
Xiaojun Zhang
Keyword(s):  
Secure Communication ◽  
Mimo System ◽  
Artificial Noise ◽  
Secrecy Capacity ◽  
Capacity Optimization ◽  
New Type

scholarly journals Secrecy capacity optimization artificial noise: the ergodic secrecy capacity lower bound and optimal power allocation

2020 ◽  
Author(s):  
Yebo Gu ◽  
Zhilu Wu ◽  
Zhendong Yin ◽  
Bowen Huang
Keyword(s):  
Lower Bound ◽  
Channel Estimation ◽  
Closed Form ◽  
Power Allocation ◽  
Estimation Error ◽  
Closed Form Expression ◽  
Artificial Noise ◽  
Secrecy Capacity ◽  
Capacity Optimization ◽  
Form Expression

Abstract The secure transmission problem of MIMO wireless system in fading channels is studied in this paper. We add a secrecy capacity optimization artificial noise(SCO-AN) to the transported signal for improving the security performance of the system. The closed-form expression of secrecy capacity's lower bound is obtained. Base on the closed-form expression of secrecy capacity's lower bound, We optimize the power allocation between the information-bearing signal and the SCO-AN. By calculating, the optimal ratio of power alloation betwenn the information-bearing signal and the SCO-AN is obtained. Through simulation, the results shows the secrecy capacity increases with more receiving antennas and less eavesdropping antennas.And more power should be allocated to the SCO-AN with the increase of the colluding eavedroppers.More over, we study the effect of channel estimation error on power allocation between information-bearing signal and SCO-AN and find that more power should be allocated to decrease eavesdroppers capacity if the channel estimation is not perfect.

scholarly journals Robust Secure Beamforming Design for Cooperative Cognitive Radio Nonorthogonal Multiple Access Networks

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Quanzhong Li ◽  
Sai Zhao
Keyword(s):  
Cognitive Radio ◽  
Secure Communication ◽  
Multiple Access ◽  
Spectrum Efficiency ◽  
Maximization Problem ◽  
Artificial Noise ◽  
Practical Case ◽  
Secrecy Rate ◽  
Worst Case ◽  
Rank One

By the integration of cooperative cognitive radio (CR) and nonorthogonal multiple access (NOMA), cooperative CR NOMA networks can improve the spectrum efficiency of wireless networks significantly. Due to the openness and exposure of wireless signals, secure communication is an important issue for cooperative CR NOMA networks. In this paper, we investigate the physical layer security design for cooperative CR NOMA networks. Our objective is to achieve maximum secrecy rate of the secondary user by designing optimal beamformers and artificial noise covariance matrix at the multiantenna secondary transmitter under the quality-of-service at the primary user and the transmit power constraint at the secondary transmitter. We consider the practical case that the channel state information (CSI) of the eavesdropper is imperfect, and we model the imperfect CSI by the worst-case model. We show that the robust secrecy rate maximization problem can be transformed to a series of semidefinite programmings based on S-procedure and rank-one relaxation. We also propose an effective method to recover the optimal rank-one solution. Simulations are provided to show the effectiveness of our proposed robust secure algorithm with comparison to the nonrobust secure design and traditional orthogonal multiple access schemes.

scholarly journals Artificial-Noise-Aided Energy-Efficient Secure Multibeam Wireless Communication Schemes Based on Frequency Diverse Array

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Jianbang Gao ◽  
Zhaohui Yuan ◽  
Jing Zhou ◽  
Bin Qiu
Keyword(s):  
Wireless Communication ◽  
Projection Matrix ◽  
Artificial Noise ◽  
Power Requirement ◽  
Precoding Matrix ◽  
Bee Colony ◽  
Received Power ◽  
Security Problem ◽  
New Type ◽  
Frequency Offsets

In this paper, we research synthesis scheme for secure wireless communication in multibeam directional modulation (MBDM) system, which consists of multiple legitimate users (LUs) receiving their own individual confidential messages, respectively, and multiple eavesdroppers (Eves) intercepting confidential messages. We propose a new type of array antennas, termed frequency diverse arrays (FDA), to enhance security of confidential messages. Leveraging FDA technology and artificial noise (AN) technology, we aim to address the PHY security problem for MBDM by jointly optimizing the frequency offsets, the precoding matrix and the AN projection matrix. In the first stage, with known locations of Eves, precoding matrix is designed to minimize Eve’s receiving power of confidential message (Min-ERP), while satisfying power requirement of LUs. And then artificial-noise projection matrix (ANPM) is calculated to enhance AN impact on Eves without influencing LUs. Furthermore, we research a more practical scenario, where locations of Eves are unknown. Unlike the scenario of the known locations of Eves, precoding matrix is designed to maximize AN transmit power (Max-ATP), while satisfying each LU’s requirement received power of confidential message. In the second stage, we analyze and further optimize secrecy capacity. The problem is solved by optimizing frequency offsets through modified artificial bee colony (M-ABC) algorithm. Numerical results show that the proposed scheme can achieve a secure transmission in MBDM system.

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

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Tao Hong ◽  
Geng-xin Zhang
Keyword(s):  
Power Allocation ◽  
Nonconvex Optimization ◽  
Communication System ◽  
Secure Communication ◽  
Optimization Problem ◽  
Optimization Problems ◽  
Average Power ◽  
Finite Alphabet ◽  
Artificial Noise ◽  
Communication Signals

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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