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SCO-AN:Improve Secrecy Capacity for Secure Transmission Using Power Allocation

Yebo Gu, Zhilu Wu, Zhendong Yin, Bowen Huang

Published Mar 16, 2020• 0 citations
Publisher

Abstract

Abstract Artificial noise(AN) is a core technique in physical layer security field which has been widely studied.AN reduces the channel capacity of eavesdroppers without affecting the channel capacity of the communicator so that AN can increase secrecy capacity.Secrecy capacity is defined as channel capacity of the communicator minus channel capacity of eavesdroppers.The AN is prohibited from affecting the channel capacity of the legal receiving channel. This condition brings good performance to AN as well as limitations.Recently, the secrecy capacity optimization artificial noise (SCO-AN) is proposed to increase the secrecy capacity more effectively.SCO-AN can reduce the channel capacity of the communicator to a small extent while greatly reducing the channel capacity of the eavesdropper. So, SCO-AN can further expand the secrecy capacity on the basis of AN. Due to the limitation of transmit power, SCO-AN cannot be added indefinitely, so it is an important issue to increase the secrecy capacity as much as possible under a certain power limit.In this paper, a secrecy capacity function with SCO-AN added under certain power constraints is established.Because this function is non-convex, the traditional convex optimization algorithm cannot be applied. A sequence quadratic program(SQP) is adopted to solve this power allocation problem.Simulation results show that SQP can effectively improve the secrecy capacity under a certain power limit.

DOI
10.21203/rs.3.rs-17295/v1

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IEEE Vehicular Technology Conference•Sep 1, 2019•1 citation
Abstract Artificial noise(AN) is a core technique in physical layer security field which has been widely studied.AN reduces the channel capacity of eavesdroppers without affecting the channel capacity of the communicator so that AN can increase secrecy capacity.Secrecy capacity is defined as channel capacity of the communicator minus channel capacity of eavesdroppers.The AN is prohibited from affecting the channel capacity of the legal receiving channel. This condition brings good performance to AN as well as limitations.Recently, the secrecy capacity optimization artificial noise (SCO-AN) is proposed to increase the secrecy capacity more effectively.SCO-AN can reduce the channel capacity of the communicator to a small extent while greatly reducing the channel capacity of the eavesdropper. So, SCO-AN can further expand the secrecy capacity on the basis of AN. Due to the limitation of transmit power, SCO-AN cannot be added indefinitely, so it is an important issue to increase the secrecy capacity as much as possible under a certain power limit.In this paper, a secrecy capacity function with SCO-AN added under certain power constraints is established.Because this function is non-convex, the traditional convex optimization algorithm cannot be applied. A sequence quadratic program(SQP) is adopted to solve this power allocation problem.Simulation results show that SQP can effectively improve the secrecy capacity under a certain power limit.
In this paper, we consider the physical layer security problem of the wireless communication system. For the multiple-input, multiple-output (MIMO) wireless communication system, secrecy capacity optimization artificial noise (SCO−AN) is introduced and studied. Unlike its traditional counterpart, SCO−AN is an artificial noise located in the range space of the channel state information space and thus results in a significant increase in the secrecy capacity. Due to the limitation of transmission power, making rational use of this power is crucial to effectively increase the secrecy capacity. Hence, in this paper, the objective function of transmission power allocation is constructed. We also consider the imperfect channel estimation in the power allocation problems. In traditional AN research conducted in the past, the expression of the imperfect channel estimation effect was left unknown. Still, the extent to which the channel estimation error impacts the accuracy of secrecy capacity computation is not negligible. We derive the expression of channel estimation error for least square (LS) and minimum mean squared error (MMSE) channel estimation. The objective function for transmission power allocation is non-convex. That is, the traditional gradient method cannot be used to solve this non-convex optimization problem of power allocation. An improved sequence quadratic program (ISQP) is therefore applied to solve this optimization problem. The numerical result shows that the ISQP is better than other algorithms, and the power allocation as derived from ISQP significantly increases secrecy capacity.
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.
The security of wireless information transmission in large‐scale multi‐input and multioutput (MIMO) is the focus of research in wireless communication. Recently, a new artificial noise—SCO‐AN which shows no orthogonality to the channel, is proposed to overcome the shortcomings of traditional artificial noise. In the previous research, the optimization function of SCO‐AN is not convex, and its extremum cannot be obtained. Usually, nonconvex optimization algorithms or iterative relaxation algorithms are used to get the maximum value of the optimization objective function. Nonconvex optimization algorithms or iterative relaxation algorithms are greatly affected by the initial value, and the extremum cannot be obtained by a nonconvex optimization algorithm or iterative relaxation algorithm. In this paper, we creatively apply the strong law of large numbers to obtain the optimal value of the optimization function of SCO‐AN under the condition of large‐scale MIMO: the strong law of large numbers is applied to obtain the ergodic lower bound (ELB) expression of SC for SCO‐AN. The power allocation (PA) problem of the SCO‐AN system is discussed. We use a statistical method to get the formula for calculating the optimal power distribution coefficient of the SCO‐AN system. The transmitter can use the optimal power ratio of PA to distribute the transmitted power without using the PA algorithm. The effect of imperfect channel state information is discussed. Through simulation, we found that more power should be generated for SCO‐AN if the channel estimation is imperfect and the proposed method can achieve better security performance in the large‐scale MIMO system.
We consider the problem of secure communication in wireless fading channels in the presence of non-colluding passive eavesdroppers. The transmitter has multiple antennas and is able to simultaneously transmit an information bearing signal to the intended receiver and artificial noise to the eavesdroppers. We obtain an analytical closed-form lower bound for secrecy capacity, which is used as the objective function to optimize transmit power allocation between the information signal and the artificial noise. Our analytical and numerical results show that equal power allocation is a simple and generic strategy which achieves near optimal capacity performance. We also find that adaptive power allocation based on each channel realization provides no or insignificant capacity improvement over equal power allocation.
In multiple-input multiple-output wireless communication system, artificial noise (AN) is designed to be aligned into the null space of the legitimate channel so that it has no effect on the legitimate channel. Meanwhile, AN will reduce the secrecy capacity of the eavesdropping channel so that AN increase the secrecy capacity of the wireless communication system. Nevertheless, AN technology only pays attention to the CSI of the legitimate channel but does not pay attention to the CSI of the eavesdropping channel so that the secrecy capacity of the system can be further improved. In this paper, we analyze the performance of traditional AN. A secrecy capacity optimization artificial noise for the whole communication system to further improve the system's secrecy capacity is proposed. The secrecy capacity optimization artificial noise is considered as a kind of artificial noise which is disadvantageous to the legitimate receiver but more disadvantageous to the eavesdropper. Furthermore, we further analyzed the technical details of AN technology and found the key factor affecting the secrecy capacity. Meanwhile, the secrecy capacity optimization artificial noise is effectively designed by applying these conclusions and the key factors of secrecy capacity optimization artificial noise affecting the secrecy capacity of the wireless communication system are described. The analysis and simulation results in practical environments show that the proposed method has a good performance on improving the secrecy capacity.
In this paper, we present a secure transmission scheme to improve the secrecy capacity of wiretap systems by blending the benefits of polar code and artificial noise (AN). In the considered system, a transmitter tries to communicate with a receiver without leaking any confidential information to an eavesdropper. We propose a new system utility function, referred to as message secrecy capacity (MSC), which is obtained by integrating the code rate of polar code into the conventional secrecy capacity. Then, in order to maximize the secrecy capacity of the information bits in polar code, we formulate a max-min optimization problem to optimize the powers allocated among useful signals and the AN. To address the highly non-convexity of the considered problem, we propose a concave-convex procedure (CCCP)-based algorithm by introducing some carefully designed auxiliary variables, and convergence to the set of KarushKuhn-Tucker (KKT) solutions is guaranteed. Numerical results demonstrate the effectiveness of the proposed MSC objective function and power allocation scheme.