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

Yebo Gu, Zhilu Wu, Zhendong Yin, Bowen Huang

Published Jul 27, 2020• 0 citations
Publisher

Abstract

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.

DOI
10.21203/rs.3.rs-46160/v1

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IEEE Signal Processing Letters•Jul 31, 2013•30 citations
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.
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 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.
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.
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.
We consider the problem of secure communication with multiantenna transmission in fading channels. The transmitter simultaneously transmits an information-bearing signal to the intended receiver and artificial noise to the eavesdroppers. We obtain an analytical closed-form expression of an achievable secrecy rate and use it as the objective function to optimize the transmit power allocation between the information signal and the artificial noise. Our analytical and numerical results show that equal power allocation is a simple yet near-optimal strategy for the case of noncolluding eavesdroppers. When the number of colluding eavesdroppers increases, more power should be used to generate the artificial noise. We also provide an upper bound on the SNR, above which, the achievable secrecy rate is positive and shows that the bound is tight at low SNR. Furthermore, we consider the impact of imperfect channel state information (CSI) at both the transmitter and the receiver and find that it is wise to create more artificial noise to confuse the eavesdroppers than to increase the signal strength for the intended receiver if the CSI is not accurately obtained.
In wireless communication, the transmitter (Alice) can send artificial noise (AN) to interfere with the eavesdropper (Eve). This letter considers the AN MIMO scenario, i.e., both Alice and the legitimate receiver (Bob) are equipped with multiple antennas. A closed-form expression for the lower bound of secrecy capacity is obtained. It is proved that water-filling is the optimal power allocation scheme. An efficient iterative algorithm is proposed to find the optimal power distribution ratio between information and AN so that maximum secrecy capacity can be achieved. Simulation results show that the proposed algorithm converges fast, and multiple antennas can improve the secrecy capacity to some extent compared to the AN MISO case.