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Information Communication Technologies Conference (ICTC)

Secure Transmission with Artificial Noise in Distributed Antenna Systems and Achievable Secrecy-Rate Power Optimization

Xiaoyu Wang, Yuanyuan Gao, Xiaochen Liu, Guangna Zhang

Published May 1, 2020• 1 citation
Publisher

Abstract

In this paper, the physical layer security is analyzed in distributed antenna systems (DAS). Firstly, we add artificial noise (AN) to the information bearing signal in order to disturb the passive eavesdropper without degrading the intended receiver's channel. Then, a power allocation (PA) problem maximizing achievable secrecy rate (SR) is formulated and transformed as a convex problem by use of Taylor expansion and am-gm inequality. At last, numerical results verify the effectiveness of the proposed algorithms, and provide a new insight that optimal power allocation from each AP to each user can improve SR by an order of magnitude compared with equal PA proportion to AN.

DOI
10.1109/ictc49638.2020.9123304

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In this paper, the physical layer security is analyzed in distributed antenna systems (DAS). Firstly, we add artificial noise (AN) to the information bearing signal in order to disturb the passive eavesdropper without degrading the intended receiver's channel. Then, a power allocation (PA) problem maximizing achievable secrecy rate (SR) is formulated and transformed as a convex problem by use of Taylor expansion and am-gm inequality. At last, numerical results verify the effectiveness of the proposed algorithms, and provide a new insight that optimal power allocation from each AP to each user can improve SR by an order of magnitude compared with equal PA proportion to AN.
This paper studies the artificial noise (AN) assisted secure transmission for a distributed antenna systems (DAS). To avoid a significant overhead caused by full legitimate channel state information (CSI) acquisition, tracking and collection in the central processor, we propose a distributed AN scheme utilizing the large-scale CSI of the legitimate receiver and eavesdropper. Our objective is to maximize the ergodic secrecy rate (ESR) via optimizing the power allocation between the confidential signal and AN for each remote antenna (RA) under the per-antenna power constraint. Specifically, exploiting random matrix theory, we first establish an analytical expression of the achievable ESR, which leads to a non-convex optimization problem with multiple non-convex constraints in the form of high-order fixed-point equations. To handle the intractable constraints, we recast it into a max-min optimization problem, and propose an iterative block coordinate descent (BCD) algorithm to provide a stationary solution. The BCD algorithm is composed of three subproblems, where the first two subproblems are convex with closed-form solutions, and the last one is a convex-concave game whose saddle-point is located by a tailored barrier algorithm. Simulation results validate the effectiveness of the proposed iterative algorithm and show that our scheme not only reduces the system overhead greatly but also maintains a good secrecy performance.
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.
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.
Wireless communication is particularly susceptible to eavesdropping due to its broadcast nature. Security and privacy issues have become increasingly critical for wireless networks. This paper considers the problem of secret communication in the multiuser downlink eavesdropped by a passive eavesdropper (EVE). The well-known zero-forcing preceding is adopted at the transmitter to produce concurrent data streams to the users, and at the same time an artificial noise (AN) is generated to prevent EVE from intercepting the information. We first derive an analytical closed-form expression for the secrecy sum-rate in the large system limit. We then use it as the objective function to optimize the power allocation (PA) between the information signals and the AN to maximize the secrecy sum-rate. A simple analytical expression of the optimal PA is derived in the high transmit power regime, which proves to be a near-optimal and generic strategy. The large system results are quite accurate for finite-size systems and thus can provide useful insights into system analysis and design. Our analytical and simulation results show that the AN assisted strategy achieves the same multiplexing gain as in the multiuser downlink without eavesdropping. Moreover, more power should be allocated to AN when the system serves fewer users and EVE has more antennas.
At present, there has been a large amount of research on secrecy rate optimization. However, the reliability analysis of secure transmission is equally important although relatively less attention has been dedicated to. Therefore, this paper proposes a secure transmission method with artificial noise for the physical layer security issues in the transmission process of Multiple Input Multiple Output (MIMO) wireless communication systems. Firstly, we establish an artificial noise assisted MIMO systems model. Then, the channel state information (CSI) matrix is subjected to singular value decomposition to obtain the reasonable precoding and artificial noise matrices. Finally, the impact of artificial noise on the bit error rate performance of potential eavesdropper is analyzed, and based on the analysis, the problem of maximizing the system secrecy rate is established. The concave-convex procedure (CCCP) method is used to obtain the optimal power allocation, which significantly improves the security of MIMO systems. The simulation results show that using the null space of CSI matrix and artificial noise for signal encryption effectively improves the bit error rate of potential eavesdropping nodes. In addition, the secrecy rate obtained by the CCCP algorithm is consistent with the performance obtained by the particle swarm optimization algorithm, which verifies the effectiveness of the proposed algorithm.
Utilizing artificial noise (AN) is a good means to guarantee security against eavesdropping in a multi-input multi-output system, where the AN is designed to lie in the null space of the legitimate receiver's channel direction information (CDI). However, imperfect CDI will lead to noise leakage at the legitimate receiver and cause significant loss in the achievable secrecy rate. In this paper, we consider a delayed feedback system, and investigate the impact of delayed CDI on security by using a transmit beamforming and AN scheme. By exploiting the Gauss-Markov fading spectrum to model the feedback delay, we derive a closed-form expression of the upper bound on the secrecy rate loss, where Nt= 2. For a moderate number of antennas where Nt>; 2, two special cases, based on the first-order statistics of the noise leakage and large number theory, are explored to approximate the respective upper bounds. In addition, to maintain a constant signal-to-interference-plus-noise ratio degradation, we analyze the corresponding delay constraint. Furthermore, based on the obtained closed-form expression of the lower bound on the achievable secrecy rate, we investigate an optimal power allocation strategy between the information signal and the AN. The analytical and numerical results obtained based on first-order statistics can be regarded as a good approximation of the capacity that can be achieved at the legitimate receiver with a certain number of antennas, Nt. In addition, for a given delay, we show that optimal power allocation is not sensitive to the number of antennas in a high signal-to-noise ratio regime. The simulation results further indicate that the achievable secrecy rate with optimal power allocation can be improved significantly as compared to that with fixed power allocation. In addition, as the delay increases, the ratio of power allocated to the AN should be decreased to reduce the secrecy rate degradation.