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arXiv:1511.01791 · IEEE Transactions on Information Forensics and Security

On the Role of Artificial Noise in Training and Data Transmission for Secret Communications

Ta-Yuan Liu, Shih‐Chun Lin, Y.-W. Peter Hong

Published Oct 21, 2016• 29 citations
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Abstract

This paper considers the joint design of training and data transmission in physical-layer secret communications, and examines the role of artificial noise (AN) in both of these phases. In particular, AN in the training phase is used to prevent the eavesdropper from obtaining accurate channel state information (CSI), whereas AN in the data transmission phase can be used to mask the transmission of confidential messages. By considering AN-assisted training and secrecy beamforming, we first derive bounds on the achievable secrecy rate and utilize them to obtain approximate secrecy rate expressions that are asymptotically tight at high SNR. By maximizing these expressions, power allocation policies between signal and AN in both training and data transmission phases are then proposed for conventional and AN-assisted training-based schemes, respectively. We show that the optimal AN power at high SNR should be non-vanishing with respect to the total power, and that AN usage can be more effective in the training phase than in the data transmission phase when the coherence time is large. However, at low SNR, we show that AN cannot be effectively utilized due to the lack of accurate CSI, and thus, one can often do better without. Numerical results are presented to verify our theoretical claims.

DOI
10.1109/tifs.2016.2620281

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This paper considers the joint design of training and data transmission in physical-layer secret communications, and examines the role of artificial noise (AN) in both of these phases. In particular, AN in the training phase is used to prevent the eavesdropper from obtaining accurate channel state information (CSI), whereas AN in the data transmission phase can be used to mask the transmission of confidential messages. By considering AN-assisted training and secrecy beamforming, we first derive bounds on the achievable secrecy rate and utilize them to obtain approximate secrecy rate expressions that are asymptotically tight at high SNR. By maximizing these expressions, power allocation policies between signal and AN in both training and data transmission phases are then proposed for conventional and AN-assisted training-based schemes, respectively. We show that the optimal AN power at high SNR should be non-vanishing with respect to the total power, and that AN usage can be more effective in the training phase than in the data transmission phase when the coherence time is large. However, at low SNR, we show that AN cannot be effectively utilized due to the lack of accurate CSI, and thus, one can often do better without. Numerical results are presented to verify our theoretical claims.
In this paper, we consider the joint design of training and data transmission signals for wiretap channels where the transmitter is to send a secrect massage to the receiver without being intercepted by the eavesdropper. The celebrated secrecy beamforming scheme, which may or may not be assisted by artificial-noise (AN), is adopted in the data transmission phase to achieve this task. The achievable secrecy rate for practical systems with channel estimation error is first derived. Based on the achievable secrecy rate, we find the optimal tradeoff between the energy used for training and data signals. The optimal solutions in the low and high energy regimes are characterized analytically. We show that AN does not provide any advantages in the low energy regime, while it may have significant impact in the high energy regime. Numerical results are presented to verify our theoretical claims.
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.
Secure communication with noisy feedback is studied in this correspondence. Unlike the majority of previous research efforts where the eavesdropper's channel state information (CSI)-either instantaneous or statistical CSI, is known by the legitimate users, a joint feedback and artificial noise scheme without any eavesdropper's CSI is proposed. The proposed scheme lets the source and the legitimate destination alternatively transmit private messages and degrade the eavesdropper's channel quality in all transmission phases. An insightful discovery is that if the transmit power is lager than a certain threshold, a positive secrecy capacity can be achieved, which overcomes the problem that the secrecy cannot be achieved when the legitimate user's CSI is worse than the eavesdropper's. The secrecy capacity maximization problem is investigated by adaptive power allocation for the private signals and the artificial noise where a near optimal solution of the power of artificial noise is obtained under the high SNR situation. Finally, the numerical results verify the theoretical analysis and illustrate the secrecy performance of the proposed scheme.
For physical-layer security with multiple antennas, artificial noise (AN) aided secure beamforming scheme is considered. An ergodic secrecy rate considering a channel-feedback mechanism and channel estimation is derived. In this formula, two power-splitting factors in the training and data parts (one is between a training signal and AN, and the other between an information signal and AN) are included. In a high signal-to-noise ratio region, the power-splitting factors, which maximize the approximated ergodic secrecy rate, are derived. An alternative optimization process is proposed to obtain the convergent solutions. The asymptotic characteristics of the secrecy rate and power-splitting factors are analyzed.
This paper proposes a framework for the artificial noise assisted secure transmission in multiple-input, multiple-output, multiple antenna eavesdropper (MIMOME) wiretap channels in frequency-division duplexed (FDD) systems. We focus on a practical scenario that only the eavesdroppers' channel distribution information (CDI) is available and the imperfect channel state information (CSI) of the legitimate receiver is acquired through training and analog feedback. By taking explicitly into account the signaling overhead and training power overhead incurred by channel estimation and feedback, we define the achievable effective ergodic secrecy rate (ESR), and investigate a joint power allocation and training overhead optimization problem for the maximization of effective ESR. We first derive a deterministic approximation for the achievable effective ESR which facilitates the joint optimization. Then, efficient iterative algorithms are proposed to solve the considered nonconvex optimization problem. In particular, in the high-SNR regime, a block coordinate descent method (BCDM) is proposed to handle the joint optimization. In the low-SNR regime, we transform the problem into a sequence of geometric programmings (GPs) and locate its Karush-Kuhn-Tucker (KKT) solution using the successive convex approximation (SCA) method. For the general case of SNR, we maximize the lower bound of the achievable effective ESR. Simulation results corroborate the theoretical analysis and illustrate the secrecy performance of the proposed secure transmission scheme.
This paper considers a massive MIMO network that includes one multiple-antenna base station, one multiple-antenna eavesdropper, and K single-antenna users. The eavesdropper operates in passive mode and tries to overhear the confidential information from one of the users in the down-link transmission. In order to secure the confidential information, two artificial noise (AN)-aiding schemes are proposed. In the first scheme, AN is injected into the downlink training signals to prevent the eavesdropper from obtaining the correct channel state information of the eavesdropping link. In the second scheme, AN is deployed in both downlink training phase and payload data transmission phase to further degrade the eavesdropping channel. Analytical expressions and tight approximations of the achievable secrecy rate of the considered systems are derived with taking imperfect channel estimation and two types of precoding, i.e., maximum-ratio-transmission and zero-forcing, into consideration. Optimization algorithms for power allocation are proposed to enhance the secrecy performance of the proposed AN-aiding schemes. The results reveal that deploying AN in the downlink training phase of massive MIMO networks does not affect the downlink channel estimation process at users while enabling the system to suppress the downlink channel estimation process at eavesdropper. As a consequence, the proposed AN-aided schemes improve the system performance significantly. Furthermore, implementing AN in both phases allows the considered system having a flexible solution to maximize its secrecy performance at the price of higher complexity.