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CRC Press eBooks

Discriminatory Channel Estimation for Secure Wireless Communication

Xiangyun Zhou, Lingyang Song, Yan Zhang

Published Nov 7, 2013• 1 citation
Publisher

Abstract

Through a review of the so-called discriminatory channel estimation (DCE) scheme [1,2], this chapter introduces a way to enhance physical layer secrecy from a channel estimation perspective. The DCE scheme is a novel training scheme that is aimed at providing discrimination between the channel estimation performances at a legitimate receiver (LR) and an unauthorized receiver (UR). This effectively enlarges the difference between the signalto-noise ratios (SNRs) at the two receivers and leaves more room for secrecy coding or transmission schemes in the data transmission phase. A key feature of DCE designs is the insertion of artificial noise (AN) in the training signal to degrade the channel estimation performance at UR. To do so, AN must be placed in a carefully chosen subspace to minimize its effect on LR. However, this requires preliminary knowledge of the channel at the transmitter, which can be difficult to achieve without benefiting the channel estimation at UR as well. To achieve this task, two DCE schemes were proposed in the literature, namely, the feedback-and-retraining [1] and the two-way training [2] based DCE schemes. Both of these schemes require a preliminary training stage to provide the transmitter with a rough estimate of LR’s channel and an AN-assisted training stage to enable channel estimation at LR while degrading channel estimation at UR. These schemes as well as methods to optimally allocate power among pilot signals and AN are reviewed in this chapter.

DOI
10.1201/b15496-11

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International Conference on Wireless Communications and Signal Processing (WCSP)•Oct 1, 2019•2 citations
Through a review of the so-called discriminatory channel estimation (DCE) scheme [1,2], this chapter introduces a way to enhance physical layer secrecy from a channel estimation perspective. The DCE scheme is a novel training scheme that is aimed at providing discrimination between the channel estimation performances at a legitimate receiver (LR) and an unauthorized receiver (UR). This effectively enlarges the difference between the signalto-noise ratios (SNRs) at the two receivers and leaves more room for secrecy coding or transmission schemes in the data transmission phase. A key feature of DCE designs is the insertion of artificial noise (AN) in the training signal to degrade the channel estimation performance at UR. To do so, AN must be placed in a carefully chosen subspace to minimize its effect on LR. However, this requires preliminary knowledge of the channel at the transmitter, which can be difficult to achieve without benefiting the channel estimation at UR as well. To achieve this task, two DCE schemes were proposed in the literature, namely, the feedback-and-retraining [1] and the two-way training [2] based DCE schemes. Both of these schemes require a preliminary training stage to provide the transmitter with a rough estimate of LR’s channel and an AN-assisted training stage to enable channel estimation at LR while degrading channel estimation at UR. These schemes as well as methods to optimally allocate power among pilot signals and AN are reviewed in this chapter.
This work examines the use of two-way training to efficiently discriminate the channel estimation performances at a legitimate receiver (LR) and an unauthorized receiver (UR) in a multiple-input multiple-output (MIMO) wireless system. This work improves upon the original discriminatory channel estimation (DCE) scheme proposed by Chang where multiple stages of feedback and retraining were used. While most studies on physical layer secrecy are under the information-theoretic framework and focus directly on the data transmission phase, studies on DCE focus on the training phase and aim to provide a practical signal processing technique to discriminate between the channel estimation performances (and, thus, the effective received signal qualities) at LR and UR. A key feature of DCE designs is the insertion of artificial noise (AN) in the training signal to degrade the channel estimation performance at UR. To do so, AN must be placed in a carefully chosen subspace, based on the transmitter's knowledge of LR's channel, in order to minimize its effect on LR. In this paper, we adopt the idea of two-way training that allows both the transmitter and LR to send training signals to facilitate channel estimation at both ends. Both reciprocal and nonreciprocal channels are considered and a two-way DCE scheme is proposed for each scenario. For mathematical tractability, we assume that all terminals employ the linear minimum mean square error criterion for channel estimation. Based on the mean square error (MSE) of the channel estimates at all terminals, we formulate and solve an optimization problem where the optimal power allocation between the training signal and AN is found by minimizing the MSE of LR's channel estimate subject to a constraint on the MSE achievable at UR. Numerical results show that the proposed DCE schemes can effectively discriminate between the channel estimation and, hence, the data detection performances at LR and UR.
Wireless communication is highly susceptible to eavesdropping attacks where a malicious user can exploit the broadcast nature of the wireless signals to eavesdrop on confidential information. At the physical layer, there are multiple possible avenues to utilize the inherent randomness of the wireless transmission medium to achieve secure communication. One of the lucrative possibilities is to use the channel state information (CSI) to establish a secure communication link because it is vital in decoding the received signal at the transmitter. This technique is commonly referred to as discriminatory channel estimation (DCE) where the channel estimation performance is intentionally degraded at the eavesdropper as compared to the legitimate nodes to achieve secure communication.In this thesis, we capitalize on full-duplex (FD) transmissions to transmit the pilot signals to obscure the channel estimates from the eavesdropper. FD transmission severely limits the estimation performance at the eavesdropper while the legitimate nodes can acquire robust estimates. The secrecy of channel estimates from the eavesdropper provides a bandwidth-efficient security technique as the channel estimation requires less bandwidth than the data transmission. We have presented the achievable secrecy capacity analysis along with the simulation analysis to illustrate the performance improvements achieved by the proposed novel secure channel estimation. In this thesis, we also study the impact of artificial noise (AN) to improve the secrecy achieved by the use of FD transmission of pilot signals. For a strategically located eavesdropper, we have presented novel DCE techniques where AN signals are transmitted along with pilot signals using FD transmission. The AN signals confuse the nearby eavesdropper to establish a secure and robust communication link. We have also presented novel local adaptive power allocation algorithms, where each legitimate node performs power allocation in the absence of statistical channel characteristics regarding the eavesdropping channel. We have provided an in-depth simulation analysis including a location-based simulation analysis to illustrate that the secrecy performance achieved by the proposed DCE techniques. The simulation results indicate that the proposed DCE techniques achieve robust secure communication against a strategically located eavesdropper: while the other DCE techniques are unable to avoid the leakage of information to the eavesdropper
The two-way training discriminatory channel estimation (DCE) for non-reciprocal wireless MIMO channels can efficiently differentiate the performance at the legitimate receiver (Bob) and the eavesdropper (Eve). Eve's channel estimation performance is deliberately degraded by the artificial noise (AN) inserted into the training sequence. However, it ignores the possibility that Eve can derive any useful information which can be used to reduce the AN interference during the round-trip stage. In this paper, we discuss the feasibility that Eve can derive certain helpful information from its observations during the two-way training DCE. Then, we propose a pseudo downlink channel (PDC) scheme for Eve to improve its channel estimation performance, which collapses the security of legitimate receiver.
Discriminatory channel estimation (DCE) based on two-way training can effectively enhance physical layer security in multiple-input multiple-output (MIMO) systems. In this paper, considering an active eavesdropping scenario where the eavesdropper (Eve) can adaptively switch between passive eavesdropping, and active jamming modes, we propose a new DCE-based secure transmission scheme with cooperative jamming, and artificial noise (AN) insertion in massive MIMO decode-and-forward (DF) relay systems. To characterize the performance of the proposed scheme, firstly, the closed-form expressions for normalized mean squared error (NMSE) of legitimate channels, and wiretap channels are derived. Then, according to the NMSE obtained during channel estimation phase, we design different secure transmission schemes, and derive the approximative expressions of average security rate with respect to the behavior of active Eve, including malicious jamming, and passive eavesdropping, respectively. Finally, the power allocation at source, and relay is jointly optimized to minimize the average signal to interference plus noise ratio (SINR) at the Eve while ensuring that of the legitimate receivers to be large than a threshold for the quality-of-service (QoS) requirement. Numerical results show that the proposed DCE-based secure transmission scheme can effectively discriminate the CSI between legitimate receivers, and Eve even in the presence of an active Eve, and therefore achieve a better security performance than that without DCE.
This paper proposes full-duplex transmissions from legitimate nodes to achieve channel estimation performance deterioration at an eavesdropper as compared to the legitimate receiver. The proposed discriminatory channel estimation (DCE) technique comprises of two stages where, in the first stage, the self-interference channel is estimated by the respective legitimate nodes. Followed by in-band full-duplex transmission from both legitimate nodes for channel estimation at legitimate nodes, while providing equivocation at the eavesdropper due to the superposition of two signals. The discrimination of channel estimation performance provides secrecy against the passive eavesdropper while delivering information to the legitimate receiver. We provide the mean square error (MSE) to indicate the performance achieved by linear minimum mean square error (LMMSE) estimators. We have also provided bit error rate (BER), and secrecy capacity analysis to indicate the performance of secure communication achieved by securing the channel estimates from the eavesdropper. The BER analysis shows that for proposed DCE, BER at the eavesdropper is close to 0.1 while the legitimate node is able to robustly decode the information. Finally, simulation results show that the proposed DCE outperforms existing DCE techniques for the considered scenario.
In this paper, we propose a new discriminatory channel estimation (DCE) scheme to combat active eavesdropping in multiple-input multiple-output (MIMO) decode-and-forward (DF) relay systems. In particular, through cooperative jamming (CJ) and artificial noise (AN) insertion, the discrimination between channel state information (CSI) at the active eavesdropper (Eve) and legitimate users (LUs) can be well ensured. To characterize the performance of the proposed DCE scheme, the closed-form expressions of normalized mean squared error (NMSE) of estimation for both legitimate channel and wiretap channel have been derived. In addition, the power allocation between pilot and AN during channel estimation phase is optimized to further enlarge the CSI discrimination. Simulation results validate the effectiveness of the proposed scheme to achieve a higher secrecy performance, even with an active Eve.