In PHY-security, high correlation between main and wiretap channels, which are frequently observed, can cause a significant loss of secrecy. Unfortunately, signal processing techniques at the transmitter (Alice), such as precoding and artificial noise (AN) techniques, are ineffective. Under this circumstance, this paper focuses on a slowly fading and reciprocal channel scenario wherein Alice sends a confidential message to an authorised receiver (Bob) with the transmission overheard by a passive unauthorised receiver (Eve), and all of them are equipped with multiple antennas. To prevent interception and ensure secrecy, we redesign a novel scheme of discriminatory channel estimation (DCE), in which training procedures are developed to limit the channel estimation performance at Eve while producing little effect on Alice and Bob. As a result, Eve's ability to obtain the channel information would deteriorate, thereby effectively increase the difference in decoding the message between Bob and Eve. Simulation results demonstrate the proposed scheme could provide substantial gains with respect to secrecy.
In PHY-security, high correlation between main and wiretap channels, which are frequently observed, can cause a significant loss of secrecy. Unfortunately, signal processing techniques at the transmitter (Alice), such as precoding and artificial noise (AN) techniques, are ineffective. Under this circumstance, this paper focuses on a slowly fading and reciprocal channel scenario wherein Alice sends a confidential message to an authorised receiver (Bob) with the transmission overheard by a passive unauthorised receiver (Eve), and all of them are equipped with multiple antennas. To prevent interception and ensure secrecy, we redesign a novel scheme of discriminatory channel estimation (DCE), in which training procedures are developed to limit the channel estimation performance at Eve while producing little effect on Alice and Bob. As a result, Eve's ability to obtain the channel information would deteriorate, thereby effectively increase the difference in decoding the message between Bob and Eve. Simulation results demonstrate the proposed scheme could provide substantial gains with respect to secrecy.
In physical layer security (PHY-security), the frequently observed high correlation between the main and wiretap channels can cause a significant loss of secrecy. This paper investigates a slow fading scenario, where a transmitter (Alice) sends a confidential message to a legitimate receiver (Bob) while a passive eavesdropper (Eve) attempts to decode the message from its received signal. It is assumed that Alice is equipped with multiple antennas while Bob and Eve each have a single antenna (i.e., a MISOSE system). In a MISOSE system, high correlation results in nearly collinear main and wiretap channel vectors, which help Eve to see and intercept confidential information. Unfortunately, the signal processing techniques at Alice, such as beamforming and artificial noise (AN), are helpless, especially in the extreme case of completely collinear main and wiretap channel vectors. On this background, we first investigate the achievable secrecy outage probability via beamforming and AN at Alice with the optimal power allocation between the information-bearing signal and AN. Then, an ingenious model, in which a cooperative jamming relay (Relay) is introduced, is proposed to effectively mitigate the adverse effects of high correlation. Based on the proposed model, the power allocation between the information-bearing signal at Alice and the AN at Relay is also studied to maximize secrecy. Finally, to validate our proposed schemes, numerical simulations are conducted, and the results show that a significant performance gain with respect to secrecy is achieved.
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.
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.
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.
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.
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.