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IEEE Transactions on Information Forensics and Security

In-Band Full-Duplex Discriminatory Channel Estimation Using MMSE

Fawad Ud Din, Fabrice Labeau

Published Jan 1, 2020• 8 citations
Publisher

Abstract

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.

DOI
10.1109/tifs.2020.2986885

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International Conference on Wireless Communications and Signal Processing (WCSP)•Oct 1, 2019•2 citations
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.
This paper proposes a novel secure channel estimation technique to provide security against leakage of the channel estimates to any malicious user by utilizing artificial noise (AN) along with full-duplex (FD) transmissions. AN overcomes the drawback of FD transmission, where any strategically located eavesdropper can minimize the interference signal received from the FD receiver. The proposed secure channel estimation technique comprises three stages, where the first stage is responsible for the estimation of the residual self-interference (SI) channel. The second stage acquires rough channel estimates to design AN orthogonal to the channel between legitimate transmitter-receiver for the next training stage. In the third stage, both legitimate nodes transmit orthogonal AN signals along with the known training signals using FD transmissions. For power allocation, we have presented a novel local adaptive power allocation algorithm at each legitimate node to allocate the powers to the training signals, and AN signals while ensuring equivocation at the eavesdropper. We provide the mean square error (MSE) to indicate the performance achieved by the respective nodes. We have also provided the bit error rate (BER) simulation analysis to indicate the secure communication achieved by securing the channel estimation process. The presented simulation analysis indicates that the eavesdropper is unable to decode the transmitted information while the legitimate receiver has robustly decoded the transmitted information.
The random nature of wireless channel can be utilized to achieve secure communications. Recently, there have been some contributions towards finding practical approaches to provide physical layer security, but robust and secure channel estimates are critical in achieving secrecy. In this paper, we propose that in-band full-duplex communication can be utilized by the legitimate transceiver pair to mask the channel estimates from the eavesdropper. The proposed secure channel estimation technique comprises of two stages. In the first stage, the self- interference channel is estimated by respective nodes. In the second stage, in-band full-duplex transmission from both legitimate nodes is utilized to achieve channel estimates at legitimate nodes while providing equivocation at the eavesdropper. The performance analysis shows that the proposed scheme provides robust channel estimation at the legitimate nodes while maintaining equivocation at the eavesdropper.
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
This paper studies the secrecy coding analysis achieved by the self-jamming technique in the presence of an eavesdropper by considering a short-packet Full-Duplex (FD) transmission developed based on iterative blind or semi-blind channel estimation and advanced decoding algorithms. Indeed, the legitimate receiver and eavesdropper can simultaneously receive the intended signal from the transmitter and broadcast a self-jamming or jamming signal to the others. Unlike other conventional techniques without feedback, the blind or semi-blind algorithm applied at the legitimate receiver can simultaneously estimate, firstly, the Self-Interference (SI) channel to cancel the SI component and, secondly, estimate the propagation channel, then decode the intended messages by using 5G Quasi-Cyclic Low-Density Parity Check (QC-LDPC) codes. Taking into account the passive eavesdropper case, the blind channel estimation with a feedback scheme is applied, where the temporary estimation of the intended channel and the decoded message are fed back to improve both the channel estimation and the decoding processes. Only the blind algorithm needs to be implemented in the case of a passive eavesdropper because it achieves sufficient performances and does not require adding pilot symbols as the semi-blind algorithm. In the case of an active eavesdropper, based on its robustness in the low region of the Signal-to-Noise Ratio (SNR), the semi-blind algorithm is considered by trading four pilot symbols and only requiring the feedback for channel estimation processes in order to overcome the increase in noise in the legitimate receiver. The results show that the blind or semi-blind algorithms outperform the conventional algorithm in terms of Mean Square Error (MSE), Bit Error Rate (BER) and security gap (Sg). In addition, it has been shown that the blind or semi-blind algorithms are less sensitive to high SI and self-jamming interference power levels imposed by secured FD transmission than the conventional algorithms without feedback.
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.
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.