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IEEE Vehicular Technology Conference

Power Allocation for AN-Aided Beamforming Design in MISO Wiretap Channels with Finite-Alphabet Signaling

Xiaoran Liu, Dongtang Ma, Jun Xiong, Wei Li, Longwang Cheng

Published Sep 1, 2016• 2 citations
Publisher

Abstract

In this paper, we address physical layer security in multiple-input single-output (MISO) wiretap channels in the presence of a passive eavesdropper. Artificial noise (AN) is used to provide masked beamforming for degrading the eavesdropper's channel. Existing works based on Gaussian input assumption may lead to substantial secrecy rate loss when considering practical finite-alphabet input. In order to maximize ergodic secrecy rate, a power allocation scheme between the information-bearing signal and AN is proposed. Despite the fact that there is no closed- form expression of mutual information under the constraint of finite-alphabet input, we exploit the relationship between mutual information and minimum mean square error (MMSE) to transform the original problem into a zero-searching problem, which can be solved via gradient search algorithm. Numerical simulations demonstrate that the proposed scheme offers a very good approximation to the optimal performance.

DOI
10.1109/vtcfall.2016.7881170

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arXiv:1907.01064•Jun 28, 2019•4 citations
In this paper, we address physical layer security in multiple-input single-output (MISO) wiretap channels in the presence of a passive eavesdropper. Artificial noise (AN) is used to provide masked beamforming for degrading the eavesdropper's channel. Existing works based on Gaussian input assumption may lead to substantial secrecy rate loss when considering practical finite-alphabet input. In order to maximize ergodic secrecy rate, a power allocation scheme between the information-bearing signal and AN is proposed. Despite the fact that there is no closed- form expression of mutual information under the constraint of finite-alphabet input, we exploit the relationship between mutual information and minimum mean square error (MMSE) to transform the original problem into a zero-searching problem, which can be solved via gradient search algorithm. Numerical simulations demonstrate that the proposed scheme offers a very good approximation to the optimal performance.
The problem of optimal power allocation between the information-bearing signal and the artificial noise (AN) signal is addressed in this letter to enhance the physical layer security of the multiple-input-single-output wiretap channel. Differing from the existing works concerning the secrecy rate maximization, this letter studies the problem of minimizing the secrecy outage probability given the secrecy rate, where the channel state information concerning the eavesdropper is modeled as quasi-static Rayleigh fading and only known statistically. After formulating the problem as an optimization problem of power allocation, we prove that the optimal solution can be conveniently obtained by using the method of bi-section search. Simulation results show that the proposed power allocation method is efficient and can enhance the physical layer security by reducing the secrecy outage probability.
In this letter, we aim to achieve secure communication for a multiple-input single-output (MISO) wiretap channel in the presence of multiple non-colluding eavesdroppers. It is assumed that the eavesdroppers' channels are unavailable to the transmitter, and artificial noise (AN) is used to provide masked beamforming for degrading the eavesdroppers' channels. First, we derive the secrecy rate outage probability for the masked beamforming system and then the optimal power allocation between data and AN is obtained in closed form for minimizing the secrecy rate outage probability under a total power constraint. The effects of the number of transmit antennas, the transmit power, and the target secrecy rate on the optimal power allocation parameter are characterized. Numerical results are presented to show the performance of our proposed power allocation scheme.
An artificial-noise (AN)-aided beamformer for reducing secrecy loss due to the correlation between the main and wiretap channels is designed in this letter. We consider slow-fading multiple-input-single-output wiretap channels with a passive single-antenna eavesdropper, where the source has accurate main channel information and statistical wiretap channel information. By exploiting the channel correlation, the power of the AN in the null space of the main channel can be placed more reasonably instead of using a simple uniform distribution. Then, an efficient algorithm for power allocation between the information-bearing signal and the AN is developed. The simulation results show that the secrecy rate under the transmit power and secrecy outage constraint is improved.
The secrecy rate maximization with the artificial noise (AN) aided beamforming for the multipel-input-single-output (MISO) wiretap channel is addressed in this paper under the constraint of secrecy outage probability. The channel state information (CSI) of the main channel is assumed to be perfectly known while the CSI of the eavesdropper is modeled as a complex Gaussian random vector. The generalized AN scheme where the AN is not constrained to be orthogonal to the information-bearing signal is considered. The complete solution to the maximum achievable secrecy rate and the corresponding optimal power allocation between the information-bearing signal and the AN is obtained without making any approximation of the secrecy outage probability constraint. The result shows that the optimal AN is always orthogonal to the information-bearing signal.
We consider precoder and artificial noise (AN) design for multi-antenna wiretap channels under the finite-alphabet input assumption. We assume that the transmitter has access to the channel coefficients of the legitimate receiver and knows the statistics of the eavesdropper's channel. Accordingly, we propose a secrecy rate maximization algorithm using a gradient descent-based optimization of the precoder matrix and an exhaustive search over the power levels allocated to the AN. We also propose algorithms to reduce the complexities of direct ergodic secrecy rate maximization by: 1) maximizing a cut-off rate-based approximation for the ergodic secrecy rate, simplifying the mutual information expression, which lacks a closed-form and 2) diagonalizing the channels toward the legitimate receiver and the eavesdropper, which allows for employing a per-group precoding-based technique. Our numerical results reveal that jointly optimizing the precoder and the AN outperforms the existing solutions in the literature, which rely on the precoder optimization only. We also demonstrate that the proposed low complexity alternatives result in a small loss in performance while offering a significant reduction in computational complexity.
An artificial-noise (AN)-aided beamformer specific to correlated main and wiretap channels is designed in this paper. We consider slow-fading multiple-input-single-output (MISO) wiretap channels with a passive single-antenna eavesdropper, in which independent transmitter-side and correlated receiver-side are assumed. Additionally, the source has accurate main channel information and statistical wiretap channel information. To reduce the secrecy loss due to receiver-side correlation, this paper proposes the scheme of channel-correlation-enabled transmit optimization. Particularly, the correlation is viewed as a resource to acquire more knowledge about wiretap channel. Based on this, the statistical distribution of wiretap channel is described more precisely. Then, the power of AN in the null space of main channel is placed more reasonably instead of simple uniform distribution and an elaborate beamformer for the information-bearing signal is designed. Finally, an efficient algorithm for power allocation between the information-bearing signal and the AN is developed. Simulation results show that the secrecy rate under transmit power and secrecy outage constraint is improved.