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IEEE Global Conference on Signal and Information Processing

A minorization-maximization algorithm for an-based mimome secrecy rate maximization

Mudassir Masood, Ali Ghrayeb, Prabhu Babu, Issa M. Khalil, Mazen O. Hasna

Published Dec 1, 2016• 2 citations
Publisher

Abstract

We consider the problem of secrecy rate maximization in a multi-input multi-output multi-eavesdropper (MIMOME) wiretap channel and present an exact solution. A general system model with a multi-antenna eavesdropper and a multi-antenna full-duplex receiver is considered. In particular, we perform joint beamforming and artificial noise optimization in an effort to maximize the achievable secrecy rate. The optimization is performed in the presence of artificial noise generated by both transmitter and legitimate receiver. The resulting optimization problem is non-convex and difficult to solve. We develop a minorization-maximization algorithm to solve the problem. It is iterative in nature and guaranteed to converge to a locally optimal solution. The results can therefore be used to benchmark existing methods. Numerical results are presented to demonstrate the efficacy of the proposed approach.

DOI
10.1109/globalsip.2016.7905987

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We consider the problem of secrecy rate maximization in a multi-input multi-output multi-eavesdropper (MIMOME) wiretap channel and present an exact solution. A general system model with a multi-antenna eavesdropper and a multi-antenna full-duplex receiver is considered. In particular, we perform joint beamforming and artificial noise optimization in an effort to maximize the achievable secrecy rate. The optimization is performed in the presence of artificial noise generated by both transmitter and legitimate receiver. The resulting optimization problem is non-convex and difficult to solve. We develop a minorization-maximization algorithm to solve the problem. It is iterative in nature and guaranteed to converge to a locally optimal solution. The results can therefore be used to benchmark existing methods. Numerical results are presented to demonstrate the efficacy of the proposed approach.
We consider physical layer security in a multi-input multi-output multi-eavesdropper wiretap channel and present an exact solution to the problem of secrecy rate maximization. A system model with multiple multi-antenna eavesdroppers and multiple multi-antenna full-duplex receivers is considered, which is general enough such that models existing in the literature may be considered as special cases. In particular, we perform joint beamforming and artificial noise optimization in an effort to maximize the achievable secrecy rate. The optimization is performed in the presence of artificial noise generated by both transmitter and legitimate receivers. The resulting optimization problem is non-convex and difficult to solve. We develop a minorization-maximization algorithm to solve the problem exactly and the results can therefore be used to benchmark existing methods. Numerical results are presented to demonstrate the efficacy of the proposed approach.
In this paper, we study the energy-efficient secrecy precoding problem for a general multiple-input multiple-output multiple-eavesdropper (MIMOME) wiretap channel. The system model considered here consists of a common transmitter, a legitimate receiver, and multiple eavesdroppers, all mounted with multiple antennas. In order to improve the energy efficiency (EE) performance of the proposed system, an artificial noise (AN)-aided precoding scheme is adopted. Because the formulated EE maximization problem is of huge nonconvex complexity, we solve it by employing a two-tier optimization structure. Although the outer-tier optimization problem is quite simple and can be efficiently solved by the famous golden section searching method, the inner-tier optimization problem turns out to be nonconvex and cannot be easily solved. To solve it, we relax it to a secrecy rate maximization (SRM) problem, which naturally constitutes a difference convex (DC)-type programming problem and can be iteratively solved by employing a successive convex approximation (SCA) method. Numerical simulations are further provided to demonstrate the proposed algorithms. Results show that our algorithms can converge fast to a near-optimal solution.
In this paper, secure communication over a multi-input multi-output multi-eavesdropper (MIMÓME) wiretap channel is considered. We propose an enhanced MIMÓME artificial noise (AN) model in which the receiver (Bob) adopts the latest Full-Duplex MIMO Radio technique to emit AN jointly with the transmitter (Alice). An achievable secrecy rate is obtained for this model over an unfavorable noiseless eavesdropping channel. Optimization problem is formulated to solve the beamforming and power allocation for Alice and Bob's transmitting signals and to determine the dimension allocation between the information and AN signals. Simulations are carried out to illustrate the optimization process, and the results show that the enhanced MIMÓME model outperforms existing AN models for low self-interference regime.
This paper studies a secure communication over multiple-input multiple-output multi-antenna eavesdropper (MIMOME) channels which consist of legitimate parities, namely a transmitter and receiver, equipped with multi-antennas and a passive eavesdropper with multi-antennas. For securing the communication between the legitimate parties, we consider an artificial noise (AN) scheme in which the legitimate transmitter sends its secret messages and AN signal together. Meanwhile, it is assumed that the legitimate receiver has a full-duplex capability which enables it to capture the secret message from the transmitter and simultaneously generate a jamming signal to strengthen security. While there have been studies on similar setups, most of them focus on the design of the jamming signal with the assumption of full channel-state information (CSI) and/or system parameter optimization based on numerical evaluations. On the contrary, in this work, we instead introduce a tight lower bound on an achievable ergodic secrecy rate as a versatile analytic tool and derive a closed-form expressions for the bound. To confirm the analytic results, we carry out numerical evaluations of the ergodic secrecy rate which are compared with the proposed lower bound.
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.
Joint transmit beamforming and cooperative jamming for MIMOME (multiple-input multiple-output multi-antenna-eavesdropper) wiretap channel is studied, where the model consists of a transmitter, a friendly jammer, a receiver and an eavesdropper. The optimization problem of finding transmit and jamming covariances to maximize the secrecy rate is non-convex, and blindly searching will result in local optima. Because of the transmit beamforming, the MIMOME channel can be related to an effective MISOSE channel. Using this relation, we propose an iterative algorithm that in each iteration: 1) searches the jamming covariance for the effective MISOSE channel and 2) updates the effective MISOSE channel. Numerical results show that our proposed algorithm achieves higher objective whereas blind search is trapped at local optima. The proposed algorithm achieves higher secrecy rate than the existing artificial noise scheme.