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Canadian Workshop on Information Theory (CWIT)

Secrecy rate maximization for MIMO wiretap channels with channel uncertainty

Mohamed Lassaad Ammari, Paul Fortier

Published Jun 1, 2017• 0 citations
Publisher

Abstract

A multiple-input multiple-output (MIMO) wiretap channel in the presence of one multiple-antenna eavesdropper is considered. We assume that imperfect channel state information (CSI) on the legitimate link and only statistical CSI of the eavesdropper channel are available at the transmitter. This paper addresses the issue of optimal input covariance matrix design that maximizes the secrecy rate subject to the total power constraint. The secrecy rate maximization (SRM) is studied under a relaxed assumption on the perfect CSI.We reformulate the SRM problem and propose an alternating optimization (AO) algorithm to find the optimal input covariance matrix. Simulation results are presented to validate the effectiveness of the proposed approach. The impact of the channel estimation error is investigated.

DOI
10.1109/cwit.2017.7994825

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A multiple-input multiple-output (MIMO) wiretap channel in the presence of one multiple-antenna eavesdropper is considered. We assume that imperfect channel state information (CSI) on the legitimate link and only statistical CSI of the eavesdropper channel are available at the transmitter. This paper addresses the issue of optimal input covariance matrix design that maximizes the secrecy rate subject to the total power constraint. The secrecy rate maximization (SRM) is studied under a relaxed assumption on the perfect CSI.We reformulate the SRM problem and propose an alternating optimization (AO) algorithm to find the optimal input covariance matrix. Simulation results are presented to validate the effectiveness of the proposed approach. The impact of the channel estimation error is investigated.
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In this paper, we study the secrecy rate maximization (SRM) problem for a multiple-input-multiple-output (MIMO) secrecy channel, where a multi-antenna cooperative jammer is employed to improve secret communication in the presence of multiple multi-antenna eavesdroppers. The SRM problem are not jointly convex in terms of the transmit covariance matrices of the legitimate transmitter and the cooperative jammer. To solve the non-convexity issues, we propose an alternating optimization (AO) approach to design the transmit covariance matrix of the legitimate transmitter and the cooperative jammer. Simulation results validated the performance of the proposed algorithms.
In this paper, we consider the problem of power allocation in MIMO wiretap channel for secrecy in the presence of multiple eavesdroppers. Perfect knowledge of the destination channel state information (CSI) and only the statistical knowledge of the eavesdroppers CSI are assumed. We first consider the MIMO wiretap channel with Gaussian input. Using Jensen's inequality, we transform the secrecy rate max-min optimization problem to a single maximization problem. We use generalized singular value decomposition and transform the problem to a concave maximization problem which maximizes the sum secrecy rate of scalar wiretap channels subject to linear constraints on the transmit covariance matrix. We then consider the MIMO wiretap channel with finite-alphabet input. We show that the transmit covariance matrix obtained for the case of Gaussian input, when used in the MIMO wiretap channel with finite-alphabet input, can lead to zero secrecy rate at high transmit powers. We then propose a power allocation scheme with an additional power constraint which alleviates this secrecy rate loss problem, and gives non-zero secrecy rates at high transmit powers.
Consider a multi-input multi-output (MIMO) channel wiretapped by multiple multi-antenna eavesdroppers. Assuming imperfect eavesdroppers' channel state information (CSI) at the transmitter, an outage-constrained secrecy rate maximization (OC-SRM) problem is considered. Specifically, we aim to design the transmit covariance matrix such that the outage secrecy rate is maximized for a given outage probability. The OC-SRM problem is challenging, and as a compromise, we resort to a recently developed Bernstein-type inequality approach to obtain a safe (conservative) approximate solution for OC-SRM. The merit of the proposed safe design lies in its tractability. In particular, a safe solution can be efficiently computed by alternately solving two convex conic optimization problems. The efficacy of the proposed design is demonstrated by simulations.
In this paper, we study the achievable secrecy rate of the multiple input single output (MISO) wiretap channel, which consists of a transmitter, a legitimate receiver and multiple eavesdroppers. The transmitter is equipped with multiple antennas, while the receiver and all the eavesdroppers each have a single antenna. We assume that the transmitter has perfect channel state information (CSI) for their links to legitimate receiver, but it has only imperfect CSI for their channels to eavesdroppers. Optimal transmit covariance matrix is obtained based on worst-case secrecy rate maximization, under power constraints. The maximum secrecy rate computation can be formulated as a non-convex optimal problem, which cannot be solved directly. In this paper, we transform non-convex optimal problem into a quasi-convex optimal problem which can be efficiently solved with the bisection method. The simulation result and analysis demonstrate the effectiveness of our methods.
We study robust secure transmit design in terms of input covariance matrix for Gaussian multiple-input single-output (MISO) wiretap channels in the presence of a single-antenna eavesdropper. Under the assumption that the transmitter knows partial channel state information (CSI) on the main and eavesdropper's channels, we jointly design the input covariance matrices of information-bearing signal and artificial noise (AN) to maximize the secrecy rate. Unfortunately, the secrecy rate maximization (SRM) problem is difficult to solve. We derive a safe approximation to the SRM problem and propose a tractable approach to solve it. To get more insights, we discuss the rank property of the input covariance matrix of the information-bearing signal. Finally, the simulation results are provided to verify the validity and robustness of our proposed transmit design.