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International Conference on Wireless Communications and Signal Processing (WCSP)

Robust Secure Beamforming in Cognitive MIMO Wiretap Channels With Bounded Channel Errors

Jun Xiong, Xuanhan Zhou, Kuo Cao, Xiaoran Liu, Dongtang Ma

Published Oct 21, 2020• 1 citation
Publisher

Abstract

This paper studies a cognitive multiple-input multiple-output (MIMO) network, in which a secondary transmitter aims to send confidential messages to its receiver in the presence of one multi-antenna eavesdropper, while has the interference temperature limit (ITL) for the primary user. Assuming that all the channels are imperfect and the errors are modeled by deterministically bounded model, we consider robust secure beamforming (RSB) design problem and our goal is to maximize the worst-case achievable secrecy rate subject to the total transmit power constraint and the ITL for the primary user. The formulated optimization problem is non-convex while the channel uncertainties make it more difficult to cope with. To address it, an inexact block coordinate descent (IBCD) approach is proposed to obtain the near-optimal solution, where we firstly linearize the two log-det terms of the objective function and then, the semi-infinite constraints with the bounded channel uncertainties are reformulated as linear matrix inequalities (LMIs). Finally, numerical results validate the performance of our proposed RSB algorithm.

DOI
10.1109/wcsp49889.2020.9299792

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This paper studies a cognitive multiple-input multiple-output (MIMO) network, in which a secondary transmitter aims to send confidential messages to its receiver in the presence of one multi-antenna eavesdropper, while has the interference temperature limit (ITL) for the primary user. Assuming that all the channels are imperfect and the errors are modeled by deterministically bounded model, we consider robust secure beamforming (RSB) design problem and our goal is to maximize the worst-case achievable secrecy rate subject to the total transmit power constraint and the ITL for the primary user. The formulated optimization problem is non-convex while the channel uncertainties make it more difficult to cope with. To address it, an inexact block coordinate descent (IBCD) approach is proposed to obtain the near-optimal solution, where we firstly linearize the two log-det terms of the objective function and then, the semi-infinite constraints with the bounded channel uncertainties are reformulated as linear matrix inequalities (LMIs). Finally, numerical results validate the performance of our proposed RSB algorithm.
In this paper, a multiple-input multiple-output wiretap channel model is studied, where the information packet sent from the transmitter to the desired receiver is wiretapped by a potential eavesdropper. When ideal channel state information (CSI) is available, we design the secure beamforming using a proposed iterative closed-form updating scheme based on majorization-minimization approach. Numerical results demonstrate that the proposed scheme acquires the same secrecy rate as the existing algorithms whereas it has much lower complexity. When ideal CSI is not available and channel errors are modeled by deterministically bounded model, we investigate robust secure beamforming (RSB) optimization problem whose goal is worst-case secrecy rate maximization. In the formulated optimization problem, the objective function includes the expression of a logarithm of a determinant (log det) minus log det. Instead of approximating the log det expression as a trace, we propose to linearize two log det terms. After linearization, epigraph reformulation is used to deal with deterministically bounded channel errors and semi-infinite constraints are recast as linear matrix inequalities. Finally, an alternating optimization algorithm is utilized to find the RSB design. After obtaining the RSB design, we derive the worst-case secrecy rate. Numerical results illustrate that the proposed RSB design is superior to the nonrobust one.
In this letter, we investigate the secure beamforming design for multiuser multiple-input single-output interference channel with an eavesdropper. The robust secrecy rate optimization problem is studied with the imperfect channel state information. We consider the beamforming design to maximize the minimum worst case secrecy rate subject to the transmit power constraints with norm-bounded channel uncertainty. The problem is non-convex and hard to solve. We propose an effective method to reformulate this non-convex problem as a series of tractable convex program problems with linear matrix inequality and second-order cone constraints by exploiting the conservative approximation and the sequential convex approximation methods. The simulation results demonstrate the effectiveness of the proposed algorithm.
This paper studies masked beamforming schemes for secure communication in broadcast multiple-input multiple-output (MIMO) systems with a passive multiple-antenna eavesdropper. Assuming no information about the eavesdropper is available at the transmitter, we aim to maximize the transmit power of the artificial noise while meeting mean square error (MSE) constraints at the legitimate receivers and the total power constraint at the transmitter. Based on imperfect channel state information (CSI) of the legitimate receivers at the transmitter, we present a worst-case robust masked beamforming algorithm. By exploiting alternating iterative optimization, the proposed algorithm recasts the non-convex optimization problem as two semidefinite program (SDP) based subproblems, which are solvable with interior-point methods. Simulation results are provided to illustrate the secrecy performance of the proposed algorithm.
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.
This letter investigates robust secrecy rate optimization techniques for a multiple-input-multiple-output (MIMO) wiretap channel in the presence of a multiantenna eavesdropper. In particular, two robust secrecy rate optimization problems are studied: robust power minimization with an outage secrecy rate constraint and robust secrecy rate maximization subject to the outage secrecy rate and transmit power constraints. Here, it is assumed that the legitimate transmitter has perfect channel state information (CSI) of the legitimate receiver and imperfect CSI of the eavesdropper. Both robust problems are not convex in terms of transmit covariance matrix and the outage secrecy rate constraint. Hence, we propose a conservative approximation approach to reformulate this outage secrecy rate constraint by exploiting the Bernstein-type inequality to obtain a tractable solution for these two robust problems. Numerical results have been provided to validate the convergence and the performance of the proposed robust algorithms.
This paper considers an energy-efficient transmit design in a general multiple-input single-output multiple-eavesdropper (MISOME) wiretap channel. Specifically, a transmitter sends one confidential message to a legitimate receiver, which must be kept perfectly secure from several external multi-antenna eavesdroppers. Assuming imperfect channel state information (CSI) at the transmitter, our goal is to design the input transmit covariance, such that the worst-case secrecy energy efficiency (WC-SEE) is maximized, subject to the quality of service (QoS) and total transmit power constraints. Due to the nonconvexity of this problem, an equivalent parametric reformulation, based on the fractional programming theory, is proposed to recast this problem as a sequence of semidefinite programs. By this means, the maximum WC-SEE can be found via a root search algorithm. Moreover, we also give an approach to constructing a rank-one optimal covariance matrix of the confidential message from our proposed algorithm, which implies the optimality of transmit beamforming to achieve the maximum WC-SEE. Numerical results are presented to verify the efficacy of our proposed method.