Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Log inSign up
Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Blog
Job Board
Q3AS

© 2026 Aqora Quantum S.A.S.

TermsPrivacyLegal Notice

IEEE Signal Processing Letters

A Safe Approximation Approach to Secrecy Outage Design for MIMO Wiretap Channels

Qiang Li, Wing‐Kin Ma, Anthony Man–Cho So

Published Jan 1, 2014• 43 citations
Publisher

Abstract

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.

DOI
10.1109/lsp.2013.2293884

Related papers

Robust Outage Secrecy Rate Optimizations for a MIMO Secrecy Channel

Zheng Chu, Kanapathippillai Cumanan, Zhiguo Ding +2 more

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.

IEEE Wireless Communications Letters•Nov 26, 2014•65 citations

Outage Constrained Secrecy Rate Maximization for MIMOME Multicast Wiretap Channels

Huanhuan Song, Hong Wen, Runfa Liao +2 more

In this letter, we investigate a robust transmit optimization design based on an artificial noise (AN)-aided precoding scheme for maximizing secrecy rate in a multiple-input multiple-output multiple-eavesdropper multicast network where a transmitter sends confidential information to multiple intended users and provides energy for multiple idle nodes while multiple passive eavesdroppers try to overhear the secret information. Supposing Gaussian CSI uncertainties, the proposed outage-constrained secrecy rate maximization (OC-SRM) problem is nonconvex and its analytical analysis is more challenging than several existing OC-SRM schemes. Technically, to circumvent this mathematically intractable secrecy problem, we resort to low SNR approximation and some conservative approximations (e.g., Bernstein-type inequality and sphere bounding) to reformulate the OC-SRM problem into two convex subproblems which can be efficiently solved by the off-the-shelf optimization solver. Simulation results are provided to validate the security performance of the robust AN-aided precoding design.

IEEE Wireless Communications Letters•Nov 9, 2018•10 citations

Secrecy rate maximization for MIMO wiretap channels with channel uncertainty

Mohamed Lassaad Ammari, Paul Fortier

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.

Canadian Workshop on Information Theory (CWIT)•Jun 1, 2017•0 citations

Secrecy Outage Design in MIMO-SWIPT Systems Based on a Non-Linear EH Model

Yi Xing Yuan, Zhiguo Ding

This paper consider a multiple-input multiple- output (MIMO) downlink system with simultaneous wireless information and power transfer (SWIPT). In this system, we provide secure communication by considering all non-linear energy receivers (ERs) as the potential eavesdroppers. We aim to design an optimal covariance matrix of the transmit signal based on the proposed outage-constrained secrecy rate maximization (OC-SRM) problem, where the proposed system keeps the probability of the secrecy rate outage and the harvested energy outage caused by uncertainties regarding the channel state information (CSI) below the given thresholds. The proposed maximization problem is non-convex and unlikely to be efficiently computable. To surmount the non-convexity of the proposed OC-SRM problem, we resort several transformations and approximations. In the partial channel uncertainty (PCU) model, we introduce auxiliary variables to transfer the Shannon capacity expressions into easy handled forms based on the concept of Fenchel conjugate arguments. As a compromise, we employ three safe approximation approaches to find the upper bounds of the probabilistic constraints. Moveover, an alternating optimization (AO) algorithm is proposed to solve the reformulated problem. The performance of the proposed design is efficiently validated by numerical results in our paper.

IEEE Globecom Workshops (GC Wkshps)•Dec 1, 2017•5 citations

Energy efficiency optimization for MISO wiretap channels with statistical and imperfect CSI

Weidong Mei, Zhi Chen, Jun Fang +1 more

This paper considers an energy-efficient transmit design in a multiple-input single-output (MISO) wiretap channel. In particular, a transmitter sends one confidential message to a legitimate receiver, which must be kept perfectly secure from multiple external eavesdroppers. Assuming partial eavesdroppers' channel state information (ECSI) at the transmitter, we aim to design the transmit beamformer such that the outage secrecy energy efficiency (SEE) is maximized. Two ECSI uncertainty scenarios are studied, i.e., statistical ECSI and imperfect ECSI. For the statistical ECSI case, only the distribution of ECSI is available at the transmitter. The SEE outage constraint admits a closed-form expression in this case, and an approximate solution can be obtained by solving a sequence of convex optimization problems. However, this does not apply to the imperfect ECSI case, where the channel lies in some uncertainty set centered at the true channel. We show that a conservative transmit scheme can be derived by invoking the Bernstein-type inequality. It is proved that our proposed methods always yield a solution of rank one, with either statistical or imperfect CSI. Numerical results are finally presented to confirm the efficacy of our proposed methods.

IEEE International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)•Jul 1, 2017•4 citations

Safe convex approximation to outage-based MISO secrecy rate optimization under imperfect CSI and with artificial noise

Qiang Li, Wing‐Kin Ma, Anthony Man–Cho So

Consider a scenario in which an MISO channel is overheard by multiple single-antenna eavesdroppers. The transmitter has perfect channel state information (CSI) with the legitimate channel, but has imperfect CSI with the eavesdroppers' channels. The CSI uncertainties are assumed stochastic. We formulate an artificial-noise (AN)-aided secrecy-rate maximization problem where the CSI uncertainties are handled using an outage-based formulation. Our aim is to find, for this problem, tractable designs for the transmit and AN covariances. Unfortunately, outage-based optimization problems are generally difficult to solve. The main contribution here is to derive a safe, convex optimization-based, approximation to the considered problem. The advantages of the method are shown by simulations.

Asilomar Conference on Signals, Systems and Computers (ACSSC)•Nov 1, 2011•42 citations
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.
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.
In this letter, we investigate a robust transmit optimization design based on an artificial noise (AN)-aided precoding scheme for maximizing secrecy rate in a multiple-input multiple-output multiple-eavesdropper multicast network where a transmitter sends confidential information to multiple intended users and provides energy for multiple idle nodes while multiple passive eavesdroppers try to overhear the secret information. Supposing Gaussian CSI uncertainties, the proposed outage-constrained secrecy rate maximization (OC-SRM) problem is nonconvex and its analytical analysis is more challenging than several existing OC-SRM schemes. Technically, to circumvent this mathematically intractable secrecy problem, we resort to low SNR approximation and some conservative approximations (e.g., Bernstein-type inequality and sphere bounding) to reformulate the OC-SRM problem into two convex subproblems which can be efficiently solved by the off-the-shelf optimization solver. Simulation results are provided to validate the security performance of the robust AN-aided precoding design.
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 paper consider a multiple-input multiple- output (MIMO) downlink system with simultaneous wireless information and power transfer (SWIPT). In this system, we provide secure communication by considering all non-linear energy receivers (ERs) as the potential eavesdroppers. We aim to design an optimal covariance matrix of the transmit signal based on the proposed outage-constrained secrecy rate maximization (OC-SRM) problem, where the proposed system keeps the probability of the secrecy rate outage and the harvested energy outage caused by uncertainties regarding the channel state information (CSI) below the given thresholds. The proposed maximization problem is non-convex and unlikely to be efficiently computable. To surmount the non-convexity of the proposed OC-SRM problem, we resort several transformations and approximations. In the partial channel uncertainty (PCU) model, we introduce auxiliary variables to transfer the Shannon capacity expressions into easy handled forms based on the concept of Fenchel conjugate arguments. As a compromise, we employ three safe approximation approaches to find the upper bounds of the probabilistic constraints. Moveover, an alternating optimization (AO) algorithm is proposed to solve the reformulated problem. The performance of the proposed design is efficiently validated by numerical results in our paper.
This paper considers an energy-efficient transmit design in a multiple-input single-output (MISO) wiretap channel. In particular, a transmitter sends one confidential message to a legitimate receiver, which must be kept perfectly secure from multiple external eavesdroppers. Assuming partial eavesdroppers' channel state information (ECSI) at the transmitter, we aim to design the transmit beamformer such that the outage secrecy energy efficiency (SEE) is maximized. Two ECSI uncertainty scenarios are studied, i.e., statistical ECSI and imperfect ECSI. For the statistical ECSI case, only the distribution of ECSI is available at the transmitter. The SEE outage constraint admits a closed-form expression in this case, and an approximate solution can be obtained by solving a sequence of convex optimization problems. However, this does not apply to the imperfect ECSI case, where the channel lies in some uncertainty set centered at the true channel. We show that a conservative transmit scheme can be derived by invoking the Bernstein-type inequality. It is proved that our proposed methods always yield a solution of rank one, with either statistical or imperfect CSI. Numerical results are finally presented to confirm the efficacy of our proposed methods.
Consider a scenario in which an MISO channel is overheard by multiple single-antenna eavesdroppers. The transmitter has perfect channel state information (CSI) with the legitimate channel, but has imperfect CSI with the eavesdroppers' channels. The CSI uncertainties are assumed stochastic. We formulate an artificial-noise (AN)-aided secrecy-rate maximization problem where the CSI uncertainties are handled using an outage-based formulation. Our aim is to find, for this problem, tractable designs for the transmit and AN covariances. Unfortunately, outage-based optimization problems are generally difficult to solve. The main contribution here is to derive a safe, convex optimization-based, approximation to the considered problem. The advantages of the method are shown by simulations.