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 Transactions on Information Forensics and Security

Optimal Energy-Efficient Design of Confidential Multiple-Antenna Systems

Alessio Zappone, Pin-Hsun Lin, Eduard Axel Jorswieck

Published Aug 28, 2017• 14 citations
Publisher

Abstract

Energy-efficient resource allocation in multiple-antenna wiretap channels is investigated, subject to maximum power and minimum secrecy capacity/rate constraints. Two energy-efficient metrics are optimized, namely the secrecy energy efficiency, defined as the ratio between the system secrecy capacity and the consumed power, and the secret-key energy efficiency, defined as the ratio between the system secret-key capacity and the consumed power. If the legitimate receiver and the eavesdropper have a single antenna, and the transmitter has multiple antennas, the global solution can be expressed by a simple formula that requires negligible complexity to be computed. Instead, if all nodes have multiple-antennas, provably convergent and computationally-friendly iterative algorithms are provided, which are able to determine the global maximum of the secret-key energy efficiency and candidate solutions of the secrecy energy efficiency maximization problem. Numerical results assess the performance of the proposed methods.

DOI
10.1109/tifs.2017.2746009

Related papers

Energy Efficiency in Secure Multi-Antenna Systems

Alessio Zappone, Pin-Hsun Lin, Eduard Axel Jorswieck

The problem of resource allocation in multiple-antenna wiretap channels is investigated, wherein a malicious user tries to eavesdrop the communication between two legitimate users. Both multiple input single output single-antenna eavesdropper (MISO-SE) and multiple input multiple output multiple-antenna eavesdropper (MIMO-ME) systems are considered. Unlike most papers dealing with physical layer security, the focus of the resource allocation process here is not to maximize the secrecy capacity, but rather to maximize the energy efficiency of the system. Two fractional energy-efficient metrics are introduced, namely the ratios between the system secrecy capacity and the consumed power, and between the system secret-key rate and the consumed power. Both performance metrics are measured in bit/Joule, and result in non-concave fractional optimization problems, which are tackled by fractional programming theory and sequential convex optimization. For both performance metrics, the energy-efficient resource allocation is carried out considering both perfect as well as statistical channel state information (CSI) as to the channel from the legitimate transmitter to the eavesdropper.

arXiv:1505.02385•May 10, 2015•12 citations

Energy Efficiency of Confidential Multi-Antenna Systems With Artificial Noise and Statistical CSI

Alessio Zappone, Pin-Hsun Lin, Eduard Axel Jorswieck

The problem of energy-efficient resource allocation in multiple-antenna wiretap channels is investigated, wherein a malicious user tries to eavesdrop the communication between two legitimate users. The use of artificial noise (AN) in combination with different statistical channel state information scenarios at the legitimate transmitter is considered. Unlike most previous related papers, the goal of the resource allocation is to maximize the amount of bits which can be reliably and confidentially transmitted per Joule of consumed energy. This leads to the maximization of the ratio between the system secrecy capacity and consumed power, a metric which we label secrecy energy efficiency (SEE). The resulting nonconvex maximization problems are tackled by means of the fractional programing and sequential convex optimization tools. The resulting algorithm monotonically increases the objective value, and upon convergence, yields a first-order optimal solution of the problem with a polynomial complexity. Moreover, the impact of using the AN technique on the energy consumption due to digital signal processing operations is explicitly accounted for, providing insight as to when AN is beneficial from an energy-efficient perspective, too. Numerical results show the merits of the proposed algorithms, also showing that AN does not always improve the system SEE, depending on the digital signal processor used to compute the resource allocation.

IEEE Journal of Selected Topics in Signal Processing•Sep 8, 2016•53 citations

Secrecy and energy efficiency in MIMO-ME systems

Alessio Zappone, Pin-Hsun Lin, Eduard Axel Jorswieck

The problem of resource allocation for energy-efficient secure communications in multiple input multiple output multiple-antenna eavesdropper (MIMO-ME) systems is investigated. Unlike most papers dealing with physical layer security, in this paper the goal of the resource allocation process is not only to maximize the secrecy capacity, but also the system secrecy energy efficiency (SEE), defined as the ratio between the secrecy capacity and the total consumed power and thus measured in bit/Joule, which represents the amount of information bits that can be reliably and securely transmitted per Joule of consumed energy. The energy-efficient resource allocation problem is studied considering both perfect and statistical channel state information (CSI) as to the channel from the legitimate transmitter to the eavesdropper.

IEEE International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)•Jun 1, 2015•12 citations

Energy-efficient secrecy precoding for general MIMOME wiretap channels

Bing Fang, Zuping Qian, Zhong Wei +1 more

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.

International Conference on Wireless Communications and Signal Processing (WCSP)•Oct 1, 2015•2 citations

Robust energy-efficient transmit design for misome wiretap channels

Weidong Mei, Zhi Chen, Jun Fang

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.

IEEE Global Conference on Signal and Information Processing•Dec 1, 2016•6 citations

A Low-Complexity Algorithm for Achieving Secrecy Capacity in MIMO Wiretap Channels

Thang Van Nguyen, Quang‐Doanh Vu, Markku J. Juntti +1 more

We consider a secure transmission including a transmitter, a receiver and an eavesdropper, each being equipped with multiple antennas. The aim is to develop a low-complexity and scalable method to find a globally optimal solution to the problem of secrecy rate maximization under a total power constraint at the transmitter. In principle, the original formulation of the problem is nonconvex. However, it can be equivalently translated into finding a saddle point of a minimax convex-concave program. An existing approach finds the saddle point using the Newton method, whose computational cost increases quickly with the number of transmit antennas, making it unsuitable for large scale antenna systems. To this end, we propose an iterative algorithm based on alternating optimization, which is guaranteed to converge to a saddle point, and thus achieves a globally optimal solution to the considered problem. In particular, each subproblem of the proposed iterative method admits a closed-form solution. We analytically show that the iteration cost of our proposed method is much cheaper than that of the known solution. As a result, numerical results demonstrate that the proposed method remarkably outperforms the existing one in terms of the overall run time.

International Conference on Communications•Jun 1, 2020•8 citations
Energy-efficient resource allocation in multiple-antenna wiretap channels is investigated, subject to maximum power and minimum secrecy capacity/rate constraints. Two energy-efficient metrics are optimized, namely the secrecy energy efficiency, defined as the ratio between the system secrecy capacity and the consumed power, and the secret-key energy efficiency, defined as the ratio between the system secret-key capacity and the consumed power. If the legitimate receiver and the eavesdropper have a single antenna, and the transmitter has multiple antennas, the global solution can be expressed by a simple formula that requires negligible complexity to be computed. Instead, if all nodes have multiple-antennas, provably convergent and computationally-friendly iterative algorithms are provided, which are able to determine the global maximum of the secret-key energy efficiency and candidate solutions of the secrecy energy efficiency maximization problem. Numerical results assess the performance of the proposed methods.
The problem of resource allocation in multiple-antenna wiretap channels is investigated, wherein a malicious user tries to eavesdrop the communication between two legitimate users. Both multiple input single output single-antenna eavesdropper (MISO-SE) and multiple input multiple output multiple-antenna eavesdropper (MIMO-ME) systems are considered. Unlike most papers dealing with physical layer security, the focus of the resource allocation process here is not to maximize the secrecy capacity, but rather to maximize the energy efficiency of the system. Two fractional energy-efficient metrics are introduced, namely the ratios between the system secrecy capacity and the consumed power, and between the system secret-key rate and the consumed power. Both performance metrics are measured in bit/Joule, and result in non-concave fractional optimization problems, which are tackled by fractional programming theory and sequential convex optimization. For both performance metrics, the energy-efficient resource allocation is carried out considering both perfect as well as statistical channel state information (CSI) as to the channel from the legitimate transmitter to the eavesdropper.
The problem of energy-efficient resource allocation in multiple-antenna wiretap channels is investigated, wherein a malicious user tries to eavesdrop the communication between two legitimate users. The use of artificial noise (AN) in combination with different statistical channel state information scenarios at the legitimate transmitter is considered. Unlike most previous related papers, the goal of the resource allocation is to maximize the amount of bits which can be reliably and confidentially transmitted per Joule of consumed energy. This leads to the maximization of the ratio between the system secrecy capacity and consumed power, a metric which we label secrecy energy efficiency (SEE). The resulting nonconvex maximization problems are tackled by means of the fractional programing and sequential convex optimization tools. The resulting algorithm monotonically increases the objective value, and upon convergence, yields a first-order optimal solution of the problem with a polynomial complexity. Moreover, the impact of using the AN technique on the energy consumption due to digital signal processing operations is explicitly accounted for, providing insight as to when AN is beneficial from an energy-efficient perspective, too. Numerical results show the merits of the proposed algorithms, also showing that AN does not always improve the system SEE, depending on the digital signal processor used to compute the resource allocation.
The problem of resource allocation for energy-efficient secure communications in multiple input multiple output multiple-antenna eavesdropper (MIMO-ME) systems is investigated. Unlike most papers dealing with physical layer security, in this paper the goal of the resource allocation process is not only to maximize the secrecy capacity, but also the system secrecy energy efficiency (SEE), defined as the ratio between the secrecy capacity and the total consumed power and thus measured in bit/Joule, which represents the amount of information bits that can be reliably and securely transmitted per Joule of consumed energy. The energy-efficient resource allocation problem is studied considering both perfect and statistical channel state information (CSI) as to the channel from the legitimate transmitter to the eavesdropper.
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.
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.
We consider a secure transmission including a transmitter, a receiver and an eavesdropper, each being equipped with multiple antennas. The aim is to develop a low-complexity and scalable method to find a globally optimal solution to the problem of secrecy rate maximization under a total power constraint at the transmitter. In principle, the original formulation of the problem is nonconvex. However, it can be equivalently translated into finding a saddle point of a minimax convex-concave program. An existing approach finds the saddle point using the Newton method, whose computational cost increases quickly with the number of transmit antennas, making it unsuitable for large scale antenna systems. To this end, we propose an iterative algorithm based on alternating optimization, which is guaranteed to converge to a saddle point, and thus achieves a globally optimal solution to the considered problem. In particular, each subproblem of the proposed iterative method admits a closed-form solution. We analytically show that the iteration cost of our proposed method is much cheaper than that of the known solution. As a result, numerical results demonstrate that the proposed method remarkably outperforms the existing one in terms of the overall run time.