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arXiv:1505.02385

Energy Efficiency in Secure Multi-Antenna Systems

Alessio Zappone, Pin-Hsun Lin, Eduard Axel Jorswieck

Published May 10, 2015• 12 citations
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Abstract

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.

DOI
10.48550/arxiv.1505.02385

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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 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.
The problem of resource allocation for energy-efficient secure communications in multiple-input single-output (MISO) systems is investigated, wherein a malicious user tries to eavesdrop the communication between two legitimate users. The legitimate transmitter has multiple antennas, whereas the eavesdropper and the receiver have a single antenna. Unlike most papers dealing with physical layer security, in this paper the goal of the resource allocation process is not to maximize the secrecy capacity, but rather to maximize the secrecy energy efficiency (SEE), defined as the ratio between the secrecy capacity and the total consumed power. This performance metric is measured in bit/Hz/Joule, and represents the amount of information bits that can be reliably and securely transmitted per unit of bandwidth and per Joule of consumed energy. The energy-efficient resource allocation is carried out considering three different channel state information (CSI) scenarios as to the channel from the legitimate transmitter to the eavesdropper, namely perfect CSI, partial CSI, and statistical CSI.
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.
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 energy-efficient resource allocation in multiple-antenna wiretap channels where transmit antennas are correlated is investigated. The use of artificial noise (AN) in combination with only statistical channel state information (CSI) at the legitimate transmitter is considered. The goal of this work is to do the resource allocation such that the amount of bits which can be reliably and confidentially transmitted per unit of consumed energy, namely, the secrecy energy efficiency (SEE), is maximized. The resulting non-convex maximization problems are tackled by means of fractional programming and sequential convex optimization tools, and first-order optimal solutions are obtained with polynomial complexity. Numerical results show the merits of the proposed algorithms.
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 single-antenna eavesdroppers. Assuming statistical 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, subject to the outage-constrained secrecy rate and transmit power constraints. The resultant problem is intractable to solve even after introducing a semidefinite relaxation (SDR) reformulation. To handle it, an equivalent parametric reformulation, based on the fractional programming and difference-of-concave programming theories, is proposed to recast this problem as a convex problem. By this means, the maximum outage SEE can be found in an iterative fashion. Moreover, we also give an approach to constructing a rank-one covariance matrix from our proposed method, implying the feasibility of transmit beamforming to achieve the obtained SEE performance. Numerical results are presented to show the effectiveness of our proposed method.