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IEEE Transactions on Communications

Energy Efficient Secure Communication Over Decode-and-Forward Relay Channels

Dong Wang, Bo Bob Bai, Wei Chen, Zhu Han

Published Jan 1, 2015• 59 citations
Publisher

Abstract

In this paper, we raise the concern on energy-efficient secure communication over a decode-and-forward relay network with potential eavesdroppers. Our objective is maximizing the secure energy efficiency (EE), which is defined as the ratio of secrecy rate to total power, subject to the given individual power, relay decoding rate, and target secrecy rate constraints. The problem is formulated as a unified mixed integer nonlinear optimization adapting to different assumptions of channel state information (CSI). To deal with this combinatorial optimization, a suboptimal solution scheme is developed upon some mathematical methods as decoupling of mixed integer programming, fractional programming, dual decomposition, and difference of convex functions programming. The core of the scheme is to transform the primal problem into simple subproblems step by step, and then convex programming can be exploited finally. The proposed scheme for the case with statistical eavesdropper's CSI, may be conditionally extended to the scenario with full CSI in which a local optimal solution may be obtained in certain cases. Finally, the performance and achievable secure EE of the proposed algorithm are demonstrated by simulations where the tradeoff between secure EE and secrecy rate is also revealed.

DOI
10.1109/tcomm.2014.2387342

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In this paper, we raise the concern on energy-efficient secure communication over a decode-and-forward relay network with potential eavesdroppers. Our objective is maximizing the secure energy efficiency (EE), which is defined as the ratio of secrecy rate to total power, subject to the given individual power, relay decoding rate, and target secrecy rate constraints. The problem is formulated as a unified mixed integer nonlinear optimization adapting to different assumptions of channel state information (CSI). To deal with this combinatorial optimization, a suboptimal solution scheme is developed upon some mathematical methods as decoupling of mixed integer programming, fractional programming, dual decomposition, and difference of convex functions programming. The core of the scheme is to transform the primal problem into simple subproblems step by step, and then convex programming can be exploited finally. The proposed scheme for the case with statistical eavesdropper's CSI, may be conditionally extended to the scenario with full CSI in which a local optimal solution may be obtained in certain cases. Finally, the performance and achievable secure EE of the proposed algorithm are demonstrated by simulations where the tradeoff between secure EE and secrecy rate is also revealed.
In this paper, energy-efficient secure communications via untrusted two-way relaying are investigated considering physical layer security to prevent the relays from intercepting the confidential information of users. The performance metric of secure energy efficiency (EE), defined as the ratio of the secrecy sum rate to the total power consumption, is maximized by jointly optimizing power allocation for all nodes, with the constraints of the maximum allowed power and the minimum target secrecy rate. To deal with this intractable nonconvex optimization problem, some optimization methods termed as fractional programming, alternate optimization, penalty function method, and difference of convex functions programming, are jointly applied to address a solution scheme with comparatively lower complexity. With these above-mentioned optimization methods, the primal problem is transformed into simple subproblems hierarchically so as to adopt the corresponding optimization algorithm. By simulations, the achievable secure EE, the secrecy sum rate and the total transmission power of the proposed scheme are compared with those of secrecy sum rate maximization. It is demonstrated that the proposed scheme can improve secure EE remarkably yet at the cost of secrecy sum rate loss. This fact also reveals the inherent tradeoff between energy and security.
In this paper, the energy efficiency of secure communication in a wireless decode-and-forward (DF) relay network is studied using friendly jammer. Our objective is to maximize the secure energy efficiency (SEE), measured as the numbers of bits transmitted secretly per unit of energy consumed under power constraint on each node and target secrecy rate constraint. SEE maximization requires the optimal selection of helper nodes as relays and jammer, and then the power allocation among them. The SEE maximization is achieved by joint power allocation between the source, relays and a jammer in global channel state information (CSI) scenario. In this paper, the optimal jammer and relay set is selected iteratively by a simple jammer and relay selection scheme to avoid mix integer formulation of the optimization problem. The resulting problem is solved by a joint application of fractional programming, exact penalty, alternate search, and difference of convex functions programming.
This paper investigates secrecy efficiency (SE) optimization in a friendly full-duplex (FD) decode- and-forward (DF) relay network with a passive eavesdropper. Targeting on SE maximization, the power allocation is optimized subject to the total power and minimum secrecy rate constraints adapting to the assumption of unknown eavesdropper's channel state information (CSI). By exploiting the properties of fractional programming (FP) and Difference of Convex functions (DC) programming, the resulting nonconvex optimization problem can be relaxed into a more tractable equivalent problem. Simulation results demonstrate that our proposed scheme can reach a better trade-off between security performance and energy consumption.
In this article, we raise the concern on secure energy efficiency (SEE) over the wireless-powered untrusted relay networks with nonlinear energy harvesting (EH). To achieve data confidentiality and secrecy performance enhancement concurrently, the untrusted relay can enable simultaneous energy signal reception and confidential information forwarding during the second phase, where no dedicated energy transmission phase or relaying signal splitting is needed for the energy supply. In particular, with the help of destination jamming, the relay can also harvest energy from source signal and jamming signal during the first phase, which is different from conventional relaying protocol that only harvests energy from source and recycled energy. Considering the nonlinear EH efficiency, our objective is to maximize the SEE through piecewise region selection and power allocation. To address this intractable nonconvex problem, a two-layer algorithm based on optimization decoupling, fractional programming, Lagrange dual decomposition and difference of convex functions (DC) programming is proposed. The core idea of the proposed algorithm is to convert the primary problem into simple subproblems by sequentially exploiting the above-mentioned optimization methods. Simulation results reveal the superior secrecy performance of the proposed scheme. The proposed algorithm achieves near-optimal solutions with faster convergence rate.
In this article, a new relay-aided secure communication system is investigated, where a transmitter sends signals to a destination via an amplify-and-forward (AF) relay in the presence of an eavesdropper. We consider a general system configuration, where the source, relay, destination, and eavesdropper are all equipped with multiple antennas. In the practical scenarios of unknown eavesdropper's channel state information (CSI) and uncertainty of the eavesdropper's location, we aim to maximize the expected value of the system secrecy rate over the presumed distribution of the eavesdropper's channels, by exploiting the artificial noise (AN) transmitted by the source and relay nodes. The system design issue is formulated as a nonconvex stochastic optimization problem with a source transmission power constraint and a nonconvex relay transmission power constraint. A novel computational method is proposed to solve this challenging problem. The new method is developed based on an exact penalty function method together with a parallel stochastic decomposition algorithm. Numerical simulations are performed to study the effectiveness of the proposed scheme at various locations of the eavesdropper. Simulation results show that for most cases, secure communication can be achieved without the CSI knowledge of eavesdropper's channels, and the achievable secrecy rate follows the trend of a benchmark system where the eavesdropper's full CSI is available. In particular, the achievable system secrecy rate increases with the number of antennas at the legitimate users. Moreover, the optimal power allocated for the transmission of the AN increases with the system signal-to-noise ratio. The proposed computational method achieves a higher system secrecy rate than a conventional penalty function based approach.
This paper investigates an energy-constrained relay-assisted secure communication system in the presence of a legitimate source-destination pair and a passive eavesdropper with imperfect channel state information (CSI). The energy-constrained relay exploits a power splitting (PS) protocol to simultaneously harvest energy and decode information from the received signal from the source, and then forwards the confidential signal to the full-duplex (FD) destination while it simultaneously transmits artificial noise (AN) to confuse the passive eavesdropper. This robust beamforming design is developed by maximizing the secrecy rate under the constraints of energy harvesting (EH) requirement at the relay and AN transmit power at the destination. Specifically, we formulate the joint relay beamforming and PS ratio as well as the AN power optimization as a non-convex quadratically-constrained problem. In order to circumvent this non-convexity issue, we decompose the original problem into three subproblems which can be determined by the proposed semidefinite relaxation (SDR) and successive convex optimization methods. Furthermore, we derive closed-form expressions for the optimal solutions of each subproblem. Finally, the original non-convex problem can be solved through a convergence guaranteed iterative algorithm. Simulation results are provided to demonstrate the effectiveness and superior performance of the proposed robust design compared with the benchmark schemes.