This work develops a radio resource allocation framework for energy-efficient and confidential communications in multiple-antenna wiretap channels. Statistical channel state information (CSI) is considered at the transmitter, and the artificial noise (AN) technique is used. The formulated problem is a challenging non-convex fractional program which is tackled by combining fractional programming and sequential optimization. The resulting sequential fractional programming algorithm exhibits polynomial complexity and is provably convergent to a first-order optimal resource allocation. Numerical results show the merits of the proposed algorithm with AN.
This work develops a radio resource allocation framework for energy-efficient and confidential communications in multiple-antenna wiretap channels. Statistical channel state information (CSI) is considered at the transmitter, and the artificial noise (AN) technique is used. The formulated problem is a challenging non-convex fractional program which is tackled by combining fractional programming and sequential optimization. The resulting sequential fractional programming algorithm exhibits polynomial complexity and is provably convergent to a first-order optimal resource allocation. Numerical results show the merits of the proposed algorithm with AN.
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.
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 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.
This paper studies secure wireless transmission from a multi-antenna transmitter to a single-antenna intended receiver overheard by multiple eavesdroppers with considering the imperfect channel state information (CSI) of wiretap channel.To enhance security of communication link, the artificial noise (AN) is generated at transmitter.We first design the robust joint optimal beamforming of secret signal and AN to minimize transmit power with constraints of security quality of service (QoS), i.e., minimum allowable signal-to-interference-and-noise ratio (SINR) at receiver and maximum tolerable SINR at eavesdroppers.The formulated design problem is shown to be nonconvex and we transfer it into linear matrix inequalities (LMIs).The semidefinite relaxation (SDR) technique is used and the approximated method is proved to solve the original problem exactly.To verify the robustness and tightness of proposed beamforming, we also provide a method to calculate the worst-case SINR at eavesdroppers for a designed transmit scheme using semidefinite programming (SDP).Additionally, the secrecy rate maximization is explored for fixed total transmit power.To tackle the nonconvexity of original formulation, we develop an iterative approach employing sequential parametric convex approximation (SPCA).The simulation results illustrate that the proposed robust transmit schemes can effectively improve the transmit performance.
We consider secure beamforming with artificial noise in a multiple-input single-output multiple-eavesdropper (MISOME) wiretap channel, where a transmitter has access to full channel state information (CSI) of a legitimate channel but only partial CSI of eavesdropper channels. In this paper, we first put forth a notion of symbol error probability (SEP) for confidential information—called the δ-secrecy SEP—to connect the reliability and confidentiality of the legitimate communication in MISOME wiretap channels. For single-antenna colluding and non-colluding eavesdroppers, we determine the optimal power allocation between the information-bearing signal and artificial noise to minimize the δ-secrecy SEP in the presence of weak or strong eavesdroppers, and further develop the switched power allocation for general eavesdropping attacks.
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.