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IEEE Wireless Communications Letters

Secrecy-Rate Balancing for Two-User MISO Interference Channels

Jiqing Ni, Kai‐Kit Wong, Zesong Fei, Chengwen Xing, Haixia Chen, Kin‐Fai Tong, Jingming Kuang

Published Feb 1, 2014• 19 citations
Publisher

Abstract

This paper considers a two-user multiple-input single-output (MISO) interference channel with confidential messages (IFC-CM), where the beamforming vectors at the two transmitters are jointly optimized using the closed-form Pareto-optimal parameterization. We show that coordinated beamforming is secrecy-rate optimal which is achieved by agreeing on the parameters between the two transmitters. We first analyze the feasible set of the beamforming parameters that guarantees positiveness of the secrecy rates. We then derive a quadratic relationship that finds the Pareto-optimal parameters to achieve secrecy-rate balancing beamforming.

DOI
10.1109/wcl.2013.092013.130473

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This paper considers a two-user multiple-input single-output (MISO) interference channel with confidential messages (IFC-CM), where the beamforming vectors at the two transmitters are jointly optimized using the closed-form Pareto-optimal parameterization. We show that coordinated beamforming is secrecy-rate optimal which is achieved by agreeing on the parameters between the two transmitters. We first analyze the feasible set of the beamforming parameters that guarantees positiveness of the secrecy rates. We then derive a quadratic relationship that finds the Pareto-optimal parameters to achieve secrecy-rate balancing beamforming.
This paper considers a 2-user multiple-input single-output (MISO) interference channel with confidential messages (IFC-CM), in which the Rician channel model is assumed. The coordinated beamforming vectors at the two transmitters have the similar parameterizations as those for perfect CSI, which could be optimized jointly and achieved by agreeing on the real parameters between the two users. Our main contribution is that a quadratic relationship between the two real-valued parameters can be derived for the Rician channel to reach the ergodic secrecy rate balancing point. Simulation results present the secrecy performance over the 2-user MISO IFC-CM scenario.
This letter addresses the robust optimization problem of downlink coordinated beamforming over the multiple-input single-output (MISO) interference channel with confidential messages (IFC-CM) exploiting imperfect channel state information (CSI) at the transmitters. Our aim is to minimize the total transmitted power subject to the worst-case individual signal-to-interference-plus-noise-ratio (SINR) and equivocation rates. To model the imperfect CSI, bounded ellipsoidal uncertainties for channel vector and covariance are both considered. By deriving the equivalent forms for the SINR and secrecy constraints, the worst-case robust problem can be reformulated as a semi-definite programming (SDP) with the help of rank relaxation. Simulation results show the effectiveness of the proposed algorithm.
In this paper, we study the secrecy communication in two-user MISO interference networks where an external eavesdropper is interested in the messages transmitted by both transmitters. We propose a beamforming design to maximize the achievable secrecy sum rate of the transmitters subject to the individual power constraint at each transmitter. To transform this complex non-convex problem into a convex one, we propose an iterative algorithm based on the constrained concave convex procedure (CCCP) and successive convex approximation (SCA). It is observed that the proposed algorithm converges fast to a stationary point within a few iterations. Furthermore, we also propose a low-complexity null-space beamforming design scheme in which the beamforming vectors have closed-form solutions. Simulation results show the effectiveness of the two proposed schemes in improving the secrecy sum rate performance.
A secure communication game is considered for the two-user MISO Gaussian interference channel with confidential messages, where each transmitter aims to maximize the difference between its secrecy rate and the secrecy rate of the other transmitter. In this novel problem, the weaker link tries to minimize the extra secret information obtained by its adversary, while the stronger link attempts to maximize it. We provide an information theoretic formulation for this non-cooperative zero-sum game scenario and determine that, under the assumption of Gaussian signaling at the transmitters, there exists a unique Nash equilibrium solution for the proposed problem. Moreover, we obtain in closed-form the optimal strategies (beamformers) at the transmitters that result in the Nash equilibrium. While the NE strategies are achievable in one shot when full channel state information is available at the transmitters (CSIT), we also propose an iterative step-by-step algorithm that converges to the NE point, but only requires limited CSIT. Numerical results are presented to illustrate the analytical findings and to study the role of different channel parameters on the NE strategies.
This paper investigates secrecy rate optimization problems for a multiple-input-single-output (MISO) secrecy channel in the presence of multiple multiantenna eavesdroppers. Specifically, we consider power minimization and secrecy rate maximization problems for this secrecy network. First, we formulate the power minimization problem based on the assumption that the legitimate transmitter has perfect channel state information (CSI) of the legitimate user and the eavesdroppers, where this problem can be reformulated into a second-order cone program (SOCP). In addition, we provide a closed-form solution of transmit beamforming for the scenario of an eavesdropper. Next, we consider robust secrecy rate optimization problems by incorporating two probabilistic channel uncertainties with CSI feedback. By exploiting the Bernstein-type inequality and S-Procedure to convert the probabilistic secrecy rate constraint into the determined constraint, we formulate this secrecy rate optimization problem into a convex optimization framework. Furthermore, we provide analyses to show the optimal transmit covariance matrix is rank-one for the proposed schemes. Numerical results are provided to validate the performance of these two conservative approximation methods, where it is shown that the Bernstein-type inequality-based approach outperforms the S-Procedure approach in terms of the achievable secrecy rates.
This paper considers a two-user multiple-input single-output Gaussian broadcast channel model with two sorts of information transfer, i.e., multicasting and confidential broadcasting. Specifically, three service messages are combined at the transmitter. The transmitter sends a multicast message to both users, and a confidential message to each user which is kept perfectly secret from the other user. Our goal is to jointly design the optimal input covariances for the multicast message and the two confidential messages, such that the secrecy capacity region is maximized. This problem can be formulated as a secrecy rate maximization (SRM) problem with the quality of multicast service constraint and the quality of confidential service constraint. This SRM problem is nonconvex by nature. To solve it, we reveal its hidden convexity and transform the original SRM problem into a semidefinite programming problem. Furthermore, we prove that the optimal input covariance matrices of the multicast message and the two confidential messages are always with rank one, which implies the optimality of beamforming. Besides, we show that the arithmetic complexity of our proposed method is polynomial with regard to the dimension of the optimization variables. Numerical results are finally presented to show the efficacy of our proposed method.