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National Doctoral Academic Forum on Information and Communications Technology

Robust artificial noise aided transmit designs for physical layer security

Tang Yanqun, Wei Jibo, Zhang Xiaoying, Dongtang Ma

Published Jan 1, 2013• 0 citations
Publisher

Abstract

For the cases of imperfect channel state information (CSI) on the main channel in the physical-layer-security communications, we study the artificial-noise-aided robust transmit designs. We consider two optimization problems for the multi-input single-output single-antenna eavesdropper (MISOSE) and multi-input multi-output multi-antenna eavesdropper (MIMOME) systems. Under the deterministic uncertainty model (DM), the optimization problem aims to minimize the total transmit power while guaranteeing the probabilistic constraint for the signal to interference and noise ratios (SINR) at the eavesdropper, and the SINR constraint at the legitimate receiver. For the stochastic uncertainty model (SM), the optimization problem is also to minimize the total transmit power under the probabilistic constraints for the SINRs at the legitimate receiver and the eavesdropper. These problems are hard to be solved directly. We transform the optimization problems into a single-variable optimization problem with solving a sequence of semidefinite programs. By comparison, we propose another low-complexity method based on the expectation value. Finally, we verify the performance for the proposed robust transmit designs by the simulation results.

DOI
10.1049/ic.2013.0203

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For the cases of imperfect channel state information (CSI) on the main channel in the physical-layer-security communications, we study the artificial-noise-aided robust transmit designs. We consider two optimization problems for the multi-input single-output single-antenna eavesdropper (MISOSE) and multi-input multi-output multi-antenna eavesdropper (MIMOME) systems. Under the deterministic uncertainty model (DM), the optimization problem aims to minimize the total transmit power while guaranteeing the probabilistic constraint for the signal to interference and noise ratios (SINR) at the eavesdropper, and the SINR constraint at the legitimate receiver. For the stochastic uncertainty model (SM), the optimization problem is also to minimize the total transmit power under the probabilistic constraints for the SINRs at the legitimate receiver and the eavesdropper. These problems are hard to be solved directly. We transform the optimization problems into a single-variable optimization problem with solving a sequence of semidefinite programs. By comparison, we propose another low-complexity method based on the expectation value. Finally, we verify the performance for the proposed robust transmit designs by the simulation results.
Consider the multi-input single-output multi-eavesdroppers (MISOMEs) wireless communication system. Our goal is to design an artificial noise (AN)-aided secure transmit strategy to safeguard this system from the perspective of quality-of-service (QoS). Specifically, we propose two design formulas: (1) total power minimization design under signal-to-interference-plus-noise ratio (SINR) constraints on receiver and eavesdroppers; (2) receiver's SINR maximization design under constraints of transmitted total power and eavesdroppers' SINRs. The proposed design problems jointly optimizing the information covariance and AN covariance are solved by semidefinite program (SDP) optimization approach. Through exploring the Karush-Kuhn-Tucker conditions of SDP problems, it is proved that transmit beamforming is the optimal strategy for confidential information transmission in the two designs. Finally, simulation results demonstrate that the proposed AN-aided approach in the two designs provides the best performance compared to isotropic AN and no-AN approach.
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.
Physical layer security has recently emerged as a promising approach to provide secure wireless communications. Physical layer security technology is the key means to achieve security and communication integration. The built-in security mechanism based on the characteristics of wireless channel provides a feasible idea for the realization of “one secret at a time”. It has important application prospects in integrity protection of service data, Internet of things (IoT) lightweight encryption and blockchain wireless security technology. In this paper, we consider the scenario of a unicast multiuser multiple-input single-output (MISO) downlink system in the presence of multiple single-antenna passive eavesdroppers. Instead of assuming perfect channel state information (CSI), we investigate the artificial noise (AN)-aided robust transmit beamforming scheme with imperfect CSI on legitimate receivers and no CSI regarding eavesdroppers at the transmitter. Under the fixed total transmit power, the information symbol and the AN are transmitted concurrently. We aim to guarantee each legitimate receiver's signal-to-interference-and-noise ratio(SINR) outage probability below a preset level with minimum power. Hence, as much power as possible can be allocated to AN to confuse the eavesdroppers. In order to reduce the negative impact on the legitimate receivers, the AN is transmitted in the null space of the estimated legitimate channels. To deal with this nonconvex optimization problem, a rank relaxed formulation is obtained by employing semidefinite relaxation (SDR). Then we propose two approaches by using Bernstein-type inequality and S-procedure, respectively, to transform the probabilistic constraints into deterministic constraints. The optimization problem is reformulated as a convex semidefinite program (SDP). Simulation results show that the proposed approaches have better performances than the non-robust approach.
In this letter, we study the robust artificial noise (AN) aided transmit design for a multiple-input single-output (MISO) wiretap channel with a single-antenna eavesdropper. We consider two uncertainty models for the imperfect channel state information (CSI) on the main and eavesdropper's channels at the transmitter. For the deterministic uncertainty model, we solve the worst-case secrecy rate maximization (WC-SRM) problem via semidefinite program (SDP). For the stochastic uncertainty model, we propose a suboptimal solution to the outage probability constrained secrecy rate maximization (OP-SRM) problem based on the robust design for the WC-SRM problem. The simulation results demonstrate performance improvement of the proposed worst case robust design as compared to that based on the worst case method without usage of AN.
This paper proposes a physical-layer secrecy transmission based on artificial noise (AN) for a multi-input single-output (MISO) channel overheard by one single-antenna eavesdropper. Legitimate receiver transmits AN using beamforming to improve the secret capacity. The AN is designed for two cases assuming that legitimate receiver has perfect or imperfect knowledge of eavesdropper's channel state information (CSI). The optimization problem of AN design in both cases are not convex. A one-dimensional line search on a sequence of semidefinite programs (SDP) is proposed to solve the problem in perfect CSI case through reformulation. In the case with imperfect CSI, the beamforming and AN vectors are designed for achieving quality of service discrimination. The problem is approximated to be a convex SDP problem by relaxing some restrictions. Furthermore, the optimal covariance is shown to be of rank one. Simulation results verify that our methods precede the existed AN aided scheme.
In this work, a robust artificial noise (AN) aided transmit method is proposed for a multicast multiple-input single-output (MISO) system in the presence of multiple single-antenna eavesdroppers. With the imperfect covariance-based channel state information (CSI), we aim to minimize the transmit power at the transmitter under the multicast secrecy rate constraint and the maximum transmit power constraint. The resulting optimization problem involves the joint optimization of the beamforming vector and AN covariance matrix. After using the semidefinite relaxation (SDR) technique, we derive the exact reformulation of the original optimization through the Lagrange duality. Then this non-convex problem is transformed into a one-variable optimization problem, which can be handled by solving a series of semidefinite programs (SDPs). Simulation results demonstrate the effectiveness of the proposed robust transmit method.