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Transactions on Emerging Telecommunications Technologies

A robust and distributed design for coordinated downlink beamforming for secure MISO interference channels

Zesong Fei, Jiqing Ni, Niwei Wang, Chengwen Xing, Jingming Kuang

Published Apr 7, 2014• 8 citations
Publisher

Abstract

ABSTRACT In this paper, we address the optimization problems of downlink coordinated beamforming over theK‐user multiple‐input single‐output interference channel with confidential messages. Our design objective is to minimise the total transmit power subject to the constraints of individual signal‐to‐interference plus noise ratio and equivocation rates. For the case with perfect channel state information (CSI), by deriving the equivalent forms for the signal‐to‐interference plus noise ratio and the secrecy constraints, the optimization problem is reformulated as a second‐order cone programme problem. Then, an optimal distributed algorithm using the partial Lagrangian duality is discussed. In addition we extend the analysis to the imperfect CSI scenario with bounded ellipsoidal errors, the centralised algorithm has been proposed by solving a semi‐definite programme with the help of rank relaxation, whereas the distributed robust algorithm is devised by using ADMM. Finally, the simulation results have shown that with perfect CSI, the centralised and distributed algorithms have nearly the same performance, but in the case of imperfect CSI, the centralised algorithm shows a slightly better performance. Copyright © 2014 John Wiley & Sons, Ltd.

DOI
10.1002/ett.2816

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ABSTRACT In this paper, we address the optimization problems of downlink coordinated beamforming over theK‐user multiple‐input single‐output interference channel with confidential messages. Our design objective is to minimise the total transmit power subject to the constraints of individual signal‐to‐interference plus noise ratio and equivocation rates. For the case with perfect channel state information (CSI), by deriving the equivalent forms for the signal‐to‐interference plus noise ratio and the secrecy constraints, the optimization problem is reformulated as a second‐order cone programme problem. Then, an optimal distributed algorithm using the partial Lagrangian duality is discussed. In addition we extend the analysis to the imperfect CSI scenario with bounded ellipsoidal errors, the centralised algorithm has been proposed by solving a semi‐definite programme with the help of rank relaxation, whereas the distributed robust algorithm is devised by using ADMM. Finally, the simulation results have shown that with perfect CSI, the centralised and distributed algorithms have nearly the same performance, but in the case of imperfect CSI, the centralised algorithm shows a slightly better performance. Copyright © 2014 John Wiley & Sons, Ltd.
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.
This letter investigates secure transmission with imperfect channel state information (CSI) in multi-input single-output downlink wireless networks that consist of a transmitter, a desired receiver, one eavesdropper, and an assisting jammer. Specifically, only rough first- and second-order moment information is obtained for the estimation errors of CSI. We aim to minimize the total transmit power by jointly designing the beamforming vector at transmitter and artificial noise covariance at jammer under the reliability and secrecy constraints for all the possible distributions of CSI errors. Since the chance-constrained optimization problem is non-convex, we reformulate it using a Lagrangian duality theory and semidefinite relaxation. The simulation results illustrate the validity of the proposed distributionally robust transmit scheme.
In this letter, we investigate the secure beamforming design for multiuser multiple-input single-output interference channel with an eavesdropper. The robust secrecy rate optimization problem is studied with the imperfect channel state information. We consider the beamforming design to maximize the minimum worst case secrecy rate subject to the transmit power constraints with norm-bounded channel uncertainty. The problem is non-convex and hard to solve. We propose an effective method to reformulate this non-convex problem as a series of tractable convex program problems with linear matrix inequality and second-order cone constraints by exploiting the conservative approximation and the sequential convex approximation methods. The simulation results demonstrate the effectiveness of the proposed algorithm.
In this paper, a robust quality-of-service (QoS) based secret transmit beamforming design problem is discussed for a multiple-input single-output (MISO) system which works under cooperative jamming (CJ) scheme with a helper transmitting jamming signals to confuse the eavesdropper. For the channel state information (CSI), we assume that the CSI for the legitimate link is available and the CSI for the wiretap channel is imperfect. Our system design goal is to optimize the worst-case performance of the network under the situation: minimizing the signal-to-interference-and-noise ratio (SINR) at the eavesdropper and meanwhile guaranteeing the SINR at legitimate receiver. Thus the spatial distribution of jamming signals and the beamforming vector of source are jointly optimized under a total power constraint. As this optimization problem is difficult to tackle, a method is proposed with proofs to obtain exact solver of it. Our analysis reveals that optimizing the beamforming vector of source is a better strategy compared to optimizing the spatial covariance matrix of information signals. Numerical results affirm this and show the advantage of robust transmit designs compared to a non-robust approach in lowering the SINR at the eavesdropper in the presence of channel uncertainties.
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.
This paper studies the secure beamforming design for simultaneous wireless information and power transfer in a multiple-input single-output broadcast channel with confidential messages and external eavesdroppers, where each receiver adopts the power splitting (PS) scheme to decode information and harvest energy concurrently, and it is also seen as a potential eavesdropper for messages not intended for it. Our objective is to minimize the total transmit power while guaranteeing the individual secrecy rate and energy harvesting constraints at each receiver by jointly optimizing transmit beamforming vectors, artificial noise covariance, and receive PS ratios. Both scenarios of perfect and imperfect channel state information (CSI) at the transmitter are considered. For the perfect CSI case, we propose a two-stage optimization approach to solve the original non-convex problem global optimality, and also provide a low-complexity suboptimal solution based on the particle swarm optimization algorithm. Furthermore, we also extend the above result to the colluding eavesdroppers scenario. For the imperfect CSI case, we propose a worst-case-based robust formulation, where the CSI errors are norm-bounded. With the aid of S-Procedure, we derive the equivalent forms for constraints and then transform the non-convex robust design into a convex optimization problem. Simulation results are finally presented to demonstrate the performance of our proposed schemes.