Zheng Chu | Newcastle University (original) (raw)
Papers by Zheng Chu
IEEE Transactions on Signal Processing, 2015
This paper studies the use of multi-antenna harvest-and-jam (HJ) helpers in a multi-antenna ampli... more This paper studies the use of multi-antenna harvest-and-jam (HJ) helpers in a multi-antenna amplify-and-forward (AF) relay wiretap channel assuming that the direct link between the source and destination is broken. Our objective is to maximize the secrecy rate at the destination subject to the transmit power constraints of the AF relay and the HJ helpers. In the case of perfect channel state information (CSI), the joint optimization of the artificial noise (AN) covariance matrix for cooperative jamming and the AF beamforming matrix is studied using semidefinite relaxation (SDR) which is tight, while suboptimal solutions are also devised with lower complexity. For the imperfect CSI case, we provide the equivalent reformulation of the worst-case robust optimization to maximize the minimum achievable secrecy rate. Inspired by the optimal solution to the case of perfect CSI, a suboptimal robust scheme is proposed striking a good tradeoff between complexity and performance. Finally, numerical results for various settings are provided to evaluate the proposed schemes.
2014 Sixth International Conference on Wireless Communications and Signal Processing (WCSP), 2014
The emerging radio signal enabled simultaneous wireless information and power transfer (SWIPT), h... more The emerging radio signal enabled simultaneous wireless information and power transfer (SWIPT), has drawn significant attention. To achieve secrecy transmission by cooperative jamming, especially in the upcoming 5G networks with self-sustainable mobile base stations (BSs) and yet not to add extra power consumption, we propose in this paper a new relay protocol, i.e., harvest-and-jam (HJ), in a relay wiretap channel with an additional set of spare helpers. Specifically, in the first transmission phase, a single-antenna transmitter (Tx) transfers signals carrying both information and energy to a multi-antenna amplify-and-forward (AF) relay and a group of multi-antenna helpers; in the second transmission phase, the AF relay processes the information and forwards it to the receiver while each of the helpers generates an artificial noise (AN), the power of which is constrained by its previously harvested energy, to interfere with the eavesdropper. By optimizing the transmit beamforming matrix for the AF relay and the covariance matrix for the AN, we maximize the secrecy rate for the receiver subject to transmit power constraints for the AF relay and all helpers. The formulated problem is shown to be non-convex, for which we propose an iterative algorithm based on alternating optimization. Finally, the performance of the proposed scheme is evaluated by simulations as compared to other heuristic schemes.
IET Communications, 2015
ABSTRACT
Electronics Letters, 2015
ABSTRACT
IEEE Wireless Communications Letters, 2015
ABSTRACT
IEEE Transactions on Vehicular Technology, 2000
This paper studies different secrecy rate optimization problems for a multiple-input-multiple-out... more This paper studies different secrecy rate optimization problems for a multiple-input-multiple-output (MIMO) secrecy channel. In particular, we consider a scenario where a communication through a MIMO channel is overheard by a multiple-antenna eavesdropper. In this secrecy network, we first investigate two secrecy rate optimization problems: 1) power minimization and 2) secrecy rate maximization. These optimization problems are not convex due to the nonconvex secrecy rate constraint. However, by approximating this secrecy rate constraint based on Taylor series expansion, we propose iterative algorithms to solve these secrecy rate optimization problems. In addition, we provide the convergence analysis for the proposed algorithms. These iterative optimization approaches are developed under the assumption that the transmitter has perfect channel state information. However, there are practical difficulties in having perfect channel state information at the transmitter. Hence, robust secrecy rate optimization techniques based on the worst-case secrecy rate are considered by incorporating channel uncertainties. By exploiting the S-Procedure, we show that these robust optimization problems can be formulated into semidefinite programming at low signalto-noise ratios (SNRs). Simulation results have been provided to validate the convergence of the proposed algorithms. In addition, numerical results show that the proposed robust optimization techniques outperform the nonrobust schemes in terms of the worst-case secrecy rates and the achieved secrecy rates.
IEEE Transactions on Signal Processing, 2015
This paper studies the use of multi-antenna harvest-and-jam (HJ) helpers in a multi-antenna ampli... more This paper studies the use of multi-antenna harvest-and-jam (HJ) helpers in a multi-antenna amplify-and-forward (AF) relay wiretap channel assuming that the direct link between the source and destination is broken. Our objective is to maximize the secrecy rate at the destination subject to the transmit power constraints of the AF relay and the HJ helpers. In the case of perfect channel state information (CSI), the joint optimization of the artificial noise (AN) covariance matrix for cooperative jamming and the AF beamforming matrix is studied using semidefinite relaxation (SDR) which is tight, while suboptimal solutions are also devised with lower complexity. For the imperfect CSI case, we provide the equivalent reformulation of the worst-case robust optimization to maximize the minimum achievable secrecy rate. Inspired by the optimal solution to the case of perfect CSI, a suboptimal robust scheme is proposed striking a good tradeoff between complexity and performance. Finally, numerical results for various settings are provided to evaluate the proposed schemes.
2014 Sixth International Conference on Wireless Communications and Signal Processing (WCSP), 2014
The emerging radio signal enabled simultaneous wireless information and power transfer (SWIPT), h... more The emerging radio signal enabled simultaneous wireless information and power transfer (SWIPT), has drawn significant attention. To achieve secrecy transmission by cooperative jamming, especially in the upcoming 5G networks with self-sustainable mobile base stations (BSs) and yet not to add extra power consumption, we propose in this paper a new relay protocol, i.e., harvest-and-jam (HJ), in a relay wiretap channel with an additional set of spare helpers. Specifically, in the first transmission phase, a single-antenna transmitter (Tx) transfers signals carrying both information and energy to a multi-antenna amplify-and-forward (AF) relay and a group of multi-antenna helpers; in the second transmission phase, the AF relay processes the information and forwards it to the receiver while each of the helpers generates an artificial noise (AN), the power of which is constrained by its previously harvested energy, to interfere with the eavesdropper. By optimizing the transmit beamforming matrix for the AF relay and the covariance matrix for the AN, we maximize the secrecy rate for the receiver subject to transmit power constraints for the AF relay and all helpers. The formulated problem is shown to be non-convex, for which we propose an iterative algorithm based on alternating optimization. Finally, the performance of the proposed scheme is evaluated by simulations as compared to other heuristic schemes.
IET Communications, 2015
ABSTRACT
Electronics Letters, 2015
ABSTRACT
IEEE Wireless Communications Letters, 2015
ABSTRACT
IEEE Transactions on Vehicular Technology, 2000
This paper studies different secrecy rate optimization problems for a multiple-input-multiple-out... more This paper studies different secrecy rate optimization problems for a multiple-input-multiple-output (MIMO) secrecy channel. In particular, we consider a scenario where a communication through a MIMO channel is overheard by a multiple-antenna eavesdropper. In this secrecy network, we first investigate two secrecy rate optimization problems: 1) power minimization and 2) secrecy rate maximization. These optimization problems are not convex due to the nonconvex secrecy rate constraint. However, by approximating this secrecy rate constraint based on Taylor series expansion, we propose iterative algorithms to solve these secrecy rate optimization problems. In addition, we provide the convergence analysis for the proposed algorithms. These iterative optimization approaches are developed under the assumption that the transmitter has perfect channel state information. However, there are practical difficulties in having perfect channel state information at the transmitter. Hence, robust secrecy rate optimization techniques based on the worst-case secrecy rate are considered by incorporating channel uncertainties. By exploiting the S-Procedure, we show that these robust optimization problems can be formulated into semidefinite programming at low signalto-noise ratios (SNRs). Simulation results have been provided to validate the convergence of the proposed algorithms. In addition, numerical results show that the proposed robust optimization techniques outperform the nonrobust schemes in terms of the worst-case secrecy rates and the achieved secrecy rates.