Joint transmitter and PS factor optimal design for secure transmission in MIMO full‐duplex relay network powered by SWIPT with perfect and imperfect channel state information
The joint transmitter and PS factor optimal design scheme for secure transmission in multiple‐input multiple‐output (MIMO) full‐duplex relay network powered by simultaneous wireless information and power transfer (SWIPT) is studied. An optimisation problem is presented, aimed at maximising the system security capacity by jointly optimising transmitter and PS factor while satisfying the energy harvest constraint in both perfect and imperfect channel state information (CSI). In perfect CSI case, the optimisation function is formulated with energy harvest constraint, and semidefinite relaxation (SDR) is introduced to solve the non‐convex optimisation problem. In imperfect CSI case, it is assumed that only the first and second order statistics of the eavesdropper's channels are available, but the specific distribution is unknown. In this case, the security capacity of the system is maximised while satisfying the security outage probability and energy harvest constraint. The SDR solution based on equivalent conic reformulation is proposed. And the simulation results demonstrate the effectiveness of the optimal designs in both CSI cases.
The joint transmitter and PS factor optimal design scheme for secure transmission in multiple‐input multiple‐output (MIMO) full‐duplex relay network powered by simultaneous wireless information and power transfer (SWIPT) is studied. An optimisation problem is presented, aimed at maximising the system security capacity by jointly optimising transmitter and PS factor while satisfying the energy harvest constraint in both perfect and imperfect channel state information (CSI). In perfect CSI case, the optimisation function is formulated with energy harvest constraint, and semidefinite relaxation (SDR) is introduced to solve the non‐convex optimisation problem. In imperfect CSI case, it is assumed that only the first and second order statistics of the eavesdropper's channels are available, but the specific distribution is unknown. In this case, the security capacity of the system is maximised while satisfying the security outage probability and energy harvest constraint. The SDR solution based on equivalent conic reformulation is proposed. And the simulation results demonstrate the effectiveness of the optimal designs in both CSI cases.
This paper investigates an energy-constrained relay-assisted secure communication system in the presence of a legitimate source-destination pair and a passive eavesdropper with imperfect channel state information (CSI). The energy-constrained relay exploits a power splitting (PS) protocol to simultaneously harvest energy and decode information from the received signal from the source, and then forwards the confidential signal to the full-duplex (FD) destination while it simultaneously transmits artificial noise (AN) to confuse the passive eavesdropper. This robust beamforming design is developed by maximizing the secrecy rate under the constraints of energy harvesting (EH) requirement at the relay and AN transmit power at the destination. Specifically, we formulate the joint relay beamforming and PS ratio as well as the AN power optimization as a non-convex quadratically-constrained problem. In order to circumvent this non-convexity issue, we decompose the original problem into three subproblems which can be determined by the proposed semidefinite relaxation (SDR) and successive convex optimization methods. Furthermore, we derive closed-form expressions for the optimal solutions of each subproblem. Finally, the original non-convex problem can be solved through a convergence guaranteed iterative algorithm. Simulation results are provided to demonstrate the effectiveness and superior performance of the proposed robust design compared with the benchmark schemes.
This paper studies a simultaneous wireless information and power transfer (SWIPT) system in which the transmitter not only sends data and energy to many types of wireless users, such as multiple information decoding users, multiple hybrid power-splitting users (i.e., users with a power-splitting structure to receive both information and energy), and multiple energy harvesting users, but also prevents information from being intercepted by a passive eavesdropper. The transmitter is equipped with multiple antennas, whereas all users and the eavesdropper are assumed to be equipped with a single antenna. Since the transmitter does not have any channel state information (CSI) about the eavesdropper, artificial noise (AN) power is maximized to mask information as well as to interfere with the eavesdropper as much as possible. The non-convex optimization problem is formulated to minimize the transmit power satisfying all signal-to-interference-plus-noise (SINR) and harvested energy requirements for all users so that the remaining power for generating AN is maximized. With perfect CSI, a semidefinite relaxation (SDR) technique is applied, and the optimal solution is proven to be tight. With imperfect CSI, SDR and a Gaussian randomization algorithm are proposed to find the suboptimal solution. Finally, numerical performance with respect to the maximum SINR at the eavesdropper is determined by a Monte-Carlo simulation to compare the proposed AN scenario with a no-AN scenario, as well as to compare perfect CSI with imperfect CSI.
In this paper, we study secure beamforming for simultaneous wireless information and power transfer (SWIPT) in wireless-powered full-duplex (FD) relay networks. The relay assists transmission of confidential information, while simultaneously harvesting the energy with power switching scheme by the radio-frequency (RF) signals. We propose a joint amplify-and-forward beamforming (AB) and energy signal (AB-ES) with the receiver power splitting strategy (PS) scheme to maximize the secrecy rate under harvesting energy constraints. Since these constraints make the optimization problems become non-convex and hard to tackle. We propose a two-level optimization problem to solve this problem. The out part can be solved via the one-Dimensional search, and the inner part can be solved by semidefinite relaxation (SDR) technique. Simulation results show that the proposed scheme outperforms other schemes.
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.
In this letter, we consider a multiple-input-multiple-output (MIMO) downlink system with simultaneous wireless information and power transfer (SWIPT), where the information sent to the desired receiver (DR) may be wiretapped by the malicious energy harvesting (EH) receivers (potential eavesdroppers). Assuming the channel state information (CSI) of the EH receivers is not perfectly known at the transmitter, we aim to maximize the worst-case secrecy rate by jointly designing the precoding matrix, AN covariance matrix and power splsplitting ratio, under the constraints of total transmit power and harvested energyitting ratio, under the constraints of total transmit power and harvested energy at receivers. The formulated problem is non-convex and semi-infinite, which is hard to tackle. To solve it, we first deal with the non-convexity caused by CSI errors with the aid of the S-Procedure, and then employ the Taylor series approximation techniques to transfer the nonconvex problem into a convex optimization problem. Based on that, we propose an iterative algorithm with proved convergence to solve the original problem. Simulation results are finconvex optimization problem. Based on that, we propose an iterative algorithmally provided to show the effectiveness of our proposed robust transmit design.
Simultaneous wireless information and power transfer (SWIPT) is able to prolong the lifetime of energy-constrained wireless networks. In this paper, we study the security issue of a nonregenerative multiple-input multiple-out (MIMO) relay system with SWIPT. When the full channel state information (CSI) of the eavesdropper is available, we aim to maximize the secrecy rate under the source and relay transmit power constraints and energy-harvesting (EH) constraints at the multiple EH receivers by jointly designing the source and relay beamforming matrices, which is a nonconvex optimization and is still an open problem. In order to enhance the secrecy rate effectively, we first transform the optimization into a difference of convex programming and propose a sequential parametric convex approximation-based iterative algorithm which is able to achieve a local optimum. To reduce the complexity, we also propose a singular value decomposition (SVD)-generalized SVD-based method to simplify the optimization into a joint source and relay power allocation problem. The alternating optimization is employed to find a suboptimal solution of the joint power allocation problem. When the CSI of the eavesdropper is unknown, we propose an artificial-noise (AN) aided joint source and relay beamforming scheme, which can maximize the AN power to jam the eavesdropper under the limited source and relay transmit power and satisfy the quality of service of the receiver. Simulation results have shown the effectiveness of our proposed schemes.