In this study, the authors study simultaneous wireless information and power transfer for multiuser multiple‐input–single‐output secure multicasting channels with imperfect channel state information. First, a robust secure beamforming design is considered, where the transmit power is minimised subject to the secrecy rate outage probability constraint for legitimate users and the harvested energy outage probability constraint for energy harvesting receivers. The original problem is non‐convex due to the presence of the probabilistic constraints. By utilising Bernstein‐type inequalities, the authors transform the outage constraints into the deterministic forms. In order to identify a local optimal rank‐one solution, the authors propose an efficient approach based on a constrained concave convex procedure method to convert the original problem into a sequence of convex programming problems. Finally, simulation results are provided to validate the performance of the proposed design methods.
In this study, the authors study simultaneous wireless information and power transfer for multiuser multiple‐input–single‐output secure multicasting channels with imperfect channel state information. First, a robust secure beamforming design is considered, where the transmit power is minimised subject to the secrecy rate outage probability constraint for legitimate users and the harvested energy outage probability constraint for energy harvesting receivers. The original problem is non‐convex due to the presence of the probabilistic constraints. By utilising Bernstein‐type inequalities, the authors transform the outage constraints into the deterministic forms. In order to identify a local optimal rank‐one solution, the authors propose an efficient approach based on a constrained concave convex procedure method to convert the original problem into a sequence of convex programming problems. Finally, simulation results are provided to validate the performance of the proposed design methods.
Here, the authors investigate robust secure transmission for wireless information and power transfer in heterogeneous networks (HeNets) under the deterministic and stochastic CSI errors, respectively, where one macrocell base station (MBS) and one femtocell base station (FBS) respectively serve to macrocell users (MUs) and femtocell users (FUs). Meanwhile, FUs acquire energy from the FBS and multiple eavesdroppers attempt to wiretap its downlink information. To secure the wireless information and power transfer, the authors propose an artificial noise (AN)‐aided transmission design. Under the deterministic CSI error, the authors jointly design the beamforming and AN vectors of the MBS and FBS to minimise the total transmit power, while satisfying the constraints on the signal‐to‐interference plus noise (SINR) requirement at each MU, energy harvesting (EH) and secrecy outage probability requirement at each FU. This formulated problem is non‐convex. Utilising S‐procedure and successive convex approximation technique, the authors successfully transfer it into a series of convex problems. Under the stochastic CSI error, the joint design problem is formulated with a range of outage probabilistic constraints. Further, the authors, respectively, resort to large deviation and Bernstein‐type inequalities, S‐procedure to convert it into solvable forms. Simulation results demonstrate the effectiveness of the authors’ proposed design.
This paper studies the secure transmission issue for simultaneous wireless information and power transfer in a multiuser multiple-input-multiple-output system with multiple external eavesdroppers, where the transmitter broadcasts independent confidential messages to different legitimate receivers. Each receiver can be seen as an internal eavesdropper intended by other receivers. Our objective is to achieve the robust beamforming design under imperfect channel state information, in which the total transmission power is minimized with constraints on the achievable secrecy rate and the energy harvesting. Since the problem is nonconvex, we propose a two-level optimization scheme. For the inner problem, we investigate two conservative relaxation approaches, large-deviation inequality and Bernstein-type inequality (BTI), to reformulate the outage secrecy rate constraints into some convex ones, yielding a convex optimization by semidefinite programming (SDP) relaxation. For the outer problem, it is a K-variable optimization problem, which can be solved via the novel line-dimensional-like search method. Moreover, we characterize the rank profile of SDP relaxed solution for these two approaches. Specifically, the optimal solution is proved to be rank-one. Numerical results are provided to verify the performance of the proposed algorithms, where the LDI-based scheme outperforms the BTI-based scheme in terms of energy efficiency.
This paper addresses robust designs of secure simultaneous wireless information and power transfer for multiple-input single-output (MISO) multiuser systems. By using a bounded uncertainty model for the channel state information (CSI) from transmitters to legitimate receivers and under the assumption of only available statistic knowledge of the CSI to eavesdroppers, we consider the robust designs with both worst-case and chance-constrained optimizations. To jointly optimize transmit beamforming vectors and power splitting factors, we formulate three problems aiming at minimizing the system power, maximizing the sum secrecy rate, and maximizing the minimal secrecy rate, respectively, subject to both energy harvesting and secrecy outage constraints. These problems are intractable in their original forms due to the CSI models and their non-convexity. To reach computationally efficient solutions, we first rewrite the original problems by semi-definite relaxation, then transform the CSI uncertainty related constraints by S-procedure, and finally approximate the non-convex constraints by the first-order Taylor expansion. By the reformulations, we present iterative successive convex approximation algorithm for approaching the optimized solutions. Simulation results under various setups of system parameters are provided to examine the system performance and validate the effectiveness of the proposed schemes.
Summary This paper considers a multiuser multiple‐input single‐output (MISO) broadcasting system with simultaneous wireless information and power transfer (SWIPT), which consists of one information receiver (IR) and several energy harvesting receivers (ERs) which are capable of eavesdropping the legitimate signals. For reducing cost and hardware complexity, transmit antenna selection (TAS) is applied in the transmitter. We aim to maximize the achievable secrecy rate under the individual energy harvesting constraint at the ERs and the transmit power constraint at the transmitter by jointly optimizing TAS, transmit beamforming, and artificial noise (AN). The joint optimization problem is a non‐convex mixed integer programming problem. We apply variable replacements to decouple the variable couplings and relax and approach the binary constraint by the difference of two convex constraints. Afterwards, penalty method and constrained concave convex procedure (CCCP) are applied to transform the relaxed problem into a sequence of semi‐definiteness programming (SDP) problems. Simulation results shows that our proposed joint optimization scheme is superior over existing non‐joint optimization schemes. This paper studies the joint transmit antenna selection (TAS), transmit beamforming, and artificial noise (AN) optimization in a multiple‐input multiple‐output (MISO) wiretap system with simultaneous wireless information and power transfer (SWIPT). The joint optimization problem is nonconvex and we propose a penalty method based scheme to solve it. The simulation results show that our joint optimization scheme is superior to other non‐joint optimization schemes.
In this letter, we investigate the simultaneous wireless information and power transfer in a multiple-input-single-output downlink system which consists of one multi-antenna transmitter, one single-antenna desired receiver, and multiple single-antenna eavesdroppers. Specifically, we investigate the outage-constrained secrecy rate maximization by jointly designing the transmit beamforming vector and the power splitting ratio with statistical channel uncertainties. To handle the formulated non-convex problem, we resort to semi-definite relaxation (SDR) and the Bernstein-type inequality to transform the outage constraints into a deterministic form. Then, the original problem can be efficiently solved by alternately optimizing two convex subproblems. In addition, we testify that the SDR can obtain the rank-one optimal solution. Finally, our proposed algorithm is validated by some representative numerical results.
In this paper, we investigate multiple-input single-output (MISO) simultaneous wireless information and power transfer (SWIPT) broadcast channels with confidential messages (BCC) scenario, in which a multiple-antenna transmitter simultaneously transmits confidential messages and power to multiple single-antenna receivers. Considering the imperfect channel state information (CSI), we study the joint optimization of transmit beamforming vectors, covariance of artificial noise, and power splitting ratios so as to minimize the total transmit power while satisfying the worst-case conservative secrecy rate and energy harvesting constraints. The original optimization is non-convex and intractable in general. To handle this challenge, in this paper, we first derive the exact upper or lower bounds of the constraints in original optimization problem by using the Lagrangian approach, and then convert the corresponding non-convex problem into a convex one with the aid of the rank relaxation technique. Finally, we provide simulation results to illustrate the robustness of the proposed design.