The network security is becoming more and more important in the fifth-generation (5G) networks. Therefore, the physical layer security with power transfer in heterogeneous network is investigated in this paper. The co-channel interference in the system is exploited for both secure transmission and energy harvesting in two types of eavesdropping, i.e., non-colluding and colluding eavesdropping. As such, we propose a secure transmission scheme, which obtains the maximum secrecy rate, and at the same time satisfy the outage constraints of the users' QoS and the energy harvesting requirements. Assuming that the imperfect channel state information (CSI) follows Truncated Gauss distribution, we propose a novel method based on the expectation and variance of the CSI to transform the original complex problem into the convex optimization problem. Then the algorithms for two eavesdropping cases are provided. At last, numerical results are presented to show the robustness and effectiveness of the proposed algorithms.
The network security is becoming more and more important in the fifth-generation (5G) networks. Therefore, the physical layer security with power transfer in heterogeneous network is investigated in this paper. The co-channel interference in the system is exploited for both secure transmission and energy harvesting in two types of eavesdropping, i.e., non-colluding and colluding eavesdropping. As such, we propose a secure transmission scheme, which obtains the maximum secrecy rate, and at the same time satisfy the outage constraints of the users' QoS and the energy harvesting requirements. Assuming that the imperfect channel state information (CSI) follows Truncated Gauss distribution, we propose a novel method based on the expectation and variance of the CSI to transform the original complex problem into the convex optimization problem. Then the algorithms for two eavesdropping cases are provided. At last, numerical results are presented to show the robustness and effectiveness of the proposed algorithms.
In this paper, we investigate an artificial-noise-aided secure beamforming design for simultaneous wireless information and power transfer in a two-tier downlink heterogeneous cellular network, in which each energy receiver in a femtocell is seen as a potential eavesdropper to wiretap the confidential message intended for the information receiver. Our design objective is to maximize the secrecy rate at the information receiver, while satisfying the signal-to-interference-plus-noise ratio requirement of each macrouser and the energy harvesting and transmit power constraints. Both the scenarios of perfect and imperfect channel state information (CSI) are considered. With perfect CSI, the formulated optimization problem constitutes a difference of a convex function programming problem, which is hard to directly solve. To tackle this challenge, we transform it into a series of semidefinite programs by using successive convex approximation, and an iterative algorithm is proposed to arrive at a provably convergent solution. With imperfect CSI, we address robust secure beamforming relying on the worst-case design philosophy. To circumvent this predicament, we resort to the S-procedure to reformulate the robust quadratic matrix inequality (QMI) constraints and then obtain the linear matrix inequality representations for these QMIs. Numerical results are finally presented to demonstrate the performance of our proposed schemes in improving the secrecy rate of heterogeneous cellular networks.
In this paper, we investigate secure simultaneous wireless information and power transfer (SWIPT) in a two-tier downlink heterogeneous network (HetNet), wherein the ambient interference signals are exploited for both secure communications and wireless energy harvesting. We assume one macrocell base station (MBS) and several femtocell base stations (FBSs) simultaneously send information to their macrocell users (MUs) and femtocell users, respectively. Meanwhile, the FBSs also transfer energy to some energy receivers, who act as the potential eavesdroppers and are able to wiretap the confidential messages to one MU via the cross-tier interference links. Exploiting interference in the considered HetNet, we jointly optimize the beamforming vectors and artificial noise of the MBS and the FBSs to maximize the secrecy rate of the eavesdropped MU under the quality-of-service, energy harvesting, and transmit power constraints at relevant receivers/transmitters. In particular, we first investigate the ideal case with perfect eavesdropper's channel state information (ECSI) and the optimization problem turns out to be nonconvex. By using the tools of semidefinite relaxation (SDR) and one-dimensional line search, we successfully transfer the original problem into a more tractable two-stage problem to obtain the optimal solution. Furthermore, we extend our study to the imperfect ECSI case, where the worst-case based solution is obtained with the aid of SDR and successive convex approximation. Simulation results demonstrate the effectiveness of the proposed algorithms and also bring useful insights into the design of secure SWIPT in the presence of interference.
In this paper, we investigate secure communication with the presence of multiple eavesdroppers (Eves) in a two-tier downlink dense heterogeneous network, wherein there is a macrocell base station (MBS) and multiple femtocell base stations (FBSs).Each base station (BS) has multiple users.And Eves attempt to wiretap a macrocell user (MU).To keep Eves ignorant of the confidential message, we propose a physical-layer security scheme based on cross-layer cooperation to exploit interference in the considered network.Under the constraints on the quality of service (QoS) of other legitimate users and transmit power, the secrecy rate of system can be maximized through jointly optimizing the beamforming vectors of MBS and cooperative FBSs.We explore the problem of maximizing secrecy rate in both non-colluding and colluding Eves scenarios, respectively.Firstly, in non-colluding Eves scenario, we approximate the original non-convex problem into a few semi-definite programs (SDPs) by employing the semi-definite relaxation (SDR) technique and conservative convex approximation under perfect channel state information (CSI) case.Furthermore, we extend the frame to imperfect CSI case and use the Lagrangian dual theory to cope with uncertain constraints on CSI.Secondly, in colluding Eves scenario, we transform the original problem into a two-tier optimization problem equivalently.Among them, the outer layer problem is a single variable optimization problem and can be solved by one-dimensional linear search.While the inner-layer optimization problem is transformed into a convex SDP problem with SDR technique and Charnes-Cooper transformation.In the perfect CSI case of both non-colluding and colluding Eves scenarios, we prove that the relaxation of SDR is tight and analyze the complexity of proposed algorithms.Finally, simulation results validate the effectiveness and robustness of proposed scheme.
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.
In this paper, a robust transmission scheme for simultaneous wireless information and power transfer (SWIPT) in the presence of an eavesdropper is proposed. With imperfect channel state information (CSI) at the transmitter, the optimal transmit covariance matrix is obtained based on the maximization of the worst case harvested energy for the energy receiver (ER) while guaranteeing the achievable secrecy rate constraint for the information receiver (IR). To solve such a challenging nonconvex problem, in this paper, a two-stage optimization approach is proposed. In the first stage, the original problem is transformed into a robust design problem, which can be further converted into a convex semidefinite program (SDP) problem by using S-procedure as a tool. In the second stage, the optimal transmit covariance matrix is obtained via the aid of one-dimensional search algorithm. Finally, simulation results are provided to illustrate the robustness and effectiveness of the proposed method.
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.