In this paper, we study a radio frequency (RF)-powered backscatter assisted cognitive radio network (CRN), where an eavesdropper exists. This network includes a primary transmitter, a pair of secondary transmitter and receiver, a friendly jammer and an eavesdropper. We assume that the secondary transmitter works in ambient backscatter (AmBack) mode and the friendly jammer works in harvest-then-transmit (HTT) mode, where the primary transmitter serves as energy source. To enhance the physical layer security of the secondary user, the friendly jammer uses its harvested energy from the primary transmitter to transmit jamming noise to the eavesdropper. Furthermore, for maximizing the secrecy rate of secondary user, the optimal time allocation including the energy harvesting and jamming noise transmission phases is obtained. Simulation results verify the superiority of the proposed scheme.

In this letter, we investigate the secure transmission in radio frequency (RF) powered two-hop untrusted relay networks, where the source node and untrusted relay are both wireless powered by an RF power supplier. Specifically, considering the non-linear energy-harvesting (EH) model, the two-process communication protocol is proposed. The secrecy rate is maximized by jointly designing the beamforming vector at source and beamforming matrix at relay, under the constraints of transmit power at RF power supplier and destination. The secrecy rate maximization (SRM) is non-convex, hence we propose an alternative optimization (AO) based iterative algorithm. Numerical results demonstrate that the proposed scheme can significantly increase the secrecy rate compared to the baseline schemes.

In this letter, we investigate the physical layer security in multi-user multi-relay networks, where each relay is not merely a traditional helper, but at the same time, can become a potential eavesdropper. We first propose an efficient low-complexity user and relay selection scheme to significantly reduce the amount of channel estimation as well as the amount of potential links for comparison. For the proposed scheme, we derive the closed-form expression for the lower bound of ergodic secrecy rate (ESR) to evaluate the system secrecy performance. Simulation results are provided to verify the validity of our expressions and demonstrate how the ESR scales with the number of users and relays.

This letter studies secure communication in a wireless powered communication network with a full-duplex destination node, who applies either power splitting (PS) or time switching (TS) to coordinate energy harvesting and information decoding of received signals and transmits jamming signals to the eavesdropper using the harvested energy. The secrecy rate is maximized by optimizing PS or TS ratio and power allocation. We propose iterative algorithms with power allocation optimized by the successive convex approximation method. Simulation results demonstrate that the proposed algorithms are superior to other benchmark algorithms.

In this letter, we consider a multiple-input multiple-output (MIMO) simultaneous wireless information and power transfer (SWIPT) system, in which the confidential message intended for the information receiver (IR) should be kept secret from the energy receiver (ER). Our goal is to design the optimal transmit covariance matrix so as to maximize the secrecy energy efficiency (SEE) of the system while guaranteeing the secrecy rate, energy harvesting and transmit power constraints. To deal with the original non-convex optimization problem, we propose an alternating optimization (AO)- based algorithm and also prove its convergence. Simulation results show that the proposed algorithm outperforms conventional design methods in terms of SEE.

This paper studies the design of cooperative beamforming (CB) and cooperative jamming (CJ) for the physical layer security of an amplify-and-forward (AF) relay network in the presence of multiple multi-antenna eavesdroppers. The secrecy rate maximization (SRM) problem of such a network is to maximize the difference of two concave functions, a problem which is non-convex and has no efficient solution. Based on the inner convex approximation (ICA) and semidefinite relaxation (SDR) techniques, we propose two novel low-complexity schemes to design CB and CJ for SRM in the AF network. In the first strategy, relay nodes adopt the CB only to secure transmission. Based on ICA, this design guarantees convergence to a Karush-Kuhn-Tucker (KKT) solution of the SDR of the original problem. In the second strategy, the optimal joint CB and CJ design is studied and the proposed joint design can guarantee convergence to a KKT solution of the original problem. Moreover, in the second strategy, we prove that SDR always has a rank-1 solution for the SRM problem. Simulation results show the superiority of the proposed schemes.

In this paper we establish a secure communication model where eavesdropper and intended receiver have multiple antennas. We use cooperation and jamming to achieve physical layer security. First, we study how to allocate power between the information bearing signal and the jamming signal. Second, based on this model, we also jointly optimize both the information bearing signal weights and the jamming signal weights to improve physical layer security. The optimal power allocation and the weights are obtained via an iteration algorithm to maximize the secrecy rate. Comparing with equal power allocation and some other different methods, it shows that using cooperative relaying and jamming can significantly improve the physical layer security from the simulation results.

In this letter, we propose a power allocation scheme to optimize the ergodic secrecy rate of multiple-input single-output (MISO) fading wiretap channels with a probabilistic constraint, using the statistical channel state information (CSI) of the eavesdropper (CSI-E). The analytical expressions of the false secrecy probability are derived and used as constraints in the rate maximization problem. Moreover, we obtain a suboptimal solution by formulating the power allocation problem as a Rayleigh quotient problem.