In this paper, we design joint information beam-forming and jamming beamforming to guarantee both transmit security and receive security for a full duplex base station (FD-BS). Specifically, we aim to maximize the secret transmit rate while constrain the secret receive rate to be greater than a predefined bound. We convert the original non-convex problem into a new sequence of subproblems where the semidefinite programming (SDP) relaxation can be applied to efficiently find the optimal solutions. We strictly prove that such a relaxation does not change the optimality for these subproblems. Then the global optimal solutions of the original non-convex problem can be obtained via a one-dimensional search. Simulation results are provided to verify the efficiency of the proposed algorithms.
In this paper, we design joint information beam-forming and jamming beamforming to guarantee both transmit security and receive security for a full duplex base station (FD-BS). Specifically, we aim to maximize the secret transmit rate while constrain the secret receive rate to be greater than a predefined bound. We convert the original non-convex problem into a new sequence of subproblems where the semidefinite programming (SDP) relaxation can be applied to efficiently find the optimal solutions. We strictly prove that such a relaxation does not change the optimality for these subproblems. Then the global optimal solutions of the original non-convex problem can be obtained via a one-dimensional search. Simulation results are provided to verify the efficiency of the proposed algorithms.
In this paper, we design joint information beamforming and jamming beamforming to guarantee both transmit security and receive security for a full-duplex base-station (FD-BS). Specifically, we aim to maximize the secret transmit rate while constrain the secret receive rate to be greater than a predefined bound. When FD-BS is equipped with a single transmit antenna, we derive the optimal solutions in closed-form, and interestingly, the results say that simultaneous information and jamming transmission cannot be optimal. When FD-BS is equipped with multiple transmit antennas, we convert the original nonconvex problem into a sequence of subproblems where the semidefinite programming (SDP) relaxation can be applied to efficiently find the optimal solutions. We strictly prove that such a relaxation does not change the optimality for these subproblems. Then the global optimal solutions of the original nonconvex problem can be obtained via a one-dimensional search. Simulation results are provided to verify the efficiency of the proposed algorithms.
In this paper, we investigate the physical layer security of a full-duplex base station (BS)-aided system in the worst case, where an uplink transmitter (UT) and a downlink receiver (DR) are equipped with a single antenna, while a powerful eavesdropper is equipped with multiple antennas. For securing the confidentiality of signals transmitted from the BS and UT, an artificial noise (AN)-aided secrecy beamforming scheme is proposed, which is robust to the realistic imperfect state information of both the eavesdropping channel and the residual self-interference channel. Our objective function is that of maximizing the worst-case sum secrecy rate achieved by the BS and UT, through jointly optimizing the beamforming vector of the confidential signals and the transmit covariance matrix of the AN. However, the resulting optimization problem is non-convex and non-linear. In order to efficiently obtain the solution, we transform the non-convex problem into a sequence of convex problems by adopting the block coordinate descent algorithm. We invoke a linear matrix inequality for finding its Karush-Kuhn-Tucker (KKT) solution. In order to evaluate the achievable performance, the worst-case secrecy rate is analytically derived. Furthermore, we construct another secrecy transmission scheme using the projection matrix theory for performance comparison. Our simulation results show that the proposed robust secrecy transmission scheme achieves substantial secrecy performance gains, which verifies the efficiency of the proposed method.
This paper proposes optimum beamforming for a system consisting of a source, a full-duplex (FD) relay, an intended destination, and an eavesdropper. The source and destination are single-antenna nodes, whereas the FD relay is a multi-antenna node. Our objective is to find the optimum receive and transmit beamformers at the relay so that the secrecy rate is maximized. The joint optimization problem is equivalently expressed in terms of the transmit beamformer. The resulting optimization is non-convex. However, we equivalently reformulate it to a suitable form so that the optimum solution is obtained by solving semi-definite relaxation problem, in conjunction with a line search confined to a specific region. Computer simulations demonstrate significant increase in secrecy rate compared to the conventional secure half-duplex relay communications.
In this paper, the physical-layer security of a cooperative wireless system with multi-antenna full-duplex (FD) destination is examined. More specifically, we consider a cooperative transmission scenario in which a source communicates with a destination through a relay in the presence of an eavesdropper. In order to degrade the wiretap channel, the FD destination simultaneously transmits an interference signal towards the eavesdropper, while receiving information from the relay. A joint transmit and receive beamformer design is proposed to maximize the signal-to-interference-plus-noise ratio (SINR) at the destination, while guaranteeing that the SINR at the eavesdropper is below a certain threshold. We reformulate the optimization problem as a semidefinite relaxation problem in terms of a transmit beamforming matrix. To balance the performance and system complexity, we investigate suboptimum beamforming designs based on zero-forcing criterion. We derive exact closed-form expressions for the average secrecy rates of the proposed suboptimum designs. Our results reveal that optimum and suboptimum beamforming schemes along with friendly jamming significantly improve the secrecy performance. Moreover, simulation results demonstrate that the optimum scheme outperforms suboptimum schemes, especially in high transmit power regimes.
Multibeam satellite communication plays an important role in future integrated satellite-terrestrial communication systems. However, the large area covered by the satellite beams makes itself vulnerable to be wiretapped, especially for the cases that eavesdroppers are located near the legitimate receivers. In this paper, cooperative jamming from both satellite and full-duplex receivers are investigated where we aim to minimize the power consumed by a multibeam satellite system with secrecy outage probability constraints. To tackle this problem, an algorithm of joint beamforming and power allocation via alternating optimization (JBFPA-AO) is proposed. Specifically, a feasible solution is first obtained by transforming the original non-convex problem into a semi-definitive programming (SDP) problem with relaxed constraints. And then, alternating optimization is adopted to find better solutions iteratively. Convergence of the proposed JBFPA-AO is proved, and simulation results show its effectiveness to reduce the power utilized by the satellite.
In this paper, we study a multiuser wireless powered communication system, where an energy-constrained full-duplex information transmitter (IT), powered by wireless energy from a dedicated energy transmitter (ET), intends to send confidential information to the information receiver (IR) in the presence of multiple idle users that could be the potential eavesdroppers. In the practical scenario of imperfect channel state information and assuming that the idle users need to harvest energy from the ET, we aim to maximize the worst-case secrecy rate at the IR by jointly optimizing the transmit covariance matrix at the ET as well as the information beamforming and artificial noise covariance at the IT, subject to their individual transmit power constraints and the minimum required power transferred to the idle users. We employ the semidefinite relaxation (SDR) and extended S-procedure approaches to transform the original nonconvex optimization problem into convex problem, which can be efficiently solved by solving a sequence of semidefinite programs. Furthermore, we show that the SDR is tight since there always exists a rank-one optimal solution. For performance comparison, two heuristic schemes for ease of implementation are also developed. Numerical results are presented to show the effectiveness of our proposed schemes.