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In the finite blocklength scenario, which is suitable for practical applications, a method of maximizing the average effective secrecy rate (AESR) is proposed for a UAV-enabled secure communication by optimizing the UAVs trajectory and transmit power subject to the UAVs mobility constraints and transmit power constraints. To address the formulated non-convex optimization problem, it is first decomposed into two non-convex subproblems. Then the two subproblems are converted respectively into two convex subproblems via the first-order approximation. Finally, an alternating iteration algorithm is developed by solving the two subproblems iteratively using successive convex approximation (SCA) technique. Numerical results show that our proposed scheme achieves a better AESR performance than both the benchmark schemes.
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This letter studies an unmanned aerial vehicle-enabled wireless power transfer system within a radio-map-based robust positioning design.
In this paper, we investigate the design of robust and secure transmission in intelligent reflecting surface (IRS) aided wireless communication systems. In particular, a multi-antenna access point (AP) communicates with a single-antenna legitimate receiver in the presence of multiple single-antenna eavesdroppers, where the artificial noise (AN) is transmitted to enhance the security performance. Besides, we assume that the cascaded AP-IRS-user channels are imperfect due to the channel estimation error. To minimize the transmit power, the beamforming vector at the transmitter, the AN covariance matrix, and the IRS phase shifts are jointly optimized subject to the outage rate probability constraints under the statistical cascaded channel state information (CSI) error model that usually models the channel estimation error. To handle the resulting non-convex optimization problem, we first approximate the outage rate probability constraints by using the Bernstein-type inequality. Then, we develop a suboptimal algorithm based on alternating optimization, the penalty-based and semidefinite relaxation methods. Simulation results reveal that the proposed scheme significantly reduces the transmit power compared to other benchmark schemes.
The integration of unmanned aerial vehicles (UAVs) into the terrestrial cellular networks is envisioned as one key technology for next-generation wireless communications. In this work, we consider the physical layer security of the communications links in the millimeter-wave (mmWave) spectrum which are maintained by UAVs functioning as base stations (BS). In particular, we propose a new precoding strategy which incorporates the channel state information (CSI) of the eavesdropper (Eve) compromising link security. We show that our proposed precoder strategy eliminates any need for artificial noise (AN) transmission in underloaded scenarios (fewer users than number of antennas). In addition, we demonstrate that our nonlinear precoding scheme provides promising secrecy-rate performance even for overloaded scenarios at the expense of transmitting low-power AN.
An unmanned aerial vehicle (UAV)-aided secure communication system is conceived and investigated, where the UAV transmits legitimate information to a ground user in the presence of an eavesdropper (Eve). To guarantee the security, the UAV employs a power splitting approach, where its transmit power can be divided into two parts for transmitting confidential messages and artificial noise (AN), respectively. We aim to maximize the average secrecy rate by jointly optimizing the UAVs trajectory, the transmit power levels and the corresponding power splitting ratios allocated to different time slots during the whole flight time, subject to both the maximum UAV speed constraint, the total mobility energy constraint, the total transmit power constraint, and other related constraints. To efficiently tackle this non-convex optimization problem, we propose an iterative algorithm by blending the benefits of the block coordinate descent (BCD) method, the concave-convex procedure (CCCP) and the alternating direction method of multipliers (ADMM). Specially, we show that the proposed algorithm exhibits very low computational complexity and each of its updating steps can be formulated in a nearly closed form. Our simulation results validate the efficiency of the proposed algorithm.
Secrecy transmission is investigated for a cooperative jamming scheme, where a multi-antenna jam-mer generates artificial noise (AN) to confuse eavesdroppers. Two kinds of eavesdroppers are considered: passive eavesdroppers who only overhear the legitimate information, and active eavesdroppers who not only overhear the legitimate information but also jam the legitimate signal. Existing works only treat the passive and active eavesdroppers separately. Different from the existing works, we investigate the achievable secrecy rate in presence of both active and passive eavesdroppers. For the considered system model, we assume that the instantaneous channel state information (CSI) of the active eavesdroppers is available at the jammer, while only partial CSI of the passive eavesdroppers is available at the jammer. A new zero-forcing beamforming scheme is proposed in the presence of both active and passive eavesdroppers. For both the perfect and imperfect CSI cases, the total transmission power allocation between the information and AN signals is optimized to maximize the achievable secrecy rate. Numerical results show that imperfect CSI between the jammer and the legitimate receiver will do more harm to the achievable secrecy rate than imperfect CSI between the jammer and the active eavesdropper.
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