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arXiv:2101.07502

UAV-Enabled Cooperative Jamming for Covert Communications

Hangmei Rao, Sa Xiao, Yan, Shihao, Jianquan Wang, Wanbin Tang

Published Jan 19, 2021• 1 citation
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Abstract

This work employs an unmanned aerial vehicle (UAV) as a jammer to aid a covert communication from a transmitter Alice to a receiver Bob, where the UAV transmits artificial noise (AN) with random power to deliberately create interference to a warden Willie. In the considered system, the UAV's trajectory is critical to the covert communication performance, since the AN transmitted by the UAV also generates interference to Bob. To maximize the system performance, we formulate an optimization problem to jointly design the UAV's trajectory and Alice's transmit power. The formulated optimization problem is non-convex and is normally solved by a conventional iterative (CI) method, which requires multiple approximations based on Taylor expansions and an initialization on the UAV's trajectory. In order to eliminate these requirements, this work, for the first time, develops a geometric (GM) method to solve the optimization problem. By analyzing the covertness constraint, the GM method decouples the joint optimization into optimizing the UAV's trajectory and Alice's transmit power separately. Our examination shows that the GM method can significantly outperform the CI method in terms of achieving a higher average covert rate and the complexity of the GM method is lower than that of the CI method.

DOI
10.48550/arxiv.2101.07502

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This work employs an unmanned aerial vehicle (UAV) as a jammer to aid a covert communication from a transmitter Alice to a receiver Bob, where the UAV transmits artificial noise (AN) with random power to deliberately create interference to a warden Willie. In the considered system, the UAV's trajectory is critical to the covert communication performance, since the AN transmitted by the UAV also generates interference to Bob. To maximize the system performance, we formulate an optimization problem to jointly design the UAV's trajectory and Alice's transmit power. The formulated optimization problem is non-convex and is normally solved by a conventional iterative (CI) method, which requires multiple approximations based on Taylor expansions and an initialization on the UAV's trajectory. In order to eliminate these requirements, this work, for the first time, develops a geometric (GM) method to solve the optimization problem. By analyzing the covertness constraint, the GM method decouples the joint optimization into optimizing the UAV's trajectory and Alice's transmit power separately. Our examination shows that the GM method can significantly outperform the CI method in terms of achieving a higher average covert rate and the complexity of the GM method is lower than that of the CI method.
This work employs an unmanned aerial vehicle (UAV) as a jammer to aid a covert communication from a transmitter Alice to a receiver Bob, where the UAV transmits artificial noise (AN) with random power to deliberately create interference to a warden Willie. In the considered system, the UAV’s trajectory is critical to the covert communication performance, since the AN transmitted by the UAV also generates interference to Bob. To maximize the system performance, we formulate an optimization problem to jointly design the UAV’s trajectory and Alice’s transmit power. The formulated optimization problem is non-convex and is normally solved by a conventional iterative (CI) method, which requires multiple approximations based on Taylor expansions and an initialization on the UAV’s trajectory. In order to eliminate these requirements, this work, for the first time, develops a geometric (GM) method to solve the optimization problem. By analyzing the covertness constraint, the GM method decouples the joint optimization into optimizing the UAV’s trajectory and Alice’s transmit power separately. Our examination shows that the GM method can significantly outperform the CI method in terms of achieving a higher average covert rate and the complexity of the GM method is lower than that of the CI method.
This work employs an unmanned aerial vehicle (UAV) as a jammer to aid a covert communication from a transmitter Alice to a receiver Bob, where the LAV transmits artificial noise (AN) with random power to deliberately create interference to a warden Willie. To maximize the system performance, we formulate an optimization problem to jointly design the UAV’s trajectory and Alice’s transmit power. The formulated optimization problem is non-convex that is difficult to tackle directly. To this end, this work, for the first time, develops a geometric (GM) method to solve the optimization problem. Our examination shows that the GM method can significantly outperforms a benchmark method in terms of achieving a higher average covert rate and the complexity of the GM method is lower than that of the benchmark method.
This letter presents a new cooperative jamming approach to secure the unmanned aerial vehicle (UAV) communication by leveraging jamming from other nearby UAVs to defend against the eavesdropping. In particular, we consider a two-UAV scenario when one UAV transmitter delivers the confidential information to a ground node (GN), and the other UAV jammer cooperatively sends the artificial noise to confuse the ground eavesdropper for protecting the confidentiality of the data transmission. By exploiting the fully controllable mobility, the two UAVs can adaptively adjust their locations over time (a.k.a. trajectories) to facilitate the secure communication and cooperative jamming. We assume that the two UAVs perfectly know the GN's location and partially know the eavesdropper's location a priori. Under this setup, we maximize the average secrecy rate from the UAV transmitter to the GN over one particular time period, by optimizing the UAVs' trajectories, jointly with their communicating/jamming power allocations. Although the formulated problem is non-convex, we propose an efficient solution by applying the techniques of alternating optimization and successive convex approximation.
Cognitive unmanned aerial vehicle (UAV) communication systems combine benefits of both the cognitive radio and UAV, which improves the spectral efficiency and communication coverage area. However, high-quality air-ground channel links maybe more vulnerable to potential eavesdropping or jamming attacks. Thus, this paper proposes a secure transmission approach assisted by deploying a cooperative UAV to transmit artificial noise to jam an active eavesdropper, in order to maximize the system secrecy rate under the quality of service (QoS) requirement of a primary device. Specifically, we jointly optimize the flight trajectory and transmission power of the cooperative jammer to maximize the system's secrecy rate under strict constraints. To achieve this, we convert the non-convex problem into an approximately convex problem using the block coordinate descent algorithm and successive convex approximation method. Simulation results show that compared to existing algorithms, the proposed algorithm in this study can significantly improve the system's secrecy rate.
Unmanned aerial vehicle (UAV) aided augmented reality (AR) has developed rapidly in recent years and has become a promising technology in disaster rescue, transportation, agriculture, and environmental monitoring. However, the information leakage is challenging the usage of UAV-aided AR systems with wireless communications. In this article, a dual UAVs assisted covert communication system (CCS) is proposed, where one UAV transmits the covert message to ground receivers and a cooperative UAV performs as a jammer to interfere with the malicious eavesdropper. However, flying UAVs result in fast channel fading between the UAVs and ground nodes, which reduces the covert rate of the CCSs. To maximize the average covert rate, we formulated a non-convex optimization problem under the constraint that the detection error probability (DEP) of the monitor is minimum. Furthermore, the problem is decomposed into three subproblems and transformed into convex, and these subproblems are solved alternately by designing an iterative algorithm. Simulation results reveal that the average covert rate performance of the proposed optimization algorithm can respectively achieve 16% and 40% gains than those without covert constraint and without the cooperative UAV used as a jammer.
The broadcast nature of air-to-ground line-of-sight (LoS) wireless channel imposes a great challenge in secure unmanned aerial vehicle (UAV) communications. To address this issue, this paper investigates UAV-ground communications from the physical-layer security perspective. Specifically, the investigated scenario includes a UAV serving as the base station (BS) that transmits confidential signals to a legitimate ground user, and there are multiple eavesdroppers on the ground with unknown position information. To further enhance the secrecy performance of the UAV-ground communications, an idle UAV can be employed to serve as a friendly jammer, which can transmit jamming signals to confuse the eavesdroppers. In our proposed strategy, the flying trajectory and the transmit power for both the UAVs are jointly optimized by maximizing the worst-case secrecy rate (WCSR) of the system. Considering the intractability of the formulated non-convex problem, we further provide a block coordinate descent-based iterative optimization method. Simulations verify that our proposed algorithm can significantly improve the average WCSR in comparison with the existing works.