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International Conference on Wireless Communications and Signal Processing (WCSP)

Anti-Eavesdropping in UAV Secure Communications: Joint Trajectory and Power Allocation Optimization with Two-Way Training

Gengyan Li, Xiaohan Qi, Zhihua Yang

Published Nov 2, 2023• 0 citations
Publisher

Abstract

This paper investigates an unmanned ariel vehicle (UAV)-enabled secure communication system, where an UAV sends confidential information to legitimate ground users (LGUs) in the presence of a ground eavesdropper (Eve). In order to improve the comprehensive security performance of UAV network communication, a two-way training-based discriminatory channel estimation (DCE) scheme focusing on physical layer security (PLS) is proposed. We derive the closed-form expression of the average secrecy rate (ASR) and the minimum normalized mean square error (NMSE). On the premise of ensuring the effectiveness of channel estimation errors, we aim to maximize the ASR of the system, by jointly optimizing the UAV’s flight trajectory and power allocation. Due to the intractability of the formulated problem, block coordinate descent (BCD) and successive convex approximation (SCA) techniques are applied to solve the problem. Numerical results show that the proposed scheme can enhance the security of the UAV communication. Moreover, the relationship between system ASR and UAV power allocation is revealed.

DOI
10.1109/wcsp58612.2023.10404081

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This paper investigates an unmanned ariel vehicle (UAV)-enabled secure communication system, where an UAV sends confidential information to legitimate ground users (LGUs) in the presence of a ground eavesdropper (Eve). In order to improve the comprehensive security performance of UAV network communication, a two-way training-based discriminatory channel estimation (DCE) scheme focusing on physical layer security (PLS) is proposed. We derive the closed-form expression of the average secrecy rate (ASR) and the minimum normalized mean square error (NMSE). On the premise of ensuring the effectiveness of channel estimation errors, we aim to maximize the ASR of the system, by jointly optimizing the UAV’s flight trajectory and power allocation. Due to the intractability of the formulated problem, block coordinate descent (BCD) and successive convex approximation (SCA) techniques are applied to solve the problem. Numerical results show that the proposed scheme can enhance the security of the UAV communication. Moreover, the relationship between system ASR and UAV power allocation is revealed.
This paper investigates an average secrecy rate (ASR) maximization problem for an unmanned aerial vehicle (UAV) enabled wireless communication system, wherein a UAV is employed to deliver confidential information to a ground destination in the presence of a terrestrial passive eavesdropper. By employing an artificial noise (AN) injection based secure two-phase transmission protocol, we aim at jointly optimizing the UAV’s trajectory, network transmission power, and AN power allocation over a given time horizon to enhance the ASR performance. Specifically, we divide the original non-convex problem into four subproblems, and propose a successive convex approximation based efficient iterative algorithm to solve it suboptimally with guaranteed convergence. Simulation results demonstrate significant security advantages of our designed scheme over other known benchmarks, particularly for stringent flight durations.
This paper investigates an average secrecy rate (ASR) maximization problem for an unmanned aerial vehicle (UAV) enabled wireless communication system, wherein a UAV is employed to deliver confidential information to a ground destination in the presence of a terrestrial passive eavesdropper. By employing an artificial noise (AN) injection based secure two-phase transmission protocol, we aim at jointly optimizing the UAV’s trajectory, network transmission power, and AN power allocation over a given time horizon to enhance the ASR performance. Specifically, we divide the original non-convex problem into four subproblems, and propose a successive convex approximation based efficient iterative algorithm to solve it suboptimally with guaranteed convergence. Simulation results demonstrate significant security advantages of our designed scheme over other known benchmarks, particularly for stringent flight durations.
This paper investigates an average secrecy rate (ASR) maximization problem for an unmanned aerial vehicle (UAV) enabled wireless communication system, wherein a UAV is employed to deliver confidential information to a ground destination in the presence of a terrestrial passive eavesdropper. By employing an artificial noise (AN) injection based secure two-phase transmission protocol, we aim at jointly optimizing the UAV’s trajectory, network transmission power, and AN power allocation over a given time horizon to enhance the ASR performance. Specifically, we divide the original non-convex problem into four subproblems, and propose a successive convex approximation based efficient iterative algorithm to solve it suboptimally with guaranteed convergence. Simulation results demonstrate significant security advantages of our designed scheme over other known benchmarks, particularly for stringent flight durations.
This paper exploits the mobility of an unmanned aerial vehicle (UAV) to improve the physical layer (PLS) security against potential eavesdropping scenarios, where the sensitive data transmitted from a ground base station (GBS) to multiple information receivers (IRs) is easily eavesdropped by multiple non-colluding eavesdroppers (Eves). Specifically, the UAV is employed as a friendly jammer to transmit artificial noise to degrade the wiretap channels. By leveraging the UAV's mobility and the possibility of establishing line-of-sight links, the UAV can move close to the Eves and opportunistically jam them. Especially, two practical factors, namely, the imperfect location information of Eves and the existence of no-fly zones are considered. Since only the partial position information of the Eves can be known, as the worst case, the minimum average secrecy rate of IRs is robustly optimized by jointly designing the trajectory and jamming power of the UAV, and the transmission power of the GBS to ensure the security of all IRs. However, the formulated problem with coupled variables is non-convex and intractable. As such, an efficient alternative iterative suboptimal algorithm is proposed to solve this problem by applying the block coordinate descent, successive convex approximation, slack variables, andS\mathcal {S}S-Procedure. Numerical results reveal that the proposed robust algorithm can substantially improve the max-min average secrecy rate, and the effectiveness of the proposed algorithm is further verified by comparing it with three benchmark schemes.
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.
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.