Dual AAV Cluster-Assisted Maritime Physical-Layer Secure Communications via Collaborative Beamforming

Autonomous aerial vehicles (AAVs) can be utilized as relay platforms to assist maritime wireless communications. However, complex channels and multipath effects at sea can adversely affect the quality of AAV transmitted signals. Collaborative beamforming (CB) can enhance the signal strength and range to assist the AAV relay for remote maritime communications. However, due to the open nature of AAV channels, security issue requires special consideration. This article proposes a dual AAV cluster-assisted system via CB to achieve physical-layer security in maritime wireless communications. Specifically, one AAV cluster forms a maritime AAV-enabled virtual antenna array (MUVAA) relay to forward data signals to the remote legitimate vessel, and the other AAV cluster forms an MUVAA jammer to send jamming signals to the remote eavesdropper. In this system, we formulate a secure and energy-efficient maritime communication multiobjective optimization problem (SEMCMOP) to maximize the signal-to-interference-plus-noise ratio (SINR) of the legitimate vessel, minimize the SINR of the eavesdropping vessel and minimize the total flight energy consumption of AAVs. Since the SEMCMOP is an NP-hard and large-scale optimization problem, we propose an improved swarm intelligence optimization algorithm with chaotic solution initialization and hybrid solution update strategies to solve the problem. Simulation results indicate that the proposed algorithm outperforms other comparison algorithms, and it can achieve more efficient signal transmission by using the CB-based method.

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Publication Details

Journal
IEEE Internet of Things Journal
Published
2024-12-23
DOI
https://doi.org/10.1109/jiot.2024.3521977
Citations
9
Primary Topic
UAV Applications and Optimization
Type
article
Field-Weighted Citation Impact
11.69

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article

Dual AAV Cluster-Assisted Maritime Physical-Layer Secure Communications via Collaborative Beamforming

Jiawei Huang, Hongyang Du, Geng Sun, Dusit Niyato et al.
9 citations
IEEE Internet of Things Journal
UAV Applications and Optimization
11.69
article

Dual AAV Cluster-Assisted Maritime Physical-Layer Secure Communications via Collaborative Beamforming

Jiawei Huang, Hongyang Du, Geng Sun, Dusit Niyato, Jiahui Li, Jiacheng Wang, Aimin Wang
article en
9 citations

Abstract

Autonomous aerial vehicles (AAVs) can be utilized as relay platforms to assist maritime wireless communications. However, complex channels and multipath effects at sea can adversely affect the quality of AAV transmitted signals. Collaborative beamforming (CB) can enhance the signal strength and range to assist the AAV relay for remote maritime communications. However, due to the open nature of AAV channels, security issue requires special consideration. This article proposes a dual AAV cluster-assisted system via CB to achieve physical-layer security in maritime wireless communications. Specifically, one AAV cluster forms a maritime AAV-enabled virtual antenna array (MUVAA) relay to forward data signals to the remote legitimate vessel, and the other AAV cluster forms an MUVAA jammer to send jamming signals to the remote eavesdropper. In this system, we formulate a secure and energy-efficient maritime communication multiobjective optimization problem (SEMCMOP) to maximize the signal-to-interference-plus-noise ratio (SINR) of the legitimate vessel, minimize the SINR of the eavesdropping vessel and minimize the total flight energy consumption of AAVs. Since the SEMCMOP is an NP-hard and large-scale optimization problem, we propose an improved swarm intelligence optimization algorithm with chaotic solution initialization and hybrid solution update strategies to solve the problem. Simulation results indicate that the proposed algorithm outperforms other comparison algorithms, and it can achieve more efficient signal transmission by using the CB-based method.

IEEE Internet of Things JournalVol. 12(9)
Nanyang Technological University (SG), Jilin University (CN), Jilin Province Science and Technology Department (CN), University of Hong Kong (HK)
National Natural Science Foundation of China
Openalex Percentile: Top 2%
UAV Applications and Optimization
11.69
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