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Learning-Based Intelligent Reflecting Surface-Aided Secure Maritime Communications

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Reinforcement Learning for Maritime Communications

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Abstract

Physical layer security (PLS) has attracted increasing attention as an alternative to cryptography-based techniques for maritime wireless communications (Liu et al., IEEE J. Sel. Areas Commun. 39(10), 2992–3005 (2021)). For instance, secure communication services in (Liu et al., IEEE J. Sel. Areas Commun. 39(10), 2992–3005 (2021); Shi et al., China Commun. 17(3), 26–35 (2020)) exploit the wireless channel features to address eavesdropping without relying on shared secret keys. So far, a variety of approaches have been reported to improve security in wireless communication systems, which can be used in maritime wireless communications, e.g., cooperative relaying strategies (Duan et al., IEEE Trans. Green Commun. Netw. 4(1), 139–151 (2020); Yang et al., IEEE Trans. Veh. Technol. 64(9), 4215–4229 (2015)), artificial noise-assisted beamforming (Wang et al., IEEE Trans. Inf. Forensics Secur. 12(6), 1470–1482 (2017); Wang et al., IEEE Trans. Wireless Commun. 14(1), 94–106 (2015)), and cooperative jamming (Nakai and Sugiura, IEEE Trans. Inf. Forensics Secur. 14(2), 431–444 (2019); Liu et al., in Proceedings of the 13th International Conference on Wireless Communications and and Signal Processing (WCSP), Changsha, China, Dec. 2021). However, employing a large number of antennas and relays in PLS systems incurs excessive hardware costs and high system complexity. Moreover, cooperative jamming and transmitting artificial noise require extra transmit power to guarantee transmission and thus raise challenges to implement in maritime wireless communication systems.

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Xiao, L., Yang, H., Zhuang, W., Min, M. (2023). Learning-Based Intelligent Reflecting Surface-Aided Secure Maritime Communications. In: Reinforcement Learning for Maritime Communications. Wireless Networks. Springer, Cham. https://doi.org/10.1007/978-3-031-32138-2_2

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  • DOI: https://doi.org/10.1007/978-3-031-32138-2_2

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