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Underwater Acoustic Channel Estimation Based on Signal Cancellation

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Abstract

Aiming at the requirement of underwater information security transmission, the security of encryption key generation and distribution in underwater acoustic communication is concerned. Key generation technology based on underwater acoustic channel (UAC) estimation can improve the security and real-time generation of encryption keys. In this paper, the idea of estimating the multipath structure of UAC is to retrieve the arrival signal by acquiring the parameters of larger energy Eigen-ray from real arrival signal, and to eliminate the arrival signal of larger energy Eigen-ray path from the real signal through signal cancellation, so as to eliminate the influence of side lobes of larger energy signal to arrival signals of other Eigen-ray path, to improve the estimation performance of multipath structure in underwater acoustic channel. The simulation and experimental results show that the improved algorithm can estimate the multipath structure of underwater acoustic channel more accurately and provide support for the subsequent underwater information security transmission.

Author’s Brief Introduction: Liu Junkai (1990-), Baoding City, Hebei Province, Research Direction: Underwater Acoustic Communication and Network.

Project Funding: Laboratory fund of Key Laboratory of Ocean Observation Imaging Testbed of Zhejiang Province (201801); Basic Research and Frontier Technological Projects of Strong Foundation Engineering for National Defense Basic Scientific Research (19-0391).

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Correspondence to Junkai Liu .

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© 2020 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Liu, J., Dong, Y., Zhang, G., Zhang, J. (2020). Underwater Acoustic Channel Estimation Based on Signal Cancellation. In: Gao, H., Feng, Z., Yu, J., Wu, J. (eds) Communications and Networking. ChinaCom 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 312. Springer, Cham. https://doi.org/10.1007/978-3-030-41114-5_16

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  • DOI: https://doi.org/10.1007/978-3-030-41114-5_16

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-41113-8

  • Online ISBN: 978-3-030-41114-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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