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    Coverage Enhancement of Underwater Internet of Things Using Multilevel Acoustic Communication Networks

    Xu, Jiajie and Kishk, Mustafa A. and Alouini, Mohamed-Slim (2022) Coverage Enhancement of Underwater Internet of Things Using Multilevel Acoustic Communication Networks. IEEE Internet of Things Journal, 9 (24). pp. 25373-25385. ISSN 2372-2541

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    Underwater acoustic communication networks (UACNs) are considered a key enabler to the Underwater Internet of Things (UIoT). UACN is regarded as essential for various marine applications, such as monitoring, exploration, and trading. However, a large part of existing literature disregards the 3-D nature of the underwater communication system. In this article, we propose a K -tier UACN that acts as a gateway that connects the UIoT with the space–air–ground–sea integrated system (SAGSIS). The proposed network architecture consists of several tiers along the vertical direction with adjustable depths. On the horizontal dimension, the best coverage probability (CP) is computed and maximized by optimizing the densities of surface stations (SSs) in each tier. On the vertical dimension, the depth of each tier is also optimized to minimize intertier interference and maximize overall system performance. Using tools from stochastic geometry, the total CP of the proposed K -tier network is analyzed. For given spatial distribution of UIoT device’s depth, the best CP can be achieved by optimizing the depths of the transceivers connected to the SSs through a tether. We verify the accuracy of the analysis using Monte Carlo simulations. In addition, we draw multiple useful system-level insights that help optimize the design of underwater 3-D networks based on the given distribution of UIoT device’s depths.

    Item Type: Article
    Keywords: Propagation losses; Internet of Things; Stochastic processes; Interference; Underwater communication; Underwater acoustics; Coverage probability (CP); K-tier network; stochastic geometry; underwater communication; Underwater Internet of Things (UIoT);
    Academic Unit: Faculty of Science and Engineering > Electronic Engineering
    Item ID: 17562
    Identification Number:
    Depositing User: Mustafa Kishk
    Date Deposited: 18 Sep 2023 11:37
    Journal or Publication Title: IEEE Internet of Things Journal
    Publisher: Institute of Electrical and Electronics Engineers
    Refereed: Yes
    Use Licence: This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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