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Covering Underwater Shadow Zones using Acoustic Reconfigurable Intelligent Surfaces

Longfei Zhao, Jingbo Tan, Jintao Wang, Ian F. Akyildiz, Zhi Sun

TL;DR

This work tackles underwater acoustic shadow zones by introducing acoustic RIS (aRIS) to actively reflect and steer energy into shadow regions. It develops analytical shadow-zone models for deep-sea and shallow-sea SSPs, and derives optimal deployment rules—at the sound-channel axis depth $H$ in deep water and near the seabed in shallow water—supported by Bellhop simulations and pool-tested hardware. The proposed two-element 'first absorb, then radiate' aRIS demonstrates practical beamforming gains, with deep-sea deployment achieving near-100% energy coverage and shallow-sea strategies enabling extended, multi-hop coverage; the approach remains robust under dynamic marine conditions via real-time phase compensation. Collectively, these results indicate that aRIS-enabled coverage can drastically improve reliability and reach of underwater networks in realistic ocean environments.

Abstract

To better explore the oceans, seamless communication coverage of the vast 3D underwater space is desired. Unlike terrestrial networks using radio signals, underwater acoustic communications face a unique challenge: nodes in underwater shadow zones cannot connect to the network, even within the line of sight. These shadow zones can extend for tens of kilometers, causing communication nodes to disconnect. Existing efforts focus on passive avoidance of shadow zones, but this strategy cannot ensure seamless coverage in dynamic ocean environments. This paper addresses the shadow zone problem by utilizing acoustic Reconfigurable Intelligent Surfaces (RIS) to actively control the underwater channel. Shadow zones are analytically modeled, and optimal RIS deployment strategies are developed for both deep-sea and shallow-sea environments. The acoustic RIS is redesigned considering practical engineering limitations and validated through pool tests. Bellhop-based simulations show that without RIS deployment, coverage is limited to less than 20%, regardless of source strength. However, with optimal RIS deployment, energy coverage can reach almost 100%.

Covering Underwater Shadow Zones using Acoustic Reconfigurable Intelligent Surfaces

TL;DR

This work tackles underwater acoustic shadow zones by introducing acoustic RIS (aRIS) to actively reflect and steer energy into shadow regions. It develops analytical shadow-zone models for deep-sea and shallow-sea SSPs, and derives optimal deployment rules—at the sound-channel axis depth in deep water and near the seabed in shallow water—supported by Bellhop simulations and pool-tested hardware. The proposed two-element 'first absorb, then radiate' aRIS demonstrates practical beamforming gains, with deep-sea deployment achieving near-100% energy coverage and shallow-sea strategies enabling extended, multi-hop coverage; the approach remains robust under dynamic marine conditions via real-time phase compensation. Collectively, these results indicate that aRIS-enabled coverage can drastically improve reliability and reach of underwater networks in realistic ocean environments.

Abstract

To better explore the oceans, seamless communication coverage of the vast 3D underwater space is desired. Unlike terrestrial networks using radio signals, underwater acoustic communications face a unique challenge: nodes in underwater shadow zones cannot connect to the network, even within the line of sight. These shadow zones can extend for tens of kilometers, causing communication nodes to disconnect. Existing efforts focus on passive avoidance of shadow zones, but this strategy cannot ensure seamless coverage in dynamic ocean environments. This paper addresses the shadow zone problem by utilizing acoustic Reconfigurable Intelligent Surfaces (RIS) to actively control the underwater channel. Shadow zones are analytically modeled, and optimal RIS deployment strategies are developed for both deep-sea and shallow-sea environments. The acoustic RIS is redesigned considering practical engineering limitations and validated through pool tests. Bellhop-based simulations show that without RIS deployment, coverage is limited to less than 20%, regardless of source strength. However, with optimal RIS deployment, energy coverage can reach almost 100%.
Paper Structure (19 sections, 1 theorem, 29 equations, 17 figures, 1 algorithm)

This paper contains 19 sections, 1 theorem, 29 equations, 17 figures, 1 algorithm.

Table of Contents

  1. Introduction
  2. Shadow Zone Models in Deep-Sea and Shallow-Sea Environments
  3. Deep-Sea Shadow Zone Model
  4. Shallow-Sea Shadow Zone Model
  5. Improving the Current Underwater Acoustic RIS Design Considering Practical Constraints
  6. Underwater Acoustic RIS Hardware Design
  7. Hardware Prototypes and Pool Tests
  8. Optimal Deployment of Underwater Acoustic RIS for Shadow Zone Coverage
  9. Deep-Sea Acoustic RIS Array Coverage
  10. Shallow-Sea aRIS Wide-Area Coverage
  11. Validation And Evaluations
  12. Deep-Sea Coverage Enhancement with Acoustic RIS
  13. Shallow-Sea Coverage Optimization
  14. Impact Analysis of Dynamic Marine Environment and Corresponding Robust Solution
  15. Dynamic Marine Environment Impact Analysis
  16. ...and 4 more sections

Key Result

Theorem 1

For deep-sea coverage, the optimal depth $h_{\text{opt}}$ to deploy the aRIS is at the sound channel axis depth $H$. The coverage gain $\xi$ when deploying the aRIS at the sound channel axis depth $H$ compared with deploying the aRIS at arbitrary shallower depth $h$ is given by

Figures (17)

  • Figure 1: Underwater acoustic communication network coverage.
  • Figure 2: Standard ocean sound speed profile and layered structure (left); Deep-sea V-shaped coverage pattern (right). Sound rays tend to bend toward regions with lower sound speed. As a result, the sound rays above the sound channel axis bend downward, while those below the axis bend upward, forming the V-shaped propagation path shown in the figure.
  • Figure 3: Shallow-sea surface waveguide.
  • Figure 4: Illustration of the underwater acoustic RIS hardware.
  • Figure 5: Wet-end setup of the RIS experiment.
  • ...and 12 more figures

Theorems & Definitions (1)

  • Theorem 1