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End-to-End Optical Propagation Modeling for Water-to-Air Channels under Sea Surface and UAV Effects

Mohamed Nennouche, Mohammad-Ali Khalighi, Alexis Alfredo Dowhuszko, Djamal Merad

Abstract

Underwater observatories have recently emerged as an efficient mean of marine biodiversity monitoring. In order to conduct data muling from the underwater sensors in an efficient and cost-effective way, we consider the use of optical wireless communications to transmit the data from the underwater sensors to an aerial node close to the water surface, such as an unmanned aerial vehicle (UAV). More specifically, we utilize a direct water-to-air (W2A) optical communication link between the sensor node equipped with an LED emitter and the UAV equipped with an ultra-sensitive receiver, i.e., a silicon photomultiplier (SiPM). To characterize this particularly complex communication channel, we introduce a ray-tracing algorithm based on the Monte Carlo method, incorporating the impact of bubbles modeled through the Mie scattering theory and a realistic sea surface representation derived from the JONSWAP spectrum. Additionally, we incorporate into this model the channel losses resulting from UAV instability under windy weather conditions. Furthermore, we conduct a comprehensive analysis of the wireless channel, examining the influence of key parameters such as wind speed, transmitter configurations, and receiver characteristics. Finally, we evaluate the end-to-end performance of the system by analyzing the average bit-error rate at varying depths and data rates, providing valuable insights into the feasibility and efficiency of the proposed approach.

End-to-End Optical Propagation Modeling for Water-to-Air Channels under Sea Surface and UAV Effects

Abstract

Underwater observatories have recently emerged as an efficient mean of marine biodiversity monitoring. In order to conduct data muling from the underwater sensors in an efficient and cost-effective way, we consider the use of optical wireless communications to transmit the data from the underwater sensors to an aerial node close to the water surface, such as an unmanned aerial vehicle (UAV). More specifically, we utilize a direct water-to-air (W2A) optical communication link between the sensor node equipped with an LED emitter and the UAV equipped with an ultra-sensitive receiver, i.e., a silicon photomultiplier (SiPM). To characterize this particularly complex communication channel, we introduce a ray-tracing algorithm based on the Monte Carlo method, incorporating the impact of bubbles modeled through the Mie scattering theory and a realistic sea surface representation derived from the JONSWAP spectrum. Additionally, we incorporate into this model the channel losses resulting from UAV instability under windy weather conditions. Furthermore, we conduct a comprehensive analysis of the wireless channel, examining the influence of key parameters such as wind speed, transmitter configurations, and receiver characteristics. Finally, we evaluate the end-to-end performance of the system by analyzing the average bit-error rate at varying depths and data rates, providing valuable insights into the feasibility and efficiency of the proposed approach.
Paper Structure (32 sections, 65 equations, 22 figures, 3 tables)

This paper contains 32 sections, 65 equations, 22 figures, 3 tables.

Table of Contents

  1. Introduction
  2. Underwater Wireless Optical Communications
  3. Communication Across the Sea Surface
  4. Use of UAVs in Open Ocean Environments
  5. Paper Contributions
  6. State-of-the-Art on W2A Optical Communications
  7. W2A Channel Modeling
  8. Modeling Optical Propagation in Water
  9. Modeling the W2A Interface
  10. Modeling the Effect of Air Bubbles
  11. Effect of Wind on UAV Orientation
  12. Statistical Modeling of UAV Instability
  13. UAV Deflection Angle Modeling
  14. Induced Channel Loss
  15. Monte-Carlo Simulations for Photon Propagation
  16. ...and 17 more sections

Figures (22)

  • Figure 1: Illustration of the considered W2A wireless optical link
  • Figure 2: Axes and rotation angles of a typical quadcopter UAV that can be used for data muling in the considered coral reef monitoring scenario.
  • Figure 3: Illustration of Snell's law at photon arrival at the water-air interface.
  • Figure 4: Flow chart of Monte Carlo photon propagation algorithm for the W2A link.
  • Figure 5: Simulation-based distribution of $\alpha_\mathrm{UAV}$ using (\ref{['eq:tan_alpha']}) and its analytical distribution using (\ref{['eq:pdf_alpha']}) for wind speeds: (a) $U_{10}=5$ m/s, and (b) $U_{10}=13$ m/s
  • ...and 17 more figures