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Reflections over the Sea: Reconfigurable Intelligent Surface for Maritime Self-Powered Communications

Qianqian Zhang, Long Wang, Ben Wu, Jia Mi

TL;DR

The paper tackles reliability and coverage challenges in maritime IoT for 6G by deploying a reconfigurable intelligent surface (RIS) on offshore infrastructure to create favorable line-of-sight paths. It introduces a wave-aware near-ocean channel model and a wave-energy harvesting (WEC) system to power IoT sensors, enabling self-powered operation. Real-time CSI-based RIS optimization for MU-MIMO uplinks is developed, supported by a two-stage channel estimation scheme and an SDP-based RIS design that yields practical, near-optimal reflection coefficients. Simulations show that the RIS-assisted framework can significantly boost IoT data rates under harsh sea conditions (e.g., >20% improvement), highlighting the approach's potential for robust, scalable maritime NTNs. The work also integrates mechanical design considerations with communication theory, paving the way for resilient, self-sustaining maritime networks in 6G and beyond.

Abstract

Maritime communication is becoming a vital component of 6G networks, driven by the rapid expansion of the maritime economy. However, existing technologies face critical challenges in signal coverage, availability, and robustness, especially under harsh sea conditions. This paper proposes a novel framework for the maritime Internet-of-Things (IoT) communications that leverages the reconfigurable intelligent surface (RIS) mounted on offshore infrastructures, such as wind turbines, to enhance coverage and reliability. To capture dynamic maritime environment, a near-ocean-surface channel model is developed considering the impact of sea waves. In addition, a wave energy harvesting (EH) system is designed to self-power IoT sensors for data acquisition, processing, and transmission. To support real-time adaptation, channel state information is continuously measured to optimize RIS reflection parameters and maximize multi-user communication rates. Simulation results show that the proposed system significantly improves IoT communication performance by over 20%, under harsh sea conditions.

Reflections over the Sea: Reconfigurable Intelligent Surface for Maritime Self-Powered Communications

TL;DR

The paper tackles reliability and coverage challenges in maritime IoT for 6G by deploying a reconfigurable intelligent surface (RIS) on offshore infrastructure to create favorable line-of-sight paths. It introduces a wave-aware near-ocean channel model and a wave-energy harvesting (WEC) system to power IoT sensors, enabling self-powered operation. Real-time CSI-based RIS optimization for MU-MIMO uplinks is developed, supported by a two-stage channel estimation scheme and an SDP-based RIS design that yields practical, near-optimal reflection coefficients. Simulations show that the RIS-assisted framework can significantly boost IoT data rates under harsh sea conditions (e.g., >20% improvement), highlighting the approach's potential for robust, scalable maritime NTNs. The work also integrates mechanical design considerations with communication theory, paving the way for resilient, self-sustaining maritime networks in 6G and beyond.

Abstract

Maritime communication is becoming a vital component of 6G networks, driven by the rapid expansion of the maritime economy. However, existing technologies face critical challenges in signal coverage, availability, and robustness, especially under harsh sea conditions. This paper proposes a novel framework for the maritime Internet-of-Things (IoT) communications that leverages the reconfigurable intelligent surface (RIS) mounted on offshore infrastructures, such as wind turbines, to enhance coverage and reliability. To capture dynamic maritime environment, a near-ocean-surface channel model is developed considering the impact of sea waves. In addition, a wave energy harvesting (EH) system is designed to self-power IoT sensors for data acquisition, processing, and transmission. To support real-time adaptation, channel state information is continuously measured to optimize RIS reflection parameters and maximize multi-user communication rates. Simulation results show that the proposed system significantly improves IoT communication performance by over 20%, under harsh sea conditions.
Paper Structure (14 sections, 25 equations, 4 figures, 1 algorithm)

This paper contains 14 sections, 25 equations, 4 figures, 1 algorithm.

Table of Contents

  1. Introduction
  2. System Model
  3. Maritime Channel Model
  4. Impact of Sea Wave
  5. Energy Harvesting at Buoy
  6. RIS-aided Communication System
  7. Problem Formulation
  8. Solution
  9. Channel Estimation
  10. Direct Channel Estimation
  11. Cascade Channel Estimation
  12. RIS Optimization
  13. Simulation Results and Analysis
  14. Conclusion

Figures (4)

  • Figure 1: (a) RIS-aided maritime IoT communication system. (b) Path loss and small-scale fading for free space, LoS, and NLoS links, given $f_c=5.8$ GHz, $h_t=2$ meters, $h_r=5$ meters, and $h_e=50$ meters. (c) Two-ray and three-ray LoS channel models.
  • Figure 2: (a) Impact of wave to Tx-Rx LoS link. (b) LoS probability for the Tx-Rx direct link, under different sea states, given various height of the Rx antenna. (c) Wave height and period under different sea states of open ocean in North Atlantic.
  • Figure 3: EH design with a wave energy converter.
  • Figure 4: Sum of IoT transmission rates with and without the RIS, under different sea states, given an increasing (a) antenna height $h_r^0$ of the center buoy (Rx), (b) number of RIS elements $N$, and (c) maximum transmit powers $P_{\text{max}}$.